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Tampa Bay economy.
n Vol. 3, no. 2 (fall 2002).
Tampa, Fla. :
b University of South Florida, College of Business Administration, Center for Economic Development Research.
Update on CEDR's Data Center -- From the Editor -- USF Basic Economic Development Course -- The Development Industry Cluster in Tampa Bay -- Fiscal Impacts of the Development Industry Cluster in Tampa Bay -- Follow up Study of Tampa Bay Region High School Graduates -- Hillsborough County Workforce Projections -- Center for Economic Development Research Chart (April 2001-Mar. 2002) -- Tampa Bay Employment Chart (Q3 1999-Q2 2001) -- Center for Economic Development Research Chart (July 2001-June 2002) -- Tampa Bay Employment Chart (Q4 1999-Q3 2001)
Tampa Bay Region (Fla.)
x Economic conditions
Tampa Bay Region (Fla.)
Tampa Bay Region (Fla.)
University of South Florida.
Center for Economic Development Research.
Tampa Bay Economy THEJournal of the Center for Economic Development ResearchVolume 3, No. 2 Fall 2002Update On CEDRs Data CenterBy Anand Shah, Database Specialist of the Center for Economic Development Research and Dodson Tong, Data Manager of the Center for Economic Development Research CEDRs on-line Data Center has just recently updated its databases to mid-year 2002. The Zip Code Business Patterns database was added earlier in the year. This data contains the number of business establishments located within a postal ZIP code area throughout Florida. The database also reports the number of employees by industry. The database can be accessed at http://cedr .coba.usf.edu and Query CEDR Databases. The Regional and State database section now includes a folder named ZBP which enables the user to access this type of data. CEDR also has ZIP code business pattern data for 1997 and 1998. For each year, drop-down menus allow the researcher to specify a ZIP code area by name (ordered alphabetically) or by ZIP code (ordered numerically). Additionally, the researcher can specify a ZIP code and a Standard Industrial Classification (SIC) code for the 1997 data. The 1998 data is organized by North American Industry Classification System (NAICS) codes; therefore, for 1998, the researcher specifies a ZIP code and a NAICS code. In the 1997 data, Industrial Divisions are identified by SIC codes ending in -. For example, 52 is the code for the Retail Trade Division, which includes all 4-digit SIC codes between 5200 and 5999. Industrial Divisions are headers for the SIC codes that follow. The headers contain no data themselves. Industry descriptions accompanied by an asterisk represent partially classified establishments. For example, SIC 5600* represents retail apparel and accessory stores that could not be classified into a 4digit SIC category. In a response to a query, the number of Query Results indicates the total number of industries (4-digit SIC codes) located in the specified postal ZIP code area. The query results will be zero if there are no establishments with the specified SIC code located in the ZIP code area. Otherwise the query returns the number of 4-digit SICs with business establishments in the ZIP code. In the 1998 data, NAICS sectors, representing general categories of economic activities, are identified by NAICS codes ending in -. For example, 52 is the code for the Finance & Insurance sector, which includes all 6-digit NAICS codes between 521110 and 525990. These NAICS sectors are headers for the NAICS codes that follow and contain no data themselves. In response to a query, the number of Query Results indicates the total number of establishments by 6-digit NAICS codes that are located in the specified postal ZIP code area. The query results will be zero if there are no establishments with the specified NAICS code located in the ZIP code area. Otherwise, the query returns the number of specified NAICS with business establishments in the ZIP code. Most economic activity is covered by this data set. However, data are not included for self-employed persons, domestic service workers, railroad employees, farm workers, most government employees, maritime workers on ocean-going vessels, and persons working outside the U.S. ZIP code Business Patterns data items are extracted from the Standard Statistical Establishments List, a file of all known single and multi-establishment firms. The list is maintained and updated by the U.S. Bureau of the Census. CEDR has developed and provided ZIP code maps for each of Floridas Countys that will help the researcher identify and define a local area of interest. ZIP Code Business Patterns maps are now available for 1997 and 1998, which are a graphical representation of the data. In conjunction to this ZIP Code Business Patterns data, maps for 1999 ZIP code boundaries are also made available. In addition to the ZIP code business patterns data, the Regional and State database section continues to make available the following: Cost of Living This data set provides relative costs of living for Floridas 67 counties and is released annually by the Florida Department of Education. The average cost of living in a given year (1993 to 2001) among Floridas 67 counties is set at 100% and then each Florida Countys relative cost of living is expressed relative to 100%. Education Indicators The indicators in the data set are graduation rates, drop out rates, SAT scores, average class size, and per pupil expenditures for Floridas public high schools. The Florida Department of Education distributes the data. CEDR presents the data organized by county and covering four academic years beginning with 1996-1997. Continued on page 19
