Implan Pro Manual v2 3rd Edition

User Guide Analysis Guide Data Guide

IMPLAN

Pro IMPLAN Professional Version 2.0

MIG, Inc.

IMPLAN Professional Version 2.0 Social Accounting & Impact Analysis Software

2nd Edition – June, 2000 3rd Edition – February, 2004

This volume contains 3 books: User Guide Analysis Guide Data Guide

Minnesota IMPLAN Group, Inc. 1725 Tower Drive West Suite 140 Stillwater, Minnesota 55082 www.implan.com

Information in this document is subject to change without notice. No part of this document may be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without the express written consent of Minnesota IMPLAN Group, Inc.

MIG, Inc. 1725 Tower Drive West Suite 140 Stillwater, Minnesota 55082 www.implan.com  1999-2004 Minnesota IMPLAN Group, Inc. All rights reserved. MIG, Minnesota IMPLAN Group, IMPLAN, IMPLAN Pro, and IMPLAN Professional are trademarks of the Minnesota IMPLAN Group, Inc. in the USA. Windows, Windows 95, 98, 2000, NT and XP, Access, and Excel are trademarks or registered trademarks of Microsoft Corporation.

Printed in the U.S.A.

Table of Contents Introduction.........................................................................................i Manual Conventions ..........................................................................i IMPLAN Description..........................................................................i Software Features ........................................................................... iii IMPLAN Licensing Policies............................................................. v SOFTWARE LICENSE AGREEMENT ..................................................................v DATABASE LICENSE AGREEMENT..................................................................vi

Book 1: User Guide ..................................................... i INTRODUCTION ........................................................ 1 How this Guide is Organized .......................................................... 1 Getting Started................................................................................... 1 System Requirements .............................................................................................1 Installing IMPLAN Pro Software..........................................................................1 Installing IMPLAN Structural Matrices ................................................................2 Installing IMPLAN Data Files ...............................................................................2 Creating Your First Model......................................................................................2

What’s New .......................................................................................... 4 General:...................................................................................................................4 Model Construction:................................................................................................5 Data Editing:...........................................................................................................5 Reports: ...................................................................................................................5 Impact Analysis: .....................................................................................................5

Technical Support ............................................................................. 6

Model Building ........................................................... 7 Starting the Software ....................................................................... 7 The Model ............................................................................................ 8 Study Area......................................................................................... 10 Construct Model............................................................................... 13 Construct Social Accounts (Descriptive Model) .................................................... 14 Construct Multipliers (Predictive Model) ............................................................. 15

Customizing ...................................................................................... 17 Editing Region Data.............................................................................................. 19 Viewing Study Area Data ..................................................................................... 21 Modifying Deflators .............................................................................................. 22 Modifying Margins................................................................................................ 23

Modifying Production Functions........................................................................... 24 Production Function Library ................................................................................ 25 Modifying Byproducts ........................................................................................... 29 Byproducts Library ............................................................................................... 29 Modifying Trade Flows ......................................................................................... 30 Regional Purchase Coefficients Library................................................................ 32 Aggregation........................................................................................................... 32

Advanced Model Building ...................................... 37 Entering Advanced Model Construction.................................... 37 Advanced Production Function ................................................... 39 Edit Existing Model Production Functions........................................................... 39 Edit Library Production Functions....................................................................... 39 Import Production Function from Library............................................................ 39

Advanced Byproducts..................................................................... 39 Advanced Trade Flows ................................................................... 40 Supply/Demand Pooling........................................................................................ 41 Regional Purchase Coefficients............................................................................. 41 Maximum RPC ................................................................................................... 41 First RPC ............................................................................................................ 41 Average RPC....................................................................................................... 41 Location Quotient ................................................................................................. 42

Advanced Institutional Transfers................................................ 42 Advanced Multipliers ..................................................................... 43 SAM Income.......................................................................................................... 44 Specific Disposable Income (%)............................................................................. 45 Type III ................................................................................................................. 45

IMPACT Analysis ..................................................... 47 Main Screen ...................................................................................... 47 Events................................................................................................. 48 Event Defaults ...................................................................................................... 54 Event Option Buttons ........................................................................................... 55

Groups................................................................................................ 55 Creating Groups.................................................................................................... 56 Deleting Groups .................................................................................................... 57 Importing Groups.................................................................................................. 57 Importing/Exporting Groups................................................................................. 59 Library Maintenance ............................................................................................ 61

Groups/Events Analysis ................................................................. 61 Results .................................................................................................................. 62

Projects .............................................................................................. 63

View Project Results ............................................................................................. 65

Reports....................................................................... 67 Creating ............................................................................................. 67 Print Options .................................................................................... 68 To Printer.............................................................................................................. 68 Print Preview ........................................................................................................ 69 Print to File........................................................................................................... 69 Print Setup............................................................................................................ 69 Zero Suppression................................................................................................... 69 Aggregate .............................................................................................................. 69

Study Area Reports ......................................................................... 70 1. Output, VA, Employment Report...................................................................... 70 2. Institution Commodity Demand ....................................................................... 70 3. Household Commodity Demand........................................................................ 71 4. Government Commodity Demand..................................................................... 71 5. Institution Commodity Sales ............................................................................ 71 6. General Model Information Report................................................................... 71 7. IMPLAN to SIC Bridge Report ......................................................................... 71 8. Type Codes Report ............................................................................................ 71 9. Aggregation Template....................................................................................... 71

Social Accounts Reports ................................................................ 72 1. Industry Balance Sheet Report......................................................................... 72 2. Commodity Balance Sheet Report .................................................................... 72 3. Commodity Summary ....................................................................................... 73 4. Commodity Trade Report.................................................................................. 73 5. Institution Local Commodity Demand.............................................................. 73 6. Household Local Commodity Demand .............................................................. 73 7. Government Local Commodity Demand ........................................................... 73 8. Industry Summary Report................................................................................ 73 9. Industries and Commodities in Model .............................................................. 73 10. Industry Import Matrix................................................................................... 73 11. Institution Import Matrix ............................................................................... 73

Social Accounting Matrix (SAM) Reports .................................. 74 1. Aggregate SAM (Aggregated Industries, Aggregated Rows) ............................ 74 2. Ind x Com SAM (Aggregated Industries, Row Detail) ...................................... 74 3. Ind x Com SAM (Industry Detail, Aggregated Rows) ....................................... 75 4. Ind x Com SAM (Industry Detail, Row Detail) ................................................. 75 5. 26 File CGE Format.......................................................................................... 75

Structural Matrix Reports............................................................. 75 Industry x Industry Reports ......................................................... 76 1. Institution Industry Demand............................................................................ 76

2. Household Industry Demand ............................................................................ 76 3. Government Industry Demand ......................................................................... 77 4. Industry Output/Outlay Summary ................................................................... 77 5. Aggregate IxI SAM (Aggregated Industries, Aggregated Rows)....................... 77 6. Regional Ind x Ind Direct Coefficients Report .................................................. 77 7. Regional Ind x Ind Transactions Report ........................................................... 77 8. Ind x Ind SAM (Aggregated Industries, Row Detail)........................................ 77 9. Ind x Ind SAM (Industry Detail, Aggregated Rows)......................................... 77 10. Ind x Ind SAM (Industry Detail, Row Detail) ................................................. 77

Multiplier Reports........................................................................... 78 Multiplier Report Column..................................................................................... 78

Impact Reports................................................................................. 79 Deflator Button ..................................................................................................... 80 Aggregation........................................................................................................... 80 Impact Report Table Headers............................................................................... 80

Other Features ......................................................... 83 Help System ...................................................................................... 83 IMPLAN Pro Help Topics ..................................................................................... 84

Internet Connectivity ..................................................................... 84 Converting Models .......................................................................... 86 Compacting Models......................................................................... 87 Structural Matrices Version ......................................................... 87 Memo Field........................................................................................ 88 Calculator.......................................................................................... 88 Changing Default Directories....................................................... 89 Customizing the Tool Bar .............................................................. 90 Tips and Hints .................................................................................. 90 Multiple Models .................................................................................................... 90 Current Model....................................................................................................... 90 Choosing a Sector.................................................................................................. 90 Sorting Grids......................................................................................................... 90 Tool Bars ............................................................................................................... 90

Book 2: Analysis Guide............................................ 91 INTRODUCTION ...................................................... 93 How Book 2 is Organized............................................................... 93

An Overview of Input-Output and Impact Analysis ...................................................................... 95

Defining Input-Output Analysis................................................... 95 Description Model ................................................................................................. 96 Predictive Model ................................................................................................... 96

T-Accounts......................................................................................... 97 Industry versus Commodity.......................................................... 98 Input-Output Accounting .............................................................. 98 Trade Flow Assumptions ............................................................. 100 1. Regional Purchase Coefficient (RPC).............................................................. 100 2. Supply/Demand Pooling.................................................................................. 100 3. Location Quotient - LQ ................................................................................... 101

Multipliers....................................................................................... 101 Key Assumptions ........................................................................... 103 Impact Analysis: A Definition..................................................... 104

Project Definition .................................................. 107 Defining a Project.......................................................................... 107 Margins ............................................................................................ 109 Deflators .......................................................................................... 111 Local Expenditures ....................................................................... 112 Project Definition Example......................................................... 112

Study Area Considerations .................................. 115 Functional Economic Area .......................................................... 115 Forward and Backward Linkages ............................................. 116 Small Study Areas ......................................................................... 118 Example: Small Study Area................................................................................ 118

Predefined Study Areas ............................................................... 120 Standard County Classification ................................................. 120

Database Elements ................................................ 123 National-level Matrices and Tables........................................... 123 County-level Database Components ......................................... 124 Industry Output ............................................................................. 125 Employment.................................................................................... 125 Value Added.................................................................................... 125 Final Demands ............................................................................... 126 Household Demand ....................................................................... 127 Federal Government..................................................................... 128 State and Local Government ...................................................... 128

Inventory ......................................................................................... 128 Capital.............................................................................................. 129 Exports............................................................................................. 129

Regional Accounts Construction ........................ 131 Study Area Data............................................................................. 131 National Matrices .......................................................................... 132 Net Commodity Supply and /Regional Make........................... 134 Regional Market Shares and Byproducts ................................ 135 Gross Regional Absorption and Use Matrices......................... 136 Gross Regional Commodity Demand ........................................ 139 Regional Supply/Demand Pooling and RPC............................ 141 Supply/Demand Pooling...................................................................................... 141 Regional Purchase Coefficient (RPC).................................................................. 142 Location Quotient ............................................................................................... 143 Regional Commodity Demand Less Imports....................................................... 143

Regional Commodity Imports..................................................... 146 Domestic Exports........................................................................... 148

Inter-institutional Transfers ............................... 149 SAM History.................................................................................... 149 SAM Framework ............................................................................ 150 Balancing......................................................................................... 153 Use of SAMs in I/O Research ....................................................... 154 1. Descriptive Analysis........................................................................................ 154 2. Tax Analysis.................................................................................................... 154 3. Computable General Equilibrium Modeling................................................... 154 Regional SAM Analysis Example ....................................................................... 155

Industry-by-Industry Accounts ........................... 159 1. Industry Technology Assumption.......................................... 159 2. Market Shares Assumption ..................................................... 160 Industry-by-Industry Creation................................................... 161

Predictive Model Derivation ............................... 163 MULTIPLIERS ............................................................................... 163 Type I Multipliers.......................................................................... 164 Type II Multiplier .......................................................................... 169 Type SAM Multipliers ................................................................... 171 Value-Added Multipliers .............................................................. 172

Employment Multipliers .............................................................. 173

Impact Analysis ...................................................... 175 Organizing Impacts....................................................................... 175 Example Analysis........................................................................... 177 Consumer Expenditure Activities ............................................. 181 Production Function Changes.................................................... 181 Aggregation Error ......................................................................... 182 Trade Flow Estimation Error Sources...................................... 185 Discussion of Induced Effects..................................................... 186 Type II Induced Effects....................................................................................... 186 Compensating for Induced Effect Estimation Errors ......................................... 186

Case Studies ............................................................ 189 Case Study 1: Creating a Model.................................................. 190 Case Study 2: Single Industry Impact....................................... 191 Case Study 3: Multiple Events and the Use of Margins ........ 194 Case Study 4: Using Groups and Household Final Demand Change ............................................................................................. 197 Case Study 5: Analyzing A New Industry................................. 200 Case Study 6: Using Projects and Survey Data: The Impact of a Local College ............................................................................... 202 Case Study 7: Effects of Changing Regional Purchase Coefficients (RPCs) ....................................................................... 208 Case Study 8: Creating an Aggregated Model ......................... 210 Case Study 9: Advanced Features.............................................. 212

Literature ................................................................ 215 Book 3: Database Guide ........................................ 219 INTRODUCTION .................................................... 221 How Book 3 is Organized............................................................. 221

Organizing the Data .............................................. 223 Database Construction................................................................. 223 MID.ODF Components.................................................................. 226 National Matrices & Tables......................................................... 227 Sectoring Schemes ........................................................................ 227 North American Industrial Classification System (NAICS) Codes .................... 228

Regional Economic Information System (REIS) Sectoring ................................. 228 Bureau of Labor Statistics Sectoring .................................................................. 228 Bureau of Economic Analysis Input-Output Sectoring....................................... 228 Special Sector Definitions ................................................................................... 229

Employment ............................................................ 231 Non-Disclosure ............................................................................... 231 County Business Patterns (CBP) ............................................... 232 BLS CEW.......................................................................................... 233 Non-Disclosure Adjusting the CEW Data........................................................... 234

Special Sectors ............................................................................... 235 Agriculture.......................................................................................................... 235 Construction........................................................................................................ 237 State and Local Government .............................................................................. 237 Federal Government ........................................................................................... 239

Regional Economic Information System.................................. 240 Dividing Counties and Independent Cities......................................................... 241 Deriving REIS State Non-Disclosure Adjustments ............................................ 242 Deriving REIS County Non-disclosure Estimates .............................................. 243 Distributing Disclosed 3-digit Employment and Income REIS Data to IMPLAN Sectoring ............................................................................................................. 245

Full-Time Equivalents .................................................................. 246

Value-Added ............................................................ 249 Overview.......................................................................................... 250 National Value-Added Estimates ............................................... 250 Proprietor Income and Employee Compensation................................................ 250 Indirect Business Taxes and Other Property Type Income................................ 251 Distributing National Value-Added Estimates to State and Counties............... 251

Output ...................................................................... 253 Total National Industry Output ................................................. 253 Agriculture.......................................................................................................... 253 Mining................................................................................................................. 253 Construction........................................................................................................ 254 Manufacturing .................................................................................................... 254 Transportation, Communication, Utilities ......................................................... 254 Finance, Insurance, Real Estate......................................................................... 254 Wholesale ............................................................................................................ 254 Retail................................................................................................................... 254 Services ............................................................................................................... 254

National TIO/TCO.......................................................................... 254

State and County Distribution of TIO ...................................... 255

Institution Demand ............................................... 257 Household Expenditures ............................................................. 258 Federal Government Military/ Non-military Expenditures and Sales.......................................................................................... 259 State and Local Government Purchases for Education and Non-education and Sales ............................................................. 260 Inventory Purchases and Sales .................................................. 261 Capital.............................................................................................. 261 Foreign Exports and Imports ..................................................... 262

Inter-Institutional Transfers ............................... 263 SAM Framework ............................................................................ 263 SAM Data Development ............................................................... 266 National SAM ..................................................................................................... 266 State and County SAM Data .............................................................................. 266 Household Transfer Income Data ....................................................................... 266 State and Local Government Transfers Data ..................................................... 267 Federal Transfers................................................................................................ 268 Capital................................................................................................................. 268 Trade................................................................................................................... 268

Personal Consumption Expenditure (PCE) Distribution..... 268 Balancing......................................................................................... 269

National Matrices and Tables.............................. 271 National I/O Structural Model .................................................... 271 Make Matrix ....................................................................................................... 271 Use Matrix .......................................................................................................... 272

MARGINS ........................................................................................ 273 Deflators .......................................................................................... 274 Regional Purchase Coefficients ................................................. 274 Source of Data for Predictive Equations............................................................. 275 What causes errors in trade flow estimation?..................................................... 275

Database Validation .............................................. 277 Validation Process......................................................................... 277 Force Account Construction Adjustment ................................ 277

Database Literature Citations............................. 279 Glossary and Appendices ..................................... 283

Glossary ................................................................... 285 IMPLAN Sector Scheme........................................ 291 FIPS Codes .............................................................. 303 SAM Element Description .................................... 319 IMPLAN Data Types Codes .................................. 323 IAP Database Documentation ............................. 325 Library File Documentation ................................ 341 U.S. Structural Matrices File Documentation.. 344 Sample Reports ...................................................... 349 Study Area Reports No. ............................................................. 349 Social Accounts Reports .............................................................. 349 IxC SAM Reports............................................................................ 349 Structural Matrices....................................................................... 350 Industry by Industry Reports..................................................... 350 Multipliers Reports ....................................................................... 350 Impacts Reports............................................................................. 350 Study Area Reports ....................................................................... 352 Social Accounts Reports .............................................................. 361 IxC SAM Reports............................................................................ 372 Structural Matrices....................................................................... 373 Industry-by-Industry Reports .................................................... 375 Multiplier Reports......................................................................... 382 Impacts Reports............................................................................. 391

Exporting/Importing Text Files .......................... 403 Exporting Impact Groups of Events:......................................... 403 Importing Impact Groups of Events: ........................................ 403 Exporting Regional Purchase Coefficients ............................. 405 Importing Regional Purchase Coefficients ............................. 405

IMPLAN Construction to Census........................ 407 Index......................................................................... 411

i

Introduction The IMPLAN Pro Software package includes three manuals: 1. IMPLAN Pro User Guide introduces the user to the features and commands associated with the social accounting and impact analysis software. 2. IMPLAN Pro Technical Analysis Guide is a guide to the applied and theoretical aspects of impact analysis (I/O) and input-output accounting using the IMPLAN Pro software. 3. IMPLAN Database Documentation describes the data developed by MIG, Inc. for use with IMPLAN software.

Manual Conventions These manuals are designed to provide the user with information on the software as well as actual model construction. For simplification, the following conventions have been adopted. Bold type indicates a button name or keystroke action; Italic type indicates a definition; “Quote enclosed” indicates a name.

IMPLAN Description IMPLAN (IMpact Analysis for PLANning) was originally developed by the USDA Forest Service in cooperation with the Federal Emergency Management Agency and the USDI Bureau of Land Management to assist the Forest Service in land and resource management planning. MIG began work on IMPLAN databases in 1987 at the University of Minnesota. In 1993, Minnesota IMPLAN Group, Inc was formed to privatize the development of IMPLAN data and software. Version 1 of the Windows software was developed by MIG and released in June of 1996. Since then, Version 2 was released in May of 1999. The IMPLAN system has been in use since 1979 and has evolved from a main-frame, non-interactive application that ran in "batch" mode to a menu-driven microcomputer program that is completely interactive. IMPLAN Professional introduces flexibility in the methods and assumptions used to generate social accounts and I/O multipliers and

ii takes full advantage of the Windows environment not found in other systems. There are two components to the IMPLAN system, the software and the database. The software performs the necessary calculations, using the study area data, to create the models. It also provides an interface for the user to change the region’s economic description, create impact scenarios and introduce changes to the local model. The software is described in detail in the User Guide. The databases provide all the information needed to create regional IMPLAN models. The model elements and procedures are described in the Analysis Guide, while the methodologies used to derive the data is in the Database Guide. The IMPLAN system can be used to analyze a wide variety of issues including, but not limited to: Industry relocation Stadium development Military base closings Natural resource issues Economic base analysis IMPLAN’s regional social accounting system easily allows a user to: Develop a set of balanced economic/social accounts -i.e., a descriptive model; Develop multiplier tables -i.e., a predictive model; Change any component of the system, production functions, trade flows, or database; Create custom impact analysis by entering final demand changes; Obtain any report in the system to examine the model’s assumptions and calculations. IMPLAN software was designed to serve three functions: 1. Data retrieval 2. Data reduction and model development 3. Impact analysis

iii 

The IMPLAN database, created by MIG, Inc., consists of two major parts: 1. National-level technology matrices; 2. Estimates of regional data for institutional demand and transfers, value-added, industry output and employment for each county in the U.S. as well as state and national totals. The IMPLAN data and accounts closely follow the accounting conventions used in the "Input-Output Study of the U.S. Economy" by the Bureau of Economic Analysis (1980) and the rectangular format recommended by the United Nations. Comprehensive and detailed data coverage of the entire U.S. by county, and the ability to incorporate user-supplied data at each stage of the model building process, provides a high degree of flexibility both in terms of geographic coverage and model formulation.

Software Features IMPLAN Pro features include: 1. Windows file and printer management; 2. Database editor; 3. Complete Social Accounting Matrix structure; 4. A choice of trade-flow assumptions: a. Supply-Demand Pooling; b. Regional Purchase Coefficients; c.

Location Quotients.

5. Production function editor -i.e., the tools and opportunity necessary to modify the “absorption” and “byproducts” matrices; 6. Libraries for storing frequently used production functions, byproducts, Regional Purchase Coefficients (RPCs), and impact analysis expenditures; 7. Flexible model aggregation tools; 8. Many preset reports for all stages of model building and analysis; 9. Export feature to many of the major PC file formats; 10. Flexible assumptions for induced effects;

iv 11. Type II-Based on Personal Consumption Expenditures (PCE) and Social Accounting Matrices (SAM) based local income relationship; 12. Type II-Based on user-specified disposable income rate; 13. True SAM-multipliers (Type SAM) based on social accounting matrix; 14. Menu structure for easy impact analysis; 15. Event-based impact databases; 16. Built-in and editable transaction margins; 17. Built-in and editable deflators; 18. Data in MS Access 2000 Database format; 19. Technical support by MIG, Inc.

v

IMPLAN Licensing Policies SOFTWARE LICENSE AGREEMENT This is a legal agreement between you and Minnesota IMPLAN Group, Inc., d/b/a MIG. By installing and using the Software, you are agreeing to be bound by the terms of this Agreement. If you do not agree to the terms of this Agreement, promptly return the Software and accompanying items to Minnesota IMPLAN Group, Inc., 1725 Tower Drive West, Suite 140, Stillwater, MN 55082. Grant of License MIG grants you the right to use one (1) copy of the Software on a single computer. You may not rent, lease or resell the Software. You may transfer the Software on a permanent basis provided you retain no copies and the recipient agrees to the terms of this Agreement. This Agreement is effective from the day you install the Software until terminated. You may terminate your license by returning to MIG the original disks and any backup copies. If you breach this Agreement, MIG can terminate this license upon written notification to you. Copyright The Software is owned by MIG and is protected by United States copyright laws and international treaty provisions. Therefore, you must treat the Software like any other copyrighted material except that you may either (a) make one (1) copy of the Software solely for backup or archival purposes, or (b) transfer the Software to a single hard disk provided you keep the original solely for backup or archival purposes. All titles, trademarks, copyright and other notices must be reproduced in any copy of the Software. Controlling Law This Agreement shall be governed by and construed in accordance with the laws of the State of Minnesota. Technical Support Policy MIG will support only registered users of the Software. Please return the registration card. A registered customer may permanently assign the Software and customer identification to another person if that person is responsible for maintaining the Software. Please contact us if registration information changes. WARRANTY AND LIMITATION OF LIABILITY MIG warrants the disks on which the Software is recorded to be free from defects in materials and workmanship under normal use for a period of ninety (90) days from the date of purchase. THIS WARRANTY IS EXCLUSIVE AND IN LIEU OF ALL OTHER

vi WARRANTIES, EXPRESS OR IMPLIED, INCLUDING THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. Your exclusive remedy, and MIG’s entire liability, for any breach of warranty by MIG, is the replacement of defective media. IN NO EVENT SHALL MIG BE LIABLE FOR ANY DAMAGES WHATSOEVER (INCLUDING WITHOUT LIMITATION, DAMAGES FOR LOSS OF BUSINESS PROFITS, BUSINESS INTERRUPTION, OR ANY OTHER PECUNIARY LOSS) ARISING OUT OF THE USE OR INABILITY TO USE SOFTWARE, EVEN IF MIG HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

DATABASE LICENSE AGREEMENT This is a legal agreement between you and Minnesota IMPLAN Group, Inc, d/b/a MIG. By installing and using the MIG Database, you are agreeing to be bound by the terms of this Agreement. If you do not agree to the terms of this Agreement, promptly return the database disks and accompanying items to Minnesota IMPLAN Group, Inc., 1725 Tower Drive West, Suite 140, Stillwater, MN 55082. Grant of License MIG grants you the right to use one (1) copy of the Database on a single computer solely for your own internal operations. You may not sublicense the Database or use the Database for third-party commercial time-sharing, rental or service bureau use, nor sell, lease, license electronically post, or otherwise distribute or publish Database contents or the results of any model developed using the Database, apart from written reports prepared by you or in connection with other value added services offered by you. This Agreement is effective from the day you install the Database until terminated. You may terminate this agreement by returning to MIG the original disks and any backup copies. If you breach this Agreement, MIG can terminate this license upon written notification to you. Copyright The Database is owned by MIG and is protected by United States copyright laws and international treaty provisions. Therefore, you must treat the Database like any other copyrighted material except that you may either (a) make one (1) copy of the Database solely for backup or archival purposes, or (b) transfer the Database to a single hard disk provided you keep the original solely for backup or archival purposes. All titles, trademarks, copyrights and other notices must be reproduced in any copy of the Database.

vii Controlling Law This Agreement shall be governed by and construed in accordance with the laws of the State of Minnesota. Technical Support Policy The Database is designed to be used with the IMPLAN Pro economic modeling system software which may be separately licensed from MIG. Support services are provided by MIG only to registered users of the IMPLAN Pro software. These policies are subject to change. WARRANTY AND LIMITATION OF LIABILITY MIG warrants the disks on which the Database is recorded to be free from defects in materials and workmanship under normal use for a period of ninety (90) days from the date of purchase. MIG makes no warranty as to data accuracy or that the Database will meet your requirements. The Database information is to be used with the understanding that the user bears all responsibility for proper decisions and use of the Database and subsequent analysis. THIS WARRANTY IS EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS OR IMPLIED, INCLUDING THE WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. Your exclusive remedy, and MIG’s entire liability for any breach of warranty by MIG, is the replacement of defective media. IN NO EVENT SHALL MIG BE LIABLE FOR ANY DAMAGES WHATSOEVER (INCLUDING WITHOUT LIMITATION, DAMAGES FOR LOSS OF BUSINESS PROFITS, BUSINESS INTERRUPTION, OR ANY OTHER PECUNIARY LOSS) ARISING OUT OF THE USE OR INABILITY TO USE THE DATABASE, EVEN IF MIG HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. Site Licenses If you have more than one person who needs access to the Database files covered by this license at the same time, then you must obtain a site license. The site license will allow the Database to be installed on additional machines and have additional customers registered to use the Database. Call for site license information.

BOOK 1: USER GUIDE

Chapter 1: Introduction 1

C H A P T E R

1

INTRODUCTION How this Guide is Organized Chapter 1 “Introduction” describes the steps to get started using the IMPLAN Pro Chapter 2 “Model Building” describes the process of generating a set of social accounting matrices and multipliers. Chapter 3 “ Advanced Model Building” describes some of the other features available by stepping through the model building process. Chapter 4 “IMPACT Analysis” describes how you introduce a set of economic expenditures into the software in order to derive and view the resulting economic activity. Chapter 5 “Reports” describes the options for displaying social accounting and impact data and results. Chapter 6 “Other Features” describe some of the software utilities as well as some tips for using the software.

Getting Started System Requirements Windows 95/98/2000 or NT 4.0 (Service Patch 3 or higher), Millenium, XP or later 486 or higher (Pentium processor recommended) 16MB (32MB or more recommended) 40 MB Hard disk for software. Models will range from 2 MB to 20 MB Software is designed to reside on a local hard drive and may not work properly if installed on a network server.

Installing IMPLAN Pro Software 1. Close any applications you have running. You can check for this by holding the keys at the same time.

2

Chapter 1: Introduction The task manager will be displayed. Close all applications except Explorer; 2. Insert the IMPLAN Pro CDROM in your drive; 3. The software should automatically start the installation routine from the CD. If Autorun doesn’t start, click Start then Settings, then Control Panel and Add/Remove Programs. Click Add, select your CD ROM drive and proceed with the installation from there; 4. Follow the on-screen instructions.

Installing IMPLAN Structural Matrices You will also need to install the IMPLAN structural matrices to build models successfully. The most current National Structural Matrices will be installed along with your software. If you ordered data, it will come on the IMPLAN Data CD. The IMPLAN Data CD contains the National Structural Matrices, margins, deflators, and other data relevant to a specific year of IMPLAN data. To Install IMPLAN Structural Matrices: 1. Open Windows Explorer and Select your CD ROM Drive; 2. Go to the IMPLAN Structural Matrices Directory; 3. Double click on the EXE file containing the structural matrices (e.g. 97wstrct.exe) and follow the on-screen instructions.

Installing IMPLAN Data Files Each IMPLAN data file contains the information necessary to generate a regional model, either singly or combined with other data files. If you ordered IMPLAN data, it will come on an IMPLAN Data CD. You do not need to install the data files, you can simply read them from the CD with IMPLAN Pro. If you want, you can copy the data files to your \Program Files\IMPLAN Professional 2.0\Data subdirectory using Windows Explorer. An example county, Larimer, CO, will be installed with your software.

Creating Your First Model Generating an IMPLAN model and conducting impact analysis with the IMPLAN software follows a general sequence. 1. Build a new model;

Chapter 1: Introduction 3 2. Make any modifications in your region. Changes might include modifying industry/commodity data, absorption coefficients, and/or the byproduct coefficients; 3. Build the social accounts - create a balanced set of complete SAM accounts (descriptive model); 4. Modify trade flow assumptions if desired; 5. Build the multipliers (predictive model) - choose an induced option-Type II (income based); Type SAM (SAM based); or Type I (no induced effects); 6. Define the events - enter the expenditures/final demands to be applied to the predictive model; 7. Run the analysis; 8. Create reports for analysis and final reports. The following instructions will guide you through the model building and a simple analysis. 1. Start the IMPLAN software (if this is the first time running the software, you will need to complete the registration information). Click Start, Programs, IMPLAN Professional 2.0. 2. Select File/New Model or click the Save button to create a new study area. 3. Name it “Larimer”. Click Save. 4. Select the 1994 Larimer, CO a file from the ..\Data\ directory. Either double-click the file name, or single-click on the name and click on the >> button. 5. Click Continue. 6. When the study area is done, Click OK. 7. Select Construct Model from the Model Control Center or Model/Construct from the menu bar. 8. In the Multiplier Options box, click the Type SAM option. The Social Accounts and Multipliers buttons will be filled in automatically. 9. Click Continue and the model processing will start. When the model is done click OK, then click Close. 10. From the Model Control Center, click on Impacts. 11. Click Add New. The cursor will go to the next empty Event Name cell.

4

Chapter 1: Introduction 12. Give the event a name, call it "Computers." Press the Enter key. 13. Press the Enter key to move to the next cell. 14. Click on the down arrow and select sector code 339. Press the Enter key. 15. Press the Enter key to move to the Employment cell. 16. Enter 200 in the Employment cell. Press the Enter key. 17. Make sure Industry is selected at the Basis field. Press the Enter key. Leave the other items alone. 18. Click on the Analyze button. You will see Computers in the Ungrouped Events window. 19. Make sure the Level cell is set to 1.0. Press the Enter key to move to the Impact Name field. Enter a name. Call it "Computer Run." 20. Click on Run Impact. 21. When the Impact Analysis is completed, click Yes to view the results. 22. You could now go to reports and print these results. There are additional case studies in Book 2: Analysis Guide that contain step-by-step examples to lead you through analysis using IMPLAN Pro.

What’s New There are many new features in IMPLAN Pro Version 2.0. New features include:

General: Model processing speed almost 4 times faster than version 1.1; Direct Internet connection from software for updates and technical support; Enhanced library function to include Byproducts and RPCs as well as Production functions and group impacts; Software ready for new version of RPCs, when available; Select multiple data files (*.odf) with when building a region; Expanded Personal Consumption Expenditures (PCE) categories from three to nine;

Chapter 1: Introduction 5 Expanded Government consumption & investment expenditure categories; Quick View model status without opening model; Save folder locations; Moveable toolbars.

Model Construction: New Type SAM multiplier that corrects for the commuting problem (see www.IMPLAN.com/kb article #20063); More descriptive model building screens; SAM Multipliers incorporate user-selected institutions (i.e. households, federal government); Ability to pause or cancel model processing; More descriptive Model construction screen.

Data Editing: Ability to import and export of RPC text (ASCII) files; Ability to save byproduct, regional purchase coefficient, and production function changes to the library; Added features to edit Foreign Exports and Commodity Sales; Sorting (ascend/descend) on-screen data; Use of location quotients for RPCs; Edit individual industry or institution commodity RPCs; Add or delete margins.

Reports: Expanded reports detailing more information contained in the model including: Import matrices (competitive & noncompetitive), Industry SAM, Institutional Sales; New enhanced report engine for better previewing and printing; Aggregate study area reports.

Impact Analysis: Impacts allows for “value added” or “institutional income” change directly through the impact analysis section of the software; Ability to import and export Groups and Events to text (ASCII) files;

6

Chapter 1: Introduction Rename existing groups; Additional on-screen information about impacts, including sums of event “value” and number of events in each group; Ability to rename groups; Ability to edit impact proportions spent locally (formally LPC); Ability to change all values in a particular column.

Technical Support If you require technical support, contact MIG, Inc. at: Web:

www.implan.com – the tech support page contains a Knowledge Base for on-line support, a Research Papers database. A Consultants list is also available. If you use AOL, you will need AOL 4.0 or higher (it is included on your IMPLAN Pro CD).

E-mail:

[email protected]

Fax:

(651) 439-4813

Phone:

(651) 439-4421

When you call you should be at your computer and be prepared to give the following information: Your name and product registration number; The version number of IMPLAN Pro you are using (in Help/About); The type of hardware you are using; The exact wording of any messages that appeared on your screen; A description of what happened and what you were doing at the time; A description of how you tried to solve the problem.

Chapter 2: Model Building

C H A P T E R

7

2

Model Building This chapter illustrates the software features and instructions for building models: Starting the Software The Model Study Area Construct Model Customizing

Starting the Software IMPLAN Professional software conforms to the standard look and feel of any Windows based program. Accessing menus and selecting files are all point and click procedures. To start the IMPLAN Pro software, click on the software icon from the IMPLAN program group (Figure 2-1). 

Figure 2-1 IMPLAN Pro Program Group

Once the software opens, you will be presented with the main menu. This is the starting point for building IMPLAN models. There are four menu choices, File, Tools, Window, and Help. Figure 2-2 shows the main menu screen.

8

Chapter 2: Model Building 

Figure 2-2 IMPLAN Pro Software Opening Screen

The Files option allows you to work with your IMPLAN models. The Tools option allows you to perform different maintenance operations on your models as well as customize your IMPLAN Pro menus. IMPLAN Pro help can be accessed at any time from any menu. Either click on the drop-down Help menu item or press Alt-H.

The Model Creating a model is the first step in any IMPLAN Pro project. The drop-down File menu (Figure 2-3) shows that we can either create New Model or Open Existing Model. Figure 2-3 File Menu

Chapter 2: Model Building

9

All data, accounts, expenditure patterns, reports, etc., pertaining to a specific model are kept in a single Microsoft Access 97TM database container. Existing models are those previously created by a user. The most recently used models are listed near the bottom of the File menu or in the Recent Models drop down box on the main screen. Selecting File then Open Existing Model will open the dialog box shown in Figure 2-4. Selecting the New Model icon on the icon bar will also access it. This dialog box displays information about the existing models stored on your hard drive. You can select different directories or drives by selecting the Look in. If the Preview Model Information box is checked, information about that model will be displayed when you select your model. File selection may be slowed if this option is checked. Figure 2-4 Open an Existing Model

To open an existing model, select the correct drive and directory and then select the desired model (files with an “iap” extension are IMPLAN Pro models). The default model directory is c:\program files\implan professional 2.0\models, but models can be stored anywhere.

10 Chapter 2: Model Building The first time IMPLAN Pro is opened, you will have to create a new model since there will be no existing models. The screen shown in Figure 2-5 can be displayed by selecting New Model from the File menu or by selecting the New-Model icon on the icon bar. Figure 2-5 Create New Model

Once the drive and directory have been selected, you will need to type in a model name. When creating models, we suggest using a naming system that allows you to easily find them later. If you use the name of an existing model, all information in that existing model will be overwritten with the new model. IMPLAN Pro will warn you if you have selected a model name already in use. Once you’ve selected your model name, click Save. The software will create the MS Access 97 data container and prepare for reading the study area data.

Study Area When creating a new model it is necessary to define the study area by selecting a state or county file(s). After clicking Save, Figure 2-6 will be displayed screen.

Chapter 2: Model Building 11 Figure 2-6 Build Region

All data files in the selected directory will be displayed. The data files are available at the county, state, or U.S. level. You can define a model for a single county, several counties, a state, a group of states, or the entire United States. The data files that you include in your model are combined into a single database file that forms the basis for all subsequent model-building steps. The default data directory is: c:\program files\implan professional 2.0\data. Data files can reside in different directories so you must select the proper directory and then the data files. If the data resides on a CD, then select that drive and the corresponding directories. Data files can be selected by double-clicking the desired file name or highlighting the file and clicking the >> button to move the file from the Available IMPLAN Data Files window to the Selected Files(s) window. You can jump to specific counties in the list box by typing the first letter of the county or state name. The cursor will jump to the first county or state in the list that begins with that letter. If it finds a matching name and the letter is typed again, it will move to the next name in the list beginning with that letter. Files can be unselected by double-clicking the undesired file name in the Selected File(s) portion of the menu. Files can also be

12 Chapter 2: Model Building unselected by highlighting the file in the Selected Files window and clicking the << button. Once all desired data files have been selected, click the Continue button. After the initial phase of the model has been constructed you will see the main model screen (Figure 2-7). This is the Model Control Center, displaying the current status of the model along with information about the study area. The progress bar at this stage displays Study Area Built. Figure 2-7 Model Screen

The Model Control Center shows the main model screen and displays the states/counties that comprise the region, key economic data about the compiled region, as well as buttons for further model building activities and impact analysis. These features are also available on the main screen menu bar. The Model Control Center gives you four button options that will be covered in the next four sections: 1. Construct Model - generates the social accounts and the predictive multipliers; 2. Impacts - performs impact analysis (not accessible until the multipliers have been derived); 3. Edit – allows you to customize the regional data and accounts to conform to your local knowledge or to fit a new situation; 4. Reports - generates reports describing components of the region’s social accounts and multipliers, as well as impact analysis reports.

Chapter 2: Model Building 13 Double clicking on a component county of the region shown in the States/Counties Included window will display key economic data for that individual county. Figure 2-8 shows the resulting display. Figure 2-8 Individual County Information

Since Larimer County is the only county in our example model, its data is the same as the data for the model.

Construct Model There are two different models constructed for each region. 1. The descriptive model describes the transfers of money between industries and institutions. It contains the social accounts and the input-output accounts. 2. The predictive model is the set of input-output multipliers which “predict” total regional activity based on a change in consumption - i.e., a vector of expenditures. The descriptive model must be generated before IMPLAN Pro generates the predictive model. To build your IMPLAN model, click the Construct Model button from the Model Control Center or Model/Construct from the menu bar. Once Construct Model has been selected, the Construct Model screen is displayed (Figure 2-9). The construction options correspond to the two kinds of models discussed above. Checking the Social Accounts option will create a

14 Chapter 2: Model Building descriptive model. Checking the Multipliers option will generate a predictive model. The Model Construction screen also displays information about the model status, displaying the model you are working on, as well as its directory path. It also shows you what stage of the model construction process you are on. Figure 2-9 Model Option

Construct Social Accounts (Descriptive Model) Selecting the Social Accounts option will tell the software to construct the model through the social accounts only. The balanced industry by commodity input-output accounts will be created as well as the complete social accounting matrices. The default trade flow assumptions are Regional Purchase Coefficients (RPCs). RPCs are derived with an econometric equation that predicts local purchases based on the region’s characteristics. Additional choices are available by using the advanced model construction process, discussed later in Chapter 2. The ratio of locally purchased to imported goods is perhaps the most significant factor affecting subsequent multipliers. The greater quantity of goods purchased locally, the more local economic activity will be stimulated and, hence, the larger the resulting multiplier. Unless you have specific reasons to choose a different option, we suggest using the default RPC estimates.

Chapter 2: Model Building 15

Construct Multipliers (Predictive Model) Selecting the Multipliers option will tell the software to construct the predictive model. If you have not created the social accounts first, they will be automatically constructed. If you want to include the induced effects, you will need to select the type of induced multiplier to construct. The induced effects traditionally capture household expenditures. There are several methods for determining induced effects. The default method is the Type SAM multiplier described below. It is only possible to choose one method. The Type I multipliers are generated and available for impact analysis and reports regardless of the induced multiplier method. Unless you have specific reasons not to, we suggest using the software’s Type SAM multipliers. The software will remember which option you last chose and that will be the new default. Type I Type I multipliers give the direct and indirect effects only - that is, the original expenditures resulting from the impacts plus the indirect effects of industries buying from industries. Household expenditure effects -i.e., induced effects are not estimated. Type II Type II multipliers are the direct, indirect, and induced effects where the induced effect is based on income. The relationship between PCE and income is based on resident-only income from the SAM accounts. The assumption is that there is a linear relationship between local income and local expenditures. It is possible to modify this relationship (see Chapter 2 Advanced Model Building for details). Type SAM Type SAM multipliers are the direct, indirect, and induced effects where the induced effect is based on information in the social account matrix. This relationship accounts for social security and income tax leakage, institution savings, and commuting. It also accounts for inter-institutional transfers. This multiplier is flexible in that you can include any institutions you want. In other words, if you want to create a model closed to households and state and local government, you can. If you select this option, an additional dialog box with be displayed allowing you to select the institutions you want to include (Figure 2-10).

16 Chapter 2: Model Building Figure 2-10 Type SAM Institution Selection

Figure 2-11 shows the model control panel after constructing a model. Notice the current status of the model at the top center. Figure 2-11 Model Control Panel after Model Construction

Chapter 2: Model Building 17

Customizing Customizing refers to your ability to edit the data sets provided by MIG, Inc. Since access is provided to all IMPLAN Pro data sets and parameters, you can configure the descriptive and predictive models to any desired situation. The editing routines in this software have built-in checks and lead you through the editing steps. You can also directly modify IMPLAN models through MS Access. However, a thorough understanding of the model and the tables in the database is necessary before attempting this. Warning: any changes made are immediately saved, there is no undo feature. To prevent editing errors, be sure you create a backup of your model file prior to editing. From the main screen, select File and choose Save As. Choose a new model name to save your copy. The copy will become the current model, so close the backup copy and reopen your original for editing. Modification of a model is possible by pressing the Edit button on the main model menu. Figure 2-12 Edit Menu

As seen from Figure 2-12, we have seven main choices with three additional choices in the “Region Data” option: 1. Region Data - This contains the original data from the original data files combined into your region. This includes the study area data, value added, output, employment and final demands. You can also edit the foreign exports and commodity sales data. These are all data elements from the Original Data Files (ODF) you used to build your study area.

18 Chapter 2: Model Building 2. Deflators - Deflators are used to convert impact expenditures from current year to the base year of the predictive multipliers. Conversely, the deflators can be used to inflate the study area and impact reports to the current year. 3. Margins - Margins are used to convert purchaser prices to producer prices. Margins are different depending on the consumer. Households pay transportation, wholesale, and the full retail margins. Industries or the Federal government pay different margins. For example, government may pay little or no retail margins as it has more buying power. It is possible for you to edit margins for a specific kind of consumer or region. 4. Regional Purchase Coefficients - You can alter the trade flows by specifying how much of each commodity purchasing industries and institutions buy from regional sources. 5. Production Functions - Technical coefficients start on a national average basis. If adjusted national averages don’t make sense for your region (i.e. Hawaii) or a uniquely different industry moves in, you may want to modify the production functions. 6. Byproducts - The split of commodities produced by a given industry is also national average. These too can be modified. 7. Multipliers - Although multipliers are listed as an editing choice, you cannot modify a multiplier directly. You need to edit the underlying data to change the multipliers. This screen is simply a means to view the multipliers. Current multipliers (if estimated) become obsolete once a change is made to the Study Area, RPCs, Production Function, or Byproducts matrix. Figure 2-13 shows how the model control panel indicates that a change has been made in accounts; therefore, the model needs to be rerun so that multipliers will reflect that change. Figure 2-13 Model Screen Message

Chapter 2: Model Building 19

Editing Region Data Region area data is divided into two basic categories: 1. Data elements on an industry basis - i.e., value added, output, and employment (Figure 2-14); 2. Data elements on a commodity basis - i.e., final demands, foreign exports, and institutional sales (Figure 2-15). Figure 2-14. Edit Industry Study Area Data

Figure 2-15. Edit Commodity Study Area Data

20 Chapter 2: Model Building Modifying either the commodity or industry basis data requires highlighting the desired sector number and single-clicking or pressing Enter. The dollar values can then be highlighted on the left and the new dollar value (in $millions) typed in. Figure 2-16 shows the Foreign Export edit screen. This allows you to modify foreign exports. Figure 2-16 Edit Foreign Exports

Figure 2-17 shows the Edit Commodity Sales screen. With this screen, you can change any of the institutional sales values. Figure 2-17 Edit Commodity Sales

Chapter 2: Model Building 21

Note: changes to the data only modifies the model, there is no possible way using IMPLAN Pro to modify the original IMPLAN data files (*.ODF files) purchased from MIG.

Viewing Study Area Data The ability to view the study area data across many sectors is helpful both for validation of the region’s data, or to quickly compare sectors. This is possible for both the industry-based (Figure 2-18) and the commodity-based (Figure 2-19) data elements. It is not possible to edit the study area data from these screens. Figure 2-18. View Industry-Based Study Area Data

22 Chapter 2: Model Building Figure 2-19. View Commodity-Based Study Area Data

Modifying Deflators Figure 2-20 displays the Deflators edit screen. To edit deflators, from the Edit button, select Deflators and then the year (in this case “1998”). Figure 2-20. Modify Deflators

Chapter 2: Model Building 23 

The deflators in the IMPLAN Pro model are indexed to the base year of the data. For example, for a 1996 IMPLAN data file, 1996 deflators for all commodities will be 1.0. To convert 1996 data to 1998 prices for the Fluid Milk commodity, the software uses the highlighted value shown in Figure 2-18 (1.001872) and divides it into the 1998 value. Conversely, to convert a 1996 value to 1998, the software multiplies by the appropriate deflator. It is possible to modify the deflators by highlighting the desired value and typing in a new value. Note: the new value will be permanent for that model but will not change the value in the original data sets or future models.

Modifying Margins Margins allow you to correctly allocate retail type purchases to the appropriate IMPLAN sector. The margins in the IMPLAN database are based on national averages. If you have better information, you can modify the margins. To modify, select the commodity you want to change and replace existing margin value with desired margins (Figure 2-21). The fixed field will change to Yes. Click the Balance button so the margins again sum to 1. You can also rebalance the remaining margins by hand. Figure 2-21. Modify Margins

24 Chapter 2: Model Building There are five different margin types depending on the consumer. These are Household, Industry, Investment, Federal Government, State and Local Government. Each different consumer, on average, pays a different margin because of differences in buying power. Usually, the default in most analyses is Household margins. Some sectors do not have margins. For example, Hotels and Lodging do not have margins as there are no wholesalers or retailers involved when a consumer rents a room. In this case, the purchaser price is equal to the producer price. Also, consumers do not traditionally buy raw cotton or tobacco directly from the farm. This is an example of a sector that does not produce finished consumer goods. A consumer buys from a processor through retail stores rather than directly from a resource sector such as tobacco or cotton. See the Analysis Guide for a thorough discussion of margins.

Modifying Production Functions The production function corresponds to a given industry’s column of the gross absorption matrix. It is called “gross” because it represents total commodity needs regardless of whether the good is locally purchased or imported. Figure 2-22 displays the production function for industry 65: fluid milk. All changes made to the absorption coefficients will be forced to sum to the current column total (in this example 0.848066). Editing involves highlighting the current value and typing in a new value. To delete a commodity, select and press the Delete button. To add a commodity that the industry does not currently buy, press the Add New button. Note: that value-added plus the absorption coefficient sums to 1.0. Changing the value added to output ratio must occur in the Edit – Region Data window. Any modifications made to the production function will automatically be Fixed, indicated by the Yes in the fixed column. This means that the specified value will not be affected during the balancing process. You can fix any value. You will need to balance the remaining absorption cells. Either clicking the Balance button or closing the Edit screen will balance the remaining absorption coefficients so the sum of the absorption and value added coefficients is 1.

Chapter 2: Model Building 25 Figure 2-22 Edit Absorption Coefficients

Production Function Library When the production function edit screen is active, the Library menu is available on the main menu bar (Figure 2-23). The library is a place where you can store frequently used production function changes. Figure 2-23 Library Pull-down Menu

Save/Retrieve Functions This is used to get production functions from the library or add a production function to the library.

26 Chapter 2: Model Building Save Production Function: Select the Save tab under the Save/Retrieve Functions menu item and the window shown in Figure 2-24 is displayed. Figure 2-24 Production Functions Library

Specify the sector that contains your production function (absorption coefficients) and give it a name. The software will place it into the library for later retrieval. The column of absorption coefficients representing the production function will be saved as gross inputs i.e., commodity needs from all sources whether purchased locally or imported.

Chapter 2: Model Building 27 Retrieving a Production Function: is simply a matter of selecting the Retrieve tab, highlighting the desired production function and pressing the Retrieve button (Figure 2-25). Figure 2-25 Retrieve Absorption Coefficients

However, we now have a choice on balancing the production function (forcing the absorption plus value-added coefficients to sum to 1.0). 1. Balance Value-Added assumes the chosen production function is correct and that the value-added components of the industry must be modified to fit. Each value-added coefficient is proportionately increased/decreased so that the absorption plus value-added coefficients sum to one. 2. Balance Production Function assumes that the region’s valueadded data is correct and that the absorption coefficients must be modified to fit. This is accomplished through a constant proportional reduction/increase. This is the software’s default assumption. Editing a Production Function - To edit a library production function (Figure 2-26), choose one of the previously saved production functions by double clicking on the desired industry in the left window. The current absorption coefficients are then displayed in the right window. To modify an absorption coefficient, highlight the field to be modified and type in a new value. To delete a record (i.e., a

28 Chapter 2: Model Building commodity purchased by the production function), put the cursor somewhere in that record and click on the Delete button. Figure 2-26 Edit Library Functions

To add a record select Add New, which displays the dialog box in Figure 2-27. You provide the commodity number and the absorption value and click Add. Figure 2-27 Add New Absorption Coefficient

The absorption coefficients, saved as part of the library, will reflect the new and deleted coefficients. Note: Library functions do not work with aggregated models

Chapter 2: Model Building 29

Modifying Byproducts The byproduct matrix presents a description of commodities each industry produces, in coefficient form. All industry production is accounted for, therefore the sum of the coefficients must equal one. The example shown in Figure 2-28 is for industry 65, “Fluid milk”. Figure 2-28 Edit Byproducts Coefficients

“Creamery butter” is a byproduct and represents ~0.6 percent of the “Fluid milk’s” total production. To edit a coefficient, highlight the old value and type in the new value. To delete a commodity, select the commodity and click the Delete button. To add a commodity that the industry does not currently make, click the Add New button. As with the production functions, any changes made to the byproduct coefficients will require re-balancing so the by-products sums to 1.0. Any modifications made to production will automatically be Fixed, indicated by the Yes in the fixed column. This means that the specified value will not be affected during the balancing process. You can also fix any other values. You can also re-balance by hand.

Byproducts Library The library is also available for saving byproducts changes. It has similar functionality as the Production Function library.

30 Chapter 2: Model Building

Modifying Trade Flows Changing the Regional Purchase Coefficients (RPCs), is simply a matter of typing in a new value for that commodity. There are three different RPC edit screens: 1. The Commodity Detail; 2. The Commodity Table View; 3. The Commodity by Industry. The Commodity Detail screen (Figure 2-29) shows all the commodity supply and demand statistics. Editing an RPC for a specific commodity shows you the new values for imports, commodity purchases and domestic exports. To modify a commodity RPC, select the sector from the list box and change the RPC value. Figure 2-29. Edit RPC Commodity Detail

Figure 2-30 shows the Commodity-Table View. This screen simply shows the current RPC value and the Supply/Demand pool ratio for commodities in a table format.

Chapter 2: Model Building 31 Figure 2-30. Modify RPCs using the Tabular Format Screen

The last RPC edit possibility is the Commodity by Industry (Figure 2-31). This edit screen allows you to edit an individual RPC for either industry or institution purchases of commodities. This edit change only affects that specific industry/institution purchase. Select the commodity and all purchasers of the commodity will be displayed. You can then change an individual RPC for that commodity purchase. Figure 2-31 Edit RPC Commodity by Industry

32 Chapter 2: Model Building Note: the possible range for the RPC is constrained by the Supply/Demand Pooling ratio -that is, you can not purchase more local commodity than is locally produced.

Regional Purchase Coefficients Library In additional to the production functions and the library, you can also save changes to regional purchase coefficients in the library. From the RPC edit screen, click Library on the main menu, then click Save/Retrive Commodity RPCs. You then have a choice to either save the RPCs from your current model, or retrieve previously saved RPCs. The software will check the incoming RPCs against the model’s supply/demand pooling ratio.

Aggregation Aggregation is the process of combining IMPLAN sectors by adding together the values represented by those sectors. Aggregation is useful for summarizing data for presentations and can greatly speed the model building process. However, impact analysis using aggregated multipliers is susceptible to aggregation bias and is not recommended. Note: as an alternative to aggregating your model and introducing aggregation bias, you can aggregate the Study Area and the Impact Reports to summarize your model. The process of aggregation affects all levels of data. The study area data, structural matrices, deflators, RPC’s, margins, and subsequent multipliers are all aggregated. Once a model has been aggregated, it is not possible to recover the original full-sectored model. It is also not possible to aggregate an aggregated model. If a different aggregation is required, you have to start with a new model. From the main menu with an unaggregated model active, select Model from the main menu and then select Aggregate (Figure 2-32). Figure 2-32. Aggregate a Model

Chapter 2: Model Building 33 A blank unnamed aggregation template window opens (Figure 2-33). Figure 2-33. Blank Aggregation Template

It is possible to either use/modify a pre-existing template or create a new one. To retrieve existing templates click Library and select an existing template. To create a new aggregation scheme, the first step is to create a new aggregated sector by clicking the New button and typing a sector name. In Figure 2-34, “Construction” has been entered. An aggregated sector can be created, modified or deleted.

34 Chapter 2: Model Building Figure 2-34 Using the Aggregation Window

The sectors available (i.e., not aggregated with another one of the aggregated sectors) are shown in the left-hand portion of the “Sectors” portion of the window. Items in the right-hand portion represent industries in the aggregation. To select a sector, double-click or highlight it and click on the Select button. The Remove button functions the same as the Select button but in reverse. Highlighting an existing aggregated sector and clicking on the Remove button causes it to be “released”. The aggregated sector will be deleted from the right side and aggregated sectors reappear on the left. A set of aggregated sectors can be released by deleting the existing aggregated sector name (highlight aggregate name and click on Delete). The freed sectors are available to be incorporated in other aggregated sectors. An individual IMPLAN sector cannot be incorporated in more than one aggregate. Note: aggregated sectors cannot be further aggregated.

Chapter 2: Model Building 35 To apply the aggregation to the model, press the Aggregate button. The Close button closes the aggregation window but does not apply the defined aggregations. You might do this if you only want to create aggregated reports. Once an aggregation scheme is completed you will normally want to save it for use with other models. To save, press the Library button and select the Export to Library option button (see Figure 2-35). Figure 2-35. The Aggregation Library

IMPLAN Pro asks for a scheme name and places that scheme into the library when you press the Save button.

Chapter 3: Advanced Model Building 37

C H A P T E R

3

Advanced Model Building Stepping through the model construction process allows you to modify the model at each stage. At each step, it is possible to edit elements of the social accounts, as well as modify the assumptions associated with commodity trade flows and multipliers. This chapter discusses: Entering Advanced Model Construction Advanced Production Function Advanced Byproducts Advanced Trade Flows Advanced Institutional Transfers Advanced Multipliers

Entering Advanced Model Construction To begin, select Construct Model from the Model Control Center (Figure 3-1). Figure 3-1 Model Control Panel

As seen in the previous chapter, the model construction dialog box appears. However, this time we will click on the Advanced button. This opens the Production Function tab.

38 Chapter 3: Advanced Model Building Figure 3-2 Advanced Model Options

We can now step through the five tabs that represent successive stages of the input-output model building: 1. Production Function-derives industry demands for commodities. 2. Byproducts-describes the make of commodities by industry. 3. Trade Flows-determines what portion of demand is satisfied by local production. 4. Institutional Transfers - describes the flows between institutions. 5. Multipliers - derives the predictive model for direct, indirect and induced effects of a change in expenditures or production. At each tab, clicking on the Next>> button moves you to the next tab and moves the model to the next phase. Clicking on the <
Chapter 3: Advanced Model Building 39

Advanced Production Function In the advanced section there is nothing unique that is not available in the previous production function editor. However, this is a necessary step required to get to a point where some new advanced assumptions can be defined and applied.

Edit Existing Model Production Functions The production function corresponds to a given industry’s column of the gross absorption matrix. Figure 2-22, in Chapter 2, displays the edit production function window. See that section for a detailed description of editing.

Edit Library Production Functions The library stores user-generated absorption coefficients by industry which can be edited and saved to the library for use in any model. Figure 2-26, in Chapter 2, displays the edit library screen. A description of the procedures can be found there as well.

Import Production Function from Library Any production function saved to the library can be retrieved for use in the current model. Clicking on the Import button (Figure 3-2) generates the window similar to the window shown in Figure 2-25 in Chapter 2. Procedures are the same as described there.

Advanced Byproducts Clicking the Next>> button on the Advanced Production Function tab advances us to the Byproducts tab (Figure 3-3). As in the previous tab, there is nothing unique that can’t be done using the menu items for model construction.

40 Chapter 3: Advanced Model Building

Figure 3-3 Advanced Model Options

Discussion of editing byproducts and the byproducts editing window (Figure 2-28) are shown in the preceding chapter. Clicking on the Edit Byproducts button accesses the editing screen.

Advanced Trade Flows Clicking the Next>> button on the advanced Byproducts tab moves the model processing to the Trade Flows tab (Figure 3-4). Figure 3-4 Advanced Trade Flows

Chapter 3: Advanced Model Building 41 We now have three different options for trade flow assumptions: 1.

Supply/Demand Pool

2. Regional Purchase Coefficients (RPCs) 3. Location Quotients

Supply/Demand Pooling Supply/demand pooling assumes that local demand is completely satisfied by local production when possible. There is no “crosshauling” (see the Analysis Guide for a complete discussion).

Regional Purchase Coefficients Regional Purchase Coefficients (RPCs) are derived by an econometric equation. RPCs predict how much local production is actually used locally. We also now have three possible kinds of RPCs. 1. Maximum 2. First 3. Average For any sub-state region, service sector RPCs are the observed value for the state as constrained by the supply/demand pool ratio. When multiple states are combined, we need to specify which observed RPCs we use. For further information, see the RPC discussion in the analysis guide. Note: the different type of “observed RPCs” only affects multi-state models. Maximum RPC The Maximum RPC assumption says that the combined state’s default RPCs will be at least equal to the maximum of the individual state RPCs. First RPC The U.S. Post Office uses two-letter abbreviations that are unique for each state in the United States. The First RPC simply uses the first state from the multi-state list. This arbitrary system was a hold-over from the DOS version of IMPLAN. Average RPC The Average RPC assumption results in RPCs based on an output weighted average for all combined states (the default).

42 Chapter 3: Advanced Model Building

Location Quotient We also have one other method, the Location Quotient. This method calculates the trade flows based on the regional location quotient for each industry. The trade flow coefficient is still limited to the supply/demand pooling ratio; that is you still cannot have more supply than actually available in the region. If you choose location quotient, a screen will be displayed that allows you to select between output, employment or income based location quotients (Figure 3-5). Figure 3-5 Location Quotient Options

Once the type of location quotient is selected, you will be allowed to select the base area. Typically, the base area is the United States as a whole. In the case of county models, the base area might be the state as a whole.

Advanced Institutional Transfers Clicking the Next>> button on the advanced Trade Flows tab advances us to the Institutional Transfers tab (Figure 3-6). Figure 3-6 Advanced Institutional Transfers

Chapter 3: Advanced Model Building 43

Institutional transfers show dollar flows from one institution to another. For example, transfers from households to the federal government (income taxes). To modify the data click on the Edit button. Figure 3-7 shows the institutional transfers data editing window. You should have a thorough knowledge of SAM construction prior to modifying any institutional transfers data elements, as modifications can have an affect the model’s multipliers. Figure 3-7 Editing Institutional Transfers

Each element of the SAM is described by who receives the payment, who pays, what the transfer represents, and the value of the payment. (The complete set of SAM data elements can be found in Appendix C.) To edit highlight the value and type in the desired number. When finished click on the Next>> button to generate the balanced SAMs.

Advanced Multipliers Clicking the Next>> button on the advanced Institutional Transfers tab advances us to the Multipliers tab (Figure 3-7). The Type I, Type II, Type III, and Type SAM are discussed in Chapter 2 of this book. There are two different methods for the Type II available in this screen.

44 Chapter 3: Advanced Model Building 1. SAM Income 2. Specific Disposable Income (%) Type I (inter-industry effects), Type II (income based induced effects), Type III (employment based induced effects), and Type SAM are four types of multipliers which are available in the Model Construction window. However, we now have options for the Type II multipliers as well as making the Type III available. The Type III is a holdover from the DOS version MI91-F and we don’t recommend its use. Figure 3-7 Advanced Multipliers

SAM Income The Type II induced effect works by incorporating labor income and the household consumption (PCE) into the multiplier -i.e., treating households as an endogenous industry (just like any other industry). Deriving a production function for the household industry requires dividing the PCE column (representing resident household consumption), traditionally, by the region’s labor income. The problem with this formulation is that labor income is workplacebased and does not necessarily represent the income that is spent through the PCE column. However, the data provided by the SAM can be used to directly link labor income to the PCE column.

