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Development industry cluster in Tampa Bay

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Title:
Development industry cluster in Tampa Bay
Physical Description:
1 online resource (ii, 64 p.) : ;
Language:
English
Creator:
University of South Florida -- Center for Economic Development Research
Publisher:
Center for Economic Development Research
Place of Publication:
Tampa, Fla
Publication Date:

Subjects

Subjects / Keywords:
Industrial clusters -- Florida -- Hillsborough County   ( lcsh )
Economic conditions -- Tampa Bay Region (Fla.)   ( lcsh )
Economic conditions -- Hillsborough County (Fla.)   ( lcsh )
Genre:
bibliography   ( marcgt )
non-fiction   ( marcgt )

Notes

Abstract:
Commissioned by the Tampa Bay Regional Water Coalition, this report analyzes the development industry cluster in the Tampa Bay region to determine the levels of activity and potential alternatives for employment by workers in this industry should it be curtailed.
Bibliography:
Includes bibliographical references.
Statement of Responsibility:
an analysis performed by Center for Economic Development Research, College of Business Administration, University of South Florida.
General Note:
Title from PDF of cover (viewed Aug. 12, 2009).
General Note:
"May 2002."

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University of South Florida Library
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University of South Florida
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
aleph - 002023611
oclc - 430191304
usfldc doi - C63-00018
usfldc handle - c63.18
System ID:
SFS0000296:00001


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Development Industry Cluster in Tampa Bay An Analysis Performed by CENTER FOR ECONOMIC DEVELOPMENT RESEARCH College of Business Administration1101 Channelside Dr., 2nd Floor N., Tampa, Florida 33602 Office: (813) 905-5854 or Fax: (813) 905-5856May, 2002

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Preface The Tampa Bay Regional Water Coalition is a trade association of land development, construction, building materials and related businesses. The Coalition commissioned the Center for Economic Development Research (CEDR), College of Business Administration, University of South Florida, to conduct a four-part study of the development industry cluster in Tampa Bay. This document is a final report of a four-part study. The purpose of the study is to analyze the development industry cluster in Tampa Bay to determine the levels of activity and potential alternatives for employment by workers in this industry should it be curtailed. CEDR provides information and conducts research on issues related to economic growth and development in the Nation, in the state of Florida, and particularly in the central Florida region. The Center serves the faculty, staff, and students of the College of Business Administration, the University, and individuals and organizations in the University’s service area. CEDR’s activities are designed to further the objectives of the University and specifically the objectives of the College of Business Administration Robert Anderson, Dean, College of Business Administration (COBA), USF Kenneth Wieand, Director, Center for Economic Development Research (CEDR), COBA, USF Dennis G. Colie, Economist and Principal Investigator, CEDR, COBA, USF Alexander A. McPherson, Research Associate, CEDR, COBA, USF Carol Wallace, Information Technology Specialist, CEDR, COBA, USF

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i TABLE OF CONTENTSEXECUTIVE SUMMARY.............................................................................................................. ..........................II SECTION 1: INTRODUCTION........................................................................................................ .......................1 SECTION 2: AN OPERATIONAL DEFINITION OF THE DEVELOPMENT INDUSTRY CLUSTER.........3 SECTION 3: BASELINE CONTRIBUTIONS OF THE PRIMARY INDUSTRIES...........................................9 SECTION 4: EMPLOYMENT STRUCTURE OF THE PRIMARY INDUSTRIES.........................................21 SECTION 5: ECONOMIC CONTRIBUTION OF THE DEVELOPMENT INDUSTRY CLUSTER.............32 SECTION 6: ECONOMIC IMPACTS OF A SLOWDOWN IN DEVELOPMENT..........................................37 APPENDIX A..................................................................................................................... .......................................51 PRIMARY INDUSTRIES INCLUDE REAL ESTATE AGENTS AND MANAGERS.....................................51 APPENDIX B..................................................................................................................... .......................................58 EMPLOYMENT STRUCTURE INCLUDING REAL ESTATE AGENTS AND MANAGERS......................58 APPENDIX C..................................................................................................................... .......................................62 DIFFERENCE IN EMPLOYMENT BY OCCUPATION....................................................................................62

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ii Executive Summary The purpose of this study is to examine the economic impacts, such as loss of jobs, on Tampa Bay’s economy, if there were a sharp reduction of development activity in the region. We begin the study by defining the Development Industry cluster in Tampa Bay. We select potential primary industries and use the IMPLANTM input-output economic model to measure the “magnitude of clustering” in the sense that the primary industries would tend to have the same supplierindustries. We conclude that the five construction major industry groups and a portion of the Real Estate sector form the primary industries of the Development Industry cluster by virtue of commonality of supplier industries. The five construction industry groups are 1) residential construction, 2) industrial / commercial construction, 3) utility construction, 4) highway construction and 5) construction of government facilities. The Real Estate industries included among the primary industries are Nonresidential Building Operators and Subdividers and Developers. These construction and real estate industries exhibit strong supplier-linkages with other industries in Tampa Bay to form the Development Industry cluster. The top five Tier 1 supplier industries or industry groups in the cluster are 1) engineering – architectural services, 2) wholesale trade, 3) management and consulting services, 4) motor freight transport and warehousing and 5) other business services. Next, using the REMITM economic policy-insight model, we estimate the baseline economic contributions of the primary industries of the Development Industry cluster. We find that over 156,000, or about 7.3%, of the jobs in Tampa Bay are in the primary industries of the cluster. And, the firms in these primary industries produce more than $16 billion annually or 10.25% of regional economic activity. We also use Covered Employment and Wages (ES-202) data for 2nd quarter, 2001 (most recent available) to provide a jobs-based perspective of the primary industries of the Development Industry cluster in Tampa Bay. The data are organized by Standard Industrial Classification (SIC) codes. We find that the 2,537 Tampa Bay firms in the General Building Contractors (SIC 15) group employ 14,898 workers. The majority (78%) of these workers receives an annualized wage between $35,000 and $60,000. The 455 Tampa Bay firms in the Heavy Construction (SIC 16) group employ 13,224 workers. The majority (51%) of these workers receives an annualized wage between $35,000 and $60,000. The 6,463 firms in the Special Trade Contractors (SIC 17) group employ 58,852 workers. The majority (91%) of these workers receives annualized wages of less than $35,000. The 422 Tampa Bay firms in the Operators of Nonresidential Buildings (SIC 6512) industry and in the Land Subdividers & Developers (SIC 6552) industry employ 3,034 workers. Employers were paying annualized wages of less than $35,000 to 69% of these workers. By comparing 1999 ES-202 data with another source, the U.S. Commerce Department’s 1999 (most recent available) Regional Economic Information System data series, we are able to conclude that approximately 29.6% of persons working in construction in Tampa Bay were sole proprietors. Sole proprietors are not included in ES-202 data. Assuming that the percentage has remained stable, we estimate that about 37,295 sole proprietors are working in construction in Tampa Bay in 2002.

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iii We assess the economic contribution of the Development Industry cluster using the traditional counter-factual approach. With this approach, we use the REMITM model to remove the actual output produced by the primary industries of the cluster. The model tabulates the direct effects of the removal of the primary economic activities as well as the ripple, or secondary, effects throughout the Tampa Bay economy. We find that the Development Industry cluster contributes approximately 275,500 jobs, or 12.9% of total employment, to the Tampa Bay region. As measured by output, the cluster contributes about $27 billion of economic activity, or 16.5% of total output, to the region. And, the cluster is responsible for the generation of approximately $10.6 billion of personal income, or 15.1% of labor and property income, for the workers and owners of capital in Tampa Bay. While the counter-factual approach provides a way to derive a valid assessment of the economic contribution of the Development Industry cluster, it does not portray a realistic scenario of a slowdown in regional development. The counter-factual approach simulates a complete cessation of the productive activities of the cluster’s primary industries. This is unlikely. Even if development were proscribed in some areas, economic principle tells us that substitute activities, such as remodeling or expansion of existing facilities, would occur. Therefore, rather than simulating a complete cessation, we gauge the regional economy’s expected response to a 20% slowdown in production by the primary industries of the Development Industry cluster. We measure the response by the aggregated primary and secondary impacts on employment, output and personal income. We estimate that the total impact on employment in the Tampa Bay region would be a loss of nearly 56,000 jobs or 2.6% of the employment base during the first year of a 20% slowdown. Five years after the start of the slowdown, Tampa Bay would still be 48,000 jobs below the baseline. We also estimate that the total impact on output in the Tampa Bay region would be a loss of nearly $5.5 billion of output or 3.3% of the output base during the first year of the slowdown. Five years later, annual output in Tampa Bay would still be almost $5.0 billion below the baseline. Additionally, the total impact on personal income would be a loss of over $2.2 billion or 3.2% of the personal income base during the first year. Five years after the start of the slowdown, annual personal income in Tampa Bay would still be almost 2.8% below the baseline. With the loss of nearly 56,000 jobs in the first year of the slowdown, Tampa Bay’s labor force also shrinks. We anticipate that in the first year the labor force would decline by about 11,000 workers. Furthermore, a 20% slowdown would have a significant impact on economic migration into the Tampa Bay region. In the first year of a slowdown approximately 11,800 fewer economic migrants (15.9% less in-migrants) will move into the Tampa Bay region than previously anticipated. Non-economic migrants, such as retired persons (age 65 or older), will be little affected by the slowdown. Although, about 40,000 people out-migrate from Tampa Bay each year, this number will increase by only a few hundred people each year as a result of a slowdown. In the first year of the slowdown, we estimate that Tampa Bay’s population would be about 11,950 persons less that if there were no slowdown. The reduction in population would almost entirely be due to a decline in the number of economic in-migrants.

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1 Section 1: Introduction The land development, construction, building materials, and associated industries are an integral part of Tampa Bay’s economy. As growth management issues continue to be publicly debated, these industries come under increasingly closer scrutiny. Officials often point out that growth seriously strains government’s ability to supply the infrastructure needed to support more people and businesses in the region. Consequently, some have gone as far as to suggest a moratorium on new growth. While a moratorium, or slowdown, on new developments in the region can reduce the demand for public–sector infrastructure, it could have a deleterious impact on the Tampa Bay economy. For instance, the construction industries in Tampa Bay currently employ about 5.9%, or 126,000, of the region’s workers. Even a small reduction in development activity, say 10%, can be expected to lead to the loss of 12,600 construction jobs. The purpose of this study is to examine the economic impacts, such as a loss of jobs, on Tampa Bay’s economy, if there were a sharp reduction of development activity in the region. We begin the study by defining the Development Industry cluster in Tampa Bay. We define the cluster by examining industries generally associated with development activity for commonality of supplier chains. We develop a “picture” of the cluster in terms of primary industries and supplier industries (indirect industries). The results of this analysis are reported In Section 2, An Operational Definition of the Development Industry Cluster. In Section 3, Baseline Contributions of the Primary Industries, we estimate the economic contributions of the primary industries of the Development Industry cluster. The principal measures of the baseline economic contributions are employment and output. These economic contributions provide the baseline from which we assess the economic contribution of the Development Industry cluster of Tampa Bay and the economic impacts of an interruption of development activity in the Tampa Bay region. In Section 4, Employment Structure of the Primary Industries we use the Bureau of Labor Statistics Covered Employment and Wages data to provide a jobs-based perspective of the primary industries in the Development Industry cluster in Tampa Bay. We compile and report the number of employees, average annualized wages, and the number of rims for each industry. Next, we assess the economic contribution of the Development Industry cluster using the traditional counter-factual approach. With this approach, we use the REMITM model to simulate removal of the baseline output produced by the primary industries of the cluster. The model tabulates the direct effects of the removal as well as the ripple, or secondary, effects throughout the Tampa Bay economy. Employment, output and personal income measure the economic contribution and are report in Section 5, Economic Contribution of the Development Industry Cluster In Section 6, Economic Impacts of a Slowdown in Development we gauge the regional economy’s expected response to a 20% slowdown in production by the primary

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2 industries of the Development Industry cluster in Tampa bay. As in Section 5, we aggregate the direct and secondary effects as measured by employment, output and personal income. Then we trace the impact of lost jobs by occupation, the impacts on the region’s labor force and population. We show that a slowdown significantly affects economic migration into Tampa Bay.

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3 Section 2: An Operational Definition of the Development Industry Cluster The purpose of this section is to describe the Development Industry cluster in Tampa Bay. Harvard economist, Michael Porter, in The Competitive Advantage of Nations (1990) and in On Competition (1998), develops a model in which competitive advantages are generated by the spatial concentration of firms in an industry as they interact with regional and national factors conducive to their profitability. As applied to a regional economy, Porter’s model relates the growth of a regional industry to regional infrastructure, to the spatial proximity of upstream industries that supply inputs into the production process, and to the proximity of downstream customers who purchase the industry’s products and services.1 Porter calls the grouping of an industry along with its upstream suppliers and downstream customers an industry cluster. In order to develop a picture of the Development Industry cluster in Tampa Bay, we start with selected primary industries and use the IMPLAN ProfessionalTM input-output model to identify the supplier chains (indirect industries) for the primary industries. The selected primary industries are listed below by Standard Industrial Classification (SIC) code or code groupings and their corresponding IMPLAN sector number. We call the consolidation of primary industries the Development Industry group. The Development Industry group consists of: IMPLAN sector 48 Residential Construction = parts of SICs 15 (general building contractors), 16 (heavy construction except buildings), and 17 (special trade contractors). IMPLAN sector 49 Industrial / Commercial Construction = parts of SICs 15, 16, and 17. IMPLAN sector 50 Utility Construction = parts of SICs 15, 16, and 17. IMPLAN sector 51 Highway Construction = parts of SICs 15, 16, and 17. IMPLAN sector 54 Construction of Government Facilities = parts of SICs 15, 16, and 17. IMPLAN sector 462 Real Estate = SIC 6500 which includes real estate operators and lessors, real estate agents and managers, title abstract offices, and subdividers and developers. To measure the “magnitude of clustering,” we introduce into the model a $1 million increase in the output of each primary industry. We then measure the consequent percentage increase (as a percent of the increased primary output) in other regional industries. The greater the percentage, the more economic activity there is between an indirect industry and the primary industries. To better organize the inter-industry relationships, three tiers are used. Tier 1 relationships occur when an indirect industry’s output increases by more than 1% of the increase in primary output. A Tier 2 relationship is between 0.5% and 1%. Tier 3 fills out the one-page summary of inter-industry relationships. Because spatial concentration is also an element of the clustering phenomenon, we examine the effect of introducing increased output into the model using several regional impact groupings. The regional groupings used in this study are: 1) individually, each of the seven 1 Porter represents regional competitive advantage as a “diamond”, the four corners of which are made up of the competitive nature of the industry, the interaction of firms in the industry with suppliers, the interaction with informed domestic customers, and the traditional country-specific factor cost and supply conditions.

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4 counties that make up Tampa Bay, 2) individually, each of the three metropolitan statistical areas that make up Tampa Bay, and 3) the Tampa Bay Region as a whole. We find 24 Tier 1 supplier-industries. The Tier 1 supplier-links to the primary industries, in order of frequency, are: Supplier-industry Frequency Engineering – Architectural Services73 Wholesale Trade (see note on page 6)70 Management and Consulting Services56 Motor Freight Transport and Warehousing54 Other Business Services248 Real Estate (see note on page 5)37 Accounting, Auditing and Bookkeeping22 Personnel Supply Services17 Computer and Data Processing Services11 Maintenance and Repair – Residential10 Maintenance and Repair Other Facilities10 Services to Buildings10 Communications except Radio and TV7 Miscellaneous Retail7 Automotive Dealers & Service Stations6 Paving Mixtures and Blocks6 Equipment Rental and Leasing6 Asphalt Felts and Coatings4 Banking4 Refrigeration and Heating Equipment3 Structural Wood Members – not elsewhere considered3 Electric Services1 Dimension Stone1 Veneer and Plywood1 2 Credit Reporting and Collection, Direct Mail Advertising Services, Secretarial and Court Reporting, News Syndicates, and Business Services not elsewhere considered.

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5Table 2.1Tier 1 Industries, Frequency by Location HernandoHillsboroughManateePascoPinellasSarasotaPolk County/Sarasota-Tampa-Tampa CountyCountyCountyCountyCountyCountyLakeland-BradentonSt.PetersburgBay SICIMPLAN Total Winter HavenMSAMSA CodeSectorDescription Frequency MSA 8710 506 EngineeringArchitectural Services 73 7786778788 5000,5100 447 Wholesale Trade 70 7777777777 8740 508 Management and Consulting Services 56 0770777777 4200 435 Motor Freight Transport and Warehousing 54 7737427377 7320,31,38,83,89 470 Other Business Services 48 2601777477 6500 462 Real Estate 37 2532434455 8720,8990 507 AccountingAuditing and Bookkeeping 22 0310224244 7360 474 Personnel Supply Services 17 0210201155 7370 475 Computer and Data Processing Services 11 0300000044 55 Maintenance and RepairResidential 10 1111111111 56 Maintenance and Repair Other Facilities 10 1111111111 7340 472 Services To Buildings 10 1111111111 4810,20,40,90 441 CommunicationsExcept Radio and TV 7 0000110122 5900 455 Miscellaneous Retail 7 0110110111 5500 451 Automotive Dealers & Service Stations 7 0100111111 2951 211 Paving Mixtures and Blocks 6 1100101011 7350 473 Equipment Rental and Leasing 6 0101101011 2952 212 Asphalt Felts and Coatings 4 1000001011 6000 456 Banking 4 0100100011 3585 347 Refrigeration and Heating Equipment 3 0200000100 2439 140 Structural Wood MembersN.E.C 3 1010100000 4910 443 Electric Services 1 0000000010 1410,20 40 Dimension Stone 1 1000000000 2435,6 139 Veneer and Plywood 1 0000010000 Source: This table was constructed by CEDR based on IMPLAN output tables, which are contained in this report. Use of Table: This table shows the frequency with which an industry is in Tier 1 in a particular location. For example, Engineering-Architectural Services is in Tier 1 in Hernando County 7 times. The maximum for a single industry in one location is eight, i.e. the six primary industries plus all "Construction Industries", plus "All Industries". See also the accompanying "Tier 1 Industries, Frequency by Industry".