2 Volume 3, No. 2 Fall 2002Dr. Dennis Colie............. ............................Director Dodson Tong .....................................Data Manager Alex McPherson ...................................... Economist Danny Hughes.........................................Economist Nolan Kimball ...................................Coordinator of Information/Publications Anand Shah ........................................W eb Designer David Sobush..............................Graduate AssistantCEDR StaffFrom The Editor. .This issue of The Tampa Bay Economy features an analysis of the Tampa Bay regions high school graduates based on the Florida Education and Training Placement Information Program. Also, there are two related articles regarding the development industry of Tampa Bay. They are titled Fiscal Impacts of the Development Industry Cluster in Tampa Bay and Development Industry Cluster in Tampa Bay. And this issue contains an article titled, Hillsborough County Workforce Projections contributed by the External Affairs office of Hillsborough Community College. Regional economic development data inserts for both 1st and 2nd quarters of 2002, an Update on CEDRs Data Center and an article about the upcoming USF Economic Development Course round out the contents for this issue. As always, we ask you, the journals reader, to help us make the journal add even more value to Tampa Bays economic development community. Please send us your comments and suggested improvements to: email@example.com with subject line Journal Comments.USFs Basic Economic Development CourseBy Nolan Kimball, Coordinator of Information/Publications with the Center for Economic Development Research This year marks the 26th Annual USF Economic Development Course. The course will be held at the Hilton Garden Inn in Ybor City from November 3 8, 2002. Some of the highlights of this years course are: A day at USFs St. Pete Campus Tour of downtown St. Pete and dinner at Dan Marinos Town Tavern at BayWalk Environmental presentation and tour of the Cargill Fertilizers Industrial facility The weeklong course, which is fully accredited by the International Economic Development Council (IEDC), serves as an introduction to economic development. Eighteen universities and one state agency around the U.S. offer the IEDC accredited basic economic development course (BEDC) at different times throughout the year. The course is the first step for anyone planning to become certified in the economic development field. USFs BEDC offers a diverse and experienced faculty, composed of both academicians and practitioners providing an excellent blend of theory and practice. Because participation and discussion are strongly encouraged, the class capacity is 35 people. Update On CEDRs Data Center ............................1 From The Editor .....................................................2 USF Basic Economic Development Course ...........................................2 The Development Industry Cluster in Tampa Bay..........................................3 Fiscal Inpacts of the Development Industry Cluster in Tampa Bay..........................................4 Follow up Study of Tampa Bay Region High School Graduates .......................................5 Hillsborough County Workforce Projections ........................................8 Center For Economic Development Research Chart (Apr. 2001-Mar. 2002)..............9 Tampa Bay Employment Chart (Q3 1999-Q2 2001).................................10 Center For Economic Development Research Chart (July 2001-June 2002).............11 Tampa Bay Employment Chart (Q4 1999-Q3 2001).................................12Table of Contents
3 By Dennis G. Colie, Director of the Center for Economic Development Research, and Alex McPherson, Economist with the Center for Economic Development Research In May 2002, CEDR completed a study of the economic contributions of the Development Industry cluster in the Tampa Bay region. A consortium of local trade associations collectively referred to as the Tampa Bay Regional Coalition commissioned the research. Continued on page 6 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 plus 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 supplier industries or industry groups for 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 policy-insight economic 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 at the time the report was prepared) 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 Defining a ClusterHarvard 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, Porters 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 industrys products and services. 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 wit h informed domestic customers, and the traditional country-specific factor cost and supply conditions. Porter calls the grouping of an industry along with its upstream suppliers and downstream customers an industry cluster.The Development Industry Cluster in Tampa BayWe begin 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 supplier-industries. 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.