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Specific Disposable Income (%) All disposable labor income is cycled through the household consumption function. However, if we wish to model a region where commuting is significant, we can reduce the amount of labor income re-spent through the PCE vector by changing the specific disposable income value. By default, the disposable income factor is derived from the models SAM. The model methodology is to: 1. Normalize the PCE vector -i.e., divide by the column total so that the sum of the coefficients equals one; 2. Adjust the new labor income to disposable income -i.e., remove benefits, taxes, any commuters, etc., so that what remains is available for spending through the PCE vector; 3. Apply your specified Disposable Income/Labor Income ratio to the PCE coefficients; 4. Adjust PCE coefficients for imports (imported manufacturing, mail order, etc. do not have a local effect). The result is a household production function, representing the new/lost spending as a direct result of the change in income. The model allows us to specify what the disposable income to labor income needs to be for our particular situation.

Type III The Type III multipliers are the direct, indirect, and induced effects where the induced effect is based on population. The relationship is between PCE expenditures per job and the number of jobs. The assumption is that the number of jobs linearly drives PCE expenditures.

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4

IMPACT Analysis An impact analysis involves specifying a series of expenditures and applying them to the region’s multipliers. The process is to: 1. Identify the new expenditures you want to introduce; 2. Identify the IMPLAN sector affected; 3. Enter the transaction value dollars based on the year of the model; 4. Apply those dollars spent within the region to the model. Clicking the Impact button will bring up the main impact screen (see the Analysis Guide for a complete discussion of impact analysis). This chapter discusses Main Screen Events Groups Groups/Events Analysis Projects

Main Screen Clicking the Impact button on the Model Control Center will bring up the main impact screen (Figure 4-1).

48 Chapter 4: Impact Analysis Figure 4-1. Main Impact Analysis Window

The impact analysis window is designed to help you define each transaction (or event in IMPLAN terms).

Events Impacts are described as a series of expenditure events, each with a specific name, sector value (or employment value), year for deflators, and margins. Clicking Add New will place the cursor in the Event Name field (Figure 4-1) and allow you to start entering your event information. An “Event Name” can be any text that has meaning to you. Pressing Enter or Tab will bring you to the next field, the Sector. A drop box displaying the IMPLAN Pro sectoring is available to help with the sector selection (Figure 4-2). Figure 4-2. Choosing a Sector

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By clicking the drop down arrow next to the field, a list box will be displayed with the sector names. You can either scroll down to the desired sector or type the sector number. Typing needs to be done smoothly for the software to be able to understand what you want. You can also select Factors or Institutions here as well. If you want to see the impact of a change in Employee Compensation, select 5001. For a change in household income, select 10001. Clicking the Tab key or pressing Enter moves you to the next field. You can specify either the expenditure value or the direct employment involved (Figure 4-3). These two fields are linked so that specifying one will automatically derive the other based on the output per worker ratio for that industry in the model. Figure 4-3 Value

If you have a series of events and you want to change the value or the employment on all of the transactions, you can click on the word Value or Employment at the top of the column and a Change All option will be displayed (Figure 4-4). Figure 4-4 Change All

Clicking the Tab key or pressing Enter moves you to the Basis field (Figure 4-5). This allows you to select the type of impact. You can do either an Industry impact or a Commodity impact.

50 Chapter 4: Impact Analysis Figure 4-5 Basis

An industry impact gives the entire event amount to the industry you’ve selected. A commodity impact splits the event value to all industries producing that commodity. If you have a series of events and you want to change the basis on all of the transactions, you can click on the word Basis at the top of the column and a Change All option will be displayed (Figure 4-6). Figure 4-6 Change All

Clicking the Tab key or pressing Enter moves you to the Year field. If the expenditures are in historical dollars for a year other than the regional model data, then the year of that expenditure must be specified in order to apply the correct deflator. Again, a drop down box is available to you (Figure 4-7)

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Figure 4-7. Choosing a Deflator Year

If you have a series of events and you want to change the year on all of the transactions, you can click on the word Year at the top of the column and a Change All option will be displayed (Figure 4-8). Figure 4-8 Change All Deflator Years

If the expenditure is for a retail purchase then the purchaser price must be broken out to its component producer prices. You can do this by selecting a margin type from the drop down box list of margins (Figure 4-9). The IMPLAN Pro software will apply the margins to the expenditure value for you.

52 Chapter 4: Impact Analysis Figure 4-9. Choosing a Margin

The choice of margins is important. Different kinds of consumers pay different margins. Government and industry buyers will tend to pay little or no retail margin since they buy direct from the manufacturer. Household consumers buy mostly from retail establishments so they do pay margins. You can modify the default margins by selecting the box with the two dots to the right of the margin field (Figure 4-10). Figure 4-10 Edit Margin Button

There is a Change All feature with margins as well.

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The window shown in Figure 4-11 shows the layout of the margined event: Figure 4-11. Editing Event Margins

In this example, IMPLAN sector 421’s (Sporting Goods) producer value is 41.7% of the purchaser price. The wholesale sector receives 12.9% of the purchaser value. It is possible to modify the margins by changing the numbers in the Value column. The New Value column represents the result of the margin value adjusted by the deflator. Note: If you modify deflators from the impact window it will only modify them for this impact - not the whole model or the original data sets. If you press the Default button, any modified values will be replaced by the default margins shown in the far-left column. Pressing Enter or Tab moves you to the last column, %Local. This was called Local Purchase Coefficients (LPC) in Version 1. This indicates the portion of the direct expenditure that should be applied to the model. If the event is an entirely local activity – the %Local field equals 100%. When you open this screen and select “Model RPC’s”, the %Local field will be populated with the model trade flows. You can then edit the %Local to change the value if you wish. Modifying the local expenditure proportion is particularly important

54 Chapter 4: Impact Analysis for margined items, where a purchase may be made through a local retailer, but the manufactured item itself might be imported. The default is 100%. If you click the field, a drop down box is displayed (Figure 4-12). You can then enter a value, select the 100% or “Get Model RPC”. Figure 4-12 Local Percent Options

There is a Change All feature with the Local Percent Options as well.

Event Defaults For the first event entered into the event fields, the software will preset many of the fields with defaults. The defaults stored in the software are shown in Figure 4-13 below. Figure 4-13 Event Defaults

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Any changes made by you to the defaults will be carried down to the next event record. As long as the impact analysis window remains open the latest user entries are the defaults. Once the window is closed the software reverts to the defaults

Event Option Buttons Figure 4-14 shows the Event Options from the impact main screen. There are three event option buttons. Figure 4-14 Event Options

1. The Add New button places the cursor at the end of the events in the Event Name field, ready to type in the new event record. 2. The Current button will delete the event in which the cursor is or residing. 3. The All Visible button will remove all events from the event window. 4. There is no undo feature here. This is a database and any change happens immediately and is permanent.

Groups Once events are specified you may run the analysis and view the results or Group the events to save them or to generate a more complicated scenario. Figure 4-15 shows the three grouping options within the Impacts main screen window, Create, Delete, Import (Figure 4-1). Figure 4-15 Group Activities in the Event Window

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Creating Groups Once events are specified they can be bundled together into a Group by using the Create option under group options. This group may be saved to the library and used later for any model. Groups are a way to bundle similar events so they may be run together. You can accomplish the same thing with Ungrouped events, but its more difficult to keep track of the events if they are frequently changing. The easiest approach is to create a series of events in the ungrouped events set and then create a group with those events. You can then delete the Ungrouped events and start over on a new group. For example, the expenditures for a day of golfing may be bundled into a “Golf Resort Visitors” group. When performing an analysis, it is a simple matter to run this group and apply a value representing the number of golfing days to derive an impact. Figure 4-16 shows the collection of four events into a group called “Golf Resort Visitors”. These have been entered on a per-visitor basis. Figure 4-16. Groups

The “Golf Resort Visitors” group now appears along with the rest of the groups in the group window. Groups created this way are stored in the current model. A group can have one or many events. To view or modify a group, click the desired group name and the events associated with that group appear in the event window.

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Modifying events (deleting, adding, etc.) in a group is permanent for that model but does not affect groups in the library.

Deleting Groups The Delete button will delete from the model the highlighted group name. It will not delete groups from the library of groups.

Importing Groups It is also possible to import a group from another model or the Library of groups using the Import button. Figure 4-17 shows an import group screen. Figure 4-17. Import Group Screen

The Model button (Figure 4-17) will bring up the standard Windows common dialog box. Selecting a region model will display any groups saved in that model. The Group Library button will show the groups contained in the IMPLAN Pro group library. The advantage of the library is that it will not go away when models are deleted. Note: Library functions do not work with aggregated models. The Institution (i.e., final demands) and Industry tabs will display the model’s institution demand and industry sectors as they exist in

58 Chapter 4: Impact Analysis the current model. The import function will retrieve the institution’s expenditure pattern as a group. Each institutional expenditure pattern forms an event within that group. The sum of these events is 1.0. The new group -e.g., “State and Local Gov Non-ed” shows up in the group list found in the main impact analysis screen (Figure 4-18). Figure 4-18. Import an Institution

The import function will also retrieve the model’s expenditure pattern for any IMPLAN industry (which exists in the model). Importing an expenditure pattern will form a group with the expenditures as events within that group. The new group -e.g., “Miscellaneous livestock” shows up in the group list found in the main impact analysis screen. Figure 4-19 shows the Industries.

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Figure 4-19. Import an Industry

Importing/Exporting Groups It is also possible export groups to either the library or a text file. The library allows you to keep a catalog of frequently used groups. The text file option allows you to create a file of the group transactions that can be imported into a spreadsheet, modified and then imported back into IMPLAN Pro (Figure 4-20). Figure 4-20. Save Group Menu Selection

60 Chapter 4: Impact Analysis The first option is saving to the library. Selecting the Group to Library menu item will open a window (Figure 4-21) which displays all groups created in the current model. Figure 4-21. Export Group to Library Window

To save a group to the library, highlight the group and click on Save. The saved group will now be available for use in any model even if you delete the current model. The second option is saving a group to a text file. By highlighting the desired group, as in figure 4-21, when the Export button is clicked, a file dialog box is displayed (Figure 4-22). Additional information on this is in Appendix I. Figure 4-22 Save Text File

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You can take the default name or give the file a new name, change the directory if desired, and click Export. The file is a commadelimited file with a very specific structure. In order to be able to import this file back into IMPLAN Pro, you must not change the file layout. You can, however, add and subtract rows and change values. (See Appendix G for specific group importing and exporting instructions.)

Library Maintenance Library maintenance involves deleting unwanted groups from the library. This feature is accessible through the Library/Maintenance menu selection off of the main menu bar. The dialog box displayed is very similar to the Save to Library menu except that the highlighted group is deleted from the library instead of saved. Warning: there is no undo, anything deleted, stays deleted.

Groups/Events Analysis Analysis in IMPLAN Pro is the process of applying a set of expenditures. Selecting Analysis from the Impacts window displays the window shown in Figure 4-23 below. Figure 4-23. Analyzing Events

This screen displays the groups and events you can evaluate. The Ungrouped events are those that have not been formally grouped

62 Chapter 4: Impact Analysis together. The list box also displays all groups that have been created in this model. First, select the desired set of events. The Level then needs to be set. The Level will be multiplied against the event expenditure values within the group. This actually is the direct effect that will be multiplied by the model multipliers. IMPLAN Pro assigns a default level of 1.0. The Impact Name must be specified before the impact can be run the example shows “Golf Course Run 1” representing visitors to a golf course. The name given will be the name associated with the impact reports for later viewing or printing. The Impacts List shows previous impact analyses associated with this model. Previous impacts can be deleted by clicking on an item in the list and clicking on the Delete button. Clicking the Run Impact button will start the analysis. A progress bar will track the analysis. When the analysis is complete, IMPLAN will ask if you want to display the results now. You can either select Yes or No.

Results After running the analysis you can either select Yes and view the results from the analysis screen or close the analysis window and select the Results button from the impact screen. Either way will allow you to view the direct, indirect and induced (Type SAM induced in this example) effects of the impact. The Results button appears as shown in Figure 4-24 and is found as part of the main impact analysis menu (Figure 4-1). Figure 4-24. View Results

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The Results button displays a blank version of Figure 4-25. Figure 4-25. View Impacts Results

Selecting one of the impact analyses names from the list in the top left corner will display the results for the selected analysis. The tree view in the bottom left corner shows the different kind of analysis results available. Figure 4-25 shows Output, Value-Added, and Employment in bold face. When there is a plus or minus sign in front of the topic, there are additional results available that can be displayed or hidden. Within Value-Added are additional options for Labor Income, Indirect Business Tax, and Other Property Income. By clicking the plus sign in front of Labor Income, Employee Compensation, and Proprietor Income can be displayed.

Projects It is possible to run several groups at the same time and display results for the groups added together. You can do this by creating a project. The Projects tab on the Impact Analysis screen displays the Projects window (Figure 4-26). The Projects tab is enabled when two or more groups are in the model. To create a project:

64 Chapter 4: Impact Analysis 1. Press the Add button enter in a project name or use the default project name in the dialog box; 2. Select the desired groups by highlighting the group and clicking the << button or double click on group name; 3. Click Analyze. Figure 4-26. Projects

Clicking the Analyze button brings up the same analysis screen we saw earlier for events and groups (Figure 4-20); however, since we have created one or more projects, the Projects tab is no longer grayed out. Selecting the Projects tab displays the screen shown in Figure 4-27.

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Figure 4-27. Projects Impacts

Note: it is necessary to have at least two groups in order to access the Projects tab. Choose the desired projects from the list of projects created in this model. The chosen project will then display the associated groups belonging to that project. It is possible to set both the project level as well as group level. You can change the group level by selecting the group from the list; the group level will be displayed. Click on the Run Impact button to start the analysis. Note: the group events will be multiplied by the group level which, in turn, will again be multiplied by the project level before being applied to the multipliers.

View Project Results After running the analysis, IMPLAN will ask you if you want to view the results. If Yes it will bring you right to the results screen. If No, you will return to the Impact Main Screen. You can click on Results from there to view the impact results at a later time.

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5

Reports To be useful, the results of any model construction and analysis need to be printed or transferred to other software to be documented, further formatted, graphed, etc. This process is explored in this chapter: Report Creation Print Options Study Area Reports Social Accounts Reports SAM Reports Transactions Reports Ind x Ind Reports Multiplier Reports Impact Reports

Creating To generate reports, select Model and then Print/Export Reports off the main menu bar (Figure 5-1) or click on the Reports button on the model control panel. Figure 5-1. Reports Menu Selection

The IMPLAN Pro reports section allows you to print or preview reports, or export data to other file formats. Figure 5.1a shows which

68 Chapter 5: Reports formats IMPLAN Pro supports. Remember that you have access to your actual model file through MS Access 2000 or higher. Figure 5-1a Export Options

The reports are organized under seven tabs: 1. Study Area (Figure 5-2) 2. Social Accounts (Figure 5-3) 3. SAM (Figure 5-4) 4. Structural Matrix (Figure 5-5) 5. Industry x Industry (Figure 5-6) 6. Multipliers (Figure 5-7) 7. Impacts (Figure 5-8) A sample of all the printed reports can be found in Appendix F Sample Reports. Note: the sample reports in Appendix F are based on an aggregated model. This is for display purposes only. We recommend that you do impact analysis on unaggregated models as much as possible.

Print Options To Printer The selected report is generated and sent to the default Windows printer. You may also choose to print more than one copy of each report by typing in a number or clicking on the up/down arrows on

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the scroll box. You may select more than one report at a time with this option.

Print Preview The selected report is generated and displayed on your the computer screen. It is possible to print the report from the preview screen. Print preview allows selection of one report at a time.

Print to File

IMPLAN Professional allows you to export data and reports to several different file formats. The available formats are text, Lotus 12-3, tab delimited, and Word for Windows. Print to File allows selection of only one report at a time.

Print Setup Print Setup displays the standard Windows printer setup dialog box. You are allowed to select which printer to use as well as modify printer options. See the Windows manual or use Windows Help if you have any questions or problems with this routine.

Zero Suppression Under most of the report tabs is an option that allows suppression of those sectors or commodities for which no data exists. For small regions this can substantially reduce the size of the report. However, there are times you may wish to allow display of non-existent industries in order to maintain the proper spacing, especially when comparing results for one region to those for another. When Zero Suppression is grayed out then it is not applicable for the chosen report option.

Aggregate Sector aggregation is available for both Study Area reports and Impact reports. Aggregation allows you to display the reports in fewer than 509 sectors.

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Study Area Reports These reports show the various aspects of the model data as found in the original IMPLAN data files, or as already modified by you. Figure 5.2 Study Area Reports

You may choose any one of nine report options.

1. Output, VA, Employment Report This report displays the regional industry data for output valueadded (employee compensation, proprietors income, other property income, and indirect business tax). The data elements are the combined values from the original data files and are in millions of dollars.

2. Institution Commodity Demand Institution demand (final demand) of commodities from the original combined data files is shown in this report. The demand values are based on commodity purchases, are “gross” values (includes imports), and are reported in millions of dollars. Only one value for households is displayed. Also, only one value for federal and state and local government is displayed as well. Domestic exports are determined during the model creation process and are not included in this table.

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3. Household Commodity Demand This report displays household purchases of commodities for all household categories. The sum of the households in this report will equal total household commodity purchases displayed in the Summary Institution Demand Report.

4. Government Commodity Demand This report displays government purchases of commodities for all government categories. The sum of the governments in this report will equal total government commodity purchases displayed in the Summary Institution Demand Report.

5. Institution Commodity Sales Institution commodity sales are displayed in this report. This data is from the original study area data.

6. General Model Information Report This report gives pertinent statistics on the region. It includes the individual counties/states FIPs codes, population and area. It also shows the average household income and number of households in each of nine household income categories. Note: the average household income is higher than the range for the category because of significant underreporting of income in the consumer expenditure survey. When controlled to US NIPA accounts for household income, there is an upward correction of approximately 30%.

7. IMPLAN to SIC Bridge Report This report shows the conversion of IMPLAN sectoring to the Standard Industrial Classification (SIC) codes. Appendix F (sample reports) only shows the first page of this report. The complete IMPLAN sector scheme can be found in Appendix A.

8. Type Codes Report The type codes report shows the database classification codes used by the software. This is useful for those who use the model’s data base file directly with Microsoft AccessTM. The complete report is shown in Appendix D.

9. Aggregation Template This report displays the aggregation scheme that you have either created for this model or imported from the library. The aggregation

72 Chapter 5: Reports scheme must be physically in the model to be able to generate this report.

Social Accounts Reports The process of creating a set of economic accounts applies study area data to the national absorption and byproducts matrices. The result is a set of balanced input-output accounts complete with imports and exports. Figure 5.3 Social Accounts Reports

We have 11 possible report options to select in Social Accounts.

1. Industry Balance Sheet Report The industry balance sheet describes all information available in the social accounts related to a specific industry. You must check this box as well as choose an industry on which to create the report.

2. Commodity Balance Sheet Report The commodity balance sheet describes all information available in the social accounts related to a specific commodity. You must check this box as well as choose a commodity on which to create the report.

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3. Commodity Summary The commodity summary report displays commodity-based data derived during the process of the model’s social accounts. Definitions of the column headers may be found in the glossary and their derivation is described in the Analysis Guide section of the software manual.

4. Commodity Trade Report Domestic and foreign imports and exports, in millions of dollars, plus related ratios by commodity are shown in this report.

5. Institution Local Commodity Demand This report shows institution demand for commodities from the local study area. Only totals for households and government are displayed.

6. Household Local Commodity Demand This report shows local household demand for commodities for all income categories.

7. Government Local Commodity Demand This report shows local government commodity demand for all levels of government.

8. Industry Summary Report Industry-based data on output, outlay, value-added and imports in millions of dollars, as well as technical ratios derived during social accounts, are shown in this report. Definitions of the column headers may be found in the glossary; their derivation is described in the Analysis Guide.

9. Industries and Commodities in Model This report shows which industries and commodities exist in this model. A sector with no data is considered to not exist.

10. Industry Import Matrix This is a text file report that provides a matrix of total imports, competitive and non-competitive imports to industries.

11. Institution Import Matrix This is a text file report that provides a matrix of total imports, competitive and non-competitive imports to institutions.

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Social Accounting Matrix (SAM) Reports Social accounting matrix, or SAM reports, includes all commodity flows, not only purchases and production of sales of commodities, but transfer payments to and from institutions. Like all SAMs, the sum of the rows are equal to the sum of the columns. There are five reports, four of which can only be printed out as text files (SAM and SAM Detail). Figure 5.4 SAM Reports

1. Aggregate SAM (Aggregated Industries, Aggregated Rows) This report displays the regional social accounting matrix in a highly aggregated form. It fits on a single sheet of legal sized paper. Your printer must be set up to print to legal sized paper to generate this report.

2. Ind x Com SAM (Aggregated Industries, Row Detail) This is a text file report. This industry-by-commodity SAM includes aggregated industries and commodities and full row detail for the inter-institutional transfers. This report can easily be imported into Microsoft Excel, where pivot table will create a full matrix. Check the Excel manual or use Excel Help to learn about pivot table.

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3. Ind x Com SAM (Industry Detail, Aggregated Rows) This is a text file report. This industry-by-commodity SAM includes full detail for industries and commodities and aggregated rows for the inter-institutional transfers.

4. Ind x Com SAM (Industry Detail, Row Detail) This is a text file report. This industry-by-commodity SAM includes full detail for industries and commodities and full row detail for the inter-institutional transfers.

5. 26 File CGE Format This SAM contains full detail, including imports and exports. This report generates 26 text files (of the form *1x1.dat) which are inputs into the GAMSTM software for computable general equilibrium models (CGEs). The reports index does not contain a sample of these report files.

Structural Matrix Reports These reports export all information from the model’s structural matrices to text files. Figure 5.5 Transactions Reports

76 Chapter 5: Reports Definitions of each of these matrices can be found in the glossary, and derivation is described in the Analysis Guide section of the software manual.

Industry x Industry Reports From the commodity-by-industry formulation of the social accounts we generate industry-by-industry accounts in preparation for creating multipliers. This tab allows you to generate industry-based reports similar to the commodity-based reports discussed in the previous section (Figure 5-6). Figure 5.6 Industry by Industry Reports

There are ten reports available in this category:

1. Institution Industry Demand This report is the result of converting the institution demand for commodities to an industry basis.

2. Household Industry Demand This report shows household demand on industries for all household income categories.

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3. Government Industry Demand This report shows household demand on industries for all government categories.

4. Industry Output/Outlay Summary For each industry, total value of production (output) must equal total expenditures (outlay). This report summarizes the industry output and industry outlay reconciliation.

5. Aggregate IxI SAM (Aggregated Industries, Aggregated Rows) This report displays the regional social accounting matrix on an industry-by-industry basis in a highly aggregated form. It fits on a single sheet of legal sized paper. In order to generate this report, your printer must be set up to print to legal sized paper.

6. Regional Ind x Ind Direct Coefficients Report This is a text file report and is the industry-by-industry analog of the absorption matrix. For every dollar of industry outlay, the amount purchased from each local industry is shown.

7. Regional Ind x Ind Transactions Report This is a text file report and is the industry-by-industry analog of the use matrix. It shows, in millions of dollars, the amount purchased from local industries.

8. Ind x Ind SAM (Aggregated Industries, Row Detail) This is a text file report. This industry-by-industry SAM includes aggregated industries and full row detail for the inter-institutional transfers. This report can easily be imported into Microsoft Excel where pivot table will create a full matrix. Check the Excel manual or use Excel Help to learn about pivot table.

9. Ind x Ind SAM (Industry Detail, Aggregated Rows) This is a text file report. This industry-by-industry SAM includes full detail for industries and aggregated rows for the inter-institutional transfers.

10. Ind x Ind SAM (Industry Detail, Row Detail) This is a text file report. This industry-by-industry SAM includes full detail for industries and full row detail for the inter-institutional transfers.

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Multiplier Reports A multiplier report can be generated for each of the industry variables: Output, Employment, Employee compensation, Proprietor Income, Indirect Business Taxes, and Other Property Type Income. The Value-Added report represents the sum of employee compensation, proprietor income, indirect business taxes and other property type income. The Labor Income report represents the sum of employee compensation and proprietor income. Figure 5.7 Multiplier Reports

The two text file reports can only be saved to a text file. They are both matrices of multipliers. Each row of the text file contains the industry row number, industry column number and the multiplier value. A Type I multiplier is direct-plus-indirect (inter-industry) output effects. The Induced Multiplier is induced (household) output effects only. When added to the Type I effects, the complete Type II or Type III multiplier matrix can be derived.

Multiplier Report Column Each of the multiplier report options (top portion) has the following column headers in common:

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Direct Effects Represents the response (e.g. change in employment) for a given industry per million dollars of final demand for that same industry. Indirect Effects Represents the response by all local industries caused by the iteration of industries purchasing from industries per million dollars of final demand for a given industry. Induced Effects Represents the response by all local industries caused by the expenditures of new household income generated by the direct and indirect effects per million dollars of final demand for a given industry. Induced effects may also reflect government or investment if these are selected by with the Type SAM multiplier. Total Total multiplier effect is the sum of the direct, indirect and induced effects. It represents the entire response per million dollars of final demand. Type I Multiplier The Type I multiplier is calculated by dividing the direct plus indirect effects by the direct effect. Type SAM (or II or III) Multiplier Dividing the direct-plus-indirect plus induced effects by the direct effect, calculate the Type SAM (or II or III) multiplier.

Impact Reports An impact report can be generated for each of the industry indicators: Output, Employment, Employee compensation, Proprietor Income, Indirect Business Taxes, and Other Property Type Income. The Value-Added report option represents the sum of employee compensation, proprietor income, indirect business taxes and other property type income impacts. The Labor Income report represents the sum of employee compensation and proprietor income impacts.

80 Chapter 5: Reports Figure 5-8 Impacts Reports

Before selecting any of the report options, it is necessary to select an impact results. Simply highlight the desired results (Golf Visitors in Figure 5-8 has been selected).

Deflator Button The input-output model values are all in the year of the original data used to generate the model. Likewise, all reports would be in the same year, unless inflated to a more current year. The sample reports have all been inflated to 1996 values by clicking on the deflator button and selecting a year from the drop box that appears.

Aggregation It is possible to apply an aggregation template to the impact reports as well. The aggregation template simply combines impacts for the sectors as described by the template. A template can be created from this selection or can be retrieved from the library. (See “Aggregation” in Chapter 2 if you have questions.) If the model has been aggregated the impact reports will not allow you to aggregate again.

Impact Report Table Headers Each of the impact report options have the following column headers in common:

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Direct Effects Represents the impacts (e.g. change in employment) for the expenditures and/or production values specified as direct final demand changes. Indirect Effects Represents the impacts (e.g. change in employment) caused by the iteration of industries purchasing from industries resulting from direct final demand changes. Induced Effects Represents the impacts (e.g. change in employment) on all local industries caused by the expenditures of new household income generated by the direct and indirect effects of direct final demand changes. Induced effects may also reflect government or investment if these are selected when the Type SAM multiplier was specified. Total The total impact is the sum of the direct, indirect and induced effects.

Chapter 6: Other Features

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6

Other Features Other features included in IMPLAN Pro Version 2 include: Help System Internet Connectivity Converting Models Compacting Models Structural Matrices Version Memo Field Calculator Tips and Hints

Help System IMPLAN Pro Version 2 has complete Internet updating features as well as direct Internet access to the knowledge base and other webbased help. To access these features, select Help from the main menu (Figure 61). Figure 6-1 Help Features

84 Chapter 6: Other Features

IMPLAN Pro Help Topics This provides access to the integrated help system. You can search for key words to get definitions or assistance in performing software functions. The Search on Help takes you right to the search index. Using help provides you with assistance using Windows help systems. Default Toolbar resets the IMPLAN Pro tool bar to its original appearance. About IMPLAN Professional provides information about your software version (Figure 6-2). You can also access Microsoft’s System Analysis. This provides information about your computer’s set-up. Figure 6-2 Help About

Internet Connectivity IMPLAN Pro Version 2 incorporates the latest in Internet access functionality. You can easily update your software with the latest service patch, check for structural matrix updates, or link to our webbased user assistance. Figure 6-3 shows the different Internet options. You must provide the Internet connection. Once you are connected, these features will be enabled.

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Figure 6-3 Internet Options

The first item is Start e-Update. This initiates the software update process and displays Figure 6-4. You may also start e-Update from the main tool bar. Figure 6-4 e-Update

Clicking Next initiates the connection and checks your installation with the latest files on our web site. Update files will be displayed and tell you if you have the latest files installed on your computer (Figure 6-5).

86 Chapter 6: Other Features Figure 6-5 e-Update Display

The other items in the menu from Figure 6-3 are IMPLAN Tech Support Page, On-Line Support (KB), SIC Code Search, Send Feedback to MIG. IMPLAN Tech Support Page takes you directly to the IMPLAN Pro tech support page where you can check the latest information and downloads. On-Line Support (KB) takes you directly to the IMPLAN Pro Knowledge Base where you can search for support topics. SIC Code Search takes you to a searchable database of SIC codes. Lastly, you can e-mail MIG directly from the Help menu.

Converting Models Models built with IMPLAN Pro Version 1 will need to be converted before you can use them in IMPLAN Pro Version 2. This process updates your Version 1 model with additional tables and information so that it will be compatible with Version 2. Select Tools from the main menu (Figure 6-6) and select Convert Model. Figure 6-6 Converting a Model

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This feature will also be enabled if you try to open a Version 1 model with Version 2.

Compacting Models Each regional model is stored in a Microsoft Access database. While this makes it convenient to manipulate, deleting a record or a temporary table in a database does not really remove the record or table; rather it is marked as being deleted. To recover the space, the database must be compacted. To compact your model, select Tools from the main menu bar (Figure 6-7) and select Compact Model. Figure 6-7. Compact Model

A dialog box will be displayed notifying you that compacting may take several minutes, but it will save hard disk space and make the model more efficient. Click Yes to start the compacting process.

Structural Matrices Version The data used in each IMPLAN Pro regional model has a unique set of national structural matrices. The national structural matrices provide the model the initial national absorption and byproducts matrices, sector names, SAM structure, as well as the default deflators, margins and regional purchase coefficients. To check which Structural Matrices Versions are installed on your computer, select Files from the main menu and then Structural Matrices Installed (Figure 6-8).

88 Chapter 6: Other Features Figure 6-8 Structural Matrices Installed

Memo Field Each IMPLAN Pro model has an associated memo field that allows you to make specific notes about that model. To access the memo field, select Memo from the Model menu item from the main menu bar (Figure 6-9). There is a limit of 255 characters for memo field notes. Figure 6-9 Memo Field

If you have more than one model open, then the memo field will refer to the “current” model; -i.e, the active model that will be the window on top.

Calculator If you have chosen to install the calculator when you installed your Windows software, then IMPLAN Pro will place a calculator button onto the main menu’s icon bar (Figure 6-10). Clicking the Calculator icon will display the Windows calculator.

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It is easy to copy (Ctrl-Insert) calculator results and paste (ShftInsert) results into an IMPLAN Pro data field. Figure 6-10 Calculator Icon

Changing Default Directories You can change the default directories for storing models, saving output, or reading data. Select Options from the Tools menu (Figure 6-11). Figure 6-11 Options

Highlight the option you want and click the Modify button (Figure 612). You need to then Browse to the directory you want. Figure 6-12 Change Directories

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Customizing the Tool Bar You can customize your menu and tool bars. Click Tools, Customize will display the customization screen.

Tips and Hints This section contains miscellaneous information and tips.

Multiple Models

IMPLAN Prosoftware is like any Windows program in that you can have it running concurrently with other Windows software. Several different models (as many as memory will allow) can be opened simultaneously for comparison purposes. They will remain open until each model is closed or you exit IMPLAN Pro.

Current Model If you have multiple models open, the current or active model is the one most recently used. As such, it will model with focus. The current model name bar will also be colored, while the other windows will be grayed out. Pull-down menu items apply only to the current model.

Choosing a Sector

IMPLAN Pro frequently requires sector selection (industry or commodity number). You can do this by scrolling to the item using the mouse. It is also possible to type the value to jump to the sector. The typing of the sector number is timed. Pausing while typing will “reset” the sector number. For example, if you pause after the first number while typing in “123” the software will jump to sector “23”.

Sorting Grids Any grid can be sorted by clicking the header of the column. This allows you to do things such as examine the sector that has the largest number of employee’s etc.

Tool Bars There is a tool bar at the bottom of the IMPLAN screen. This allows you to control the entire model without using the model control center.

BOOK 2: ANALYSIS GUIDE

Chapter 7: Introduction 93

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INTRODUCTION This book is a guide for studying economic issues, defining inputoutput and impact analysis terms and introducing the IMPLAN modeling process. While many of the manual’s elements are universal, it is geared to MIG’s IMPLAN modeling system.

How Book 2 is Organized Chapters 8-11 includes information for on the modeling process. Chapters 12-15 detail the calculations used in creating the predictive model, and Chapter 16 brings us back to analysis. Chapter 8: “An Overview of Input -Output & Impact Analysis” briefly explains input-output accounting, multipliers and some impact analysis terms. Chapter 9: “Project Definition” provides an economic analysis framework. Chapter 10: “Study Area Considerations” discusses study areas and regional linkages. Chapter 11: “Database Elements” defines the regional database components. Chapter 12: “Regional Accounts Construction” discusses the construction of regional economic accounts using a 3x3 example. Chapter 13: “Inter-institutional Transfers” introduces the social accounting framework and looks at a regional SAM example. Chapter 14: “Industry by Industry Accounts” creates the industry-byindustry matrix and the assumptions inherent in the calculations. Chapter 15: “Predictive Model Derivation” derives and discusses the different types of multipliers. Chapter 16: “Impact Analysis” provides an impact analysis example you can follow using IMPLAN software and discusses potential sources of impact estimation errors. Chapter 17: “Case Studies” consists of several case studies illustrating different analysis techniques.

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An Overview of Input-Output and Impact Analysis This section should be considered an introduction to input-output (I/O) analysis only and not an exhaustive discussion. There are a number of good introductory texts available. This chapter discusses: Defining Input-Output Analysis T-Accounts Industry Versus Commodity Input-Output Accounting Trade Flow Assumptions Multipliers Key Assumptions Defining Impact Analysis

Defining Input-Output Analysis Francois Quesnay first described inter-industry relationships in 1758. Wassily Leontief developed the concept of multipliers from inputoutput tables, receiving a Nobel Prize in 1973 for his work. Input-output analysis is a means of examining relationships within an economy, both between businesses and between businesses and final consumers. It captures all monetary market transactions for consumption in a given time period. The resulting mathematical formulae allow examination of the effects of a change in one or several economic activities on an entire economy (impact analysis). A primary input-output study is based on data collected directly from industries. An example is the United States’ Benchmark Study of Input-Output accounts (the data is actually based on economic censes collected directly from firms). Other countries have done primary national level input-output studies as well. Primary state or

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Chapter 8: Overview local level input-output studies are not common due to the high cost of data collection. Secondary input-output studies rely on data collected from other sources to construct the accounts. The inter-industry transaction information usually comes from some other primary study. IMPLAN is an example of a secondary input-output modeling system. There are two phases in input/output analysis: 1. Descriptive modeling 2. Predictive modeling

Description Model A Descriptive Model includes information about local economic interactions known as regional economic accounts. These tables describe a local economy in terms of the flow of dollars from purchasers to producers within the region. Trade Flows are also part of the descriptive model. They describe the movement of goods and services within a region and the outside world (regional imports and exports). The initial IMPLAN data details all purchases, including imported goods and services. When regional economic accounts are created, imports to the region are removed from the initial data, allowing examination of local inter-industry transactions and final purchases. By adding Social Accounting data, an analyst can examine nonindustrial transactions, such as payment of taxes by businesses and households. Social accounting data includes tax collection by governments and payments to households and businesses. Input-output accounting describes the flow of commodities from producers to intermediate and final consumers. Social Accounting Matrices (SAMs) show the flow of money between institutions. Both are part of the descriptive model.

Predictive Model The regional economic accounts are used to construct local level multipliers. Multipliers describe the response of the economy to a stimulus (a change in demand or production). The multipliers represent the Predictive Model. Purchases for final use (final demand) drive an input-output model. Industries producing goods and services for consumption purchase goods and services from other producers. These other producers, in

Chapter 8: Overview 97 turn, purchase goods and services. These indirect purchases (or indirect effects) continue until leakages from the region (imports, wages, profits, etc) stop the cycle. The indirect effects and the effects of increased household spending (induced effects) can be mathematically derived as sets of multipliers. The derivation is called the Leontief inverse. The resulting sets of multipliers describe the change of output for each industry caused by a one dollar change in final demand for any given industry.

T-Accounts The input-output analysis framework is similar to a financial accounting framework that tracks purchases of and expenditures on goods and services in dollars. Input-output accounting traces the flow of dollars between businesses and between businesses and final consumers. An input-output accounting framework can be illustrated using classic financial accounting T-Accounts which include receipts (income) and expenditures (expenses) on each side of a “T” (Figure 81). Figure 8-1. Input-Output “T” accounts

Receipts Sales to Industries Sales to Institutions Exports

Expenditures Purchases of goods and services Local Imported Investment Payroll Taxes Profits Distributed Retained

On the left hand side are receipts. This includes income from sales of goods and services to industries and consumers. Institutions are consumers. An institution might be a household, a school, a government agency, investment or export.

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Chapter 8: Overview On the right hand side of the T account are expenditures. Industries make expenditures on goods and services to produce other goods and services. Profits balance expenditures with receipts. Like any double entry bookkeeping system, the receipts must balance the expenditures. This is a fundamental foundation of input/output accounting. Across the entire economy, businesses and consumers receive income and make expenditures. In a balanced set of accounts, all receipts equal all expenditures.

Industry versus Commodity The terms industry and commodity are often confusing to a beginning analyst. The collection of businesses purchasing goods and services are called industries. The goods and services themselves are called commodities. Industries consist of businesses producing goods and services. Commodities are the goods and services. Confusion arises because industries and commodities share the same names. Industries derive their names from the primary commodity they produce. The primary commodity is determined by value. Industries can produce more than one commodity. Commodities other than primary commodities are called secondary commodities or byproducts. Most input-output data is collected on a commodity-by-industry basis. The commodity basis makes it easier to collect transactions data by asking what a company buys, instead of where the commodity was bought. IMPLAN uses a commodity/industry economic account framework. The IMPLAN accounts closely follow the accounting conventions used in the "Input-Output Study of the U.S. Economy" by the Bureau of Economic Analysis and the rectangular format recommended by the United Nations.

Input-Output Accounting Input-output accounting replaces the T-Accounts with several tables showing income and expenditures as the flow of goods and services in dollars:

Chapter 8: Overview 99 The Use Table details the dollar value of goods and services purchased by each industry to use in their production process. A column is a single industry, the rows are the commodities and the units are dollars. The Value Added Table details payments made by each industry to workers, taxes, interest, profits, and other income; one column for each industry. The Make Table gives the value of each commodity or service produced by each industry. It is possible for a single industry to produce more than one category of goods and services. In this table, a row is an industry, a column is a commodity, and the units are dollars. The Final Demand Table consists of purchases of goods and services for final consumption. Each row is a commodity; the columns are the final demand sectors and the units are dollars. Three other tables are standard input-output social accounts: The Absorption Table is a coefficient form of the Use table derived by dividing each element of the Use table by the respective industry’s total dollar output. An industry will use a number of commodities to produce its products. The Absorption table shows the proportions of each commodity it uses. Each column is an industry’s production function. A production function shows the proportions of commodities used to produce one dollar of output. The Byproducts Table is a coefficient form of the Make table derived by dividing each element by the Make table row (industry) totals. Each industry can produce more than one commodity. The Byproducts table shows what percentage of an industry’s total output each commodity represents. The Market Shares Table is another coefficient form of the Make table derived by dividing each Make element by the Make column (commodity) total. Since some industries produce more than one commodity, several different industries can be producing the same commodity. The Market Shares table shows what percentage of the total production of a commodity is produced by each industry.

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Trade Flow Assumptions Trade flow assumptions are part of the input-output descriptive model from which multipliers are derived. IMPLAN Pro allows you to choose which assumption it will use to estimate regional trade flows. Trade Flows describe the movement of goods and services between a region and the outside world (regional imports and exports). There are several ways of estimating how much of a commodity’s production will be used to supply local demand and consequently how much will be exported from the region: 1. Regional Purchase Coefficients (RPCs) 2. Supply/Demand Pooling 3. Location Quotient (LQ)

1. Regional Purchase Coefficient (RPC) The RPC represents the proportion of local demand purchased from local producers. For example, an RPC of 0.25 for a given commodity means that for each $1 of local need, 25% will be purchased from local producers. This method is based on the characteristics of the region and describes the actual trade flows for the region mathematically. IMPLAN Pro software generates RPCs automatically with a set of econometrically based set of equations. There is a different equation for each commodity with variables filled by study area data. The RPCs are limited by the supply/demand pooling ratio. By default, all industries/institutions are treated equally -i.e., each will take an equal proportion of its needs from local sources based on that RPC. The IMPLAN Pro software allows you to edit a commodity RPC (applied equally to all consumers of the commodity), or you may give specific RPC values to specific users of a given commodity.

2. Supply/Demand Pooling Supply/Demand Pooling assumes that local demand will buy as much locally as possible; all local need that can possibly be met by local producers will be. Since this minimizes imports, it will maximize local economic activity and the resulting multiplier. The percent of local usage is based on physical capacity for the region. The total commodity supply is divided by the demand (Chapter 4). If the ratio is .8, then 80% of local needs will be met by local demand. If

Chapter 8: Overview101 supply is greater than demand, 100% of that demand will be met by local production and the remainder is exported. Note: the original IMPLAN software (based on the Univac 1000 computer) used supply/demand pooling to calculate imports and exports.

3. Location Quotient - LQ Location Quotients are based on commodity output. The location quotient equation is a fixed equation, comparing the ratios of local production to national production ratios. This implies that the base region is self-sufficient. If commodity production for a region approaches the similar proportion as the base region, the RPC approaches 1. The equation is: Lqi = (Regioni / Regionsum) / (USi / USsum) where: Regioni is the region’s production of commodity I, Regionsum is the region’s total production of all commodities USi is the U.S.’s production of commodity I, and USsum is the U.S.’s total production of all commodities. The LQ for a commodity is constrained to be less than or equal to 1.

Multipliers Final consumption (or final demand) drives input-output models. Industries respond to meet demands directly or indirectly (by supplying goods and services to industries responding directly). Each industry that produces goods and services generates demands for other goods and services and so on, round by round. Multipliers describe these iterations. There are three different multipliers developed for predictive modeling: the Type I, the Type II, and the Type SAM. Step-by-step descriptions of multiplier calculations are given later. Briefly: we start with the Transactions table and derive a coefficient matrix by dividing each industry column element by the column total. This coefficient matrix is also known as the A Matrix. The columns of the A Matrix are production functions. A production function shows where an industry spends, and in what proportions, to generate each dollar of output.

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Chapter 8: Overview Through algebraic manipulation of the A Matrix, we derive the multipliers. The resulting equation is the predictive model: X = (I - A)-1 * Y where: X = Total industry output I = Identity matrix A = A Matrix Y = Final Demand. This can also be interpreted as: ∆X = (I - A)-1 * ∆Y or Change in Total Industry Output = (I - A)-1 * Change in Final Demand. The predictive model shows how output will change with a given change in final demand. The (I - A) inverse is the matrix of multipliers also known as the Leontief inverse. Multipliers break the effects of stimuli on economic activity down into three components. 1. Direct effects are the changes in the industries to which a final demand change was made. 2. Indirect effects are the changes in inter-industry purchases as they respond to the new demands of the directly affected industries. 3. Induced effects typically reflect changes in spending from households as income increases or decreases due to the changes in production. The Type I multiplier measures the direct and indirect effects of a change in economic activity. It captures the inter-industry effects only, i.e. industries buying from local industries. A Type II multiplier captures direct and indirect effects. In addition to the inter-industry effects, the Type II also takes into account the income and expenditures of households. The household income and the household expenditures are treated as industries. This internalizes the household sector, including the induced or household spending, effects.

Chapter 8: Overview103 The Type SAM multiplier uses all information about the institutions selected to be included in the predictive model. If only households are included, all information for industries, factors and households are included.

Key Assumptions Input-output modeling is based on several assumptions: Constant Returns to Scale No Supply Constraints Fixed Commodity Input Structure Homogenous Sector Output Industry Technology Assumption The first assumption is that the production functions (an industry’s list of expenditures) are assumed to have constant returns to scale. This means the production functions are considered linear; if additional output is required, all inputs increase proportionately. No supply constraints means supplies are unlimited. An industry has unlimited access to raw materials and its output is limited only by the demand for its products. A fixed commodity input structure implies that price changes do not cause a firm to buy substitute goods. This structure assumes that changes in the economy will affect the industry’s output but not the mix of commodities and services it requires to make its products. The fourth assumption is that there is homogeneous sector output. In other words: the proportions of all the commodities produced by that industry remain the same, regardless of total output. An industry won’t increase the output of one product without proportionately increasing the output of all its other products. The industry technology assumption comes into play when data is collected on an industry-by-commodity basis and then converted to industry-by-industry matrices. It assumes that an industry uses the same technology to produce all its products. In other words, an industry has a primary or main product and all other products are byproducts of the primary product.

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Impact Analysis: A Definition Economic impact analysis involves applying a final demand change to a predictive economic input-output model, and then analyzing the resulting changes in the economy. A concise definition of impact analysis is: an assessment of change in overall economic activity as a result of some change in one or several economic activities. In practice, economic impact analysis can mean many different things. It might measure the impacts of a new factory moving into an area. It might involve estimating the local impacts of a professional football team moving into an area or the effects of tourist spending. Governments use impact analysis for policy decisions and planning. Researchers use impact analysis to study relationships of different elements in an economy. An impact analysis begins by converting a topic of concern (or project) to a set of economic issues and actors (those involved with the impact). For example, our project might be the preservation of an endangered species. This might translate to the economic issues: withdrawal of natural resources from economic development, encouragement of recreational and educational uses of the land, and the development of an administrative and research structure to preserve and enhance the species. Once the issues have been identified, the actors involved can be identified and their actions converted to a set of expenditures. These expenditures are the initial changes that stimulate further economic activity. The actions and the economic activity they stimulate are the impact. As we prepare to run our initial changes through the predictive model, we will need to know whether the expenditures are made in purchaser or producer prices and the year(s) of the expenditures. Producer prices are those paid at the factory door. This is the money an industry receives for its output. Input-output models such as IMPLAN are concerned with the effects on industries and values are in producer prices. Purchaser prices are those paid at the retail level. A purchaser price actually includes a mix of producer elements. For instance; the price of a roll of film from a retail outlet includes the retail markup,

Chapter 8: Overview105 wholesale markup, transportation costs from the producer to the retailer, and the price at the factory door. If an impact analysis involves purchaser prices, the values need to be subdivided to work with the producer-priced input-output model. This is done using margins. Margins represent the difference between producer and purchaser prices. Margining assigns direct expenditures to the correct I/O sector multipliers. It splits a purchaser price into the appropriate producer values, each value impacting a specific industry. If the expenditure dollars are for a year different than the model’s data, a deflator will need to be applied. Deflators account for the changes in actual value of the dollar over the years. Price changes need to be accounted for otherwise the impacts will be estimated incorrectly. Although IMPLAN Pro provides a framework to conduct an analysis of economic impacts, each stage of an analysis should be carefully scrutinized to make sure it is logical. Procedures and assumptions need to be validated. The IMPLAN software makes it simple to step back and look at results.

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Project Definition This chapter begins the process of defining economic impact analysis using IMPLAN Pro. We will consider the decisions going into the analysis, and discuss key concepts, the margins, deflators, and local expenditures. Defining a Project Margins Deflators Local Expenditures Project Definition Example

Defining a Project In order to decide what to include in your analysis, you must thoroughly understand the issues you wish answered. Sometimes a project will involve several economic issues, each with a set of actors and actions. A project definition should include: Objectives Impact location Local expenditures versus imports Activity time-frame Institutions affected (government, households, investment) Industries or commodities affected Later, as we prepare to run our impacts through the predictive model, we will need to know: Dollar amounts of the final demand changes Whether the expenditures are made in purchaser or producer prices Year(s) of the expenditures

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Chapter 9: Project Definition What are the Project Objectives? To frame the questions, it is helpful to know what kinds of answers are needed. You might want to know the number of employees a new plant will add to the economy and the effects of their household spending. In this case, your questions will revolve around the new production, wage and salary income, and personal consumption expenditure patterns. Where is the Impact Location? What is the geographic location of the initial economic activity? Any economic impact analysis needs to be defined in terms of a bound area. The study area might be a state, a county, or a collection of counties. We start the study area decision process with the site of the initial impact. Other considerations will be discussed later in this chapter. Which are the Local Expenditures? Each issue will have actions expressed as expenditures. Some of these expenditures may be imports or take place outside of the study area. To study the effects on the local economy, you will need to use only the local expenditures. For example, you want to know the effect of a special event bringing in 10,000 tourists. A local expenditure would be payments to hotels, a non-local expenditure would be an airline ticket purchased at point of origin. What is the Activity Time-frame? What is the time span during which the impact takes place? Many impacts are one-time economic stimuli. Others are temporary, but might span several years (such as a large construction project). Others can involve phased impacts that might include investment and operations. Phased impacts can be modeled using IMPLAN by staging the impacts in different runs. Who are the Institutions making or affected by the final demand change? Institutions refer to the type of final demand sector. An institution might be any industry, households, federal or state government. Is this an Industry or Commodity driven impact? You will need to decide if this is an impact to a given industry or a change in demand for a given commodity. In an IMPLAN model, final demand changes can be made either through an industry or business, or through a commodity, or product. If you are going to need margins, you will choose commodity. In an industry final demand change, only the industry impacted receives the final demand change. With a commodity final demand change, all industries producing the commodity receive part of the change.

Chapter 9: Project Definition 109 Note: under a commodity-driven analysis, a portion of the initial change will be lost if an industry that would otherwise produce that commodity is missing from the region, or if an institution (household, state and local, or federal sales) produces that commodity. Which IMPLAN Sector will you apply the final demand changes to? The data sectoring scheme can be found in Appendix A. For a detailed description of what is included in each sector, refer to the “Standard Industrial Classification Manual”. What are the Dollar Amounts of the final demand changes? Specifying the values of the expenditures involve two more decisions: 1. Are the values in Producer or Purchaser Prices? Producer prices are those paid at the factory door. Purchaser prices are those paid at the retail level. Since IMPLAN data are in producer prices, if our changes are in purchaser prices, we will need to subdivide our values by using margins (described below). 2. What Year are the expenditures made in? If expenditures are in a year different from that of the model year, a deflator will need to be applied (described below). A deflator accounts for the changes in value of a dollar over the years.

Margins If an impact analysis involves purchaser prices, the values need to be subdivided to work with the producer-priced input-output model. This is done using margins. Margins represent the difference between producer and purchaser prices. Margining assigns direct expenditures to the correct I/O sector multipliers. It splits a purchaser price into the appropriate producer values. Input-output accounts list values at the point of production. Note: all values in input-output models are in producer prices. Therefore, the value of the impacts, if purchased by end users or consumers, must be split into the portion going to the retailer, the wholesaler, transportation, and the manufacturer.

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Chapter 9: Project Definition Purchaser Price = Producer Price + Transportation Cost + Wholesale Markup + Retail Markup Retailers produce a service. They gather commodities for sale to consumers. The value of that service is the mark-up, or margin, the retailers apply to the goods. Wholesalers have a similar mark-up. Transportation costs occur from factory to wholesaler and from wholesaler to the site of consumption -i.e., the retailer. The proportion of the value going to each sector is called the margin. Figure 9-1 uses a lawnmower as an example. Figure 9-1. Margins for a Katydid Lawnmower Manufacturer

Producer Value at Factory = $175

+ Transportation Margin = $15

+

Transportation

Wholesaler Margin = $100

+ Transportation Margin = $15 Retailer

Transportation

+ Retailer Margin = $100

Purchaser Price = $405

The purchaser price is the price paid by the consumer at the retail outlet. For a Katydid Lawnmower, the consumer pays $405. The producer value of this item (the price at the factory door) is $175. The margins are the difference ($240) tacked onto the item on its way from the factory to the consumer. The wholesaler paid $190 for the lawnmower (producer price plus transportation from the factory to the warehouse). The retailer paid $305 to stock his store with the lawnmower. For his services he received $100 from the consumer. Margining assigns direct expenditures to the correct I/O sector multipliers. It splits a purchaser price into the appropriate producer values, each value impacting a specific industry. Margins allow us to

Chapter 9: Project Definition 111 be more specific as to the economic activity triggered by a retail purchase. If the purchaser price were applied to the retail sector multipliers, we would trigger an average production of all items provided by retail (plastics for toys, oil for refined gasoline, lumber for furniture and so on) instead of triggering the production of a lawnmower and its associated linkages. Margins allow import activity to be specified for each of the margin sectors, as well as for the producing sector. For example, we can specify that the lawnmower’s manufacturer exists outside of the region and the $175 dollar producer value stimulates no local economic activity. We can leave the remaining margins to stimulate the local retail, wholesale and transportation sectors. Separating margins also allows you to “cut-out” a middleman. If a purchase were made directly from the wholesaler, the retail margin could be deleted. Only retail stores that buy goods from manufacturers use margins. Any purchases made by consumers from service-oriented stores do not have margins. Service businesses produce the service at the same time it is purchased so there is no mark-up. Eating and drinking establishments also have no margins, producing a prepared meal at the time of purchase. Margins are associated with the manufacturing sector of the commodity being purchased. To use margins, you need to specify the commodity being bought. For example, a purchase of gasoline by a consumer means that you select “Refined petroleum” as the impact sector and then tell the software to use “Household” margins. Margins for all commodities are included in the MIG software. Simply specifying “margin” in the event transactions window will cause the software to apply the appropriate margins (see the User Guide for more application information).

Deflators Inflation and the fluctuations of the economy change the value of a dollar and commodities over time. Deflators are used to adjust values from one time period to another. For example: Farmer Joe sold 100 bushels of corn in 1993 for $250, but in 1996 he sold 100 bushels of corn for $300 (though it could have gone down in price). Each value represents (for its year) 100 bushels

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Chapter 9: Project Definition of corn and the inputs required to produce it, but the numbers of dollars are different. For an accurate impact analysis, expenditures need to be expressed in the same year’s dollars as the model’s data. If an impact occurs in one year, but the data is for a different year, the impact expenditures must be adjusted to be consistent with the base year data. Using our Farmer Joe example: if we specify $300 for corn bought in 1996 using a 1993 model without using deflators, we are actually specifying 120 bushels of corn. To get the 100 bushels of corn and the inputs required to produce it we need to deflate the $300 to 1993 values (in this case $250). MIG’s IMPLAN databases come with deflators derived from the most recent Bureau of Labor Statistics Growth Model. The Events window will allow you to specify the year of your expenditures and the software will then use the appropriate deflator (see User Guide for more application information). Deflators are applied after margining. Deflators are associated with commodities and are different for different goods and services. A purchase must be subdivided into its appropriate producer values and then the correct deflator can be applied to each one.

Local Expenditures Every analysis needs to start with Local Expenditures. Local expenditures, as the name suggests, are the final demand changes that occur only within your study region. If local expenditures are not used, then you will be overstating the impacts. You can either predetermine the local expenditure, or let IMPLAN do it for you. If you allow IMPLAN to derive the local proportion, the software will use the model’s regional purchase coefficients. You may then change that value.

Project Definition Example Some examples of impact analysis might be in the form of questions: What happens to the local economy if a factory closes? What are the effects on a region if a military base shuts down? If resources are spent building a recreation area for tourism, what might the benefits be?

Chapter 9: Project Definition 113 We will use the factory example. We will imagine the closure of a beeswax candle factory. Objective: To determine the employment and income impacts of the factory shut down. Where the activities occur: In this case, the impact location would be the area surrounding the factory. Our factory is in Larimer County. Since we are interested in the impacts of a change in employment and associated household spending we want to be sure and include where our employees live. The factory is near the county line and more than half its workforce live in the neighboring county: Weld County. So we will include both Larimer and Weld counties in our study area. Local expenditures: Our factory is entirely within the study area so all production loss will be local losses. Activity time frame: This is a one-time, but permanent, loss of production. Therefore, jobs are permanently lost and all associated PCE (personal consumption expenditures) and other economic activities are also permanently lost. Institutions: The only institutions affected in the factory closure are households. The loss of a factory results in decreased employment and household income. For this example, we expect the effects on government, schools, police, etc. to be negligible. If we thought they would be important, we would have to specify those changes separately. Industry/Commodity: This will involve an industry change. We are interested in the factory, not the goods and services it produces. We can find the IMPLAN sector number in Appendix A. Our bees wax candle factory is IMPLAN sector number 432. Dollar Expenditure: The actual dollar change has to be specified. In this case, how much output will be lost in this area as a result of the factory closing. Our beeswax candle factory has an annual output of 1 million dollars. Purchaser versus Producer Prices: Typically, industry output reductions are in producer prices and, indeed, our million is in output (producer price). Year of Impact: If the model dollars and initial change dollars are in different years, the expenditures need to be deflated. In our case the

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Chapter 9: Project Definition factory is closing in 1999 and the model year is 1996. We will tell the software to deflate our 1999 value.

Chapter 10: Study Area 115

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Study Area Considerations The study area is one of the most important project definition decisions since the extent of the impacts will be dependent on the size of the study area. The trick is to cover enough area to include the most important aspects of the impact, and yet not too much area or the effects will be masked by extraneous economic activity. Typically, the larger the study area, the more economic activity is internalized and the larger the multipliers will be. So, to isolate the effects of an impact, we basically want to make as small a study area as we can, while still including the areas necessary to capture all the important effects. This chapter discusses: Functional Economic Area Forward and Backward Linkages Small Study Areas Example Small Study Area Predefined Study Areas Standard County Classification

Functional Economic Area We can use the concept of a functional economic area to guide us. A functional economic area is semi self-sufficient economic unit (and therefore an ideal unit for input-output analysis). It includes the places where people live, work, and shop, and can sometimes be identified by physical or other characteristics. A study area needs to be a functional economic area centering on the needs of the impacted industries or services (depicted in Figure 10-1). Building a study area involves a number of decisions. The analyst needs to consider: initial impact site residential location of the labor force (commuters) travel corridors

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Chapter 10: Study Area location of supporting industries and services location of consumers Figure 10-1. An Impact’s Functional Economic Area.

Travel Corridors

Location of support services

Residential location of labor force

Impact Site

Consumer locations

Location of supporting industries

If induced effects, or household purchases, are important to an analysis, then commuting areas and travel corridors will need to be considered. People spend money where they reside as well as where they work. If an industry is located in one county, and the workers reside in another adjacent county, then both counties should be included in the study area to ensure the effects of household spending are properly estimated.

Forward and Backward Linkages Supporting industries and services and the major consumers of industry products are its backward and forward linkages. Linkages refer to the connections between industries and consumers. Figure 10-2 depicts some forward and backward linkages for a sawmill producing dimensioned lumber. An industry purchases goods and services to produce its products. A backward linkage is between an industry and its suppliers or a household and the producers of household goods and services. In Figure 10-2, the sawmill’s backward linkages are the purchases of labor, electricity, and logs (all used to produce its lumber).

Chapter 10: Study Area 117 A forward linkage is between an industry producing a good or service and the consumers of that good or service. The consumers may be another industry who will add further value to the purchased good in the production of their product. The wood furniture manufacturer is a forward linkage for the sawmill. The sawmill also exports and sells to households (both forward linkages). Input-output model multipliers trace backward linkages only. Figure 10-2. Forward and Backward Linkages.

Labor

Exports

Utilities

Backward Linkages

Parts and transportation

Forward Linkages

Household consumption

Value added remanufacturing

An industry’s multipliers do not capture forward linkages. For example, the transportation system and any wholesale distribution system for agricultural feed grain is not part of the feed grain industry’s multipliers. A study of the importance of the feed grain industry to a region must also consider the forward linkage of its distribution network in addition to the feed grain industry impacts derived through its own multipliers. The study area should account for the location of buyers and sellers of goods and services important to the analysis. As an example, if the industry under study buys goods from an industry in an adjacent county, having both counties in the study area would be necessary to capture the effects of the linkage.

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Chapter 10: Study Area

Small Study Areas A small study area will have a high level of leakage. Leakages are any payments made to imports or value-added sectors which do not in turn re-spend the dollars within the region. A study area that is actually part of a larger functional economic region will likely miss important backward linkages. For example, linkages with the labor force may be missing. Workers who live and spend outside the study area may actually hold local jobs. Sometimes an analyst is required to analyze an artificially small area. Comparing those impacts with a more logical functional economic area will show economic linkages that might return back to the small area. This will help recover leakages. Study areas are typically a collection of counties. A county is the smallest standard area for IMPLAN data sets. A ZIP code-based study area is possible to build but requires the creation of a custom data file. ZIP code-based databases are available from MIG. A ZIP code based study area allows the analysis of economic impacts on: individual cities regions not based on county or other political boundaries small areas within a city A zip code file is a proportional reduction of a larger county database. This assumes that employees live within the ZIP code area in the same proportions as in the larger database. The smaller the area, the less likely this is to be true. This can cause the induced effects to be overstated. If the major retail is located within the region, then the induced effects may be okay as workers will come back in to spend money. If you know something about the area and the proportion of workers living outside the study area, you can adjust the induced effects to reflect your knowledge.

Example: Small Study Area Let’s look at data for the City of Denver, Colorado and the counties immediately surrounding it (Figure 10-3).

Chapter 10: Study Area 119 Figure 10-3. CO 1993 Data Col. 1

CO County Arapahoe Denver Douglas Jefferson United States

Col. 2

Col. 3

PCE POW Income ($mill) ($mill) 8,942 8,006 10,596 16,125 1,651 681 8,685 7,153 ($bill) ($bill) 4,378 4,222

Col. 4

Col. 5

Col. 6

Col. 7

Total PI PI/POW PCE/PI PCE/POW ($mill) (%) (%) (%) 11,270 141 79 112 12,524 78 85 66 2,193 322 75 242 10,943 153 79 121 ($bill) (%) (%) (%) 5,375 127 81 104

POW Income = place of work income or employee income. These are wages, benefits and other income derived from employment linked geographically to the site of the workplace. Total PI = Labor Income. This income is from all sources, including employment income and transfer payments linked geographically to the recipient’s place of residence. Note: labor income is given by place of residence and employment income is given by place of employment. Since Denver County is the core of a large metropolitan area, many of the employees commute in from the surrounding counties. As a result, employment income generated in the county exceeds the total labor income of those who reside within the county. Column 5 of the table shows the ratio of labor income to employment income. Denver’s ratio is 78%, while in surrounding counties from where the labor commutes, labor income exceeds employment income. This is particularly true for Douglas County where labor income is three times employment income (322%). The U.S. data shows that, overall, labor income exceeds employment income by 27%. PCE (personal consumption expenditures) represents spending by households within each county. There is a strong relationship between PCE and total labor income. Because of commuting patterns, PCE to employment income for an individual county may not be closely linked. In this case, the ratios range from 66% to 242% (Column 7). Type II multipliers assume a linear relationship, implying that for each dollar of employment income we get 66 cents of PCE (Denver) and up to $2.42 of PCE for Douglas County. Similar relationships are also evident in the Type III IMPLAN multipliers which are based on employment rather than employment income.