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6Table 2.2Tier 1 Industries, Frequency by Primary Industry ResidentialCommercial/UtilityHighwayGovernmentAverageRealAverage ConstructionIndustrialConstructionConstructionBuildingConstructionEstateAll (Implan 48)Construction(Implan 50)(Implan 51)Construction(Implan 48,(Implan 462)Industries SICIMPLAN Total (Implan 49)(Implan 54)49, 50, 51, CodeSectorDescription Frequency and 54) 8710 506 EngineeringArchitectural Services 73 91010101010410 5000,5100 447 Wholesale Trade 70 101010101010010 8740 508 Management and Consulting Services 56 88888808 4200 435 Motor Freight Transport and Warehousing 54 1066106907 7320,31,38,83,89 470 Other Business Services 48 07868766 6500 462 Real Estate 37 7030701010 8720,8990 507 AccountingAuditing and Bookkeeping 22 04708300 7360 474 Personnel Supply Services 17 42207200 7370 475 Computer and Data Processing Services 11 02303300 55 Maintenance and RepairResidential 10 000000100 56 Maintenance and Repair Other Facilities 10 000000100 7340 472 Services To Buildings 10 000000100 4810,20,40,90 441 CommunicationsExcept Radio and TV 7 20000050 5500 451 Automotive Dealers & Service Stations 7 70000000 5900 455 Miscellaneous Retail 7 70000000 7350 473 Equipment Rental and Leasing 6 60000000 2951 211 Paving Mixtures and Blocks 6 00060000 6000 456 Banking 4 40000000 2952 212 Asphalt Felts and Coatings 4 00040000 3585 347 Refrigeration and Heating Equipment 3 21000000 2439 140 Structural Wood MembersN.E.C 3 30000000 4910 443 Electric Services 1 00000010 1410,20 40 Dimension Stone 1 00010000 2435,6 139 Veneer and Plywood 1 10000000 Source: This table was constructed by CEDR based on IMPLAN output tables, which are contained in this report. Use of Table: This table shows the frequency with which an industry is in Tier 1 in a particular Sector. For example, EngineeringArchitectural Services is in Tier 1 in the Residential Construction Sector 9 times. The maximum for a single industry in one Sector is ten, i.e. the seven counties of Tampa Bay, the Tampa-St. Petersburg MSA, the Sarasota-Bradenton MSA, and Tampa Bay. See also the accompanying "Tier 1 Industries, Frequency by Location".

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7 Five of the six primary industries exhibit “clustering” in the sense that they tend to have the same supplier-industries. The Real Estate industry, however, appears to rely on a somewhat different set of suppliers than the other five, which are construction industries. This finding is likely due to the Standard Industrial Classification (SIC) definition of the Real Estate industry division to which the input-output model conforms. About one-half of the Real Estate industry division in Tampa Bay is comprised of Real Estate Agents and Managers, who presumably mostly deal with the resale of properties. Importantly, however, the Real Estate industry also includes Land Subdividers and Developers, who would be closely related to construction industries. The IMPLAN model does not allow the separation of the Real Estate industry division into its individual industry components for refined analysis. But, from the frequency table by primary industry, it can be seen that there are three Tier 1 supplier-industries, which are solely related to Real Estate. These three industries are 1) Maintenance and Repair – Residential, 2) Maintenance and Repair Other Facilities, and 3) Services to Buildings. Also, the Residential Construction industry, the Utility Construction industry and Government Building Construction industry exhibit links with the Real Estate industry, while the Commercial / Industrial Construction industry and the Highway Construction industry do not exhibit a link with Real Estate. The findings further show that within the construction-industries grouping there are no supplier linkages between construction industries. In contrast, the Real Estate industry emerges as a Tier 1 industry, when the only primary industry considered is the Real Estate industry itself. This indicates intra-industry linkages within the classification of businesses called Real Estate. The following is a list of supplier links that appear at least once in Tier 2, but never appear in Tier 1: Automotive Repair and Services Miscellaneous Repair Shops Legal Services Building Material and Gardening Credit Agencies Wood Kitchen Cabinets General Merchandise Stores Insurance Carriers Landscape and Horticultural Services Water Transportation Millwork Industrial and Fluid Valves Glass and Glass Products except Containers Security and Commodity Brokers Sanitary Services and Steam Supply Commercial Printing Wood Preserving Reconstituted Wood Products

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8 We conclude that the five construction major industry groups and a portion of the Real Estate sector form the primary industries of the Development Industry cluster by virtue of commonality of supplier industries. The Real Estate industries included among the primary industries are Nonresidential Building Operators (SIC 6512), Subdividers and Developers (SIC 6552), and possibly Real Estate Agents and Managers (SIC 6531). The Real Estate industries not included among the primary industries of the cluster are Tier 1 suppliers to the primary industries. Based on the input-output analysis, the Development Industry cluster in Tampa Bay is broadly defined to include the primary industries plus their Tier 1 and Tier 2 supplier-industries. Tables 2.1 and 2.2 show the frequency with which the Tier 1 industries emerge by location, i.e. regional grouping, and by primary industry, respectively. Because we use ten regional groupings (the Lakeland-Winter Have MSA is coincident with Polk County) and eight industry groupings, the maximum frequency a Tier 1 supplier-industry can achieve is 80.

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9 Section 3: Baseline Contributions of the Primary Industries Using the REMITM model, we estimate the economic contributions of the primary industries of the Development Industry cluster. These economic contributions provide a baseline from which we assess the economic impacts of the cluster. (Economic impacts are discussed later in this report.) Based on the results reported in Section 2 of this report, we define the primary industries of the Development Industry cluster to be: Construction Major Industry Group Residential Construction Industrial / Commercial Construction Utility Construction Highway Construction Construction of Government Facilities and two industries of the Real Estate Group Subdividers and Developers Nonresidential Building Operators.3We measure the baseline economic contributions of the primary industries within the cluster by employment, output, and personal income.4 That is, the industries hire a number of workers (employment), who produce goods and services of value (output).5 The value-added – less indirect business taxes from production is distributed among the workers and the owners of the capital that the workers use in the production process (personal income). Table 3.1 shows estimates of employment by location (place of work) from 2002 to 2007. Panel A shows total employment in each county and a summation of the counties’ employment for the Tampa Bay region. Panel B reflects employment by the construction major industry groups in each county and Tampa Bay. Panel C gives the percentage of total employment contributed by jobs in the construction industries for each location. 3 It is also possible that some activities of the Real Estate Agents and Managers industry are consistent with a primary industry of the Development Industry cluster. However, data are not available to quantify the applicable proportion of the Real Estate Agents and Managers industry that applies to the cluster. The tables in Appendix A describe the baseline for the primary industries of the cluster, if the Real Estate Agents and Managers industry were included in its entirety as a primary industry of the cluster. Including Real Estate Agents and Managers as a primary industry within the cluster does not materially effect the findings of this study.4 Estimates of personal income are only available for the construction major industry group.5 In this context, workers include both wage earning and salaried employees as well as sole proprietors under contract to a firm in one of the primary industries. Technically, output is equal to sales plus or minus an inventory adjustment.

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10Table 3.1 Development Industry Cluster – REMI Baseline Primary Industries: Construction Major Industry Groups EMPLOYMENT Panel A Employment (000s) Total Location200220032004200520062007 Hernando43.85244.59545.30745.94946.50947.072 Hillsborough783.506798.732814.520829.625845.062861.097 Manatee159.296162.159165.157167.954170.695173.471 Pasco105.737107.122108.435109.637110.764111.969 Pinellas580.113586.852594.073600.892607.839615.298 Polk245.968250.046253.927257.481260.942264.494 Sarasota215.068218.125221.103223.857226.467229.258 Tampa Bay2133.5402167.6312202.5222235.3952268.2782302.659 Panel B Construction Employment (000s) by Sector > Non-Manufacturing > Construction Location200220032004200520062007 Hernando3.4633.4733.4783.4693.4543.446 Hillsborough41.61941.68141.74541.68341.66841.788 Manatee8.2588.2538.2538.2248.1958.187 Pasco9.1689.1609.1449.0999.0529.036 Pinellas32.77032.57132.38032.11131.88531.787 Polk15.69015.78815.85115.85415.85615.899 Sarasota15.20115.20315.17315.08214.98014.929 Tampa Bay126.169126.129126.024125.522125.090125.072 Panel C Construction Employment (% of Total) by Sector > Non-Manufacturing > Construction Location200220032004200520062007 Hernando7.90%7.79%7.68%7.55%7.43%7.32% Hillsborough5.31%5.22%5.13%5.02%4.93%4.85% Manatee5.18%5.09%5.00%4.90%4.80%4.72% Pasco8.67%8.55%8.43%8.30%8.17%8.07% Pinellas5.65%5.55%5.45%5.34%5.25%5.17% Polk6.38%6.31%6.24%6.16%6.08%6.01% Sarasota7.07%6.97%6.86%6.74%6.61%6.51% Tampa Bay5.91%5.82%5.72%5.62%5.51%5.43% Almost six percent of the jobs in Tampa Bay are in the construction industries. Among the counties of Tampa Bay, the number of jobs in construction ranges from approximately 41,600 in Hillsborough County to 3,500 in Hernando County. Pasco County has the largest share of its employment (8.67% in 2002) in construction, while Manatee County has the smallest

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11 percentage (5.18% in 2002) of its employment in construction. Barring an unforeseen economic shock, we expect construction jobs in Tampa Bay to slightly decline from about 126,200 in 2002 to 125,100 in 2007. Table 3.2 shows estimates of output by location from 2002 to 2007. Panel A shows total output in each county and a summation of the counties’ output for the Tampa Bay region. Panel B reflects output by the construction major industry groups in each county and Tampa Bay. Panel C gives the percentage of total output contributed by the construction industries for each location.Table 3.2 Development Industry Cluster – REMI Baseline Primary Industries: Construction Major Industry Groups OUTPUT Panel A Output (Bil. 01$) Total Location200220032004200520062007 Hernando2.6782.7642.8522.9273.0023.077 Hillsborough61.82464.02466.19768.28070.49472.719 Manatee12.01312.42812.83013.19613.57513.940 Pasco6.7706.9537.1287.2917.4607.625 Pinellas46.06247.60849.12750.56152.05753.551 Polk19.75720.38820.98821.54022.11122.670 Sarasota14.88115.32515.75816.16416.58617.010 Tampa Bay163.985169.491174.878179.959185.285190.592 Panel B Output (Bil. 01$) Construction Location200220032004200520062007 Hernando0.3050.3080.3110.3130.3150.317 Hillsborough3.9433.9994.0374.0694.1154.171 Manatee0.7540.7630.7700.7730.7800.786 Pasco0.8040.8130.8170.8210.8250.832 Pinellas3.0083.0283.0343.0363.0493.071 Polk1.4631.4901.5061.5191.5351.555 Sarasota1.3971.4141.4201.4241.4301.439 Tampa Bay11.67511.81511.89511.95312.04912.172 Panel C Output (% of Total) Construction Location200220032004200520062007 Hernando11.38%11.15%10.92%10.68%10.49%10.30% Hillsborough6.38%6.25%6.10%5.96%5.84%5.74% Manatee6.28%6.14%6.00%5.86%5.74%5.64% Pasco11.88%11.69%11.47%11.25%11.06%10.91% Pinellas6.53%6.36%6.18%6.00%5.86%5.74% Polk7.41%7.31%7.18%7.05%6.94%6.86% Sarasota9.39%9.22%9.01%8.81%8.62%8.46% Tampa Bay7.12%6.97%6.80%6.64%6.50%6.39%

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12 Over seven percent of the Tampa Bay economy is generated by the economic activity of the construction industries. Among the counties of Tampa Bay, construction output ranges from approximately $3.9 billion in Hillsborough County to $305 million in Hernando County. The economies of Hernando County and Pasco County heavily depend on the construction industries as evidenced by their 11.38% and 11.88%, respectively, construction output to total output shares. While we expect construction jobs in Tampa Bay to gradually decline, construction output is expected to increase from about $11.67 billion in 2002 to $12.17 billion in 2007 (in constant 2001 $s). The anticipated decline in employment and contemporaneous rise is output is indicative of increasing productivity in the construction industries. Table 3.3 shows estimates of personal income originating in the construction industries by location from 2002 to 2007. Panel A shows total personal income originating in each county and a summation of the counties’ personal income for the Tampa Bay region. Panel B reflects personal income originating in the construction major industry groups in each county and Tampa Bay. Panel C gives the percentage of total personal income originating in the construction industries for each location. Over six percent of personal income originating in Tampa Bay is derived from the output of the construction industries. Among the counties of Tampa Bay, personal income from construction industries’ production ranges from $1.6 billion in Hillsborough County to $92 million in Hernando County. As a percentage of a county’s total personal income, construction industries in Pasco County contribute the largest share (9.03%), closely followed by Hernando County (8.21%) and Sarasota County (8.06%). In Tampa Bay, personal income measured in nominal dollars – derived from the construction industries is expected to increase from about $4.4 billion in 2002 to $5.2 billion in 2007. This is an 18.2% increase over five years, indicating that personal income from construction would keep up with an average inflation rate of about 3.64% per annum.

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13Table 3.3 Development Industry Cluster – REMI Baseline Primary Industries: Construction Major Industry Groups PERSONAL INCOME Panel A Personal Income (Bil. nominal) Total Labor & Property Income Location200220032004200520062007 Hernando1.1201.1821.2451.3101.3761.445 Hillsborough28.46930.16531.96033.84535.87838.049 Manatee4.5414.7725.0195.2805.5585.854 Pasco2.7592.8913.0263.1673.3143.472 Pinellas19.49120.44121.45022.51423.65724.881 Polk7.7548.1568.5668.9929.4439.919 Sarasota6.3376.6677.0047.3557.7218.112 Tampa Bay70.47174.27478.27082.46386.94791.732 Panel B Personal Income (Bil. nominal) Total Labor & Property Income > Non-manufacturing > Construction Location200220032004200520062007 Hernando0.0920.0950.0990.1020.1060.109 Hillsborough1.6101.6771.7451.8101.8801.960 Manatee0.2740.2830.2930.3020.3120.323 Pasco0.2490.2580.2660.2740.2820.292 Pinellas1.1081.1411.1741.2071.2421.284 Polk0.5420.5650.5880.6090.6310.656 Sarasota0.5110.5280.5450.5600.5760.594 Tampa Bay4.3864.5474.7104.8645.0295.218 Panel C Personal Income (% of Total) Total Labor & Property Income > Non-manufacturing > Construction Location200220032004200520062007 Hernando8.21%8.04%7.95%7.79%7.70%7.54% Hillsborough5.66%5.56%5.46%5.35%5.24%5.15% Manatee6.03%5.93%5.84%5.72%5.61%5.52% Pasco9.03%8.92%8.79%8.65%8.51%8.41% Pinellas5.68%5.58%5.47%5.36%5.25%5.16% Polk6.99%6.93%6.86%6.77%6.68%6.61% Sarasota8.06%7.92%7.78%7.61%7.46%7.32% Tampa Bay6.22%6.12%6.02%5.90%5.78%5.69% Tables 3.4 and 3.5 show the baseline economic contributions of Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512). We measure the contributions by employment and output. Consistent with available government data, the REMITM model’s results for employment and output are aggregated for major group 65, Real Estate. We apportioned the model’s results to estimate the contributions of these two industries. We use information from the U.S. Census

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14 Bureau’s 1997 Economic Census to apportion output to our industries of interest.6 The apportionment is made in accord with sales per employee in each of the industries of the major group. For example, sales per employee for Nonresidential Building Operators (SIC 6512) is $164,637 (92 $s), which is 19.37% of the total of sales per employee for all industries within the major group. Thus, we assign 19.37% of the REMITM model’s results for Real Estate output to Nonresidetial Building Operators. Similarly, sales per employee for Subdividers and Developers (SIC 6552) is $143,105 (92 $s) or 16.84% of the major group total. We then divide the apportioned output by sales per employee (01 $s) to calculate the number of employees needed to generate the apportioned level of output. Furthermore, the REMITM model results for personal income are aggregated at the division level, i.e. Finance, Insurance, and Real Estate (FIRE). We were unable to make a reliable apportionment of personal income to our real estate industries of interest. Table 3.4 shows estimates of employment by location (place of work) from 2002 to 2007. Panel A shows total employment in each county and a summation of the counties’ employment for the Tampa Bay region. Panel B reflects employment by Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) in each county and Tampa Bay. These two real estate industries are part of the Development Industry cluster. Panel C gives the percentage of total employment contributed by jobs in the two real estate industries for each location. About 1.4 percent of the jobs in Tampa Bay are in the two aforementioned real estate industries. Among the counties of Tampa Bay, the number of jobs in these industries ranges from approximately 11,300 in Hillsborough County to 435 in Hernando County. Sarasota County has the largest share of its employment (1.67% in 2002) in these real estate industries, while Polk County has the smallest percentage (0.88% in 2002) of its employment in the industries. We expect jobs in the two industries in Tampa Bay to increase from about 30,200 in 2002 to 35,000 in 2007. 6 The Economic Census is a full-blown census of U.S. business establishments and is carried out every 5 years (years ending in 2 and 7). Due to a disclosure problem, the information we use for apportionment – the Comparative Statistics for Florida, which is taken from the 1997 census report, actually reflects 1992 data.