4Fiscal Impacts of the Development Industry Cluster in Tampa BayBy Dennis G. Colie, Ph.D., Director of the Center for Economic Development Research While an accompanying article, The Development Industry Cluster in Tampa Bay, in this issue of The Tampa Bay Economy describes a recent analysis of the economic impacts of the cluster, a similar analysis of fiscal impacts is also revealing. An impact is the consequence of a well-defined change in structure of a regional economy. An economic impact refers to a change in production, distribution and consumption within a region. A fiscal impact refers to a change in governments revenues and expenditures due a change occurring within a region. The change in structure that causes the impact could be, for example, the relocation of a business into the region. We often use the principles of economic impact analysis to estimate the economic contribution of a firm, industry, or industry cluster to a regional economy. When doing so, we employ a counter-factual approach. That is, we virtually remove all of the economic activity of the firm, industry or cluster from the region using a computer-based model. The impact of the removal of the economic activity provides an estimate of the economic contribution to the region. Usually, we measure and report the contribution in terms of employment, output and income. Table 1 shows the differences in local revenues (Panel A) and expenditures (Panel B) due to a 20% slowdown of the economic activity of the Development Industry Cluster. We estimate that during its first year the slowdown would cause a loss of $104.4 million of revenue to local governments throughout Tampa Bay. At the same time expenditures would drop by $143.6 million. Therefore, we estimate that the net fiscal impact (difference in revenues minus difference in expenditures) on local governments would be approximately +$39.2 million. We could expect property tax revenues for Tampa Bay to fall by $6.8 million in the first year of the slowdown, while expenditures for K through 12 education and libraries would also fall $12.7 million. The slowdown would have the largest fiscal impact on Hillsborough County, where county and municipal governments, as well as other taxing authorities, would be expected to lose $40.3 million in revenues, but decrease expenditures by $55.0 million. The net fiscal impact in Hillsborough County is expected to be +$14.7 million. Continued on page 5 The analysts researching the accompanying article, The Development Industry Cluster in Tampa Bay, used the counterfactual approach to measure and report the economic contribution of the cluster. However, their analysis did not attempt to estimate the fiscal impact of the Development Industry Cluster in Tampa Bay. This article extends the previous research by estimating the fiscal impact of the cluster. Analysts for the accompanying article used the REMITM Policy Insight model to estimate the economic contribution of the cluster. The REMITMmodel is a widely used commercially available structural model. The models structural equations are based on historical economic and demographic data for each of the seven counties that make up the Tampa Bay region. Besides being useful for making economic impact estimates, the REMITM model can also be used to make estimates of fiscal impacts. Currently, however, the historical data of the model is based on statewide averages rather than county-specific data. Thus, we can only interpret an estimate of fiscal impact as a general guide to the differences in governments revenues and expenditures resulting from a change in regional economic structure.
5 Table 2 shows the differences in state revenues (Panel A) and expenditures (Panel B) due to a 20% slowdown of the economic activity of the Development Industry cluster. We estimate that during its first year the slowdown would cause a loss of $212.9 million of revenue to the State of Florida government. At the same time state expenditures would drop by $234.5 million. Therefore, we estimate that the net fiscal impact (difference in revenues minus difference in expenditures) on the State of Florida government would be approximately +$21.6 million. We also estimate that the largest source of a decrease in revenue to the state from the Tampa Bay region would be a $107.5 million decline in general sales tax revenue during the first year of the slowdown. We expect that the largest decrease in use of funds by the state would be $10.5 million of intergovernmental disbursements to local governments. Of the $10.5 million decrease in intergovernmental disbursements, we estimate that local governments of the Tampa Bay region would absorb $9.1 million of the loss in revenues. (See Table 1, Panel A, State Intergovernmental revenues.) Estimates of economic impact measure how people who live or work in a region may be affected by a change in the structure of the regional economy, whereas estimates of fiscal impact measure changes of state and local governments revenues and expenditures due to the structural change. A regional economy is a highly complex structure of flows of goods, services and payments. The REMITM Policy Insight model dynamically simulates the structure of these flows within Tampa Bays regional Continued from page 4 Fiscal Impacts of the Development Industry Cluster in Tampa BayBy David Sobush, Graduate Assistant with the Center for Economic Development Research Editors Note: The author refers to the Tampa Bay Region Economic Market Report This report is prepared annually by the Center for Economic Development Research (CEDR) and is published by the Tampa Bay Partnership. Copies of previous reports can be found at CEDRs website: http://cedr.coba.usf.edu. Previous editions of the Tampa Bay Region Economic Market Report paint a less than rosy picture regarding public secondary education in the area. The education indicators offered in the Continued on page 16 economy. This article about the fiscal impact of the Development Industry cluster is not intended to be an exhaustive study, but illustrates how the model measures the fiscal impact of a change to the local economy.Follow up Study of Tampa Bay Region High School GraduatesMarket Report concentrate on data at the K-12 level. While items such as SAT scores and graduation rates do indeed speak to an areas success or failure to educate, they leave much to be desired. Indicators such as those mentioned above are limited in that they are of a predictive nature, rather than of a representative nature. They attempt to predict how a society will behave in the future. The Florida Department of Education (DOE) established the Florida Education and Training Placement Information Program (FETPIP) as a data collection system to obtain follow-up data