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Chapter 10: Study Area Problem 1: If an input-output analysis is based only on Denver County, then the household expenditures are a reduced fraction of new employment. The implication is that economic impacts are lost to the counties in which the commuters reside. In reality, a chunk of that “lost” payroll comes back to Denver retailers but that link does not exist in a basic input-output model. Problem 2: If an input-output analysis is based only on Douglas County, then the induced effects of any new job has tremendous leverage ($2.42 PCE for each dollar employment income). This implies that for each new job in Douglas County there will be approximately 2 1/2 new employees working in Denver but residing in Douglas County. This can only be true if the current Douglas County commuter relationship remains constant. The lesson is that for most studies, logical regions include not only the source of economic activity but also the labor force directly involved.

Predefined Study Areas The U.S. Bureau of Census and the Department of Commerce have predefined study areas, such as the Census Commuting Area or the Metropolitan Statistical Areas (MSA). Both of these are based on counties. The MSAs capture metropolitan regions quite well, whereas the commuting areas tend to be large. Both will work. Tolbert and Kizer (1990) have defined 382 labor market areas (875 sub-market areas) for the U.S. based on county level journey-to-work data from the 1990 Census. There are also Bureau of Economic Analysis (BEA) economic areas based on counties, but each is centered on a Census-defined Metropolitan area. The BEA regions are defined to have a minimum population of 100,000.

Standard County Classification Counties and states are organized along the Federal Information Processing Standard (FIPS) code system. This is not an absolute standard (the Bureau of Census has its own system). MIG data products use the FIPS system. The FIPS system assigns a 2 digit numerical code to states, and a 3digit numerical code to counties. For example, Minnesota is FIPS 27, and Washington County is FIPS 163. The FIPS is often presented as

Chapter 10: Study Area 121 the state and county numbers run together: Washington county MN becomes 27-163.

Chapter 11: Database 123

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Database Elements Understanding the data used to create a model helps in interpreting the results. This section describes each data element. Each element in an IMPLAN database can be accessed and edited to reflect an analyst’s knowledge of local conditions. The methodologies used in developing an MIG database are discussed in the third manual of this book: Database Guide. This chapter discusses: National-level Matrices and Tables County-level Database Components Industry Output & Employment Value Added Final Demands Personal Consumption Expenditures (PCE) State and Federal Government Inventory Capital Formation Exports

National-level Matrices and Tables The IMPLAN databases consist of two major parts: 1) national-level matrices and tables and 2) economic and physical data at the county and/or state level. There are several national-level matrices included with each IMPLAN database. 1. The National Absorption Table is a coefficient form of the National Use Table (described herein) derived by dividing each element of the Use Table by the respective industry’s total dollar output. The resulting Absorption Table shows how an industry spends each dollar of outlay on goods and services to produce a dollar of output. Each column is an industry’s production

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Chapter 11: Database function. A production function shows the proportions of commodities used to produce one dollar of output. 2. The National Byproducts Table is a coefficient form of the National Make Table derived by dividing each element by the Make Table row (industry) totals. Each industry can produce more than one commodity. The Byproducts Table shows what percentage of an industry’s total output each commodity represents. 3. Deflators are used to adjust values from one time period to another. The MIG IMPLAN databases come with tables of deflators derived from the most current Bureau of Labor (BLS) Statistics Growth Model. Deflators are associated with commodities and are different for different goods and services. 4. Margins split a purchaser price into the appropriate producer values. Margins for all commodities are included in the MIG software. The national matrices are used with regional data to create a regional model and can be edited to reflect knowledge of local conditions. When a data set is purchased, it includes a national matrix data set. shows what percentage of the total production of a commodity is produced by each industry.

County-level Database Components The local economic data in an IMPLAN database can be divided into four main categories or components. These components are: 1. Industry Output 2. Employment 3. Value Added 4. Final Demands Some physical data is also included: FIPS (Federal Information Processing System) codes land area population. Each state has a unique two-digit FIPS code and the counties within a state are given three-digit FIPS designations. The land area measure is in square miles and excludes bodies of water.

Chapter 11: Database 125

Industry Output Industry output is a single number in dollars, or millions of dollars, for each industry. The dollars represent the value of an industry’s total production. The data were derived from a number of sources, including Bureau of Census economic censuses, BEA output estimates, and the BLS employment projections.

Employment Employment is listed as a single number of jobs for each industry. Data came from ES202 employment security data supplemented by county business patterns and REIS data. All IMPLAN databases, after 1985, include both full-time and parttime workers in employment estimates. In the IMPLAN 1985 database, employment is given as full-time equivalent jobs. Most published estimates are full-time and part-time employment. This means that total employment in a region using 1985 IMPLAN data would generally be below most published estimates.

Value Added There are four sub-components of value-added. These are: 1. Employee Compensation 2. Proprietary Income 3. Other Property Type Income 4. Indirect Business Taxes 1. Employee compensation describes the total payroll costs (including benefits) of each industry in the region. It includes the wages and salaries of workers who are paid by employers, as well as benefits such as health and life insurance, retirement payments, and non-cash compensation. Employee compensation is derived for each industry from ES202 and REIS data. 2. Proprietary income consists of payments received by selfemployed individuals as income. Any income received for payment of self-employed work, as reported on Federal tax forms, is counted here. This includes income received by private business owners, doctors, lawyers, and so forth.

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Chapter 11: Database 3. Other property type income consists of payments for rents, royalties, and dividends. Payments to individuals in the form of rents received on property, royalties from contracts, and dividends paid by corporations are included here as well as corporate profits earned by corporations. Other property type income numbers are derived from U.S. Bureau of Economic Analysis Gross State Product data. 4. Indirect business taxes consist of excise taxes, property taxes, fees, licenses, and sales taxes paid by businesses. These taxes occur during the normal operation of businesses but do not include taxes on profit or income. Indirect business tax numbers are derived from U.S. Bureau of Economic Analysis Gross State Product data.

Final Demands Final demands are institutions (or end users) who buy goods and services for consumption. These goods and services disappear from the economy and are not used to generate more products. Exports are included in final demands since the given commodity will not be used to create more products in the region. Final demand data comes from government surveys, NIPA, Federal procurement and sales data. In input-output analysis, final demands are allocated to producing industries with margins allocated to the service sectors associated with bringing the product to the final user (transportation, insurance, wholesale and retail trade). IMPLAN final demands are in producer prices. It is possible for institutions to have a “negative purchase”, i.e. a sale. In IMPLAN, sales of goods by institutions are treated as contributions to the overall supply of a commodity. There are 13 sub-components for final demands and institutional sales. These are: 1. Household Personal Consumption Expenditures (PCE) – nine income levels (starting with 1996 data) 2. Federal Government Military Purchases 3. Federal Government Non-Military Purchases 4. Federal Government Non-Military Investment 5. Federal Government Sales

Chapter 11: Database 127 6. State and Local Government Non-Education Purchases 7. State and Local Government Education Purchases 8. State and Local Government Non-Education Investment 9. State and Local Government Sales 10. Inventory Purchases 11. Inventory Sales 12. Capital 13. Foreign Exports

Household Demand Household consumption is the largest component of final demand. It consists of payments by individuals/households to industries for goods and services used for personal consumption. Part of total labor income is not available for spending; it is used to pay personal taxes, pay off principle and interest on loans, make credit card payments or purchase new residential housing (classified as Gross Private Domestic Investment). Some labor income also goes toward savings. The average savings rate for U.S. residents in 1993 was 4.1% (SCB July, 1994). There are nine income levels with different PCE profiles: Households Households Households Households Households Households Households Households Households

1996 – 1999 datasets Less than $5,000 $5,000 to $9,999 $10,000 to $14,999 $15,000 to $19,999 $20,000 to $29,999 $30,000 to $39,999 $40,000 to $49,999 $50,000 to $69,999 $70,000 plus

2000 and later datasets Less than $9,999 $10,000 to $14,999 $15,000 to $24,999 $25,000 to $34,999 $35,000 to $49,999 $50,000 to $74,999 $75,000 to $99,999 $100,000 to $149,999 $150,000 plus

Spending patterns can differ dramatically between income levels. For example, low income spending is more heavily weighted toward food, clothing and shelter related commodities. The higher income levels have more disposable income for luxury spending. The personal consumption expenditure patterns can be edited to reflect knowledge of local conditions.

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Chapter 11: Database Purchases made by individuals for final consumption are shown as payments made directly to the industry producing the goods or service and the margin sectors. The PCE profiles have already been margined.

Federal Government Federal government purchases are divided between military, nonmilitary uses, and investment. Federal Military Purchases are those made to support the national defense. Goods range from food for troops to missile launchers. Federal Non-military Purchases are made to supply all other government functions. Government Investment is expenditures made for capital goods and construction. Payments made to other governmental units are transfers and are not included in Federal government purchases. The transfers are tracked in the inter-institutional data (SAM data). Federal Government Sales are sales of commodities by the government. For example: timber sales, park entrance fees, sales of surplus military equipment, and sales of surplus dairy products.

State and Local Government State and local government purchases are divided between public education, non-education, and investment. Public Education Purchases are for elementary, high school, and higher education. Non-Education Purchases are for all other government activities, like state government operations, police protection and sanitation. State and Local Investment are expenditures for capital goods and construction. Private education purchases are not counted here. Private sector education purchases show up in IMPLAN sectors 495 (Elementary and Secondary Schools) and 496 (Colleges, Universities and Schools). State and Local Government Sales are sales of commodities by the government. For example: college dormitory lodging, municipal liquor stores, and park camping.

Inventory Inventory Purchases happen when industries do not sell all output created in one year. Inventory can be thought of as one big warehouse for a region. Any commodity produced that is not immediately consumed or used to produce more commodities gets dumped here.

Chapter 11: Database 129 Inventory Sales occur when industries sell more than they produce and need to deplete inventory. Inventory purchases and sales generally involve industries producing goods (e.g. agriculture, mining, and manufacturing) as opposed to service industries.

Capital Capital Formation are private expenditures made to obtain durable goods or capital equipment (equipment whose life is longer than one year). The values are not expenditures by an industrial sector but rather represent the increase in a region’s overall durable goods assets. The dollar values in the IMPLAN database are in producer prices. Typically, capital equipment is purchased directly from the producer and not through a retail outfit.

Exports Foreign Exports are demands made for goods and services by consumers and industries outside the U.S. It is the value of commodities exported beyond national borders. Note: domestic exports are demands for goods and services by consumers and industries outside the study area but within the U.S. Domestic exports are calculated during the IMPLAN model creation and are not part of the database.

Chapter 12: Regional Accounts 131

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Regional Accounts Construction This chapter describes the creation of regional economic accounts. IMPLAN Pro creates the accounts from the study area data and national matrices automatically. This section is designed to help you understand what is going on behind the scenes. In this part of the model development, the regional transaction matrices are developed and imports are removed from the accounts. A three-by-three example will be used throughout this section to illustrate the calculations. This chapter discusses: Study Area Data National Matrices Net Commodity Supply and Regional Make Matrix Regional Market Shares and Byproducts Gross Regional Absorption and Use Matrices Regional Gross Commodity Demand Regional Supply/Demand Pooling and RPC Regional Commodity Demand Less Imports Regional Commodity Imports Domestic Exports

Study Area Data The user-defined study area database is chosen from any combination of counties or states. Figure 12-1 shows the initial layout of data in a three-by-three example. At this point the Industry-Commodity Transactions Table is missing. Regional data will be applied to national matrices to create a set of regional accounts. The value-added components are employee compensation, proprietors’ income, other property type income, and indirect business taxes. The final demand components in the initial Final Demands Table are personal consumption expenditures, state and local education and

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Chapter 12: Regional Accounts non-education purchases, federal military and non-military purchases, inventory purchases and capital formation. Figure 12-1 Regional Data Final Demands A A Commodities B

Industry B

C

3.0 19.0

S&L Non Ed Ed 2.0 0.0 2.0 3.0

Fed Non Mil Mil 1.0 0.0 0.5 0.0

3.5

1.5

0.4

PCE

?

C Emp Comp 4.0 Prop Income 0.5 Other Prop Inc 1.5 Indirect Bus Tax 0.5 Total VA 6.5 TIO 10.0

10.0 2.5 10.0 1.5 24.0 30.0

1.0

0.1

Inventory Capital Purch Formation 5.0 1.0

0.5 0.5

1.5

0.0

12.0 10.0 6.0 2.0 30.0 40.0

Total industry output (TIO) for industry A is 10.0, B is 30.0, and C is 40.0. Reading down the columns shows industry and final demand purchases of commodities. Industries also make payments to the value-added components. Final demands purchase commodities for final use. The row values show who is purchasing the commodities.

National Matrices National absorption and byproducts matrices are provided with the databases. The National Absorption Table is derived from the National Use Table (Figure 12-2). Figure 12-2. National Use Table Industry B

A A Commodities B C Value Added National TIO

400.0 800.0 1,600.0 5,200.0 8,000.0

0.0 3,000.0 3,000.0 14,000.0 20,000.0

C 8,000.0 0.0 2,000.0 40,000.0 50,000.0

The Absorption Table (Figure 12-3) was created by dividing each column element of the Use Table (Figure 12-2) by the total industry output (TIO) of each industry.

Chapter 12: Regional Accounts 133 Figure 12-3. National Absorption Table

A Commodities B

A 0.05 0.10

Industry B 0.00 0.15

C 0.16 0.00

C VA Coefficient National TIO

0.20 0.65 1.00

0.15 0.70 1.00

0.04 0.80 1.00

The National Absorption Table represents the purchases of commodities by industries to produce the industry’s output. The columns in Figure 12-3 are the industry’s production functions. For every dollar of total industry outlays (including payments to profits) industry A spends 0.05 dollars for commodity A, 0.10 dollars for commodity B, and 0.20 dollars for commodity C. Industry A also spends 0.65 dollars on value-added components. In other words, Industry A spends 5 percent of its total outlays on commodity A and so forth. Industry A’s production function is this proportional breakdown. The National Byproducts Table is derived from the National Make Table (Figure 12-4 below). Figure 12-4. National Make Table

A A Industry B C Gross Comm Prod

7,200.0 0.0 5,000.0 12,200.0

Commodity B 0.0 20,000.0 0.0 20,000.0

C 800.0 0.0 45,000.0 45,800.0

TIO 8,000.0 20,000.0 50,000.0

The Byproducts Table (Figure 12-5) was created by dividing each row element of the National Make Table (Figure 12-4) by the corresponding TIO. Figure 12-5. National Byproducts Table

A Industry B

A 0.90 0.00

Commodity B 0.00 1.00

C 0.10 0.00

TIO 1.00 1.00

C

0.10

0.00

0.90

1.00

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Chapter 12: Regional Accounts The Byproducts Table shows all the commodities made by each industry and the proportion of the industry’s total production each commodity represents. Looking across the row, Commodity A is 90% of Industry A’s production and 10 percent of Industry A’s production is Commodity C. Since Industry A produces mostly Commodity A, Industry A derives its name from Commodity A.

Net Commodity Supply and /Regional Make The Net Commodity Supply is the total production of each commodity for the region after foreign exports have been subtracted. Net commodity supply is used in deriving the supply/demand pooling ratio. Supply/demand pooling is one option for generating regional trade flow estimates. There are several steps involved with calculating net commodity supply. First, the National Byproducts Table is multiplied by the regional total industry output (TIO) from the study area data. The result is the Regional Make Table (Figure 12-6 below). Figure 12-6. Calculate Net Commodity Supply National Byproducts Matrix Commodity A B A 0.90 0.00 Industry B 0.00 1.00 C 0.10 0.00

C 0.10 0.00 0.90

Regional Make Matrix Commodity A B A 9.0 0.0 Industry B 0.0 30.0 C 4.0 0.0 13.0 30.0

C 1.0 0.0 36.0 37.0

Gross Commodity Production

+

-

x

TIO 10.0 30.0 40.0

1 4 0 18.0

0 0 0 30.0

0 0 2 39.0

Inventory Sales State and Local Government Sales Federal Government Sales Total Regional Commodity Supply

1 17.0

0 30.0

0 39.0

Foreign Exports Net Commodity Supply

=

Chapter 12: Regional Accounts 135 The sum of the columns is the gross commodity production, or the total value of each commodity produced, by industry, in the region. Note: if a regional industry does not exist, then the TIO is zero and the resulting industry row in the regional make table is zero. Other sources of commodity production come from sales by governments and inventory. Some government agencies produce commodities similar to those found in the private sector. For example; colleges produce lodging, eating and drinking and the federal government sells timber and surplus goods. Withdrawals from inventory also add to gross commodity production. These activities are federal, state and local, and inventory sales. These sales elements are added to gross commodity production, resulting in total regional commodity supply. From the total regional commodity supply, foreign exports (a final demand element in the regional data base) are removed. Foreign exports are, by definition, being removed from the region and therefore are unavailable for use by industries within the region. Inventory additions also remove commodities from the available supply, but they are not currently subtracted from the total regional commodity supply in IMPLAN Pro. Net commodity supply is the total regional commodity supply minus foreign exports. This value represents the commodities available for use within the region or for domestic exports.

Regional Market Shares and Byproducts Once the Regional Make Table is created, the Regional Market Shares and Regional Byproducts Tables can be created. The Regional Byproducts Table shows the percentage of an industry’s total output each commodity produced represents. The Regional Byproducts Table is used to convert industry output to commodity output and vice-versa. The Regional Byproducts Table is created by dividing each row element of the Regional Make Table by the total industry output (Figure 12-7 below).

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Chapter 12: Regional Accounts Figure 12-7 Regional Market Share and Byproducts Regional Make Matrix Commodity A B C TIO A 9.0 0.0 1.0 10.0 Industry B 0.0 30.0 0.0 ¸ 30.0 C 4.0 0.0 36.0 40.0 ¸ 18.0 30.0 39.0 Total Regional Commodity Supply

Regional Make Matrix Commodity A B A 9/10 0 Industry B 0 1 C 1/10 0

Regional Make Matrix Commodity A B A 9/18 0 Industry B 0 1 C 4/18 0

C 1/10 0 9/10

C 1/39 0 36/39

=

=

Regional Byproducts Commodity A B 0.9 0.0 0.0 1.0 0.1 0.0

C 0.1 0.0 0.9

Regional Market Shares Commodity A B 0.5 0.0 0.0 1.0 0.2 0.0

C 0.0 0.0 0.9

The Regional Market Shares Table is derived by dividing each element of the Regional Make Table by total regional commodity supply (Figure 12-7). Note: the columns of the Market Shares Table above will not necessarily sum to 1.0. Total regional commodity supply includes the non-industrial contributions to commodity supply (government and inventory sales) while the Market Shares Table details only industry sources. The Market Shares Table shows what percentage of the total production of a commodity is produced by each industry and is used in creating the industry-by-industry transactions table used in the multiplier development.

Gross Regional Absorption and Use Matrices The regional absorption matrix is created from a combination of study area data and the National Absorption Table elements.

Chapter 12: Regional Accounts 137 The National Absorption Table column (production function) elements represent the goods and services purchased by an industry to produce its output. Each column of an absorption table plus the value added coefficients (payments made to the value added elements: employee compensation, proprietor’s income, indirect business taxes, and other property type income) equals 1.0. The IMPLAN study area database includes regional value-added and total output. The value-added components are added and the total is divided by total output to get a regional value-added coefficient. The regional absorption column total is one minus the regional valueadded coefficient (Figure 12-8 following page). Note: the one exception is when total industry output and the valueadded coefficient are zero (the industry does not exist within the region) then the table column total is 0. For example, Industry B (in Figure 12-8) has a regional value-added coefficient of 0.8 while nationally the coefficient is 0.7. This means that the corresponding National Absorption Table column is 0.3 (1.00.7) and must be adjusted to sum to 0.2 (1.0-0.8). This means the region pays relatively more of each dollar outlay for value-added and less for intermediate goods and services. Each element of the National Absorption Table for Industry B is adjusted by a factor of 0.667 (0.2/0.3). The resulting column balancesi.e., absorption column total plus the total value added coefficient equals 1.0.

Chapter 12: Regional Accounts

A Commodities B C Reg VA Coefficient Regional TIO

A Commodities B C Total VA TIO

3,000.0 3,000.0 14,000.0 20,000.0

24.0 30.0

C

30.0 40.0

0.0 2,000.0 40,000.0 50,000.0

10.00

30.00

40.00

Gross Regional Use Matrix (includeds imports) Industry A B C 0.50 0.00 8.00 1.00 3.00 0.00 2.00 3.00 2.00 6.50 24.00 30.00

6.5 10.0

?

Regional Use Matrix Industry A B

Commodities B 800.0 C 1,600.0 Value Added 5,200.0 National TIO 8,000.0

National Use Matrix Industry A B C A 600.0 0.0 8,000.0

Figure 12-8 Absorption Adjustment

138

Regional TIO

A Commodities B C Reg VA Coefficient

Absorption Factor: (1-Reg VA)/(1-Nat VA)

A Commodities B C Reg Absorp Subtotal Reg VA Coefficient Regional TIO

Commodities B C Absorption Subtotal VA Coefficient National TIO

0.15 0.15 0.30 0.70 1.00

1.00

0.35 0.65 1.00

0.67

0.20 0.80 1.00

?

Industry B

C

1.25

0.25 0.75 1.00

0.00 0.04 0.20 0.80 1.00

0.16

1.00

1.00

1.00

Gross Regional Absorption Matrix Industry A B C 0.05 0.00 0.20 0.10 0.10 0.00 0.20 0.10 0.05 0.65 0.80 0.75

A

Regional Absorption Matrix

0.10 0.20 0.35 0.65 1.00

National Absorption Matrix Industry A B C A 0.05 0.00

Chapter 12: Regional Accounts 139 In Figure 12-8 the resulting table is the Gross Regional Absorption Table. It is ‘gross’ because imports (included as part of the national table) have yet to be removed. ‘Imports’ are anything imported from outside the region; at this point domestic and foreign imports are lumped. The Gross Regional Use Matrix can be derived from the Gross Regional Absorption Table by multiplying each element by the regional total industry output.

Gross Regional Commodity Demand Like gross regional absorption, the gross regional commodity demand will include imports (both domestic and foreign). Combining gross regional use with the gross regional final demands derives total gross regional commodity demand. Gross regional commodity demand is the sum of the final demand commodity purchases and the commodity purchases by industries from the Gross Regional Use Table (Figure 12-9).

140

Chapter 12: Regional Accounts

Figure 12-9. Gross Regional Commodity Demand Gross Regional Industry A

S&L B

C

Fed

PCE Non Ed

A

0.5

0

8

Commodities B C

1

3

0

2

3

2

Gross Inter. Ind. Demand

3.5

6

10

Emp Comp

4

10

12

Prop Income

0.5

2.5

10

Other Prop Inc

1.5

10

6

Indirect Bus Tax

0.5

1.5

2

Total Value Added

6.5

24

30

Total Industry Output

10

30

40

+

Ed

Inv

Non Mil

Mil

Purch

Capital

Comm.

Form

Demand

3

2

0

1

0

5

0.5

20

19

2

3

0.5

0

1

0.5 =

30

3.5

1.5

1

0.4

0.1

1.5

0

15

Chapter 12: Regional Accounts 141

Regional Supply/Demand Pooling and RPC Once regional net commodity supply (calculated earlier in this chapter) and gross regional commodity demand are calculated, trade flows (or imports) can be estimated. Supply/Demand (S/D) pooling and Regional Purchase Coefficients (RPCs) are two ways imports can be estimated. Once imports are estimated, they can be removed from the regional social accounts. Supply/demand pooling maximizes the internal use of goods and services and, therefore, maximizes the multiplier, sometimes quite unrealistically. Supply/demand pooling is an option offered by the IMPLAN software. Current IMPLAN software uses RPCs as the default trade flow estimate. An econometric equation with variable values filled in from regional data is used to estimate RPCs for commodities.

Supply/Demand Pooling Supply/Demand (S/D) Pooling assumes that all commodity production in a region that can be used will be used to satisfy gross regional commodity demand (Figure 12-10). Figure 12-10 Calculate Supply Demand Pooling Net Gross Net S/D Commodity Commodity Trade Supply Demand Flows A Comm. B C

17.0 30.0 39.0

-

Net Commodity Supply A 17.0 Comm. B C

30.0 39.0

Regional Purchase Coefficient A 0.10 Comm. B 0.25 C 0.75

20.0 30.0 15.0

=

Gross Commodity Demand 20.0 ÷

30.0 15.0 Supply/ Demand Pool Ratio 0.85 1.00 1.00

-3.0 0.0 24.0 Supply/ Demand Pool Ratio 0.85

=

1.00 1.00

Model RPC 0.10 0.25 0.75

If S/D > 1.0 then SD = 1.0

142

Chapter 12: Regional Accounts Gross regional commodity demand is subtracted from net regional commodity supply to derive the net supply/demand trade flows. The net supply/demand trade flows is an indicator of domestic import requirements and domestic exports. A negative value indicates that commodities must be imported to meet demand. A positive value indicates there is more supply than demand in the region and the excess is exported to domestic markets. The supply/demand pooling ratio is calculated by dividing each element of the net commodity supply vector by each corresponding element of the gross commodity demand vector. There is an upper limit of 1.0 (local production cannot supply more than 100% of local demand). This means that if supply exceeds demand, then demand only takes what is needed.

Regional Purchase Coefficient (RPC) Estimating regional trade flows (imports and exports) across regional boundaries is perhaps the largest source of error in deriving nonsurvey I/O models (Stevens and Trayor 1980). Use of Regional Purchasing Coefficients is one way to eliminate some of the errors inherent in a non-survey model. The Regional Purchase Coefficients (RPCs) method is based on the characteristics of the region and describes the actual trade flows for the region mathematically. There is a different equation for each commodity with variables filled by study area data. Information about the data sources used to derive these predictive equations can be found in the Data Guide. An RPC represents the portion of the total local demand that is met by local production and attempts to account for cross-hauling - the regional importation and exportation of commodities from the same sector. For example, an RPC value of 0.8 for the commodity "fish" means that local fishermen provide 80% of the local demand for fish (by fish processors, fish wholesalers, and others). The remaining 20%, is imported. IMPLAN Pro software generates RPCs automatically. All industries/institutions are treated equally unless you specify otherwise -i.e., each will take an equal proportion of its needs from local sources based on that RPC.

Chapter 12: Regional Accounts 143 The IMPLAN Pro software allows you to edit a commodity RPC (applied equally to all consumers of the commodity), or you may give specific RPC values to specific users of a given commodity. The equation: 1-RPC for each commodity represents commodity import proportion (domestic and foreign imports for the region). A model’s RPCs are a mixture of the estimated RPCs, national RPCs and the constraining S/D pooling ratios. When IMPLAN calculates RPCs it uses the S/D pooling ratio to set the maximum possible supply available. It also uses the national RPCs with the implied assumption being that the region will import foreign goods and services at the same rate as the nation. In Figure 12-10, the S/D pooling ratio is compared to the regional purchase coefficient that was derived for each commodity. The model’s regional RPCs indicate that for Commodity A, 10 percent of demand is met by local production. For Commodity B, it is 25 percent.

Location Quotient Location Quotients are based on commodity output. The location quotient equation is a fixed equation. It is based on comparing the ratios of local production to national production ratios: Lqi = (Regioni / Regionsum) / (USi / USsum) where: •

Regioni is the region’s production of Commodity i,

•

Regionsum is the region’s total production of all commodities

•

USi is the U.S.’s production of Commodity i, and

•

USsum is the U.S.’s total production of all commodities.

The LQ for a commodity is constrained to be less than or equal to one.

Regional Commodity Demand Less Imports Imports are removed from the regional economic accounts using the regional purchase coefficients. Each element of the Regional Use Table and the final demands are multiplied by the associated commodity level RPC. Note: value-added and total industry output are not affected by this calculation.

144

Chapter 12: Regional Accounts The resulting table (Figure 12-11) represents total local economic interactions; the buying of locally produced goods and services by local industries as well as the purchases by consumers for final use. Note: this method of calculating trade flows assumes that an RPC for a single commodity applies equally to all consumers of that commodity.

6.5 10

Total Value Added Total Industry Output

0.05 0.25 1.5 1.8 4 0.5 1.5 0.5 6.5 10

A Commodities B C Gross Inter. Ind. Demand Emp Comp Prop Income Other Prop Inc Indirect Bus Tax Total Value Added Total Industry Output

A

Industry

0.5

Indirect Bus Tax

Regional Commodity Demand w/o Imports

4 0.5 1.5

30

24

1.5

10 2.5 10

0 3 3 6

30

24

10 2.5 10 1.5

0 0.75 2.25 3

B

Industry A B 0.5 1 2 3.5

Emp Comp Prop Income Other Prop Inc

A Commodities B C Gross Inter. Ind. Demand

Regional Comm. Demand w/ Imports

40

30

2

12 10 6

8 0 2 10

40

30

12 10 6 2

0.8 0 1.5 2.3

C

C

0.3 4.8 2.6

PCE

PCE 3 19 3.5

Figure 12-11. Regional Commodity Demand and Removing Imports

0.1 0.25 0.75

0.2 0.5 1.1

Non Ed

S&L

RPC

Model

2 2 1.5

S&L Non Ed

Fed Non Mil 0 1 3 0.5 1 0.4

0 0.8 0.8

Ed

0.1 0.1 0.3

Non Mil

Fed

(Multiply by RPC)

Ed

145

Inv Cap Purch Form 0 0.5 0.1 0 0.3 0.1 0.1 1.1 0

Mil

Inv Capital Purch Form 0 5 0.5 0 1 0.5 0.1 1.5 0

Mil

Chapter 12: Regional Accounts

146

Chapter 12: Regional Accounts

Regional Commodity Imports Now regional commodity imports can be calculated for both intermediate and final demands. The regional commodity demands with imports are subtracted from the regional commodity demands without imports. The results are imports-to-commodity demand (Figure 12-12). The domestic and foreign imports are still lumped in the imports-tocommodity demand. The imports are separated into foreign and domestic imports based on the RPC for the nation and is the same for all IMPLAN regions: 1-RPC = Foreign imports ratio (national rate) 1-RPC = Foreign and Domestic Imports Ratio (regional rate) This ratio multiplied by the gross regional commodity demand gives the foreign imports for the commodity. The total regional imports less the foreign imports gives the domestic imports. IMPLAN performs these domestic and foreign imports calculations before printing reports.

1.8

4 0.5 1.5 0.5 6.5 10

Gross Inter. Ind. Demand Emp Comp Prop Income Other Prop Inc Indirect Bus Tax Total Value Added Total Industry Output

30

24

10 2.5 10 1.5

3

0 0.75 2.25

40

30

12 10 6 2

2.3

0.8 0 1.5

0.3 4.75 2.63

0.45 0.75 0.5 1.7

A Commodities B C Gross Inter Ind Demand

3

0 2.25 0.75 7.7

7.2 0 0.5

2.7 14.25 0.88

Imports to Regional Commodity Demand Industry A B C PCE

0.05 0.25 1.5

A Commodities B C

Ed

Ed 1.8 0 1.5 2.25 0.38 0.25

S&L Non Ed

0.2 0 0.5 0.75 1.13 0.75

Regional Commodity Demand without Imports Industry S&L A B C PCE Non Ed

Figure 12-12.Regional Commodity Demand without Imports

0.9 0.38 0.1

Fed Non Mil

0.1 0.13 0.3

Fed Non Mil

0 0 0.03

Mil

0 0 0.08

Mil

Inv Purch 4.5 0.75 0.38

0.5 0.25 1.13

Inv Purch

Cap Form 0.45 0.38 0

0.05 0.13 0

Capital Form

147

18 22.5 3.75

Imported Commodity Demand

2 7.5 11.25

Local Commodity Demand

Chapter 12: Regional Accounts

148

Chapter 12: Regional Accounts

Domestic Exports The local commodity supply that is not used locally is exported to markets outside the region. Local commodity demand is subtracted from net commodity supply to derive domestic commodity exports (Figure 12-13). Figure 12-13. Domestic Exports. Figure 18. Domestic Exports.

A Commodities B C

Net Commodity Supply 17.0 30.0 39.0

-

Local Commodity Demand 2.00 7.50 11.25

=

Domestic Commodity Exports 15.00 22.50 27.75

The result is a balanced set of regional economic accounts. These are industry-by-commodity net of imports and exports, but do not include complete inter-institutional information.

Chapter 13: Inter-Institution Transfers 149

C H A P T E R

1 3

Inter-institutional Transfers Adding additional data to the regional economic accounts and then balancing the resulting matrices generates social accounting matrices. MIG’s unique IMPLAN data sets include institutional data that makes the creation of Social Accounting Matrices possible. Inter-institutional transfers provide information on non-market financial flows. They capture payments of taxes by individuals and businesses, transfers of government funds to people and businesses, and transfer of funds from people to people. This chapter discusses: SAM History SAM Framework Use of SAMs in Input/Output Research Descriptive Analysis Tax Analysis CGE Modeling Regional SAM Analysis Example

SAM History Richard Stone spearheaded the initial development of the SAM framework. It was a natural outgrowth of input/output accounting, extending market-based transaction accounting to non-market financial flows. In the beginning, SAM development work involved construction of SAMs for several developing countries, including Sri Lanka, Botswana, and Swaziland (Pyatt and Round, 1985). These studies, funded by the World Bank and other development organizations, set out to incorporate national account data into a SAM framework. The principle uses of SAMs in these cases were as a baseline for development planning and other model building. SAMs continue to be used in research work and governmental policy decision making. MIG’s data sets allow the creation of local area SAMs without the burden of extensive data collection.

150

Chapter 13: Inter-Institutional Transfers

SAM Framework Like input-output analysis, a full social accounting matrix is a double-entry bookkeeping system similar to the T-Accounts in financial accounting. Just like in standard accounting, the SAM must balance: receipts must equal expenditures. The matrix format allows the double entry bookkeeping to be displayed in a single-entry format. A social accounting matrix includes the typical components of input-output models: the Use matrix the Make matrix Value added (called Factors in SAMs) Final demand (called Institutions in SAMs) Exports and Imports (called Trade in SAMs) Value-added is payment to labor and to capital. Factors include payments to land, labor and capital. In a flow of funds SAM, such as IMPLAN, the only factors looked at are payments to labor and returns on capital. Capital stock and land are not considered. So in IMPLAN, factors and value-added are the same. Final demands are an institutional demand for the final use of commodities. Institutions are households, governments, and capital. In IO, exports are treated as consumption like any other final demand element. In SAMs, exports are removed from the make matrix which represents only local consumption (Figure 13-1). Non-industrial financial flows are added to the I/O elements to create a complete SAM table: Factor exports Institution exports Factor imports Factor Distribution (to Institutions) Inter-institutional transfers A unique SAM sector is also added. Enterprises capture corporate profits. An industry makes a payment to other-property-type-income. The other-property-type-income is subdivided into payments to

Chapter 13: Inter-Institution Transfers 151 households, dividends and payments to profit. These payments by other property type income to profits are enterprise entries. Factor Exports are payments received by factor sectors (employee compensation, proprietary income, other property income and indirect business taxes) from outside the region. An example might be a stock dividend to a person living in the area from a company based outside the region. Institution Exports are payments received by institution sectors (households, governments, inventory, or capital investment) from outside the study area. An example would be a person commuting to a job outside the region; the payment is to a household from an industry outside the study area. Factor Imports are imports from outside the study area by factor sectors. Factor imports looks at the distribution of the payments made to factor sectors by industries; where does that factor payment end up? For example: a company within the region may hire an employee who lives outside the region. The company makes a payment to the factor sector employee compensation that ends up going outside the region. Factor Distribution is payments from factor sectors (employee compensation, proprietary income, other property income and indirect business taxes) to institutions sectors (households, federal and state governments, inventory, capital investment or enterprises). For example: a portion of employee compensation might go to social security - a government agency (institution). Inter-institutional Transfers refer to the payments from institutions to other institutions. For example: the federal government grants money to state governments and households (welfare and social security payments) and households pay taxes to governments and save money to capital. Figure 13-1 shows a typical SAM layout with the new elements shaded (lighter shaded areas represent totals with SAMs data added to previous input/output totals). Each entry is a separate matrix. The column and row headings are the different economic actors. The column entries represent expenditures or payments made by the economic actor at the top of the column. The row entries represent receipts or income to the economic actor at the beginning of the row.

Value Added

Factors

Factor Trade Total Factor Outlay

Total Industry Outlay

Total

Transfers

Imports

Total Commodity Outlay

Sales

Make

Commodity

Trade

Capital

Enterprises

Institutions

Use

Commodity

Industry

Industry

Factors

Chapter 13: Inter-Institutional Transfers

Figure 13-1. SAM Framework

152

Total Institution Outlay

Imports

Transfers

Consumption

Institutitons

Total Enterprise Outlay

Transfers

Enterprises

Total Capital Outlay

Transfer

Transfers

Consumption

Capital

Total Trade Outlay

Exports

Exports

Exports

Exports

Exports

Trade

Total Trade Income

Total Capital Income

Total Enterprise Income

Total Institution Income

Total Factor Income

Total Commodity Income

Total Industry Income

Total

Chapter 13: Inter-Institution Transfers 153 The real contribution of a SAM is the distribution of institutional income to other institutions. These inter-institutional transfers show the flow of non-industrial funds. Inter-institutional transfers include transfers from businesses to households (interest and dividend payments), transfers from people to government (payment of taxes), and transfers from governments to people (social security, unemployment compensation, etc.). Inter-institutional transfers also include the capital accounts. Government capital accounts show surplus and deficits. For businesses, this is investment and borrowing. For households, this is a net saving.

Balancing After the regional set of balanced economic accounts are created, the SAM data can be added. It is necessary to balance the SAM table by making adjustments in the imports, exports, and capital accounts based on the data in the regional economic accounts. We will use household sectors an example. Households receive income from industries and institutions and use it to buy goods and services, pay taxes, and save for the future. We have information about income, consumption and tax payments. Savings are the balancing element. We assume our income, consumption and tax payments data are accurate and savings become the difference. Savings can be either positive or negative. Negative savings means the household spends more than it makes. This is accomplished by withdrawing from household capital stocks or borrowing from financial institutions. Other balancing elements work similarly. The difference between government income and spending is a surplus or deficit (and sure enough, the SAM shows the U.S. with a deficit). Foreign trade balance is the balancing element between imports and exports. It describes the relationship between foreign imports and foreign exports.

154

Chapter 13: Inter-Institutional Transfers

Use of SAMs in I/O Research Given the complete accounting of monetary flows in a region, there are many uses for regional social accounting matrices. Three possible uses are: 1. Descriptive Analysis 2. Tax Analysis, and 3. CGE Modeling

1. Descriptive Analysis The most basic analysis that can be done is descriptive. Identifying the flow of dollars through an economy is an important step in understanding the structure of the local economy. Though industrial production and consumption is important, non-industrial dollar flows can also be a large part of local economic activity. For example, retirement transfer payments are important to many rural economies particularly resort areas.

2. Tax Analysis The impact on taxes from changes in economic activities can be modeled. Income information can be combined with SAM tax information to make estimates of the taxes generated by a change in final demand. This is a simple ratio estimate, but it will give a good first estimate of the tax effects. The same can be done with business taxes. Taxes are paid out of labor income and limit disposable income. Tax policies can be examined with regard to individual tax burdens on different income groups. A SAM allows you to examine the actual magnitude of taxes and transfer payments. Using a SAM with a spreadsheet program such as Excel or Lotus allows you to analyze the impact effects on taxes.

3. Computable General Equilibrium Modeling The computable general equilibrium (CGE) model was developed from macro-economic modeling and classic economic theory. It is used to analyze policies or projects involving price responses, and assumes the existence of profit-maximizing producers and utility-maximizing consumers. Central to CGE modeling is Walras’ Law: for all goods with a value greater than zero, the quantity supplied must equal the quantity

Chapter 13: Inter-Institution Transfers 155 demanded. While this is true for SAM-based input-output modeling, a CGE model is more flexible in the form its mathematical descriptions of the production and consumer demand relationships can take. Basically, solution algorithms find a price vector and a commodity production level that cause all markets to clear (everything produced is purchased). Functional forms of production and demand equations are developed with the SAM serving as a base equilibrium point from which comparative static’s analyses are performed. Local level SAM data from IMPLAN models can be used for regional CGE modeling. Production and consumption function forms and elasticities must be added to the IMPLAN SAM data to build the CGE model. Consideration must be given to the handling of domestic and foreign trade and the estimates of import demand and export supply elasticities. Once calibrated, a CGE model can be used to simulate large final demand changes, resource supply restrictions, tax policies, and a wide variety of other economic perturbations. More information on CGE modeling can be found in Lindall et al, “IMPLAN SAM: A Social Accounting Matrix for Regional I/O Systems”.

Regional SAM Analysis Example Figure 13-2, on the next page, is a balanced example SAM. The first two rows (industries and commodities) represent the IMPLAN input/output data reduced to one element. The rows represent institutions receiving payments, the columns represent institutions making payments. All monetary transactions are included, both market and non-market. In the first column, industries make payments to commodities and the value-added components. The third column represents the distribution of employee compensation received by industries. Employee compensation pays 19.0 to households, 2.0 to federal government in the form of payroll taxes, and 1.0 to state and local government in payroll taxes. Note: the corresponding rows and columns balance. The household (HH) row details income to households from all sources (not just employee compensation). Households receive income from other property type income (dividends and interest); state and federal government (social security, unemployment compensation, and interest payments); and from being self-employed.

156

Chapter 13: Inter-Institutional Transfers These transfer payments comprise a large portion of household income, but would not have been captured in traditional input-output analysis. By examining the household column, we can see where households spend (or distribute) their income. Households buy and consume commodities and make payments to state and federal government for taxes. What is left over goes to capital accounts for capital purchases and savings. Trade and capital take up the slack between the other accounts and the totals. There is no way of getting hard data for these accounts at this time, so they are used to balance the other accounts with the totals.

1,767.9 8,334.2

Total 5,847.5

2,786.9

96.5

163.4

17.0 2.2

2362.8 327.6

Employee Comp

0.2 0.6

Institution Payments--> Industry Comm. 5,664.1 1,786.1 2,786.9 302.9 1,262.3 428.3

Households Federal Gov. NonDefense Federal Gov. Defense S&L Govt NonEducation State/Local Govt Education Enterprises (Corporations) Capital Inventory Additions/Deletions Trade

Institution Receipts Industry Commodity Employee Compensation Proprietary Income Other Property Income Indirect Business Taxes

Figure 20. Social Accounting Matrices

Figure 13-2 Social Account Matrix

302.9

0.0

286.6 16.3

Propr. Income

1,262.3

4.0

384.3 944.7

103.8

-71.3 -103.3

Other Prop Income

87.1

428.3

341.2

IBT

3,820.0

1,153.8

20.0

121.4

353.5

2,171.3

HH

796.0

8.8

246.0

24.6 52.8

370.7

93.0

FG Non-def

24.6

4.1

20.5

FG Defense

1,156.9

81.4

0.0

461.5

208.8

405.2

S&L gov Non-ed

461.5

44.0

417.5

S&L Gov Education 0.0

384.3

109.7

18.0

143.5 113.1

Ent

1,987.4

27.8 311.4

251.4

466.8 0.0

930.1

Capital

46.5

22.8

0.0

0.0

23.7

Inventory

3,398.1

650.1 16.6

8.4

51.9 1.1

Trade 2,670.1

31,037.3

3,398.1

46.5

1,987.4

384.3

461.5

1,156.9

24.6

796.0

3820.0

428.3

1,262.3

302.9

2,786.9

5,847.5

8,334.2

Total

Chapter 13: Inter-Institutional Transfers 157

Chapter 14: I x I Accounts 159

C H A P T E R

1 4

Industry-by-Industry Accounts The standard input/output predictive model is in an industry-byindustry format. The industry-by-industry accounts are derived using the Regional Absorption Table with imports removed and the Regional Market Shares Table. The result is a table of industries purchasing from local industries (as opposed to industries purchasing commodities). This chapter discusses: Industry Technology Assumption Market Shares Assumption Industry-by-Industry Creation

1. Industry Technology Assumption The MIG databases are created from industry-by-commodity data. Any time data is converted from industry-by-commodity to an industry-by-industry model, there is an assumption made about the technology used to create the commodities. The industry technology assumption states that: An industry uses the same technology to produce its byproducts as it does to produce its main (primary) product. This means that when an industry produces more than one commodity, one commodity is the main product, or, the primary commodity. All other commodities are assumed to be byproducts. Therefore, all the other commodities are produced using the same technology as the primary commodity. When a purchase is made of a commodity from an industry, that industry’s production function is triggered no matter which product (primary or secondary) was purchased. This means that purchases of the same commodities from different industries will trigger different production functions.

160

Chapter 14: I x I Accounts

2. Market Shares Assumption The market shares assumption states that: Producing industries contribute to consuming industries in the same proportions as producing industries contribute to total production. This assumes that the probability of a purchase occurring from Industry A is the same as Industry A’s contribution to the total regional production of the given commodity. An industry’s market share coefficient is the percent of the total regional commodity production that industry produces. For example, Figure 14-1 shows that of the total regional production of Commodity A, Industry C produces 20 percent. Figure 14-1. Regional Market Shares

A Industry B C

Regional Market Shares Commodity A B C 0.5 0.0 0.0 0.0 1.0 0.0 0.2 0.0 0.9

As an example; suppose Industry A’s absorption of commodities, for each dollar spent, is 0.005 for Commodity A, 0.025 for Commodity B, and 0.15 for Commodity C (See Figure 14-1). How much does Industry A buy from Industry C? Industry A buys 0.005 units of Commodity A and we know that Industry C produces 22.2 percent of the regional supply of Commodity A. Industry C will supply 22.2 percent of Industry A’s need of 0.005 units of Commodity A. That is, Industry A buys 0.222 * 0.005 = 0.00111 units of Commodity A from Industry C. This calculation is the same as a table multiplication of the Market Shares and Absorption Tables. This is the method used by IMPLAN to calculate the industry-by-industry transaction matrix. Note: this method is also used to convert final demands from a commodity basis to an industry basis.

Chapter 14: I x I Accounts 161

Industry-by-Industry Creation This calculation is based on two assumptions: 1. the Industry Technology Assumption 2. the Market Shares Assumption Figure 14-2 shows the Industry-by-Industry (IxI) Table created by pre-multiplying the Regional Absorption Table (net of imports) with the Market Shares Table. Figure 14-2 Industry by Industry Calculation Regional Commodity Demand Regional Absorption w/o Imports Matrix w/o Imports Industry Industry A B C A B C A 0.05 0.00 0.80 A 0.005 0.000 0.020 Commodities B 0.25 0.75 0.00 Commodities B 0.025 0.025 0.000 C 1.50 2.25 1.50 C 0.150 0.075 0.038 Total Value Added 6.5 24.0 30.0 Total Industry 10.0 30.0 40.0 Output x Regional IxI Matrix Industry A B C A 0.006 0.002 0.011 Industry B 0.025 0.025 0.000 C 0.140 0.069 0.039

Regional Market Shares Commodity A B C A 0.500 0.000 0.026 Industry B 0.000 1.000 0.000 C 0.222 0.000 0.923

In linear algebra, a matrix of size IxC times a CxI yields an IxI matrix. Starting with the commodity by industry (CxI) use matrix, we multiply the industry-by-commodity (IxC) Market Shares Table. In essence, we are combining two commodity/industry matrices into a single industry-by-industry matrix. The resulting Regional IxI Matrix is also called the Regional Direct Coefficients Table. By multiplying Total Industry Output by the Regional IxI Table, we can compute the Regional Transactions Table

Chapter 15: Predictive Model 163

C H A P T E R

1 5

Predictive Model Derivation Final consumption (or final demand) drives input-output models. Industries respond to meet demands directly or indirectly (by supplying goods and services to industries responding directly). Each industry that produces goods and services generates demands for other goods and services and so on, round by round. These iterations generate the multipliers. This section illustrates the mathematics involved in generating the different types of multipliers. Multipliers Type I Multipliers Type II Multipliers Type SAM Multipliers Value Added Multipliers Employment Multipliers

MULTIPLIERS Multipliers break the effects of stimuli on economic activity down into three components: 1. Direct effects are the changes in the industry used to describe the events being analyzed. 2. Indirect effects are the changes in inter-industry purchases as they respond to the new demands of the directly affected industries. 3. Induced effects reflect changes in spending from households as income/population increases or decreases due to the changes in production. There are three different multipliers commonly developed for predictive modeling, the Type I, the Type II, and Type SAM.

164

Chapter 15: Predictive Model

Type I Multipliers The Type I multiplier measures the direct and indirect effects of a change in economic activity. They capture the inter-industry effects only, i.e. industries buying from local industries. Type I multipliers are the first set of multipliers generated. We start with a Regional Transactions Table (developed in the last chapter). A Transactions Table is similar to a Use Table, but instead of showing transactions as industries buying commodities, it shows transactions as industries buying from other industries. Figure 15-1 shows a Transactions Table (base year input-output transactions). There are three industry sectors (A, B, and C). Figure 15-1: Transactions Table ($millions) Industry A

B

C

FD

TIO

A

0.06

0.06

0.44

9.44

10.00

Industry B

0.25

0.75

0.00

29.00

30.00

C

1.40

2.07

1.56

34.97

40.00

Value-Added

6.50

24.00

30.00

10.00

30.00

40.00

Imports Industry Outlay

The first column shows purchases by Industry A to produce its output. Industry A purchases $0.06 million from other A industries, $0.25 million from Industry B, and $1.4 million from Industry C. These purchases are for goods and services used directly in the manufacturing of Industry A’s goods. Industry A also makes $6.5 million in value-added payments to labor, interest on borrowing, indirect taxes, and corporate profits. The total outlay shows all expenditures made to produce Industry A’s goods. Industry A’s total outlay is $10 million. The Industry A row shows who buys (or demands) Industry A’s products. Industry A buys $0.06 million from itself, Industry B buys $0.06 million from Industry A, and Industry C buys $0.44 million worth of goods from Industry A. Note: the total industry outlay and total industry output are equal. As with T-Accounts, receipts equal expenditures.

Chapter 15: Predictive Model 165 Next, we derive a coefficient matrix by dividing each industry column element by the column total. This coefficient matrix is also known as the A Matrix. Figure 15-2 is the coefficient form of the Transactions Table shown in Figure 15-1. Figure 15-2: A Matrix Industry A

B

C

A

0.006

0.002

0.011

Industry B

0.025

0.025

0.000

C

0.140

0.069

0.039

Value-Added

0.650

0.800

0.750

1.000

1.000

1.000

Imports Industry Output

The columns are the production functions: where an industry spends and in what proportions to generate each dollar of output. For Industry A, 0.006, or 0.6 percent of its total outlays are for Industry A’s products. Industry A spends 0.65, or 65 percent of its total outlay on value-added. Through algebraic manipulation of the data in Figure 15-2, we derive the Type I multipliers. The first step in this transformation is to rewrite the A Matrix as a series of linear equations. X1 = 0.006 * X1 + 0.002 * X2 + 0.011 * X3 * Y1 X2 = 0.025 * X1 + 0.025 * X2 + 0.000 * X3 * Y2 X3 = 0.140 * X1 + 0.069 * X2 + 0.039 * X3 * Y3

or as matrices: X1 X2 X3

=

0.006

0.002

0.011

0.025

0.025

0.000

0.140

0.069

0.039

X1 *

X2

Y1 +

X3

The equations can also be written in matrix notation:

X=A*X+Y This notation simply states that output (Xi)is equal to transactions(A*Xi) plus final demands (Yi).

Y2 Y3

166

Chapter 15: Predictive Model We then subtract the transactions (A*X) from both sides of the equation (i.e., output minus transactions equals final demands). Our linear equations become: X1 - 0.006 * X1 - 0.002 * X2 - 0.011 * X3 = Y1 X2 - 0.025 * X1 - 0.025 * X2 - 0.000 * X3 = Y2 X3 - 0.140 * X1 - 0.069 * X2 - 0.039 * X3 = Y3

and the matrices: X1 X2

-

X3

0.006

0.002

0.011

0.025

0.025

0.000

0.140

0.069

0.039

X1 *

Y1

X2

=

Y2

X3

Y3

and in matrix notation: X - A * X = Y.

We restate the problem to isolate the X term. Our linear equations become: (1-0.006) * X1 - 0.002 * X2 - 0.011 * X3 = Y1 - 0.025 * X1 + (1-0.025) * X2 - 0.000 * X3 = Y2 - 0.140 * X1 - 0.069 * X2 + (1-0.039) * X3 = Y3

In the matrix form we can see the Identity Matrix created: 1

0

0

0

1

0

0

0

1

-

0.006

0.002

0.011

0.025

0.025

0.000

0.140

0.069

0.039

X1 *

X2

Y1 =

X3

Y2 Y3

In matrix notation we have: (I - A) * X = Y

where I is the Identity Matrix. Solving for X involves multiplying the (I-A) inverse from both sides of the equation. The Leontief Inverse is sometimes referred to as the (IA) Inverse Matrix. -1

-1

(I - A) * (I-A) * X = (I - A) * Y

This resulting equation is the Predictive Multiplier Model: -1 X = (I - A) * Y.

Chapter 15: Predictive Model 167 This can also be interpreted as: -1

Change in Total Industry Output = (I - A) * Change in Final Demand. or

∆X = (I - A)-1 * ∆Y The predictive model shows how output will change with a given change in final demand. The (I - A) inverse is the matrix of multipliers. Figure 15-3 shows the resulting table of Type I multipliers. Figure 15-3: Type I Output Multipliers Table Industry A

B

C

A

1.008

0.003

0.011

Industry B

0.026

1.026

0.000

C

0.148

0.074

1.042

Type I Multiplier

1.182

1.103

1.054

For a one dollar change in Industry A’s final demand, there is a corresponding change of 1.008 dollars in total Industry A output, a 0.026 dollar change in Industry B’s output, and a 0.148 change in Industry C’s output. A one-dollar change in Industry A final demand results in a 1.182 dollar change in total economy output. This number, 1.182, is the multiplier for Industry A. From Figure 15-3 (the table of Type I output multipliers) we generate multipliers for each component of value-added, as well as employment. This is possible because of the relationship between output and income (found in the production function), and output and employment (found in the regional database). Figure 15-4 shows the data used to calculate the value-added Type I multipliers. Figure 15-4 Type I Value-Added Multipliers Direct & Value-Added Total Direct Indirect per $ of & Indirect Requirements Output ValueAdded A 1.008 0.650 0.655 Industry

B

0.026

0.800

0.021

C

0.148

0.750

0.111

Type I Multiplier

1.182

0.787

168

Chapter 15: Predictive Model The first column is the Type I output multiplier for Industry A (from Figure 15-3). This represents the direct and indirect requirements. The second column is the total value-added required for 1 dollar of output (Figure 15-4). This is the output to value-added ratio. The last column is the total direct and indirect value-added derived by multiplying columns one and two. The value-added multiplier is the direct plus the indirect (the total of the last column) divided by the direct (% spent on value added) or 0.787/0.655= 1.20. For a $1 dollar income change in Industry A, there is $1.20 total income change over the entire economy. Figure 15-5 gives another, more concise, example of the derivation of Type I multipliers starting with the Regional Industry-by-Industry Matrix. Figure 15-5 Output Multipliers Calculation Regional IxI Matrix Industry A B C A Industry B C

0.006 0.025 0.140

0.002 0.025 0.069

0.011 A 0.000 Industry B 0.039 C

Identity Matrix Industry A B 1.00 0.00 0.00

0.00 1.00 0.00

C 0.00 0.00 1.00

-1

A Industry B C Total

Regional Multipliers (I-A) Regional (I-A) Matrix Industry Industry A B C A B 1.008 0.003 0.011 A 0.994 -0.002 0.026 1.026 0.000 Industry B -0.025 0.975 0.148 0.074 1.042 C -0.140 -0.069 1.182 1.103 1.054

C -0.011 0.000 0.961

First, the Regional IxI Coefficients Table (also called the A Matrix) is subtracted from an Identity Table. The I-A ensures that the standard matrix inversion conditions are satisfied: the matrix is square and non-singular. The result is the Regional (I-A) Table. This (I-A) table is then inverted forming the Regional (I-A)-1 Table or the Leontief Inverse matrix. In this example, for each one dollar change in the output in Industry A , there will be an additional change of 0.008 dollars in Industry A, a 0.026 dollar change in Industry B, and a 0.148 dollar change in Industry C for an overall change in 1.182 dollars in the entire economy.

Chapter 15: Predictive Model 169

Type II Multiplier A Type II multiplier captures direct and indirect effects. In addition to the inter-industry effects, the Type II also takes into account the income and expenditures of households. The household income row and the household expenditures (PCE - personal consumption expenditures) column are treated as an industry and included in the Leontief inversion. This internalizes the household sector, including the induced or household spending, effects. The Type II multiplier says that for a one dollar change in final demand for Industry A, increases occur in inter-industry economic activity (as in Type I). But it also says the incomes of people employed producing the output of industry A increase. These people spend their income on personal consumption (PCE), which leads to demands from local industries. The result is a higher estimate of economic activity than in the Type I multiplier. Figure 15-6 shows a general way of calculating Type II multipliers. Figure 15-6 Type II Calculation Regional IxI Matrix

Identity Matrix

Industry A

B

Industry C

PCE

A

0.006 0.002

0.011

0.006

Industry B

0.025 0.025

0.000

0.136

C

0.140 0.069

0.039

HH Income

0.450 0.417

0.550

A

B

C

A

1.00

0.00

0.00

0.00

Industry B

0.00

1.00

0.00

0.00

0.071

C

0.00

0.00

1.00

0.00

0.000

HH Income

0.00

0.00

0.00

1.00

Regional Multipliers (I-A)

-

-1

Regional (I-A) Matrix

Industry A

B

Industry C

PCE

A

B

C

A

1.013 0.007

0.016

0.008

A 0.994 -0.002 -0.011 -0.006

Industry B

0.111 1.099

0.091

0.156

Industry B -0.025 0.975 0.000 -0.136

C

0.200 0.119

1.098

0.095

C -0.140 -0.069 0.961 -0.071

HH Income

0.612 0.527

0.649

1.121

-0.450 -0.417 -0.550 1.000

Total

1.94

1.75

1.85

The total multiplier for Industry A is 1.94 which is considerably higher than the Type I multiplier of 1.182 from Figure 15-5.

170

Chapter 15: Predictive Model Type II multipliers assume that as incomes rise, spending on all goods and services rise. For example, a household purchases coffee for its own consumption. The Type II scenario assumes that as incomes rise, the household will purchase proportionately more coffee. There are three different ways to calculate the Type II multipliers. The traditional “textbook” approach (not done with IMPLAN Pro), the IMPLAN Pro default method using information from the social accounting matrices, and IMPLAN Pro’s specific disposable income method. The differences between these three involve creating the household consumption coefficients. For the first method, the “textbook”, dividing household consumption by total labor income in the region creates the household consumption coefficients. There are several problems with the “textbook” approach. First, there is the commuting problem. The labor income is earned in the region and the household consumption is based on households who live in the region. If labor income is being spent outside the region by commuters, then the Type II multiplier will be overstated. Since household consumption is based on resident expenditures, and household expenditures can be based on income from all sources, or if there is significant out-commuting, you could have consumption expenditures larger than labor income, causing the household coefficients to sum to something greater than 1.0. The second problem is that PCE is residence-based and is the result of all sources of household income. This includes household income from transfer payments. Labor income is workplace based, and therefore does not include the other income sources. If you use labor income, then you can have consumption functions that sum to more than 1.0. There is also a problem in handling taxes and savings with the “textbook” method. Since we are normalizing the household consumption spending with labor income, we are not accounting for social security or income taxes, nor are we accounting for savings. IMPLAN Pro provides two methods for calculating the Type II multipliers, the default SAM and the specific disposable income. The first IMPLAN Pro method is based on the SAM data. Instead of dividing household expenditures by labor income like the “textbook” method, IMPLAN Pro divides household expenditures by total household income as defined by the social accounting data. This

Chapter 15: Predictive Model 171 accounts for all sources of income, removes income taxes and allows for savings. We still have a commuting problem in that the model still assumes that all income will be spent locally by households. We are still using labor income which includes payments for social security taxes. The last IMPLAN Pro method for the Type II is to specify the disposable income factor. Here we normalize the local household consumption spending, then apply a factor to the vector of spending to account for savings and taxes. We can also account for commuting and social security taxes as well. The drawback is that it puts a burden on you to specify the factor. Data for this is scarce. The Type SAM multiplier automatically handles all the Type II drawbacks.

Type SAM Multipliers The induced effects captured in the Type II multipliers addressed what was once a leakage -i.e., the household income. IMPLAN Pro Version 2 incorporates another form of multiplier, the Type SAM. The Type SAM actually uses all social accounting matrix information to generate a model that captures the inter-institutional transfers. A model can be built that incorporates not only households, but also other institutions as well (Figure 15-7). Figure 15-7 Type SAM Model Regional IxI Matrix Industry A

B

C

Factors

Institutions

A

0.006

0.002

0.011

0.000

0.006

Industry B

0.025

0.025

0.000

0.000

0.136

C

0.140

0.069

0.039

0.000

0.071

Factors

0.450

0.417

0.550

0.000

0.000

Institutions

0.000

0.000

0.000

0.992

0.010

Inverse A

B

C

Factors

Institutions

A

1.013

0.007

0.016

0.008

0.008

Industry B

0.111

1.099

0.091

0.157

0.158

C

0.201

0.119

1.098

0.096

0.096

Factors

0.612

0.527

0.649

1.122

0.123

Institutions

0.613

0.528

0.650

1.124

1.133

1.325

1.225

1.205

172

Chapter 15: Predictive Model

Figure 15-7 shows the layout of a very simple SAM model. The multipliers generated are not too different from the Type II above. This is due to the nature of the example. Typically, a Type SAM model will have smaller values than a standard Type II. For households, the Type SAM multipliers use information about inter-institutional transfers to account for commuting, social security tax payments as well as household income taxes and savings. Labor income is transferred to the factor account, which distributes the income to households who live in the region, social security taxes, and households that live outside the region. Households that live in the region then make consumption expenditure with only disposable income as well as making payments to income taxes and savings. Similar multipliers can be derived to capture investment or any other institutions. For example, government can be included in the model if we think that government activity is directly linked to the local economy.