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15Table 3.4 Development Industry Cluster – REMI Baseline Primary Industries: Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) EMPLOYMENT Panel A Employment (000s) Total Location200220032004200520062007 Hernando43.85244.59545.30745.94946.50947.072 Hillsborough783.506798.732814.520829.625845.062861.097 Manatee159.296162.159165.157167.954170.695173.471 Pasco105.737107.122108.435109.637110.764111.969 Pinellas580.113586.852594.073600.892607.839615.298 Polk245.968250.046253.927257.481260.942264.494 Sarasota215.068218.125221.103223.857226.467229.258 Tampa Bay2133.5402167.6312202.5222235.3952268.2782302.659 Panel B Industry Employment (000s) by Sector > Non-Manufacturing > Real Estate > SICs 6552 & 6512 Location200220032004200520062007 Hernando0.4350.4500.4640.4780.4940.508 Hillsborough11.31811.71512.12312.51812.93913.358 Manatee2.0952.1632.2332.2992.3702.438 Pasco1.0381.0681.1011.1321.1651.198 Pinellas9.5399.80910.09210.36710.66310.960 Polk2.1632.2362.3112.3822.4572.530 Sarasota3.5983.6933.7893.8833.9824.081 Tampa Bay30.18531.13432.11333.05934.07135.073 Panel C Industry Employment (% of Total) by Sector > Non-Manufacturing > Real Estate > SICs 6552 & 6512 Location200220032004200520062007 Hernando0.99%1.01%1.02%1.04%1.06%1.08% Hillsborough1.44%1.47%1.49%1.51%1.53%1.55% Manatee1.31%1.33%1.35%1.37%1.39%1.41% Pasco0.98%1.00%1.02%1.03%1.05%1.07% Pinellas1.64%1.67%1.70%1.73%1.75%1.78% Polk0.88%0.89%0.91%0.92%0.94%0.96% Sarasota1.67%1.69%1.71%1.73%1.76%1.78% Tampa Bay1.41%1.44%1.46%1.48%1.50%1.52% Table 3.5 shows estimates of output by location from 2002 to 2007. Panel A shows total output in each county and a summation of the counties’ output for the Tampa Bay region. Panel B reflects output by Subdividers and Developers (SIC 6552) and Nonresidential Building

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16 Operators (SIC 6512) in each county and Tampa Bay. Panel C gives the percentage of total output contributed by jobs in the two real estate industries for each location.Table 3.5 Development Industry Cluster – REMI Baseline Primary Industries: Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) OUTPUT Panel A Output (Bil. 01$) Total Location200220032004200520062007 Hernando2.682.762.852.933.003.08 Hillsborough61.8264.0266.2068.2870.4972.72 Manatee12.0112.4312.8313.2013.5813.94 Pasco6.776.957.137.297.467.62 Pinellas46.0647.6149.1350.5652.0653.55 Polk19.7620.3920.9921.5422.1122.67 Sarasota14.8815.3215.7616.1616.5917.01 Tampa Bay163.985169.491174.878179.959185.285190.592 Panel B Output (Bil. 01$) BY Real Estate > SICs 6552 & 6512 Location200220032004200520062007 Hernando0.0740.0760.0790.0810.0840.086 Hillsborough1.9231.9912.0602.1272.1992.270 Manatee0.3560.3680.3800.3910.4030.414 Pasco0.1760.1820.1870.1920.1980.204 Pinellas1.6211.6671.7151.7621.8121.862 Polk0.3680.3800.3930.4050.4180.430 Sarasota0.6110.6270.6440.6600.6770.693 Tampa Bay5.1305.2915.4575.6185.7905.960 Panel C Output (% of Total) by Real Estate > SICs 6552 & 6512 Location200220032004200520062007 Hernando2.76%2.76%2.76%2.77%2.80%2.81% Hillsborough3.11%3.11%3.11%3.12%3.12%3.12% Manatee2.96%2.96%2.96%2.96%2.97%2.97% Pasco2.61%2.61%2.63%2.64%2.65%2.67% Pinellas3.52%3.50%3.49%3.48%3.48%3.48% Polk1.86%1.86%1.87%1.88%1.89%1.90% Sarasota4.11%4.09%4.09%4.08%4.08%4.08% Tampa Bay3.13%3.12%3.12%3.12%3.12%3.13% Over three percent of the Tampa Bay economy is generated by the economic activity of the two aforementioned real estate industries. Among the counties of Tampa Bay, output by these two industries ranges from approximately $1.9 billion in Hillsborough County to $74

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17 million in Hernando County. Over four percent of Sarasota County’s economy depends on the activities of these two real estate industries. We expect output in these industries to gradually increase from about $5.13 billion in 2002 to $5.96 billion in 2007 (in constant 2001 $s). Tables 3.6 and 3.7 show the baseline contributions of the Development Industry cluster as measured by employment and output, respectively. Table 3.6 shows estimates of employment by location (place of work) from 2002 to 2007. Panel A shows total employment in each county and a summation of the counties’ employment for the Tampa Bay region. Panel B reflects employment in the primary industries of the Development Industry cluster in each county and Tampa Bay. Panel C gives the percentage of total employment contributed by jobs in the primary industries for each location. Over seven percent of the jobs in Tampa Bay are in the primary industries of the Development Industry cluster. Among the counties of Tampa Bay, the number of jobs in the primary industries ranges from approximately 52,900 in Hillsborough County to 3,900 in Hernando County. Pasco County has the largest share of its employment (9.65% in 2002) in the primary industries, while Manatee County has the smallest percentage (6.50% in 2002) of its employment in the cluster’s primary industries. Absent an unforeseen and destabilizing economic shock, we expect jobs in Tampa Bay’s primary development industries to gradually increase from about 156,400 to about 160,100 during the next five years. However, this increase in employment is expected at a lower rate than the overall Tampa Bay growth rate in employment, as indicated by the decline in the percentage of employment in the primary development industries from 7.33% in 2002 to 6.95% in 2007. Table 3.7 shows estimates of output by location from 2002 to 2007. Panel A shows total output in each county and a summation of the counties’ output for the Tampa Bay region. Panel B reflects output by the primary industries of the Development Industry cluster in each county and Tampa Bay. Panel C gives the percentage of total output contributed by the primary industries for each location.

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18Table 3.6 Development Industry Cluster – REMI Baseline Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) EMPLOYMENT Panel A Employment (000s) Total Location200220032004200520062007 Hernando43.85244.59545.30745.94946.50947.072 Hillsborough783.506798.732814.52829.625845.062861.097 Manatee159.296162.159165.157167.954170.695173.471 Pasco105.737107.122108.435109.637110.764111.969 Pinellas580.113586.852594.073600.892607.839615.298 Polk245.968250.046253.927257.481260.942264.494 Sarasota215.068218.125221.103223.857226.467229.258 Tampa Bay2133.5402167.6312202.5222235.3952268.2782302.659 Panel B Construction Employment (000s) by Sector > Non-Manufacturing > Construction Industry Employment (000s) by Sector > Non-Manufacturing > Real Estate > SICs 6552 & 6512 Location200220032004200520062007 Hernando3.8983.9233.9423.9473.9483.954 Hillsborough52.93753.39653.86854.20154.60755.146 Manatee10.35310.41610.48610.52310.56510.625 Pasco10.20610.22810.24510.23110.21710.234 Pinellas42.30942.38042.47242.47842.54842.747 Polk17.85318.02418.16218.23618.31318.429 Sarasota18.79918.89618.96218.96518.96219.010 Tampa Bay156.354157.263158.137158.581159.161160.145 Panel C Construction Employment (% of Total) by Sector > Non-Manufacturing > Construction Industry Employment (% of Total) by Sector > Non-Manufacturing > Real Estate > SICs 6552 & 6512 Location200220032004200520062007 Hernando8.89%8.80%8.70%8.59%8.49%8.40% Hillsborough6.76%6.69%6.61%6.53%6.46%6.40% Manatee6.50%6.42%6.35%6.27%6.19%6.13% Pasco9.65%9.55%9.45%9.33%9.22%9.14% Pinellas7.29%7.22%7.15%7.07%7.00%6.95% Polk7.26%7.21%7.15%7.08%7.02%6.97% Sarasota8.74%8.66%8.58%8.47%8.37%8.29% Tampa Bay7.33%7.26%7.18%7.09%7.02%6.95%

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19Table 3.7 Development Industry Cluster – REMI Baseline Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) OUTPUT Panel A Output (Bil. 01$) Total Location200220032004200520062007 Hernando2.6782.7642.8522.9273.0023.077 Hillsborough61.82464.02466.19768.28070.49472.719 Manatee12.01312.42812.83013.19613.57513.940 Pasco6.7706.9537.1287.2917.4607.625 Pinellas46.06247.60849.12750.56152.05753.551 Polk19.75720.38820.98821.54022.11122.670 Sarasota14.88115.32515.75816.16416.58617.010 Tampa Bay163.985169.491174.878179.959185.285190.592 Panel B Output (Bil. 01$) Construction Output (Bil. 01$) by Real Estate > SICs 6552 & 6512 Location200220032004200520062007 Hernando0.3790.3850.3900.3940.3990.403 Hillsborough5.8665.9906.0976.1966.3146.441 Manatee1.1101.1311.1491.1641.1821.201 Pasco0.9800.9941.0041.0131.0231.035 Pinellas4.6294.6954.7494.7984.8614.934 Polk1.8311.8701.8991.9231.9531.985 Sarasota2.0092.0412.0642.0832.1072.133 Tampa Bay16.80417.10617.35317.57117.83918.132 Panel C Output (% of Total) Construction Output (% of Total) by Real Estate > SICs 6552 & 6512 Location200220032004200520062007 Hernando14.14%13.91%13.68%13.45%13.28%13.11% Hillsborough9.49%9.36%9.21%9.07%8.96%8.86% Manatee9.24%9.10%8.96%8.82%8.71%8.61% Pasco14.48%14.30%14.09%13.89%13.71%13.58% Pinellas10.05%9.86%9.67%9.49%9.34%9.21% Polk9.27%9.17%9.05%8.93%8.83%8.76% Sarasota13.50%13.32%13.10%12.89%12.70%12.54% Tampa Bay10.25%10.09%9.92%9.76%9.63%9.51% Over ten percent of the Tampa Bay economy is generated by the economic activity of the primary industries of the Development Industry cluster. Among the counties of Tampa Bay, the primary industries’ output ranges from approximately $5.9 billion in Hillsborough County to $379 million in Hernando County. The economies of Hernando County and Pasco County

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20 heavily depend on the primary industries of the Development Industry cluster as evidenced by their 14.14% and 14.48%, respectively, industry output to total output shares. The primary industries’ output is expected to increase from about $16.8 billion in 2002 to $18.1 billion in 2007 (in constant 2001 $s). Steady employment and a contemporaneous rise in output is indicative of increasing productivity in the primary industries of the Development Industry cluster.

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21 Section 4: Employment Structure of the Primary Industries Based on the results reported in Section 2 of the report, we define the primary industries of the Development Industry cluster to be: Construction Major Industry Groups Residential Construction Industrial / Commercial Construction Utility Construction Highway Construction Construction of Government Facilities and two industries of the Real Estate Group Subdividers and Developers Nonresidential Building Operators.7We use ES-202 data to compile the number of employees, average annual wages, and the number of firms for each of the primary industries of the Development Industry cluster. The Bureau of Labor Statistics (BLS) Covered Employment and Wages data (also called the ES-202 data) is based on the national Unemployment Insurance program for which premiums are collected monthly by state agencies. ES-202 data is gathered from the information sent to a state agency by firms that employ “covered workers.” For this study, we use ES-202 data from the 2ndQuarter 2001, which is the most recent period available to us. Tables 4.1 through 4.3 show the number of employees, average annualized wages, and the number of firms for each industry in the General Building Contractors (SIC 15), Heavy Construction except buildings (SIC 16), and Special Trades Contractors (SIC 17) major groups, respectively.8 Table 4.4 displays the number of employees, average annual wages, and the number of firms in the two pertinent industries of the Real Estate group. Table 4.5 aggregates the findings presented in Tables 4.1 through 4.4 in order to provide a complete picture of the employment structure of the primary industries of the Development Industry cluster in Tampa Bay. We choose three ranges of average wage to organize and present our findings. The ranges are 1) below $35,000, 2) between $35,000 and $60,000, and 3) above $60,000. For each location, we divide total wages paid by an industry during the 2nd Quarter 2001 by the average number of employees during that quarter to obtain an average wage for the quarter. We then annualize the average quarterly wage. 7 It is also possible that some activities of the Real Estate Agents and Managers industry are consistent with a primary industry of the Development Industry cluster. However, data are not available to quantify the applicable proportion of the Real Estate and Managers industry that applies to the cluster. The tables in Appendix B describe the employment structure for the primary industries of the cluster, if the Real Estate Agents and Managers industry were included in its entirety as a primary industry of the cluster. Including Real Estate Agents and Managers as a primary industry within the cluster does not materially effect the findings of this study.8 Here we use the descriptive titles for the construction major industry groups from the Standard Industrial Classification (SIC) system. These three SIC groups, when aggregated, correspond to the five groups of the IMPLANTM model’s scheme, which are listed in the first paragraph of this section.

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22 Table 4.1 reveals that the 2,537 Tampa Bay firms in the General Building Contractors group were employing 14,898 workers during the 2nd Quarter 2001. Employers were paying annualized wages of less than $35,000 to 2,509 workers (17%), annualized wages of between $35,000 and $60,000 to11,687 workers (78%), and annualized wages over $60,000 to 702 workers (5%). Building contractors, who are based in Hillsborough County, employ 5,094 workers, or 34% of all workers employed by building contractors in Tampa Bay. Most of these workers are earning an annualized wage between $35,000 and $60,000 (47 out of the 5,094 are earning less than $35,000). Only firms based in Manatee County or Sarasota County pay employees more than $60,000, annualized. Pasco County is the home base of the largest number of firms (775 firms) in the General Building Contractors group in Tampa Bay. Table 4.2 reveals that the 455 Tampa Bay firms in the Heavy Construction group were employing 13,224 workers during the 2nd Quarter 2001. Employers were paying annualized wages of less than $35,000 to 6,482 workers (49%) and annualized wages of between $35,000 and $60,000 to 6,742 workers (51%). Heavy construction firms, which are based in Hillsborough County, employ 4,439 workers, or 34% of all workers employed by the Heavy Construction industry group in Tampa Bay. Table 4.3 reveals that the 6,463 Tampa Bay firms in the Special Trades Contractors group were employing 58,852 workers during the 2nd Quarter 2001. Employers were paying annualized wages of less than $35,000 to 53,548 workers (91%) and annualized wages of between $35,000 and $60,000 to 5,304 workers (9%). Special trades contractors, who are based in Hillsborough County, employ 20,006 workers, or 34% of all workers employed by the special trades in Tampa Bay.