6 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 Departments 1999 (most recent available at the time the report was prepared) 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. 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 clusters 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 economys 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. Continued from page 3 The Development Industry Cluster in Tampa BayContinued on page 7
7 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 (See table 5 on page 8). 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 Bays 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. Continued from page 6 The Development Industry Cluster in Tampa BayContinued on page 8
8 Continued from page 7 The Development Industry Cluster in Tampa BayContinued on page 13 This report focuses on the following questions: 1)What are the top growth industries in Hillsborough County? 2)Based on annual demand, what are the top high-wage jobs for students who complete HCC education and training? 3)How well do HCCs current programs match these high demand, high wage jobs? What are the top growth industries in Hillsborough County? 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 Bays 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. The full text of the report is available for view at CEDRs website, http://cedr.coba.usf.edu, under Recent Projects. Editors note: We thank the authors and John Huerta, vicepresident for External Affairs, Hillsborough Community College, for permission to republish this article in The Tampa Bay Economy. The original version of this article is available at http:/ /www.hccfl.edu/dao/pre. We project the workforce for Hillsborough County through the year 2009 as reported by the State of Florida. (Primary source of data is the Florida Department of Labor and Employment Security, Florida Labor Market Statistics web site at http:// www2.myflorida.com/awi/lms/default.asp) Overview Floridas population is expected to increase by 2.5 million people over the next ten years with total employment growing by 1.7 million for the same period. In Hillsborough County, service industries will dominate job demand with Business Services and Health Services accounting for the majority of the growth. The economy is continuously becoming more knowledge-based and less production-based, placing an increasing emphasis on producing better educated and higher skilled workers to meet employment demands. (See Appendix 1 for more detail.) Purpose Our purpose is to identify the fastest growing industries and the high demand, high-wage occupations over the next several years in Hillsborough County, and to examine how well Hillsborough Community Colleges (HCC) current programs match the projected annual employment demand for this area. Hillsborough County Workforce ProjectionsBy Edwin Goolsby and Jan Schwartz, Department of Planning, Research and Evaluation, Hillsborough Community College
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13 Table 1 shows the top ten growth industries through the year 2009 in Hillsborough County. Included in the table are the projected average annual increase and percentage increase in jobs for each industry. The top three industries, Business Services, Health Services and Local Government, will account for 72% of the annual demand for new workers in Hillsborough County during this period. And, out of these three industries, Business Services and Health Services will account for nearly two-thirds (64.8%) of all new jobs annually in Hillsborough County. Appendix 2 contains information about the number of jobs and annual demand in Hillsborough County for the top five occupations from the top ten industries of Table 1. Based on annual demand, what are the top high-wage jobs for students who complete HCC education and training? Continued from page 8 Hillsborough County Workforce ProjectionsContinued on page 14 The top high demand, high-wage jobs for the county will be in nursing, computer related occupations and some special trades, such as automotive mechanics and electricians. Table 2 reports the top 15 high demand, high-wage occupations, which require post-secondary vocational training (not an Associate in Science degree), ranked by annual demand in Hillsborough County. Annual demand, as shown in the table, includes demand to meet new job growth as well as attrition. Of the top 15 occupations in Table 2, five fall into the Business Services and Health Services related industries. The top three occupations account for almost 60% of annual demand. The annual demand for LPNs accounts for almost one-quarter (23%) of the new jobs among the 15 occupations. Automotive Mechanic (Auto Dealers & Service industry) accounts for 19.7% and Drafter (Business Services) makes up 19.0% of annual demand for new jobs among these occupations. Table 3 (on page 14) reports the top 15 high demand, highwage occupations, which require an A.S. degree, ranked by annual demand in Hillsborough County. Annual demand, as shown in the table, includes demand to meet new job growth as well as attrition. Of the 15 occupations that require an Associate in Science (A.S.) degree, eight are in the Health Services industry. The top two occupations, RN and Computer Support Specialist, account for over 65.7% of annual demand, with the annual demand for RNs accounting for over one-third (35.9%) of the group of occupations requiring an A.S. degree. Computer Support Specialist accounts for 29.7% of annual demand. Table 4 (on page 14) reports the top 15 high demand, highwage occupations, which require a Bachelor of Arts (B.A.) degree. We rank the occupation by annual demand in Hillsborough County. Annual demand, as shown in the table, includes demand to meet new job growth as well as attrition. HCC students who earn an Associate of Arts (A.A.) can transfer to a 4-year college or university to obtain their B.A. degree. Of the occupations in Table 4, seven are in the Business Services industry and four are in the Education Services industry. The top two occupations, Systems Analyst and Computer Programmer, account for over one-third (34.8%) of annual demand. Overall, occupations in Business Services make up 61.6% of annual demand reflected in Table 4, while Education Services make up another 25.6% of the annual demand.