Value-Added Multipliers Income multipliers (or any of the value-added components) are derived from the relationship between income and output. In our study area data, we have total industry output and total income for each sector. From these we can calculate income per dollar of output. Industry A’s multiplier is split into the direct and indirect effects and then multiplied by the income per dollar of output ratio to get the income direct and indirect effects. Figure 15-8 illustrates the calculation of the Type I income multiplier.

Chapter 15: Predictive Model 173 Figure 15-8. Type I Income Multipliers Industry Total Income/ Output Income $Output A 10.0000 4.5000 0.4500 Industry B 30.0000 12.5000 0.4167 C 40.0000 22.0000 0.5500 Income Multiplier for Sector A Type I Direct Effects A 1.0000 Industry B 0.0000 C 0.0000 Total

Income Direct Effects 0.4500

Type I Indirect Effects 0.0081 0.0258 0.1483

+

x

Income Indirect Effects 0.0960

Income/ $Output 0.450 0.417 0.550

¸

=

Income Direct Effects 0.4500

Income Direct Effects 0.4500 0.0000 0.0000 0.4500

=

Income Indirect Effects 0.0036 0.0108 0.0816 0.0960

Type I Income Multiplier 1.2132

The Type I income multiplier is derived by dividing the direct plus indirect effects by the direct effects. The calculated income multiplier is 1.2132. For each dollar of income generated by the new economic activity, an additional 0.2132 dollars of income are created.

Employment Multipliers The employment multiplier is created in the same manner as the income multiplier, but using output per worker ratios instead of output per dollar of income. Figure 15-9 shows the creation of employment multipliers. First, the employment per dollar of output is calculated, then the direct and indirect effects are estimated (Type I multipliers). The level of employment per million dollars of output is multiplied by the output multiplier. The result is an employment multiplier of 1.276. For each job created, an additional 0.276 jobs are generated.

174

Chapter 15: Predictive Model Figure 15-9. Type I Employment Multipliers Industry Total Employment/ Output Employment $Output A 10.000 0.750 0.075 Industry B 30.000 1.800 0.060 C 40.000 5.000 0.125 Employment Multiplier for Sector A Type I Type I Direct Indirect Effects Effects A 1.000 0.008 Industry B 0.000 0.026 C 0.000 0.148

Employ Direct Effects 0.075

+

x

Employ Indirect Effects 0.021

Employment/ $Output 0.075 0.060 0.125

÷

=

Employ Direct Effects 0.075

Employment Employment Direct Indirect Effects Effects 0.075 0.001 0.000 0.002 0.000 0.019 0.075 0.021

=

Type I Employ Multiplier 1.276

Both the income and employment multipliers are used to give additional insight as to how an economy is affected by some economic change.

Chapter 16: Impact Analysis 175

C H A P T E R

1 6

Impact Analysis Once a predictive model is generated, impacts to the region’s economy can be analyzed. This chapter discusses the organization of impacts and some impact analysis considerations. The development of a golf course in Larimer County, Colorado is used to illustrate the building of a predictive model and the introduction of a final demand change. This example can be done on MIG software with the Larimer County, Colorado file. The data used is 1993 Version 3.15.96. If you use a different data year or version, you may get different results. This chapter discusses: Organizing Impacts Example Analysis Consumer Expenditure Activities Production Function Changes Aggregation Error Trade Flow Estimation Error Sources Discussion of Induced Effects Type II Compensating for Induced Effect Estimation Errors

Organizing Impacts The IMPLAN software needs economic impacts organized around a project. Any economic impact begins with an event or a direct purchase (i.e. initial change). Figure 16-1 illustrates the organizational view of the expenses (events) associated with an impact analysis. The project is at the top of the hierarchy. It represents the entire impact analysis. A project may be a single event or may involve many layers of groups.

176

Chapter 16: Impact Analysis Figure 16-1. Impact Organization

Project Group A Event 1 Transactions & Margins Event 2 Transactions & Margins

Group B Event 1 Transactions & Margins Event 2 Transactions & Margins

A group of events might comprise a single activity. Activities (or groups of events) are collections of related transactions or events. The grouping of effected activities represents the project. If a project involved studying the effects of the development of a golf resort, the activities might include the construction of the golf course as well as the related golf course visitors’ expenditures. Events define the sector impacted and the dollar amount. Margins and deflators are also included in the events. Margins are required if purchases are made at the retail level. Deflators are required if the dollar amounts are for a year different from the year found in the MIG database.

Chapter 16: Impact Analysis 177 Figure 16-2 has examples of projects, groups, and events. Figure 16-2. Project/Group/Event Examples Projects Groups Industry Closure Computer plant closes Fishing Trip

Grocery shopping

Oil and Gas Lodging Other Military Base Closing

Loss of Payroll

Events Loss of output by computer sector Vegetables Meat Packing Fluid Milk Refined Petroleum Lodging Photo finishing Amusement & recreation services Reduction of personal consumption expenditures in the area

Example Analysis Objectives: To understand the impact of a new golf course on the economy of Larimer County, Colorado. There are two parts of this analysis: construction and visitor spending. Impact location: The region of interest is Larimer County. The model multipliers will give all additional indirect and induced effects triggered by new expenditures resulting from the new golf course. Local expenditures: A portion of the construction and visitor expenditures are local. This is identified in the following tables. Activity time frame: The construction takes place in the first year. The golf visitors take place in the next and subsequent years. Institutions affected: This is a final demand change in investment (construction), the expenditure of which will be directly specified. Also of households (golf resort visitors) whose impacts will be captured through Type III multipliers. Overall, impacts are considered small enough to not have significant effects on government and other investment activities. Industry or commodities: This scenario will involve commodities since we are not concerned with who is providing the goods and services. The commodities affected are listed in the tables below. Dollar expenditure: A total of $10.3.million is spent on construction. The golf visitors spend $197 each day.

178

Chapter 16: Impact Analysis Purchaser or producer prices: The construction dollars spent on contractors are in producer prices since the construction materials are coming directly from the manufacturer. The furnishings are at retail prices. Some of the visitor expenditures are in purchaser prices, some are in producer prices. The table below identifies the IMPLAN sector used, whether the dollars are producer or purchaser, and the year of the activity data. These tables contain the information used to create this impact scenario. Figure 16-3 shows the breakdown of the construction expenditures. There will be a total of $10.3 million spent locally. Nine million dollars will be spent on contractors. Furnishing expenditures will be $1.3 million and will be margined. Figure 16-3: Construction Activity ($MM) IMPLAN Producer/ Event Sector Description Purchaser $ Contractors 48 Residential Producer Construction Furnishings 153 Household Purchaser Furniture Total Margins Transportation Wholesale Retail Total Margins Total Manufacturing Total

Dollar Year 1992 1992

Total Spent Expenditures Locally $11.00 $9.00 $12.00

$1.30

$23.00

$10.30 $0.013 $0.078 $0.581 $0.672 $0.628 $1.300

The example predictive model was built using the 1993 (Version 6.18.96) Larimer County, Colorado data set. The steps for building the model can be found in the case studies section or in the Case Studies chapter of this book. The initial changes are the values identified as “Spent Locally” in Figure 16-3 and Figure 16-4. The construction impacts are estimated first. Figure 16-4 has the results of the impact analysis. The construction project contributes a total of $14.5 million in new final demand in the county. Total industry output change is $18.6 million. There is an employment change of 283 full and part-time jobs earning $4.9 million in employee compensation.

Chapter 16: Impact Analysis 179 Figure 16-4. Construction Activity Total Final Industry Demand Output Direct Effects $10,299,500 $10,299,500 Indirect Effects $0 $3,310,900 Induced Effects $4,225,300 $5,256,600 Total Effects $14,524,800 $18,867,000

Employee Compensation $1,984,800 $1,238,000 $1,670,200 $4,893,000

Total Value Added $3,935,600 $2,033,400 $3,342,200 $9,311,200

Employment 112 73 98 283

It is important to identify which visitors are from out-of-town and which are local. Including local visitors is not usually desirable since they could have spent their money locally elsewhere (merely shifting expenditures from one local activity to another). Selecting the correct retail margin can also be difficult if the analyst does not know exactly what the visitor is buying at the retail store. To use margins correctly, the analyst has to select the appropriate commodity (margins are associated with commodities). A local visitor survey can be the best method for determining the appropriate commodities. Since this is unknown here, it is assumed that the visitors are buying sporting goods. Golf visitor expenditures are shown in Figure 16-5. A total of $197 in local expenditures are estimated for each visitor day. This data would likely come from a visitor survey. It’s estimated that each visitor will spend $75 on lodging, $60 on eating and drinking, $40 on golf fees, and $22 on other retail purchases. Margins are applied only to the other retail purchases.

180

Chapter 16: Impact Analysis Figure 16-5 Golf Visitors Activity ($ Per Visitor Day) IMPLAN Event

Sector

Producer/ Description

Dollar

Purchaser $ Year

Total

Spent

Expenditures

Locally

Lodging

463 Hotels & Lodging

Producer

1992

$75.00

$75.00

Eating & Drinking

454 Eating & Drinking Producer

1992

$60.00

$60.00

Golf Fees

488 Amusement & Producer Recreation 153 Sporting & Athletic Purchaser Goods

1992

$40.00

$40.00

1992

$22.00

$22.00

$197.00

$197.00

Retail Purchases Total Margins Transportation

$0.088

Wholesale

$2.838

Retail

$9.900

Total Margins

$12.826

Total Manufacturing

$9.174

Total

$22.000

It was estimated that there would be 30,600 out-of-town golf visitors the first year of operation. At this level, the golf visitors contribute a total of $10.6 million in new final demand in the county (Figure 16-6). Total industry output change is $12.7 million. There is an employment change of 342 jobs earning $4.5 million in employee compensation. Figure 16-6. Golf Visitors

Direct Effects Indirect Effects Induced Effects Total Effects

Final Demand $5,556,5000 $0 $5,098,700 $10,655,200

Total Industry Output $5,556,500 $967,300 $6,343,100 $12,866,900

Employee Compensation $2,189,200 $278,800 $2,015,500 $4,483,500

Total Value Added $3,890,600 $535,500 $4,033,000 $8,459,100

Employment 208 15 119 342

It is important to note that the impact size is directly dependent on the number of visitors. Also, all effects are positive. This analysis only considers the effects of changes in expenditures associated with construction and operation of this golf course. An analyst may also need to consider the additional activities, such as new roads, sewers, schools, or other government activities, as well as any costs, e.g. environmental or social which IMPLAN does not automatically consider.

Chapter 16: Impact Analysis 181

Consumer Expenditure Activities Handling tourism expenditure data often requires assumptions as to how to distribute these expenditures to the IMPLAN sectoring scheme for impact analysis. E.g., an expenditure of $100 for groceries requires specifying which of the 50 odd IMPLAN food processing and agricultural sectors represent the average grocery-shopping list. The PCE activity database makes life easier if you are willing to accept national average expenditure patterns for general expenditure categories. The Bureau of Economic Analysis creates these expenditure patterns for their work on the national benchmark I-O tables in order to bridge the NIPA (National Income and Product Account) PCE (Personal Consumption Expenditure) data into their IO commodity sectoring scheme. The following are three examples of the 122 expenditure categories in the file: 1111 2100 5700

Food for off-premise consumption i.e. groceries Shoes and other footwear Stationery & writing supplies

In the activity database, each of the 122 categories are an activity with events specifying the individual purchases and margins. Activity levels can be edited (in millions of dollars) to model Recreation/Tourism (or whatever purpose) impacts. We recommend primary tourism surveys be conducted with specific sectors (or aggregated sectors) forming the basis of the expense categories on the survey form. Note: activities for impact analysis must be selected individually from the activity database, as the database is far too large to fit into memory in its entirety.

Production Function Changes The industry production functions are derived from the column of the Absorption Table for a given industry. These production functions are national averages which are modified for the particular region. This can introduce errors in regions where the industry is dissimilar to a national average. Each industry’s production function can be adjusted. This can be accomplished by changing one or many elements of the gross

182

Chapter 16: Impact Analysis absorption column. Keep in mind that the absorption column plus the value-added coefficients must sum to 1.0.

Aggregation Error Aggregating speeds up the model development process and reduces the size of reports, but it can introduce errors due to the loss of data detail. Errors are introduced from production functions, output per worker averages, and other value-added ratios. Aggregating the region’s industry sectors before generating multipliers has the effect of taking several individual industries and combining them to form a totally new industry (the sum of the individual industries). Dramatic errors can happen when multipliers are derived from the production functions of aggregated industries. The production function of the new aggregated industry becomes the weighted average of the individual production functions. Industries with the greatest outputs have the greatest influence on the aggregated industry, but the new industry’s production function may not truly represent an industry being impacted. This generates an aggregation-induced error. For example: Figures 16-7 and 16-8 show the aggregated multipliers of two regions. Eastern Arkansas (Figure 16-8) consists of 12 Arkansas counties and is a subset of the state of Arkansas (Figure 167). Note: aggregated multipliers for the state are greater than for the aggregated sub-state model for all industries except “mining” - an intuitively illogical result since the sub-state region has less activity. However, the aggregation error can produce these results. Figure 16-7 Arkansas Output Multipliers (Aggregated) 1 AGG AG, FORESTRY & FISHERIES

Type I

Type III

1.3889

2.0705

35 AGG MINING

1.1305

1.2138

48 AGG CONSTRUCTION

1.3771

1.9659

58 AGG MANUFACTURING

1.3830

1.7914

433 AGG TRANSP, COMM & UTILITIES

1.2642

1.6560

447 AGG TRADE

1.1450

2.2077

456 AGG F.I.R.E.

1.1520

1.5074

463 AGG SERVICES

1.2537

2.2614

510 AGG GOVERNMENT

1.1404

2.3152

Chapter 16: Impact Analysis 183 Figure 16-8 Eastern Arkansas Output Multipliers (Aggregated) 1 AGG AG, FORESTRY & FISHERIES

Type I

Type III

1.3536

1.8779

35 AGG MINING

1.1715

1.4332

48 AGG CONSTRUCTION

1.2766

1.7473

58 AGG MANUFACTURING

1.2624

1.5816

433 AGG TRANSP, COMM & UTILITIES

1.2046

1.5179

447 AGG TRADE

1.1073

2.0405

456 AGG F.I.R.E.

1.1182

1.3841

463 AGG SERVICES

1.2006

2.0465

510 AGG GOVERNMENT

1.1309

2.1571

This result is not surprising if we take a quick look at the mining sector data. Figure 16-9 and 16-10 show unaggregated multipliers for the mining sectors. In every case, multipliers for existing mining sectors in Eastern Arkansas (Figure 16-8) are less than for the state (Figure 16-7). An aggregated multiplier is the weighted average of its components. At the state level, sector 47, “Misc. nonmetallic Minerals” is 72% of the aggregated mining sector’s output (Figure 16-9). This sector is also the smallest of the mining multipliers. For East Arkansas, sector 38, “Natural Gas and Crude Petroleum” is 46% of the aggregated mining sector’s output, which happens to be the largest of the mining sector multipliers. Multiplying the component Type I and Type III multipliers by the industry output weights yields the weighted Type I and III multipliers shown in Figures 16-9 and 16-10. The sum of the individual weighted pieces come close to the mining sector multipliers shown in Figures 16-9 and 16-10. The upshot is that the mining industry for the state is not the same as the mining industry for East Arkansas. The moral of this example is to be very careful what you aggregate or aggregate only the IMPLAN impact reports. Also, if you wish to gauge both local impacts and statewide impacts based on a single local event, then be sure that the state industry resembles the local industry being impacted, or else modify the IMPLAN data base for the state.

184

Metal Ores, Not Elswhere Clas Coal Mining Natural Gas & Crude Petroleum Natural Gas Liquids Dimension Stone Sand And Gravel Clay, Ceramic, Refractory Min Chemical, Fertilizer Mineral Nonmetallic Minerals Misc. Nonmetallic Minerals, N

36 37 38 39 40 41 42 45 46 47

Natural Gas & Crude Petroleum Natural Gas Liquids Dimension Stone Sand And Gravel Misc. Nonmetallic Minerals, N

38 39 40 41 47

Total / Weighted Average

1.1992

Coal Mining

37

1.0102

1.0644

1.0666

1.0789

1.3046

TYPE I

1.0635

1.3056

1.2622

1.2615

1.1343

1.155

1.091

1.3513

1.2137

SECTOR

Figure 16-10. East Arkansas (1991)

Total / Weighted Average

1.2799

Uranium-radium-vanadium Ores

35 1.3488

TYPE I

SECTOR

Figure 16-9. Arkansas (1991)

Chapter 16: Impact Analysis

1.0185

1.482

1.6224

1.2602

1.5254

1.3923

TYPE III

1.0704

1.6245

1.3107

1.4419

1.5482

1.5941

1.2822

1.6156

1.4186

1.6122

1.6232

TYPE III

1.0000

0.7224

0.0000

0.0010

0.0046

0.0235

0.0087

0.0099

0.2173

0.0032

0.0059

0.0035

(ratio)

26.5535

4.8843

2.0544

3.8519

2.5912

12.4549

0.7168

(MM$)

1.0000

0.1839

0.0774

0.1451

0.0976

0.4690

0.0270

(ratio)

Base Year TIO

2324.73

1679.47

0.1148

2.22

10.5816

54.5507

20.1613

22.9498

505.198

7.5338

13.7782

8.1708

(MM$)

Base Year TIO

1.1725

0.1858

0.0824

0.1547

0.1053

0.6119

0.0324

TYPE I

Weighted

1.1328

0.7683

0.0001

0.0012

0.0057

0.0266

0.0100

0.0108

0.2937

0.0039

0.0080

0.0045

TYPE I

Weighted

1.4134

0.1873

0.1147

0.2353

0.1230

0.7155

0.0376

TYPE III

Weighted

1.2150

0.7733

0.0001

0.0013

0.0066

0.0363

0.0138

0.0127

0.3511

0.0046

0.0096

0.0057

TYPE III

Weighted

Chapter 16: Impact Analysis 185

Trade Flow Estimation Error Sources Cross-hauling makes the accurate estimation of trade flows particularly difficult. Cross-hauling occurs when transporters (haulers) of an identical commodity pass each other going opposite directions on the highway. A particular commodity or service sector may contain a range of qualities and/or features. Differences in features, cost or quality (real or perceived) will affect whether or not a local consumer purchases a locally produced commodity or service. A few factors that can cause cross-hauling are: Cost - The same item may be available at less cost from a nonlocal producer. Quality - The local product may not be the same quality as that available elsewhere. Features - The local commodity may not be substitutable with a similarly classed commodity produced elsewhere. For example: goats and rabbits are quite often lumped into a single "Miscellaneous livestock" category, yet a fur coat manufacturer will not view them as substitutable. Aggregating different products or services into a single category can increase crosshauling. Given a choice between two suppliers of a substitutable commodity, a consumer may still choose the one that is more expensive, or of inferior quality for any one of a number of cultural, administrative, or perception reasons. A tourist may buy hand-made Indian jewelry even though the similar jewelry costs less and may be of better quality when made by machine. An American may buy a car made in Detroit when a cheaper and better quality car can be imported. Multipliers are extremely sensitive to different levels of economic activity within a region. Although cross-hauling makes accurate estimation of trade flows difficult, it is important to identify imports as accurately as possible.

186 Chapter 16: Impact Analysis

Discussion of Induced Effects The induced effects, or the effects of household spending, must be used cautiously. There are times when the induced effects should be left out or be scaled back. For example: a short term construction project will generate a flurry of economic activity that will die off with the completion of the project. Including household spending through the induced effect would imply the construction workers would spend their income locally, when in reality they are probably commuters or only shortterm residents who will take their money home when they leave.

Type II Induced Effects The Type II induced effect occurs as a result of increased income in the region. The direct and indirect effects generate an increase in worker income. This may be from new employment in the region or simply that the current employees are earning more, perhaps as the result of higher productivity. If the increased income is from new workers from outside the region, then the induced effects are justified. If the change is an income increase for current employees, then the induced effects may be overstated. The Type II induced effects assume that an increase in income results in increased household expenditure for goods and services, with the increase in expenditures occurring linearly. As a result, the Type II induced effects may overstate reality. For example: before the economic change, a household buys coffee. After the economic change, the Type II says that the household will buy more coffee due to higher income of the household. This would not necessarily be the case. The use of marginal expenditure patterns would take care of this problem. Although industry production functions are also linear increases in expenditures, an industry output usually requires more of the same inputs to increase output, whereas households do not. Increased household income can mean increased luxury spending or savings and investment rather than an increase in spending for shelter, food, utilities, or clothing.

Compensating for Induced Effect Estimation Errors There are a several ways to reduce the overstatement of induced effects.

Chapter 16: Impact Analysis 187 1. Scale back effects - The effects can be scaled back to reduce the impact. 2. Separate final demand change for induced effects - The induced effects can be estimated separately as a change in final demand. This technique allows the analyst to pre-determine how much income actually goes into the induced effect. 3. Change the disposable income factor in Type II - IMPLAN allows you to specify how much of the new direct labor income is recirculated through the local economy.

Chapter 17: Case Studies 189

C H A P T E R

1 7

Case Studies These case studies are designed to introduce the analyst to a variety of issues and techniques that can be used to address impact related issues. In each case study, you perform the steps necessary to achieve the impact results. As you progress through the case studies, you will notice that the step-by-step instructions will become less specific. It will be up to you to figure out the necessary keystrokes. If you have difficulty, check out the previous examples, the manual, or the on-line help. Bold words indicate a mouse click or keystroke. Hints are italicized. Answers have been provided to written questions. We have not included the numerical answers in case of changes in data. These case studies and more are available along with numerical answers on our web site at www.implan.com. Case Studies included: 1. Creating a Model 2. Single Industry Impact 3. Multiple Events and the Use of Margins 4. Using Groups and Household Final Demand Change 5. Analyzing a New Industry 6. Using Projects and Surveys 7. Effects of Changing Regional Purchase Coefficients 8. Creating an Aggregated Model 9. Advanced Features

190 Chapter 17: Case Studies

Case Study 1: Creating a Model TASK: Create a study area and run the model through the Type SAM multipliers. STEPS: 1. Select File/New Model or click the New Model button to create a new study area. 2. The Create a New Model dialog box will be displayed. Give your model a name call it Washington. Click Save. 3. Select the 2001 Washington, MN a file from the ..\DATA\ directory. Either double-click the file name, or single-click on the name and click on the Select button to move the file to the Selected Files box. 4. Click Continue. 5. When the study area is done, Click OK. 6. Select Construct Model from the model control center or Model/Construct. 7. In the Multiplier Options box, click the Type SAM option. The Social Accounts and Multipliers buttons will be filled in automatically. 8. Click Continue and the model processing will start. When the model processing is complete click OK, then click Close. 9. Once the model is built, examine the output multipliers. If you are connected to a printer, print them by selecting Reports, choosing the Multipliers tab, and if the To Printer option is not selected, then select the To Printer option, Output option, and Zero Suppressed option, then click Continue. If you are not connected to a printer, go to Edit/Multipliers, select the sector from the list. You will see the individual multiplier column elements from the Leontief Inverse. The actual multiplier for the sector you chose is the sum of the column elements. In the bottom right corner is the column sum. 10. What is the Type I output multiplier for sector 117? 11. What is the Induced effect for sector 117? 12. What is the Type SAM multiplier?

Chapter 17: Case Studies 191

Case Study 2: Single Industry Impact TASK: Create a single industry impact using the computer sector. This will demonstrate the impact of new jobs to a local economy. The scenario is that a “Wood windows and door” firm is adding 200 more jobs to its Washington, MN plant. What is the impact of these new jobs? STEPS: 1. If you have not created a model, then create a model through multipliers by following the steps in Case Study 1. 2. From the model control center, click the Edit button. 3. Select Region Data, then Study Area Data. 4. Click on the View Industry Table tab. 5. Scroll down to sector 117. 6. Examine the data. This is a good way to quickly look up a region’s employment and income for a particular sector. 7. Click the Close icon on the menu bar. 8. At the model control center click on Impacts. 9. Select Ungrouped Events in the groups window if its not already selected. If there are events, click on All which will delete all current events in group. 10. Click on Add New. The cursor will go to the next empty Event Name cell. 11. Give the event a name, call it "Windows". Press the Enter key. 12. Press Enter again to move to the sector cell. 13. Click on the down arrow and select sector code 117. Press the Enter key twice to move the cursor to the employment cell. 14. Enter 200 in the Employment cell. Press the Enter key. What have we done? 15. Make sure Industry is selected in the Basis field. Press the Enter key. Leave the other items alone. 16. Click on the Analyze button. You will see "Computers" under Event Name and the Ungrouped Events highlighted in the list box.

192 Chapter 17: Case Studies 17. Make sure the Level cell is set to 1.00. 18. Place your cursor on the Impact Name field and enter a name. Call it "Computer Run." 19. Click on Run Impact. 20. When the Impact Analysis is completed, click Yes to view the results. 21. You will see your output results. Click on the other results options (value-added, employment) to change the view. 22. You could now go to reports and print these like we did in Case Study 1. 23. What is the total impact for: Output Employment: Labor Income: 24. Close the results window and change the computer event Basis from Industry to Commodity and rerun the impact 25. Write down the total impact: Total Impact: Output: Employment Labor Income: 26. Why is there a difference? 27. Close the results window and change the computer event back to Industry and change the Year to 2004 and rerun the impact 28. What is the total impact: Output: Employment Labor Income: 29. Why is there a difference? Hints for Step:

Chapter 17: Case Studies 193 14. We have entered the number of new jobs we are expecting in Larimer County for industry 117. This will allow us to examine the contribution that firm makes to the Larimer County economy. This value could also be entered as a negative value if it reflects jobs leaving the county. 26. The difference is due to entering the event as a commodity change as opposed to an industry change. In an industry change, all of the impact is on the industry or set of firms. In a commodity change, we are affecting a good or service. There can be numerous producers of a particular good or service so the impact gets spread around to all producers of the commodity. Since different industries are now being affected, the results will likely be slightly different. There are also non-industrial suppliers of commodities that are not included in the inversion. These suppliers consist of households, government, and capital. Any commodity change to these sectors will be lost to the model. 29. The difference arises from using the 2004 deflator. The deflator reflects the increasing cost of windows.

194 Chapter 17: Case Studies

Case Study 3: Multiple Events and the Use of Margins TASK: Create an analysis of a golf course development. The groups are in your model library. This demonstrates how to do a simple multi-event analysis, import groups from the library, and introduce the concept of margins and the construction sectors. STEPS: If you have not created a model, then create a model through multipliers by following the steps in Case Study 1. 1. From the Model Control Center, click on Impacts. 2. First we want to set up an group for construction. There will be two events in this group. 3. Click on Add New. 4. Type “Contractors”, press the Enter key, then press the Enter key again to move to the Sector field. 5. Select sector 33 by clicking the button. Press the Enter key. 6. Press the Enter key again to move to the Value field. 7. Enter 9,000,000 and Click on Add New. 8. Type “Furnishings”, press the Enter key, the press Enter again to move to the Sector field. 9. Select sector 363, press the Enter key. 10. Enter 1,300,000 (you don’t need the comas), press the Enter key, and again press the Enter key. 11. At the Basis, select Commodity. 12. Move to the Margin column and select Household. 13. Click Create in the Group option box. 14. Name it “Construction Expenditures”, click OK. 15. Select Ungrouped Events in the Group option box. 16. Click All in the Event options box to delete all events in the group.

Chapter 17: Case Studies 195 17. Click Add New and enter the following information for Golf Visitor Expenditures. Event Name Retail Eating & Drinking Lodging Golf Fees

Sector 409 481

Value 22 60

Basis Commodity Industry

479 478

75 40

Industry Industry

Margin Household

%Local 100% 100% 100% 100%

Leave Employment, Deflator and Year on default. 18. Click Create in the Group option box. 19. Name it “Golf Resort Visitors” click OK. 20. Click the Ungrouped Events and click All under the Delete options. 21. Click Golf Resort Visitors group. Review the entries. 22. Open the margins by clicking the Edit button next to the Margin type field in the “retail” event. Are margins used for services? 23. Why do we need margins? 24. Run the analysis. Click Analyze. 25. Select Construction Expenditures and set the Level to 1.00 (it should already be the default). 26. Click on Impact Name and enter “Golf Course Construction”. 27. Click Run Impact. Click No when done. 28. Select the Golf Resort Visitors group and set the Level to 30,600. Click on Impact name and call it “Golf Course Visitors”. 29. Click Run Impact. Click Yes when done. 30. From the Impact Results screen select your runs and write down the following results. Golf Course Construction Total Output (for all sectors) Total Employment Total Labor Income

Golf Course Golf Visitors

Total

196 Chapter 17: Case Studies 31. For the total column, you can add across the rows. Try creating a project and running both impacts together. You can check your summation. 32. Close the Results screen. Click on the Projects Tab. Click on “Construction Expenditures” in the Groups to Add list box. Click the << button to move the group to the Projects list box, it will ask for a Project Name. You can leave it “Project 1”. Click OK. 33. Click on “Golf Resort Visitors” in the Groups to Add list box and click the << button. 34. Click Analyze. Select “Project 1”. Click on Impact Name call it “Both” and then click Run Impact. Hints for Step: 22. Margins are used only for goods purchased at a retail level. This does not include eating and drinking or services. 23. We need margins since these purchases are being made at the retail level using retail (purchaser) prices. IMPLAN models are all in terms of producer prices so the purchaser values must be converted into producer prices. Note that when we use margins, we need to specify the producer of the commodity being bought, and not the retail sector that is selling the commodity.

Chapter 17: Case Studies 197

Case Study 4: Using Groups and Household Final Demand Change TASK: Examine the impacts of a military base closure. This demonstrates using the personal consumption expenditure vector from the model as a group. We are going to examine three different groups of events for this particular analysis. There are two impacts. The first is the loss of the income earned and spent by the base workers. We will assume that there are 2,500 employees at the base with payrolls of $75 million and all employees will leave the region. The second is the loss of a $10 million contract by a local food producer. We want to first examine the effects of losing a military base. STEPS: 1. If you have not created a model, then create a model through multipliers by following the steps in Case Study 1. 2. We will assume that payrolls (salary only) at the base are $75 million and all employees will leave the region. The disposable income factor is 70%. We need to apply a disposable income factor to the payrolls data so we exclude the income used to pay taxes and savings. 3. Start at the Model Control Center. 4. We need to import the household consumption function from our model as a group of events. This will allow us to estimate the impacts of the income received by the military base employees. Click Impacts. Delete any old groups or events. 5. Click Import. 6. Select the Institution tab. 7. Select "Households – 35-50k". We are going to use the spending pattern of these households as a proxy for the military base employees. 8. Click Import. 9. Click OK when it is Imported Successfully. 10. Click Close.

198 Chapter 17: Case Studies As an alternative you can set up an event and select a household category from the sector selection list box. 11. We now want to estimate the impacts. Click Analyze. 12. Select the "Households” group. 13. Click Group Level. Enter the disposable income. 14. Click Impact Name. Enter "Employee Spending." 15. Click Run Impact. Click Yes when the impact is completed. 16. Select Employee Spending from the Impacts list box. 17. Select the Employment option. 18. What is the employment loss? Direct: Indirect: Induced: Total: 19. Close the results screen. We now want to examine the loss of the food processor. Create a new event to represent the $10 million food processing contract loss. 20. Select Ungrouped Events from the Groups list box. If there are any events in the ungrouped events, click All from the Event Options, Delete options box. 21. Click Add New under Event Options. 22. Enter the name "Food Processor", then press Enter, then Enter again. 23. Select industry 62 (Fluid Milk) with either the pull down menu, (click the down arrow and scroll to sector 62) or enter "62" and press Enter. 24. Enter 10,000,000 in the Value cell. Note that you do not have to enter the commas in the value cell, but if you do, the software will accept it. Press Enter. 25. Check that Industry is selected in the Basis field, if not click the drop down box and select Industry. 26. Under the Groups option box, click Create.

Chapter 17: Case Studies 199 27. Enter the name "Food Processors" and Click OK. 28. Click Analyze and run the Food Processors group. Note: accept default level of 1.0 as $10 million was already specified under the event. 29. View the results. What is the employment loss? Direct: Indirect: Induced: Total: 30. What is the total employment loss from both the payrolls and the milk industry? 31. How else might the local economy be affected? Hints for Steps: 13. The disposable income should be $63,750,000 the result of multiplying our disposable income factor (70%) * payrolls of $75,000,000. 31. There might be additional losses the economy would face that an impact assessment would not capture. For example, with potential out-migration of military workers, tax collections would likely decline. You may also want to print the tax impact report and run the losses through the state and local government expenditures vector. Housing values might decline since there might be a flood of houses on the market. On the up side, it might rally the community together to enhance their economic development prospects. These types of issues, even though they cannot be easily modeled, should also be considered.

200 Chapter 17: Case Studies

Case Study 5: Analyzing A New Industry TASK: What do we do if we have a new industry moving into the study region and the industrial sector does not exist in your model. This section demonstrates importing a production function as a final demand group as well as the treatment of employees. This also involves a discussion on what the direct impact actually represents. The scenario is that we have a new company in an existing sector 280. The company will have $10,000,000 in sales and employ 100 people with a payroll of $3,000,000. Use a disposable income figure of 0.70. STEPS: 1. If you have not created a model, then create a model through multipliers by following the steps in Case Study 1. 2. The first method is to use the importing from the model feature to create an impact using a group of events to represent the industry. 3. Click Impacts. 4. Click Import. 5. Select the Industry tab. 6. Click on the list box and enter 319 and click Import. 7. Click OK, then Close. 8. Click Analyze. 9. Select "280 Metal Cutting Machine Tools" from the groups list box. 10. Click on the Group Level text box and set the value to 10,000,000. 11. Click on the Impact Name box and type "Metal Cutting Tools." 12. Click Run Impact. 13. When the impact is finished, click Yes. 14. Select "Metal Cutting Tools" from the list box. What is the direct output impact? What happened to the rest of the $10 million? Estimate the effects of "Metal Cutting Tools" employee spending. Assume that all employees are new to the region.

Chapter 17: Case Studies 201 15. From the Model Control Center, click Impacts. 16. Click Import. 17. Select the Institution tab. 18. Select "Households – 35-50k" Click Import. 19. Click OK. 20. Click Close. 21. Run the analysis using the payrolls adjusted for the disposable income factor and examine the results. What should the group level be set to? 22. What is the total employment impact? Another way to test this is to make the industry exist by editing the region data and adding employment, income, and output to the nonexistent sector and make it exist. Try this without hints. Hints for Steps: 14. A portion of the $10 million gets spent on value-added elements (wages, profits, etc.). Another portion gets “lost” to imports since not all goods and services the company purchases come from local sources. The value of the imports is noted in the last row, “Trade” of the direct effects output report. Also, doing an impact in this manner changes the definition of direct and indirect slightly. When we enter a $10 million dollar change in the usual way, by selecting the industry in the event window, we would see the $10 million as a direct effect. The direct effects table is now really the same as the first round of the indirect effects. The indirect effects are all subsequent rounds of the indirect. The induced effects are only from the employment of the indirect impacts. We have ignored the induced effects of the 100 workers in this new business. We can estimate this separately. 22. Set the Group level to $3,000,000 * 0.70 = $2,100,000.

202 Chapter 17: Case Studies

Case Study 6: Using Projects and Survey Data: The Impact of a Local College TASK: Examine the impacts of a college or university on a local economy. This demonstrates using the private education sector compared to using the state and local institution expenditure pattern. It also illustrates the use of survey data in the impact analysis. STEPS: 1. If you have not created a model, then create a model through multipliers by following the steps in Case Study 1. 2. First examine the effects of the college expenditures on goods and services. Do this by importing the State and Local expenditures vector. From the Model Control Center, click Impacts. 3. Click Import. 4. Select the Institution tab. 5. Select the State/Local Government Education. 6. Click Import. 7. After Imported Successfully click OK. 8. Click Close. 9. Select State/Local Government Education from the groups option box. You can scroll down and examine the types of expenditures made on average. At this point, you could also edit the expenditure pattern. Note that the %Local has been set to the model’s regional purchase coefficient. This means that some of the direct spending will leak out of the region. 10. All the expenditure events will sum to 1.0. We now wish to estimate the impacts of a $25 million college operation - Click Analyze. 11. Select the State/Local Education group. 12. Click the Group Level field and type 25,000,000. 13. Click in the Impact Name field and type in “SL College Education”. 14. Click Run Impact.

Chapter 17: Case Studies 203 15. Acknowledge Impact analysis is completed..." - Click Yes. 16. Select SL College Education. 17. What is the sum of the Direct Effects column? 18. The direct effects add up to $25 million, but how much of it is trade? 19. Do all sectors have indirect or induced effects? Note that all direct payments to sector 11001 and higher have no indirect or induced effects. Their direct effects are also are leakages from the local economy. 20. Which industry has most of the direct employment? 21. Look at the individual industry impacts-are these reasonable? State and Local Education" actually contains the expenditure patterns for all levels of public education - elementary through college. What if we were to use private college education IMPLAN sector 462 as a proxy for public college? This section will illustrate how results differ. 23. Close the Results window and go back to Impacts. 24. In the main Impact window, select the Ungrouped Events and delete any and all events that exist by clicking All under the Delete option. Make sure Ungrouped Events is highlighted, otherwise you will be deleting an existing group. 25. Place the cursor in Event Name field, or click Add New, and type "College". Press Enter, and then Enter again to move to the next field. 26. In the Sector field, type 462 and press Enter. 27. In the value field type 25,000,000 and press Enter. 28. Select Industry in the Basis field. Click on the Create a Group button and call it “Private College”. Go back to Ungrouped Events and click All under the Delete options. 29. Click Analyze. 30. Select the “Private College” group. 31. Move to Impact Name and type "Private College Proxy." 32. Select Run Impact. 33. Click Yes.

204 Chapter 17: Case Studies 34. Select Private College Proxy. 35. What is the difference between these runs? 36. Which method yields the greatest impacts? Now examine the student spending. Suppose we have done a survey of students and have found the following purchasing patterns. Since we did this study for use in IMPLAN, we remembered to ask about local purchases and what types of commodities were bought. The following table contains the data. The assumptions are that the students are in school for 200 days, and there were 5,000 students during the school year. The data in the table is filled out as follows: the local spending of $1.50 * 200 days * 5,000 students equals a total of $1,500,000 in meals in town expenditures. You will need to look up the IMPLAN sector in Appendix A of the software manual. 37. Fill in the table:

Meals bought in town Beer from a store Stationary Parking Auto Gas Newspapers

Per Student Spending $1.50

Value

Sector

Basis

Margin

%Local

$0.75 $2.00 $1.75 $1.15 $0.12

38. We want to set up an impact event to estimate the effects of this spending. These are all purchaser prices so margins will be needed (see the manual for discussion of margins). Try to set up the event on your own. If you have trouble, the following will walk you through this exercise. 39. Delete All Visible events. 40. Click on Ungrouped Events. 41. Next set up the student purchases. Click on Add New. 42. Enter "Meals", press Enter to set the value, then Enter or Tab to move to the next cell. 43. Enter 481, or click on the down arrow and scroll to 481, press Enter to close the scroll box and Enter or Tab to move to the next cell.

Chapter 17: Case Studies 205 44. Enter 1,500,000 and press Enter. The direct employment will show. Press Enter again. 45. Select Industry from the drop down box. Press Enter and Enter again to move to the Margin box. For sectors needing margins, select commodity. 46. Click on the down arrow and select Household. You will get a warning screen that there are no margins for this sector (because meals are purchased from the producer). Click OK. If the margins exist, Household will stay selected. (Remember to click on the margin field to select the type of margin you want.) Reset the Basis to industry for the “Meals” event. 47. Do the rest of the student-spending table like above. You may get “Industry does not exist in this model”. This is ok, simply accept. Since we are margining, the margin sectors which do exist will still get the correct impact. 48. When you are done entering the data, click the Create button in the Groups option box. 49. Give the group a name, try "Student Spending". Click OK. Save this to the library. Select Import/Export from the menu bar. Click Export, and Group to Library. Select "Student Spending," Click Save. Click OK. Click Close. You don't need to do this every time you create a group. You can do this when you want to use a group in a different model. 50. Run the analysis and examine the total employment change, and total labor income: The last step is to examine the spending of the faculty and other employees. There are 450 faculty working at the University, and 350 civil service employees. The faculty payroll is $22,500,000, and the civil service payroll is $7,000,000. Disposable income ratios for high and medium income are 65% and 75% respectively. 51. Click Impacts. 52. Click Import. 53. Select the Institution tab. 54. Select Households $75k to $100k -the faculty. 55. Click Import. 56. Click OK.

206 Chapter 17: Case Studies 57. Select Households $25k to $35k (of Households Medium Income)-the civil service workers. 58. Click Import. 59. Click OK. 60. Click Close. THE NEXT PART DOES NOT CONTAIN HINTS. IF YOU HAVE TROUBLE REFER TO PREVIOUS EXERCISES. 61. Run the analysis using the payrolls adjusted for the disposable income factor. What is the faculty disposable income that you will enter in the Group Level? What is the civil service staff disposable income that you will enter in the Group Level? 62. What is the total employment impact for faculty? 63. What is the total employment impact for civil service? 64. Close the Results window and get back to the Impacts window. Click the Projects tab. It should not be grayed out at this point. 65. Highlight the Households $75k to $100k group under the Groups to Add. Click on the Add Groups to Project arrow button. Give the project a name "Project 1". Highlight the Households $25k to $35k group and click the << button. 66. Click Analyze. 67. Select the Projects tab. Highlight Project 1. You should see the two groups along with their group level you gave them earlier in this exercise. You can click on either of the groups and edit the group level if you wish. Leave them as they are for now. Leave the project level at 1.0. Name the run "Both" and click Run Impact. 68. What is the total employment reported value? Hints for Steps: 18. Two things, first we specified %Local to the model RPCs, this allow leakage of some of the direct effects out of the area. Second, any commodity-based event has the potential to lose some impact since there are non-industrial suppliers of many commodities that are not counted by the multipliers. This will show up as trade. 21. Stay on the Employment option and look at the distribution of jobs by the different sectors. Sector 503 "State and Local Education" has the greatest number of direct jobs.

Chapter 17: Case Studies 207 Look at the Output tab, scroll down the list and examine the industries selling to the college. There are a large number of different sectors involved, some only marginally. The bulk of the impact is the college wages (sector 503 output is equal to the value of employee compensation). Some other impacts are in sector 458 "Services to builidings." This represents landscaping and other maintenance. Others are sector 30 "Power generation," and sector 390 "Wholesale Trade." This represents an average buying pattern for a school. 35 The direct output change for the “Private College Proxy” is $25 million because we entered $25 million as an industry and left the LPC=NO. The direct output change for the “SL Govt Education” case is also $25 million, but it shows up in the level. The direct effects for the “SL Govt Education” case is really the first round of the indirect effects. Within this column are payments to SL Ed teachers (sector 503). This makes the indirect effects (direct + indirect in this case) much higher than the $8 million of the “Private College Proxy”. 37. Per Student Spending $1.50

Value $1,500,000

Sector 481

Basis Industry

Margin No

%Local 100%

$0.75

$750,000

86

Commodity

Yes

$2.00

$2,000,000

133

Commodity

Yes

Parking Auto Gas

$1.75 $1.15

$1,750,000 $1,150,000

490 142

Industry Commodity

No Yes

Newspapers

$0.12

$120,000

413

Commodity

Yes

Model RPC Model RPC 100% Model RPC Model RPC

Meals bought in town Beer from a store Stationery

60. The value to use as the level for the high income run is: $22,500,000 * 0.65 = $14,625,000. The low income run is: $7,000,000 * 0.75 = $5,250,000.

208 Chapter 17: Case Studies

Case Study 7: Effects of Changing Regional Purchase Coefficients (RPCs) TASK: Regional Purchase Coefficients (RPCs) define the trade flow in a region. For each commodity in the model, the RPC represents a percentage of local demand met by local producers. For example, if local demand for lumber is $100, an RPC of 0.40 indicates that 40%, or $40, of local demand is met with local supply. The rest of demand is imported. We want to examine the effects of changes in RPC’s. on various sectors. STEPS: 1. If you have not created a model, then create a model through multipliers by following the steps in Case Study 1. 2. First check the default RPC for Hotels and motels (sector 479). 3. From the Model Control Center click Edit and then Regional Purchase Coefficients. 4. There are two ways to view the RPCs, either the Commodity Detail view which gives information on the calculation of commodity supply and demand, or the Commodity Table view which only gives the supply/demand pooling ratio and the RPC. Choose the one that best suits you. 5. Write down the value of the RPC for sector 479. 6. Check the Type SAM Output multiplier for sector 479 7. Does the Hotels and motels RPC seem too high? 8. Change the RPC to 0.04 and rerun the model. From the Edit Regional Purchase Coefficients screen, select industry 479. 9. Change the value to 0.04. 10. Close the Edit screen. 11. Click OK. 12. Click Construct Model. 13. Click Continue. Click Close. 14. Check the Type SAM output multiplier for sector 479, did the change make much difference on the multipliers?

Chapter 17: Case Studies 209 Now change the RPC of an industry that has more linkages within the region. 15. Create a new Washington County model. 16. Check the RPC for industry 11 which includes dairy farms. 17. Check the multiplier value for sector 62 Fluid milk by closing the RPC edit screen and clicking EDIT and MULTIPLIERS and selecting industry 62. 18. Lets assume that that 62 Fluid milk gets as much local raw milk (sector 11) as possible. 19. Change the RPC value to 1.00. What happens? 20. Reset the Dairy RPC value to 0.8 and rerun the model. Once the model is run check the multiplier for sector 62. 21. What is the impact of changing the RPC? Hints for Steps: 7. Yes, the RPC means local purchases of local production. How many local people stay in hotels in their hometown? Likely not many. 14. No it did not. This is because very few industries use Hotels and Lodging to any great extent. The fewer the linkages, the lower the multiplier. 19. You exceeded the RPC constraint of .802 21. The RPC has been increased, leading to more local interaction. Dairy is used heavily by fluid milk producers so there is more interaction in the local economy with dairy than there was with the hotels and motels example.

210 Chapter 17: Case Studies

Case Study 8: Creating an Aggregated Model TASK: Create an aggregated model and compare it to an unaggregated model. This demonstrates the use of the aggregation template and some of the dangers in aggregation. STEPS: 1. Start with no models open. Click File/New or the New File button. 2. Give the file a name, “Washington Agg”. 3. Click Save. 4. Select a file from the data directory (Washington 2001). 5. Click Continue. 6. When the study area is done, click OK. 7. Select Model from the top menu bar. 8. Select Aggregate. 9. Click Library. 10. Select the 2 Digit NAICS template, and click Import. 11. Select one of the imported aggregated sectors and examine the contents. 12. Click Aggregate. 13. A warning screen will appear. Once a model has been aggregated, it cannot be unaggregated. You will need to build a new model if you want an unaggregated version. One safe solution is to use File/Save As and give the model a new name prior to aggregation and you will have a clean copy of it. In this case, just click Yes. 14. When the aggregation is complete, click OK. 15. Click Close. 16. Continue building the model as before. Look at the reports, run a test impact. 17. What are the advantages to an aggregated model? What are the disadvantages?

Chapter 17: Case Studies 211 Hints for Steps: 17. ADVANTAGES: There are two advantages, speed and model manageability. An aggregated model will run and invert much faster than an unaggregated version. Also, if you want to examine a model for education purposes, a small (2 digit NAICS) model is very easy to examine. You can put it in a spreadsheet and view the entire set of accounts (see Tips Page). DISADVANTAGES: One disadvantage is that you lose industry detail. Another is that an aggregated model will be different than an aggregated model unless you specify supply/demand pooling as the method of estimating trade flows. If you decide not to aggregate the model, you can always still aggregate the impact reports by applying a template to the report.

212 Chapter 17: Case Studies

Case Study 9: Advanced Features TASK: This example steps through the model building process using the Advance features tab. The advanced features allow for editing the model as it is being built. If you want to edit several different parts of the model, such as production functions, byproducts, and regional purchase coefficients, you should use the advanced features. If you build a model and then decide to edit any portion of the model, you will need to re-run the model. After you make your edit change, the software will prompt you to re-run. The model will only be re-run from your edit point. STEPS: 1. Create a new model, click File/New Model or click the New File button. 2. Give the model a name, “Larimer”. 3. Select your study area. 4. Click OK when the study area has been built. 5. Click Construct Model. 6. Click Advanced. The software will process the model through the production functions. 7. Production Functions: At this point, you either Edit Existing Model Production Functions, Edit Library Production Functions, or Import a Production Function From The Library. 8. Click Next>> to finish processing the production functions and process the byproducts. 9. Byproducts: You can change an industry’s production of commodities at this stage. Click the Edit Byproducts button and then click the sector you want to edit. You can change the byproducts value. The sum of the values has to be equal to 1.0. You can change one value and then use the Balance button to scale all others so the sum is 1.0. Click Close when done. Then click Next>> to go to the next stage. 10. Trade Flows: This allows editing of the regional purchase coefficients. Supply/demand pooling maximizes the trade flows. The RPC selection has either Max, First, or Average. This only applies to multi-state models. This corresponds to how the

Chapter 17: Case Studies 213 observed RPCs are utilized when creating a multi-state model. Max uses the maximum observed value from all states, First uses the observed values in the first state on the list. Average uses the average value. We also have a location quotient option as well. 11. Click Next>> to process the trade flows and move to the next stage. 12. This state will allow editing of the inter-institutional transfers data prior to creating the SAM accounts. Click Edit to modify the SAM data. This is the only place you can edit the SAM data. This should be done only if you thoroughly understand the SAM. 13. The next stage is the multipliers options. You can select Type I, II, III, or SAM. For the Type II, you can select either the default income (SAM income) or specify your own disposable income. 14. At any point during the advanced model construction, you can select Continue and the model will process from that point using the defaults. At end of the Institutional Transfers stage, you can also select Close and process the multipliers later.

Literature Review

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L I T E R A T U R E

Literature Borgen, Herdi and Stephen C. Cooke; “Income Multipliers for Idaho from Implan Data”; from Proceedings; IMPLAN; May 2022 1991, from Western Rural Development Center, OR State Univ., Corvallis, OR. Charney, Alberta H. and Julie P. Leones; “Free the Type II Multiplier!”; Paper presented at the 1996 Western Regional Science Association Meetings, Napa, CA 1996. Hanson, Kenneth A., and Sherman Robinson, “Data, Linkages, and Models: U.S. National Income and Product Accounts in the Framework of a Social Accounting Matrix”, Economic Research Service, U.S. Department of Agrinculture, July 1988. Hoover, Edgar M, and Frank Giarratani. An Introduction to Regional Economics. New York: Alfred A. Knopf, 1984. Jack Faucett Associates. 1983. “The Multiregional Input-Output Accounts, 1977”; vols I-IV; Report submitted to the U.S. Dept. of Health and Human Services, Contract#HHS-10081-00-57, July 1983. Kehoe, P.J. and T.J. Kehoe. 1994. “A Primer on Static Applied General Equilibrium Models.” Federal Reserve Bank of Minneapolis, Quarterly Review 18 (1994): (2):2-16. Leontief, Wassily et al. Studies in the Structure of the American Economy. New York: Oxford University Press, 1953. Lindall, Scott, Greg Alward, Jay Sullivan, and Anwar Hussain. 1995. “IMPLAN SAM: A Social Accounting Matrix for Regional IO Systems”. Paper given at the Mid-Continent Regional Science Association Meetings (Note: this paper is available off of the IMPLAN web site: www.implan.com.) Lindall, Scott A. and Douglas C. Olson, Micro IMPLAN 1990/1985 Database Documentation. Minnesota IMPLAN Group, Inc., Stillwater, MN. May 1993.

216 Literature Review Miller, Ronald E., and Peter D. Blair. Input-Output Analysis Foundations and Extensions. Prentice-Hall, Englewood Cliffs, New Jersey, 1985. Polenske, Karen R. 1972. “Implementation of a Multiregional InputOutput Model for the U.S.”; Input-Output Techniques ; Eds. A. Brady and A.P. Carter; North-Holland Publishing Co. 1972 pp171-181. Pyatt, Graham, and Jeffry I. Round. Social Accounting Matrices, A Basis for Planning, The World Bank, Washington, D.C., 1985. Rickman, Dans and R.Keith Schwer. 1995. “A comparison of the multipliers of IMPLAN, REMI, and RIMS II: Benchmarking ready-made models for comparison”; in The Annals of Regional Science; Vol 29; pp363-374. Rutherford, T.F. 1994. “Applied General Equilibrium Modeling with MPSGE as a GAMS Subsystem”. Department of Economics Working Paper, Univ. of Colorado. 44 p. Rutherford, T.F. 1993. “MILES: A Mixed Inequality and Nonlinear Equation Solver”. Department of Economics Working Paper, Univ. of Colorado. 43 p. Shoven, J.B. and J. Whalley. 1972. “A General Equilibrium Calculation of the Effects of Differential Taxation of Income from Capital in the U.S.” Journal of Public Economics 1(1972):281-321. Shoven, J.B. and J. Whalley. “Applied General Equilibrium Models of Taxation and International Trade: An Introduction and Survey”. Journal of Economic Literature 22.9 (1984):10071051. Shoven, J.B. and J. Whalley. Applying General Equilibrium. New York: Cambridge University Press. 1992. P. 299. Stevens, B. and G. Trainor. “Error Generation in Regional InputOutput Analysis and Its Implications for Non-Survey Models”, Ed. S. Pleeter: Economic Impact Analysis: Methodology and Applications., Amsterdam: Marinus Nijhoff. 1980 p.68-84. Tolbert, Charles and Mary Kizer. 1987. “Labor Market Areas for the U.S.”, USDA ERS Staff Report AGES87072. August, 1987.

Literature Review

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U.S. Department of Commerce, “ Definitions and Conventions of the 1977 Input-Output Accounts”, Unpublished Report, Bureau of Economic Analysis, Washington DC. U.S. Department of Commerce, “1996 Consumer Expenditure Survey, Diary and Survey”, Computer Diskettes and Unpublished Data, Bureau of Labor Statistics, Washington DC, 1990. U.S. Department of Commerce, “1996 Regional Economic Information System Data”, Computer CD, Bureau of Economic Analysis, Regional Measurement Division, Washington DC, 1991. U.S. Department of Commerce, “Definitions and Conventions of the 1972 Input-Output Study”, BEA Staff Paper, Bureau of Economic Analysis, Washington DC, July 1980. U.S. Department of Commerce, “1996 Survey of Government Finances”, Computer Tape, Bureau of Census, Washington DC, 1991. U.S. Office of Management and Budget, Standard Industrial Classification Manual. National Technical Information Service, Washington D.C., 1987.

BOOK 3: DATABASE GUIDE

Chapter 18: Introduction 221

C H A P T E R

1 8

INTRODUCTION This book provides a technical discussion of data methodology. It assumes an understanding of input-output terminology. The Analysis Guide provides conceptual overviews of input-output and impact analysis with terminology definitions. IMPLAN databases are constructed exclusively by Minnesota IMPLAN Group and are designed for use with IMPLAN Pro software. This manual describes the construction of the databases in detail. Databases are available for all 3,000 plus counties in the United States with numerous economic and demographic variables at a 509 industrial sector level (4-6 digit NAICS). Variables include employment, value-added, government purchases, and household purchases. A variety of wealth and transfer data is also incorporated. This data allows for construction of a complete set of social accounting matrices (SAMs). This document will: Provide an overview of MIG’s database construction techniques; Document the procedures to estimate each component of the *.ODF data files; Document the formation of the national matrices and tables; Discuss data accuracy, implied assumptions and other validation considerations.

How Book 3 is Organized Chapter 19 “Organizing the Data” is an overview of the data construction process and provides some general information about the IMPLAN data files. Chapter 20 “Employment” defines the employment data elements and describes data sources and procedures for estimating non-disclosures. Chapter 21 “Value-Added” defines the four components of valueadded and describes their data sources.

222

Chapter 18: Introduction Chapter 22 “Output” defines output and describes its data sources. Chapter 23 “Final Demands” defines the components of IMPLAN final demands and describes their sources of data. Chapter 24 “Inter-institutional Transfers” defines the structure of the SAM framework and SAM data development. Chapters 25 “National Matrices and Tables” describes the construction of the national use and make tables which are incorporated into each regional model. This chapter also covers regional purchase coefficients and national average deflators and margins. Chapter 26 “Database Validation” describes efforts to check data and developed models required assuring credibility and confidence in model results. Also “force-account construction” is discussed.

Chapter 19: Organizing the Data 223

C H A P T E R

1 9

Organizing the Data IMPLAN data, prior to processing, comes from many sources and different formats. It comes as published data, sets of relationships or ratios, numbers with unique units, or as estimates. Constructing a database means gathering data from all these sources, converting it to a consistent format, and estimating the missing pieces, all the while controlling it with other data to maintain accuracy. This chapter presents an overview of the construction process and provides some general information about the data files. This chapter discusses: Database Construction *.ODF components National Matrices and Tables Sectoring Schemes

Database Construction There are three different levels of data; national, state, and county. Raw data availability differs with each level. At the national level, each database component is available. At the state level data, some raw data is available. At the county level, employment, employee compensation, proprietary income, population, federal and state expenditures and selected wealth data are available, while other county data is estimated. At the Zip code level only County Business Patterns and demographic data from the Census Bureau are available. Each year, MIG gathers data at the national level, converts it to IMPLAN data format and derives new national I/O matrices (use, make, by-products, absorption, and market shares) as well as national tables for deflators, margins and RPCs. Then state level data is gathered and controlled to the national totals, and county level data is gathered and controlled to state totals. The state and county I/O matrices are not estimated as part of the data development process as IMPLAN software creates region specific matrices during the model creation stage.

224

Chapter 19: Organizing the Data In Figure 19-1, the shaded areas indicate data provided in the IMPLAN data files. The IMPLAN software estimates the remaining cells.

Value Added

Factors

Total Institution Outlay

Total Capital Outlay

Total Trade Outlay

Total Industry Outlay

Total

Total Factor Outlay

Exports

Exports

Exports

Total Industry Income

Exports

Total Trade Income

Total Capital Income

Total Enterprise Income

Total Institution Income

Total Factor Income

Total Commodity Income

Total

225

Trade

Transfer

Consumption

Capital

Imports

Total Enterprise Outlay

Transfers

Enterprises

Trade

Imports

Transfers

Consumption

Institutitons

Exports

Factor Trade

Transfers

Factors

Transfers

Total Commodity Outlay

Sales

Make

Commodity

Capital

Enterprises

Institutions

Use

Commodity

Industry

Industry

Figure 19-1: Regional IMPLAN Data

Chapter 19: Organizing the Data

226

Chapter 19: Organizing the Data IMPLAN data from MIG consists of .ODF files with county (and/or state) level and national level data and a set of national I/O matrices and tables.

MID.ODF Components There are six main components of an IMPLAN *.ODF data file. The next chapters will deal with the methodologies involved with the data derivation for each component. These are: 1. Employment 2. Value-Added (Factors) 3. Output 4. Final (Institutional) Demand 5. Inter-Institutional Transfers 6. National Structural Matrices All value-added, output, and employment information are on an industry basis. There are four sub-components of value added, also known as factors. These are: 1. Employee Compensation 2. Proprietary Income 3. Other Property Type Income 4. Indirect Business Taxes Final Demand, also known as Institution Demand, consists of households and government purchasing goods and services for their own use. This also includes exports. There are 13 institution subcomponents. These are: 1. Household Personal Consumption Expenditures (PCE) – nine income levels (starting with 1996 data) 2. Federal Government Military Purchases 3. Federal Government Non-Military Purchases 4. Federal Government Non-Military Investment 5. State and Local Government Non-Education Purchases 6. State and Local Government Education Purchases 7. State and Local Government Non-Education Investment

Chapter 19: Organizing the Data 227 8. Inventory Purchases 9. Capital 10. Foreign Exports 11. State and Local Government Sales 12. Federal Government Sales 13. Inventory Sales All institution demand in the original data is measured on a commodity basis.

National Matrices & Tables The national I/O matrices are: Use Make Absorption By-Products Market Shares In addition to the national I/O matrices, MIG IMPLAN data files include a number of tables: Margins Deflators RPCs A discussion of the methodologies used to derive these matrices and tables is in the Analysis Guide.

Sectoring Schemes Throughout the database development discussion, reference will be made to different industrial sectoring schemes such as the IMPLAN scheme, or the REIS scheme. These are all ways to classify data. In general, an industrial classification scheme allows categorization according to the type of products or services produced. All employment and value-added data used in IMPLAN has its origins in a report or survey of a single establishment. An establishment may be a small business with a single location, or it

228

Chapter 19: Organizing the Data may be a branch location of a large firm. Each establishment is counted separately on the Unemployment or Social Security rolls. The establishment either submits an unemployment report or responds to a census or a survey and is counted by the data collection agency. That agency assigns the establishment a code depending on the primary type of product produced by that establishment.

North American Industrial Classification System (NAICS) Codes The most common scheme is the federal government’s 6-digit North American Industrial Classification Systems (NAICS codes) as described in the 2002 North American Industrial Classification Systems Manual. The Office of Management and Budget publishes the NAICS manual. This scheme has five levels of detail using numbers to refer to detail level with 2-digit detail as the most aggregated and 6-digit detail the least aggregated. While the CEW/ES202 employment and income data is reported at this level, most data is not. Starting with the 1997/98, many US data series converted to the NAICS from the Standard Industrial Classification system (SIC). NAICS itself has already gone through its second incarnation. There are two versions: 1997 and 2002.

Regional Economic Information System (REIS) Sectoring Another other major data set used to derive IMPLAN databases is from the Bureau of Economic Analysis’s Regional Economic Information System (REIS). Their sectoring scheme is a modified 3digit NAICS scheme. Most modifications are in the government sectors and use of several 2-digit codes.

Bureau of Labor Statistics Sectoring Data from the Bureau of Labor Statistics (BLS) is used for deflators and some output estimates. The BLS uses a different sectoring scheme, again based on the SIC code system. As of publication of this manual the BLS has not converted to NAICS.