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23Table 4.1 Development Industry Cluster – ES 202 Employment Data Primary Industries: General Building Contractors (SIC 15) EMPLOYEESNumber of Employees by Average Annualized Wage Hernando Hillsborough Manatee SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 1521Single Family Housing 267 3,034 627 1522Other Residential Construction 12 47 48 1531Operative Builders 12 77 4 1541Industrial Buildings 28 371 89 1542Other Non-res. Construction 25 1,564 179 TotalGeneral Building Contractors 319250 475,0470 52716179 Number of Firms FirmsFirmsFirms TotalGeneral Building Contractors 83 528 56 Number of Employees by Average Annualized Wage Pasco Pinellas Polk SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 1521Single Family Housing 721 2,433 934 1522Other Residential Construction 24 247 60 1531Operative Builders 43 4 1541Industrial Buildings 15 183 446 1542Other Non-res. Construction 20 1,153 370 TotalGeneral Building Contractors 760200 04,0590 1,3085060 Number of Firms FirmsFirmsFirms TotalGeneral Building Contractors 775 515 219 Number of Employees by Average Annualized Wage Sarasota Tampa Bay SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K 1521Single Family Housing 1,271 1,9227,365 1522Other Residential Construction 23 154307 1531Operative Builders 14 20134 1541Industrial Buildings 30 431,119 1542Other Non-res. Construction 523 3702,761702 TotalGeneral Building Contractors 231,315523 2,50911,687702 Number of Firms FirmsFirms TotalGeneral Building Contractors 351 2,527

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24Table 4.2 Development Industry Cluster – ES 202 Employment Data Primary Industries: Heavy Construction (SIC 16) EMPLOYEESNumber of Employees by Average Annualized Wage Hernando Hillsborough Manatee SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 1611Highway & Street Construction 82 1,343 253 1622Bridge, Tunnel, & Elevated Highway 307 18 1623Water, Sewer, Pipeline & Communications 28 1,578 663 1629Heavy Construction NEC 213 1,211 268 TotalHeavy Construction 1102130 1,5782,8610 9342680 Number of Firms FirmsFirmsFirms TotalHeavy Construction 15 119 36 Number of Employees by Average Annualized Wage Pasco Pinellas Polk SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 1611Highway & Street Construction 188 495 1,717 1622Bridge, Tunnel, & Elevated Highway 211 1623Water, Sewer, Pipeline & Communications 247 955 471 1629Heavy Construction NEC 122 455 1,228 TotalHeavy Construction 55700 1,6614550 4712,9450 Number of Firms FirmsFirmsFirms TotalHeavy Construction 43 108 85 Number of Employees by Average Annualized Wage Sarasota Tampa Bay SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K 1611Highway & Street Construction 537 1,5553,060 1622Bridge, Tunnel, & Elevated Highway 229307 1623Water, Sewer, Pipeline & Communications 430 4,372 1629Heavy Construction NEC 204 3263,375 TotalHeavy Construction 1,17100 6,4826,7420 Number of Firms FirmsFirms TotalHeavy Construction 49 455

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25Table 4.3 Development Industry Cluster – ES 202 Employment Data Primary Industries: Special Trade Contractors (SIC 17) EMPLOYEESNumber of Employees by Average Annualized Wage Hernando Hillsborough Manatee SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 1711Plumbing, Heating & Air Conditioning 297 3,690 750 1721Painting & Paper Hanging 41 1,138 162 1731Electrical Work 113 4,246 455 1741Masonry, Stone Setting, & Other Stone Work 90 918 157 1742Plastering, Drywall, Acoustical & Insulation Work 192 1,752 302 1743Terrazzo, Tile, Marble, & Mosaic Work 23 218 37 1751Carpentry Work 218 911 146 1752Floor Laying and Other Floor Work NEC 1 240 27 1761Roofing, Siding, & Sheet Metal Work 144 1,259 464 1771Concrete Work 234 1,710 242 1781Water Well Drilling 16 166 60 1791Structural Steel Erection 23 294 158 1793Glass & Glazing Work 314 1794Excavation Work 109 602 145 1795Wrecking & Demolition Work 393 1 1796Installation or Erection of Building Equipment NEC 420 23 1799Special Trade Contractors NEC 160 1,735 162 TotalSpecial Trade Contractors 1,5521090 15,2464,7600 3,268230 Number of Firms FirmsFirmsFirms TotalSpeical Trade Contractors 316 1,619 496 Number of Employees by Average Annualized Wage Pasco Pinellas Polk SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 1711Plumbing, Heating & Air Conditioning 993 3,340 1,347 1721Painting & Paper Hanging 212 605 403 1731Electrical Work 623 3,444 1,098 1741Masonry, Stone Setting, & Other Stone Work 292 613 247 1742Plastering, Drywall, Acoustical & Insulation Work 144 1,271 118 1743Terrazzo, Tile, Marble, & Mosaic Work 136 313 56 1751Carpentry Work 402 678 180 1752Floor Laying and Other Floor Work NEC 18 222 66 1761Roofing, Siding, & Sheet Metal Work 341 1,048 461 1771Concrete Work 419 1,637 406 1781Water Well Drilling 52 12 108 1791Structural Steel Erection 214 199 301 1793Glass & Glazing Work 31 186 78 1794Excavation Work 390 591 496 1795Wrecking & Demolition Work 13 28 2 1796Installation or Erection of Building Equipment NEC 2 129 192 1799Special Trade Contractors NEC 593 976 609 TotalSpecial Trade Contractors 4,87500 15,1351570 5,9761920 Number of Firms FirmsFirmsFirms TotalSpecial Trade Contractors 676 1,584 699 Number of Employees by Average Annualized Wage Sarasota Tampa Bay SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K 1711Plumbing, Heating & Air Conditioning 1,646 12,063 1721Painting & Paper Hanging 326 2,887 1731Electrical Work 1,295 11,274 1741Masonry, Stone Setting, & Other Stone Work 688 3,005 1742Plastering, Drywall, Acoustical & Insulation Work 307 2,3341,752 1743Terrazzo, Tile, Marble, & Mosaic Work 282 1,065 1751Carpentry Work 593 3,128 1752Floor Laying and Other Floor Work NEC 40 614 1761Roofing, Siding, & Sheet Metal Work 474 4,191 1771Concrete Work 882 5,530 1781Water Well Drilling 49 297166 1791Structural Steel Erection 21 895315 1793Glass & Glazing Work 86 695 1794Excavation Work 444 2,668109 1795Wrecking & Demolition Work 7 23421 1796Installation or Erection of Building Equipment NEC 42 2806 1799Special Trade Contractors NEC 377 2,8771,735 TotalSpecial Trade Contractors 7,496630 53,5485,3040 Number of Firms FirmsFirms TotalSpeical Trade Contractors 1,073 6,463

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26 Table 4.4 reveals that the 422 Tampa Bay firms in the two real estate industries of interest were employing 3,034 workers during 2nd Quarter 2001. Employers were paying annualized wages of less than $35,000 to 2,081 workers (69%), annualized wages between $35,000 and $60,000 to 730 workers (24%), and annualized wages over $60,000 to 223 workers (7%). All of the 223 employees earning an annualized wage over $60,000 work for firms based in Sarasota County. Firms based in Hillsborough County employ the largest number of these workers: 978 in the Nonresidential Building Operators industry and 470 in the Subdividers and Developers industry.Table 4.4 Development Industry Cluster – ES 202 Employment Data Primary Industries: Real Estate (SIC 65) EMPLOYEESNumber of Employees by Average Annualized Wage Hernando Hillsborough Manatee SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 6512Operators of Nonresidential Buildings 11 978 60 6552Land Subdividers & Developers 80 470 111 TotalReal Estate 9100 9784700 601110 Number of Firms FirmsFirmsFirms TotalReal Estate 8 126 28 Number of Employees by Average Annualized Wage Pasco Pinellas Polk SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 6512Operators of Nonresidential Buildings 44 440 45 6552Land Subdividers & Developers 149 278 107 TotalReal Estate 441490 71800 15200 Number of Firms FirmsFirmsFirms TotalReal Estate 33 134 34 Number of Employees by Average Annualized Wage Sarasota Tampa Bay SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K 6512Operators of Nonresidential Buildings 39 1,61700 6552Land Subdividers & Developers 223 465730223 TotalReal Estate 390223 2,082730223 Number of Firms FirmsFirms TotalGeneral Buliding Contractors 59 422

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27 Table 4.5 sums up the number of employees by average annual wages and the number of firms in the primary industries of the Development Industry cluster in Tampa Bay. In 2ndQuarter of 2001, there were 9,867 firms employing 90,008 workers. These employers were paying 72% of the workers annualized wages less than $35,000, 27% of the workers annualized wages between $35,000 and $60,000, and 1% of the workers annualized wages over $60,000. Firms based in either Sarasota County or Manatee County employed all of the workers earning over $60,000. Although an almost equal number of firms are based in Pinellas County and in Hillsborough County, the Hillsborough County firms employ many more workers than the Pinellas County firms.Table 4.5 Development Industry Cluster – ES 202 Employment Data Primary Industries: General Building Contractors (SIC 15, Heavy Construction (SIC 16), Special Trade Contractors (SIC 17), and Real Estate (SIC 65) EMPLOYEESNumber of Employees by Average Annualized Wage Hernando Hillsborough Manatee SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 15xxGeneral Building Contractors 31925 475,047 52716179 16xxHeavy Construction 110213 1,5782,861 934268 17xxSpecial Trade Contractors 1,552109 15,2464,760 3,26823 65xxReal Estate 91 978470 60111 Total 2,0723470 17,84913,1380 4,3141,118179 Number of Firms FirmsFirmsFirms Total 422 2,392 616 Number of Employees by Average Annualized Wage Pasco Pinellas Polk SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 15xxGeneral Building Contractors 76020 4,059 1,308506 16xxHeavy Construction 557 1,661455 4712,945 17xxSpecial Trade Contractors 4,875 15,135157 5,976192 65xxReal Estate 44149 718 152 Total 6,2361690 17,5144,6710 7,9073,6430 Number of Firms FirmsFirmsFirms Total 1,527 2,341 1,037 Number of Employees by Average Annualized Wage Sarasota Tampa Bay SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K 15xxGeneral Building Contractors 231,315523 2,50911,688702 16xxHeavy Construction 1,171 6,4826,7420 17xxSpecial Trade Contractors 7,49663 53,5485,3040 65xxReal Estate 39223 2,082730223 Total 8,7291,378746 64,62124,464925 Number of Firms FirmsFirms Total 1,532 9,867

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28 The ES-202 employment and wage data presented above do not include sole proprietors, who do not pay unemployment insurance premiums. Another source, the Regional Economic Information System (REIS) reports employment and income that includes sole proprietors.9 The REIS is the most comprehensive of the federal income and employment data. REIS provides income data broken out by sources other than job earnings (including investment income and transfer payments) and job data beyond wage and salary jobs (including proprietorships and military employment). The collected data are by-products of various federal and state programs, such as unemployment insurance, Social Security, federal income taxes, veterans benefits, and military payroll. The latest REIS information available to us is for the year 1999. REIS provides employment data for industry divisions (1-digit SIC level), such as Division C – Construction or Division H – Finance, Insurance, and Real Estate (FIRE). And, REIS provides income data at the major group level (2-digit SIC level), such as Major Group 15 – General Building Contractors or Major Group 65 – Real Estate. In contrast, the ES-202 data set provides employment data and wage data at the industry level (4-digit SIC level). We compare REIS and ES-202 1999 data sets for Division C Construction in order to examine the role of sole proprietorships in the Development Industry cluster.10Table 4.6 is the comparison of 1999 REIS employment data with 1999 ES-202 employment data for Division C – Construction. We obtain the ES-202 annual employment numbers by taking an average over the four quarters of 1999. The comparison implies that in 1999 approximately 29.56% of persons working in construction in Tampa Bay were sole proprietors. Assuming the percentage has remained stable, we estimate that of the 126,169 persons, who are working in construction in Tampa Bay in 2002, about 37,295 are sole proprietors.11 9 The Bureau of Economic Analysis, U. S. Department of Commerce, collects and publishes the REIS data series.10 A similar comparison for the cluster’s primary industries, which are in Major Group 65 – Real Estate, is not possible because the employment data are aggregated at the Division level.11 See Table 3.1, Section 3, for total employment of 126,169 in the Construction Major Industry Groups in Tampa Bay. The REMITM baseline we use for employment data in Section 3 includes sole proprietors.

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29Table 4.6 Development Industry Cluster Comparison of REIS and ES 202 Employment Data Division C – Construction Source Data:Source Data:Implied SoleImplied % of 1999 REIS1999 ES 202ProprietorsProprietors Number of Persons Working Location Hernando3,0981,5371,56150.39% Hillsborough35,24427,4267,81822.18% Manatee7,8454,4593,38643.16% Pasco7,9605,3152,64533.23% Pinellas28,46320,0448,41929.58% Polk14,2099,9344,27530.09% Sarasota13,8809,2644,61633.26% Tampa Bay110,69977,97932,72029.56% Table 4.7 is a comparison of income and wage data for the construction division of Tampa Bay’s economy. The source of the income data is the 1999 REIS data set; the source of the wage data is 1999 ES-202 data. Income is a different metric from wages. Income is a more comprehensive measure than wages and includes such items as dividends, interest, rents, and royalties. However, probably the most important difference between income and wages for our purpose of comparison is that ES-202 wages do not include benefits received by an employee inkind, such as medical insurance, while income does include the value of in-kind employment benefits. In Panel A of Table 4.7, we report the estimation of an Implied Average Income for a sole proprietor in the construction industries. We find the Implied Average Income by subtracting total ES-202 wages from total REIS income for each location. This yields total Implied Proprietors’ Income, which we then divided by our estimate of the number of sole proprietors, as shown in Table 4.6, to obtain the Implied Average Income per Proprietor. We estimate the Implied Average Income per Proprietor for the construction industries in Tampa Bay to be $32,547 (99 $s). In Panel B of Table 4.7, we compare the Implied Average Income per Proprietor to the average ES-202 wage. We find that in Tampa Bay during 1999, on average, a sole proprietor working in the construction industries had an income that was 109% of the wage of an employee in the construction industries. The proprietor income-to-employee wage differential ranged from 122% in both Manatee County and Sarasota County to 102% in Pinellas County.

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30Table 4.7 Development Industry Cluster – Comparison of REIS and ES 202 Wage/Income Data Division C – Construction Panel A ImpliedImplied Average Source Data:Source Data:Propietors'Income per 1999 REIS1999 ES 202IncomeProprietor Income / Wages (99 $s) Location Hernando$72,026,000$32,575,037$39,450,963$25,273 Hillsborough$1,194,616,000$907,509,863$287,106,137$36,724 Manatee$233,092,000$121,056,845$112,035,155$33,088 Pasco$192,353,000$123,493,671$68,859,329$26,034 Pinellas$853,901,000$597,858,873$256,042,127$30,412 Polk$437,527,000$293,759,331$143,767,669$33,630 Sarasota$417,272,000$259,602,198$157,669,802$34,157 Tampa Bay$3,400,787,000$2,335,855,818$1,064,931,182$32,547 Panel B Implied Average Income per Implied AverageSource Data:Proprietor Income per1999 ES 202relative to ProprietorAvg. WageES 202 Avg. Wage Income / Wages (99 $s) Location Hernando$25,273$21,194119% Hillsborough$36,724$33,089111% Manatee$33,088$27,149122% Pasco$26,034$23,235112% Pinellas$30,412$29,827102% Polk$33,630$29,571114% Sarasota$34,157$28,023122% Tampa Bay$32,547$29,955109% One plausible explanation for the observed differentials is that sole proprietors require a higher rate of payment for services than employees in order to purchase their own benefits package. Another possible explanation is that sole proprietors tend to have more investment income than employees. A third explanation may be that sole proprietors work more hours in a year than employed persons do in the construction industries. Although we are not able to compare REIS and ES-202 data for the real estate industries, anecdotal evidence suggests that the industries also rely on sole proprietors acting as independent agents. Hence, we remind the reader that while the employment structure depicted by Tables 4.1 through 4.5 of this report offers more current information than the latest available REIS data and gives a breakdown to industry level (4-digit SIC) not available from REIS, the picture is incomplete. However, the REMITM model we use for describing the Development Industry

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31 cluster’s baseline in Section 3 and the economic impacts of the cluster in Section 5 does include sole proprietors in its metrics.

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32 Section 5: Economic Contribution of the Development Industry Cluster We assess the economic contribution of the Development Industry cluster using the traditional counter-factual approach. With this approach, we use the REMI TM model to remove the actual output produced by the primary industries of the cluster. (See Table 3.7 for the primary industries’ output.) The model tabulates the direct effects of the removal of the primary economic activities as well as the ripple, or secondary, effects throughout the Tampa Bay economy. We provide three measurements of the economic contribution of the Development Industry cluster: 1) employment, 2) output, and 3) personal income. Table 5.1 reports the contribution measured by employment. Panel A shows total employment in each county and a summation for the Tampa Bay region before the hypothetical removal of the primary industries’ output from the economy. Panel B shows total employment in each county and a summation for the Tampa Bay region after the hypothetical removal of the primary industries’ output from the economy. Panels C and D show the difference in employment before removal and after removal of the primary industries’ output. In Panel C the difference is expressed as thousands of jobs that would be lost. In Panel D the difference is expressed as the percentage of jobs lost from the total employment base after the hypothetical removal of the primary industries’ output from the economy. As expressed in Panels C or D of Table 5.1, the difference in employment measures the economic contribution of the Development Industry cluster In terms of the number of jobs, Hillsborough County benefits most from the economic activities of the Development Industry cluster in Tampa Bay. In Hillsborough County, the cluster contributes slightly over 99,000 jobs.12 As a percentage of total employment, Pasco County benefits most from the economic activities of the Development Industry cluster. In Pasco County, the cluster contributes 16% of total employment. The Development Industry cluster contributes approximately 275,500 jobs, or 12.9% of total employment, to the Tampa Bay region. 12 See Panel C, Table 5.1. Hypothetically, counter-factual removal of the economic output of the primary industries of the Development Industry cluster in 2002 would result in a loss of 99,111 jobs in Hillsborough County. In subsequent years, the model predicts that the employment impact would be lessened by job creation in other industries so that by 2007 the loss in Hillsborough County would be 81,231 jobs from the baseline shown in Panel A, Table 5.1. In all locations, the model predicts that the employment impact will be ameliorated through time.