14 How well do HCCs current programs match these high demand, high-wage jobs? HCCs programs currently provide training for many of the high demand, high-wage occupations Table 5 (on page 15) reports the number of completers for academic years 98/99 through 00/01 for occupations with a program designed specifically for them. A completer is a person who successfully completes the requirements for a certificate or a degree in a particular field of study. Panel A, Table 5, shows the number of completers of programs that support four of the top 15 occupations requiring post-secondary vocational training. The Emergency Medical Technician, which is in the Health Services industry, produced the most completers Three hundred seventytwo persons have completed the Emergency Medical Technician program over the most recent three academic years. Panel B, Table 5, shows the number of completers of programs that Continued from page 13 Hillsborough County Workforce ProjectionsContinued on page 15 support the top 15 occupations requiring an A.S. degree. The Registered Nurse (RN), Health Services industry, produced 484 graduates during the last three academic years. Panel C, Table 5, reports that 3,794 graduates received an A.A. degree in the past three academic years. These graduates are eligible to continue their education at a 4-year college or university and to obtain the skills and knowledge needed to support those occupations requiring a B.A. degree. Summary In summary, the top three industries for job growth in Hillsborough County are Business Services, Health Services and Local Government. We expect these three industries to account for approximately 72% of the annual demand for workers in Hillsborough County through the year 2009. The top high demand, highwage jobs for the county will be in nursing, computer related occupations and some special trades, such as automotive mechanics and electricians. HCCs programs currently provide training for many of these high demand, high-wage occupations. However, HCC does not currently have specific programs for all high demand, highwage occupations requiring postsecondary vocational training or an A.S. degree. For example, HCC currently does not offer a specific program for Licensed Practical Nurse (LPN), Automotive Mechanic, and Drafter. These three occupations are projected to account for about 62% of the annual demand for new jobs among those requiring some post-secondary vocational training.
15 Continued from page 14 Hillsborough County Workforce ProjectionsContinued on page 16 Appendices Appendix 1 Trends in the Florida Economy (Hillsborough County is expected to mirror these statewide trends) Population Floridas population is expected to increase by almost 2.5 million over the next ten years; however, this is a much slower growth rate than the two previous decades. Floridas population age will show a decrease in children and youth and a larger proportion of middle age to older people. Minorities and immigrants will see an increase in the percentage of the population. Employment The projected slowdown in population growth will cause overall employment levels to grow more slowly. The states and countys employment will continue its shift towards the service-producing sector and away from the goodsproducing sector. As our economy continues to become more knowledge-based and less production-based, the emphasis on better-educated and higher-skilled workers will continue to grow. Advances in Technology Technological and scientific advances will continue to have a significant impact on industry employment continuing the global economic trend of replacing labor with capital. Computers will be common in almost all industries and occupations. Advances in communications technologies and greater use of the Internet will continue to enhance worker productivity and improve the efficiency of business. Florida Industry Employment Projections Highlights Total, All industries Total employment is projected to grow by nearly 1.7 million over the next ten years with a projected annual growth rate of 2.3 percent. Due to the rapid growth in services, all major industry divisions, except public utilities, transportation and communications, will show a decline in percentage of total employment. Goods-producing Sector Employment growth within this sector will be slow, accounting for only 4.3 percent of the new jobs. Construction will lead this sector with special trade construction contractors (plumbers, electricians, roofers, etc.) accounting for almost 77 percent of new construction jobs. Agriculture, forestry and fishing employment will be the third slowest growing division in this sector. Manufacturing will be the second slowest growing division. Fabricated metals will gain the most jobs while apparel and textile jobs lose the most in this division. Mining will show a net decline in employment within this sector. Service-producing Sector Employment growth will continue to be highly concentrated in this sector, accounting for more than 90 percent of the new jobs created during this period (through 2009). Within this sector, trade and services industries will account for almost eight in ten of the new jobs and provide 70 percent of all new jobs. Transportation, communications and public utilities will be the second fastest-growing major industry in Florida. One-fifth of all new jobs will be in trade with nearly 80 percent of those in retail as population growth and strong consumer spending continue to stimulate the economy. Food stores and eating/drinking establishments will account for more than half of the new retail jobs. Nondepository credit institutions (consumer finance companies, mortgage bankers, etc.) will be the second fastestgrowing industry in this sector. Finance, insurance and real estate will grow more slowly with banking growing the slowest due to increased automation. Business services and health services combined will account for almost 65 percent of the new jobs in this sector; business services will be the fastest growing. Local government will be the fastest growing among government employment; federal government will grow at a much slower rate.