Bureau of Economic Analysis Input-Output Sectoring This 508-sector scheme is the basis for the Bureau of Economic Analysis’s Benchmark Input-Output Study. This scheme is nearly 6 digit NAICS for manufacturing, and more aggregate for service

Chapter 19: Organizing the Data 229 sectors. By necessity IMPLAN’s sectoring is very similar. The major difference is the number of retail sectors. The 1997 BEA scheme for the BEA’s benchmark model is included in the IMPLAN bridge table in Appendix A.

Special Sector Definitions IMPLAN sectors 1-494 are private sector producers with the exception of sector 398 which contains both private post office activities as well as the quasi-private US Postal Service. Public sector producers of goods and services show up in IMPLAN sectors 495-499 and IMPLAN sectors 503-506 are the administrative government sectors. The government sectors are discussed in detail in Chapter 9. Sectors 500-509 are considered special sectors. Of these sectors only 509 contains a production function; hence is the only one which will generate indirect effects Some sectors cause an inordinate amount of confusion. The main culprits are construction, government and special sectors as these sectors do not directly correspond to the NAICS codes. “Owner occupied dwellings” (IMPLAN sector 509) is a special sector developed by BEA. It estimates what owner/occupants would pay in rent if they rented rather than owned their homes. This sector creates an industry out of owning a home. Its production function represents repair and maintenance of that home. There is no employment or employee compensation for this industry. Indirect business taxes is largely made up of property taxes paid by the homeowner and the other property income is the difference between the rental value of the home and the costs of home ownership. Interest payments and mortgage payments are a transfer in the SAM and are not part of the production function for this sector. Its sole product (output) is ownership and is purchased entirely by personal consumption expenditures – i.e., the household sector. This sector is included in the database to insure consistency in the flow of funds. It captures the expenses of home ownership such as repair and maintenance construction, various closing costs and other expenditures related to the upkeep of the space in the same way expenses are captured for rental properties. The utility sectors (IMPLAN sectors 30-32) consist of private sector providers of these services. Public sector providers of these services are included in the government enterprise sectors.

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Chapter 19: Organizing the Data “Education services” (IMPLAN sectors 461-463) are also private sector providers of these services. The public sector counterparts are included in the state and local education sector. “Non-comparable imports” (IMPLAN sector 500) consists of goods that are not available anywhere in the nation. “Scrap” (IMPLAN sector 501) is only a by-product commodity. There is no unique “Scrap” industry. “Scrap” consists of commodities that are cast off as part of a production process and then resold as scrap. “Used and second hand goods” (IMPLAN sector 502) is also only a commodity. It consists of goods that have been previously used and then resold. “Rest-of-world” is sector 507. This consists of net foreign flows of factor income. The “Domestic services” sector (IMPLAN sector 494) consists of producers of household services such as cleaning and maid services. “Inventory valuation adjustment” (IMPLAN sector 508) is an estimate of the value of goods removed from inventory that were produced in a previous time period. Since the value of these goods is different from the value of goods produced in the present time, this adjustment aligns the value of those goods. Note that the agriculture sectors (1-13) now conform directly to the NAICS code. Older IMPLAN databases (2000 and earlier) were commodity based and did not correspond well to the SIC code. Construction sectors (33-45); however, in the current data is based on Census categories rather than NAICS codes. A crosswalk between the 1997 Census of Construction categories and IMPLAN sectors can be found in Appendix G.

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Employment Employment includes total wage and salary employees as well as selfemployed jobs in a region. It includes both full-time and part-time workers and is measured in annual average jobs. In all, there are three different employment data sets used to create the IMPLAN data. Each is used in conjunction with the other since no one data set provides enough information to make a complete IMPLAN database. These data sets are the CEW (Covered Employment and Wages – formerly known as ES202) data, Regional Economic Information System (REIS), and County Business Patterns. A number of IMPLAN sectors require special attention. These are the Agriculture, Construction, and the Government Sectors. They are discussed in the Special Sectors section later in this chapter. In general, CEW data provide the County level industry structure for the IMPLAN database. The County Business Patterns data is used to make non-disclosure adjustments to CEW data, while the REIS data is used for control totals. This chapter discusses: Non-Disclosure County Business Patterns BLS CEW Special Sectors Regional Economic Information System Distributing disclosed 2-digit Employment and Income REIS Data to IMPLAN sectoring FTE

Non-Disclosure Government data made available to the public is subject to nondisclosure rules. This applies when the data reported might disclose the operations of a single firm, and is most likely at the county level. The specific rules for non-disclosure differ depending on the government agency.

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Chapter 20: Employment The government usually will not release information if it might breach the confidentiality of reporting establishments. Though this maintains businesses’ trust in the government's requests for information, it makes the collection of complete data sets difficult. Much of the IMPLAN development time is spent estimating data not disclosed by government sources. To estimate employment, County Business Patterns data are adjusted for disclosure. Next, the County Business Patterns are used to adjust the CEW data for disclosure and the CEW data used to adjust the REIS data for disclosure. The REIS data is expanded to separate wage and salary employment and self-employment. This gives a ratio of self-employed to wage and salary workers. The REIS data is then used as final control totals with the CEW data providing the 6 digit NAICS industry structure.

County Business Patterns (CBP) County Business Patterns (CBP) is a program run by the U.S. Department of Census. There are three primary data sources for County Business Patterns: the Bureau of Census Economic Census, Bureau of Census Annual Survey of Manufacturers, and the Internal Revenue Service Quarterly Payroll File (FICA). The annual employment data is based on first quarter employment. This is a point-in-time estimate and not an annual average. Data at a 6-digit NAICS level of detail includes; total number of establishments, total first quarter employment, first quarter and total annual payroll, and a breakdown of the number of firms for 12 different employment size classes. As might be expected with 6-digit level specification, there are significant disclosure problems. Even when the sector is not disclosed, CBP provides the number of firms by employee size class. The CBP data gives a picture of the industrial structure of a region and is used to adjust the CEW data for non-disclosure. There is a significant time lag, generally three years, between the current year and the most recent CBP data, but an industrial structure generally changes only slowly over time. There are virtually no disclosure problems with the national level CBP data. This national data set is used to help estimate the nondisclosed sectors in the state level data.

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Estimating the non-disclosed sectors in the state level CBP data, requires three steps: 1. Estimate the missing element using the midpoints of the numberof-establishments-by-employee-size-class. This provides an initial estimate. 2. Add the 6, 5, 4 ,3 and 2 digit NAICS elements from the bottom-up to make the first adjustment to the non-disclosed elements with the corresponding NAICS’. This ensures that the 6-digit NAICS’ add to the 5-digit NAICS’, the 5-digit NAICS’ add to the 4-digit NAICS’, the 4-digit NAICS’ add to the 3-digit NAICS’, until finally the 3-digit NAICS’ add to the 2-digit NAICS’. 3. A top-down pass is made next so that non-disclosed elements are adjusted again to ensure that all data add to the overall total. This procedure is performed on the national, state, and county data. This adjusting provides a complete set of CBP employment data that is internally consistent within a county, state, or nation.

BLS CEW The CEW data set is one of the most important used in the IMPLAN database development. This data provides the industry structure for the states and counties. The data is provided by the U.S. Department of Labor as part of the Unemployment Insurance CEW - Covered Employment and Wages Program. The CEW data set provides annual average wage and salary establishment counts, employment counts, and payrolls by county at the 6-digit NAICS code level. This data is collected from a federal/state partnership program. Data is collected by the state employment services departments and passed to the U.S. Department of Labor. States collect the data as part of the Unemployment Insurance Program. As a result, only establishments that pay Unemployment Insurance are captured with this data source, hence the name "Covered Employment". Since this data only captures covered employees, the data set misses self-employed people, railway employment, or any other establishments who do not pay into the Unemployment Insurance program. The CEW agriculture sectors are not complete enough to use in IMPLAN development. This is a result of the way the CEW data is collected. Since only unemployment insurance covered employment is captured with the CEW, and most farm employment is self-

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Chapter 20: Employment employment, CEW data misses much of the farm data. Farm data is supplemented with additional data discussed in the next section. Railroad employment is not captured well with the CEW data since railroads are exempt from the unemployment insurance program. At this point, railroad employment is plugged into the CEW data set from the REIS data. The establishments and employees not captured by the CEW data set are counted by additional data described in the Special Sectors section and the Regional Economic Information System (REIS) Data. REIS employment data is only available at the 3-digit NAICS code level for states, and the 2-digit NAICS code level for counties.

Non-Disclosure Adjusting the CEW Data Adjusting the CEW data for non-disclosure is more complex than the CBP data. The CEW program does not provide the number of establishments by employee size class as does the CBP program. In general, the procedure starts with the national level data that is used to control the state level data. The county data is also used to provide a "first guess" at the state level data. The state level nondisclosure adjustment is made. The county level data is then nondisclosure adjusted and forced to add to the state totals. Step A. - Creating State Files The national file may need non-disclosure adjusting for only a few sectors. This adjustment is typically made by hand. The state files require non-disclosure adjusting. The first step is to calculate the magnitude of the missing values. The next step is to distribute the “missing” values based on the distribution of the related CBP data. This provides a "first guess" for distribution of the missing CEW elements. Once all data is filled in, the Vector RAS procedure is started. This adds up all related SIC codes, starting with the 6-digit data, and moving to the 5, 4, 3,and 2-digit data respectively. This procedure compares the group total with the actual total, and then makes adjustments only to the elements that are non-disclosed to ensure that the SIC groups add to the totals.

Chapter 20: Employment Step B. Creating County Files The county CEW files are created much the same as the state files. The only real difference being that the state totals are used as controls when RAS’ing the missing data.

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A Vector RAS involves adding elements to control totals within a single vector. This is used primarily with the NAICS Code related data where 6-digit elements add to 5digit elements and so forth.

Step C. Finished Output - Re-Sectoring to IMPLAN 528 The resulting files from this procedure are a complete set of 4-digit SIC data. The next step is to re-sector the 4-digit SIC code data to the IMPLAN 528 sector scheme. Appendix A has the bridge table that shows which 3 or 4-digit SIC codes relate to IMPLAN 509 codes. At the same time the data is reformatted, the Special Sectors are added to the IMPLAN 509 data set.

Special Sectors There are several sectors that are not covered by the CEW data discussed above. Agriculture (IMPLAN 1-13) Construction (IMPLAN 33-45) State and Local Government (IMPLAN 497-499, 503-504) Federal Government (IMPLAN 398, 495-496, 505-506)

Agriculture The agriculture sectors are particularly difficult to estimate since there is no employment and earnings data collected on a commodity basis, even at the national level. The only farm employment and income value is derived by the BEAs’ Regional Economic Information System (REIS) program. As a result, MIG developed procedures to estimate employment and income by commodity systematically for every county. This estimate of employment and income is then used to distribute the total farm employment value given by the REIS data. The primary data set for agriculture is the National Agricultural Statistical Service (NASS) estimates of agricultural production for the given year. This data set provides estimates of value of production

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Chapter 20: Employment (output) by specific commodity at the state level. The county level data is not consistent enough for our use. Other data used to estimate county agricultural activity is from the Census of Agriculture. The Census data provides dollar value of livestock related commodities and the number of acres for crop type commodities for all counties in the US. Of course, there are nondisclosure problems with this data. Non-disclosing the Census of Agriculture involves using national and state ratios, and the number of farms (which is never non-disclosed) to estimate non-disclosed elements. For state level livestock data that is not disclosed, national average market value per farm is applied to state numbers of farms raising livestock. For state level crop data that is non-disclosed, national average acres per farm are applied to the state number of farms raising crops. At the county level, related state average market value per farm is applied to county numbers of farms raising livestock. For county level crop data, related state average acres per farm is applied to the county number of farms raising crops. Once the data is non-disclosure adjusted, the agriculture data is resectored to the IMPLAN 13 Agriculture related sectors. The Census categories are now NAIS based sectoring and can be related directly to the 13 IMPLAN sectors The “cattle ranching and farming sector (IMPLAN 11) also includes dairy farming. When the agriculture data is combined into the IMPLAN 509 sector employment and earnings file, adjustments are made to translate the livestock values and crop acres into employment and earnings estimates. Data from the NASS Value of Production provided state and national market values. Market values and acres for crop commodities from the Census provided county level estimates. Output per worker and earnings per worker data are used to translate both livestock and crop market value data into employment and earnings estimates. The output-per-worker and earnings-perworker estimates are derived from the Census of Agriculture. This procedure provided an allocation basis for the IMPLAN agriculture sectors. When adjustments are made to REIS control totals (discussed below), the REIS farm employment and income data are allocated to the 11 agriculture sectors.

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It is apparent that some of the state and county farm sectors are subject to large adjustments when controlled to the national totals. This is a result of inconsistencies between sources. The benchmark data set is the published NASS data. Since the agriculture data is entirely derived, analysts with better agriculture data are encouraged to use it when building their IMPLAN models.

Construction There are 13 new and maintenance and repair construction sectors (IMPLAN sectors 33-45). We use REIS data to provide total construction employment and income values. These values are allocated to the 13 IMPLAN construction sectors based on the Census of Construction. The Census of Construction provides information on value of construction for all the IMPLAN sectors at the state level. The construction values are price updated to the current year. State level construction values are combined with output-per-worker estimates and earnings-per-worker estimates derived from the current national input-output study to form a set of employment and earnings estimates for each state. There is no related county level construction data in the Census of Construction. As a result, the state level distribution vectors are used as a proxy for the counties. The county level REIS total construction employment and income values are distributed using the state level vector.

State and Local Government State and local government employment and earnings are available through the CEW data. However, this data is subject to nondisclosure rules similar to the private sector data. However, we can not use CBP data as a basis to non-disclose the CEW state and local government data because CEW data does not cover government establishments. As a result, we use the Annual Survey of Government Employment to provide the data. There are five components of state and local government employment and earnings. Figure 20-1 illustrates the state and local activities that comprise each IMPLAN state and local government sector.

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Chapter 20: Employment Figure 20-1 State & Local Government Sectors Current IMPLAN Sector 497 Local Passenger Transit

498 State and Local Electric Utilities 499 Other state and Local Government Enterprises

503 State and Local Government Education

504 State and Local Government Non-E Education

State and Local Activity Bus Transit Subway Transit Other Transit Electric Power Sanitation Sewerage Water Supply Gas Supply Airports Water trans. & terminals Housing & Community Development Liquor Stores Elementary & Secondary Instruction Elementary & Secondary Non-instruction Higher Education Instruction Higher Education Non-instruction Parks & Recreation Health Hospitals Police Judicial and Legal Financial Administrative Highways Public Welfare Fire Protection Natural Resources Corrections Libraries Social Insurance

The Survey of Governments: Employment provides all information required without any non-disclosure problems. This data is resectored into the IMPLAN sectoring and combined with the CEW data. A problem does exist with the Survey. State government employment and income are only reported at the state level. There is no indication as to which county the state employment is located. To estimate this, state university enrollment is used for the education sector, and totals from the CEW data is used to allocate other government employment. There is a distinction between the government enterprise and government industry sectors, which is often a source of confusion. This is true for state and local government, as well as the federal government. Government enterprise sectors are government activities in which a majority (more than 50%) of its budget is covered by revenues from goods or services produced by that agency.

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Enterprise sectors produce goods and services that are sold to intermediate or final demand. Government Industry (State and Local Government Education and Non-Education, and Federal Government: Military and Non-Military) normally involve traditional government services not associated with the private sector. State enterprise sectors are IMPLAN 497-499 (Figure 20-1).

Federal Government The federal government data is available directly from the CEW file. It is treated separately since there are no non-disclosure adjustments required by the CEW. Figure 20-2 shows the various federal government sectors. Figure 20-2: Federal Sectors Current IMPLAN Sector 398 U.S. Postal Service 495 Federal Electric Utilities

496 Other Federal Government Enterprises

505 Federal Gov-Military 506 Federal Gov-Non-Military

Federal Activity Postal Service Bonneville Power Administration South Eastern Power Administration South Western Power Administration Tennessee Valley Authority Upper Colorado River Storage Airports (National) Department Stores (Military PXs) Variety Stores (Military PXs) General Merchandise (Military PXs) Grocery Stores (Military PXs) Auto & Home Supply (Military PXs) Gas Stations (Military PXs) Eating & Drinking (Officers/Enlisted Clubs) Drug Stores (Military PXs) Liquor Stores (Military PXs) Misc. Stores (Military PXs) Federal Home Loan Bank Over Seas Investment Co. Pension Guarantee Fund Bank Deposit Insurance Funds Motion Pictures (Military PXs) Bowling Alleys (Military PXs) Department of Defense All other government activities

The only problem area with this data is the Government Industry sectors, “Federal military” and “Federal non-military”. It is not possible to distinguish between these two administrative government sectors with only the CEW data. Therefore, the CEW data provides only total federal government industry employment and earnings. REIS data separates Military and Non-Military Government so the split is made with REIS data. The enterprise sectors are derived from the CEW data directly.

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Regional Economic Information System The final set of employment and income information is the Bureau of Economic Analysis’s (BEA) Regional Economic Information System (REIS) data. This data set is the most inclusive available and provides information on sectors such as agriculture, construction and railroads not directly available through other series such as CEW. The REIS data series also provides information on self-employment and proprietary income. The major drawback to this data is that it is only available at the 3-digit NAICS level for state and county income, and the 3-digit and 2-digit level for state and county employment, respectively. This data is used to provide control totals to the CEW wage and salary data, and to provide a means to estimate proprietors’ employment and income. This is necessary to complete the IMPLAN value-added data. The information used in developing the IMPLAN data in this section is the following: 3-digit State level wage and salary income - SA7 tables 3-digit State level wage and salary employment - SA27 tables 3-digit State level total income (wage and salary and selfemployment) - SA5 tables 3-digit State level total employment (wage and salary and selfemployment) - SA25 tables 3-digit County level total income (wage and salary and selfemployment) - CA5 tables 2-digit County level total employment (wage and salary and selfemployment) - CA25 tables 6-digit disclosed ES202 state and county employment and income data described earlier in this chapter aggregated to the 3-digit BEA sectoring scheme The BEA employment and income data is subject to non-disclosures so there are two parts to this effort: 1. Derive estimates for non-disclosed data 2. Develop 3-digit county employment data based on the 2-digit county employment data available from the BEA.

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Dividing Counties and Independent Cities Unlike the CEW and CBP data which give information on all counties and independent cities in the U.S., the BEA have combined independent cities with their neighboring counties in their REIS data series. In Virginia there are 23 such combinations (one in Wisconsin 1994 and earlier). Figure 20-3 below shows the affected areas. Figure 20-3. Combined VA and WI Cities and Counties NAME OF COMBINED CITIES/COUNTIES VIRGINIA ALBEMARLE; CHARLOTTESVILLE ALLEGHANY; COVINGTON AUGUSTA; STAUNTON; WAYNESBORO BEDFORD; BEDFORD CITY CAMPBELL; LYNCHBURG CARROLL; GALAX DINWIDDIE; COLONIAL HEIGHTS; PETERSBURG FAIRFAX; FAIRFAX CITY; FALLS CHURCH FREDERICK; WINCHESTER GREENSVILLE; EMPORIA HENRY; MARTINSVILLE JAMES CITY; WILLIAMSBURG MONTGOMERY; RADFORD PITTSYLVANIA; DANVILLE PRINCE GEORGE; HOPEWELL PRINCE WILLIAM; MANASSAS; MANASSAS PARK ROANOKE; SALEM ROCKBRIDGE; BUENA VISTA; LEXINGTON ROCKINGHAM; HARRISONBURG SOUTHAMPTON; FRANKLIN SPOTSYLVANIA; FREDERICKSBURG WASHINGTON; BRISTOL WISE; NORTON YORK; POQUOSON WISCONSIN MENOMINEE; SHAWANO

REIS COUNTY ID 901 903 907 909 911 913 918 919 921 923 929 931 933 939 941 942 944 945 947 949 951 953 955 958 901

The 3-digit ES202 employment and income data is used to proportion the REIS data into its component counties with the following exceptions: Census of Agriculture employment by county (derived in a previous step) is used to split agricultural employment and income. Annual Census of government data is used to split federal and state and local government employment and income. Federal civilian employment and income is used as a proxy to split the REIS federal military sector.

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Chapter 20: Employment Motor freight and warehouse employment and income data from CEW data is used as a proxy to split the REIS railroad transportation sector.

Deriving REIS State Non-Disclosure Adjustments The U.S. 3-digit REIS employment and income data have no nondisclosures, however, the states do. The task here is to estimate nondisclosed state values making sure that the states’ values add up to the U.S. values and that internally, the state industry sectors add up to the more aggregated state sectors. Disclosing wage and salary employment (SA27 tables). The first estimate is simply the corresponding CEW employment value. The CEW problem sectors: Farm, Railroad and Federal Military, are not a problem using REIS data as there are few nondisclosures at the state level in REIS. After plugging in the initial estimates, the state values are RAS'ed using the U.S. as controls for the row values and the 1-digit State REIS values as the column control. Disclosing wage and salary and self-employment (SA25 tables). The four component BEA Gross State Product data is a source of information at state level which will tell us whether there is any selfemployment income and, therefore, any self-employment. If there is no self-employment, then wage and salary (WS) plus self-employment employment is equal to WS employment only, which is derived in the previous step “Disclosing Wage and Salary Employment”. In some cases, a single 3-digit non-disclosure remains within a 2-digit group which can be derived through subtracting all disclosed 3-digit data from the 2-digit control value. Conversely, there may be self-employment and no corresponding WS employment. In these cases a first estimate based on U.S. income per self-employed is used. For sectors that have WS and self-employment and are non-disclosed, the first estimate is based on U.S. self-employment to WS employment ratios for that sector. The resulting estimates are then RAS'ed using U.S. as row controls (sum of all states equals the U.S. values for each industry) and state 2-digit values (sum of state sub-sectors equals the state higher industry aggregation value) as the column controls. The individual WS plus self-employed value is subject to the constraint of being at least one plus the WS employment.

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Disclosing wage and salary income (SA5 tables). The first estimate is the corresponding state level CEW income/employment ratio times the state WS employment derived above. After, plugging in the initial estimates, the state values are RAS'ed using the U.S. as controls for the row values and the 2-digit State REIS values as the column control. Estimating Other Labor Income The Survey of Current Business contains estimates of Other Labor Income (OLI) and Wage and Salary (WS) Income for National Income and Product Accounts (NIPA) sectors. The NIPA sectors are bridged to the REIS sectoring scheme and the NIPA OLI to wage and salary income are derived and applied to state REIS wage and salary income (derived above) to establish a first estimate of OLI. This estimate of OLI by REIS sector is then controlled to the state REIS estimate of OLI. These values of OLI, while not part of the IMPLAN database, are used to help estimate self-employment income in the next step. Disclosing wage and salary and self-employment income (SA25 tables). If there are no proprietors (i.e., no self-employment), then state level values of WS and proprietor income are equal to wage and salary income plus OLI. Otherwise, non-disclosures are first estimated using U.S. proprietor/WS ratio for each industry. After plugging the initial estimates, the state values are RAS'ed using the U.S. as controls for the industry row values, and the 2-digit State REIS values as the column control.

Deriving REIS County Non-disclosure Estimates The goal is to estimate employment and income for REIS nondisclosures for each sector in each county. For each industry sector, the sum of the counties within a state is to equal the state value and, within a county, the sum of the 2-digit industries within a 1-digit aggregation is equal to the 1-digit aggregation. Disclosing wage and salary employment for Government sectors BEA gives an employment code rather than a value if employment is less than 10. If this applies to one subsector, then the correct value can be derived by subtraction. If two subsectors are involved, then there can be problems. These problems tend to involve state and local, and federal military government. These counties are consistently small, rural counties where military reservists comprise the bulk of the federal military government employment. For these counties, a ratio of military employment to total government is derived (from

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Chapter 20: Employment similar sized counties within the state) and applied. State and local government is then the residual of total government minus all federal government. Disclosing 2-digit wage and salary plus self employment. The county’ share of the state's 2-digit BEA employment is assumed to be the same as its share of the 2-digit CEW data. Therefore, state and county 6-digit CEW employment data is aggregated to 1-digit and the ratio of county CEW divided by state CEW, times state BEA data for each industry, gives us the first estimate of non-disclosed county data. Subsequently, the estimates are RAS'ed so the sum of counties is the state value for each industry, and the sum of all industries for a county is the employment given by BEA data. Disclosing 3-digit wage and salary plus self employment. The county’s share of the state's 3-digit BEA employment is assumed to be the same as its share of the 3-digit CEW data. Therefore, state and county 6-digit CEW employment data is aggregated to 3-digit and the ratio of county CEW divided by state CEW times state BEA data for each industry gives us the first estimate of non-disclosed county data. The sectors not covered by CEW are based on the 3-digit county income (CA5 tables) as follows: 1. Railroad employment is equal to county income divided by state level income per worker. If county level income is non-disclosed then the truck transportation industry is used as a proxy -i.e., railroad employment is equal to the state total of non-disclosed railroad employment (state railroad employment minus disclosed county railroad employment) times county level truck transportation divided by state level truck transportation. 2. Household employment is equal to county income divided by state level income per worker. If county level income is non-disclosed then the personal services industry is used as a proxy -i.e., Household employment is equal to the state total of non-disclosed household employment times county level personal services divided by state level personal services. Subsequently, the estimates are RAS'ed so that the sum of counties is the state value for each industry and that the sum of the 3-digit industries for a county is the 2-digit employment derived in the previous step. To calculate wage and salary only employment data for the county, "CA7" tables, it is assumed that the number of proprietors to wage

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and salary workers ratio for a state is constant for all its component counties. County 3-digit wage and salary plus proprietor income. Earnings per wage and salary worker by industry by county is calculated using the 3-digit CEW data and applied to the county level wage and salary data derived above. Other labor income (OLI) is derived using state level OLI per wage and salary income at the state level. Finally, proprietor (self-employment) income is derived using state level income per proprietor. There are cases at the county level where no wage and salary employees exist (i.e., no CEW data) yet there are proprietors -i.e., an existing value in the 3-digit total income BEA REIS data - table CA5. In these cases, the number of workers involved is calculated using state level income per worker.

Distributing Disclosed 3-digit Employment and Income REIS Data to IMPLAN Sectoring With a complete disclosed set of 3-digit REIS income (national income being adjusted to NIPA, see next chapter) and employment data, it is now possible to distribute that data to the 509 IMPLAN sectors using the disclosed CEW data. Distributing National Employment and Income Starting with the national data, the 3-digit adjusted REIS employment (including self-employed) is distributed to 6-digit CEW sectoring based on weighting described by U.S. current CEW wage and salary employment, and the results are aggregated to the IMPLAN current sectoring scheme. REIS 3-digit employment compensation and proprietor income is similarly distributed to 6-digit CEW sectoring based on weighting described by U.S. current CEW wage and salary income with the results aggregated to the 509 IMPLAN sectors. The national values are consequently adjusted for "Force Account Construction". Force account construction is construction work (both new and maintenance) performed by employees of non-construction sectors. This economic activity (employment, value-added (VA) and output) is shifted from the non-construction sector to the appropriate construction industry in order to satisfy BEA Input-Output definitions. The force account adjustment factors are taken from the BEA Benchmark I-O. The force account adjustment for states is made when the state data is adjusted to U.S. totals. The force account

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Chapter 20: Employment adjustment for county data is made when the county data is adjusted to state totals. Distributing State and County Employment and Income State 3-digit REIS employment and income is distributed as is the national data using the CEW employment and income data for each of the corresponding states. Each industry of the resulting 51 state (including Washington D.C.) estimates are forced to sum to the national value. County 3-digit disclosed REIS employment and income also is distributed, as is the national data using CEW employment for each of the corresponding counties. Resulting county industry data is forced to sum to the corresponding state values. Special Considerations for Distribution The first consideration is a reminder that the Agricultural and Construction sectors are not defined by 6-digit NAICS but are commodity based (agriculture) and by type of construction (construction). Therefore, other distributors are used (see the “Special Sectors” section in this chapter) and not CEW data. Also CEW does not cover Railroad transportation, but there is a one-to-one correspondence between 3-digit REIS data and IMPLAN sectoring, so no distribution is necessary. At the county level there are industries for which there is 3-digit REIS income and employment but no corresponding 6-digit CEW data, meaning that there is only self-employment and no wage and salary employment. For these cases, the 3-digit REIS data is distributed to industries based on the state distribution. If this distribution would place less than 0.4 employees to a particular industry then that piece of the distribution is added to the largest component of the distribution. Finally, sectors with less than 0.5 employees and less than $6000 of income (employee compensation + proprietor income) are zeroed out. All employment is then rounded to the nearest whole number.

Full-Time Equivalents Full-Time Equivalents (FTE), is one way to count jobs. An FTE is assumed to work 2,080 hours in a standard year. FTE is not full and part-time job counts. When employment is counted as full and parttime, a job is a job, and one cannot tell from the data the number of hours worked or the proportion that is full or part-time.

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IMPLAN data is full and part-time employment (with the exception of the 1985 database). If an analyst is interested in reporting full time equivalent jobs (FTE), data can be collected to translate the IMPLAN data into FTEs. Translating to FTEs is an easy process. First, data can be obtained on the number of hours worked by NAICS code. Hours worked data is available from your state agency that administers the Unemployment Insurance program (usually called Employment Security, Employment, Jobs Services or other). Match the NAICS codes to the related IMPLAN Code (Appendix A), and divide the number of hours worked by the standard year, 2080 hours. You can then multiply your employment impact report by this vector of FTE conversions.

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Value-Added Value-Added consists of four components. 1. Employee Compensation 2. Proprietor Income 3. Other Property Income 4. Indirect Business Tax Employee compensation is wage and salary payments as well as benefits, including: health and life insurance, retirement payments, and any other non-cash compensation. It includes all income to workers paid by employers. Proprietary income consists of payments received by self-employed individuals as income. This is income recorded on Federal Tax Form 1040C. Proprietary income includes income received by private business owners, doctors, lawyers, and so forth. Any income a person receives for payment of self-employed work is counted. Other property type income consists of payments from interest, rents, royalties, dividends, and profits. This includes payments to individuals in the form of rents received on property, royalties from contracts, and dividends paid by corporations. This also includes corporate profits earned by corporations. Indirect business taxes consist primarily of excise and sales taxes paid by individuals to businesses. These taxes occur during the normal operation of these businesses but do not include taxes on profit or income. This chapter discusses: Overview National Value Added Estimates Distributing National Estimates to States and Counties

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Overview The calculation of value-added data starts with calculating earnings. The sources of data for earnings are the same as for employment. The main difference is that County Business Patterns are employment only. If the county doesn’t have income disclosed, then state-level income per worker ratios are used for a first estimate. To estimate income, state-level income per worker ratios are used with the employment estimates derived above. Next, the income estimates are used to disclose the CEW data and the CEW data used to non-disclosure adjust the REIS data. The REIS data is expanded to separate wage and salary Income and proprietors’ Income. The REIS data is then used as final control totals with the CEW data providing the 6-digit NAICS industry structure.

National Value-Added Estimates All IMPLAN value-added data is ultimately controlled to National Income and Product Accounts (NIPA) data published in the Survey of Current Business (SCB) by the Bureau of Economic Analysis (BEA).

Proprietor Income and Employee Compensation As shown in the previous chapter, 6-digit U.S. employee compensation and proprietor income is derived based on REIS controls (actually at the national level there are no non-disclosures in the income and employment data) and distributed to IMPLAN 509 sector data. The next step is to adjust the IMPLAN 509 sector data to NIPA control totals. For Proprietors’ Income a single proportional adjustment factor is applied for all sectors. However, for Employee Compensation NIPA has additional sector data available (Table 6.2C in the SCB). U.S. 509-sector employee compensation including OLI is adjusted so that the sum of the IMPLAN sectors comprising one of the NIPA industry sectors is equal to the NIPA value. A single adjustment factor is applied to each of the IMPLAN sub-sectors of a given NIPA sector. As discussed above, the "Force Account" construction adjustment is applied, resulting in the IMPLAN employee compensation and proprietor income that appears in the current IMPLAN data base. These become the 509 sector controls to which the state earnings data sum to in the previous chapter.

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Indirect Business Taxes and Other Property Type Income The procedure to derive national 509 IMPLAN sector data for both Indirect Business Taxes (IBT) and Other Property Type Income (OPTI) is the same. The base data set is the BEA’s Gross State Product (GSP) series which gives state level estimates of the components of value-added by 3-digit SIC. Nationally, a ratio of Employee Compensation to IBT or OPTI is generated based on the BEA Input-Output benchmark table. The ratios are applied to the national 509 sector IMPLAN Employee Compensation values to derive the first estimate of IBT and OPTI. The estimates are then adjusted so that their sum is equal to the national NIPA values for IBT and OPTI. State level estimates are derived by first creating a 509 sector ratio estimate for IBT and OPTI and then controlling the estimated vectors to the BEA GSP data.

Distributing National Value-Added Estimates to State and Counties Employee Compensation and Proprietor Income is distributed to 509 IMPLAN sectors for states and counties as described in the previous chapter. IBT for the state is based on IBT to labor income (Employee Compensation plus Proprietor Income) ratios from the BEA 4component GSP data. Each of the GSP IBT ratios is applied to the state labor income data of the corresponding current 509 IMPLAN sector. These state level estimates of IBT are controlled so that the sum of the states' IBT is equal to the U.S. IBT for each industry. At the county level, the IBT to labor income ratio at the state level is used for each of the IMPLAN industries. Counties' IBT is forced to sum to the state level IBT for each industry. OPTI for the state is calculated using the national IMPLAN OPTI to labor income ratio times state labor income for each industry. The state level estimates of OPTI are controlled so that the sum of the states is equal to the national value for each industry. County level OPTI also uses the OPTI to labor income ratio generated by using state level data. The county level OPTI is then forced to sum to the state level OPTI for each industry.

Chapter 22: Output

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Output Total Industry Output (TIO) is the value of production by industry for a given time period. For IMPLAN, TIO is annual calendar year production. Output can be measured either by the total value of purchases by intermediate and final consumers, or by intermediate outlays plus value-added. Output can also be thought of as a value of sales plus or minus inventory. This chapter discusses: Total National Industry Output National TIO/TCO State and County Distribution of TIO

Total National Industry Output Total Industry Output (TIO) is by necessity estimated from a multitude of sources. IMPLAN output data comes from similar sources as used by the BEA in developing the benchmark IO. Most output data is from the BEA’s output series and the Annual Survey of Manufacturers. Other sectors use information from other various surveys and censuses. In some cases, there are no census or surveys available. In these cases, earnings data derived above are used along with earnings to output ratios from the BLS growth model are used to estimate the missing output.

Agriculture Agriculture output is derived from values estimated during the creation of the agriculture data for the employment and earnings data set. The primary source is the NASS value of production data and the Census of Agriculture. Estimates of output per worker and earnings per dollar of output are from the Census and other unpublished sources.

Mining Mining output estimates are derived from the Mineral Commodity Summaries. This USDI Bureau of Mines publication provided output estimates for most of the mining sectors. For the Metal Mining

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Chapter 22: Output Services and Uranium-Radium-Vanadium Ores (IMPLAN 34 and 35 respectively) TIO/Earnings ratios are used.

Construction Construction output is derived from the current Annual Survey of Construction Put-In-Place. The values are price adjusted to current dollars. State estimates are from the Census and Survey of Construction Activity.

Manufacturing Manufacturing output is derived from the Annual Survey of Manufacturers, Statistics for Industry Groups. This data provides value of production estimates for all 6-digit manufacturing sectors. Also derived from this data set are values for Inventory Change.

Transportation, Communication, Utilities Data for this industry group is derived primarily from the BEA’s output series. A secondary source is the BLS growth model.

Finance, Insurance, Real Estate Finance, Insurance, Real Estate group output is estimated using the BLS growth model and the BEA’s output series.

Wholesale Wholesale trade output as estimated using the BEA’s output series. A secondary source is the BLS growth model.

Retail Retail Group output is estimated using gross margin information from the current Annual Survey of Retail Trade. A secondary source is the BLS growth model.

Services Service output is estimated using both the current Annual Survey of Services and the TIO/Earnings ratios. Only a few sectors are covered with the current Survey data. These are hotels, business services, personal services. The BLS growth model output estimates are used for service sectors not covered by annual censuses.

National TIO/TCO All output data estimated is collected to form one national total industry output vector. Total Commodity Output is estimated by

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multiplying the Total industry output by the make matrix. This resulted in total commodity output estimates. The national output estimates are fine-tuned by means of the national social accounts and estimated intermediate TIO and TCO estimates. Briefly, this is accomplished by examining the final demands and value added estimates forming the national social accounts, the related TCO and TIO, and the resulting intermediate commodity and industry output estimates. Adjustments are made to some output estimates to eliminate negative intermediate output estimates.

State and County Distribution of TIO For Agricultural sectors (IMPLAN sectors 1-13), state TIO comes directly from the NASS data. County data is a function of output per worker and state/county employment. For all of the remaining industrial sectors (IMPLAN sectors 14-499), TIO is national output per worker times state/county employment adjusted for value-added to employment ratios that deviate from national average. In other words, if the employee compensation (or proprietor income, indirect business tax or other property type income) to employment ratio for the county or state is higher than national average then output per worker will also be adjusted upward and vice versa. The resulting TIOs are checked to make sure they are positive and greater than value-added. State TIOs are forced to sum to U.S. TIO and county TIOs are forced to sum to state TIOs. Sectors 500 to 509 are "special" sectors. Their values are set as follows: Sector 509 is set to the PCE value for owner-occupied dwellings. Non Comparable Imports, Scrap, & Used and secondhand goods (500-502) are not industries, therefore TIO is zero. Federal and State & Local Government (503-506) TIO’s are, by definition, equal to value-added. Rest of World Industry and Inventory Valuation Adjustment (507, 508) are distributed to states and counties based on their proportion of total U.S. economic activity (as represented by total employee compensation). That is, if a state has 10% of the national employee compensation, it receives 10% of the national rest of world industry TIO.

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Chapter 23: Institution Demand

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Institution Demand In general, institution demand is estimated nationally and then allocated to states and counties. Institution demand data is not available for some of the variables at the state or county level. This chapter will discuss the data sources and the distribution procedures. Institution demand, or final demand as it is sometimes called, is demand for goods and services for final use. Final use means that the good or service will be consumed and not incorporated into another product. Household consumption expenditures, also known as Personal Consumption Expenditures (PCE), consist of payments by individuals/households to industries for goods and services used for personal consumption. PCE is the largest component of final demand. Federal Government purchases are divided between military, non-military, and investment. Federal military purchases are those made to support the national defense. Goods range from food for troops to missile launchers. Non-military purchases are made to supply all other government functions. Investment consists of government demand for capital goods. Payments made to other governmental units are transfers and are not included in Federal Government purchases. State and local government purchases are divided between public education, non-education, and investment. Public education purchases are for elementary, high school, and higher education. Non-education purchases are for all other government activities. These include state government operations, and operations including police protection and sanitation. Private sector education purchases are not counted here. Private education purchases show up as intermediate purchases for IMPLAN sectors 461 and 462. Inventory purchases are made when industries do not sell all output created in one year. Each year, a portion of output goes to inventory. Inventory sales occur when industries sell more than they produce and need to deplete inventory. Inventory purchases and sales generally involve goods-producing industries (e.g. agriculture,

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Chapter 23: Institution Demand mining, and manufacturing). IMPLAN values for inventory sales and purchases are net. Capital expenditures are made by industries and institutions to obtain capital equipment and construction. The dollar values in the IMPLAN database are expenditures made to a specific industrial sector producing the capital equipment. The values do not represent capital investment by that industrial sector. Foreign exports are demands made to industries for goods that are exported beyond national borders. These represent goods and services demanded by foreign parties. Domestic exports are calculated during the IMPLAN model creation and are not part of the database. Inter-institutional transfers are monetary flows between institutions. The institutions are households, federal government, state and local government, capital, and trade. These flows represent non-industrial transfers of funds such as household payments of taxes and government payments to households in the form of social security and welfare. There are also transfers between federal and state and local government in the form of grants.

Household Expenditures National household Personal Consumption Expenditures (PCE) are estimated using the BEA Benchmark I-O Study and the Consumer Expenditure Survey (CES), diary and survey. This provides estimates of consumer expenditures on goods and services by different income classes. If the CES data is not current year, the expenditures are price updated. CES expenditures are in terms of purchaser prices, so margining is necessary. This is accomplished using the margins described in Chapter 26, “Database Validation”. Applying the margins allocates the CES data to the appropriate IMPLAN sector. The result is a vector of total PCE. The vector of PCE is adjusted to the National Income and Product Accounts (NIPA) PCE control total. The adjusted PCE total is then allocated to the nine income classes based on the CES data. This provides the PCE estimate for the different income classes. National PCE are distributed to state and counties based on the number of households and household income for each of the nine PCE income categories. A vector of spending is developed for one household for each of the CES income classes. The number of households by each of the nine income classes by county is obtained

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from the Census. Expenditures made by households (by income class) are multiplied by the number of households (by income class) to form the PCE estimate for each county. These estimates are then controlled to the US totals.

Federal Government Military/ Non-military Expenditures and Sales Federal expenditure data is obtained from the Federal Procurement Data Center, a federal agency that tracks government purchases. This information is available at the state and county level. These values are adjusted to NIPA control totals. Federal Sales data is estimated using NIPA control totals and the I/O distribution. The exception to this is Federal Timber Sales. The Federal Procurement data gives us federal government purchases for each state and county in the U.S.. Its 6-digit NAICS data is bridged to 509 IMPLAN sectors and its functions are aggregated to IMPLAN's two final demand categories (military and non-military). This data indicates what share of the U.S.'s Federal Purchases occurs in which state and which county by industry. For example, federal purchase of mainframe computers (NAICS 334111, current IMPLAN sector 302) in Minnesota is 10 percent of the U.S. purchase, according to the federal procurement data; therefore, Minnesota has 10 percent of the national NIPA value for that sector. The reason the federal procurement data is not used directly is due to the procurement data not incorporating small contracts (<$5000). There are several sectors for which NIPA data indicates federal purchases while it is nonexistent in the federal procurement tapes. For these sectors state/county output to U.S. output ratios act as the distributor for the NIPA data. Procurement data at the state level is forced to sum to U.S. procurement data and, similarly, procurement data at the county level is forced to sum to the state level; therefore, distributed county level federal purchases data will sum to the national value. Federal investment is based on NIPA data and an allocation to IMPLAN sectors based on the current benchmark study. Federal sales data is distributed to states and counties based on state and county TIO to U.S. TIO ratios. The one exception is federal sales

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Chapter 23: Institution Demand of stumpage (IMPLAN sector 24) which by BEA definition represents sales activity of the USDA Forest Service. The U.S. Forest Service provides unpublished timber sale data at the county and state level. The Forest Service provides federal stumpage sales data to MIG. IMPLAN Sector 15 sales (or stumpage sales) for the federal government is defined to be the sales volume of timber harvested (includes sawlogs and all convertible volume) from national Forest land. Data is obtained from a database maintained by the Washington Office Timber Sale Accounting (TSA) branch). Data for the current fiscal year current is obtained and consists of: 1. normal distribution or revenues received by the Forest Service as a result of the timber sale 2. Purchaser Road Credits (PRC) directly related to the stumpage volume 3. Associated charges to purchasers not directly related to stumpage (includes items such as road maintenance, slash disposal, and coop scaling). IMPLAN data is presented on a calendar basis. TSA's database has individual sales stored by county and state FIP's codes; data is summed for all sales in county, state, and national totals. Total figures for the nation and states are compared to the Forest Service's timber sale accounting reports (TSPIRS) as a benchmark to insure the validity of the data.

State and Local Government Purchases for Education and Non-education and Sales Data for State and Local Government Purchases and Sales is obtained from the current Annual Survey of Governments: Finances data series. This provided total expenditures for education and noneducation as well as sales at the state level. County level information is not possible to ascertain. This data is only used for distribution of NIPA control totals. The State and Local government expenditure and sales data give comparative expenditure levels by function (education, noneducation, and sales) for each of the 51 states (included Washington D.C.) and the U.S. With this data, a share of the U.S. State and Local government expenditures is developed for each state which, when applied to the total national IMPLAN values, provides an estimate

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for all sectors for each state. This state estimate of total state and local government expenditure and sales is distributed to the IMPLAN sectors based on the U.S. distribution. In other words, a normalized state distribution vector of non-education government expenditures will look like the U.S. normalized version with three exceptions. The first exception is U.S. sales of stumpage (sector 15) which is based on each state's share of the U.S.'s employment in "Logging". This assumes that a higher share of state forest lands exist in states with more commercial logging. The second and third exceptions are the education and non-education final demand purchases from the education and non-education rows, which represent compensation to employees of those agencies (already derived for state and county IMPLAN data). County level education and non-education expenditures are based on corresponding employment. IMPLAN state level expenditure data is distributed to the counties as a direct proportion of the county's share of the state's state and local government employment. Sales data, on the other hand, is distributed to counties based on county TIO as a proportion of state TIO for each sector. State and local investment is based on total capital expenditures from the Annual Survey of Government Finances. The expenditure patterns are based on the Benchmark IO expenditure patterns.

Inventory Purchases and Sales For the manufacturing sectors, the Annual Survey of Manufacturers provides the inventory data. For agriculture, the NASS data provides the values. Other sectors are derived from I/O ratios. National IMPLAN Inventory Purchases, Inventory Sales and Foreign Export final demand vectors are distributed to states and counties on the basis of TIO (total industry output). Therefore, each county/state share of the national final demand value is proportional to its share of economic activity as represented by TIO.

Capital Capital expenditures, or Gross Private Capital Formation (GPCF) as it is sometimes called, are estimated using the current BEA Wealth data showing capital expenditures made by firms. This provides information on who spent what, but for the GPCF final demand we need information on where the capital expenditure is made. This

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Chapter 23: Institution Demand shows the demand on an industry for capital goods and is accomplished by using the NIPA investment data and the investment matrix provided by the Benchmark Study workfile. The national GPCF is distributed to states and counties based on total employment in all construction industries (IMPLAN current sectors 33-45). This implies that a purchase of capital goods within a state or county is linked to overall construction activity within that area. Therefore, a county containing 0.3% of the national construction employment would receive 0.3% of the national GPCF for all sectors except the new and repair and maintenance construction sectors (IMPLAN current sectors 33-45). National GPCF for those sectors are distributed directly to the county or state based on TIO to national TIO ratios for each of those sectors.

Foreign Exports and Imports Foreign export data is from the U.S. Department of Commerce’s Foreign Trade Statistics series. This data series provides detailed national information on in and outflows and is used as the structure for the national set of I/O accounts. National IMPLAN foreign exports final demand vectors are distributed to states and counties on the basis of TIO (total industry output). Therefore, each county/state share of the national final demand value is proportional to its share of economic activity as represented by TIO. Census data identifying the source of shipment does exist, however, it only identifies the location of the wholesale/retail broker and not the site of production.

Chapter 24: Inter-Institution Transfers

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Inter-Institutional Transfers Regional social accounting matrices, or SAMs, represent an IMPLAN extension for regional economic modeling. IMPLAN type interindustry models provide information on market transactions between firms, consumers, and other forms of final demands. SAMs provide information on non-market financial flows. SAMs capture payments of taxes by individuals and businesses, transfers of government funds to people and businesses, and transfer of funds from people to people. MIG has developed methodologies for creating local (county) area SAM data that is consistent with National Income and Produce Accounts (NIPA). This chapter discusses: SAM Framework SAM Data Development PCE Distribution Balancing

SAM Framework Essentially, SAM accounts are an extension of traditional inputoutput accounts. Like input-output analysis, a full social accounting matrix is a double entry booking system capable of tracing monetary flows through debits and credits similar to T-Accounts in basic financial accounting. The matrix format allows the double entry bookkeeping to be displayed in a single entry format. Figure 24-1 shows a typical SAM layout. The column entries represent expenditures (payments) made by the economic agents. The row entries represent receipts or income to agents. By accounting definition, all receipts must equal all expenditures. That is, the SAM must balance. The shaded areas in Figure 24-1 are the inter-industry transfer cells.

Value Added

Factors

Factor Trade Total Factor Outlay

Total Industry Outlay

Total

Transfers

Imports

Total Commodity Outlay

Sales

Make

Commodity

Trade

Capital

Enterprises

Institutions

Use

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Industry

Industry

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Chapter 24: Inter-Institution Transfers

Figure 24-1 SAM Framework

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Total Institution Outlay

Imports

Transfers

Consumption

Institutitons

Total Enterprise Outlay

Transfers

Enterprises

Total Capital Outlay

Transfer

Transfers

Consumption

Capital

Total Trade Outlay

Exports

Exports

Exports

Exports

Exports

Trade

Total Trade Income

Total Capital Income

Total Enterprise Income

Total Institution Income

Total Factor Income

Total Commodity Income

Total Industry Income

Total

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The column and row entries represent the different economic actors. Following across the row, “Industry” represents industries producing goods and services. “Commodity” represents the goods and services consumed by industries and institutions. “Factors” are factors of production, such as employee compensation, proprietors’ income and other income. “Institutions” represents households, governments accounts. “Capital” represents investment and borrowing. “Enterprises” represent the distribution of corporate profits. “Exports” and “Imports” show monetary flows into and out of a region. Individual elements within the SAM tables include the use and make matrices and value-added. The use table shows the use of commodities by industry or the goods and services required to produce an industries output. The make table shows the make of commodities by industry, or who produces commodities. These are typical components of input-output models. Also found in typical I/O models are final demand or institutional consumption, exports and imports. The SAM adds non-industrial financial flows in addition to the typical I/O elements. Looking first at receipts or income, industries make payments to commodities for goods and services, payments to workers and profits (factors), payments to institutions (households, governments, capital) of distributions, taxes, and borrowing. Lastly, industries make payments to imports for use in production. The total is total industry outlay. Commodities make payments in the sense that there is a sum paid to produce commodities. There are also non-industrial sales of commodities from institutions. Institutional income is also distributed to other institutions. This is the real contribution of a SAM. These inter-institutional transfers show the flow of non-industrial funds. Inter-institutional transfers include transfers from businesses to households (interest and dividend payments), transfers from people to government (payment of taxes), and transfers from governments to people (social security, unemployment compensation among others). Inter-institutional transfers also include the capital accounts. For businesses, this is investment and borrowing. For households this is net savings. Government capital accounts show surplus and deficits.

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SAM Data Development Since the IMPLAN data provided an I/O data and model source, it is natural to develop SAM accounts that could be used with the IMPLAN data. A SAM with complete accounting of flows actually serves as a check for IMPLAN data since a SAM gives a complete picture of taxation and savings for households and governments.

National SAM The U.S. SAM data comes directly from the National Income and Product Accounts.

State and County SAM Data State and county SAM data is derived from a number of sources. The IMPLAN data contributes a large portion of the local area data. All inter-industry information is derived from the MIG IMPLAN databases. IMPLAN gives the SAM the use and make tables, the factor receipts, and the commodities purchased by institutions. Other SAM elements are derived from a variety of sources.

Household Transfer Income Data Estimates of household income and expenditure transfers come from four primary sources. The first is the IMPLAN industry data. The second is the REIS CA 35 Table. The third is from the BLS Consumer Expenditure Survey. The fourth is the Annual Survey of Government Finances. Household income received from industries is from the IMPLAN data. This income is by place of work, and is income received by individuals where they perform the work. Social accounting data is by definition place-of-residence. The REIS data provides the residency adjustment. Household income is adjusted for place-of-residence so it is consistent with other sources of household income. Residence-based household income is derived from the Bureau of Economic Analysis (BEA)’s Regional Economic Information System (REIS) data. REIS has estimates of income by place of work and place of residence, as well as some transfer payments data. Household expenditures on federal taxes are from the CES data distributed to states and counties on the basis of the area’s demographic makeup. It is assumed that within different income groups, taxation and spending patterns are similar across the nation. CES data is available for regions, however, to get income and

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expenditure patterns by different region and different income group would not be possible given the small sample sizes. The results would not be statistically significant. We have several income categories nationally as opposed to one income group which varies by several regions.

State and Local Government Transfers Data State and local government income and expenditures comes from the Annual Survey of State and Local Government Expenditures. Figure Table 24-2. State and Local Transfers Data State Code County Code Government Name Government Code Property Tax Total Sales Tax Alcoholic Beverage Tax Amusement License Corporate License Hunting Motor Vehicle Tax Motor Vehicle Operators PU License Occupational Business License Other License Individual Income Tax Corporate Income Tax Death and Gift Tax Document Stock Tax Severance Tax Taxes NEC Interest Earnings Fines Forfeits Rents Royalties State Education Transfers Table 4 continued: State & Local Transfers Data Local Education Transfers State Local Social Security Federal Grants In Aid State and Local Borrowing Corporate Interest Personal Interest Federal Education Transfers Total Education Operations State and Local Sales State and Local Non-Education Purchases Federal Transfers Data

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Chapter 24: Inter-Institution Transfers State and local income and expenditures comes directly from the current Survey of Government. This data gives state and local revenues and expenditures by specific category.

Federal Transfers Estimates of federal income come from estimates of household tax liabilities based on the CES data. Corporate taxes are estimated from the IMPLAN Other Property Type Income (OPTI) data. The State and local transfers data also includes federal payments to state and local governments. Federal government income and expenditures for states and counties are estimated from CES information and local demographic data. The relationship between income and taxes is analyzed and then projected to the states and counties to form initial estimates.

Capital The capital accounts are a balancing item that is allowed to float. If the other elements are specified correctly, the capital accounts will be accurate.

Trade Trade is also a balancing item, although some components are specified. Trade flows of labor income are captured by the place-ofresidence adjustment made from the REIS data. The remainder of the trade entries are used for balancing. The trade accounts are primarily from the IMPLAN data and are also used as balancing elements.

Personal Consumption Expenditure (PCE) Distribution Accuracy in the distribution of household spending and income is critical since mistakes are quite apparent in tax and savings rates. For household commodity purchases, the primary source is the BLS Consumer Expenditure Survey (CES). This is also the source for splitting the household commodity purchases and tax payments into three income segments. The source for splitting household income into three segments is the Census of Population. This caused some difficulty in that CES and Census household definitions are different. CES uses a consumer unit as their basis, Census uses the household. As a result, there are 85 million

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consumer units in the U.S. and 93 million households. There is also some problems with CES income estimation. There appears to be significant under-reporting of income, which seems to enlarge the lower income segments. However, after adjusting the CES income to REIS income totals, the resulting tax and savings rates appear to be quite reasonable. There is, one other modification made on households. Household income received from industries is an establishment-based value. That is the industry pays wages and salaries to employees regardless if they live in the region or not. Household expenditures are residential-based. Household spending occurs by where the household resides. As a result, there is a residence adjustment made to the income data to make it a place of residence value. The data elements are all balanced to the national SAM totals to ensure consistency across the regions. In this way, the state and local totals are consistent with national income and product accounts.

Balancing After the data is collected, it is necessary to balance the SAM table. Balancing is accomplished by making adjustments in the imports, exports, and capital accounts. The IMPLAN Pro software balances the SAM. Balancing of households can serve as an example. Households receive income from industries and institutions. With this income, households buy goods and services, pay taxes, and save for the future. We have information about income, consumption and tax payments. The difference between income and spending (or saving) is a balancing element. Savings can be either positive or negative. Negative savings means the household spends more than it makes. This is accomplished by withdrawing from household capital stocks or borrowing from financial institutions. Other balancing elements work similarly. The difference between government income and spending is a surplus or deficit (not surprisingly, the SAM shows the U.S. deficit). Foreign trade balance occurs between imports and exports and the balance of trade.

Chapter 25: National Matrices & Tables

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National Matrices and Tables The structural matrices form the basis for the inter-industry flows (the flow of dollars between industries). There are two structural matrices, the Use Matrix and the Make Matrix. The Use Matrix shows the use of commodities by each industry. The Make Matrix shows the production of commodities made by each industry. The Use Matrix, in coefficient form, is the Absorption Matrix (also known as the Production Functions). The make matrix has two coefficient forms, the Byproducts Matrix and the Market Shares Matrix. The Byproducts Matrix represents the proportion of each commodity an industry produces. The Market Shares Matrix represents the proportion of each commodity within a region produced by each industry. This chapter discusses: National I/O Structural Model Make Matrix Use Matrix Margins Deflators Regional Purchase Coefficients (RPCs)

National I/O Structural Model The two national structural matrices, the Use and Make, are developed in conjunction with the IMPLAN database. The Use and Make Tables are actually stored in IMPLAN in their coefficient forms: Absorption and Byproducts Matrices. The structural matrices are developed along with the complete set of national I/O accounts as outlined in the previous sections.

Make Matrix The Make Matrix represents the make, or production, of commodities by industry. The Bureau of Economic Analysis (BEA) Benchmark I/O Study of the U.S. Make Table forms the basis for the IMPLAN model.

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Chapter 25: National Matrices & Tables The Benchmark IO make table is price updated to the current year using the price deflators discussed in Chapter 9. The U.S. Make Matrix is rearranged into IMPLAN format and dividing each row element by the row total forms a Byproducts Matrix (see the Analysis Guide for a complete discussion). Since the Make Matrix is stored as coefficients, and we did not have total commodity output (TCO) controls, it is not necessary to RAS the Make Table. Accepting the Byproducts Matrix now makes it possible to calculate TCO as the sum of each column of total industry output (TIO), distributed across the matrix.

Use Matrix The creation of the Use Matrix is more complex than the Make Matrix. The final demand, value-added, total industry output and total commodity output data are first estimated as described in the previous sections. Matrix RAS

We then bridge the 508 sector BEA Use Table to the 509 IMPLAN sectors. but requires splitting out trade sectors. In general, there is very little difference in production functions for a BEA sector split over several IMPLAN sectors. In cases where one BEA sector is split into several IMPLAN sectors, the split is based on income. Once the resectoring of the BEA data is complete, the adjustment of the Use Table can be done. The value-added, final demands, total industry and commodity output are placed in a table as shown in Figure 25-1. At this point, all information except for the Use and Trade Matrix is complete. Trade is completed once the software has processed the data. To complete the national Use Matrix, the intermediate industry and commodity output values are calculated. The intermediate outputs are used as new row and column control totals for the Use Matrix. The Use Matrix is then RASed to match the new row and column totals.

The RAS is a procedure used to re-balance matrices. This procedure is used numerous times throughout the IMPLAN database development process. The procedure requires a matrix of size mxn and a vector of row size n and column size m totals. The preRAS matrix row and column totals do not equal the vector of row and column totals. The RAS procedure forces the matrix to add to the vector of row and column totals. This is accomplished by allocating the vector row and column elements to the matrix based on the matrices distribution pattern. The result is a new matrix consistent with the vector of row and column totals. RAS, sometimes called the Ratio Allocation System or Richard A. Stone system, actually refers to the variable appearance of the coefficient matrix in the original paper: (rAs).

Chapter 25: National Matrices & Tables

273

This procedure calculates the difference between the new and old row and column totals and distributes the differences within the matrix. This is done iteratively until the differences drop to zero. Figure 25-1 IO Layout Industry Industry Commodity Use ?? Factors Institutions Trade Total

Commodity Make

Factors

Institution Final Demands

Value Added Sales Imports TIO

Transfers Trade

Transfers Imports

Trade Exports Exports

Total TCO TIO

Exports Exports

TCO

After the adjustments are made, the national model balances with total value-added, equaling total final demand. Total commodity output equals total industry output, making intermediate industry and commodity output equivalent.

MARGINS In input-output models, including IMPLAN, all expenditures are in terms of producer prices. This allocates all expenditures to the industries that produce goods or services. As a result, any data received in purchaser prices (prices paid by final consumers) needs to be converted or allocated to the producing industries. Margins enable one to move from producer to purchaser prices or vice-versa. A complete discussion of margins is in the Analysis Guide. An example is probably the easiest means to describe margins. Assume that a consumer spends $1.00 at a retail store. A portion of that dollar, 20 cents in this case, is retained by the retailer. A portion, 20 cents, of the dollar is paid to the wholesaler and so forth until the dollar is fully allocated (Figure 25-2). Figure 25-2 Margins

Sector Retail Wholesale Transportation Manufacturing TOTAL

Dollars $0.20 $0.10 $0.10 $0.60 $1.00

Margin 20% 10% 10% 60% 100%

Margins are particularly important in the formation of the Personal Consumption Expenditure (PCE) values. Together with each personal

274

Chapter 25: National Matrices & Tables consumption category is a set of margins showing the distribution of the PCE Purchaser Price. Margins are derived from the Bureau of Economic Analysis InputOutput tables. The margins used to form the PCE data elements are compiled from data from the BEA Detailed Workfile. The data from BEA provide information on the margins associated with each of the different Personal Consumption categories. These PCE categories are modified to fit the IMPLAN sectoring scheme.

Deflators Deflators account for relative price changes during different time periods and are derived from the Bureau of Labor Statistics (BLS) Growth Model. BLS produces a time series of output estimates for each of the 224 BLS industry sectors as part of the Growth Model. The output estimates are used to create the output deflators for the 224 sectors. The 224 sector data is then allocated to the IMPLAN 528 sectors. All IMPLAN sectors comprising a BLS sector are allowed to have the same deflator. Appendix G shows the bridging of the BLS 224 scheme to the IMPLAN 528 scheme. BLS data only includes industry sectors. To get deflators for value added/income components of the data, Implicit PCE Deflators from BEA’s survey of Current Business are used.

Regional Purchase Coefficients IMPLAN is a non-survey I/O model and is derived from a national model. The national model represents the "average" condition for a particular industry. Consequently, without adjustments for regional differences, the national production functions do not necessarily represent industries comprising a local or regional economy. Stevens and Trainor (1980) note that estimating regional trade flows (imports and exports) across regional boundaries is perhaps the largest source of error in deriving non-survey I/O models. Use of Regional Purchasing Coefficients (RPCs) is one way to eliminate some of the bias inherent in non-survey models. Gross regional trade flows (gross exports and imports) or commodities are estimated by developing regional purchase coefficients (RPCs). An RPC represents the proportion of the total demands for a given

Chapter 25: National Matrices & Tables

275

commodity that is supplied by the region to itself. For example, given an RPC value of 0.8 for the commodity "fish", then 80% of the demand by fish processors, fish wholesalers, foreign exports, and all other demands for fish are met by local producers. Alternatively 20% (l.0RPC) of the demand is imported.