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33Table 5.1 Development Industry Cluster – REMI Counter-factual Removal of Output Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) EMPLOYMENTPanel A Total Employment before Removal (000s) Location200220032004200520062007 Hernando43.85244.59545.30745.94946.50947.072 Hillsborough783.506798.732814.52829.625845.062861.097 Manatee159.296162.159165.157167.954170.695173.471 Pasco105.737107.122108.435109.637110.764111.969 Pinellas580.113586.852594.073600.892607.839615.298 Polk245.968250.046253.927257.481260.942264.494 Sarasota215.068218.125221.103223.857226.467229.258 Tampa Bay2133.5402167.6312202.5222235.3952268.2782302.659 Panel B Total Employment after Removal (000s) Location200220032004200520062007 Hernando37.92238.79739.66140.47341.18141.829 Hillsborough684.395702.285722.238741.663760.92779.866 Manatee142.369145.747149.363152.79156.04159.214 Pasco88.81890.48792.26393.94595.50596.869 Pinellas505.386515.493526.698537.352547.552557.166 Polk213.775218.339223.168227.777232.16236.391 Sarasota185.389189.828194.236198.31202.026205.642 Tampa Bay1858.0541900.9761947.6271992.312035.3842076.977 Panel C Difference in Employment after Removal (000s) Location200220032004200520062007 Hernando-5.930-5.798-5.646-5.476-5.328-5.243 Hillsborough-99.111-96.447-92.282-87.962-84.142-81.231 Manatee-16.927-16.412-15.794-15.164-14.655-14.257 Pasco-16.919-16.635-16.172-15.692-15.259-15.100 Pinellas-74.727-71.359-67.375-63.540-60.287-58.132 Polk-32.193-31.707-30.759-29.704-28.782-28.103 Sarasota-29.679-28.297-26.867-25.547-24.441-23.616 Tampa Bay-275.486-266.655-254.895-243.085-232.894-225.682 Panel D Difference in Employment after Removal (% change) Location200220032004200520062007 Hernando-13.52%-13.00%-12.46%-11.92%-11.46%-11.14% Hillsborough-12.65%-12.08%-11.33%-10.60%-9.96%-9.43% Manatee-10.63%-10.12%-9.56%-9.03%-8.59%-8.22% Pasco-16.00%-15.53%-14.91%-14.31%-13.78%-13.49% Pinellas-12.88%-12.16%-11.34%-10.57%-9.92%-9.45% Polk-13.09%-12.68%-12.11%-11.54%-11.03%-10.63% Sarasota-13.80%-12.97%-12.15%-11.41%-10.79%-10.30% Tampa Bay-12.91%-12.30%-11.57%-10.87%-10.27%-9.80%

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34 Table 5.2 reports the contribution measured by output. Panel A shows total output in each county and a summation for the Tampa Bay region before the hypothetical removal of the primary industries’ output from the economy. Panel B shows total output in each county and a summation for the Tampa Bay region after the hypothetical removal of the primary industries’ output from the economy. Panels C and D show the difference in output before removal and after removal of the primary industries’ output. In Panel C the difference is expressed as output that would be lost. In Panel D the difference is expressed as the percentage of output lost from total output after the hypothetical removal of the primary industries’ output from the economy. As expressed in Panels C or D of Table 5.2, the difference in output measures the economic contribution of the Development Industry cluster In terms of output, Hillsborough County benefits most from the economic activities of the Development Industry cluster in Tampa Bay. In Hillsborough County, the cluster contributes slightly over $10 billion of output. As a percentage of total output, Pasco County benefits most from the economic activities of the Development Industry cluster. In Pasco County, the cluster contributes over 21% of total output. The Development Industry cluster contributes approximately $27 billion of output, or 16.5% of total output, to the Tampa Bay region. Table 5.3 reports the contribution measured by personal income. Panel A shows total personal income (labor & property income) in each county and a summation for the Tampa Bay region before the hypothetical removal of the primary industries’ output from the economy. Panel B shows total personal income (labor & property income) in each county and a summation for the Tampa Bay region after the hypothetical removal of the primary industries’ output from the economy. Panels C and D show the difference in total personal income (labor & property income) before removal and after removal of the primary industries’ output. In Panel C the difference is expressed as income that would be lost. In Panel D the difference is expressed as the percentage of income lost from total personal income after the hypothetical removal of the primary industries’ output from the economy. As expressed in Panels C or D of Table 5.2, the difference in personal income measures the economic contribution of the Development Industry cluster In terms of personal income, Hillsborough County benefits most from the economic activities of the Development Industry cluster in Tampa Bay. In Hillsborough County, the cluster contributes over $4.3 billion of income. As a percentage of total personal income, Pasco County benefits most from the economic activities of the Development Industry cluster. In Pasco County, the cluster contributes over 18% of total personal income. The Development Industry cluster contributes approximately $10.6 billion of personal income, or 15.14% of total personal income (labor & property income), to the Tampa Bay region.

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35Table 5.2 Development Industry Cluster – REMI Counter-factual Removal of Output Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) OUTPUTPanel A Output before Removal (Bil. 01$) Total Location200220032004200520062007 Hernando2.6782.7642.8522.9273.0023.077 Hillsborough61.82464.02466.19768.28070.49472.719 Manatee12.01312.42812.83013.19613.57513.940 Pasco6.7706.9537.1287.2917.4607.625 Pinellas46.06247.60849.12750.56152.05753.551 Polk19.75720.38820.98821.54022.11122.670 Sarasota14.88115.32515.75816.16416.58617.010 Tampa Bay163.985169.491174.878179.959185.285190.592 Panel B Output after Removal (Bil. 01$) Total Location200220032004200520062007 Hernando2.1522.2462.3402.4272.5132.590 Hillsborough51.72354.07556.55658.97161.46563.904 Manatee10.41010.86211.31511.73912.15612.557 Pasco5.3315.5295.7355.9316.1256.299 Pinellas38.59840.35342.17243.90545.65347.316 Polk16.76317.45318.15218.81819.48320.116 Sarasota11.95412.46512.98613.47613.96514.440 Tampa Bay136.931142.982149.255155.266161.359167.222 Panel C Difference in Output after Removal (Bil. 01$) Location200220032004200520062007 Hernando-0.526-0.518-0.511-0.499-0.489-0.487 Hillsborough-10.101-9.950-9.640-9.309-9.028-8.815 Manatee-1.602-1.566-1.515-1.458-1.419-1.383 Pasco-1.439-1.425-1.393-1.361-1.335-1.325 Pinellas-7.465-7.256-6.956-6.655-6.404-6.235 Polk-2.994-2.935-2.836-2.722-2.628-2.554 Sarasota-2.927-2.859-2.772-2.688-2.621-2.570 Tampa Bay-27.053-26.509-25.623-24.692-23.926-23.370 Panel D Difference in Output after Removal (% change) Location200220032004200520062007 Hernando-19.63%-18.74%-17.93%-17.06%-16.30%-15.83% Hillsborough-16.34%-15.54%-14.56%-13.63%-12.81%-12.12% Manatee-13.34%-12.60%-11.81%-11.05%-10.45%-9.92% Pasco-21.26%-20.49%-19.54%-18.66%-17.90%-17.38% Pinellas-16.21%-15.24%-14.16%-13.16%-12.30%-11.64% Polk-15.15%-14.40%-13.51%-12.64%-11.89%-11.27% Sarasota-19.67%-18.66%-17.59%-16.63%-15.80%-15.11% Tampa Bay-16.50%-15.64%-14.65%-13.72%-12.91%-12.26%

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36Table 5.3 Development Industry Cluster – REMI Counter-factual Removal of Output Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) PERSONAL INCOMEPanel A Personal Income (Total Labor & Property Income) before Removal (Bil. nominal) Location200220032004200520062007 Hernando1.1201.1821.2451.3101.3761.445 Hillsborough28.46930.16531.96033.84535.87838.049 Manatee4.5414.7725.0195.2805.5585.854 Pasco2.7592.8913.0263.1673.3143.472 Pinellas19.49120.44121.45022.51423.65724.881 Polk7.7548.1568.5668.9929.4439.919 Sarasota6.3376.6677.0047.3557.7218.112 Tampa Bay70.47174.27478.27082.46386.94791.732 Panel B Personal Income (Total Labor & Property Income) after Removal (Bil. nominal) Location200220032004200520062007 Hernando0.9480.9991.0551.1161.1781.243 Hillsborough24.15525.56027.25029.10431.13133.286 Manatee3.9684.1694.4074.6664.9435.237 Pasco2.2612.3622.4802.6112.7502.893 Pinellas16.62417.45318.45219.54720.72821.965 Polk6.5646.8797.2477.6518.0858.542 Sarasota5.2845.5845.9166.2716.6427.032 Tampa Bay59.80463.00666.80770.96675.45780.198 Panel C Difference in Personal Income (Labor & Property Inc.) after Removal (Bil. nominal) Location200220032004200520062007 Hernando-0.172-0.183-0.190-0.194-0.198-0.202 Hillsborough-4.314-4.605-4.710-4.741-4.747-4.763 Manatee-0.573-0.603-0.612-0.614-0.615-0.617 Pasco-0.498-0.529-0.546-0.556-0.564-0.579 Pinellas-2.867-2.988-2.998-2.967-2.929-2.916 Polk-1.190-1.277-1.319-1.341-1.358-1.377 Sarasota-1.053-1.083-1.088-1.084-1.079-1.080 Tampa Bay-10.667-11.268-11.463-11.497-11.490-11.534 Panel D Difference in Personal Income (Labor & Property Inc.) after Removal (% change) Location200220032004200520062007 Hernando-15.36%-15.48%-15.26%-14.81%-14.39%-13.98% Hillsborough-15.15%-15.27%-14.74%-14.01%-13.23%-12.52% Manatee-12.62%-12.64%-12.19%-11.63%-11.07%-10.54% Pasco-18.05%-18.30%-18.04%-17.56%-17.02%-16.68% Pinellas-14.71%-14.62%-13.98%-13.18%-12.38%-11.72% Polk-15.35%-15.66%-15.40%-14.91%-14.38%-13.88% Sarasota-16.62%-16.24%-15.53%-14.74%-13.97%-13.31% Tampa Bay-15.14%-15.17%-14.65%-13.94%-13.21%-12.57%

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37 Section 6: Economic Impacts of a Slowdown in Development While the counter-factual approach used in Section 5 provides the means to derive a valid assessment of the total economic contribution of the Development Industry cluster, it does not portray a realistic scenario of a slowdown in regional development. This is so, because the counter-factual approach calls for the complete cessation of the productive activities of the cluster’s primary industries. A complete cessation is most unlikely. Even if development of agricultural acreage or wilderness were proscribed, for example, economic principle tells us that substitute activities, such as remodeling or expansion of existing facilities, would take place. Therefore, rather than simulating a complete cessation, we gauge the regional economy’s expected response to a 20% slowdown in production (output) by the primary industries of the Development Industry cluster. As in Section 5, the measurements of the economic impact of a 20% slowdown are: 1) employment, 2) output, and 3) personal income. Table 6.1 reports the economic impact measured by employment. Panel A shows total employment in each county and a summation for the Tampa Bay region before the 20% slowdown in production by the primary industries of the cluster. Panel B shows total employment in each county and a summation for the Tampa Bay region after the 20% slowdown in production by the primary industries of the cluster. Panels C and D show the difference in employment before slowdown and after slowdown. In Panel C the difference is expressed as thousands of jobs that would be lost. In Panel D the difference is expressed as the percentage of jobs lost from the total employment base after the 20% slowdown in production by the primary industries of the cluster. The loss of jobs, which is reported in Panels C or D of Table 6.1, reflects the aggregated primary and secondary effects. The primary effect is the direct loss of jobs in the construction and real estate industries due to the 20% slowdown in production. The secondary effect, or multiplier effect, is caused by two phenomena. First, jobs are lost in industries that supply goods and services to the construction and real estate industries. Second, lost jobs translate into lost income. And, less income means reduced spending by households and, as a result, more jobs are lost in industries that traditionally provide households with goods and services. In terms of the number of jobs lost, Hillsborough County would experience the greatest economic impact of a 20% slowdown of economic activity in the Development Industry cluster. Hillsborough County loses over 20,000 jobs in the first year of the slowdown. Pinellas County would also experience a severe economic impact losing over 15,000 jobs in the first year. In terms of the percent of total employment lost, Pasco County would experience an economic impact of more than three percent of the jobs in the county lost during the first year of the slowdown.

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38Table 6.1 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) EMPLOYMENTPanel A Total Employment before 20% Slowdown (000s) Location200220032004200520062007 Hernando43.85244.59545.30745.94946.50947.072 Hillsborough783.506798.732814.52829.625845.062861.097 Manatee159.296162.159165.157167.954170.695173.471 Pasco105.737107.122108.435109.637110.764111.969 Pinellas580.113586.852594.073600.892607.839615.298 Polk245.968250.046253.927257.481260.942264.494 Sarasota215.068218.125221.103223.857226.467229.258 Tampa Bay2133.5402167.6312202.5222235.3952268.2782302.659 Panel B Total Employment after 20% Slowdown (000s) Location200220032004200520062007 Hernando42.65643.41644.15644.82145.40445.974 Hillsborough763.391779.088795.599811.408827.411843.817 Manatee155.873158.820161.923164.822167.635170.458 Pasco102.300103.723105.105106.373107.552108.782 Pinellas564.921572.281580.205587.667595.116602.901 Polk239.443243.593247.625251.337254.914258.535 Sarasota209.047212.351215.570218.532221.300224.189 Tampa Bay2077.6312113.2722150.1832184.9602219.3322254.656 Panel C Difference in Employment after 20% Slowdown (000s) Location200220032004200520062007 Hernando-1.196-1.179-1.151-1.128-1.105-1.098 Hillsborough-20.115-19.644-18.921-18.217-17.651-17.280 Manatee-3.423-3.339-3.234-3.132-3.060-3.013 Pasco-3.437-3.399-3.330-3.264-3.212-3.187 Pinellas-15.192-14.571-13.868-13.225-12.723-12.397 Polk-6.525-6.453-6.302-6.144-6.028-5.959 Sarasota-6.021-5.774-5.533-5.325-5.167-5.069 Tampa Bay-55.909-54.359-52.339-50.435-48.946-48.003 Panel D Difference in Employment after 20% Slowdown (% change) Location200220032004200520062007 Hernando-2.73%-2.64%-2.54%-2.45%-2.38%-2.33% Hillsborough-2.57%-2.46%-2.32%-2.20%-2.09%-2.01% Manatee-2.15%-2.06%-1.96%-1.86%-1.79%-1.74% Pasco-3.25%-3.17%-3.07%-2.98%-2.90%-2.85% Pinellas-2.62%-2.48%-2.33%-2.20%-2.09%-2.01% Polk-2.65%-2.58%-2.48%-2.39%-2.31%-2.25% Sarasota-2.80%-2.65%-2.50%-2.38%-2.28%-2.21% Tampa Bay-2.62%-2.51%-2.38%-2.26%-2.16%-2.08%

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39 We estimate that the total impact on employment in the Tampa Bay region would be a loss of nearly 56,000 jobs or 2.62% of the employment base during the first year of the slowdown. Furthermore, we find that five years after the start of the slowdown, employment in Tampa Bay would still be 48,000 jobs below the baseline. Table 6.2 reports the economic impact measured by output per annum. Panel A shows total output in each county and a summation for the Tampa Bay region before the 20% slowdown in output by the primary industries of the cluster. Panel B shows total output in each county and a summation for the Tampa Bay region after the 20% slowdown in output by the primary industries of the cluster. Panels C and D show the difference in output before slowdown and after slowdown. In Panel C the difference is expressed as billions of dollars in output that would be lost. In Panel D the difference is expressed as the percentage of output lost from the total output base after the 20% slowdown in output by the primary industries of the cluster. The loss of output, which is reported in Panels C or D of Table 6.2, reflects the aggregated primary and secondary effects. The primary effect is the 20% direct reduction of output in the construction and real estate industries. The secondary effect, or multiplier effect, is caused by two phenomena. First, sales, i.e. output, are lost in industries that supply goods and services to the construction and real estate industries. Second, lost sales translate into lost income. And, less income means reduced spending by households and, as a result, more sales are lost in industries that traditionally provide households with goods and services. In terms of output lost, Hillsborough County would experience the greatest economic impact of a 20% slowdown of economic activity in the Development Industry cluster. Hillsborough County loses over $2.0 billion in the first year of the slowdown. Pinellas County would also experience a severe economic impact losing over $1.5 billion of output in the first year. In terms of the percent of total output lost, Pasco County would experience an economic impact of more than four percent of output in the county lost during the first year of the slowdown. We estimate that the total impact on output in the Tampa Bay region would be a loss of nearly $5.5 billion of output or 3.34% of the output base during the first year of the slowdown. Furthermore, we find that five years after the start of the slowdown, annual output in Tampa Bay would still be almost $5.0 billion below the baseline. Table 6.3 reports the economic impact measured by personal income (labor & property income) per annum. Panel A shows total personal income in each county and a summation for the Tampa Bay region before the 20% slowdown in output by the primary industries of the cluster. Panel B shows total personal income in each county and a summation for the Tampa Bay region after the 20% slowdown in output by the primary industries of the cluster. Panels C and D show the difference in personal income before slowdown and after slowdown. In Panel C the difference is expressed as billions of dollars in personal income that would be lost. In Panel D the difference is expressed as the percentage of personal income lost from the total personal income base after the 20% slowdown in output by the primary industries of the cluster.