16 Continued from page 15 Hillsborough County Workforce Projections Appendix 2 Fastest growing occupations in Hillsborough County within the top ten industries (Note: several occupations may fit into more than one industry, these are the top five occupations within the listed industry regardless of the education or training required.) Continued from page 5 Follow up Study of Tampa Bay Region High School Graduateson former students. The information includes employment, continuing post-secondary education, military service, public assistance participation, and incarceration data. The expressed goal of the FETPIP is to provide accurate, timely and comprehensive outcome information to Floridas education, workforce development, and social service programs. The information gathered by the FETPIP indicates the current performance of educational services delivered in the past. Individuals T racked The FETPIP is limited in its ability to track individuals. Generally, the FETPIP fails to capture those individuals who move or study out-of-state. A next step for tracking systems such as the FETPIP would be to conduct them on a national basis, thereby increasing the percentage of individuals tracked. Statewide, the FETPIP captured data for 83.60% of year 2000 high school graduates, compared to 81.01% for the Tampa Bay region. Within the Tampa Bay region, Hillsborough County had the largest capture percentage (85.39%), and Pasco County had the lowest capture percentage (79.17%). Historical trends in data capture are displayed below. Continued on page 17
17 Employment The Florida Department of Education tracks wages and earnings by examination of employer tax rolls. Of the individuals tracked, 73.24% earned wages reported on quarterly employer tax rolls during the fourth quarter (October 1st December 31st) of the year 2000. Of these individuals, the DOE reports 64.16% as employed less than full time. An individual is considered as employed full time if they earned at least $2,678 in the quarter of interest. The figure of $2,678 is derived by multiplying the minimum wage ($5.15) by 40 hours per week by 13 weeks per quarter. However, this simple metric might vastly understate the true hourly wages of employees. For example, suppose an individual hired halfway through the quarter earned $2,678 by the end of the quarter. This individual would be included in the group earning between $5.15 and $7.49 per hour, when in fact their true wages would be more than $9.00 per hour. Similarly, reported wages for employees that work more than 40 hours per week (overtime) would be overstated. Earnings by Level Of those employed full time, more than half made less than $7.50 per hour. Hillsborough County had the highest percentage of graduates earning more than $9.00 at 8.67%. Of those earning between $7.50 and $8.99 per hour, Sarasota County had the highest percentage of graduates (9.75%). Of those employed full time and earning less than $7.49 per hour, Manatee County had the highest percentage of graduates. Continued from page 16 Follow up Study of Tampa Bay Region High School GraduatesContinued on page 18 Federal Employment Data Tampa Bay region Class of 2000 graduates filled 737 positions within the Federal Government. Of these 737, 701 are employed by one of the branches of the United States Military (Navy, Marine Corps, Air Force, and Army). Roughly 60% of all Tampa Bay region federal employees (all federal employment) came from either Pinellas or Hillsborough County. Of Floridas 3,664 Class of 2000 graduates that found employment with the Federal Government, 20.11% came from the Tampa Bay region. Continuing Education Data This section details the persons continuing their education in a public post-secondary environment at any level through information provided by the Florida Department of Education. Data is based on fall enrollments. Private college and university enrollments are also captured through the Office of Student Financial Aids voucher system. The persons not captured here do not attend school in Florida. This failure is perhaps the greatest weakness of the current tracking system. Students that enroll in outof-state universities and colleges (both public and private) typically are of high academic ability, and would not be included in this data. However, if the individual went to school out-of-state, but came home and worked during the winter holiday, they would be listed as working less than full time. In this respect, the tracking system would not be viewed as providing an accurate assessment of student or school achievement. Continuing education data is classified by the FETPIP as falling into one of four categories: district post-secondary programs, community/junior college, enrollment at one of the former State University System (SUS) institutions, and/or enrollment at a private college or university located in Florida. Students may be in multiple settings, and therefore the sum of the