Source of Data for Predictive Equations Empirical trade flow data was obtained from the 1977 Multi-Regional Input-Output Accounts (MRIOA) which is a cross-sectional data base of state input-output accounts linked with consistent cross interstate trade flows. The MRIOA provided 51 125 sector input-output tables for all states and the District of Columbia, accompanied by 125 sets of industry-specific interstate trade flow matrices by mode of transportation. The parameters for the RPC predictive equation are calculated for the first 24 (sectors with a shippable commodity) of the 125 MRIOA commodity sectors. Each of the MRIOA sectors corresponds exactly to one or several of IMPLAN commodity sectors. The service sectors (non-shippable commodities) are the observed values for the state.

What causes errors in trade flow estimation? 1. A particular commodity or service classification may contain a number of different grades or attributes. A quality difference, real or perceived, can determine whether or not a local consumer is able or willing to purchase a locally produced commodity or service. Aggregating different products or services into a single category aggravate this problem. Goats and rabbits are quite often lumped into a single "Miscellaneous livestock" category, yet a fur coat manufacturer will not view them as substitutable. 2. Given a choice between two suppliers of a substitutable commodity, a consumer may still choose the one that is more expensive, or of inferior quality for any one of a number of cultural, administrative, or other perception reasons. A tourist may buy hand-made Indian jewelry even though the similar jewelry costs less and may be of better quality when machine made. An American may buy a car made in Detroit when a cheaper and better quality car can be imported. Any number of factors can affect costs and cause inefficiencies observed when haulers of an identical commodity pass each other going opposite directions on the highway (otherwise known as "cross-hauling").

Chapter 26: Database Validation 277

C H A P T E R

2 6

Database Validation Validating the database is an important final step in the data development process. This chapter discusses: Validation Process Force Account Construction Adjustment

Validation Process Once the national model is complete and balanced, it is checked thoroughly for errors. The model is built and multipliers generated. All values are passed to the states and counties based on the procedures outlined in Chapter 20-25. Once the data is passed to the states and counties, an extensive validation process takes place. State and county models are built and evaluated. The data is also passed through a program that calculates ratios on every value in the database. Any outliers are examined and either documented or fixed if a program or data bug is the cause. Once this process is complete, the databases are released to the public. Users should still examine their study areas and make changes if required. Some users like to update values to more recent time periods or may have additional data. Users should also examine the model’s regional purchase coefficients. RPCs will be discussed in the next section.

Force Account Construction Adjustment To conform to I/O accounting definitions, IMPLAN databases have an adjustment made at the time of construction. This adjustment is called the force account construction adjustment and is an attempt to keep production activities consistent across sectors. Some non-construction industries, such as mining, have a large construction component. The force account construction adjustment moves an industry’s construction activity from the industry’s sector to the appropriate construction sector.

278

Chapter 26: Database Validation Construction sectors can have production functions very different than the industry involving the construction. By keeping the activities separated, expenditures made during production will be more accurately allocated. For example, a mine usually requires the construction of a road to get to the mining site. The force account adjustment removes the construction activity from the mining sector and places it into the road construction sector. The net result is that mining values may be slightly smaller than published estimates and the construction values may be slightly higher.

Citations

279

C I T A T I O N S

Database Literature Citations Executive Office of the President. Standard Industrial Classification Manual. Executive Office of Management and Budget, Washington D.C., 1987. General Services Administration, Unpublished Data, Federal Procurement Data Center, Washington, 1990-97. International Trade Association, "1997 Trade Statistics", Unpublished Data, International Trade Association, 1997. Palmer, C. and L.E. Siverts, IMPLAN Analysis Guide. U.S. Department of Agriculture, Forest Service, Systems Application Unit, Land Management Planning, Fort Collins, Colorado, 1985. Stevens, B. and G. Trainor. “Error generation on regional inputoutput analysis and its implications for non-survey models”. Ed. S. Pleeter. Economic Impact Analysis: Methodology and Applications. Amsterdam: Marinus Nijhoff, 1980, p. 68-84. U.S. Department of Agriculture, Agricultural Outlook, Economic Research Service, Washington, 1997. U.S. Department of Agriculture, "Federal Timber Sales", Unpublished Data, U.S. Forest Service, Fort Collins, CO, 1997. U.S. Department of Agriculture, Published Estimates of Crop Production, National Agricultural Statistical Service, Washington, 1997. U.S. Department of Commerce. "Annual Survey of Governments, 19xx: Finance Statistics". Unpublished Data, Bureau of the Census, Washington, [producer] current. Ann Arbor, MI: Inter-University Consortium for Political and Social Research [distributor], 1997. U.S. Department of Commerce. "Annual Revision of the U.S. National Income and Product Accounts". Survey of Current Business, Bureau of Economic Analysis. July, 1992.

280

Citations U.S. Department of Commerce, "Annual Survey of Governments, 1992: Employment Statistics" Unpublished Data, Bureau of the Census, Washington, [producer] current. Ann Arbor, MI: Inter-University Consortium for Political and Social Research [distributor], 1992. U.S. Department of Commerce, "Annual Survey of Manufactures, Statistics for Industry Groups and Industries", Bureau of the Census, Washington, 1997. U.S. Department of Commerce, current Annual Survey of Retail Trade, Bureau of the Census, Washington, 1997. U.S. Department of Commerce, “Annual Survey of Service Industries Trade”, Washington DC, 1997. U.S. Department of Commerce, "BLS Growth Model", Unpublished Data, Bureau of Labor Statistics, Office of Employment Projections. 19xx. U.S. Department of Commerce. BLS Handbook of Methods. Department of Labor, Bureau of Labor Statistics, Washington, 1989. U.S. Department of Commerce, "The 1992 Census of Agriculture, Geographic Area Series", Computer CD, Bureau of the Census, Washington, 1995. U.S. Department of Commerce, "The 1992 Census of Construction", Computer CD, Bureau of the Census, Washington, current. 1995 U.S. Department of Commerce, "Consumer Expenditure Survey, Diary and Survey", Unpublished data, Bureau of Labor Statistics, Washington, 19xx. U.S. Department of Commerce, "County Business Patterns, 19xx", Unpublished Data, Bureau of the Census, Washington, 19xx. U.S. Department of Commerce, "Counties and County Equivilents of the States of the United States", National Bureau of Standards, Washington, 1979. U.S. Department of Commerce. "The Detailed Input-Output Structure of the U.S. Economy, 1977, Volume I, The Use and Make of Commodities by Industries", Bureau of Economic Analysis, Washington DC, 1984

Citations

281

U.S. Department of Commerce. "The Detailed Input-Output Structure of the U.S. Economy, 1977, Volume II, Transactions", Bureau of Economic Analysis, Washington DC, 1984. U.S. Department of Commerce. 1980. Definitions and Conventions of the 1972 Input-Output Study. Bureau of Economic Analysis, Washington DC. U.S. Department of Commerce, "Employment and Employment Compensation in the 1977 Input-Output Accounts", Survey of Current Business, Bureau of Economic Analysis, November, 1985. U.S. Department of Commerce, "Foreign Trade Statistics", Computer Tape, Bureau of the Census, February 1991. U.S. Department of Commerce, "4 Component Gross State Product by State", Unpublished Data, Bureau of Economic Analysis, 1989, 1991. U.S. Department of Commerce, "Guide to Foreign Trade Statistics", Bureau of the Census, February 1991. U.S. Department of Commerce, "The 1982 Input-Output Structure of the U.S. Economy", Computer Tape, Bureau of Economic Analysis, Inter-industry Division, 1991. U.S. Department of Commerce, "Personal Consumption Expenditures and Gross Private Fixed Investment Item Detail", Unpublished Data, accession number: BEA IED 84008(1984). U.S. Department of Commerce, "current Regional Economic Information System Data", Computer CD & Diskettes, Bureau of Economic Analysis, Regional Measurement Division, 1991 U.S. Department of Commerce, Unpublished Data, Bureau of Labor Statistics, Covered Employment and Wages (ES202 Program), Washington, 1992 U.S. Department of Commerce, "Wealth Data", Unpublished Data, Bureau of Economic Analysis, Washington, 1992. US. Department of Health and Human Services. 1983. The multiregional input-output accounts, 1977. Vol. I-VI, Jack Yaucett & Associates, Report submitted to the US,

282

Citations Department of Health and Human Services, Contract No. HHS-100-81-0057, July 1983. U.S. Department of the Interior, Mineral Commodity Summaries 1992. Bureau of Mines, Washington, 1992 U.S. Department of Interior, 1987 Minerals Yearbook. Bureau of Mines, Washington, 1989. U.S. Department of Interior, Survey Methods and Statistical Summary of Nonfuel Minerals, Bureau of Mines, Washington, April 1992. Yuskavage, Robert E, "Employment and Employee Compensation in the 1977 Input-Output Accounts". Survey of Current Business. November, 1985,pp 11-25.

GLOSSARY AND APPENDICES

Glossary

285

G L O S S A R Y

Glossary Absorption Table

A coefficient form of the use table derived by dividing each element of the use table by total industry output.

Backward Linkage

Links an industry to its suppliers or a household (an institution) and the producers of household goods and services.

Balanced Accounts

In the complete set of social accounts, commodity production is equal to commodity use for each commodity and industry output is equal to industry outlay for each industry.

Byproducts Table

A coefficient form of the make table derived by dividing each element by the make table row totals.

Commodities

The goods and services produced by industries.

Direct Coefficients

For each dollar outlay for a given industry the amount used for purchase of goods and service from each industry sector modeled.

Direct Effects

The set of expenditures applied to the predictive model (i.e., I/O multipliers) for impact analysis.

Final Demands

Consist of purchases of goods and services for final consumption as opposed to an intermediate purchase where the good will be further remanufactured.

Forward Linkage

Links between an industry producing a good or service, and the consumers of the good or service.

Indirect Effects

The inter-industry effects of input-output analysis. The impacts above and beyond

286

Glossary the direct effects when applied to the Type I multipliers. Induced Effects

The impacts of household expenditures in I/O analysis.

Industries

The collection of businesses in an economy within a given region. purchasing goods and services and paying workers.

Input-Output Accounts

The accounting of all current money flows from and to (outlays and outputs) industries located

Input-Output Analysis:

An economic model that allows the assessment of change in overall economic activity as a result of some corresponding change in one or several activities

Institutions

Refer to the type of final demand sector. They are personal consumption expenditures, or purchases made by households, federal, state, and local purchases, investment purchases, and trade.

Inter-institutional Transactions

Transactions between those who are typically final consumers in the regional economic accounts. Inter-institutional transactions include payments of taxes by individuals or businesses to government, or government payments to individuals or businesses like social security payments. These inter-institutional transactions are captured in the complete social accounts.

Labor Income

In general it represents all forms of employment income. In I/O it is the sum of employee compensation and proprietor income (except for IMPLAN multiplier report 603 which includes only employee compensation).

Local Purchase Coefficients

Proportion of specified impacts which will be applied to model multipliers. We allow the software to estimate a portion to be directly imported and therefore that

Glossary

287

portion will not have indirect or induced effects. Make Table

The make of commodities by industry. It shows each industry’s production of goods and services. It is possible for a single industry to produce more than a single category of good or service.

Margins

Represent the difference between producer and purchaser prices.

Market Shares Table

A coefficient form of the make table derived by dividing each make element by the make column total.

Net Commodity Supply

Total value of a commodity produced by the region net of the value of foreign export.

Predictive Model

The mathematical representation of the input-output multipliers. Mathematically it is: X = (I - A)-1 * Y.

Primary Commodity

Of the commodities produced by an industry, it has the greatest value. The industry is classified based on its primary commodity.

Primary I/O Studies

Input-output studies based on data collected directly from industries.

Producer Prices

Prices of the goods at the site of production for commodity industries. For the margin industries, it is the value added (or the margin) to the value of goods purchased for resale.

Production Function

The relationship between the output of a good and the inputs required to produce that good for any given industry.

Purchaser Prices

Prices paid by the end user of the good or service at a retail store.

Regional Economic

The regional economic accounts show all

288

Glossary Accounts

dollar transactions, both inter-industrial and to final consumers for the study area in question.

Secondary Commodities

The commodities produced by a single industry which are of lesser value than the primary commodity i.e., byproducts) produced by retail store.

Secondary I/O Studies

Input-output studies based on reformulation of data collected from a primary study.

Social Accounting Matrices (SAMs)

A set of regional economic accounts which describe transfers between institutions, as well as, value added components.

RPC (Regional Purchase Coefficients)

Ratios representing the portion of regional demands purchased from local producers. RPCs are used to estimate the trade flows of the model before multipliers are generated.

RSC (Regional Sales Coefficients)

Ratios representing the portion of regional production used to satisfy local demand.

T-Accounts

A standard layout for double-entry accounting. Assets are recorded on the left half of the “T” and liabilities (including profits) are recorded on the right. The sum of the left and right halves balance -i.e., are equal.

Total Regional Commodity Supply

Total value of locally produced commodity supply for a region. Includes industry and institutional sources.

Type I Multipliers

The total production requirements of all industries within a given region to meet the industry demands triggered by $1 of consumption of the goods/services produced by a specified industry.

Type II Multipliers

The total production requirements of all industries within a given region to meet the industry and household demands triggered by $1 of consumption of the

Glossary

289

goods/services produced by a specified industry. Household income and expenditures are treated as an additional regional industry. Type III Multipliers

The total production requirements of all industries within a given region to meet the industry and household demands triggered by $1 of consumption of the goods/services produced by a specified industry. The induced component is employment based using the regional average PCE per person.

Type SAM Multipliers

The total production requirements of all industries within a given region to meet the industry and institution(s) demands, as specified by the user, triggered by $1 of consumption of the goods/services produced by a specified industry. The user specifies which of the final demands are to be incorporated into the Leontief inverse.

Use Table

The use of commodities by industry. It shows business purchases of goods and services for use in the production process.

Value-Added

Payments made by industry to workers, interest, profits and indirect business taxes.

Appendix A: IMPLAN Sector Scheme

A P P E N D I X

A

IMPLAN Sector Scheme This appendix shows the IMPLAN data sectoring for IMPLAN data base files. These sectors are bridged to the NAICS code and the BEA commodity classifications for the current input-output benchmark tables. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38

IMPLAN Description Oilseed farming Grain farming Vegetable and melon farming Tree nut farming Fruit farming Greenhouse and nursery production Tobacco farming Cotton farming Sugarcane and sugar beet farming All other crop farming Cattle ranching and farming Poultry and egg production Animal production, except cattle and poultry and eggs Logging Forest nurseries, forest products, and timber tracts Fishing Hunting and trapping Agriculture and forestry support activities Oil and gas extraction Coal mining Iron ore mining Copper, nickel, lead, and zinc mining Gold, silver, and other metal ore mining Stone mining and quarrying Sand, gravel, clay, and refractory mining Other nonmetallic mineral mining Drilling oil and gas wells Support activities for oil and gas operations Support activities for other mining Power generation and supply Natural gas distribution Water, sewage and other systems New residential 1-unit structures, nonfarm New multifamily housing structures, nonfarm New residential additions and alterations, nonfarm New farm housing units and additions and alterations Manufacturing and industrial buildings Commercial and institutional buildings

BEA 1997 1111A0 1111B0 111200 111335 1113A0 111400 111910 111920 1119A0 1119B0 112100 112300 112A00 113300 113A00 114100 114200 115000 211000 212100 212210 212230 2122A0 212310 212320 212390 213111 213112 21311A 221100 221200 221300 230110 230120 230130 230140 230210 230220

NAICS 11111 11112 11113 11114 1112 111335 11131 11132 1114 11191 11192 11193 111991 11194 111992 11211 11212 1123 1122 1124 1133 1131 1132 1141 1142 115 211 2121 21221 21223 21222 21229 21231 21232 21239 213111 213112 213113 213114 2211 2212 2213 23* 23* 23* 23* 23* 23*

11115

11116

11119

11133 exc. 111335

111998 11213 1125

213115

1129

291

292 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88

Appendix A: IMPLAN Sector Scheme IMPLAN Description BEA 1997 Highway, street, bridge, and tunnel construction 230230 Water, sewer, and pipeline construction 230240 Other new construction 230250 Maintenance and repair of farm and nonfarm residential 230310 Maintenance and repair of nonresidential buildings 230320 Maintenance and repair of highways, streets, bridges, 230330 Other maintenance and repair construction 230340 Dog and cat food manufacturing 311111 Other animal food manufacturing 311119 Flour milling 311211 Rice milling 311212 Malt manufacturing 311213 Wet corn milling 311221 Soybean processing 311222 Other oilseed processing 311223 Fats and oils refining and blending 311225 Breakfast cereal manufacturing 311230 Sugar manufacturing 311310 Confectionery manufacturing from cacao beans 311320 Confectionery manufacturing from purchased chocolate 311330 Nonchocolate confectionery manufacturing 311340 Frozen food manufacturing 311410 Fruit and vegetable canning and drying 311420 Fluid milk manufacturing 311511 Creamery butter manufacturing 311512 Cheese manufacturing 311513 Dry, condensed, and evaporated dairy products 311514 Ice cream and frozen dessert manufacturing 311520 Animal, except poultry, slaughtering 311611 Meat processed from carcasses 311612 Rendering and meat byproduct processing 311613 Poultry processing 311615 Seafood product preparation and packaging 311700 Frozen cakes and other pastries manufacturing 311813 Bread and bakery product, except frozen, manufacturing 31181A Cookie and cracker manufacturing 311821 Mixes and dough made from purchased flour 311822 Dry pasta manufacturing 311823 Tortilla manufacturing 311830 Roasted nuts and peanut butter manufacturing 311911 Other snack food manufacturing 311919 Coffee and tea manufacturing 311920 Flavoring syrup and concentrate manufacturing 311930 Mayonnaise, dressing, and sauce manufacturing 311941 Spice and extract manufacturing 311942 All other food manufacturing 311990 Soft drink and ice manufacturing 312110 Breweries 312120 Wineries 312130 Distilleries 312140

NAICS 23* 23* 23* 23* 23* 23* 23* 311111 311119 311211 311212 311213 311221 311222 311223 311225 31123 31131 31132 31133 31134 31141 31142 311511 311512 311513 311514 31152 311611 311612 311613 311615 3117 311813 311811 311812 311821 311822 311823 31183 311911 311919 31192 31193 311941 311942 31199 31211 31212 31213 31214

Appendix A: IMPLAN Sector Scheme 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138

IMPLAN Description Tobacco stemming and redrying Cigarette manufacturing Other tobacco product manufacturing Fiber, yarn, and thread mills Broadwoven fabric mills Narrow fabric mills and schiffli embroidery Nonwoven fabric mills Knit fabric mills Textile and fabric finishing mills Fabric coating mills Carpet and rug mills Curtain and linen mills Textile bag and canvas mills Tire cord and tire fabric mills Other miscellaneous textile product mills Sheer hosiery mills Other hosiery and sock mills Other apparel knitting mills Cut and sew apparel manufacturing Accessories and other apparel manufacturing Leather and hide tanning and finishing Footwear manufacturing Other leather product manufacturing Sawmills Wood preservation Reconstituted wood product manufacturing Veneer and plywood manufacturing Engineered wood member and truss manufacturing Wood windows and door manufacturing Cut stock, resawing lumber, and planing Other millwork, including flooring Wood container and pallet manufacturing Manufactured home, mobile home, manufacturing Prefabricated wood building manufacturing Miscellaneous wood product manufacturing Pulp mills Paper and paperboard mills Paperboard container manufacturing Flexible packaging foil manufacturing Surface-coated paperboard manufactuing Coated and laminated paper and packaging materials Coated and uncoated paper bag manufacturing Die-cut paper office supplies manufacturing Envelope manufacturing Stationery and related product manufacturing Sanitary paper product manufacturing All other converted paper product manufacturing Manifold business forms printing Books printing Blankbook and looseleaf binder manufacturing

BEA 1997 312210 312221 312229 313100 313210 313220 313230 313240 313310 313320 314110 314120 314910 314992 31499A 315111 315119 315190 315200 315900 316100 316200 316900 321113 321114 321219 32121A 32121B 321911 321912 321918 321920 321991 321992 321999 322110 3221A0 322210 322225 322226 32222A 32222B 322231 322232 322233 322291 322299 323116 323117 323118

NAICS 31221 312221 312229 3131 31321 31322 31323 31324 31331 31332 31411 31412 31491 314992 314991 314999 315111 315119 31519 3152 3159 3161 3162 3169 321113 321114 321219 321211 321212 321213 321214 321911 321912 321918 32192 321991 321992 321999 32211 32212 32213 32221 322225 322226 322221 322222 322223 322224 322231 322232 322233 322291 322299 323116 323117 323118

293

294 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188

Appendix A: IMPLAN Sector Scheme IMPLAN Description Commercial printing Tradebinding and related work Prepress services Petroleum refineries Asphalt paving mixture and block manufacturing Asphalt shingle and coating materials manufacturing Petroleum lubricating oil and grease manufacturing All other petroleum and coal products manufacturing Petrochemical manufacturing Industrial gas manufacturing Synthetic dye and pigment manufacturing Other basic inorganic chemical manufacturing Other basic organic chemical manufacturing Plastics material and resin manufacturing Synthetic rubber manufacturing Cellulosic organic fiber manufacturing Noncellulosic organic fiber manufacturing Nitrogenous fertilizer manufacturing Phosphatic fertilizer manufacturing Fertilizer, mixing only, manufacturing Pesticide and other agricultural chemical manufacturing Pharmaceutical and medicine manufacturing Paint and coating manufacturing Adhesive manufacturing Soap and other detergent manufacturing Polish and other sanitation good manufacturing Surface active agent manufacturing Toilet preparation manufacturing Printing ink manufacturing Explosives manufacturing Custom compounding of purchased resins Photographic film and chemical manufacturing Other miscellaneous chemical product manufacturing Plastics packaging materials, film and sheet Plastics pipe, fittings, and profile shapes Laminated plastics plate, sheet, and shapes Plastics bottle manufacturing Resilient floor covering manufacturing Plastics plumbing fixtures and all other plastics products Foam product manufacturing Tire manufacturing Rubber and plastics hose and belting manufacturing Other rubber product manufacturing Vitreous china plumbing fixture manufacturing Vitreous china and earthenware articles manufacturing Porcelain electrical supply manufacturing Brick and structural clay tile manufacturing Ceramic wall and floor tile manufacturing Nonclay refractory manufacturing Clay refractory and other structural clay products

BEA 1997 32311A 323121 323122 324110 324121 324122 324191 324199 325110 325120 325130 325180 325190 325211 325212 325221 325222 325311 325312 325314 325320 325400 325510 325520 325611 325612 325613 325620 325910 325920 325991 325992 325998 326110 326120 326130 326160 326192 32619A 3261A0 326210 326220 326290 327111 327112 327113 327121 327122 327125 32712A

NAICS 323111 323112 323113 323114 323115 323119 323121 323122 32411 324121 324122 324191 324199 32511 32512 32513 32518 32519 325211 325212 325221 325222 325311 325312 325314 32532 32541 32551 32552 325611 325612 325613 32562 32591 32592 325991 325992 325998 32611 32612 32613 32616 326192 326191 326199 32614 32615 32621 32622 32629 327111 327112 327113 327121 327122 327125 327123 327124

Appendix A: IMPLAN Sector Scheme 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238

IMPLAN Description Glass container manufacturing Glass and glass products, except glass containers Cement manufacturing Ready-mix concrete manufacturing Concrete block and brick manufacturing Concrete pipe manufacturing Other concrete product manufacturing Lime manufacturing Gypsum product manufacturing Abrasive product manufacturing Cut stone and stone product manufacturing Ground or treated minerals and earths manufacturing Mineral wool manufacturing Miscellaneous nonmetallic mineral products Iron and steel mills Ferroalloy and related product manufacturing Iron, steel pipe and tube from purchased steel Rolled steel shape manufacturing Steel wire drawing Alumina refining Primary aluminum production Secondary smelting and alloying of aluminum Aluminum sheet, plate, and foil manufacturing Aluminum extruded product manufacturing Other aluminum rolling and drawing Primary smelting and refining of copper Primary nonferrous metal, except copper and aluminum Copper rolling, drawing, and extruding Copper wire, except mechanical, drawing Secondary processing of copper Nonferrous metal, except copper and aluminum, Secondary processing of other nonferrous Ferrous metal foundries Aluminum foundries Nonferrous foundries, except aluminum Iron and steel forging Nonferrous forging Custom roll forming All other forging and stamping Cutlery and flatware, except precious, manufacturing Hand and edge tool manufacturing Saw blade and handsaw manufacturing Kitchen utensil, pot, and pan manufacturing Prefabricated metal buildings and components Fabricated structural metal manufacturing Plate work manufacturing Metal window and door manufacturing Sheet metal work manufacturing Ornamental and architectural metal work manufacturing Power boiler and heat exchanger manufacturing

BEA 1997 327213 32721A 327310 327320 327331 327332 327390 327410 327420 327910 327991 327992 327993 327999 331111 331112 331210 331221 331222 331311 331312 331314 331315 331316 331319 331411 331419 331421 331422 331423 331491 331492 331510 33152A 33152B 332111 332112 332114 33211A 332211 332212 332213 332214 332311 332312 332313 332321 332322 332323 332410

NAICS 327213 327211 327212 327215 32731 32732 327331 327332 32739 32741 32742 32791 327991 327992 327993 327999 331111 331112 33121 331221 331222 331311 331312 331314 331315 331316 331319 331411 331419 331421 331422 331423 331491 331492 33151 331521 331524 331522 331525 331528 332111 332112 332114 332115 332116 332117 332211 332212 332213 332214 332311 332312 332313 332321 332322 332323 33241

295

296 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288

Appendix A: IMPLAN Sector Scheme IMPLAN Description Metal tank, heavy gauge, manufacturing Metal can, box, and other container manufacturing Hardware manufacturing Spring and wire product manufacturing Machine shops Turned product and screw, nut, and bolt manufacturing Metal heat treating Metal coating and nonprecious engraving Electroplating, anodizing, and coloring metal Metal valve manufacturing Ball and roller bearing manufacturing Small arms manufacturing Other ordnance and accessories manufacturing Fabricated pipe and pipe fitting manufacturing Industrial pattern manufacturing Enameled iron and metal sanitary ware manufacturing Miscellaneous fabricated metal product manufacturing Ammunition manufacturing Farm machinery and equipment manufacturing Lawn and garden equipment manufacturing Construction machinery manufacturing Mining machinery and equipment manufacturing Oil and gas field machinery and equipment Sawmill and woodworking machinery Plastics and rubber industry machinery Paper industry machinery manufacturing Textile machinery manufacturing Printing machinery and equipment manufacturing Food product machinery manufacturing Semiconductor machinery manufacturing All other industrial machinery manufacturing Office machinery manufacturing Optical instrument and lens manufacturing Photographic and photocopying equipment Other commercial and service industry machinery Automatic vending, commercial laundry and drycleaning Air purification equipment manufacturing Industrial and commercial fan and blower manufacturing Heating equipment, except warm air furnaces AC, refrigeration, and forced air heating Industrial mold manufacturing Metal cutting machine tool manufacturing Metal forming machine tool manufacturing Special tool, die, jig, and fixture manufacturing Cutting tool and machine tool accessory manufacturing Rolling mill and other metalworking machinery Turbine and turbine generator set units manufacturing Other engine equipment manufacturing Speed changers and mechanical power transmission Pump and pumping equipment manufacturing

BEA 1997 332420 332430 332500 332600 332710 332720 332811 332812 332813 332910 332991 332994 332995 332996 332997 332998 332999 33299A 333111 333112 333120 333131 333132 333210 333220 333291 333292 333293 333294 333295 333298 333313 333314 333315 333319 33331A 333411 333412 333414 333415 333511 333512 333513 333514 333515 33351A 333611 333618 33361A 333911

NAICS 33242 33243 3325 3326 33271 33272 332811 332812 332813 33291 332991 332994 332995 332996 332997 332998 332999 332992 332993 333111 333112 33312 333131 333132 33321 33322 333291 333292 333293 333294 333295 333298 333313 333314 333315 333319 333311 333312 333411 333412 333414 333415 333511 333512 333513 333514 333515 333516 333518 333611 333618 333612 333613 333911

Appendix A: IMPLAN Sector Scheme 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338

IMPLAN Description Air and gas compressor manufacturing Measuring and dispensing pump manufacturing Elevator and moving stairway manufacturing Conveyor and conveying equipment manufacturing Overhead cranes, hoists, and monorail systems Industrial truck, trailer, and stacker manufacturing Power-driven handtool manufacturing Welding and soldering equipment manufacturing Packaging machinery manufacturing Industrial process furnace and oven manufacturing Fluid power cylinder and actuator manufacturing Fluid power pump and motor manufacturing Scales, balances, and miscellaneous general purpose Electronic computer manufacturing Computer storage device manufacturing Computer terminal manufacturing Other computer peripheral equipment manufacturing Telephone apparatus manufacturing Broadcast and wireless communications equipment Other communications equipment manufacturing Audio and video equipment manufacturing Electron tube manufacturing Semiconductors and related device manufacturing All other electronic component manufacturing Electromedical apparatus manufacturing Search, detection, and navigation instruments Automatic environmental control manufacturing Industrial process variable instruments Totalizing fluid meters and counting devices Electricity and signal testing instruments Analytical laboratory instrument manufacturing Irradiation apparatus manufacturing Watch, clock, and other measuring and controlling Software reproducing Audio and video media reproduction Magnetic and optical recording media manufacturing Electric lamp bulb and part manufacturing Lighting fixture manufacturing Electric housewares and household fan manufacturing Household vacuum cleaner manufacturing Household cooking appliance manufacturing Household refrigerator and home freezer manufacturing Household laundry equipment manufacturing Other major household appliance manufacturing Electric power and specialty transformer manufacturing Motor and generator manufacturing Switchgear and switchboard apparatus manufacturing Relay and industrial control manufacturing Storage battery manufacturing Primary battery manufacturing

BEA 1997 333912 333913 333921 333922 333923 333924 333991 333992 333993 333994 333995 333996 33399A 334111 334112 334113 334119 334210 334220 334290 334300 334411 334413 33441A 334510 334511 334512 334513 334514 334515 334516 334517 33451A 334611 334612 334613 335110 335120 335211 335212 335221 335222 335224 335228 335311 335312 335313 335314 335911 335912

297

NAICS 333912 333913 333921 333922 333923 333924 333991 333992 333993 333994 333995 333996 333997 333999 334111 334112 334113 334119 33421 33422 33429 3343 334411 334413 334412 334414 334415 334416 334417 334418 334419 334510 334511 334512 334513 334514 334515 334516 334517 334518 334519 334611 334612 334613 33511 33512 335211 335212 335221 335222 335224 335228 335311 335312 335313 335314 335911 335912

298 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388

Appendix A: IMPLAN Sector Scheme IMPLAN Description Fiber optic cable manufacturing Other communication and energy wire manufacturing Wiring device manufacturing Carbon and graphite product manufacturing Miscellaneous electrical equipment manufacturing Automobile and light truck manufacturing Heavy duty truck manufacturing Motor vehicle body manufacturing Truck trailer manufacturing Motor home manufacturing Travel trailer and camper manufacturing Motor vehicle parts manufacturing Aircraft manufacturing Aircraft engine and engine parts manufacturing Other aircraft parts and equipment Guided missile and space vehicle manufacturing Propulsion units and parts for space vehicles and Railroad rolling stock manufacturing Ship building and repairing Boat building Motorcycle, bicycle, and parts manufacturing Military armored vehicles and tank parts manufacturing All other transportation equipment manufacturing Wood kitchen cabinet and countertop manufacturing Upholstered household furniture manufacturing Nonupholstered wood household furniture Metal household furniture manufacturing Institutional furniture manufacturing Other household and institutional furniture Wood office furniture manufacturing Custom architectural woodwork and millwork Office furniture, except wood, manufacturing Showcases, partitions, shelving, and lockers Mattress manufacturing Blind and shade manufacturing Laboratory apparatus and furniture manufacturing Surgical and medical instrument manufacturing Surgical appliance and supplies manufacturing Dental equipment and supplies manufacturing Ophthalmic goods manufacturing Dental laboratories Jewelry and silverware manufacturing Sporting and athletic goods manufacturing Doll, toy, and game manufacturing Office supplies, except paper, manufacturing Sign manufacturing Gasket, packing, and sealing device manufacturing Musical instrument manufacturing Broom, brush, and mop manufacturing Burial casket manufacturing

BEA 1997 335921 335929 335930 335991 335999 336110 336120 336211 336212 336213 336214 336300 336411 336412 336413 336414 33641A 336500 336611 336612 336991 336992 336999 337110 337121 337122 337124 337127 33712A 337211 337212 337214 337215 337910 337920 339111 339112 339113 339114 339115 339116 339910 339920 339930 339940 339950 339991 339992 339994 339995

NAICS 335921 335929 33593 335991 335999 33611 33612 336211 336212 336213 336214 3363 336411 336412 336413 336414 336415 336419 3365 336611 336612 336991 336992 336999 33711 337121 337122 337124 337127 337125 337129 337211 337212 337214 337215 33791 33792 339111 339112 339113 339114 339115 339116 33991 33992 33993 33994 33995 339991 339992 339994 339995

Appendix A: IMPLAN Sector Scheme 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438

IMPLAN Description Buttons, pins, and all other miscellaneous Wholesale trade Air transportation Rail transportation Water transportation Truck transportation Transit and ground passenger transportation Pipeline transportation Scenic and sightseeing transportation and support Postal service Couriers and messengers Warehousing and storage Motor vehicle and parts dealers Furniture and home furnishings stores Electronics and appliance stores Building material and garden supply stores Food and beverage stores Health and personal care stores Gasoline stations Clothing and clothing accessories stores Sporting goods, hobby, book and music stores General merchandise stores Miscellaneous store retailers Nonstore retailers Newpaper publishers Periodical publishers Book publishers Database, directory, and other publishers Software publishers Motion picture and video industries Sound recording industries Radio and television broadcasting Cable networks and program distribution Telecommunications Information services Data processing services Nondepository credit intermediation and related Securities, commodity contracts, investments Insurance carriers Insurance agencies, brokerages, and related Funds, trusts, and other financial vehicles Monetary authorities and depository credit Real estate Automotive equipment rental and leasing Video tape and disc rental Machinery and equipment rental and leasing General and consumer goods rental except video tapes Lessors of nonfinancial intangible assets Legal services Accounting and bookkeeping services

BEA 1997 33999A 420000 481000 482000 483000 484000 485000 486000 48A000 491000 492000 493000 4A0000 4A0000 4A0000 4A0000 4A0000 4A0000 4A0000 4A0000 4A0000 4A0000 4A0000 4A0000 511110 511120 511130 5111A0 511200 512100 512200 513100 513200 513300 514100 514200 522A00 523000 524100 524200 525000 52A000 531000 532100 532230 532400 532A00 533000 541100 541200

NAICS 339993 339999 42 481 482 483 484 485 486 487 488 491110 492 493 441 442 443 444 445 446 447 448 451 452 453 454 51111 51112 51113 51114 51119 5112 5121 5122 5131 5132 5133 5141 5142 5222 5223 523 5241 5242 525 521 5221 531 5321 53223 5324 53221 53222 53229 533 5411 5412

5323

299

300 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488

Appendix A: IMPLAN Sector Scheme IMPLAN Description Architectural and engineering services Specialized design services Custom computer programming services Computer systems design services Other computer related services, including facilities Management consulting services Environmental and other technical consulting services Scientific research and development services Advertising and related services Photographic services Veterinary services All other miscellaneous professional and technical Management of companies and enterprises Office administrative services Facilities support services Employment services Business support services Travel arrangement and reservation services Investigation and security services Services to buildings and dwellings Other support services Waste management and remediation services Elementary and secondary schools Colleges, universities, and junior colleges Other educational services Home health care services Offices of physicians, dentists, and other health Other ambulatory health care services Hospitals Nursing and residential care facilities Child day care services Social assistance, except child day care services Performing arts companies Spectator sports Independent artists, writers, and performers Promoters of performing arts and sports and agents for Museums, historical sites, zoos, and parks Fitness and recreational sports centers Bowling centers Other amusement, gambling, and recreation industries Hotels and motels, including casino hotels Other accommodations Food services and drinking places Car washes Automotive repair and maintenance, except car washes Electronic equipment repair and maintenance Commercial machinery repair and maintenance Household goods repair and maintenance Personal care services Death care services

BEA 1997 541300 541400 541511 541512 54151A 541610 5416A0 541700 541800 541920 541940 5419A0 550000 561100 561200 561300 561400 561500 561600 561700 561900 562000 611100 611A00 611B00 621600 621A00 621B00 622000 623000 624400 624A00 711100 711200 711500 711A00 712000 713940 713950 713A00 7211A0 721A00 722000 811192 8111A0 811200 811300 811400 812100 812200

NAICS 5413 5414 541511 541512 541513 541519 54161 54162 54169 5417 5418 54192 54194 54191 54193 55 5611 5612 5613 5614 5615 5616 5617 5619 562 6111 6112 6113 6114 6115 6216 6211 6212 6214 6215 622 623 6244 6241 6242 7111 7112 7115 7113 7114 712 71394 71395 7131 7132 72111 72112 72119 7212 722 811192 81111 81112 8112 8113 8114 8121 8122

54199

6116

6117

6213 6219

6243

71391

71392

7213

811191 811198

71393

71399

Appendix A: IMPLAN Sector Scheme 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509

IMPLAN Description Drycleaning and laundry services Other personal services Religious organizations Grantmaking and giving and social advocacy Civic, social, professional and similar organizations Private households Federal electric utilities Other Federal Government enterprises State and local government passenger transit State and local government electric utilities Other State and local government enterprises Noncomparable imports Scrap Used and secondhand goods State & Local Education State & Local Non-Education Federal Military Federal Non-Military Rest of the world adjustment to final uses Inventory valuation adjustment Owner-occupied dwellings

BEA 1997 812300 812900 813100 813A00 813B00 814000 S00101 S00102 S00201 S00202 S00203 S00300 S00401 S00402 S00500 S00500 S00500 S00500 S00600 S00700 S00800

NAICS 8123 8129 8131 8132 8134 814

8133 8139

301

Appendix B: FIPS Codes

A P P E N D I X

303

B

FIPS Codes On the following pages are listed the Federal Information Processing Standard ("FIPS") Codes for each state and county in the U.S. The first two numbers identify the state, while the last three digits of the code classify the counties (see figure). ALABAMA State Code 01 01 01 01 01 01

County Code 001 003 005 007 009 011

Description Autauga Baldwin Barbour Bibb Blount Bullock

IMPLAN data file naming conventions use the FIPs codes. For example the county code for Larimer is ‘069’, so for the 1994 Larimer County, Colorado (CO) data file, the name is CO94-069.ODF

304

Appendix B: FIPS Codes

01

AL

ALABAMA

01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133

AUTAUGA BALDWIN BARBOUR BIBB BLOUNT BULLOCK BUTLER CALHOUN CHAMBERS CHEROKEE CHILTON CHOCTAW CLARKE CLAY CLEBURNE COFFEE COLBERT CONECUH COOSA COVINGTON CRENSHAW CULLMAN DALE DALLAS DE KALB ELMORE ESCAMBIA ETOWAH FAYETTE FRANKLIN GENEVA GREENE HALE HENRY HOUSTON JACKSON JEFFERSON LAMAR LAUDERDALE LAWRENCE LEE LIMESTONE LOWNDES MACON MADISON MARENGO MARION MARSHALL MOBILE MONROE MONTGOMERY MORGAN PERRY PICKENS PIKE RANDOLPH RUSSELL ST. CLAIR SHELBY SUMTER TALLADEGA TALLAPOOSA TUSCALOOSA WALKER WASHINGTON WILCOX WINSTON

02

AK

ALASKA

02 02 02

010 013 016

ALEUTIAN ISLANDS 2 ALEUTIANS EAST 2 ALEUTIANS WEST

1

02 02 02 02 02 02

020 050 060 068 070 090

02 02 02 02 02 02 02 02 02 02 02 02

100 110 122 130 140 150 164 170 180 185 188 201

02 02 02 02

220 231 232 240

02 02 02

261 270 280

02 02

282 290

ANCHORAGE BETHEL BRISTOL BAY 3 DENALI DILLINGHAM FAIRBANKS NORTH STAR HAINES JUNEAU KENAI PENINSULA KETCHIKAN GATEWAY 1 KOBUK KODIAK ISLAND 3 LAKE AND PENINSULA MATANUSKA-SUSITNA NOME NORTH SLOPE 2 NORTHWEST ARCTIC PRINCE OF WALESUTE KETCHIKAN SITKA 4 SKAGWAY-YAKUTAT-ANGOON 5 SKAGWAY-ANGOON SOUTHEAST FAIRBANKS VALDEZ-CORDOVA WADE HAMPTON WRANGELL PETERSBURG 5 YAKUTAT YUKON-KOYUKUK

04

AZ

ARIZONA

04 04 04 04 04 04 04 04 04 04 04 04 04 04 04

001 003 005 007 009 011 012 013 015 017 019 021 023 025 027

APACHE COCHISE COCONINO GILA GRAHAM GREENLEE LAPAZ2 MARICOPA MOHAVE NAVAJO PIMA PINAL SANTA CRUZ YAVAPAI YUMA

05

AR

ARKANSAS

05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045

ARKANSAS ASHLEY BAXTER BENTON BOONE BRADLEY CALHOUN CARROLL CHICOT CLARK CLAY CLEBURNE CLEVELAND COLUMBIA CONWAY CRAIGHEAD CRAWFORD CRITTENDEN CROSS DALLAS DESHA DREW FAULKNER

05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05 05

047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149

FRANKLIN FULTON GARLAND GRANT GREENE HEMPSTEAD HOT SPRING HOWARD INDEPENDENCE IZARD JACKSON JEFFERSON JOHNSON LAFAYETTE LAWRENCE LEE LINCOLN LITTLE RIVER LOGAN LONOKE MADISON MARION MILLER MISSISSIPPI MONROE MONTGOMERY NEVADA NEWTON OUACHITA PERRY PHILLIPS PIKE POINSETT POLK POPE PRAIRIE PULASKI RANDOLPH ST. FRANCIS SALINE SCOTT SEARCY SEBASTIAN SEVIER SHARP STONE UNION VAN BUREN WASHINGTON WHITE WOODRUFF YELL

06

CA

CALIFORNIA

06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039

ALAMEDA ALPINE AMADOR BUTTE CALAVERAS COLUSA CONTRA COSTA DEL NORTE EL DORADO FRESNO GLENN HUMBOLDT IMPERIAL INYO KERN KINGS LAKE LASSEN LOS ANGELES MADERA

Appendix B: FIPS Codes 305 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06 06

041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115

MARIN MARIPOSA MENDOCINO MERCED MODOC MONO MONTEREY NAPA NEVADA ORANGE PLACER PLUMAS RIVERSIDE SACRAMENTO SAN BENITO SAN BERNARDINO SAN DIEGO SAN FRANCISCO SAN JOAQUIN SAN LUIS OBISPO SAN MATEO SANTA BARBARA SANTA CLARA SANTA CRUZ SHASTA SIERRA SISKIYOU SOLANO SONOMA STANISLAUS SUTTER TEHAMA TRINITY TULARE TUOLUMNE VENTURA YOLO YUBA

08

CO

COLORADO

08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08

001 003 005 007 009 011 013 014 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065

ADAMS ALAMOSA ARAPAHOE ARCHULETA BACA BENT BOULDER 9 BROOMFIELD CHAFFEE CHEYENNE CLEAR CREEK CONEJOS COSTILLA CROWLEY CUSTER DELTA DENVER DOLORES DOUGLAS EAGLE ELBERT EL PASO FREMONT GARFIELD GILPIN GRAND GUNNISON HINSDALE HUERFANO JACKSON JEFFERSON KIOWA KIT CARSON LAKE

08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08 08

067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125

LA PLATA LARIMER LAS ANIMAS LINCOLN LOGAN MESA MINERAL MOFFAT MONTEZUMA MONTROSE MORGAN OTERO OURAY PARK PHILLIPS PITKIN PROWERS PUEBLO RIO BLANCO RIO GRANDE ROUTT SAGUACHE SAN JUAN SAN MIGUEL SEDGWICK SUMMIT TELLER WASHINGTON WELD YUMA

KENT NEW CASTLE SUSSEX

12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12

043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 086 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133

GLADES GULF HAMILTON HARDEE HENDRY HERNANDO HIGHLANDS HILLSBOROUGH HOLMES INDIAN RIVER JACKSON JEFFERSON LAFAYETTE LAKE LEE LEON LEVY LIBERTY MADISON MANATEE MARION MARTIN 7 MIAMI-DADE MONROE NASSAU OKALOOSA OKEECHOBEE ORANGE OSCEOLA PALM BEACH PASCO PINELLAS POLK PUTNAM ST. JOHNS ST. LUCIE SANTA ROSA SARASOTA SEMINOLE SUMTER SUWANNEE TAYLOR UNION VOLUSIA WAKULLA WALTON WASHINGTON

09

CT

CONNECTICUT

09 09 09 09 09 09 09 09

001 003 005 007 009 011 013 015

FAIRFIELD HARTFORD LITCHFIELD MIDDLESEX NEW HAVEN NEW LONDON TOLLAND WINDHAM

10

DE

DELAWARE

10 10 10

001 003 005

11

DC

DISTRICT OF COLUMBIA

13

GA

GEORGIA

11

001

WASHINGTON DC

12

FL

FLORIDA

12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041

ALACHUA BAKER BAY BRADFORD BREVARD BROWARD CALHOUN CHARLOTTE CITRUS CLAY COLLIER COLUMBIA 7 DADE DE SOTO DIXIE DUVAL ESCAMBIA FLAGLER FRANKLIN GADSDEN GILCHRIST

13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 043 045 047 049 051

APPLING ATKINSON BACON BAKER BALDWIN BANKS BARROW BARTOW BEN HILL BERRIEN BIBB BLECKLEY BRANTLEY BROOKS BRYAN BULLOCH BURKE BUTTS CALHOUN CAMDEN CANDLER CARROLL CATOOSA CHARLTON CHATHAM

306 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13

Appendix B: FIPS Codes 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195 197 199 201

CHATTAHOOCHEE CHATTOOGA CHEROKEE CLARKE CLAY CLAYTON CLINCH COBB COFFEE COLQUITT COLUMBIA COOK COWETA CRAWFORD CRISP DADE DAWSON DECATUR DE KALB DODGE DOOLY DOUGHERTY DOUGLAS EARLY ECHOLS EFFINGHAM ELBERT EMANUEL EVANS FANNIN FAYETTE FLOYD FORSYTH FRANKLIN FULTON GILMER GLASCOCK GLYNN GORDON GRADY GREENE GWINNETT HABERSHAM HALL HANCOCK HARALSON HARRIS HART HEARD HENRY HOUSTON IRWIN JACKSON JASPER JEFF DAVIS JEFFERSON JENKINS JOHNSON JONES LAMAR LANIER LAURENS LEE LIBERTY LINCOLN LONG LOWNDES LUMPKIN MCDUFFIE MCINTOSH MACON MADISON MARION MERIWETHER MILLER

13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13

205 207 209 211 213 215 217 219 221 223 225 227 229 231 233 235 237 239 241 243 245 247 249 251 253 255 257 259 261 263 265 267 269 271 273 275 277 279 281 283 285 287 289 291 293 295 297 299 301 303 305 307 309 311 313 315 317 319 321

MITCHELL MONROE MONTGOMERY MORGAN MURRAY MUSCOGEE NEWTON OCONEE OGLETHORPE PAULDING PEACH PICKENS PIERCE PIKE POLK PULASKI PUTNAM QUITMAN RABUN RANDOLPH RICHMOND ROCKDALE SCHLEY SCREVEN SEMINOLE SPALDING STEPHENS STEWART SUMTER TALBOT TALIAFERRO TATTNALL TAYLOR TELFAIR TERRELL THOMAS TIFT TOOMBS TOWNS TREUTLEN TROUP TURNER TWIGGS UNION UPSON WALKER WALTON WARE WARREN WASHINGTON WAYNE WEBSTER WHEELER WHITE WHITFIELD WILCOX WILKES WILKINSON WORTH

15

HI

HAWAII

15 15 15 15 15 15

001 003 007 009 501 901

HAWAII HONOLULU KAUAI 3 MAUI KALAWAO 2 MAUI KALAWAO 1 MAUI KALAWAO

16

ID

IDAHO

16 16 16 16

001 003 005 007

ADA ADAMS BANNOCK BEAR LAKE

16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16

009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087

BENEWAH BINGHAM BLAINE BOISE BONNER BONNEVILLE BOUNDARY BUTTE CAMAS CANYON CARIBOU CASSIA CLARK CLEARWATER CUSTER ELMORE FRANKLIN FREMONT GEM GOODING IDAHO JEFFERSON JEROME KOOTENAI LATAH LEMHI LEWIS LINCOLN MADISON MINIDOKA NEZ PERCE ONEIDA OWYHEE PAYETTE POWER SHOSHONE TETON TWIN FALLS VALLEY WASHINGTON

17

IL

ILLINOIS

17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063

ADAMS ALEXANDER BOND BOONE BROWN BUREAU CALHOUN CARROLL CASS CHAMPAIGN CHRISTIAN CLARK CLAY CLINTON COLES COOK CRAWFORD CUMBERLAND DE KALB DE WITT DOUGLAS DU PAGE EDGAR EDWARDS EFFINGHAM FAYETTE FORD FRANKLIN FULTON GALLATIN GREENE GRUNDY

Appendix B: FIPS Codes 307 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17

065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195 197 199 201 203

HAMILTON HANCOCK HARDIN HENDERSON HENRY IROQUOIS JACKSON JASPER JEFFERSON JERSEY JO DAVIESS JOHNSON KANE KANKAKEE KENDALL KNOX LAKE LA SALLE LAWRENCE LEE LIVINGSTON LOGAN MCDONOUGH MCHENRY MCLEAN MACON MACOUPIN MADISON MARION MARSHALL MASON MASSAC MENARD MERCER MONROE MONTGOMERY MORGAN MOULTRIE OGLE PEORIA PERRY PIATT PIKE POPE PULASKI PUTNAM RANDOLPH RICHLAND ROCK ISLAND ST. CLAIR SALINE SANGAMON SCHUYLER SCOTT SHELBY STARK STEPHENSON TAZEWELL UNION VERMILION WABASH WARREN WASHINGTON WAYNE WHITE WHITESIDE WILL WILLIAMSON WINNEBAGO WOODFORD

18

IN

INDIANA

18 18

001 003

ADAMS ALLEN

18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18

005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153

BARTHOLOMEW BENTON BLACKFORD BOONE BROWN CARROLL CASS CLARK CLAY CLINTON CRAWFORD DAVIESS DEARBORN DECATUR DE KALB DELAWARE DUBOIS ELKHART FAYETTE FLOYD FOUNTAIN FRANKLIN FULTON GIBSON GRANT GREENE HAMILTON HANCOCK HARRISON HENDRICKS HENRY HOWARD HUNTINGTON JACKSON JASPER JAY JEFFERSON JENNINGS JOHNSON KNOX KOSCIUSKO LAGRANGE LAKE LA PORTE LAWRENCE MADISON MARION MARSHALL MARTIN MIAMI MONROE MONTGOMERY MORGAN NEWTON NOBLE OHIO ORANGE OWEN PARKE PERRY PIKE PORTER POSEY PULASKI PUTNAM RANDOLPH RIPLEY RUSH ST. JOSEPH SCOTT SHELBY SPENCER STARKE STEUBEN SULLIVAN

18 18 18 18 18 18 18 18 18 18 18 18 18 18 18

155 157 159 161 163 165 167 169 171 173 175 177 179 181 183

SWITZERLAND TIPPECANOE TIPTON UNION VANDERBURGH VERMILLION VIGO WABASH WARREN WARRICK WASHINGTON WAYNE WELLS WHITE WHITLEY

19

IA

IOWA

19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113

ADAIR ADAMS ALLAMAKEE APPANOOSE AUDUBON BENTON BLACK HAWK BOONE BREMER BUCHANAN BUENA VISTA BUTLER CALHOUN CARROLL CASS CEDAR CERRO GORDO CHEROKEE CHICKASAW CLARKE CLAY CLAYTON CLINTON CRAWFORD DALLAS DAVIS DECATUR DELAWARE DES MOINES DICKINSON DUBUQUE EMMET FAYETTE FLOYD FRANKLIN FREMONT GREENE GRUNDY GUTHRIE HAMILTON HANCOCK HARDIN HARRISON HENRY HOWARD HUMBOLDT IDA IOWA JACKSON JASPER JEFFERSON JOHNSON JONES KEOKUK KOSSUTH LEE LINN

308

Appendix B: FIPS Codes

19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19

115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195 197

LOUISA LUCAS LYON MADISON MAHASKA MARION MARSHALL MILLS MITCHELL MONONA MONROE MONTGOMERY MUSCATINE O'BRIEN OSCEOLA PAGE PALO ALTO PLYMOUTH POCAHONTAS POLK POTTAWATTAMIE POWESHIEK RINGGOLD SAC SCOTT SHELBY SIOUX STORY TAMA TAYLOR UNION VAN BUREN WAPELLO WARREN WASHINGTON WAYNE WEBSTER WINNEBAGO WINNESHIEK WOODBURY WORTH WRIGHT

20

KS

KANSAS

20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059

ALLEN ANDERSON ATCHISON BARBER BARTON BOURBON BROWN BUTLER CHASE CHAUTAUQUA CHEROKEE CHEYENNE CLARK CLAY CLOUD COFFEY COMANCHE COWLEY CRAWFORD DECATUR DICKINSON DONIPHAN DOUGLAS EDWARDS ELK ELLIS ELLSWORTH FINNEY FORD FRANKLIN

20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20

061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195 197 199 201 203 205 207 209

GEARY GOVE GRAHAM GRANT GRAY GREELEY GREENWOOD HAMILTON HARPER HARVEY HASKELL HODGEMAN JACKSON JEFFERSON JEWELL JOHNSON KEARNY KINGMAN KIOWA LABETTE LANE LEAVENWORTH LINCOLN LINN LOGAN LYON MCPHERSON MARION MARSHALL MEADE MIAMI MITCHELL MONTGOMERY MORRIS MORTON NEMAHA NEOSHO NESS NORTON OSAGE OSBORNE OTTAWA PAWNEE PHILLIPS POTTAWATOMIE PRATT RAWLINS 05NO REPUBLIC RICE RILEY ROOKS RUSH RUSSELL SALINE SCOTT SEDGWICK SEWARD SHAWNEE SHERIDAN SHERMAN SMITH STAFFORD STANTON STEVENS SUMNER THOMAS TREGO WABAUNSEE WALLACE WASHINGTON WICHITA WILSON WOODSON WYANDOTTE

21

KY

KENTUCKY

21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139

ADAIR ALLEN ANDERSON BALLARD BARREN BATH BELL BOONE BOURBON BOYD BOYLE BRACKEN BREATHITT BRECKINRIDGE BULLITT BUTLER CALDWELL CALLOWAY CAMPBELL CARLISLE CARROLL CARTER CASEY CHRISTIAN CLARK CLAY CLINTON CRITTENDEN CUMBERLAND DAVIESS EDMONSON ELLIOTT ESTILL FAYETTE FLEMING FLOYD FRANKLIN FULTON GALLATIN GARRARD GRANT GRAVES GRAYSON GREEN GREENUP HANCOCK HARDIN HARLAN HARRISON HART HENDERSON HENRY HICKMAN HOPKINS JACKSON JEFFERSON JESSAMINE JOHNSON KENTON KNOTT KNOX LARUE LAUREL LAWRENCE LEE LESLIE LETCHER LEWIS LINCOLN LIVINGSTON

Appendix B: FIPS Codes 309 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21

141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195 197 199 201 203 205 207 209 211 213 215 217 219 221 223 225 227 229 231 233 235 237 239

LOGAN LYON MCCRACKEN MCCREARY MCLEAN MADISON MAGOFFIN MARION MARSHALL MARTIN MASON MEADE MENIFEE MERCER METCALFE MONROE MONTGOMERY MORGAN MUHLENBERG NELSON NICHOLAS OHIO OLDHAM OWEN OWSLEY PENDLETON PERRY PIKE POWELL PULASKI ROBERTSON ROCKCASTLE ROWAN RUSSELL SCOTT SHELBY SIMPSON SPENCER TAYLOR TODD TRIGG TRIMBLE UNION WARREN WASHINGTON WAYNE WEBSTER WHITLEY WOLFE WOODFORD

22

LA

LOUISIANA

22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043

ACADIA ALLEN ASCENSION ASSUMPTION AVOYELLES BEAUREGARD BIENVILLE BOSSIER CADDO CALCASIEU CALDWELL CAMERON CATAHOULA CLAIBORNE CONCORDIA DE SOTO EAST BATON ROUGE EAST CARROLL EAST FELICIANA EVANGELINE FRANKLIN GRANT

22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22

045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127

IBERIA IBERVILLE JACKSON JEFFERSON JEFFERSON DAVIS LAFAYETTE LAFOURCHE LA SALLE LINCOLN LIVINGSTON MADISON MOREHOUSE NATCHITOCHES ORLEANS OUACHITA PLAQUEMINES POINTE COUPEE RAPIDES RED RIVER RICHLAND SABINE ST. BERNARD ST. CHARLES ST. HELENA ST. JAMES ST. JOHN THE BAPTIST ST. LANDRY ST. MARTIN ST. MARY ST. TAMMANY TANGIPAHOA TENSAS TERREBONNE UNION VERMILION VERNON WASHINGTON WEBSTER WEST BATON ROUGE WEST CARROLL WEST FELICIANA WINN

23

ME

MAINE

23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031

ANDROSCOGGIN AROOSTOOK CUMBERLAND FRANKLIN HANCOCK KENNEBEC KNOX LINCOLN OXFORD PENOBSCOT PISCATAQUIS SAGADAHOC SOMERSET WALDO WASHINGTON YORK

24

MD

MARYLAND

24 24 24 24 24 24 24 24 24 24 24

001 003 005 009 011 013 015 017 019 021 023

ALLEGANY ANNE ARUNDEL BALTIMORE CALVERT CAROLINE CARROLL CECIL CHARLES DORCHESTER FREDERICK GARRETT

24 24 24 24 24 24 24 24 24 24 24 24 24

025 027 029 031 033 035 037 039 041 043 045 047 510

HARFORD HOWARD KENT MONTGOMERY PRINCE GEORGE'S QUEEN ANNE'S ST. MARY'S SOMERSET TALBOT WASHINGTON WICOMICO WORCESTER BALTIMORE CITY

25

MA

MASSACHUSETTS

25 25 25 25 25 25 25 25 25 25 25 25 25 25

001 003 005 007 009 011 013 015 017 019 021 023 025 027

BARNSTABLE BERKSHIRE BRISTOL DUKES ESSEX FRANKLIN HAMPDEN HAMPSHIRE MIDDLESEX NANTUCKET NORFOLK PLYMOUTH SUFFOLK WORCESTER

26

MI

MICHIGAN

26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083

ALCONA ALGER ALLEGAN ALPENA ANTRIM ARENAC BARAGA BARRY BAY BENZIE BERRIEN BRANCH CALHOUN CASS CHARLEVOIX CHEBOYGAN CHIPPEWA CLARE CLINTON CRAWFORD DELTA DICKINSON EATON EMMET GENESEE GLADWIN GOGEBIC GRAND TRAVERSE GRATIOT HILLSDALE HOUGHTON HURON INGHAM IONIA IOSCO IRON ISABELLA JACKSON KALAMAZOO KALKASKA KENT KEWEENAW

310 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26

Appendix B: FIPS Codes 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165

LAKE LAPEER LEELANAU LENAWEE LIVINGSTON LUCE MACKINAC MACOMB MANISTEE MARQUETTE MASON MECOSTA MENOMINEE MIDLAND MISSAUKEE MONROE MONTCALM MONTMORENCY MUSKEGON NEWAYGO OAKLAND OCEANA OGEMAW ONTONAGON OSCEOLA OSCODA OTSEGO OTTAWA PRESQUE ISLE ROSCOMMON SAGINAW ST. CLAIR ST. JOSEPH SANILAC SCHOOLCRAFT SHIAWASSEE TUSCOLA VAN BUREN WASHTENAW WAYNE WEXFORD

27

MN

MINNESOTA

27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061

AITKIN ANOKA BECKER BELTRAMI BENTON BIG STONE BLUE EARTH BROWN CARLTON CARVER CASS CHIPPEWA CHISAGO CLAY CLEARWATER COOK COTTONWOOD CROW WING DAKOTA DODGE DOUGLAS FAIRBAULT FILLMORE FREEBORN GOODHUE GRANT HENNEPIN HOUSTON HUBBARD ISANTI ITASCA

27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27

063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173

JACKSON KANABEC KANDIYOHI KITTSON KOOCHOCHIN LAC QUI PA LAKE LAKE OF TH LE SUEUR LINCOLN LYON MCLEOD MAHNOMEN MARSHALL MARTIN MEEKER MILLE LACS MORRISON MOWER MURAY NICOLLET NOBLES NORMAN OLMSTED OTTER TAIL PENNINGTON PINE PIPESTONE POLK POPE RAMSEY RED LAKE REDWOOD RENVILLE RICE ROCK ROSEAU ST. LOUIS SCOTT SHERBURNE SIBLEY STEARNS STEELE STEVENS SWIFT TODD TRAVERSE WABASHA WADENA WASECA WASHINGTON WATONWAN WILKIN WINONA WRIGHT YELLOW MED

28

MS

MISSISSIPPI

28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031

ADAMS ALCORN AMITE ATTALA BENTON BOLIVAR CALHOUN CARROLL CHICKASAW CHOCTAW CLAIBORNE CLARKE CLAY COAHOMA COPIAH COVINGTON

28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28

033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163

DE SOTO FORREST FRANKLIN GEORGE GREENE GRENADA HANCOCK HARRISON HINDS HOLMES HUMPHREYS ISSAQUENA ITAWAMBA JACKSON JASPER JEFFERSON JEFFERSON DAVIS JONES KEMPER LAFAYETTE LAMAR LAUDERDALE LAWRENCE LEAKE LEE LEFLORE LINCOLN LOWNDES MADISON MARION MARSHALL MONROE MONTGOMERY NESHOBA NEWTON NOXUBEE OKTIBBEHA PANOLA PEARL RIVER PERRY PIKE PONTOTOC PRENTISS QUITMAN RANKIN SCOTT SHARKEY SIMPSON SMITH STONE SUNFLOWER TALLAHATCHIE TATE TIPPAH TISHOMINGO TUNICA UNION WALTHALL WARREN WASHINGTON WAYNE WEBSTER WILKINSON WINSTON YALOBUSHA YAZOO

29

MO

MISSOURI

29 29 29 29 29 29

001 003 005 007 009 011

ADAIR ANDREW ATCHISON AUDRAIN BARRY BARTON

Appendix B: FIPS Codes 311 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29