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40Table 6.2 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) OUTPUTPanel A Output before 20% Slowdown (Bil. 01$) Total Location200220032004200520062007 Hernando2.6782.7642.8522.9273.0023.077 Hillsborough61.82464.02466.19768.28070.49472.719 Manatee12.01312.42812.83013.19613.57513.940 Pasco6.7706.9537.1287.2917.4607.625 Pinellas46.06247.60849.12750.56152.05753.551 Polk19.75720.38820.98821.54022.11122.670 Sarasota14.88115.32515.75816.16416.58617.010 Tampa Bay163.985169.491174.878179.959185.285190.592 Panel B Output after 20% Slowdown (Bil. 01$) Total Location200220032004200520062007 Hernando2.5722.6602.7472.8242.9012.974 Hillsborough59.78062.00364.22666.36068.61070.855 Manatee11.69012.11112.51912.89813.27913.649 Pasco6.4806.6646.8437.0107.1807.349 Pinellas44.55046.13147.70249.18250.71352.231 Polk19.15019.79420.40820.97821.56122.129 Sarasota14.28914.74415.19015.61016.03716.465 Tampa Bay158.511164.107169.636174.862180.281185.653 Panel C Difference in Output after 20% Slowdown (Bil. 01$) Location200220032004200520062007 Hernando-0.106-0.104-0.105-0.103-0.101-0.103 Hillsborough-2.044-2.021-1.970-1.919-1.884-1.864 Manatee-0.322-0.317-0.310-0.298-0.296-0.290 Pasco-0.290-0.289-0.285-0.282-0.281-0.276 Pinellas-1.512-1.478-1.425-1.378-1.344-1.320 Polk-0.606-0.594-0.580-0.562-0.550-0.541 Sarasota-0.592-0.581-0.568-0.554-0.549-0.544 Tampa Bay-5.473-5.384-5.243-5.097-5.004-4.939 Panel D Difference in Output after 20% Slowdown (% change) Location200220032004200520062007 Hernando-3.96%-3.76%-3.68%-3.51%-3.35%-3.34% Hillsborough-3.31%-3.16%-2.98%-2.81%-2.67%-2.56% Manatee-2.68%-2.55%-2.42%-2.26%-2.18%-2.08% Pasco-4.29%-4.16%-4.00%-3.86%-3.76%-3.62% Pinellas-3.28%-3.10%-2.90%-2.73%-2.58%-2.46% Polk-3.07%-2.91%-2.76%-2.61%-2.49%-2.39% Sarasota-3.98%-3.79%-3.60%-3.43%-3.31%-3.20% Tampa Bay-3.34%-3.18%-3.00%-2.83%-2.70%-2.59%

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41 The loss of income, which is reported in Panels C or D of Table 6.2, reflects the aggregated primary and secondary effects. The primary effect is the loss of income from the construction and real estate industries due to the 20% slowdown in production. The secondary effect, or multiplier effect, is caused by two phenomena. First, personal income is lost in industries that supply goods and services to the construction and real estate industries. Second, less income means reduced spending by households and, as a result, sales and income are lost in industries that traditionally provide households with goods and services. In terms of income lost, Hillsborough County would experience the greatest economic impact of a 20% slowdown of economic activity in the Development Industry cluster. Hillsborough County loses almost $1.0 billion in the first year of the slowdown. Pinellas County would also experience a severe economic impact, losing about $0.6 billion of income in the first year. In terms of the percent of total personal income lost, Pasco County would experience an economic impact of almost 3.8% of income in the county lost during the first year of the slowdown. We estimate that the total impact on personal income in the Tampa Bay region would be a loss of over $2.2 billion or 3.17% of the personal income base during the first year of the slowdown. Furthermore, we find that five years after the start of the slowdown, annual personal income in Tampa Bay would still be almost 2.78% below the baseline. In summary, we estimate that a 20% slowdown in production by the primary industries of the Development Industry cluster of Tampa Bay would have the following first-year consequences: 1) nearly 56,000 lost jobs, 2) over $5 billion of sales foregone, and 3) over $2 billion of lost income. With 56,000 lost jobs, what other structural changes to Tampa Bay’s economy may be expected? Table C.1, Appendix C, shows the difference in employment by occupation in Tampa Bay after a 20% slowdown in production in the primary industries of the Development Industry cluster. Panel A, Table C.1, lists those occupations that lose more than 1,000 jobs. Not surprisingly, the construction trades suffer the biggest impact with a loss of about 12,640 jobs. Panel B, Table C.1, lists occupations that are expected to lose between 100 and 999 jobs. And, Panel C, Table C.1, lists occupations that are expected to lose less than 100 jobs. Notably, there is no occupation that is expected to gain in jobs as a result of a 20% slowdown in the primary industries of the Development Industry cluster.

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42Table 6.3 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) PERSONAL INCOMEPanel A Personal Income (Total Labor & Property Income) before 20% Slowdown (Bil. nominal) Location200220032004200520062007 Hernando1.1201.1821.2451.3101.3761.445 Hillsborough28.46930.16531.96033.84535.87838.049 Manatee4.5414.7725.0195.2805.5585.854 Pasco2.7592.8913.0263.1673.3143.472 Pinellas19.49120.44121.45022.51423.65724.881 Polk7.7548.1568.5668.9929.4439.919 Sarasota6.3376.6677.0047.3557.7218.112 Tampa Bay70.47174.27478.27082.46386.94791.732 Panel B Personal Income (Total Labor & Property Income) after 20% Slowdown (Bil. nominal) Location200220032004200520062007 Hernando1.0841.1431.2041.2681.3331.401 Hillsborough27.56529.18730.94932.81834.84036.998 Manatee4.4224.6444.8885.1485.4245.719 Pasco2.6552.7782.9083.0453.1903.345 Pinellas18.89119.80620.80621.87023.01324.235 Polk7.5057.8858.2838.7029.1469.616 Sarasota6.1176.4366.7697.1177.4817.870 Tampa Bay68.23971.87975.80779.96884.42789.184 Panel C Difference in Personal Income (Labor & Property Inc.) after 20% Slowdown (Bil. nominal) Location200220032004200520062007 Hernando-0.036-0.039-0.041-0.042-0.043-0.044 Hillsborough-0.904-0.978-1.011-1.027-1.038-1.051 Manatee-0.119-0.128-0.131-0.132-0.134-0.135 Pasco-0.104-0.113-0.118-0.122-0.124-0.127 Pinellas-0.600-0.635-0.644-0.644-0.644-0.646 Polk-0.249-0.271-0.283-0.290-0.297-0.303 Sarasota-0.220-0.231-0.235-0.238-0.240-0.242 Tampa Bay-2.232-2.395-2.463-2.495-2.520-2.548 Panel D Difference in Personal Income (Labor & Property Inc.) after 20% Slowdown (% change) Location200220032004200520062007 Hernando-3.21%-3.30%-3.29%-3.21%-3.12%-3.04% Hillsborough-3.18%-3.24%-3.16%-3.03%-2.89%-2.76% Manatee-2.62%-2.68%-2.61%-2.50%-2.41%-2.31% Pasco-3.77%-3.91%-3.90%-3.85%-3.74%-3.66% Pinellas-3.08%-3.11%-3.00%-2.86%-2.72%-2.60% Polk-3.21%-3.32%-3.30%-3.23%-3.15%-3.05% Sarasota-3.47%-3.46%-3.36%-3.24%-3.11%-2.98% Tampa Bay-3.17%-3.22%-3.15%-3.03%-2.90%-2.78%

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43 With the loss of nearly 56,000 jobs in the first year of the slowdown, Tampa Bay’s labor force also shrinks. We anticipate that in the first year the labor force would decline by about 11,000 workers. Although the labor force begins to grow again in the second year after a slowdown, the trend continues to be below the baseline. Table 6.4 depicts the labor force. Panel A shows the total labor force in each county and a summation for the Tampa Bay region before the 20% slowdown in output by the primary industries of the cluster. Panel B shows the total labor force in each county and a summation for the Tampa Bay region after the 20% slowdown in output by the primary industries of the cluster. Panels C and D show the difference in the size of the labor force before slowdown and after slowdown. In Panel C the difference is expressed in thousands of workers that would be lost from the labor force. In Panel D the difference is expressed as the percentage decline from the labor force baseline after the 20% slowdown in output by the primary industries of the cluster. We find that a 20% slowdown in production by the primary industries of the Development Industry cluster would have a significant impact on economic migration into the Tampa Bay region. Table 6.5 depicts economic in-migration.13 Panel A shows anticipated yearly economic in-migration for each county and a summation for the Tampa Bay region before the 20% slowdown in output by the primary industries of the cluster. Panel B shows anticipated yearly economic in-migration for each county and a summation for the Tampa Bay region after the 20% slowdown in output by the primary industries of the cluster. Panels C and D show the difference in the number of anticipated economic in-migrants before slowdown and after slowdown. In Panel C the difference is expressed in thousands of previously anticipated economic in-migrants who would not come to Tampa Bay. In Panel D the difference is expressed as the percentage decline of anticipated economic in-migrants from the baseline after the 20% slowdown in output by the primary industries of the cluster. The principal reason for the decline of in-migration to Tampa Bay is a reduction in the relative employment opportunity. In the first year of a slowdown approximately 11,800 fewer economic migrants (15.9% less in-migrants) will move into the Tampa Bay region than previously anticipated. 13 Economic migrants are persons under age 65 (who were part of the civilian population of the US the proceeding year) who respond to economic and / or amenity factors by moving into a region. The relative employment opportunity, the real relative wage rate, the relative wage mix and an amenity factor determine the rate of economic migration.

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44Table 6.4 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) LABOR FORCEPanel A Total Labor Force before 20% Slowdown (000s) Location200220032004200520062007 Hernando53.12454.34255.57556.74058.05059.286 Hillsborough549.669564.210578.586592.488606.332620.283 Manatee135.562139.347142.963146.358149.755153.015 Pasco171.525176.562181.326185.789190.315194.502 Pinellas481.769491.664501.114509.960518.828527.569 Polk235.083240.970246.752252.217257.712263.035 Sarasota156.769160.790164.633168.236171.859175.324 Tampa Bay1783.5011827.8851870.9491911.7881952.8511993.014 Panel B Total Labor Force after 20% Slowdown (000s) Location200220032004200520062007 Hernando52.78653.73954.81355.86557.08958.258 Hillsborough546.326557.941570.483583.063595.942609.164 Manatee134.769137.874141.067144.159147.333150.426 Pasco170.328174.385178.557182.600186.819190.770 Pinellas478.748486.105493.998501.765509.877518.071 Polk233.729238.449243.479248.387253.459258.449 Sarasota155.741158.952162.312165.565168.931172.200 Tampa Bay1772.4271807.4451844.7091881.4041919.4501957.338 Panel C Difference in Labor Force after 20% Slowdown (000s) Location200220032004200520062007 Hernando-0.338-0.603-0.762-0.875-0.961-1.028 Hillsborough-3.343-6.269-8.103-9.425-10.390-11.119 Manatee-0.793-1.473-1.896-2.199-2.422-2.589 Pasco-1.197-2.177-2.769-3.189-3.496-3.732 Pinellas-3.021-5.559-7.116-8.195-8.951-9.498 Polk-1.354-2.521-3.273-3.830-4.253-4.586 Sarasota-1.028-1.838-2.321-2.671-2.928-3.124 Tampa Bay-11.074-20.440-26.240-30.384-33.401-35.676 Panel D Difference in Labor Force after 20% Slowdown (% change) Location200220032004200520062007 Hernando-0.64%-1.11%-1.37%-1.54%-1.66%-1.73% Hillsborough-0.61%-1.11%-1.40%-1.59%-1.71%-1.79% Manatee-0.58%-1.06%-1.33%-1.50%-1.62%-1.69% Pasco-0.70%-1.23%-1.53%-1.72%-1.84%-1.92% Pinellas-0.63%-1.13%-1.42%-1.61%-1.73%-1.80% Polk-0.58%-1.05%-1.33%-1.52%-1.65%-1.74% Sarasota-0.66%-1.14%-1.41%-1.59%-1.70%-1.78% Tampa Bay-0.62%-1.12%-1.40%-1.59%-1.71%-1.79%

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45Table 6.5 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) ECONOMIC IN-MIGRATIONPanel A Economic In-migrants before 20% Slowdown (000s) Location200220032004200520062007 Hernando2.8802.7722.7122.6582.5572.462 Hillsborough20.32819.04718.09717.36916.92316.642 Manatee6.8696.2645.8425.4625.1024.798 Pasco8.4177.6227.0666.6056.1775.877 Pinellas16.97915.51014.66514.02013.57313.331 Polk9.4708.7768.2057.6467.1486.724 Sarasota9.4778.7548.3107.8847.4677.115 Tampa Bay74.42068.74564.89761.64458.94756.949 Panel B Economic In-migrants after 20% Slowdown (000s) Location200220032004200520062007 Hernando2.5482.3512.4222.4122.3512.287 Hillsborough16.51714.22314.74114.64314.72214.851 Manatee6.0555.2345.1254.8774.6294.413 Pasco7.2416.1326.0465.7595.485.297 Pinellas13.83411.58711.95511.88211.89712.004 Polk7.976.8416.8136.4796.1725.901 Sarasota8.4247.4377.4217.1536.876.623 Tampa Bay62.58953.80554.52353.20552.12151.376 Panel C Difference of Economic In-migrants after 20% Slowdown (000s) Location200220032004200520062007 Hernando-0.332-0.421-0.290-0.246-0.206-0.175 Hillsborough-3.811-4.824-3.356-2.726-2.201-1.791 Manatee-0.814-1.030-0.717-0.585-0.473-0.385 Pasco-1.176-1.490-1.020-0.846-0.697-0.580 Pinellas-3.145-3.923-2.710-2.138-1.676-1.327 Polk-1.500-1.935-1.392-1.167-0.976-0.823 Sarasota-1.053-1.317-0.889-0.731-0.597-0.492 Tampa Bay-11.831-14.940-10.374-8.439-6.826-5.573 Panel D Difference of Economic In-migrants after 20% Slowdown (% change) Location200220032004200520062007 Hernando-11.53%-15.19%-10.69%-9.26%-8.06%-7.11% Hillsborough-18.75%-25.33%-18.54%-15.69%-13.01%-10.76% Manatee-11.85%-16.44%-12.27%-10.71%-9.27%-8.02% Pasco-13.97%-19.55%-14.44%-12.81%-11.28%-9.87% Pinellas-18.52%-25.29%-18.48%-15.25%-12.35%-9.95% Polk-15.84%-22.05%-16.97%-15.26%-13.65%-12.24% Sarasota-11.11%-15.04%-10.70%-9.27%-8.00%-6.91% Tampa Bay-15.90%-21.73%-15.99%-13.69%-11.58%-9.79%

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46 Economic migrants are a subset of all migrants. Table 6.6 depicts in-migration whether motivated by economic factors or otherwise. Panel A shows anticipated yearly in-migration for each county and a summation for the Tampa Bay region before the 20% slowdown in output by the primary industries of the cluster. Panel B shows anticipated yearly in-migration for each county and a summation for the Tampa Bay region after the 20% slowdown in output by the primary industries of the cluster. Panels C and D show the difference in the number of anticipated in-migrants before slowdown and after slowdown. In Panel C the difference is expressed in thousands of previously anticipated in-migrants who would not come to Tampa Bay. In Panel D the difference is expressed as the percentage decline of anticipated in-migrants from the baseline after the 20% slowdown in output by the primary industries of the cluster. Compare the difference in in-migrants (Table 6.6, Panel C) with the difference in economic in-migrants (Table 6.5, Panel C). Note that almost the entire decline of in-migration is due to a decline in economic in-migration. This observation implies that non-economic inmigration, such as retired persons (age 65 or older), will be little affected by a slowdown in production by the primary industries of the Development Industry cluster. In the previous discussion of this Section of our report, we have described the economic impact of a 20% slowdown in production in the primary industries of the Development Industry cluster. The economic impact manifests itself and is measured by changes in employment, output and personal income. We also described how the slowdown motivates structural changes in Tampa Bay’s economy. Thus far, we examined changes in the labor force and migration into the Tampa Bay region. Now, we further examine structural changes to the region’s economy through differences from the baseline in population and out-migration. Table 6.7 reports population. Panel A shows total population in each county and a summation for the Tampa Bay region before the 20% slowdown in output by the primary industries of the cluster. Panel B shows total population in each county and a summation for the Tampa Bay region after the 20% slowdown in output by the primary industries of the cluster. Panels C and D show the difference in population before slowdown and after slowdown. In Panel C the difference is expressed in thousands of people. In Panel D the difference is expressed as the percentage of people lost from the total population baseline after the 20% slowdown in output by the primary industries of the cluster. In the first year, we estimate that Tampa Bay’s population would be about 11,950 less than if there were no slowdown. The reduction in population is almost entirely due to a decline in the number of economic in-migrants, who quickly recognize the relative decline in employment opportunities in the region. (See from Panel C, Table 6.5 that the difference in economic in-migrants in year 2002 is close to the difference in population.)