18 percentages in each category may exceed the percentage of the whole for a county. District post-secondary programs are typically of a vocational nature and are differentiated from other vocational programs in that they are offered by the local school district. Statewide, 3.61% the of Class of 2000 graduates were enrolled in such a program. In the Tampa Bay region, the percentage was 5.28%. Manatee County had the greatest percentage (10.54%), while Hernando County had the lowest (0.77%). Community and junior colleges are a popular post secondary educational program due to their relative abundance, low cost, and easily transferable credit. Additionally, the Floridas popular Prepaid College Program includes a 2+2 option, where the student spends two years at a community college before transferring to a university. Statewide, 57.12% of the Class of 2000 graduates were enrolled in community college classes, compared to 52.89% of Tampa Bay region graduates. Within the region, Hernando County had the highest percentage of graduates enrolled in community college (64.69%) and Hillsborough County had the lowest (46.27%). Statewide, 37.81% of the Class of 2000 graduates enrolled in one of Floridas 11 public universities. Tampa Bay region graduates enrolled in these universities in greater numbers (40.29%). Within the region, Hillsborough County graduates enrolled at a state university in the greatest numbers (48.00%), and Hernando County graduates enrolled the fewest (28.87%). The Florida Office of Student Financial Aids voucher system provides data on enrollment at in-state private colleges and universities. Graduates from the Tampa Bay region enrolled in private colleges and universities within the state of Florida at roughly the same rate as their counterparts throughout the state, 6.79% to 6.06% respectively. In the Tampa Bay region, Polk County had the greatest percentage of its graduates enroll in private colleges and universities (12.44%), whereas Manatee County graduates enrolled in those institutions the least (4.52%). Public Assistance Many school districts and educators view self-sufficiency of its graduates as a basic goal of an educational system. One possible measure of an inability to provide for ones self or family is the receiving of public assistance such as Temporary Aid to Needy Families (TANF) and/or Food Stamps. Polk County had the highest percentage (3.63%) of its Class of 2000 graduates receive some sort of government assistance, whereas Pasco County had the lowest percentage (0.98%). In the Tampa Bay region, 2.04% of the Class of 2000 graduates received either TANF or food stamps. In this respect, the Tampa Bay region out-performs the State of Florida as a whole, where 2.75% of the Class of 2000 graduates received public assistance. FL DOC Data Another way to measure the effectiveness of an educational system is to measure the number of its graduates that have been Continued from page 17 Follow up Study of Tampa Bay Region High School Graduatesreprimanded by society and find themselves monitored or incarcerated by the criminal justice system. In this respect, graduates of the Tampa Bay region appear in the Department of Corrections databases at rates slightly greater than the statewide average. In the Tampa Bay region, neither Hernando, Pasco, Polk, nor Sarasota counties found any of their Class of 2000 graduates incarcerated. Manatee county had the highest percentage of its tracked graduates incarcerated, 0.08%. Hillsborough county had the highest rate of individuals under community supervision, at 0.8%, and Hernando county found itself with the lowest rate of community supervision, at 0.3%. Conclusions For the measurements of public education quality, the data presented here suggests that the Tampa Bay region out-performs the statewide aggregate. However, these measurements of educational quality leave room for debate. A higher percentage of Tampa Bay students continue their formal education after high school graduation in public or private universities. If this is perceived as better, then one must assume that working full time following graduation is not and therefore Tampa Bays higher percentage of full time workers actually reflects poorly upon the areas educational system. Of course, for the measurements of public assistance reception and inclusion within the Department of Corrections database, the fewer graduates represented by those measurements, the better reflection upon the public school system. But the other measurements tracked by the FETPIP require one to make a value judgement as to whether more or less of a particular measurement reflects poorly or favorably upon the educational system that matriculated an individual. Furthermore, the tracking system can only be used to correctly evaluate a school or school districts performance if a student does not migrate between schools or school districts during the course of his or her education. The Florida Comprehensive Assessment Test (FCAT) is often criticized in that the test results are applied to the school (or teacher) where an individual took the FCAT, and not the previous schools (or teachers) involved in the individuals prior education. In similar fashion, the FETPIP assigns blame or praise to the last school or school district attended. Determination of how students achievement at prior schools and districts should be weighted or segmented to measure the quality of educational services delivered would be a difficult and potentially contentious issue, perhaps resulting in nearly continuous testing for students in order that their segments be more transferable. While the FETPIP possesses some structural flaws, it clearly presents a progressive attitude towards assessing the quality of education delivered within an area. Resulting outcomes, rather than predicative indicators, provide a better basis by which to judge. Tracking programs such as the FETPIP will improve as interstate communication between departments of education increases; fewer graduates will slip through the cracks of the tracking system and more accurate assessment can take place.