013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161

BATES BENTON BOLLINGER BOONE BUCHANAN BUTLER CALDWELL CALLAWAY CAMDEN CAPE GIRARDEAU CARROLL CARTER CASS CEDAR CHARITON CHRISTIAN CLARK CLAY CLINTON COLE COOPER CRAWFORD DADE DALLAS DAVIESS DE KALB DENT DOUGLAS DUNKLIN FRANKLIN GASCONADE GENTRY GREENE GRUNDY HARRISON HENRY HICKORY HOLT HOWARD HOWELL IRON JACKSON JASPER JEFFERSON JOHNSON KNOX LACLEDE LAFAYETTE LAWRENCE LEWIS LINCOLN LINN LIVINGSTON MCDONALD MACON MADISON MARIES MARION MERCER MILLER MISSISSIPPI MONITEAU MONROE MONTGOMERY MORGAN NEW MADRID NEWTON NODAWAY OREGON OSAGE OZARK PEMISCOT PERRY PETTIS PHELPS

29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29

163 165 167 169 171 173 175 177 179 181 183 185 186 187 189 195 197 199 201 203 205 207 209 211 213 215 217 219 221 223 225 227 229 510

PIKE PLATTE POLK PULASKI PUTNAM RALLS RANDOLPH RAY REYNOLDS RIPLEY ST. CHARLES ST. CLAIR STE. GENEVIEVE ST. FRANCOIS ST. LOUIS SALINE SCHUYLER SCOTLAND SCOTT SHANNON SHELBY STODDARD STONE SULLIVAN TANEY TEXAS VERNON WARREN WASHINGTON WAYNE WEBSTER WORTH WRIGHT ST. LOUIS CITY

30

MT

MONTANA

30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067

30 30 30

069 071 073

BEAVERHEAD BIG HORN BLAINE BROADWATER CARBON CARTER CASCADE CHOUTEAU CUSTER DANIELS DAWSON DEER LODGE FALLON FERGUS FLATHEAD GALLATIN GARFIELD GLACIER GOLDEN VALLEY GRANITE HILL JEFFERSON JUDITH BASIN LAKE LEWIS AND CLARK LIBERTY LINCOLN MCCONE MADISON MEAGHER MINERAL MISSOULA MUSSELSHELL PARK AND 2 YELLOWSTONE PETROLEUM PHILLIPS PONDERA

30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30

075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 901

POWDER RIVER POWELL PRAIRIE RAVALLI RICHLAND ROOSEVELT ROSEBUD SANDERS SHERIDAN SILVER BOW STILLWATER SWEET GRASS TETON TOOLE TREASURE VALLEY WHEATLAND WIBAUX YELLOWSTONE 1 PARK (inc YLWSTONE)

31

NE

NEBRASKA

31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103

ADAMS ANTELOPE ARTHUR BANNER BLAINE BOONE BOX BUTTE BOYD BROWN BUFFALO BURT BUTLER CASS CEDAR CHASE CHERRY CHEYENNE CLAY COLFAX CUMING CUSTER DAKOTA DAWES DAWSON DEUEL DIXON DODGE DOUGLAS DUNDY FILLMORE FRANKLIN FRONTIER FURNAS GAGE GARDEN GARFIELD GOSPER GRANT GREELEY HALL HAMILTON HARLAN HAYES HITCHCOCK HOLT HOOKER HOWARD JEFFERSON JOHNSON KEARNEY KEITH KEYA PAHA

312

Appendix B: FIPS Codes

31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31

105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185

KIMBALL KNOX LANCASTER LINCOLN LOGAN LOUP MCPHERSON MADISON MERRICK MORRILL NANCE NEMAHA NUCKOLLS OTOE PAWNEE PERKINS PHELPS PIERCE PLATTE POLK RED WILLOW RICHARDSON ROCK SALINE SARPY SAUNDERS SCOTTS BLUFF SEWARD SHERIDAN SHERMAN SIOUX STANTON THAYER THOMAS THURSTON VALLEY WASHINGTON WAYNE WEBSTER WHEELER YORK

32

NV

NEVADA

32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32

001 003 005 007 009 011 013 015 017 019 021 023 027 029 031 033 510

CHURCHILL CLARK DOUGLAS ELKO ESMERALDA EUREKA HUMBOLDT LANDER LINCOLN LYON MINERAL NYE PERSHING STOREY WASHOE WHITE PINE CARSON CITY CITY

33

NH

NEW HAMPSHIRE

33 33 33 33 33 33 33 33 33 33

001 003 005 007 009 011 013 015 017 019

BELKNAP CARROLL CHESHIRE COOS GRAFTON HILLSBOROUGH MERRIMACK ROCKINGHAM STRAFFORD SULLIVAN

34

NJ

NEW JERSEY

34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041

ATLANTIC BERGEN BURLINGTON CAMDEN CAPE MAY CUMBERLAND ESSEX GLOUCESTER HUDSON HUNTERDON MERCER MIDDLESEX MONMOUTH MORRIS OCEAN PASSAIC SALEM SOMERSET SUSSEX UNION WARREN

35

NM

NEW MEXICO

35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35

001 003 005 006 007 009 011 013 015 017 019 021 023 025 027 028 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061

BERNALILLO CATRON CHAVES CIBOLA2 COLFAX CURRY DE BACA DONA ANA EDDY GRANT GUADALUPE HARDING HIDALGO LEA LINCOLN LOS ALAMOS LUNA MCKINLEY MORA OTERO QUAY RIO ARRIBA ROOSEVELT SANDOVAL SAN JUAN SAN MIGUEL SANTA FE SIERRA SOCORRO TAOS TORRANCE UNION VALENCIA

36

NY

NEW YORK

36 36 36 36 36 36 36 36 36 36 36 36 36

001 003 005 007 009 011 013 015 017 019 021 023 025

ALBANY ALLEGANY BRONX BROOME CATTARAUGUS CAYUGA CHAUTAUGUS CHEMUNG CHENANGO CLINTON COLUMBIA CORTLAND DELAWARE

36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36

027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123

DUTCHESS ERIE ESSEX FRANKLYN FULTON GENESEE GREENE HAMILTON HERKIMER JEFFERSON KINGS LEWIS LIVINGSTON MADISON MONROE MONTGOMERY NASSAU NEW YORK NIAGARA ONEIDA ONONDAGA ONTARIO ORANGE ORLEANS OSWEGO OTSEGO PUTNAM QUEENS RENSSELAER RICHMOND ROCKLAND ST. LAWRENCE SARATOGA SCHENECTADY SCHOHARIE SCHUYLER SENECA STUEBEN SUFFOLK SULLIVAN TIOGA TOMPKINS ULSTER WARREN WASHINGTON WAYNE WESTCHESTER WYOMING YATES

37

NC

NORTH CAROLINA

37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045

ALAMANCE ALEXANDER ALLEGHANY ANSON ASHE AVERY BEAUFORT BERTIE BLADEN BRUNSWICK BUNCOMBE BURKE CABARRUS CALDWELL CAMDEN CARTERET CASWELL CATAWBA CHATHAM CHEROKEE CHOWAN CLAY CLEVELAND

Appendix B: FIPS Codes 313 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37

047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195

COLUMBUS CRAVEN CUMBERLAND CURRITUCK DARE DAVIDSON DAVIE DUPLIN DURHAM EDGECOMBE FORSYTH FRANKLIN GASTON GATES GRAHAM GRANVILLE GREENE GUILFORD HALIFAX HARNETT HAYWOOD HENDERSON HERTFORD HOKE HYDE IREDELL JACKSON JOHNSTON JONES LEE LENOIR LINCOLN MCDOWELL MACON MADISON MARTIN MECKLENBURG MITCHELL MONTGOMERY MOORE NASH NEW HANOVER NORTHAMPTON ONSLOW ORANGE PAMLICO PASQUOTANK PENDER PERQUIMANS PERSON PITT POLK RANDOLPH RICHMOND ROBESON ROCKINGHAM ROWAN RUTHERFORD SAMPSON SCOTLAND STANLY STOKES SURRY SWAIN TRANSYLVANIA TYRRELL UNION VANCE WAKE WARREN WASHINGTON WATAUGA WAYNE WILKES WILSON

37 37

197 199

YADKIN YANCEY

38

ND

NORTH DAKOTA

38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105

ADAMS BARNES BENSON BILLINGS BOTTINEAU BOWMAN BURKE BURLEIGH CASS CAVALIER DICKEY DIVIDE DUNN EDDY EMMONS FOSTER GOLDEN VALLEY GRAND FORKS GRANT GRIGGS HETTINGER KIDDER LA MOURE LOGAN MCHENRY MCINTOSH MCKENZIE MCLEAN MERCER MORTON MOUNTRAIL NELSON OLIVER PEMBINA PIERCE RAMSEY RANSOM RENVIL05 RICHLAND ROLETTE SARGENT SHERIDAN SIOUX SLOPE STARK STEELE STUTSMAN TOWNER TRAILL WALSH WARD WELLS WILLIAMS

39

OH

OHIO

39 39 39 39 39 39 39 39 39 39 39 39 39

001 003 005 007 009 011 013 015 017 019 021 023 025

ADAMS ALLEN ASHLAND ASHTABULA ATHENS AUGLAIZE BELMONT BROWN BUTLER CARROLL CHAMPAIGN CLARK CLERMONT

39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39

027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175

CLINTON COLUMBIANA COSHOCTON CRAWFORD CUYAHOGA DARKE DEFIANCE DELAWARE ERIE FAIRFIELD FAYETTE FRANKLIN FULTON GALLIA GEAUGA GREENE GUERNSEY HAMILTON HANCOCK HARDIN HARRISON HENRY HIGHLAND HOCKING HOLMES HURON JACKSON JEFFERSON KNOX LAKE LAWRENCE LICKING LOGAN LORAIN LUCAS MADISON MAHONING MARION MEDINA MEIGS MERCER MIAMI MONROE MONTGOMERY MORGAN MORROW MUSKINGUM NOBLE OTTAWA PAULDING PERRY PICKAWAY PIKE PORTAGE PREBLE PUTNAM RICHLAND ROSS SANDUSKY SCIOTO SENECA SHELBY STARK SUMMIT TRUMBULL TUSCARAWAS UNION VAN WERT VINTON WARREN WASHINGTON WAYNE WILLIAMS WOOD WYANDOT

314

Appendix B: FIPS Codes

40

OK

OKLAHOMA

40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139

ADAIR ALFALFA ATOKA BEAVER BECKHAM BLAINE BRYAN CADDO CANADIAN CARTER CHEROKEE CHOCTAW CIMARRON CLEVELAND COAL COMANCHE COTTON CRAIG CREEK CUSTER DELAWARE DEWEY ELLIS GARFIELD GARVIN GRADY GRANT GREER HARMON HARPER HASKELL HUGHES JACKSON JEFFERSON JOHNSTON KAY KINGFISHER KIOWA LATIMER LE FLORE LINCOLN LOGAN LOVE MCCLAIN MCCURTAIN MCINTOSH MAJOR MARSHALL MAYES MURRAY MUSKOGEE NOBLE NOWATA OKFUSKEE OKLAHOMA OKMULGEE OSAGE OTTAWA PAWNEE PAYNE PITTSBURG PONTOTOC POTTAWATOMIE PUSHMATAHA ROGER MILLS ROGERS SEMINOLE SEQUOYAH STEPHENS TEXAS

40 40 40 40 40 40 40

141 143 145 147 149 151 153

TILLMAN TULSA WAGONER WASHINGTON WASHITA WOODS WOODWARD

41

OR

OREGON

41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071

BAKER BENTON CLACKAMAS CLATSOP COLUMBIA COOS CROOK CURRY DESCHUTES DOUGLAS GILLIAM GRANT HARNEY HOOD RIVER JACKSON JEFFERSON JOSEPHINE KLAMATH LAKE LANE LINCOLN LINN MALHEUR MARION MORROW MULTNOMAH POLK SHERMAN TILLAMOOK UMATILLA UNION WALLOWA WASCO WASHINGTON WHEELER YAMHILL

42

PA

PENNSYLVANIA

42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051

ADAMS ALLEGHENY ARMSTRONG BEAVER BEDFORD BERKS BLAIR BRADFORD BUCKS BUTLER CAMBRIA CAMERON CARBON CENTRE CHESTER CLARION CLEARFIELD CLINTON COLUMBIA CRAWFORD CUMBERLAND DAUPHIN DELAWARE ELK ERIE FAYETTE

42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42

053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133

FOREST FRANKLIN FULTON GREENE HUNTINGDON INDIANA JEFFERSON JUNIATA LACKAWANNA LANCASTER LAWRENCE LEBANON LEHIGH LUZERNE LYCOMING MCKEAN MERCER MIFFLIN MONROE MONTGOMERY MONTOUR NORTHAMPTON NORTHUMBERLAND PERRY PHILADELPHIA PIKE POTTER SCHUYLKILL SNYDER SOMERSET SULLIVAN SUSQUEHANNA TIOGA UNION VENANGO WARREN WASHINGTON WAYNE WESTMORELAND WYOMING YORK

44

RI

RHODE ISLAND

44 44 44 44 44

001 003 005 007 009

BRISTOL KENT NEWPORT PROVIDENCE WASHINGTON

45

SC

SOUTH CAROLINA

45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045

ABBEVILLE AIKEN ALLENDALE ANDERSON BAMBERG BARNWELL BEAUFORT BERKELEY CALHOUN CHARLESTON CHEROKEE CHESTER CHESTERFIELD CLARENDON COLLETON DARLINGTON DILLON DORCHESTER EDGEFIELD FAIRFIELD FLORENCE GEORGETOWN GREENVILLE

Appendix B: FIPS Codes 315 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45

047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091

GREENWOOD HAMPTON HORRY JASPER KERSHAW LANCASTER LAURENS LEE LEXINGTON MCCORMICK MARION MARLBORO NEWBERRY OCONEE ORANGEBURG PICKENS RICHLAND SALUDA SPARTANBURG SUMTER UNION WILLIAMSBURG YORK

46

SD

SOUTH DAKOTA

46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46

003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071

46 46 46 46 46 46 46 46 46 46 46 46 46

073 075 077 079 081 083 085 087 089 091 093 095 097

AURORA BEADLE BENNETT BON HOMME BROOKINGS BROWN BRULE BUFFALO BUTTE CAMPBELL CHARLES MIX CLARK CLAY CODINGTON CORSON CUSTER DAVISON DAY DEUEL DEWEY DOUGLAS EDMUNDS FALL RIVER FAULK GRANT GREGORY HAAKON HAMLIN HAND HANSON HARDING HUGHES HUTCHINSON HYDE JACKSON (Inc 2 WSHA.) JERAULD JONES KINGSBURY LAKE LAWRENCE LINCOLN LYMAN MCCOOK MCPHERSON MARSHALL MEADE MELLETTE MINER

46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46

099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 135 137

MINNEHAHA MOODY PENNINGTON PERKINS POTTER ROBERTS SANBORN SHANNON SPINK STANLEY SULLY TODD TRIPP TURNER UNION WALWORTH 1 WASHABAUGH YANKTON ZIEBACH

47

TN

TENNESSEE

47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105

ANDERSON BEDFORD BENTON BLEDSOE BLOUNT BRADLEY CAMPBELL CANNON CARROLL CARTER CHEATHAM CHESTER CLAIBORNE CLAY COCKE COFFEE CROCKETT CUMBERLAND DAVIDSON DECATUR DE KALB DICKSON DYER FAYETTE FENTRESS FRANKLIN GIBSON GILES GRAINGER GREENE GRUNDY HAMBLEN HAMILTON HANCOCK HARDEMAN HARDIN HAWKINS HAYWOOD HENDERSON HENRY HICKMAN HOUSTON HUMPHREYS JACKSON JEFFERSON JOHNSON KNOX LAKE LAUDERDALE LAWRENCE LEWIS LINCOLN LOUDON

47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47

107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189

MCMINN MCNAIRY MACON MADISON MARION MARSHALL MAURY MEIGS MONROE MONTGOMERY MOORE MORGAN OBION OVERTON PERRY PICKETT POLK PUTNAM RHEA ROANE ROBERTSON RUTHERFORD SCOTT SEQUATCHIE SEVIER SHELBY SMITH STEWART SULLIVAN SUMNER TIPTON TROUSDALE UNICOI UNION VAN BUREN WARREN WASHINGTON WAYNE WEAKLEY WHITE WILLIAMSON WILSON

48

TX

TEXAS

48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059

ANDERSON ANDREWS ANGELINA ARANSAS ARCHER ARMSTRONG ATASCOSA AUSTIN BAILEY BANDERA BASTROP BAYLOR BEE BELL BEXAR BLANCO BORDEN BOSQUE BOWIE BRAZORIA BRAZOS BREWSTER BRISCOE BROOKS BROWN BURLESON BURNET CALDWELL CALHOUN CALLAHAN

316 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48

Appendix B: FIPS Codes 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195 197 199 201 203 205 207 209

CAMERON CAMP CARSON CASS CASTRO CHAMBERS CHEROKEE CHILDRESS CLAY COCHRAN COKE COLEMAN COLLIN COLLINGSWORTH COLORADO COMAL COMANCHE CONCHO COOKE CORYELL COTTLE CRANE CROCKETT CROSBY CULBERSON DALLAM DALLAS DAWSON DEAF SMITH DELTA DENTON DE WITT DICKENS DIMMIT DONLEY DUVAL EASTLAND ECTOR EDWARDS ELLIS EL PASO ERATH FALLS FANNIN FAYETTE FISHER FLOYD FOARD FORT BEND FRANKLIN FREESTONE FRIO GAINES GALVESTON GARZA GILLESPIE GLASSCOCK GOLIAD GONZALES GRAY GRAYSON GREGG GRIMES GUADALUPE HALE HALL HAMILTON HANSFORD HARDEMAN HARDIN HARRIS HARRISON HARTLEY HASKELL HAYS

48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48

211 213 215 217 219 221 223 225 227 229 231 233 235 237 239 241 243 245 247 249 251 253 255 257 259 261 263 265 267 269 271 273 275 277 279 281 283 285 287 289 291 293 295 297 299 301 303 305 307 309 311 313 315 317 319 321 323 325 327 329 331 333 335 337 339 341 343 345 347 349 351 353 355 357 359

HEMPHILL HENDERSON HIDALGO HILL HOCKLEY HOOD HOPKINS HOUSTON HOWARD HUDSPETH HUNT HUTCHINSON IRION JACK JACKSON JASPER JEFF DAVIS JEFFERSON JIM HOGG JIM WELLS JOHNSON JONES KARNES KAUFMAN KENDALL KENEDY KENT KERR KIMBLE KING KINNEY KLEBERG KNOX LAMAR LAMB LAMPASAS LA SALLE LAVACA LEE LEON LIBERTY LIMESTONE LIPSCOMB LIVE OAK LLANO LOVING LUBBOCK LYNN MCCULLOCH MCLENNAN MCMULLEN MADISON MARION MARTIN MASON MATAGORDA MAVERICK MEDINA MENARD MIDLAND MILAM MILLS MITCHELL MONTAGUE MONTGOMERY MOORE MORRIS MOTLEY NACOGDOCHES NAVARRO NEWTON NOLAN NUECES OCHILTREE OLDHAM

48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48

361 363 365 367 369 371 373 375 377 379 381 383 385 387 389 391 393 395 397 399 401 403 405 407 409 411 413 415 417 419 421 423 425 427 429 431 433 435 437 439 441 443 445 447 449 451 453 455 457 459 461 463 465 467 469 471 473 475 477 479 481 483 485 487 489 491 493 495 497 499 501 503 505 507

ORANGE PALO PINTO PANOLA PARKER PARMER PECOS POLK POTTER PRESIDIO RAINS RANDALL REAGAN REAL RED RIVER REEVES REFUGIO ROBERTS ROBERTSON ROCKWALL RUNNELS RUSK SABINE SAN AUGUSTINE SAN JACINTO SAN PATRICIO SAN SABA SCHLEICHER SCURRY SHACKELFORD SHELBY SHERMAN SMITH SOMERVELL STARR STEPHENS STERLING STONEWALL SUTTON SWISHER TARRANT TAYLOR TERRELL TERRY THROCKMORTON TITUS TOM GREEN TRAVIS TRINITY TYLER UPSHUR UPTON UVALDE VAL VERDE VAN ZANDT VICTORIA WALKER WALLER WARD WASHINGTON WEBB WHARTON WHEELER WICHITA WILBARGER WILLACY WILLIAMSON WILSON WINKLER WISE WOOD YOAKUM YOUNG ZAPATA ZAVALA

Appendix B: FIPS Codes 317

49

UT

UTAH

49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057

BEAVER BOX ELDER CACHE CARBON DAGGETT DAVIS DUCHESNE EMERY GARFIELD GRAND IRON JUAB KANE MILLARD MORGAN PIUTE RICH SALT LAKE SAN JUAN SANPETE SEVIER SUMMIT TOOELE UINTAH UTAH WASATCH WASHINGTON WAYNE WEBER

50

VT

VERMONT

50 50 50 50 50 50 50 50 50 50 50 50 50 50

001 003 005 007 009 011 013 015 017 019 021 023 025 027

ADDISON BENNINGTON CALEDONIA CHITTENDEN ESSEX FRANKLIN GRAND ISLE LAMOILLE ORANGE ORLEANS RUTLAND WASHINGTON WINDHAM WINDSOR

51

VA

VIRGINIA

51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 036 037 041

ACCOMACK ALBEMARLE ALLEGHANY AMELIA AMHERST APPOMATTOX ARLINGTON AUGUSTA BATH BEDFORD BLAND BOTETOURT BRUNSWICK BUCHANAN BUCKINGHAM CAMPBELL CAROLINE CARROLL CHARLES CITY CHARLOTTE CHESTERFIELD

51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51

043 045 047 049 051 053 057 059 061 063 065 067 069 071 073 075 077 079 081 083

51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51

085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 125 127 131 133 135 137 139 141 143 145 147 149 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 191 193 195 197 199

CLARKE CRAIG CULPEPER CUMBERLAND DICKENSON DINWIDDIE ESSEX FAIRFAX FAUQUIER FLOYD FLUVANNA FRANKLIN FREDERICK GILES GLOUCESTER GOOCHLAND GRAYSON GREENE GREENSVILLE HALIFAX (Includes South Boston 1995 and on) HANOVER HENRICO HENRY HIGHLAND ISLE OF WIGHT JAMES CITY KING AND QUEEN KING GEORGE KING WILLIAM LANCASTER LEE LOUDOUN LOUISA LUNENBURG MADISON MATHEWS MECKLENBURG MIDDLESEX MONTGOMERY NELSON NEW KENT NORTHAMPTON NORTHUMBERLAND NOTTOWAY ORANGE PAGE PATRICK PITTSYLVANIA POWHATAN PRINCE EDWARD PRINCE GEORGE PRINCE WILLIAM PULASKI RAPPAHANNOCK RICHMOND ROANOKE ROCKBRIDGE ROCKINGHAM RUSSELL SCOTT SHENANDOAH SMYTH SOUTHAMPTON SPOTSYLVANIA STAFFORD SURRY SUSSEX TAZEWELL WARREN WASHINGTON WESTMORELAND WISE WYTHE YORK

51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51

510 515 520 530 540 550 560 570 580 590 595 600 610 620 630 640 650 660 670 678 680 683 685 690 700 710 720 730 735 740 750 760 770 775 780 790 800 810 820 830 840

ALEXANDRIA BEDFORD BRISTOL BUENA VISTA CHARLOTTESVILLE CHESAPEAKE 8 CLIFTON FORGE COLONIAL EIGHTS COVINGTON DANVILLE EMPORIA FAIRFAX FALLS CHURCH FRANKLIN FREDERICKSBURG GALAX HAMPTON HARRISONBURG HOPEWELL LEXINGTON LYNCHBURG MANASSAS MANASSAS PARK MARTINSVILLE NEWPORT NEWS NORFOLK NORTON PETERSBURG POQUOSON PORTSMOUTH RADFORD RICHMOND ROANOKE SALEM 6 SOUTH BOSTON STAUNTON SUFFOLK VIRGINIA BEACH WAYNESBORO WILLIAMSBURG WINCHESTER

53

WA

WASHINGTON

53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061

ADAMS ASOTIN BENTON CHELAN CLALLAM CLARK COLUMBIA COWLITZ DOUGLAS FERRY FRANKLIN GARFIELD GRANT GRAYS HARBOR ISLAND JEFFERSON KING KITSAP KITTITAS KLICKITAT LEWIS LINCOLN MASON OKANOGAN PACIFIC PEND OREILLE PIERCE SAN JUAN SKAGIT SKAMANIA SNOHOMISH

318

Appendix B: FIPS Codes 54 54 54 54 54 54 54 54 54 54

091 093 095 097 099 101 103 105 107 109

TAYLOR TUCKER TYLER UPSHUR WAYNE WEBSTER WETZEL WIRT WOOD WYOMING

55

WI

WISCONSIN

55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 078 079 081 083

ADAMS ASHLAND BARRON BAYFIELD BROWN BUFFALO BURNETT CALUMET CHIPPEWA CLARK COLUMBIA CRAWFORD DANE DODGE DOOR DOUGLAS DUNN EAU CLAIRE FLORENCE FOND DU LAC FOREST GRANT GREEN GREEN LAKE IOWA IRON JACKSON JEFFERSON JUNEAU KENOSHA KEWAUNEE LA CROSSE LAFAYETTE LANGLADE LINCOLN MANITOWOC MARATHON MARINETTE MARQUETTE MENOMINEE MILWAUKEE MONROE OCONTO

53 53 53 53 53 53 53 53

063 065 067 069 071 073 075 077

SPOKANE STEVENS THURSTON WAHKIAKUM WALLA WALLA WHATCOM WHITMAN YAKIMA

54

WV

WEST VIRGINIA

54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045 047 049 051 053 055 057 059 061 063 065 067 069 071 073 075 077 079 081 083 085 087 089

BARBOUR BERKELEY BOONE BRAXTON BROOKE CABELL CALHOUN CLAY DODDRIDGE FAYETTE GILMER GRANT GREENBRIER HAMPSHIRE HANCOCK HARDY HARRISON JACKSON JEFFERSON KANAWHA LEWIS LINCOLN LOGAN MCDOWELL MARION MARSHALL MASON MERCER MINERAL MINGO MONONGALIA MONROE MORGAN NICHOLAS OHIO PENDLETON PLEASANTS POCAHONTAS PRESTON PUTNAM RALEIGH RANDOLPH RITCHIE ROANE SUMMERS

1. 2. 3. 4. 5. 6. 7. 8. 9.

County only exists in 1982 and 1985 databases. County exists beginning with the 1990 database. County exists beginning with the 1991 database. County exists in the 1990 to 1992 databases. County exists beginning with the 1993 database. No longer exists after 1994. Dade renamed to Miami-Dade beginning with the 2000 database. No longer exists after 2000 County exists beginning with the 2002 database

55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55

085 087 089 091 093 095 097 099 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141

ONEIDA OUTAGAMIE OZAUKEE PEPIN PIERCE POLK PORTAGE PRICE RACINE RICHLAND ROCK RUSK ST. CROIX SAUK SAWYER SHAWANO SHEBOYGAN TAYLOR TREMPEALEAU VERNON VILAS WALWORTH WASHBURN WASHINGTON WAUKESHA WAUPACA WAUSHARA WINNEBAGO WOOD

56

WY

WYOMING

56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56

001 003 005 007 009 011 013 015 017 019 021 023 025 027 029 031 033 035 037 039 041 043 045

ALBANY BIG HORN CAMPBELL CARBON CONVERSE CROOK FREMONT GOSHEN HOT SPRINGS JOHNSON LARAMIE LINCOLN NATRONA NIOBRARA PARK PLATTE SHERIDAN SUBLETTE SWEETWATER TETON UINTA WASHAKIE WESTON

Appendix C: SAM Elements

A P P E N D I X

319

C

SAM Element Description Institution Receipts 1001 1001 1001 2001 2001 2001

Description Industry Total Industry Total Industry Total Commodity Total Commodity Total Commodity Total

Institution Payments 2001 25001 28001 1001 10001 11001

2001 2001

Commodity Total Commodity Total

11002 11003

2001

Commodity Total

12001

2001 2001 2001 2001 5001 6001 7001 8001 10001 10001

Commodity Total Commodity Total Commodity Total Commodity Total Employee Compensation Proprietary Income Other Property Income Indirect Business Taxes Households Households

10001

Type of Transfer 15052 15051 15051 15050 15051 15051

Description Commodity Make Commodity Trade Commodity Trade Commodity Use Commodity Trade Commodity Trade

15051 15051

Commodity Trade Commodity Trade

15051

Commodity Trade

15051 15051 15051 15051 15053 15053 15053 15053 15052 15002

Commodity Trade Commodity Trade Commodity Trade Commodity Trade Factor Receipts Factor Receipts Factor Receipts Factor Receipts Commodity Make Emp Comp (Wages/Salary w/o Soc Sec) Employee Comp (Other Labor Income) Transfers Proprietors Inc (w/o Soc Sec & CCA) Rent with Capital Consumption Adj Business Transfers Interest (Net-from Industries) Interest (Net-from RoW) Interest (Gross) Interest (Gross)

12002 12003 14001 14002 1001 1001 1001 1001 2001 5001

Description Commodity Total Foreign Trade Domestic Trade Industry Total Households Federal Government NonDefense Federal Government Defense Federal Government Investment State/Local Govt NonEducation State/Local Govt Education State/Local Govt Investment Capital Inventory Additions/Deletions Industry Total Industry Total Industry Total Industry Total Commodity Total Employee Compensation

Households

5001

Employee Compensation

15003

10001 10001

Households Households

5001 6001

Employee Compensation Proprietary Income

15010 15004

10001

Households

7001

Other Property Income

15005

10001 10001 10001 10001 10001

Households Households Households Households Households

7001 7001 7001 10001 11001

15006 15008 15036 15009 15009

10001

Households

11001

10001

Households

12001

15010

Transfers

15007 15011 15051 15037 15051 15052

Dividends Surplus or Deficit Commodity Trade Factor Trade Commodity Trade Commodity Make

10001

Households

12001

10001 10001 10001 10001 10001 11001

Households Households Households Households Households Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government

13001 14001 25001 28001 28001 2001

Other Property Income Other Property Income Other Property Income Households Federal Government NonDefense Federal Government NonDefense State/Local Govt NonEducation State/Local Govt NonEducation Enterprises (Corporations) Capital Foreign Trade Domestic Trade Domestic Trade Commodity Total

5001

Employee Compensation

15013

Wage Accruals Less Surplus

5001

Employee Compensation

15014

5001

Employee Compensation

15015

6001

Proprietary Income

15014

7001

Other Property Income

15008

Soc Sec Tax, Employee Contribution Soc Sec Tax, Employer Contribution Soc Sec Tax, Employee Contribution Interest (Net-from Industries)

11001 11001 11001 11001 11001

15010

Transfers

15009

Interest (Gross)

320 11001 11001 11001 11001 11001 11001 11001 11001 11001 11001 11001 11001 11002 11002 11003 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001 12001

Appendix C: SAM Elements NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government NonDefense Federal Government Defense Federal Government Defense Federal Government Investment State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation

7001

Other Property Income

15016

7001

Other Property Income

15036

Surplus-Subsidy, Govt Enterprises Interest (Net-from RoW)

8001

Indirect Business Taxes

15017

Indirect Bus Tax: Excise Taxes

8001

Indirect Business Taxes

15018

Indirect Bus Tax: Custom Duty

8001

Indirect Business Taxes

15019

Indirect Bus Tax: Fed NonTaxes

10009

Households

15009

Interest (Gross)

10009

Households

15027

Personal Tax: Income Tax

10009

Households

15028

10009

Households

15029

13001

Enterprises (Corporations)

15026

Personal Tax: Estate and Gift Tax Personal Tax: NonTaxes (Fines, Fees Corporate Profits Tax

25001

Foreign Trade

15051

Commodity Trade

28001

Domestic Trade

15051

Commodity Trade

11001

Federal Government NonDefense Capital Federal Government NonDefense Commodity Total

15010

Transfers

15011 15010

Surplus or Deficit Transfers

15052

Commodity Make

14001 11001 2001 5001

Employee Compensation

15013

Wage Accruals Less Surplus

5001

Employee Compensation

15014

5001

Employee Compensation

15015

Soc Sec Tax, Employee Contribution Soc Sec Tax, Employer Contribution Soc Sec Tax, Employee Contribution Interest (Net-from Industries)

6001

Proprietary Income

15014

7001

Other Property Income

15008

7001

Other Property Income

15016

8001

Indirect Business Taxes

15020

Surplus-Subsidy, Govt Enterprises Indirect Bus Tax: Sales Tax

8001

Indirect Business Taxes

15021

Indirect Bus Tax: Property Tax

8001

Indirect Business Taxes

15022

8001

Indirect Business Taxes

15023

Indirect Bus Tax: Motor Vehicle Lic Indirect Bus Tax: Severance Tax

8001

Indirect Business Taxes

15024

Indirect Bus Tax: Other Taxes

8001

Indirect Business Taxes

15025

Indirect Bus Tax: S/L NonTaxes

10001

Households

15009

Interest (Gross)

10001

Households

15027

Personal Tax: Income Tax

10001

Households

15028

10001

Households

15029

10001

Households

15030

10001

Households

15031

Personal Tax: Estate and Gift Tax Personal Tax: NonTaxes (Fines, Fees Personal Tax: Motor Vehicle License Personal Tax: Property Taxes

10001

Households

15032

11001

Federal Government NonDefense

15010

Personal Tax: Other Tax (Fish/Hunt) Transfers

Appendix C: SAM Elements 12001

12002

State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt NonEducation State/Local Govt Education

12002 12003

State/Local Govt Education State/Local Govt Investment

14001 12001

12003 13001 14001 14001 14001 14001 14001

State/Local Govt Investment Enterprises (Corporations) Capital Capital Capital Capital Capital

14001 7001 2001 7001 7001 10009 11001

14001

Capital

11003

14001

Capital

12001

14001 14001 14001 14001 14001 14002 14002 14002 25001 25001 25001 25001 25001

Capital Capital Capital Capital Capital Inventory Additions/Deletions Inventory Additions/Deletions Inventory Additions/Deletions Foreign Trade Foreign Trade Foreign Trade Foreign Trade Foreign Trade

13001 14002 25001 28001 28001 2001 25001 28001 1001 7001 10009 10009 11001

25001

Foreign Trade

11001

25001 25001

Foreign Trade Foreign Trade

11002 11003

25001

Foreign Trade

12001

25001 25001 25001 25001 25001 25001 28001 28001 28001 28001

Foreign Trade Foreign Trade Foreign Trade Foreign Trade Foreign Trade Foreign Trade Domestic Trade Domestic Trade Domestic Trade Domestic Trade

12002 12003 14001 14001 14002 25001 1001 7001 10009 11001

28001 28001

Domestic Trade Domestic Trade

11002 11003

28001

Domestic Trade

12001

28001 28001 28001 28001

Domestic Trade Domestic Trade Domestic Trade Domestic Trade

12002 12003 14001 14002

12001 12001 12001

13001

Enterprises (Corporations)

15007

Dividends

13001

Enterprises (Corporations)

15026

Corporate Profits Tax

25001

Foreign Trade

15051

Commodity Trade

28001

Domestic Trade

15051

Commodity Trade

12001

State/Local Govt NonEducation Capital State/Local Govt NonEducation Capital Other Property Income Commodity Total Other Property Income Other Property Income Households Federal Government NonDefense Federal Government Investment State/Local Govt NonEducation Enterprises (Corporations) Inventory Additions/Deletions Foreign Trade Domestic Trade Domestic Trade Commodity Total Foreign Trade Domestic Trade Industry Total Other Property Income Households Households Federal Government NonDefense Federal Government NonDefense Federal Government Defense Federal Government Investment State/Local Govt NonEducation State/Local Govt Education State/Local Govt Investment Capital Capital Inventory Additions/Deletions Foreign Trade Industry Total Other Property Income Households Federal Government NonDefense Federal Government Defense Federal Government Investment State/Local Govt NonEducation State/Local Govt Education State/Local Govt Investment Capital Inventory Additions/Deletions

321

15010

Transfers

15011 15010

Surplus or Deficit Transfers

15011 15001 15052 15033 15035 15011 15011

Surplus or Deficit Corporate Profits with IVA Commodity Make Capital Consumption Allowance NIPA Statistical Discrepency Surplus or Deficit Surplus or Deficit

15011

Surplus or Deficit

15011

Surplus or Deficit

15011 15011 15051 15011 15051 15052 15051 15051 15051 15010 15010 15051 15010

Surplus or Deficit Surplus or Deficit Commodity Trade Surplus or Deficit Commodity Trade Commodity Make Commodity Trade Commodity Trade Commodity Trade Transfers Transfers Commodity Trade Transfers

15051

Commodity Trade

15051 15051

Commodity Trade Commodity Trade

15051

Commodity Trade

15051 15051 15011 15051 15051 15051 15051 15037 15051 15051

Commodity Trade Commodity Trade Surplus or Deficit Commodity Trade Commodity Trade Commodity Trade Commodity Trade Factor Trade Commodity Trade Commodity Trade

15051 15051

Commodity Trade Commodity Trade

15051

Commodity Trade

15051 15051 15051 15051

Commodity Trade Commodity Trade Commodity Trade Commodity Trade

Appendix D: IMPLAN Type Codes

A P P E N D I X

D

IMPLAN Data Types Codes Type Code 1-509 1001 2001 3001-3509 5001 6001 7001 8001 10001 10002 10003 10004 10005 10006 10007 10008 10009 11001 11002 11003 12001 12002 12003 13001 14001 14002 15001 15002 15003 15004 15005 15006 15007 15008 15009 15010 15011 15012 15013 15014 15015 15016 15017 15018

Type Industry/Commodity Industry Commodity SAM Commodity Codes Factors Factors Factors Factors Households LT10k Households 10-15k Households 15-25k Households 25-35k Households 35-50k Households 50-75k Households 75-100k Households 100-150k Households 150k+ Institutions Institutions Institutions Institutions Institutions Institutions Institutions Institutions Institutions Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers

Description Industry Detail Industry Total Commodity Total Commodity Detail Employee Compensation Proprietary Income Other Property Income Indirect Business Taxes Households LT10k Households 10-15k Households 15-25k Households 25-35k Households 35-50k Households 50-75k Households 75-100k Households 100-150k Households 150k+ Federal Government NonDefense Federal Government Defense Federal Government Investment State/Local Govt NonEducation State/Local Govt Education State/Local Govt Investment Enterprises (Corporations) Capital Inventory Additions/Deletions Corporate Profits with IVA Emp Comp (Wages/Salary w/o Soc Sec) Employee Comp (Other Labor Income) Proprietors Inc (w/o Soc Sec & CCA) Rent with Capital Consumption Adj Business Transfers Dividends Interest (Net-from Industries) Interest (Gross) Transfers Surplus or Deficit Savings (Surplus) not use Wage Accruals Less Surplus Soc Sec Tax, Employee Contribution Soc Sec Tax, Employer Contribution Surplus-Subsidy, Govt Enterprises Indirect Bus Tax: Excise Taxes Indirect Bus Tax: Custom Duty

323

324

Appendix D: IMPLAN Type Codes

15019 15020 Type Code 15021 15022 15023 15024 15025 15026 15027 15028 15029 15030 15031 15032 15033 15034 15035 15036 15037 15038 15050 15051 15052 15053 15054 15055 15056 20001 24001 25001 28001

Transfers Transfers Type Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Transfers Employment Output Trade Trade

Indirect Bus Tax: Fed NonTaxes Indirect Bus Tax: Sales Tax Description Indirect Bus Tax: Property Tax Indirect Bus Tax: Motor Vehicle Lic Indirect Bus Tax: Severance Tax Indirect Bus Tax: Other Taxes Indirect Bus Tax: S/L NonTaxes Corporate Profits Tax Personal Tax: Income Tax Personal Tax: Estate and Gift Tax Personal Tax: NonTaxes (Fines, Fees Personal Tax: Motor Vehicle License Personal Tax: Property Taxes Personal Tax: Other Tax (Fish/Hunt) Capital Consumption Allowance Retained Profits (Profits w/IVA&CCA NIPA Statistical Discrepency Interest (Net-from RoW) Factor Trade Adjustment to retained earnings Commodity Use Commodity Trade Commodity Make Factor Receipts Foreign Commodity Transshipments Industry Use Industry Trade Employment (all occupations) Industry Output Foreign Trade Domestic Trade

Appendix E: IAP Documentation

A P P E N D I X

325

E

IAP Database Documentation IMPLAN Professional uses Microsoft Access as its database. The model file name is NAME.IAP and can be opened with Access. This section documents the IMPLAN Pro database and the underlying model tables. There are 45 standard tables in an IAP file. The first tables are the SA tables. SA represents study area. These are created during the region build selection. The SA tables are populated with data from the ODF files. There are several attached tables with US information. The regional table are generated as part of the model building process. These model files where these tables are located are MS Access 97 files. Complete List of Tables CGE Account Deflators1 General Information IMCommodity Transactions IMEvents IMFactor Transactions IMGroups IMIndustry Transactions IMInstitutions Transactions IMMArgins IMProjects Industry/Commodity Codes Margins Margins Codes Model Specs Multiplier Specs Observed RPCs Regional Absorption Regional Byproducts Regional Commodity Balances Regional Direct Institutional Requirements Regional Factor Balances Regional Factor Distribution Regional Industry Balances Regional Institution Balances Regional Institution Demand Regional IxI Regional Market Shares Regional Multipliers Induced Regional Multipliers Institution Regional Multipliers Type I Regional SAM Balances

Regional SAM Balances Aggregated Regional SAM Balances Industry Detail Regional SAM Balances IxI Regional SAM Balances IxI Indistry Detail Regional SAM Distribution Regional Value Added Coefficients RPC Methods rptEC Multipliers rptEmployment Multipliers rptIBT Multipliers rptOPTI Multipliers rptOutput Multipliers rptPersonal Income Multipliers rptPropInc Multipliers rptTotal VA Multipliers SACommodity Sales SAEmployment SAFinal Demands SAForeign Exports SAOutput SAM Rollup SARatios SATransfers SAValue Added Tax Impacts Type Code Rollup Type Codes Type Codes Agg US Absorption Table US Absorption Totals US Byproducts Table

326

Appendix E: IAP Documentation

Table: CGE Account Contains the complete social accounting matrix in full detail. Used for computable general equilibrium models and SAM analysis outside the IMPLAN Pro software. Name Institution Receipts Institution Payments Submatrix Transaction

Type Integer Integer Text Single

Size 2 2 5 4

Description The institution code receiving income The institution code making payments A code for the SAM matrix (see CGE file description The value of the social accounting matrix transaction

Table: Deflators Contains deflator information for use in the impact assesment portion of the program. Can be extracted and used outside IMPLAN Pro. Name Industry Year

Type Integer Single

Size 2 4

Description Industry code Each year of the deflator table is represented by a different field. The total number of fields depends on the data release.

Table: General Information Contains general information about the study area used in the model building process. There is a record for every state or county included in the study region. Name State Name County Name

Type Text Text

Size 25 25

Population Area State Code County Code Year Structure PI Total PI <5K

Single Single Text Text Long Text Single Single

4 4 4 4 4 20 4 4

PI 5-10K

Single

4

PI 10-15K

Single

4

PI 15-20K

Single

4

PI 20-30K

Single

4

PI 30-40K

Single

4

PI 40-50K

Single

4

PI 50-70K

Single

4

Description The name of the state included in the region The name of the county. This will contain the state name if a state file is used. The total population of the area Land area in square miles State FIPS code County FIPS code Base year of data The name of the associated U.S. structural matrices. Total personal income Total personal income for households with less than $5K in income. Total personal income for households with $5-10K in income. Total personal income for households with $10-15K in income. Total personal income for households with $15-20K in income. Total personal income for households with $20-30K in income. Total personal income for households with $30-40K in income. Total personal income for households with $40-50K in income. Total personal income for households with $50-70K in

Appendix E: IAP Documentation 327 PI 70K+

Single

4

HH Total HH <5K HH 5-10K HH 10-15K HH 15-20K HH 20-30K HH 30-40K HH 40-50K HH 50-70K HH 70K+ Aggregation Name

Single Single Single Single Single Single Single Single Single Single Text

4 4 4 4 4 4 4 4 4 4 50

income. Total personal income for households with over $70K in income. Total number of households in the region. Total households with less than $5K in income. Total households with $5-10K in income. Total households with $10-15K in income. Total households with $15-20K in income. Total households with $20-30K in income. Total households with $30-40K in income. Total households with $40-50K in income. Total households with $50-70K in income. Total households with over $70K in income. The name of the aggregation scheme in use if there is one.

Table: IMCommodity Transactions Created during the impact assessment portion of the program. Contains commodity impact data used to create the impact reports. Name Sector Value RPC

Type Integer Single Single

Size 2 4 4

Description The commodity code. The dollar value of the impact. The Regional Purchase Coefficient used to localize the impact (optional.)

Table: IMEvents Contains all Event related data used to create the impact reports. Name EventID Event Name Sector Ind/Com Value Employment

Type Long Text Integer Yes/No Single Single

Size 4 50 2 1 4 4

Year

Integer

2

Deflator

Single

4

Description The Event identification code Name of the event The IMPLAN sector the event impacts Industry or Commodity type impact The dollar value of the impact The number of direct employees the impact will generate. The year of the dollar value of the impact. If different than base year, the deflator will adjust the Value to a base year value. The deflator value used to change event dollars into model year dollars (optional)

Table: IMGroups Contains all information to tie groups to events Name Group ID EventID Group Name Unit Description Level

Type Long Long Text Text Single

Size 4 4 50 50 4

Description The Group identification code The Event identification code The name of the group The description of the measure of the groups The number of groups desired for a particular impact

328

Appendix E: IAP Documentation run. The level is multiplied by each event to get the total direct impact

Table: IMIndustry Transactions Created during the impact assessment portion of the program. contains industry impact data used to create the impact reports. Name Sector Value RPC

Type Integer Single Single

Size 2 4 4

Description The industry code The dollar value of the impact The Regional Purchase Coefficient used to localize the impact (optional)

Table: IMMargins Contains margin information for use in the impact assessments Name EventID Type

Type Long Single

Size 4 4

Sector MargSector Deflator

Integer Integer Single

2 2 4

Value

Single

4

Description The event identification number The type of margin used: household; industry; government; investment. The sector that a margin is being applied to. The sector that is receiving the margined values The deflator value used to change event dollars into model year dollars (optional) The dollar value of the impact.

Table: IMProjects Contains all information to tie projects to groups Name ProjectID GroupID Project Name Level

Type Long Long Text Single

Size 4 4 50 4

Description The project identification number. The group identification number. The name given to the project The number of projects desired for a particular impact run. The level is multiplied by each group to get the total direct impact

Table: Industry/Commodity Codes Contains the code numbers for industries and commodites. Name Industry/Commodity Code

Type Integer

Size 2

Description

Text

50

Description The code number for each unique industry or commodity. Industries and commodities share the same name and number. The description of the industry or commodity identified by the code.

Table: Margins Contains margin information used in changing purchaser prices into producer prices. This table provides the basis for the IMMargins table.

Appendix E: IAP Documentation 329 Name Type

Type Long

Size 4

Sector MargSector Value

Integer Integer Single

2 2 4

Description The type of margin used: household; industry; government; investment. The sector that a margin is being applied to. The sector that is receiving the margined values The dollar value of the impact.

Table: Margin Codes Contains margin information used in changing purchaser prices into producer prices. This table provides the basis for the IMMargins table. Name Type Code

Type Long

Size 4

Description

Text

50

Description Code for type of transaction. In this case, it is the industry or commodity code Description of the sector involved.

Table: Model Specs Contains information for various aspects of the model building process. Name Detail

Type Text

Size 15

Value

Single

4

Description Type of specification based on model progress and type of model built. Flag for each detail entry.

Table: Observed RPCs All observed regional purchase coefficients for non-shippable commodities. Has all states included. Name State Code Commodity Code Observed RPC

Type Text Integer Single

Size 2 2 4

Description State identifier code. Code that identifies the commodity The observed RPC value.

Table: Regional Absorption Table contains the regional absorption matrix created during the construction of the regional social accounts. The absorption table shows industry purchases of commodities in a unitary form. The regional absorption values are also known as the production functions. Name Industry Code

Type Integer

Size 2

Commodity Code Gross Absorption Coefficient RPC

Integer Single

2 4

Single

4

Foreign Import Proportion

Single

4

Fixed

Yes/No

1

Description Code for the industry making the absorption purchases. Code for the commodity being used. Total absorption value prior to adjustment for imports. Regional purchase coefficient value adjusted for supply/demand pooling. This value allows splitting of the absorption into its local and import components. Ratio that allows splitting of imports into its foreign and domestic components. For use in editing the absorption values. If fixed is

330

Appendix E: IAP Documentation yes, the value will not change when re-balanced.

Table: Regional Byproducts Table contains the regional byproducts matrix created during the construction of the regional social accounts. The byproducts table shows industry production of commodities in a unitary form. Name Industry Code

Type Integer

Size 2

Commodity Code Byproducts Coefficient RSC

Integer Single Single

2 4 4

Foreign Export Proportion

Single

4

Fixed

Yes/No

1

Description Code for the industry making the absorption purchases. Code for the commodity being used. Byproducts balue. Regional sales coefficient value. This value allows splitting of the make of commodities into the locally sold and export components. Ratio that allows splitting of exports into its foreign and domestic components. For use in editing the byproducts values. If fixed is yes, the value will not change when re-balanced.

Table: Regional Commodity Balances Contains information on regional commodity balances filled in as the model is being constructed. This table contains all information for construction of net commodity supply/commodity demand and imports. Name Commodity Code Industry Commodity Production Institutional Commodity Sales Total Commodity Supply

Type Integer Single

Size 2 4

Description Commodity identifier. Value of commodity production by industries

Single

4

Single

4

Net Commodity Supply Intermediate Commodity Demand Institutional Commodity Demand Total Gross Commodity Demand Foreign Exports

Single Single

4 4

Single

4

Value of commodities sold by institutions, i.e.households, government, and inventory. Total commodity available in the region. The sum of industry commodity production and institutional commodity sales. Total commodity supply less foreign exports. The demand for commodities by industries for use in production. The sum of the Use matrix rows. Demand for commodities by final demand elements.

Single

4

Single

4

Domestic Exports

Single

4

Intermediate Imports

Single

4

Institutional Imports Foreign Transshipments

Single Single

4 4

Total Imports

Single

4

Sum of intermediate and institutional commodity demand. Not adjusted for imports. Total commodities exported to foreign markets. Used in net commodity supply calculation. From study area data. Residual value of commodity demanded and supplied within the region. Commodities imported to satisfy intermediate demand. Commodities imported to satisfy institutional demand. Commodities imported into the region and exported with no further processing. Sum of intermediate and institutional imports.

Appendix E: IAP Documentation 331 Domestic Supply/Demand Ratio Average RPC

Single

4

Single

4

Foreign Import Proportion

Single

4

Total Commodity Output Total Domestic Commodity Output Average RSC

Single Single

4 4

Single

4

Foreign Export Proportion

Single

4

Demand/Supply Ratio

Single

4

Net commodity supply divided by total gross commodity demand. Regional purchase coefficient. Total local commodities purchased by local consumers. Calculated by regression and limited by the supply/demand pooling ratio. A ratio that allows splitting the imports into foreign and domestic. Derived from the national model. Sum of commodity production Sum of domestic commodity production. Regional sales coefficient. Proportion of commodity exported. A ratio that allows splitting the exports into foreign and domestic. Derived from the each model. Inverse of supply/demand pooling ratio.

Table: Regional Factor Balances Contains factor portion of SAM model development. Name Type Code Total Receipts Gross Outlays to Households Outlays to Government Outlays to Enterprises Outlays to Capital Outlays to ROW Total Gross Outlays Net Receipts Domestic Factor Imports Average Household RSC Foreign Export Proportion Domestic Outlays to Households Total Outlays

Type Single Single Single

Size 4 4 4

Description Type of transaction identifier. Total receipts of factor incomes Total income paid to households

Single Single Single Single Single Single Single Single Single

4 4 4 4 4 4 4 4 4

Single

4

Total income paid to governments. Total income paid to enterprises. Total income paid to capital. Total income paid to rest-of-world. Total outlays to all institutions. Sum of above. Income less expenditures. Imports of factor receipts Exports of household factor income. Ratio for splitting factor exports into foreign and domestic components. Payments to households from local sources.

Single

4

Sum of all outlays. Should be equal to total receipts.

Table: Regional Industry Balances Contains information on regional industry balances filled in as the model is being constructed. This table contains all information for construction of industry outlays. Name Industry Code Industry Output

Type Integer Single

Size 2 4

Industry Outlay

Single

4

Gross Intermediate Outlay

Single

4

Total Value Added

Single

4

Description Industry identifier. Value of production by industry. From study area data. Total expenditures by industry to produce its output. Is equal to industry output. Total industry expenditures on goods and services to produce industry output. Total payments to value added elements. From study area data.

332

Appendix E: IAP Documentation

Total Imports Total Foreign Imports Absorption Adjustment

Single Single Single

4 4 4

Industry RPC

Single

4

Total imports used in the production process. Total foreign imports used in the production process. Absorption adjustment ratio used to regionalize the national absorption matrix. Regional purchase coefficient on an industry basis. Used in the impact assessment portion of the program.

Table: Regional Institution Balances Contains information developed during the balancing of the SAM accounts on an institution basis. Name Type Code Domestic Commodity Outlays Domestic Commodity Imports Foreign Commodity Imports Outlays to Households Outlays to Government Outlays to Enterprises Prelim Outlays to Capital Domestic NonCommodity Imports Foreign NonCommodity Imports Preliminary Total Outlays Domestic Commodity Receipts Domestic Commodity Exports Foreign Commodity Exports Receipts from Factors Receipts from Households Receipts from Governments Receipts from Enterprises Preliminary Capital Receipts Domestic NonCommodity Exports Foreign NonCommodity Exports Preliminary Total Receipts Net Receipts Surplus or Savings Deficit or Borrowing Capital Outlay Balances Capital Receipts Balances Revised Outlays to Capital

Type Single Single

Size 4 4

Description Type of transaction Total local outlays for commodities by institutions.

Single

4

Total domestic commodity imports by institutions.

Single

4

Total foreign commodity imports by institutions.

Single Single Single Single Single

4 4 4 4 4

Single

4

Single Single

4 4

Total institutional payments to households. Total institutional payments to goverments. Total institutional payments to enterprises. Institutional payments to capital prior to balancing. Domestic imports of institutional transfer payments not related to commodities. Foreign imports of institutional transfer payments not related to commodities. Institutional transfer payments prior to balancing. Total local receipts of transfer income.

Single

4

Domestic exports of transfer income.

Single

4

Foreign exports of transfer income.

Single Single Single

4 4 4

Total income receipts from factor balances table. Total income receipts from households. Total income receipts from governments.

Single Single

4 4

Total income receipts from enterprises Income receipts from capital prior to balancing.

Single

4

Exports of institutional income to domestic markets.

Single

4

Exports of institutional income to foreign markets.

Single Single Single Single Single Single Single

4 4 4 4 4 4 4

Total income prior to balancing. Income less expenditures prior to balancing. Preliminary savings. Preliminary borrowing. Value necessary to balance capital outlays. Value necessary to balance capital receipts. Capital expenditures after balancing.

Appendix E: IAP Documentation 333 Revised Capital Receipts Revised Net Receipts Total Outlays Total Receipts

Single Single Single Single

4 4 4 4

Income receipts from capital after balancing. Income less expenditures after balancing. Total institutional expenditures after balancing. Total institutional income after balancing.

Table: Regional Institution Demand Contains local final demand information Name Type Code Commodity Code Gross Institution Demand RPC Foreign Import Proportion

Type Integer Integer Single Single Single

Size 2 2 4 4 4

Description Type of transaction. Commodity identifier. Total institutional final demand for commodities. Regional purchase coefficient. Ratio that splits foreign and domestic imports.

Table: Regional IxI Balances Contains regional industry by industry table. Created by multiplying the absorption by the market shares tables. Name Industry Col Code Industry Row Code IxI Direct Requirements

Type Integer Integer Single

Size 2 2 4

Description Table column identifier. Table row identifier. Industry by Industry direct requirements coefficient.

Table: Regional Market Shares Contains regional market shares table. Created by dividing the make matrix by its column elements. Name Industry Code Commodity Code Regional Market Shares RSC

Type Integer Integer Single Single

Size 2 2 4 4

Foreign Export Proportion

Single

4

Description Industry identifier. Commodity identifier. Regional market shares value. Regional sales coefficient. Determines portion of market shares exported outside the region. Portion of exports going to foreign markets.

Table: Regional Multipliers Induced Contains induced regional multipliers table. This is only the induced portion of the multipliers. To obtain the Type II or III, this is added to the Type I table. Name Industry Col Code Industry Row Code Multiplier

Type Integer Integer Single

Size 2 2 4

Description Table column identifier. Table row identifier. Induced multiplier.

Table: Regional Multipliers Type I Contains Type I regional multipliers table. Name Industry Col Code

Type Integer

Size 2

Description Table column identifier.

334

Appendix E: IAP Documentation

Industry Row Code IxI Direct Requirements

Integer Single

2 4

Table row identifier. Industry by Industry direct requirements coefficient.

Table: Regional SAM Balances Contains SAM balance information with industry part aggregated to one sector. Name Institution Payments Institution Receipts Type of Transfer Value RSC

Type Integer Integer Integer Single Single

Size 2 2 2 4 4

Foreign Export Proportion

Single

4

Description Code for type of institution making expenditures. Code for type of institution receiving income. Type of institutional transfer. Value of transfer. Regional sales coefficient. Portion of transfers that go to outside markets. Proportion of income that goes to foreign markets.

Table: Regional SAM Balances Aggregated Contains SAM balance information without the type of transfer information. Name Institution Payments Institution Receipts Value

Type Integer Integer Single

Size 2 2 4

Description Code for type of institution making expenditures. Code for type of institution receiving income. Value of transfer.

Table: RPC Methods Contains information for creation of the regional purchase coefficients. Includes the regression coefficients and also information collected from the study region. Name Commodity Code MRIO 1 MRIO 2 FIMP US Comm Emp Method

Type Integer Integer Integer Single Single Text

Size 2 2 2 4 4 8

BO B1 B2 B3 B4 Local Comm Emp Local Comm EC Total Local Emp Total US Emp Local Land Area Land Area RPC

Single Single Single Single Single Single Single Single Single Single Single Single

4 4 4 4 4 4 4 4 4 4 4 4

Description Commodity identifier. Multi-Region input output study code number 1 Multi-Region input output study code number 2 Foreign import proportion coefficient. US commodity based employment Identifies the RPC method used for each sector. Possibilities are REGRESS, OBSERVED. Beta coefficient 0 Beta coefficient 1 Beta coefficient 2 Beta coefficient 3 Beta coefficient 4 Local commodity based employment. Local commodity based employee compensation. Total local commodity based employment. Total US commodity based employment. Study region land area in square miles. US land area in square miles. Calculated regional purchase coefficient.

Appendix E: IAP Documentation 335

Table: rptEC Multipliers Report table with employee compensation multipliers. Name Industry Code Direct Effects

Type Integer Single

Size 2 4

Indirect Effects

Single

4

Induced Effects

Single

4

Type I Multiplier Type II Multiplier Type III Multiplier

Single Single Single

4 4 4

Description Industry identifier. Employee compensation direct effects of $1 change in final demand. Employee compensation indirect effects of $1 change in final demand. Employee compensation induced effects of $1 change in final demand. Type I employee compensation multiplier. Type II employee compensation multiplier. Type III employee compensation multiplier.

Table: rptEmployment Multipliers Report table with employment multipliers. Name Industry Code Direct Effects

Type Integer Single

Size 2 4

Indirect Effects

Single

4

Induced Effects

Single

4

Type I Multiplier Type II Multiplier Type III Multiplier

Single Single Single

4 4 4

Description Industry identifier. Employment direct effects of 1 million dollar change in final demand. Employment indirect effects of a change in final demand. Employment induced effects of a change in final demand. Type I employment multiplier. Type II employment multiplier. Type III employment multiplier.

Table: rptIBT Multipliers Report table with indirect business taxes multipliers. Name Industry Code Direct Effects

Type Integer Single

Size 2 4

Indirect Effects

Single

4

Induced Effects

Single

4

Type I Multiplier Type II Multiplier Type III Multiplier

Single Single Single

4 4 4

Description Industry identifier. Indirect business taxes direct effects of $1 change in final demand. Indirect business taxes indirect effects of $1 change in final demand. Indirect business taxes induced effects of $1 change in final demand. Type I indirect business taxes multiplier. Type II indirect business taxes multiplier. Type III indirect business taxes multiplier.

Table: rptOPTI Multipliers Report table with other property type income multipliers. Name Industry Code Direct Effects

Type Integer Single

Size 2 4

Description Industry identifier. Other property type income direct effects of $1 change in final demand.

336

Appendix E: IAP Documentation

Indirect Effects

Single

4

Induced Effects

Single

4

Type I Multiplier Type II Multiplier Type III Multiplier

Single Single Single

4 4 4

Other property type income indirect effects of $1 change in final demand. Other property type income induced effects of $1 change in final demand. Type I other property type income multiplier. Type II other property type income multiplier. Type III other property type income multiplier.

Table: rptOutput Multipliers Report table with output multipliers. Name Industry Code Direct Effects Indirect Effects Induced Effects Type I Multiplier Type II Multiplier Type III Multiplier

Type Integer Single Single Single Single Single Single

Size 2 4 4 4 4 4 4

Description Industry identifier. Output direct effects of $1 change in final demand. Output indirect effects of $1 change in final demand. Output induced effects of $1 change in final demand. Type I output multiplier. Type II output multiplier. Type III output multiplier.

Table: rptPersonal Income Multipliers Report table with personal income multipliers. Name Industry Code Direct Effects

Type Integer Single

Size 2 4

Indirect Effects

Single

4

Induced Effects

Single

4

Type I Multiplier Type II Multiplier Type III Multiplier

Single Single Single

4 4 4

Description Industry identifier. Personal income direct effects of $1 change in final demand. Personal income indirect effects of $1 change in final demand. Personal income induced effects of $1 change in final demand. Type I personal income multiplier. Type II personal income multiplier. Type III personal income multiplier.