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47Table 6.6 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) IN-MIGRATIONPanel A In-migrants before 20% Slowdown (000s) Location200220032004200520062007 Hernando3.4633.3423.2703.2013.0962.993 Hillsborough25.74624.35723.30522.48321.95021.579 Manatee7.8047.1816.7426.3465.9805.671 Pasco8.3227.5086.9266.4295.9985.697 Pinellas17.55816.04715.16114.47213.99513.727 Polk11.42910.70610.1129.5339.0228.583 Sarasota10.5559.8049.3338.8798.4558.095 Tampa Bay84.87778.94574.84971.34368.49666.345 Panel B In-migrants after 20% Slowdown (000s) Location200220032004200520062007 Hernando3.1312.9212.9792.9552.892.817 Hillsborough21.93519.53419.9519.75819.7519.79 Manatee6.996.1516.0265.7615.5075.286 Pasco7.1476.0185.9065.5845.3015.117 Pinellas14.41412.12512.45112.33512.3212.402 Polk9.9298.7728.728.3668.0477.76 Sarasota9.5028.4878.4448.1487.8587.603 Tampa Bay73.04864.00864.47662.90761.67360.775 Panel C Difference of In-migrants after 20% Slowdown (000s) Location200220032004200520062007 Hernando-0.332-0.421-0.291-0.246-0.206-0.176 Hillsborough-3.811-4.823-3.355-2.725-2.200-1.789 Manatee-0.814-1.030-0.716-0.585-0.473-0.385 Pasco-1.175-1.490-1.020-0.845-0.697-0.580 Pinellas-3.144-3.922-2.710-2.137-1.675-1.325 Polk-1.500-1.934-1.392-1.167-0.975-0.823 Sarasota-1.053-1.317-0.889-0.731-0.597-0.492 Tampa Bay-11.829-14.937-10.373-8.436-6.823-5.570 Panel D Difference of In-migrants after 20% Slowdown (% change) Location200220032004200520062007 Hernando-9.59%-12.60%-8.90%-7.69%-6.65%-5.88% Hillsborough-14.80%-19.80%-14.40%-12.12%-10.02%-8.29% Manatee-10.43%-14.34%-10.62%-9.22%-7.91%-6.79% Pasco-14.12%-19.85%-14.73%-13.14%-11.62%-10.18% Pinellas-17.91%-24.44%-17.87%-14.77%-11.97%-9.65% Polk-13.12%-18.06%-13.77%-12.24%-10.81%-9.59% Sarasota-9.98%-13.43%-9.53%-8.23%-7.06%-6.08% Tampa Bay-13.94%-18.92%-13.86%-11.82%-9.96%-8.40%

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48Table 6.7 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) POPULATIONPanel A Population before 20% Slowdown (000s) Location200220032004200520062007 Hernando135.179137.715140.195142.637145.002147.291 Hillsborough1083.0491114.3841144.9021174.8211204.4241233.865 Manatee285.692292.853299.698306.258312.564318.665 Pasco359.788366.290372.426378.240383.815389.262 Pinellas963.966978.119991.8201005.2741018.7071032.290 Polk517.351530.011542.200553.932565.260576.248 Sarasota349.431357.524365.280372.713379.845386.737 Tampa Bay3694.4563776.8963856.5213933.8754009.6174084.358 Panel B Population after 20% Slowdown (000s) Location200220032004200520062007 Hernando134.842136.949139.127141.307143.448145.540 Hillsborough1079.2091105.6281132.6341159.6261186.7931214.182 Manatee284.871290.981297.072302.999308.774314.425 Pasco358.580363.556368.625373.540378.357383.156 Pinellas960.789970.945981.816992.9781004.5571016.616 Polk515.840526.529537.261547.738557.986568.034 Sarasota348.369355.119361.944368.593375.065381.394 Tampa Bay3682.5003749.7073818.4793886.7813954.9804023.347 Panel C Difference in Population after 20% Slowdown (000s) Location200220032004200520062007 Hernando-0.337-0.766-1.068-1.330-1.554-1.751 Hillsborough-3.840-8.756-12.268-15.195-17.631-19.683 Manatee-0.821-1.872-2.626-3.259-3.790-4.240 Pasco-1.208-2.734-3.801-4.700-5.458-6.106 Pinellas-3.177-7.174-10.004-12.296-14.150-15.674 Polk-1.511-3.482-4.939-6.194-7.274-8.214 Sarasota-1.062-2.405-3.336-4.120-4.780-5.343 Tampa Bay-11.956-27.189-38.042-47.094-54.637-61.011 Panel D Difference in Population after 20% Slowdown (% change) Location200220032004200520062007 Hernando-0.25%-0.56%-0.76%-0.93%-1.07%-1.19% Hillsborough-0.35%-0.79%-1.07%-1.29%-1.46%-1.60% Manatee-0.29%-0.64%-0.88%-1.06%-1.21%-1.33% Pasco-0.34%-0.75%-1.02%-1.24%-1.42%-1.57% Pinellas-0.33%-0.73%-1.01%-1.22%-1.39%-1.52% Polk-0.29%-0.66%-0.91%-1.12%-1.29%-1.43% Sarasota-0.30%-0.67%-0.91%-1.11%-1.26%-1.38% Tampa Bay-0.32%-0.72%-0.99%-1.20%-1.36%-1.49%

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49 As the slowdown continues beyond year 2002, the population difference from the predicted baseline grows larger each year. However, note from Panel C, Table 6.5 (and Panel C, Table 6.6) that the loss of in-migrants peaks in the second year (year 2003) of a slowdown and then the loss gets smaller thereafter. As this occurs, there would also be a significant change in out-migration from the Tampa Bay region. The difference in population would effect the more populous counties, of course. Without a future shock to the regional economy, such as a slowdown in development activities, we expect Hillsborough County’s population to reach about 1,234,000 persons by 2007. With a slowdown, we estimate the 2007 population would be about 19,700 fewer people, or a 1.60% reduction. We also expect Pinellas County’s population to reach about 1,032,000 persons by 2007. With a slowdown, we estimate the 2007 population would be about 15,700 fewer people, or a 1.52% reduction. Without a future shock to the regional economy, we anticipate the Tampa Bay region’s population to be approximately 4,084,000 persons in 2007. With a slowdown in development activities, we estimate the 2007 population would be about 61,000 fewer people, or a 1.49% reduction. The population differences, which were just described above, are due to a large decline of in-migration and a small increase in out-migration. Table 6.8 reports differences from the baseline in population, in-migration and out-migration.14 Panel A shows the difference in population from the baseline after a 20% slowdown. Panel B shows the difference in in-migrants after a 20% slowdown. Panel C shows the difference in out-migrants after a 20% slowdown. To approximate the number of out-migrants we assume that the net effect of births and deaths is zero.15In the first year of the slowdown about 127 more people leave Tampa Bay than would have otherwise out-migrated. This number grows to about 804 additional out-migrants five years after the slowdown began. Over the six years that we model the slowdown scenario, there would be 3,043 additional out-migrants over a baseline of approximately 240,000 persons, or a 1.27% increase of out-migration. In conclusion, we find that a 20% slowdown in the output of the primary industries of the Development Industry cluster would have the following first-year consequences: 1) nearly 56,000 jobs lost, 2) over $5 billion of sales foregone, and 3) over $2 billion of lost income. Over time, structural changes in Tampa Bay’s economy include a diminishing rate of growth of both the population and the labor force. Economic in-migration falls off significantly, while non14 Between 1996 and 2000, net migration for Tampa Bay has averaged 41,030 persons per year. See “Tampa Bay Region: 2001 Economic Market report,” prepared for the Tampa Bay Partnership by the USF Center for Economic Development Research. We estimate that, on average, in-migrants have been outnumbering out-migrants by two-toone. About 40,000 people out-migrated from Tampa Bay annually.15 This is a simplifying assumption. In Tampa Bay, through 1996 to 1999 deaths have slightly exceeded births. The net effect of births and deaths on Tampa Bay’s population, 1996 to 1999, was –975, -527, -771, and –916. See “Tampa Bay Region: 2001 Economic Market report,” prepared for the Tampa Bay Partnership by the USF Center for Economic Development Research.

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50 economic in-migration – such as persons 65 and older – is not affected. Out-migration would increase slightly over the baseline.Table 6.8 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) OUT-MIGRATIONPanel A Difference in Population after 20% Slowdown (000s) Location200220032004200520062007 Hernando-0.337-0.766-1.068-1.330-1.554-1.751 Hillsborough-3.840-8.756-12.268-15.195-17.631-19.683 Manatee-0.821-1.872-2.626-3.259-3.790-4.240 Pasco-1.208-2.734-3.801-4.700-5.458-6.106 Pinellas-3.177-7.174-10.004-12.296-14.150-15.674 Polk-1.511-3.482-4.939-6.194-7.274-8.214 Sarasota-1.062-2.405-3.336-4.120-4.780-5.343 Tampa Bay-11.956-27.189-38.042-47.094-54.637-61.011 Panel B Difference of In-migrants after 20% Slowdown (000s) Location200220032004200520062007 Hernando-0.332-0.421-0.291-0.246-0.206-0.176 Hillsborough-3.811-4.823-3.355-2.725-2.200-1.789 Manatee-0.814-1.030-0.716-0.585-0.473-0.385 Pasco-1.175-1.490-1.020-0.845-0.697-0.580 Pinellas-3.144-3.922-2.710-2.137-1.675-1.325 Polk-1.500-1.934-1.392-1.167-0.975-0.823 Sarasota-1.053-1.317-0.889-0.731-0.597-0.492 Tampa Bay-11.829-14.937-10.373-8.436-6.823-5.570 Panel C Difference of Out-migrants after 20% Slowdown (000s) Location200220032004200520062007 Hernando-0.005-0.008-0.011-0.016-0.018-0.021 Hillsborough-0.029-0.093-0.157-0.202-0.236-0.263 Manatee-0.007-0.021-0.038-0.048-0.058-0.065 Pasco-0.033-0.036-0.047-0.054-0.061-0.068 Pinellas-0.033-0.075-0.120-0.155-0.179-0.199 Polk-0.011-0.037-0.065-0.088-0.105-0.117 Sarasota-0.009-0.026-0.042-0.053-0.063-0.071 Tampa Bay-0.127-0.296-0.480-0.616-0.720-0.804

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51 Appendix A Primary Industries Include Real Estate Agents and Managers Some activities of the Real Estate Agents and Managers (SIC 6531) industry are consistent with a primary industry within the Development Industry cluster. For instance, commercial real estate transactions and activity associated with the sale of new residential structures are consistent with the primary economic activities of firms in the cluster. However, data are not available to quantify the applicable proportion of the Real Estate Agents and Managers industry that applies to the cluster. Thus, the information in this appendix depicts the Development Industry cluster, if the Real Estate Agents and Managers industry were included in toto as a primary industry within the cluster. We apportion the REMITM model’s result from major group 65, Real Estate, to the Real Estate Agents and Managers industry in the same manner as described in Section 3 for the other primary real estate industries. Table A.1 shows estimates of employment by location (place of work) from 2002 to 2007. Panel A shows total employment in each county and a summation of the counties’ employment for the Tampa Bay region. Panel B reflects employment by Real Estate Agents and Managers (SIC 6531) in each county and Tampa Bay. Panel C gives the percentage of total employment contributed by jobs in the Real Estate Agents and Managers industry for each location. About 0.7 percent of the jobs in Tampa Bay are in Real Estate Agents and Managers industry. Among the counties of Tampa Bay, the number of jobs in this industry ranges from approximately 5,700 in Hillsborough County to 218 in Hernando County. Sarasota County has the largest share of its employment (0.84% in 2002) in the industry, while Polk County has the smallest percentage (0.44% in 2002) of its employment in the industry. We expect jobs in the industry in Tampa Bay to increase from about 15,000 in 2002 to 17,500 in 2007.

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52Table A.1 Development Industry Cluster – REMI Baseline Real Estate Agents and Managers (SIC 6531) EMPLOYMENT Panel A Employment (000s) Total Location200220032004200520062007 Hernando43.85244.59545.30745.94946.50947.072 Hillsborough783.506798.732814.52829.625845.062861.097 Manatee159.296162.159165.157167.954170.695173.471 Pasco105.737107.122108.435109.637110.764111.969 Pinellas580.113586.852594.073600.892607.839615.298 Polk245.968250.046253.927257.481260.942264.494 Sarasota215.068218.125221.103223.857226.467229.258 Tampa Bay2133.5402167.6312202.5222235.3952268.2782302.659 Panel B Industry Employment (000s) by Sector > Non-Manufacturing > Real Estate > SIC 6531 Location200220032004200520062007 Hernando0.2180.2250.2320.2390.2470.254 Hillsborough5.6595.8586.0616.2596.4706.679 Manatee1.0471.0811.1171.1501.1851.219 Pasco0.5190.5340.5510.5660.5820.599 Pinellas4.7694.9055.0465.1835.3325.480 Polk1.0811.1181.1561.1911.2281.265 Sarasota1.7991.8461.8951.9421.9912.040 Tampa Bay15.09315.56716.05616.52917.03517.537 Panel C Industry Employment (% of Total) by Sector > Non-Manufacturing > Real Estate > SIC 6531 Location200220032004200520062007 Hernando0.50%0.50%0.51%0.52%0.53%0.54% Hillsborough0.72%0.73%0.74%0.75%0.77%0.78% Manatee0.66%0.67%0.68%0.68%0.69%0.70% Pasco0.49%0.50%0.51%0.52%0.53%0.53% Pinellas0.82%0.84%0.85%0.86%0.88%0.89% Polk0.44%0.45%0.46%0.46%0.47%0.48% Sarasota0.84%0.85%0.86%0.87%0.88%0.89% Tampa Bay0.71%0.72%0.73%0.74%0.75%0.76% Table A.2 shows estimates of output by location from 2002 to 2007. Panel A shows total output in each county and a summation of the counties’ output for the Tampa Bay region. Panel B reflects output by the Real Estate Agents and Managers (SIC 6531) industry in each county and Tampa Bay. Panel C gives the percentage of total output contributed by jobs in the Real Estate Agents and Managers industry for each location.

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53Table A.2 Development Industry Cluster – REMI Baseline Real Estate Agents and Managers (SIC 6531) OUTPUT Panel A Output (Bil. 01$) Total Location200220032004200520062007 Hernando2.6782.7642.8522.9273.0023.077 Hillsborough61.82464.02466.19768.28070.49472.719 Manatee12.01312.42812.83013.19613.57513.940 Pasco6.7706.9537.1287.2917.4607.625 Pinellas46.06247.60849.12750.56152.05753.551 Polk19.75720.38820.98821.54022.11122.670 Sarasota14.88115.32515.75816.16416.58617.010 Tampa Bay163.985169.491174.878179.959185.285190.592 Panel B Output (Bil. 01$) BY Real Estate > SIC 6531 Location200220032004200520062007 Hernando0.0190.0190.0200.0200.0210.022 Hillsborough0.4810.4980.5160.5320.5500.568 Manatee0.0890.0920.0950.0980.1010.104 Pasco0.0440.0450.0470.0480.0500.051 Pinellas0.4060.4170.4290.4410.4530.466 Polk0.0920.0950.0980.1010.1040.108 Sarasota0.1530.1570.1610.1650.1690.174 Tampa Bay1.2841.3241.3661.4061.4491.491 Panel C Output (% of Total) by Real Estate > SIC 6531 Location200220032004200520062007 Hernando0.69%0.69%0.69%0.69%0.70%0.70% Hillsborough0.78%0.78%0.78%0.78%0.78%0.78% Manatee0.74%0.74%0.74%0.74%0.74%0.74% Pasco0.65%0.65%0.66%0.66%0.66%0.67% Pinellas0.88%0.88%0.87%0.87%0.87%0.87% Polk0.47%0.47%0.47%0.47%0.47%0.47% Sarasota1.03%1.02%1.02%1.02%1.02%1.02% Tampa Bay0.78%0.78%0.78%0.78%0.78%0.78% About 0.8 percent of the Tampa Bay economy is generated by the economic activity of the two aforementioned real estate industries. Among the counties of Tampa Bay, output by the Real Estate Agents and Managers (SIC 6531) industry ranges from approximately $481 million in Hillsborough County to $19 million in Hernando County. Slightly over one percent of Sarasota County’s economy depends on the activities of by the Real Estate Agents and Managers (SIC 6531) industry. We expect output in the industry to gradually increase from about $1.3 billion in 2002 to $1.5 billion in 2007 (in constant 2001 $s).

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54 Tables A.3 and A.4 show the baseline contributions of the Development Industry cluster, if the Real Estate Agents and Managers industry were included in toto as a primary industry of the Development Industry cluster. Employment and output measure baseline contributions. Table A.3 shows estimates of employment by location (place of work) from 2002 to 2007. Panel A shows total employment in each county and a summation of the counties’ employment for the Tampa Bay region. Panel B reflects employment in the primary industries of the Development Industry cluster in each county and Tampa Bay. Panel C gives the percentage of total employment contributed by jobs in the primary industries for each location. Approximately 8.04 percent of the jobs in Tampa Bay are in the primary industries of the Development Industry cluster. This is less than a one percent (about 15,000 jobs) increase in the employment baseline, when Real Estate Agents and Managers are added as a primary industry of the cluster. Table A.4 shows estimates of output by location from 2002 to 2007. Panel A shows total output in each county and a summation of the counties’ output for the Tampa Bay region. Panel B reflects output by the primary industries of the Development Industry cluster in each county and Tampa Bay. Panel C gives the percentage of total output contributed by the primary industries for each location.

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55Table A.3 Development Industry Cluster – REMI Baseline Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552), Nonresidential Building Operators (SIC 6512) and Real Estate Agents and Managers (SIC 6531) EMPLOYMENT Panel A Employment (000s) Total Location200220032004200520062007 Hernando43.85244.59545.30745.94946.50947.072 Hillsborough783.506798.732814.52829.625845.062861.097 Manatee159.296162.159165.157167.954170.695173.471 Pasco105.737107.122108.435109.637110.764111.969 Pinellas580.113586.852594.073600.892607.839615.298 Polk245.968250.046253.927257.481260.942264.494 Sarasota215.068218.125221.103223.857226.467229.258 Tampa Bay2133.5402167.6312202.5222235.3952268.2782302.659 Panel B Construction Employment (000s) by Sector > Non-Manufacturing > Construction Industry Employment (000s) by Sector > Non-Manufacturing > Real Estate > SICs 6552 & 6512 & 6531 Location200220032004200520062007 Hernando4.1164.1474.1734.1864.1954.209 Hillsborough58.59659.25459.92960.46061.07761.825 Manatee11.40011.49711.60311.67311.75011.844 Pasco10.72510.76310.79610.79710.79910.833 Pinellas47.07847.28547.51747.66147.88048.227 Polk18.93419.14219.31819.42719.54119.694 Sarasota20.59920.74220.85720.90720.95321.050 Tampa Bay171.447172.830174.193175.110176.196177.682 Panel C Construction Employment (% of Total) by Sector > Non-Manufacturing > Construction Industry Employment (% of Total) by Sector > Non-Manufacturing > Real Estate > SICs 6552 & 6512 & 6531 Location200220032004200520062007 Hernando9.39%9.30%9.21%9.11%9.02%8.94% Hillsborough7.48%7.42%7.36%7.29%7.23%7.18% Manatee7.16%7.09%7.03%6.95%6.88%6.83% Pasco10.14%10.05%9.96%9.85%9.75%9.67% Pinellas8.12%8.06%8.00%7.93%7.88%7.84% Polk7.70%7.66%7.61%7.54%7.49%7.45% Sarasota9.58%9.51%9.43%9.34%9.25%9.18% Tampa Bay8.04%7.97%7.91%7.83%7.77%7.72%

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56Table A.4 Development Industry Cluster – REMI Baseline Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552), Nonresidential Building Operators (SIC 6512) and Real Estate Agents and Managers (SIC 6531) OUTPUT Panel A Output (Bil. 01$) Total Location200220032004200520062007 Hernando2.6782.7642.8522.9273.0023.077 Hillsborough61.82464.02466.19768.28070.49472.719 Manatee12.01312.42812.83013.19613.57513.940 Pasco6.7706.9537.1287.2917.4607.625 Pinellas46.06247.60849.12750.56152.05753.551 Polk19.75720.38820.98821.54022.11122.670 Sarasota14.88115.32515.75816.16416.58617.010 Tampa Bay163.985169.491174.878179.959185.285190.592 Panel B Output (Bil. 01$) Construction Output (Bil. 01$) BY Real Estate > SICs 6552 & 6512 &6531 Location200220032004200520062007 Hernando0.3970.4040.4100.4140.4200.425 Hillsborough6.3476.4886.6126.7286.8647.009 Manatee1.1991.2231.2441.2621.2831.304 Pasco1.0251.0401.0511.0611.0721.086 Pinellas5.0355.1125.1785.2395.3155.400 Polk1.9231.9651.9972.0252.0572.093 Sarasota2.1622.1982.2252.2492.2762.306 Tampa Bay18.08818.43018.71818.97719.28819.623 Panel C Output (% of Total) Construction Output (% of Total) by Real Estate > SICs 6552 & 6512 & 6531 Location200220032004200520062007 Hernando14.84%14.60%14.38%14.15%13.98%13.81% Hillsborough10.27%10.13%9.99%9.85%9.74%9.64% Manatee9.98%9.84%9.70%9.56%9.45%9.36% Pasco15.13%14.95%14.75%14.55%14.38%14.24% Pinellas10.93%10.74%10.54%10.36%10.21%10.08% Polk9.73%9.64%9.52%9.40%9.30%9.23% Sarasota14.53%14.34%14.12%13.91%13.72%13.56% Tampa Bay11.03%10.87%10.70%10.54%10.41%10.30% About 11.03 percent of the Tampa Bay economy is generated by the economic activity of the primary industries of the Development Industry cluster. This is less than a one percent

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57 (about $1.3 billion) increase in the output baseline, when Real Estate Agents and Managers are added as a primary industry of the cluster. Because only some activities of the Real Estate Agents and Managers (SIC 6531) industry are consistent with a primary industry within the Development Industry cluster, we conclude that the effect of omitting a portion of this industry from the cluster’s baseline is small – less than 15,000 jobs and less than $1.3 billion of output. We point out that the omission of a portion of the Real Estate Agents and Managers industry from the cluster will have a downward bias, i.e. the results are not exaggerated, on our examination of the Economic Impact of the Development Industry Cluster in Section 5 of this report.

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58 Appendix B Employment Structure Including Real Estate Agents and Managers Some activities of the Real Estate Agents and Managers (SIC 6531) industry are consistent with a primary industry within the Development Industry cluster. For instance, commercial real estate transactions and activity associated with the sale of new residential structures are consistent with the primary economic activities of firms in the cluster. However, data are not available to quantify the applicable proportion of the Real Estate Agents and Managers industry that applies to the cluster. Thus, the information in this appendix depicts the employment structure of the Development Industry cluster, if Real Estate Agents and Managers were included in toto as a primary industry of the cluster. Table B.1 is an extension of Table 4.4. In Table B.1 the Real Estate Agents and Managers industry (SIC 6531) is aggregated with Operators of Nonresidental Buildings (SIC 6512) and Land Subdividers and Developers (SIC 6552). Table B.1 reveals that the 2,773 Tampa Bay firms in these three real estate industries of interest were employing 13,532 workers during 2nd Quarter 2001. Employers were paying annualized wages of less than $35,000 to 9,336 workers (69%), annualized wages between $35,000 and $60,000 to 3,973 workers (29%), and annualized wages over $60,000 to 223 workers (2%). All of the 223 employees earning an annualized wage over $60,000 work for firms based in Sarasota County in the Land Subdividers and Developers industry. All employees in the Real Estate Agents and Managers industry in Tampa Bay were being paid less than $35,000 in annualized wages – except in Hillsborough County where annualized wages were at the $35,000 to $60,000 level.

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59Table B.1 Development Industry Cluster – ES 202 Employment Data Primary Industries: Real Estate (SIC 65) EMPLOYEESNumber of Employees by Average Annualized Wage Hernando Hillsborough Manatee SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 6512Operators of Nonresidential Buildings 11 978 60 6531Real Estate Agents & Managers 170 3,243 581 6552Land Subdividers & Developers 80 470 111 TotalReal Estate 26100 9783,7130 6411110 Number of Firms FirmsFirmsFirms TotalReal Estate 57 781 169 Number of Employees by Average Annualized Wage Pasco Pinellas Polk SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 6512Operators of Nonresidential Buildings 44 440 45 6531Real Estate Agents & Managers 559 3,828 804 6552Land Subdividers & Developers 149 278 107 TotalReal Estate 6031490 4,54600 95600 Number of Firms FirmsFirmsFirms TotalReal Estate 193 872 246 Number of Employees by Average Annualized Wage Sarasota Tampa Bay SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K 6512Operators of Nonresidential Buildings 39 1,61700 6531Real Estate Agents & Managers 1,312 7,2543,2430 6552Land Subdividers & Developers 223 465730223 TotalReal Estate 1,3510223 9,3363,973223 Number of Firms FirmsFirms TotalReal Estate 455 2,773

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60 Table B.2 shows the employment structure of the Development Industry cluster, if the Real Estate Agents and Managers industry were included in toto as a primary industry of the Development Industry cluster.Table B.2 Development Industry Cluster – ES 202 Employment Data Primary Industries: General Building Contractors (SIC 15), Heavy Construction (SIC 16), Special Trade Contractors (SIC 17), and Real Estate (SIC 65) EMPLOYEESNumber of Employees by Average Annualized Wage Hernando Hillsborough Manatee SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 15xxGeneral Building Contractors 31925 475,047 52716179 16xxHeavy Construction 110213 1,5782,861 934268 17xxSpecial Trade Contractors 1,552109 15,2464,760 3,26823 65xxReal Estate 261 9783,713 641111 Total 2,2423470 17,84916,3810 4,8951,118179 Number of Firms FirmsFirmsFirms Total 471 3,047 757 Number of Employees by Average Annualized Wage Pasco Pinellas Polk SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K<$35K$35-60K>$60K 15xxGeneral Building Contractors 76020 4,059 1,308506 16xxHeavy Construction 557 1,661455 4712,945 17xxSpecial Trade Contractors 4,875 15,135157 5,976192 65xxReal Estate 603149 4,546 956 Total 6,7951690 21,3424,6710 8,7113,6430 Number of Firms FirmsFirmsFirms Total 1,687 3,079 1,249 Number of Employees by Average Annualized Wage Sarasota Tampa Bay SICDescription<$35K$35-60K>$60K<$35K$35-60K>$60K 15xxGeneral Building Contractors 231,315523 2,50911,688702 16xxHeavy Construction 1,171 6,4826,7420 17xxSpecial Trade Contractors 7,49663 53,5485,3040 65xxReal Estate 1,351223 9,3363,973223 Total 10,0411,378746 71,87527,707925 Number of Firms FirmsFirms Total 1,928 12,218

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61 Table B.2 is a summation of the number of employees by average annual wages and the number of firms in the primary industries of the Development Industry cluster (including Real Estate Agents and Managers) in Tampa Bay. In 2nd Quarter of 2001, there were 12,218 firms employing 100,507 workers. These employers were paying 72% of the workers annualized wages less than $35,000, almost 28% of the workers annualized wages between $35,000 and $60,000, and under 1% of the workers annualized wages over $60,000.

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62 Appendix C Difference in Employment by Occupation Table C.1 shows the difference in employment by occupation in Tampa Bay after a 20% slowdown in production by the primary industries of the Development Industry cluster. Panel A, Table C.1, lists those occupations that lose more that 1,000 jobs. Not surprisingly, the construction trades suffer the biggest impact with a loss of about 12,640 jobs. Panel B, Table C.1, lists occupations that are expected to lose between 100 and 999 jobs. And, Panel C, Table C.1, lists occupations that are expected to lose less than 100 jobs. Notably, there is no occupation that is expected to gain in jobs as a result of a 20% slowdown in the primary industries of the Development Industry cluster.Table C.1 Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) EMPLOYMENT BY OCCUPATION Tampa Bay Panel ADifference in Employment after Slowdown (000s) More than 1,000 Lost Jobs Occupation200220032004200520062007 Construction trades-12.640-12.510-12.320-12.090-11.900-11.760 Managerial & administration-4.908-4.791-4.636-4.489-4.374-4.300 Help, laborers & mat movers hand-4.878-4.742-4.578-4.414-4.273-4.169 Other cleric & admin support workers-2.808-2.738-2.637-2.546-2.479-2.441 Food prep and service-2.001-1.859-1.704-1.569-1.467-1.403 Blue collr wrker supervisors-1.731-1.706-1.670-1.632-1.601-1.581 Management support-1.633-1.599-1.545-1.494-1.455-1.433 Secretar, stenog & typists-1.577-1.517-1.443-1.373-1.314-1.269 Other mech, inst & rep-1.458-1.437-1.407-1.376-1.351-1.336 Motor vehicle operators-1.391-1.342-1.281-1.222-1.174-1.141 Fin records processing-1.306-1.249-1.185-1.125-1.074-1.035 All other sales & rel wrkrs-1.249-1.171-1.083-1.002-0.935-0.887 Mach&rel mech, inst & rep-1.246-1.247-1.237-1.226-1.220-1.220 Gard, nurs, greenhse, lawn serv-1.130-1.122-1.105-1.087-1.074-1.067 Clean & blding serv, ex priv hh-1.128-1.075-1.011-0.954-0.910-0.879 Salespersons, retail-1.078-1.009-0.931-0.860-0.805-0.767 Material rec, sched, disp & distr-1.002-0.937-0.862-0.794-0.739-0.699

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63Table C.1 (continued) Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) EMPLOYMENT BY OCCUPATION Tampa Bay Panel BDifference in Employment after Slowdown (000s) 100 to 999 Lost Jobs Occupation200220032004200520062007 Cashiers-0.855-0.800-0.738-0.683-0.640-0.612 Protective service-0.653-0.748-0.804-0.852-0.895-0.937 Information clerks-0.621-0.599-0.572-0.551-0.536-0.530 Hand wrkrs, incl assemb&fabricat-0.606-0.553-0.496-0.445-0.403-0.372 Material moving equip oper-0.589-0.577-0.562-0.547-0.534-0.526 Comput, math & oper res-0.571-0.554-0.525-0.496-0.472-0.458 Mktng & sales worker suprvisrs-0.548-0.517-0.482-0.451-0.426-0.410 Engin & scienc tech & technol-0.516-0.494-0.467-0.441-0.420-0.405 Vhicle&mobile equip mech & rep-0.469-0.448-0.424-0.403-0.386-0.375 Engineers-0.462-0.442-0.418-0.394-0.375-0.362 Personal service-0.441-0.401-0.361-0.329-0.308-0.296 Teachers, librarians, couns-0.428-0.483-0.514-0.542-0.569-0.598 Tech, xcpt hlth, engin & scienc-0.383-0.366-0.344-0.324-0.308-0.297 Oth mach setters&oper&tnders-0.367-0.331-0.292-0.258-0.230-0.209 All other service wrkrs-0.343-0.332-0.317-0.304-0.294-0.288 Real est agents, brokers & apprais-0.325-0.329-0.329-0.329-0.330-0.331 Writers, artists & entertainers-0.308-0.283-0.256-0.232-0.213-0.200 Adjstrs, investiga & collectors-0.302-0.283-0.262-0.244-0.230-0.221 Private household wrkrs-0.253-0.214-0.177-0.147-0.125-0.109 Recrd processing, xcpt fin-0.249-0.235-0.219-0.204-0.192-0.185 Farm wrkrs-0.235-0.227-0.216-0.206-0.199-0.195 Lawyers-0.214-0.208-0.199-0.191-0.184-0.180 Social, rec & relig wrkrs-0.199-0.215-0.225-0.235-0.247-0.261 Hlth technic & technologists-0.174-0.177-0.180-0.186-0.196-0.211 Counter and rental clerks-0.171-0.159-0.146-0.136-0.128-0.122 All other profes wrkrs-0.165-0.163-0.158-0.152-0.148-0.146 Inspect, tsters & graders precis-0.118-0.106-0.093-0.082-0.073-0.066 All other extraction & rel wrkers-0.116-0.114-0.111-0.108-0.105-0.103 Secur & finan serv sales wrkrs-0.116-0.105-0.094-0.085-0.078-0.073 Veter asst, all other rel wrkrs-0.115-0.112-0.107-0.103-0.100-0.098 Woodwrkrs, precision-0.106-0.102-0.097-0.093-0.089-0.087

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64Table C.1 (continued) Development Industry Cluster – REMI 20% Development Slowdown Primary Industries: Construction Major Industry Groups plus Subdividers and Developers (SIC 6552) and Nonresidential Building Operators (SIC 6512) EMPLOYMENT BY OCCUPATION Tampa Bay Panel CDifference in Employment after Slowdown (000s) – Less than 100 Lost Jobs Occupation200220032004200520062007 Hlth assessmnt & treating-0.094-0.099-0.106-0.117-0.133-0.153 Insurance sales wrkrs-0.087-0.082-0.076-0.071-0.068-0.066 Metal wrkrs, precision-0.085-0.073-0.061-0.050-0.041-0.035 Architects & surveyors-0.083-0.079-0.075-0.071-0.067-0.065 Electr equip mech, inst & rep-0.082-0.075-0.068-0.062-0.057-0.053 Mach tool cut&form oper, met&plast-0.073-0.062-0.050-0.040-0.032-0.026 Mail clerks & messengers-0.073-0.068-0.062-0.058-0.054-0.051 Health service-0.072-0.078-0.085-0.095-0.110-0.128 All other transp&mat mov equip oper-0.070-0.069-0.068-0.066-0.065-0.064 Communic equip operators-0.067-0.060-0.052-0.046-0.040-0.036 Other precision wrkrs-0.065-0.061-0.057-0.053-0.050-0.047 Metal fabricat mach oper-0.064-0.061-0.058-0.055-0.053-0.051 Textile and related oper-0.063-0.055-0.046-0.039-0.034-0.030 Print, binding & rel wrkrs-0.058-0.052-0.046-0.040-0.036-0.032 Comput oper & periph equip oper-0.056-0.050-0.044-0.038-0.034-0.030 Physical scientists-0.049-0.048-0.045-0.043-0.042-0.041 Farm oper & managers-0.048-0.046-0.044-0.043-0.041-0.041 All other plant & syst oper-0.045-0.044-0.042-0.040-0.038-0.037 Food wrkrs, precision-0.042-0.037-0.033-0.029-0.026-0.023 Woodworking mach oper-0.041-0.039-0.036-0.034-0.032-0.030 Supervisors, farm&for&agri rel-0.041-0.041-0.040-0.039-0.039-0.039 Text, appar & furn wrkrs, precis-0.038-0.034-0.029-0.026-0.023-0.021 Social scientists-0.037-0.040-0.041-0.041-0.042-0.043 Assemblers, precision-0.036-0.028-0.020-0.013-0.008-0.003 Life scientists-0.035-0.037-0.037-0.038-0.039-0.039 Commun equip mech, inst & rep-0.033-0.030-0.027-0.024-0.022-0.020 Anim brdrs&trnrs; caretak, ex farm-0.029-0.029-0.027-0.026-0.026-0.026 Forestry & logging-0.026-0.026-0.026-0.025-0.024-0.024 Met&plast process mach oper-0.025-0.020-0.014-0.008-0.004-0.001 Printing wrkrs, precision-0.020-0.019-0.017-0.015-0.013-0.012 Stationary engineers-0.014-0.015-0.015-0.015-0.015-0.016 Health diagnosing-0.014-0.015-0.017-0.020-0.024-0.030 Travel agents-0.010-0.008-0.006-0.005-0.004-0.003 Water&liqu wste trtmnt plant&sys oper-0.008-0.014-0.019-0.022-0.025-0.027 Comb mach tool setters&oper&tnders-0.007-0.006-0.004-0.003-0.002-0.001 Oil and gas extraction-0.007-0.006-0.005-0.005-0.004-0.004 Rail transportation wrkrs-0.006-0.006-0.005-0.005-0.004-0.004 Fish, hunters & trappers-0.006-0.005-0.005-0.005-0.004-0.004 Water transp & rel wrkrs-0.005-0.004-0.003-0.003-0.002-0.002 Num ctrl mach tool oper, met&plast-0.005-0.003-0.002-0.0010.0000.001 Elec pwr gen plant oper&distr&disp-0.004-0.004-0.004-0.004-0.004-0.004 Judges, magis & oth judic wrkrs-0.002-0.005-0.008-0.009-0.011-0.012 Chemic plant & syst oper-0.002-0.002-0.001-0.0010.0000.000 Gas & petro plant & syst-0.002-0.002-0.002-0.001-0.001-0.001 Mining, quarry & tunneling-0.002-0.002-0.001-0.001-0.001-0.001 Post clerks & mail carriers0.0000.0000.0000.0000.0000.000


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