Table: rptPropInc Multipliers Report table with proprietors income multipliers. Name Industry Code Direct Effects

Type Integer Single

Size 2 4

Indirect Effects

Single

4

Induced Effects

Single

4

Type I Multiplier Type II Multiplier Type III Multiplier

Single Single Single

4 4 4

Description Industry identifier. Proprietors income direct effects of $1 change in final demand. Proprietors income indirect effects of $1 change in final demand. Proprietors income induced effects of $1 change in final demand. Type I proprietors income multiplier. Type II proprietors income multiplier. Type III proprietors income multiplier.

Appendix E: IAP Documentation 337

Table: rptSAIndustry Data Report table with study area data. Name Industry Code Industry Output Employment Employee Compensation Proprietor Income Other Property Income Indirect Business Tax

Type Integer Single Single Single Single Single Single

Size 2 4 4 4 4 4 4

Description Industry identifier. Value for output Value for employment Value for EC Value for PI Value for OPI Value for IBT

Table: rptTotal VA Multipliers Report table with value added multipliers. Name Industry Code Direct Effects

Type Integer Single

Size 2 4

Indirect Effects

Single

4

Induced Effects

Single

4

Type I Multiplier Type II Multiplier Type III Multiplier

Single Single Single

4 4 4

Description Industry identifier. Value added direct effects of $1 change in final demand. Value added indirect effects of $1 change in final demand. Value added induced effects of $1 change in final demand. Type I value added multiplier. Type II value added multiplier. Type III value added multiplier.

Table: SACommodity Sales Study area data table with commodity sales information. Name Type Code Commodity Code Commodity Sales

Type Integer Single Single

Size 2 4 4

Description Type of transaction. Commodity identifier. Commodity sales by institutions.

Table: SAEmployment Study area data table with employment information. Name Type Code Industry Code Employment

Type Integer Single Single

Size 2 4 4

Description Type of transaction. Industry identifier. Full and part-time annual average employment

Table: SAFinal Demands Study area data table with final demands information. Name Type Code Commodity Code Gross Final Demand

Type Integer Single Single

Size 2 4 4

Description Type of transaction. Commodity identifier. Demand for commodities by institutions including

338

Appendix E: IAP Documentation imports.

Table: SAForeign Exports Study area data table with foreign export information. Name Type Code Commodity Code Foreign Exports

Type Integer Single Single

Size 2 4 4

Description Type of transaction. Commodity identifier. Commodities sold to foreign markets.

Size 2 4 50

Description Type of transaction. Summary code Description

Table: SAM Rollup Table for creating SAM reports. Name Type Code Summary Code Description

Type Integer Long Text

Table: SAOutput Study area data table with output information. Name Type Code Industry Code Output

Type Integer Single Single

Size 2 4 4

Description Type of transaction. Industry identifier. Value of production, similar to industry sales plus or minus inventory.

Table: SARatios Study area data table with information on various ratios used in impact and multiplier calculations. Name Sector Output Employment Employee Compensation Proprietor Income Total Value Added Indirect Business Taxes OPTI

Type Integer Single Single Single Single Single Single Single

Size 2 4 4 4 4 4 4 4

Description Industry identifier. Total output by sector. Employment for $1,000,000 of output Employee Compensation for $1,000,000 of output Proprietor incomeI for $1,000,000 of output Total value added for $1,000,000 of output Indirect Business Taxes for $1,000,000 of output Other Property Type Income for $1,000,000 of output

Table: SATransfers Study area data table with inter-institutional transfers information. Name Institution Payments Institution Receipts Type of Transfer Value

Type Integer Integer Integer Single

Size 2 2 2 4

Description Code for type of institution making expenditures. Code for type of institution receiving income. Type of institutional transfer. Value of transfer.

Appendix E: IAP Documentation 339

Table: SAValue Added Study area data table with value added information. Name Type Code Industry Code Value Added

Type Integer Single Single

Size 2 4 4

Description Type of transaction. Industry identifier. Value added elements by industry. Included are employee compensation, proprietors income, IBT, OPTI.

Size 2 50 2 2 8

Description Paying institution Description Receiving institution Transfer type Coefficient value of tax

Table: Tax Impacts Table for tax report. Name Institution Payments Column Header Institution Receipts Type of Transfer SAM Value

Type Integer Text Integer Integer Double

Table: Type Code Rollup Type code information for summarizing reports. Name Summary Code Type Code

Type Integer Integer

Size 2 2

Description Type of transaction. Type of transaction.

Table: Type Codes Table containing information on all transaction types in the data set. Name Type Code Type Description Comments

Type Integer Text Text Text

Size 2 25 50 150

Description Type of transaction. Descriptor of transaction type. Additional description of transaction. Additional comments.

Table: Type Codes Agg Type code information for summarizing reports. Name Type Code Type Description

Type Integer Text Text

Size 2 25 50

Description Type of transaction. Descriptor of transaction type Additional description

Table: US Absorption Table Table contains the United States absorption matrix from the structural matrices table. Name Industry Code

Type Integer

Size 2

Description Code for the industry making the absorption purchases.

340

Appendix E: IAP Documentation

Commodity Code Absorption Coefficient

Integer Single

2 4

Code for the commodity being used. US absorption value.

Table: US Absorption Totals Table contains the United States absorption matrix from the structural matrices table. Name Industry Code

Type Integer

Size 2

Total Absorption Coefficient

Single

4

Description Code for the industry making the absorption purchases. Column total for US absorption values.

Table: US Byproducts Table Table contains the United States absorption matrix from the structural matrices table. Name Industry Code

Type Integer

Size 2

Commodity Code Byproducts Coefficient

Integer Single

2 4

Description Code for the industry making the absorption purchases. Code for the commodity being used. US Byproducts value.

Appendix E: IAP Documentation 341

Library File Documentation Table: Aggregation Industries Table contains information on aggregation schemes created with IMPLAN Pro. Name ID Aggregated Industry code Aggregated Industry Description

Type Integer Integer Text

Size 2 2 255

Description Aggregation scheme identifier. Aggregated industry identifier code. Description of aggregated industry.

Table: Aggregation Template Table contains aggregation template information. Name ID Industry Code Aggregated Industry Code Industry Description

Type Integer Integer Integer Text

Size 2 2 2 50

Description Aggregation scheme identifier. Disaggregated industry code. Aggregated industry identifier code. Description of aggregated industry.

Table: IMEvents Table contains event information saved to the library.. Name EventID Event Name Sector Ind/Com

Type Long Text Integer Yes/No

Size 4 50 2 1

Value Employment Year Deflator

Single Single Integer Single

4 4 2 4

Margin

Integer

2

LPC

Yes/No

1

Level Resulting Values

Single Single

4 4

Description Event identifier. Name of event. Industry of commodity identifier. Code to determine if event is industry or commodity based. Dollar value of transaction. Number of employees transaction involves. Year of transaction dollars. Value used to deflate transaction value to model year dollars. Type of margin if transaction dollars are in purchaser prices. Local purchase coefficients used if transaction is not solely local. Number of transactions in the event. Level times the transaction value.

342

Appendix E: IAP Documentation

Table: IMGroups Table contains group information saved to the library.. Name Name Group ID EventID Group Name Unit Description Level

Type Type Long Long Text Text Single

Size Size 4 4 50 50 4

Description Description The Group identification code The Event identification code The name of the group The description of the measure of the groups The number of groups desired for a particular impact run. The level is multiplied by each event to get the total direct impact

Table: IMMargins Contains margin information for use in the impact assessments saved to the library. Name EventID Type

Type Long Single

Size 4 4

Sector MargSector Deflator

Integer Integer Single

2 2 4

Value

Single

4

Description The event identification number The type of margin used: household; industry; government; investment. The sector that a margin is being applied to. The sector that is receiving the margined values The deflator value used to change event dollars into model year dollars (optional) The dollar value of the impact.

Table: IMProjects Contains all information to tie projects to groups saved to the library. Name ProjectID GroupID Project Name Level

Type Long Long Text Single

Size 4 4 50 4

Description The project identification number. The group identification number. The name given to the project The number of projects desired for a particular impact run. The level is multiplied by each group to get the total direct impact

Table: Industry/Commodity Codes Contains the code numbers for industries and commodities saved to library. Name Industry/Commodity Code

Type Integer

Size 2

Description

Text

50

Description The code number for each unique industry or commodity. Industries and commodities share the same name and number. The description of the industry or commodity identified by the code.

Appendix E: IAP Documentation 343

Table: Production Functions Contains the production functions saved to the library. Name ID Ind Code Com Code Abs Coefficient

Type Integer Integer Integer Single

Size 2 2 2 4

Description Production function identifier code. Industry identifier. Commodity identifier. Production function coefficient saved to library.

Table: Production Functions Description Contains the description of the production functions saved to the library. Name ID Ind Code Description

Type Integer Integer Text

Size 2 2 75

Description Production function identifier code. Industry identifier. Description of the production function saved to library.

344

Appendix E: IAP Documentation

U.S. Structural Matrices File Documentation Table: 1987 Bureau of Economic Analysis 537 Sectors Contains the Benchmark IO industry descriptions. This is a bridge from BEA to SIC codes. Name Industry Number Industry Description Related SIC Codes

Type Text Text Text

Size 6 55 42

Description BEA industry identifier. BEA industry description. Related Standard Industrial Classification codes.

Table: 1987 Standard Industrial Classification Codes Contains all SIC codes as published by the Office of Management and Budget. Name Index Major Sector SIC Code Description

Type Double Text Text Text

Size 8 1 4 100

Description MIG index used in programming. 1 Digit SIC code. Standard Industrial Classification codes. Standard Industrial Classification codes description.

Size 2 4 4

Description IMPLAN industry code. Deflator for 1977 All other deflators.

Table: Deflators Contains deflators. Name Industry 1977 1977-Current year

Type Integer Number Number

Table: Foreign Import Proportions Contains information for splitting the imports between foreign and domestic. Derived from the national model Name Commodity Code Foreign Import Proportion

Type Integer Single

Size 2 4

Description Commodity identifier. Ratio that splits foreign and domestic imports.

Table: General Information Contains information the IMPLAN data set for the particular year and structural matrices. Name Structure Industries Commodities Land Area

Type Text Long Long Double

Size 50 8 8 8

Description Structural matrices file name. Maximum number of industries in a model. Maximum number of commodities in a model. US land area.

Appendix E: IAP Documentation 345 Population Version

Double Date/Time

8 8

US Population. Database version associated with this structural matrices version.

Table: Industry/Commodity Codes Contains the code numbers for industries and commodities saved to library. Name Industry/Commodity Code

Type Integer

Size 2

Description

Text

50

Description The code number for each unique industry or commodity. Industries and commodities share the same name and number. The description of the industry or commodity identified by the code.

Table: Margins Contains standard margin information. Name Type

Type Single

Size 4

Sector MargSector Value

Integer Integer Single

2 2 4

Description The type of margin used: household; industry; government; investment. The sector that a margin is being applied to. The sector that is receiving the margined values The dollar value of the impact.

Table: Margins Codes Contains margin information used in changing purchaser prices into producer prices. This table provides the basis for the IMMargins table. Name Type Code

Type Long

Size 4

Description

Text

50

Description Code for type of transaction. In this case, it is the industry or commodity code Description of the sector involved.

Table: Observed RPCs All observed regional purchase coefficients for non-shippable commodities. Has all states included. Name State Code Commodity Code Observed RPC

Type Text Integer Single

Size 2 2 4

Description State identifier code. Code that identifies the commodity The observed RPC value.

Table: ODF Read Information on reading the ODF binary files. Name Type Code Name Location Table Location

Type Integer Text Single Text

Size 2 30 4 20

Description Type of transaction Name of item. Location in binary file. Table item is written to.

346

Appendix E: IAP Documentation

Table: RPC Methods Contains information for creation of the regional purchase coefficients. Includes the regression coefficients and also information collected from the study region. Name Commodity Code MRIO 1 MRIO 2 FIMP

Type Integer Integer Integer Single

Size 2 2 2 4

US Comm Emp Method

Single Text

4 8

BO B1 B2 B3 B4 Local Comm Emp Local Comm EC Total Local Emp Total US Emp Local Land Area Land Area RPC Foreign Import Proportions

Single Single Single Single Single Single Single Single Single Single Single Single Single

4 4 4 4 4 4 4 4 4 4 4 4 4

Description Commodity identifier. Multi-Region input output study code number 1 Multi-Region input output study code number 2 Foreign import proportion coefficient used for RPC calculation. US commodity based employment Identifies the RPC method used for each sector. Possibilities are REGRESS, OBSERVED. Beta coefficient 0 Beta coefficient 1 Beta coefficient 2 Beta coefficient 3 Beta coefficient 4 Local commodity based employment. Local commodity based employee compensation. Total local commodity based employment. Total US commodity based employment. Study region land area in square miles. US land area in square miles. Calculated regional purchase coefficient. Foreign Import Proportion coefficient used for model calculations.

Table: SIC to IMPLAN Bridge Contains the bridge codes to move from SIC to IMPLAN codes. Name IMPLAN 528 Description SIC Code

Type Integer Text Text

Size 2 50 4

Description IMPLAN industry/commodity code number. IMPLAN code description. Related Standard Industrial Classification codes.

Table: Type Codes Table containing information on all transaction types in the data set.. Name Type Code Type Description Comments

Type Integer Text Text Text

Size 2 25 50 150

Description Type of transaction. Descriptor of transaction type. Additional description of transaction. Additional comments.

Table: US Absorption Table Table contains the United States absorption matrix from the structural matrices table. Name Industry Code Commodity Code Absorption Coefficient

Type Integer Integer Single

Size 2 2 4

Description Code for the industry making the absorption purchases. Code for the commodity being used. US absorption value.

Appendix E: IAP Documentation 347

Table: US Absorption Totals Table contains the United States absorption matrix from the structural matrices table. Name Industry Code Total Absorption Coefficient

Type Integer Single

Size 2 4

Description Code for the industry making the absorption purchases. Column total for US absorption values.

Table: US Byproducts Table Table contains the United States absorption matrix from the structural matrices table. Name Industry Code Commodity Code Byproducts Coefficient

Type Integer Integer Single

Size 2 2 4

Description Code for the industry making the absorption purchases. Code for the commodity being used. US Byproducts value.

Table: US Output Table contains the United States output estimates. Name Type Code Industry Code Output

Type Integer Integer Single

Size 2 2 4

Description Type of transaction. Industry identifier. US Value of production.

Appendix F: Sample Reports

A P P E N D I X

349

F

Sample Reports This appendix shows an example portion of all reports available through the Reports section of the IMPLAN Pro software.

Study Area Reports Institution Commodity Demand Household Commodity Demand Government Commodity Demand Institutional Sales Output, VA, Employment General Model Information IMPLAN to Standard Industrial Classification (SIC) Bridge Type Codes Aggregation Template

No. SA001 SA011 SA012 SA040 SA050 SA090 SA091 SA092 SA100

Social Accounts Reports Ind and Com in Model Commodity Summary Institution Local Commodity Demand Household Local Commodity Demand Government Local Commodity Demand Commodity Trade Industry Summary Industry Balance Sheet Commodity Balance Sheet Industry Import Matrix Institution Import Matrix

EA001 EA020 EA030 EA031 EA032 EA040 EA050 EA060 EA070 Text201 Text202

IxC SAM Reports Aggregate IxC SAM (Aggregated Ind, Aggregated Rows) Ind x Com SAM (Aggregated Industries, Row Detail) Ind x Com SAM (Industry Detail, Aggregated Rows) Ind x Com SAM (Ind Detail, Row Detail) CGE Format

SAM001 Text301 Text302 Text303 Text304

350

Appendix F: Sample Reports

Structural Matrices Regional Use Regional Make Gross Absorption Regional Absorption Byproducts Market Shares

Text401 Text402 Text403 Text404 Text405 Text406

Industry by Industry Reports Institution Industry Demand Household Industry Demand Government Industry Demand Industry Output/Outlay Summary Aggregate IxI SAM (Aggregated Ind, Aggregated Rows) Regional IxI Direct Coefficients Regional IxI Transactions Ind x Ind SAM (Aggregated Ind, Row Detail) Ind x Ind SAM (Industry Detail, Aggregated Rows) Ind x Ind SAM (Indu Detail, Row Detail)

II030 II031 II032 II050 II060 Text501 Text502 Text503 Text504 Text505

Multipliers Reports Output Employment Labor Income Total Value Added Employee Compensation Proprietor’s Income Other Property Type Income Indirect Business Taxes Type I Multipliers Induced Multipliers

MR010 MR020 MR030 MR040 MR050 MR060 MR070 MR080 Text601 Text602

Impacts Reports Output Employment Labor Income Total Value Added Employee Compensation

IM010 IM020 IM030 IM040 IM050

Appendix F: Sample Reports Proprietor’s Income Other Property Type Income Indirect Business Taxes Project Impact Description Group Impact Description Tax Impacts

IM060 IM070 IM080 IM091 IM092 IM100

351

352

Appendix F: Sample Reports

Study Area Reports Study Area reports display the region’s data as found in the IMPLAN data files, or as modified by the user. All final demand data is in commodity basis and contain demand for both local and imported production. Several of the reports also contain definitional data about IMPLAN sectoring and database type codes.

Institution Commodity Demand - report #SA001: (otherwise known as final demands) all data is on commodity basis and contains imports.

Households: purchase of commodities by individuals for personal use. This is a summation for all categories of household income. Also known as PCE –i.e., Personal Consumption Expenditures. Federal Gov: purchase of commodities by all categories of Federal government. State & Local: purchase of commodities by all categories of State and Local governments. Capital: purchase of commodities for investment purposes by private entities. Inventory: additions to inventory, also known as “involuntary investment”. Foreign Exports: shipment of commodities to destinations outside of the U.S.

Appendix F: Sample Reports

353

Household Commodity Demand – report SA011: contains detail of the household final demand (PCE) summarized in the Institution Commodity Demand Report. It represents purchases of commodities by individuals for personal use. All data is commodity basis and contains imports. The nine categories of households (1996 and later data) are based on total annual household income as described by the column headers. For 1995 and earlier data sets the three categories are:

Low Med High

1992-1995 $0-20,000 $20,000-50,000 $50,000+

1977-1991 $0-15,000 $15,000-30,000 $30,000

354

Appendix F: Sample Reports

Government Commodity Demand – report SA012: contains detail of the administrative government purchases of commodities. All data is commodity basis and contains imports.

Non-Defense Federal Government Expenditures: purchase of commodities by Federal agencies other than defense agencies. Defense Federal Government Expenditures: purchase of commodities by Federal defense agencies. Investment Federal Government Expenditures: capital goods expenditures by all Federal agencies. This category only exists in 1996 and later data sets. Before 1996 investment was part of the non-defense expenditures. Non-education State and Local Government Expenditures: purchase of commodities by non-educational state and local government agencies. Education State and Local Government Expenditures: purchase of commodities by educational (primary, secondary and higher-ed) state and local government agencies. Investment State and Local Government Expenditures: capital goods expenditures by all state and local government agencies. This category only exists in 1996 and later data sets. Before 1996 investment was part of the non-education expenditures.

Appendix F: Sample Reports

355

Institutional Sales – report SA040: sales of commodities by non-industry sectors. In IMPLAN these are contributions to the region’s commodity supply as opposed to the BEA’s definition of a negative final demand.

PCE: sales of commodities by households (nine categories starting with 1996 data, three categories previously –most commonly used and second hand goods. Federal Government: sales of commodities by all non-enterprise Federal government agencies –e.g., military base retail, surplus, and USFS stumpage. St & Local Government: sales of commodities by all non-enterprise state and local government agencies – e.g., dormitories, campgrounds, and surplus. Capital: sales by investment, normally scrap materials. Inventory: represents a reduction of inventory –i.e., sales from production of previous years. Total Sales: sum of all previous institutional sales columns.

356

Appendix F: Sample Reports

Output, VA, Employment - report #SA050: report of data concerning local industries.

Industry Output: total industry production for a given data year. It is equal to shipments plus net additions to inventory. Employment: number of full and part-time jobs (annual average) required by a given industry – includes self-employed. Employee Compensation: total payroll costs (wages and salaries plus benefits) paid by local industries. Proprietor Income: income from self-employment. Other Property Income: includes corporate income, rental income, interest and corporate transfer payments. Indirect Business Taxes: sales, excise, fees, licenses and other taxes paid during normal operation of industry. This includes all payments to the government except for taxes based on income. Total Value Added: the value added to intermediate goods and services. It is equal to employee compensation plus proprietor income plus other property income plus indirect business taxes.

Appendix F: Sample Reports

357

General Model Information - report #SA090: displays number of households and median household income by annual household income category as well as some basic descriptive data for each county/state making up the model and totals. Note that for many income categories, median income exceeds the category range. This is an apparent underreporting of income to CES which shows up when we control CES data to REIS data (~30% upward revision).

Structural Matrix Name: defines the name of the Access data file containing the national structural matrices being used for this model. State/County Code: the FIPS (Federal information processing system) code defining this state and county. Area: the land area in square miles. For Michigan the state area in square miles is much larger when you include the Great Lakes than the land area shown by IMPLAN. Household Income: the average income within each income class. Note average income may exceed range. This is a result of using REIS to control CES data for the CES income ranges, apparently there is a tremendous amount of underreporting of income, especially in the lower income classes (~30% upward revision).

358

Appendix F: Sample Reports

IMPLAN to Standard Industrial Classification (SIC) Bridge - report #SA091: bridges the 1987 SIC codes to the IMPLAN sectoring. This is similar to appendix A in the software manual.

Appendix F: Sample Reports

Type Codes - report #SA092: type codes associated with the elements in the IMPLAN data base. This table is necessary to understand the data in Access database which represents the IMPLAN model. It also corresponds to Appendix D in the IMPLAN software manual.

359

360

Appendix F: Sample Reports

Aggregation Template - report #SA100: display aggregation of IMPLAN sectors based on the template currently residing in the model –whether or not the model or impact report has yet to be aggregated.

Appendix F: Sample Reports

361

Social Accounts Reports The process of creating a set of economic accounts applies study area data to the national absorption and byproducts matrices. The result is a set of balanced accounts complete with imports and exports. At this point all demands are on a commodity basis and differentiated between local and imported purchases.

Ind and Com in Models

- report #EA001

:

Ind: numbers appearing in this column indicate that industry sector exists in the model. Com: numbers appearing in this column indicate that commodity sector exists in the model.

362

Appendix F: Sample Reports

Commodity Summary- report #EA020:

Industry Commodity Production: regional production of commodities by industries. Institutional Commodity Sales: regional production of commodities by non-industry sources. Total Commodity Supply: total regional production of commodities. Equal to the sum of industry and institutional commodity production. Net Commodity Supply: locally produced goods and services available for local use (Total Commodity Supply minus Foreign Exports). Intermediate Commodity Demand: locally generated demand by industries for local and/or imported commodities. Institutional Commodity Demand: locally generated demand by non-industry sources (e.g., households and government) for local and/or imported commodities. Note, this does not include foreign exports. Total Gross Commodity Demand: locally generated demand by all sources for local and/or imported commodities. Equal to the sum of intermediate and institutional commodity demand. Domestic S/D Ratio: relationship of net commodity supply to total gross commodity demand. It is used by IMPLAN as an upper limit to the regional purchase coefficient. If supply exceeds demand the ratio is set to one. Average RPC: the regional purchase coefficients are IMPLAN’s estimated fraction of the region’s gross regional commodity demand, which is satisfied by local commodities. Average RSC: the regional sales coefficients are the fraction of net commodity supply used to meet regional gross commodity demand: RSC = (RPC * GCD) /NCS

Appendix F: Sample Reports

363

Institution Local Commodity Demand - report #EA030: (otherwise known as final demands) all data is commodity basis and is net of imports.

Households: purchase of commodities by individuals for personal use. This is a summation for all categories of household income. Also known as PCE –i.e., Personal Consumption Expenditures. Federal Gov: purchase of commodities by all categories of Federal government. State & Local: purchase of commodities by all categories of State and Local governments. Capital: purchase of commodities for investment purposes by private entities. Inventory: additions to inventory, also known as “involuntary investment”. Foreign Exports: shipment of commodities to destinations outside of the U.S.

364

Appendix F: Sample Reports

Household Local Commodity Demand - report #EA031: contains detail of the household final demand (PCE) summarized in the Institution Local Commodity Demand Report. It represents purchases of commodities by individuals for personal use. ) All data is commodity basis and is net of imports. The 9 categories of households (1996 to 1999) are based on total annual household income as described by the column headers. For 1995 and earlier data sets the three categories are: 1992-1995

1977-1991

Low

$0-20,000

$0-15,000

Med

$20,000-50,000

$15,000-30,000

High

$50,000+

$30,000

Appendix F: Sample Reports

365

Government Commodity Demand - report #EA032: contains detail of the administrative government purchases of commodities. ) All data is commodity basis and is net of imports.

Non-Defense Federal Government Expenditures: purchase of commodities by Federal agencies other than defense agencies. Defense Federal Government Expenditures: purchase of commodities by Federal defense agencies. Investment Federal Government Expenditures: capital goods expenditures by all Federal agencies. This category only exists in 1996 and later data sets. Before 1996 investment was part of the defense and non-defense expenditures. Non-education State and Local Government Expenditures: purchase of commodities by non-educational state and local government agencies. Education State and Local Government Expenditures: purchase of commodities by educational (primary, secondary and higher-education) state and local government agencies. Investment State and Local Government Expenditures: capital goods expenditures by all state and local government agencies. This category only exists in 1996 and later data sets. Before 1996 investment was part of the education and non-education expenditures.

366

Appendix F: Sample Reports

Commodity Trade - report #EA040:

Foreign Exports: commodities shipped to outside of the U.S. by local producers. Domestic Exports: exports by the region to the rest of the U.S. It equals net commodity supply time the quantity: one minus the regional sales coefficient. Total Exports: all regional exports – equal to foreign plus domestic exports. Intermediate Imports: imports of specific commodity by all local industries. Institutional Imports: imports of specific commodity by all local non-industry institutions Total Imports: imports of specific commodity by all regional sources. It is the sum of intermediate plus institutional imports. Foreign Export Proportion: proportion of total exports representing foreign exports.

Appendix F: Sample Reports

367

Industry Summary - report #EA050:

Industry Outlay: distribution of all income by industry. It is the sum of gross intermediate outlay plus total value added. It is also equal to total industry output. Gross Intermediate Outlay: payment by industry for all goods and services (commodities), both local and imported. Total Value Added: value added during production to all purchased intermediate goods and services. It is the sum of employee compensation plus proprietor’s income plus other property income plus indirect business taxes. Total Imports: imports of all commodities by the given industry from all sources, foreign and domestic. Total Foreign Imports: imports of commodities by the given industry from foreign sources. Absorption Adjustment: the ratio required to make the national intermediate coefficients plus Regional Factor add to 1.0. the adjusted National coefficients become the regional intermediate input coefficients. This rebalancing is required as value added coefficients vary for each region. IMPLAN assumes that all local is correct and that national relationships must adjust to the local conditions.

368

Appendix F: Sample Reports

Industry Balance Sheet - report #EA060:

Commodity Production: value of each commodity produced by the industry of interest –i.e., the corresponding industry row of the make matrix. Market Share Coefficient: the non-zero components from the corresponding industry row of the market share matrix. Ones (1.0) indicate that this industry is the only producer of that commodity. By-product Coefficient: the non-zero components from the corresponding industry row of the by-products matrix. Note that the sum of the column is 1.0. RPC (regional purchase coefficients): the IMPLAN estimated fraction of the region’s commodity demand met by using locally produced commodities. Total Commodity Export: domestic (to the rest of the U.S.) plus foreign commodity export. Gross Absorption Coefficeint: the corresponding industry column from the national absorption matrix (if not modified by the user) as adjusted for the local value added coefficients. Gross Inputs: the industry of interest’s total purchase of the commodities (including imported commodities). RPC (regional purchase coefficients): the IMPLAN estimated fraction of the region’s commodity demand met by using locally produced commodities.

Appendix F: Sample Reports

369

Regional Absorption Coefficient: fraction of total outlay spent by the industry on specific locally produced commodities. This is the product of the gross absorption coefficient times the RPC. Regional Inputs: the industry’s local purchase of each commodity. This is the product of gross inputs times the RPC. Value-Added Coefficient: portion of total industry outlay going to each element of value-added.

370

Appendix F: Sample Reports

Commodity Balance Sheet - report #EA070:

Industry production: total production of the highlighted commodity by each industry and institution producing the commodity. Market Share Coefficient: the non-zero components from the corresponding industry row of the market share matrix. Note that the sum of the column is 1.0. By-product Coefficient: the non-zero components from the corresponding industry row of the by-products matrix. RPC (regional purchase coefficients): the IMPLAN estimated fraction of the region’s commodity demand met by using locally produced commodities. Gross Absorption Coefficient: the corresponding industry column from the national absorption matrix (if not modified by the user) as adjusted for the local value-added coefficients. Gross Inputs: the industry of interest’s total purchase of the commodities (including imported commodities).

Appendix F: Sample Reports

371

RPC (regional purchase coefficients): the IMPLAN estimated fraction of the region’s commodity demand met by using locally produced commodities. Regional Absorption Coefficient: fraction of gross outlay spent by the industry on specific locally produced commodities. This is the product of the total absorption coefficient times the RPC. Regional Inputs: the industry’s local purchase of each commodity. This is the product of gross inputs times the RPC. The next two Social Accounts reports print only a text files as a series of records with five fields (columns).

Industry Import Matrix - report # Text201: total, competitive and non-competitive commodity imports by each industry. Commodity Code: Commodity being imported. Industry Code: Industry purchasing imported commodity . Imports: Total value of import. Competitive Imports: Value of imported commodity (this commodity is also produced locally). Non-Competitive Imports: Value of imported commodity (this commodity is not produced locally).

Institution Import Matrix - report # Text202: total, competitive and non-competitive commodity imports by each institution. Commodity Code: Commodity being imported. Type Code: Institution purchasing imported commodity (see appendix d for type codes). Imports: Total value of import. Competitive Imports: Value of imported commodity (this commodity is also produced locally). Non-Competitive Imports: Value of imported commodity (this commodity is not produced locally).

372

Appendix F: Sample Reports

IxC SAM Reports Aggregate IxC SAM (Aggregated Industries, Aggregated Rows) - report # SAM001: industries are aggregated to a single sector and institutions are limited to the same categories as the columns. Values are in millions of dollars.

The following three reports are available only in text form and are in the following format: “Rows, Columns, Value”

Ind x Com SAM (Aggregated Industries, Row Detail) - report # Text301: industries are aggregated to a single sector. The institution rows are as detailed as IMPLAN allows. This gives more detail for indirect business taxes and government receipts. Values are in millions of dollars.

Ind x Com SAM (Industry Detail, Aggregated Rows) - report # Text302: complete industry detail; therefore, if this report is to pulled into Excel it is necessary to aggregate the model to less than 225. Excel has a limit to the number of colums (for a pivot table) of 254. The institution rows are aggregated. Values are in millions of dollars. Ind x Com SAM (Industry Detail, Row Detail) - report # Text303: complete industry detail, therefore if this report is to pulled into Excel it is necessary to aggregate the model to less than 225. Excel has a limit to the number of colums (for a pivot table) of 254. The institution rows are as detailed as IMPLAN allows. This gives more detail for indirect business taxes and government receipts. Values are in millions of dollars. CGE Format- report # Text304: 26 text files are generated by this file and are intended as input into a GAMS CGE model. Values are in millions of dollars.

Appendix F: Sample Reports

373

Structural Matrices All reports are text files only with the format of : “Rows, Cols, Value”

Regional Use - report # Text401: Rows – commodity Columns – Industry Value – purchase of a local commodity by local industry (millions of dollars)

Regional Make

- report # Text402

:

Rows – Industry Columns – Commodity Value – production of commodities by local industry (millions of dollars)

Gross Absorption

- report # Text403

:

Rows – commodity Columns – Industry Value – proportion of total industry outlay used to purchase local and imported commodities (coefficient)

Regional Absorption

- report # Text404

:

Rows – commodity Columns – Industry Value – proportion of total industry outlay used to purchase local commodities (coefficient)

By-products - report # Text405: Rows – Industry Columns – Commodity Value – the commodity composition of each industry’s total output (coefficient – row sum equals 1.0).

Market Shares

- report # Text406

:

Rows – Industry Columns – Commodity Value – the portion of the region’s total supply of each commodity produced by a given industry or institution (coefficient – column sum equals 1.0).

Appendix F: Sample Reports

375

Industry-by-Industry Reports Institution Industry Demand - report # II030: (otherwise known as final demands) all purchases are from industries or institutions (industry basis) and is net of imports.

Households: purchase from industries by individuals for personal use. This is a summation for all categories of household income. Also known as PCE –i.e., Personal Consumption Expenditures. Federal Gov: purchase from industries by all categories of Federal government. State & Local: purchase from industries by all categories of State and Local governments. Capital: purchase from industries for investment purposes by private entities. Inventory: additions to inventory, also known as “involuntary investment”. Foreign Exports: shipment from industries to destinations outside of the U.S.

376

Appendix F: Sample Reports

Household Industry Demand - report # II031: contains detail of the household final demand (PCE) summarized in the Institution Industry Demand Report. It represents purchases from industries or institutions (industry basis) by individuals for personal use, and are net of imports. The 9 categories of households (1996 to 1999) are based on total annual household income as described by the column headers. For 1995 and earlier data sets the three categories are: 1992-1995

1977-1991

Low

$0-20,000

$0-15,000

Med

$20,000-50,000

$15,000-30,000

High

$50,000+

$30,000

Appendix F: Sample Reports

377

Government Industry Demand - report # II032: contains detail of the administrative government purchases from industries or institutions (industry basis) and are net of imports.

Non-Defense Federal Government Expenditures: purchase from industries by Federal agencies other than defense agencies. Defense Federal Government Expenditures: purchase from industries by Federal defense agencies. Investment Federal Government Expenditures: capital goods expenditures by all Federal agencies. This category only exists in 1996 and later data sets. Before 1996 investment was part of the defense and non-defense expenditures. Non-education State and Local Government Expenditures: purchase from industries by non-educational state and local government agencies. Education State and Local Government Expenditures: purchase from industries by educational (primary, secondary and higher-ed) state and local government agencies.

378

Appendix F: Sample Reports

Investment State and Local Government Expenditures: capital goods expenditures by all state and local government agencies. This category only exists in 1996 and later data sets. Before 1996 investment was part of the education and non-education expenditures.

Appendix F: Sample Reports

379

Industry Output/Outlay Summary- report # II050:

Total Outlay: distribution of all income by industry. It is the sum of intermediate outlay plus total value added plus imports. It is also equal to total industry output. Intermediate Outlay: payment by industry for all goods and services produced by local industries. Institutional Outlay: payment by industry for all goods and services produced by local institutions (non industy sectors). Value Added: value added during production to all purchased intermediate goods and services. It is the sum of employee compensation plus proprietor’s income plus other property income plus indirect business taxes. Imports: imports of all commodities by the given industry from all sources, foreign and domestic. It is the sum of intermediate outputs plus final demands. Total Output: total production by the given industry for the year of data. Intermediate Output: sales by industries to all other local industries. Final Demand: sales by industries to all local institutions and exports.

380

Appendix F: Sample Reports

Aggregate IxI SAM (Aggregated Industries, Aggregated Rows) - report # II060: Industries are aggregated to a single sector and institutions are limited to the same categories as the columns. Values are in millions of dollars.

The following four IxI reports print only a text files as a series of records with Three fields (columns).

Industry Import Matrix - report # Text506: total, competitive and non-competitive commodity imports by each industry. Rows: Industry products being imported Cols: Industry purchasing imported products Value: Total value of import

Institution Import Matrix - report # Text507: total, competitive and non-competitive commodity imports by each institution. Rows: Industry products being imported Cols: Institution purchasing imported commodity (see appendix d for type codes) Value: Total value of import

Appendix F: Sample Reports

381

Regional IxI Direct Coefficients - report # Text501: Rows: Producing Industry Cols: Purchasing Industry Value: A-matrix coefficient

Regional IxI Transactions - report # Text502: Rows: Producing Industry Cols: Purchasing Industry Value: Transaction in millions of dollars The following two IxI SAM print only a text files as a series of records with many fields (columns) representing a complete SAM.

Ind x Ind SAM (Aggregated Industries, Row Detail) - report # Text503 Industries are aggregated to a single sector. The institution rows are as detailed as IMPLAN allows. This gives more detail for indirect business taxes and government receipts. Values are in millions of dollars.

Ind x Ind SAM (Industry Detail, Aggregated Rows) - report # Text504: Complete industry detail, therefore if this report is to pulled into Excel it is necessary to aggregate the model to less than 225. Excel has a limit to the number of colums (for a pivot table) of 254. The institution rows are aggregated. Values are in millions of dollars.

Ind x Ind SAM (Industry Detail, Row Detail) - report # Text505: Complete industry detail, therefore if this report is to pulled into Excel it is necessary to aggregate the model to less than 225. Excel has a limit to the number of colums (for a pivot table) of 254. The institution rows are as detailed as IMPLAN allows. This gives more detail for indirect business taxes and government receipts. Values are in millions of dollars.

382

Appendix F: Sample Reports

Multiplier Reports Output Multipliers - report # MR010:

Direct: direct change in output (millions of dollars) per million dollar change in final demand. Indirect: indirect change in output (millions of dollars) per million dollar change in final demand resulting from interaction of local industries purchasing from local industries. Induced: induced change in output (millions of dollars) per million dollar change in final demand resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects. Type I: direct plus indirect divided by the direct effect. Type II or Type SAM: direct plus indirect plus induced divided by the direct effect.

Appendix F: Sample Reports

383

Employment Multipliers - report # MR020:

Direct: direct change in employment (jobs) per million dollar change in final demand. Indirect: indirect change in employment (jobs) per million dollar change in final demand resulting from interaction of local industries purchasing from local industries. Induced: induced change in employment (jobs) per million dollar change in final demand resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects. Type I: direct plus indirect divided by the direct effect. Type II or Type SAM: direct plus indirect plus induced divided by the direct effect.

384

Appendix F: Sample Reports

Labor Income Multipliers - report # MR030:

These multipliers are based on employee compensation plus proprietor income. In IMPLAN Pro 1.1 and in the DOS software this was known as personal income. Direct: direct change in labor income (millions of dollars) per million dollar change in final demand. Indirect: indirect change in labor income (millions of dollars) per million dollar change in final demand resulting from interaction of local industries purchasing from local industries. Induced: induced change in labor income (millions of dollars) per million dollar change in final demand resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects. Type I: direct plus indirect divided by the direct effect. Type II or Type SAM: direct plus indirect plus induced divided by the direct effect.

Appendix F: Sample Reports

Value Added Multipliers

- report # MR040

385

:

Direct: direct change in value added (millions of dollars) per million dollar change in final demand. Indirect: indirect change in value added (millions of dollars) per million dollar change in final demand resulting from interaction of local industries purchasing from local industries. Induced: induced change in value added (millions of dollars) per million dollar change in final demand resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects. Type I: direct plus indirect divided by the direct effect. Type II or Type SAM: direct plus indirect plus induced divided by the direct effect.

386

Appendix F: Sample Reports

Employee Compensation Multipliers - report # MR050:

Direct: direct change in employee compensation (millions of dollars) per million dollar change in final demand. Indirect: indirect change in employee compensation (millions of dollars) per million dollar change in final demand resulting from interaction of local industries purchasing from local industries. Induced: induced change in employee compensation (millions of dollars) per million dollar change in final demand resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects. Type I: direct plus indirect divided by the direct effect. Type II or Type SAM: direct plus indirect plus induced divided by the direct effect.

Appendix F: Sample Reports

387

Proprietors’ Income Multipliers - report # MR060:

Direct: direct change in proprietor’s income (millions of dollars) per million dollar change in final demand. Indirect: indirect change in proprietor’s income (millions of dollars) per million dollar change in final demand resulting from interaction of local industries purchasing from local industries. Induced: induced change in proprietor’s income (millions of dollars) per million dollar change in final demand resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects. Type I: direct plus indirect divided by the direct effect. Type II or Type SAM: direct plus indirect plus induced divided by the direct effect.

388

Appendix F: Sample Reports

Other Property Type Income Multipliers - report # MR070:

Direct: direct change in other property type income (millions of dollars) per million dollar change in final demand. Indirect: indirect change in other property type income (millions of dollars) per million dollar change in final demand resulting from interaction of local industries purchasing from local industries. Induced: induced change in other property type income (millions of dollars) per million dollar change in final demand resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects. Type I: direct plus indirect divided by the direct effect. Type II or Type SAM: direct plus indirect plus induced divided by the direct effect.

Appendix F: Sample Reports

389

Indirect Business Taxes Multipliers - report # MR080:

Direct: direct change in indirect business taxes (millions of dollars) per million dollar change in final demand. Indirect: indirect change in indirect business taxes (millions of dollars) per million dollar change in final demand resulting from interaction of local industries purchasing from local industries. Induced: induced change in indirect business taxes (millions of dollars) per million dollar change in final demand resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects. Type I: direct plus indirect divided by the direct effect. Type II or Type SAM: direct plus indirect plus induced divided by the direct effect. The following 2 reports are available only in text form and are in the following format: “Rows, Columns, Value”

Type I Multipliers

- report # Text601

:

Rows: Industry Columns: Industry Value: multiplier representing interactive effects of industries buying from industries

Induced Multipliers: - report # Text602: Rows: Industry

390

Appendix F: Sample Reports

Columns: Industry Value: multiplier representing additional interactive effects institutions – traditionally it includes the additional effects of households.

Appendix F: Sample Reports

391

Impacts Reports Output

- report #IM010

:

Direct: direct change in output (millions of dollars) per change in final demand specified by the user’s scenario. Indirect: indirect change in output (millions of dollars) ) per change in final demand specified by the user’s scenario, resulting from interaction of local industries purchasing from local industries. Induced: induced change in output (millions of dollars) per change in final demand specified by the user’s scenario, resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects.

392 Appendix F: Sample Reports

Employment - report #IM020:

Direct: direct change in employment (jobs) ) per change in final demand specified by the user’s scenario. Indirect: indirect change in employment (jobs) ) per change in final demand specified by the user’s scenario, resulting from interaction of local industries purchasing from local industries. Induced: induced change in employment (jobs) per change in final demand specified by the user’s scenario, resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects.

Appendix F: Sample Reports

Labor Income - report #IM030: These multipliers are based on employee compensation plus proprietor income. In IMPLAN Pro 1.1 and in the DOS software this was known as personal income.

Direct: direct change in labor income (millions of dollars) per change in final demand specified by the user’s scenario. Indirect: indirect change in labor income (millions of dollars) ) per change in final demand specified by the user’s scenario, resulting from interaction of local industries purchasing from local industries. Induced: induced change in labor income (millions of dollars) per change in final demand specified by the user’s scenario, resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects.

393

394 Appendix F: Sample Reports

Total Value-Added - report #IM040:

Direct: direct change in total value added (millions of dollars) per change in final demand specified by the user’s scenario. Indirect: indirect change in total value added (millions of dollars) ) per change in final demand specified by the user’s scenario, resulting from interaction of local industries purchasing from local industries. Induced: induced change in total value added (millions of dollars) per change in final demand specified by the user’s scenario, resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects.

Appendix F: Sample Reports

395

Employee Compensation - report #IM050:

Direct: direct change in employee compensation (millions of dollars) per change in final demand specified by the user’s scenario. Indirect: indirect change in employee compensation (millions of dollars) ) per change in final demand specified by the user’s scenario, resulting from interaction of local industries purchasing from local industries. Induced: induced change in employee compensation (millions of dollars) per change in final demand specified by the user’s scenario, resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects.

396 Appendix F: Sample Reports

Proprietors’ Income - report #IM060:

Direct: direct change in proprietor’s income (millions of dollars) per change in final demand specified by the user’s scenario. Indirect: indirect change in proprietor’s income (millions of dollars) ) per change in final demand specified by the user’s scenario, resulting from interaction of local industries purchasing from local industries. Induced: induced change in proprietor’s income (millions of dollars) per change in final demand specified by the user’s scenario, resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects.

Appendix F: Sample Reports

397

Other Property Type Income - report #IM070:

Direct: direct change in other property type income (millions of dollars) per change in final demand specified by the user’s scenario. Indirect: indirect change in other property type income (millions of dollars) ) per change in final demand specified by the user’s scenario, resulting from interaction of local industries purchasing from local industries. Induced: induced change in other property type income (millions of dollars) per change in final demand specified by the user’s scenario, resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects.

398 Appendix F: Sample Reports

Indirect Business Tax - report #IM080:

Direct: direct change in indirect business tax (millions of dollars) per change in final demand specified by the user’s scenario. Indirect: indirect change in indirect business tax (millions of dollars) ) per change in final demand specified by the user’s scenario, resulting from interaction of local industries purchasing from local industries. Induced: induced change in indirect business tax (millions of dollars) per change in final demand specified by the user’s scenario, resulting from interaction of institutions – usually associated with additional effects of households. Total: sum of direct, indirect and induced effects.

Appendix F: Sample Reports

399

Project Impact Description - report #IM091: This report describes the current values associated with the groups and events combined to create the chosen project. This report needs to be created at the time the impact analysis is run in order to capture the values directly associated with that impact run.

400 Appendix F: Sample Reports

Group Impact Description - report #IM092: This report describes the current values associated with the events combined to create the chosen group. This report needs to be created at the time the impact analysis is run in order to capture the values directly associated with that impact run.

Appendix F: Sample Reports

401

Tax Impacts - report #IM100: This report describes taxes related to the chosen impact analysis. These estimates are based strictly on the same data underlying the region SAM data. These values are based on the average for all industries within the model; the average taxes associated with each household income class; the average taxes and transfers associated with each of the government institutions defined by the model.

Appendix G: Text Files 403

A P P E N D I X

G

Exporting/Importing Text Files Version 2.0 allows you to export and import groups of events and RPCs. Importing must be done carefully since any deviation from the Excel template included on your software CDROM will cause the data to not import correctly. This feature will be useful if you have a large number of changes you want to make to a group of events or RPCs or you want to build your groups in a spreadsheet instead of the IMPLAN Pro software.

Exporting Impact Groups of Events: 1. From the Impact Screen select the Groups/Events tab, click on Import/Export on the main menu bar. Click on Export and then Group to Text File. 2. Click on the group you want to export, then click Export. A dialog box will be displayed allowing you to give your export file a name. Give it a name that will remind of the group’s contents, then click Save. 3. The file will be comma separated and will import easily into Excel. You will need to select Comma as the field separator.

Importing Impact Groups of Events: 1. Build a model through multipliers. 2. Open the “Import CSV-Group Import Template.xls” in Excel. This template has all information necessary to create the import file. There are example records in the template. Before changing this template, SAVE IT UNDER A DIFFERENT NAME. You can enter your information in the template. 3. If you have margins, you can specify all information including the margin value, margin deflator, and margin local purchases proportion (formerly LPC). If you want margins but don’t know what the margin value, deflator or LPC is, then simply leave the margin value as zero, the margin deflator as one, and the margin local purchases as zero and they will be filled in when imported. 4. IT IS VERY IMPORTANT THAT YOU DO NOT HAVE COMMAS IN THE VALUE FIELD. THE FILE WILL NOT IMPORT CORRECTLY WITH ANY FORMATING IN THE VALUE FIELD.

404

Appendix G: Text Files

5. After you’ve entered information into your Excel template, save the template.. Then do a File/Save As and select Comma Separated Value (CSV) from the Save As Type drop down box. Click Ok when it tells you that it cannot save multiple sheets. 6. Back to the IMPLAN Pro software and from the Impacts screen, click Import. Select Text File. Select your carefully crafted file and click Open. Your file should import. 7. If it doesn’t, go back to your spreadsheet and make sure the data is correctly formatted. 8. Be careful not to leave any extraneous lines at the end of the import sheet as the software will try to import this.

Appendix G: Text Files 405

Exporting Regional Purchase Coefficients You can save your model’s RPCs. You might use this if you have made significant changes to your model’s RPCs and you want to build a new model with similar trade flow calculations. 1. Click the Edit button from the Model Control Center. Click on Regional Purchase Coefficients. 2. From the RPC edit screen, click Edit on the main menu. You the click Export Text File RPCs. 3. Give it a name, the default is “TEXT RPC (St Joseph IN.iap).csv”. Click Save.

Importing Regional Purchase Coefficients 1. Once the model is built through social accounts, you can import new RPCs into your model. 2. Open the “Import CSV-RPC Import Template.xls” in Excel. This template has all information necessary to create the import file and contains example records. Before changing this template, SAVE IT UNDER A DIFFERENT NAME. You can enter your information in the template. 3. Edit the template to add your own RPCs. 4. After you’ve entered your information into your Excel template, save the template you’ve created. Then do a File/Save As and select Comma Separated Value (CSV) from the Save As Type drop down box. Click OK when it tells you that it cannot save multiple sheets. 5. Go back to IMPLAN Pro. 4. Click the Edit button from the Model Control Center. Click on Regional Purchase Coefficients. 6. Click on Edit from the menu. Then click on Import Text file RPCs. Select the file you saved. This will import the new RPCs. HOWEVER, IT WILL STILL TEST YOUR NEW RPCs AGAINST THE S/D POOLING RATIO! You can allow it to exceed, but your model might be unbalanced. 7. You will then need to rerun the model from the RPC point on.

Appendix H: Construction 407

A P P E N D I X

H

IMPLAN Construction to Census IMPLAN Sector Name

Census Short Description

33 New residential 1-unit structures, nonfarm

Single-family houses

34 New multifamily housing structures, nonfarm

All other residential buildings

34 New multifamily housing structures, nonfarm

Apartment buildings, condos, & coops

35 New residential additions and alterations, nonfarm

Apartment buildings, condos, & coops

35 New residential additions and alterations, nonfarm

Single-family houses

36 New farm housing units and additions and alterations

Single-family houses

37 Manufacturing and industrial buildings

Mfg & light industrial buildings

37 Manufacturing and industrial buildings

Mfg & light industrial warehouses

38 Commercial and institutional buildings

All other commercial buildings

38 Commercial and institutional buildings

Amusement, social, & rec buildings

38 Commercial and institutional buildings

Commercial warehouses

38 Commercial and institutional buildings

Educational buildings

38 Commercial and institutional buildings

Farm buildings, nonresidential

38 Commercial and institutional buildings

Health care & institutional buildings

38 Commercial and institutional buildings

Hotels & motels

38 Commercial and institutional buildings

Office buildings

38 Commercial and institutional buildings

Other building construction

38 Commercial and institutional buildings

Public safety buildings

38 Commercial and institutional buildings

Religious buildings

39 Highway, street, bridge, and tunnel construction

Airport runways & related work

39 Highway, street, bridge, and tunnel construction

Bridges, tunnels, & elevated highways

39 Highway, street, bridge, and tunnel construction

Highways, streets, & related work

39 Highway, street, bridge, and tunnel construction

Private driveways & parking areas

40 Water, sewer, and pipeline construction

Sewers, water mains, & related fac

41 Other new construction

Billboards

41 Other new construction

Blast furnaces, petrol ref, chem comp

41 Other new construction

Conservation & development construction

41 Other new construction

Dam & reservoir construction

41 Other new construction

Dry/solid waste disposal

41 Other new construction

Fencing

41 Other new construction

Harbor & port facilities

41 Other new construction

Heavy military construction

41 Other new construction

Marine construction

41 Other new construction

Mass transit construction

408

Appendix H: Construction IMPLAN Sector Name

Census Short Description

41 Other new construction

Oilfields

41 Other new construction

Other nonbuilding construction

41 Other new construction

Outdoor swimming pools

41 Other new construction

Pipeline constr other than sewer & water

41 Other new construction

Power & communication trans lines

41 Other new construction

Power plants

41 Other new construction

Recreational facilities

41 Other new construction

Sewage & water treatment plants

41 Other new construction

Ships

41 Other new construction

Tank storage facilities other than water

41 Other new construction

Water storage facilities

42 Maintenance and repair of farm and nonfarm residential structures 42 Maintenance and repair of farm and nonfarm residential structures 43 Maintenance and repair of nonresidential buildings

Apartment buildings, condos, & coops

43 Maintenance and repair of nonresidential buildings

Amusement, social, & rec buildings

43 Maintenance and repair of nonresidential buildings

Commercial warehouses

43 Maintenance and repair of nonresidential buildings

Educational buildings

43 Maintenance and repair of nonresidential buildings

Farm buildings, nonresidential

43 Maintenance and repair of nonresidential buildings

Health care & institutional buildings

Single-family houses All other commercial buildings

43 Maintenance and repair of nonresidential buildings

Hotels & motels

43 Maintenance and repair of nonresidential buildings

Mfg & light industrial buildings

43 Maintenance and repair of nonresidential buildings

Mfg & light industrial warehouses

43 Maintenance and repair of nonresidential buildings

Office buildings

43 Maintenance and repair of nonresidential buildings

Other building construction

43 Maintenance and repair of nonresidential buildings

Public safety buildings

43 Maintenance and repair of nonresidential buildings

Religious buildings

44 Maintenance and repair of highways, streets, bridges, and tunnels 44 Maintenance and repair of highways, streets, bridges, and tunnels 44 Maintenance and repair of highways, streets, bridges, and tunnels 44 Maintenance and repair of highways, streets, bridges, and tunnels 44 Maintenance and repair of highways, streets, bridges, and tunnels 45 Other maintenance and repair construction

Airport runways & related work

Billboards

45 Other maintenance and repair construction

Blast furnaces, petrol ref, chem comp

Bridges, tunnels, & elevated highways Highways, streets, & related work Private driveways & parking areas Sewers, water mains, & related fac

45 Other maintenance and repair construction

Conservation & development construction

45 Other maintenance and repair construction

Dam & reservoir construction

45 Other maintenance and repair construction

Dry/solid waste disposal

45 Other maintenance and repair construction

Fencing

Appendix H: Construction 409 IMPLAN Sector Name

Census Short Description

45 Other maintenance and repair construction

Harbor & port facilities

45 Other maintenance and repair construction

Heavy military construction

45 Other maintenance and repair construction

Marine construction

45 Other maintenance and repair construction

Mass transit construction

45 Other maintenance and repair construction

Oilfields

45 Other maintenance and repair construction

Other nonbuilding construction

45 Other maintenance and repair construction

Outdoor swimming pools

45 Other maintenance and repair construction

Pipeline constr other than sewer & water

45 Other maintenance and repair construction

Power & communication trans lines

45 Other maintenance and repair construction

Power plants

45 Other maintenance and repair construction

Recreational facilities

45 Other maintenance and repair construction

Sewage & water treatment plants

45 Other maintenance and repair construction

Ships

45 Other maintenance and repair construction

Tank storage facilities other than water

45 Other maintenance and repair construction

Water storage facilities

Index

411

Index %Local ..............................................................53 1977 Multi-Regional Input-Output Accounts.....275

A A Matrix ..........................................................101 About IMPLAN Professional..............................84 Absorption matrix ............................................271 Absorption table.................................................99 Advanced Byproducts.........................................39 Advanced Institutional Transfers.........................42 Advanced Model Building ..................................37 Advanced Multipliers .........................................43 Advanced Production Function ...........................39 Advanced Trade Flows .......................................40 Aggregation ................................................. 32, 80 Aggregation Error ............................................182 Agriculture.......................................................235

B Backward linkage.............................................116 Balancing.............................................24,153, 269 Basis..................................................................50 Benchmark I/O study........................................271 Benchmark Input-Output Study.........................228 Byproducts Library.............................................29 Byproducts Matrix........................... 18, 98, 99, 271

Commodity-Table View .....................................30 Compacting Models............................................87 Constant returns to scale ...................................103 Construct Model.................................................12 Construction.....................................................237 Converting Models .............................................86 County Business Patterns..................................232 Creating a model ................................................. 8 Creating Groups .................................................56 Crosshauling ....................................................185 Current Model ....................................................90 Customizing .......................................................17

D Database Validation..........................................277 Default Directories .............................................89 Default model directory ....................................... 9 Default Toolbar ..................................................84 Deflator Button...................................................80 Deflators ..............................18, 105, 111, 124, 274 Deleting Groups .................................................57 Descriptive model...............................................14 Descriptive Model ........................................14, 96 Direct effects....................................................102 Direct Effects .....................................................81 Domestic commodity exports............................148 Domestic services.............................................230

E C Calculator ..........................................................88 Capital .............................................................258 Capital Formation.............................................129 CEW................................................................233 CGE Modeling .................................................154 Change All................................................... 50, 51 Choosing a Sector...............................................90 Commodity ........................................................98 Commodity by Industry......................................31 Commodity Detail ..............................................30

Edit ....................................................................12 Edit Commodity Sales ........................................20 Editing a Production Function.............................27 Editing Region Data ...........................................19 Employee compensation ........................... 125, 249 Employment............................................. 125, 231 Employment multiplier .....................................173 Enterprises .......................................................150 ES-202 .............................................................233 e-Update.............................................................85 Event Defaults....................................................54 Event Name........................................................48

412

Index

Event Options ....................................................55 Events................................................................48 Example Analysis.............................................177 Expenditure value...............................................49

F Factor Distribution ...........................................151 Factor Exports..................................................151 Factor Imports..................................................151 Federal Government .........................................239 Federal Government purchases .........................257 Federal Government Sales ................................128 Federal Military Purchases................................128 Federal Non-military Purchases ........................128 Final demand table .............................................99 FIPS.................................................................120 Fixed field..........................................................23 Foreign Export edit screen ..................................20 Foreign Exports........................................ 129, 258 Forest products.................................................229 Forward linkage ...............................................117 Full time equivalents ........................................246 Functional economic area .................................115

IMPLAN Sectoring...........................................229 Importing Groups ...............................................57 Importing/Exporting Groups ...............................59 Income multipliers............................................172 Indirect business taxes .............................. 126, 249 Indirect effects....................................................97 Indirect effects..................................................102 Indirect Effects ...................................................81 induced effects ...................................................97 Induced effects .................................................102 Induced Effects........................................... 81, 185 Industry..............................................................98 Industry output .................................................125 Industry x Industry Reports.................................76 Input-output analysis ..........................................95 Institution demand ............................................257 Institution Exports ............................................151 Inter-Institutional Transfers................149, 151, 263 Internet Connectivity ..........................................84 Inventory purchases..........................................257 Inventory Purchases..........................................128 Inventory Sales.................................................129 Inventory valuation adjustment .........................230 IxI....................................................................161

L G Government Investment....................................128 Gross regional commodity demand ........... 139, 142 Groups ...............................................................55 Groups/Events Analysis......................................61

H Help System.......................................................83 Household consumption ...................................127 Household consumption expenditures ...............257

I Impact analysis......................................... 104, 175 IMPACT Analysis..............................................47 Impact Reports ...................................................79 Impacts ..............................................................12

Labor market areas ...........................................120 Leakage...................................................... 97, 118 Leontief inverse.......................................... 97, 102 Library Maintenance...........................................61 Local Expenditures...........................................112 Local Purchase Coefficients................................53 Location Quotients ................................... 101, 143 LPC ...................................................................53

M Main menu .......................................................... 7 Make..................................................................99 make matrix .....................................................271 Margin types ......................................................24 Margins................................. 18, 52, 105, 109, 124 MARGINS .......................................................273 Market shares assumption .................................160 Market shares matrix .................................. 99, 271 Memo Field........................................................88

Index Metropolitan Statistical Areas ...........................120 Model Control Center.........................................12 Model status.......................................................14 Modifying Byproducts........................................29 Modifying Deflators ...........................................22 Modifying Margins.............................................23 Modifying Production Functions.........................24 Modifying Trade Flows ......................................30 Multiple Models.................................................90 Multiplier Reports ..............................................78 Multipliers ............................................18, 96, 101

N National absorption ..........................................123 National byproducts..........................................124 National Value Added Estimates.......................250 Net Commodity Supply ....................................134 New Model ..........................................................8 Non-comparable imports ..................................230 Non-disclosure rules.........................................231 Non-education Purchase ...................................128

413

Proprietary income ................................... 125, 249 Public Education Purchases...............................128 Purchaser prices................................................104

R Recent Models..................................................... 9 Region Data .......................................................17 Regional byproducts .........................................135 Regional commodity imports ............................146 Regional Economic Information System............228 regional market shares ......................................136 Regional Purchase Coefficients ......................................... 18, 41, 100, 142, 274 Regional Purchase Coefficients Library...............32 REIS ................................................................240 Reports................................................... 12, 67, 68 Rest-of-world ...................................................230 Results ...............................................................62 Retrieving a Production Function ........................27

S O Open Existing Model............................................8 Other property type income....................... 126, 249 Owner occupied dwellings” ..............................229

P PCE .................................................................258 PCE activity database .......................................181 Personal Consumption Expenditures .................258 Predictive model...................... 14, 15, 96, 102, 166 Preview Model Information ..................................9 Primary commodity............................................98 Primary input-output ..........................................95 Print Options......................................................68 Producer prices.................................................104 Production Function Changes ...........................181 Production Function Library ...............................25 Production functions............................18, 101, 124 Project definition.............................................. 107 Projects..............................................................63

SAM Framework..............................................150 SAM Income ......................................................44 SAM Reports......................................................74 SAMs...............................................................263 Save Production Function ...................................26 Scrap................................................................230 Search on Help ...................................................84 Secondary commodities ......................................98 Secondary input-output.......................................96 Sector selection ..................................................48 Sectoring Schemes............................................227 Social Accounting ..............................................96 Social Accounts Reports .....................................72 Specific Disposable Income (%)..........................45 Standard Industrial Classification ......................228 State & Local Government................................237 State and local government purchases................257 State and Local Government Sales ....................128 State and local Investment.................................128 Structural matrices............................................271 Structural Matrices Version.................................87 Structural Matrix Reports....................................75 Study Area Reports.............................................70 Supply/Demand Pooling .............. 41, 100, 141, 142

414

Index

T

Used and second hand goods.............................230

T-Accounts ........................................................97 Tax Analysis ....................................................154 TIO..................................................................253 Tool Bar.............................................................90 Total ..................................................................81 Total Industry Output .......................................253 total regional commodity supply .......................135 Tourism expenditure.........................................181 Trade Flows ............................................... 96, 100 Transactions table.............................................164 Type I ................................................................15 Type I multiplier ..............................................102 Type II...............................................................15 Type II multiplier ..................................... 102, 169 Type SAM .........................................................15 Type SAM multiplier........................................103 Type SAM Multipliers......................................171

V Value Added ....................................................249 Value Added Multipliers...................................172 Value added table ...............................................99 View Project Results...........................................65 View the study area data .....................................21

Y Year...................................................................50

Z ZIP code based study area.................................118

U Use matrix ..........................................99, 271, 272