ES202 This data set is a Bureau of Labor Statistics (BLS) sponsored collection of job and wage data from all employers participating in Floridas unemployment insurance program. It is organized by 1-digit level Standard Industrial Classification (SIC) codes (and totals for all SIC codes), and describes the number of units (i.e. an establishment designated as a single reporting unit for the unemployment insurance system). The number of covered employees, total wages of those employees, and average wages. The data set is partitioned for each Florida County and provides monthly data (by quarter) from first quarter 1988 to fourth quarter 2001. A version with annual data from 1988 to 2001 is also available. Gross Sales This data series, which is provided by the Florida Department of Revenue, is intended as a measure of economic activity. Gross sales are the sum of taxable and nontaxable sales as reported by businesses to the Florida Department of Revenue. The Florida Department of Revenue reports gross sales and taxable sales to CEDR by kind code. In order to protect the confidentiality of businesses reporting to the Florida Department of Revenue, CEDR has aggregated certain kind codes and converted the aggregations to categories. The data set is partitioned by Florida Counties and provides monthly data beginning with 1994. Housing Permits This data set of construction authorized by building permits is distributed by the Manufacturing and Construction Division, Bureau of the Census. The data set is primarily based on reports submitted to the Bureau by local building permit officials in response to a mail survey, although some data may be generated by Census Bureau interviewers or imputed from past data. The data on CEDRs web site is organized by state, by county, and by Metropolitan Statistical Area (MSA) for each month of a year from January 1996 to June 2002. The data describe the number of units and aggregate value for which building permits have been issued by single-family, 2-family, 3&4family and 5-family units. Local Area Unemployment Statistics (LAUS) This labor force data set is prepared monthly by the Bureau of Labor Statistics (BLS) and describes labor force participation, employment, unemployment, and unemployment rate by county of residence. (Data is also included by Florida MSA.) The self-employed are counted as employed persons in the LAUS data. The LAUS estimates are based on a combination of data from the Current Population Survey (CPS), unemployment insurance claim data, the Current Employment Statistics (CES) survey of establishments, and ES-202 data. Statewide and Florida counties data are available. The data can be displayed by month from January 1990 to June 2002. Annual averages are also available. Personal Income Per Capita Personal Income, and Population These three data sets are organized by county, or by MSA, per year and are released annually through the Regional Economic Information System (REIS) of the Bureau of Economic Analysis (BEA). The data are based on place of employment and reflect annual averages. In producing REIS, BEA makes use of TABLES WITH ANNUAL MEASURES Personal income by major source and earning by industry, Wage and salary disbursements by industry, Total full-time and part-time salary employment by industry, State economic profiles, Transfer payments, Farm income and expenses, and Personal tax and non-tax payments. Update On CEDRs Data CenterContinued from page 1 19 data that are byproducts of the administration of various federal and state programs, including unemployment insurance, Social Security, federal income taxes, veterans benefits, and military payroll. Hence, the REIS data series, which includes farming and non-farming, military and civilian, proprietorships (i.e. selfemployment) and wage and salary employment, are more comprehensive than ES202. ES202 data covers non-farming and salary employment only. BEA defines Personal Income as the current income received by persons from all sources (including investment income and transfer payments) minus their personal contributions for social insurance. Personal income includes both monetary income (including non-paycheck income such as employer contributions to pensions) and non-monetary income (such as food stamps and net rental value to owner-occupants of their homes). The REIS county and MSA data are issued about 16 months after the year in which the observations were made. Currently CEDRs data center has this information from 1969 to 2000. CEDR has also recently received from the Bureau of Economic Analysis (U.S. Dept. of Commerce) State Personal Income, 1929 2000. There are tables with annual measures for each of the states of the U.S. Although the State Personal Income, 1929 2000 tables are not available on line, you can go to CEDRs home page and click on Request Data from CEDR to e-mail your individualized data need request. Other items that can be found at CEDRs web site are reports of recent studies and publications as well as links to other sites containing data of interest for economic developers. CEDRs on-line data center continues to garner wide interest. In 2002, annual web hits from July were up 75% reaching 99,837 vs. 57,029 the same time last year. These logs are excluding CEDR internal staff hits, and average a monthly count of 14,262 vs. last years count of 8,147. During the most recent period, users remained at the site for an average of 9.4 minutes per visit. Check CEDRs web site at http://cedr .coba.usf.edu for new projects and continuous updated data sources.
NON-PROFIT ORG. U.S. POSTAGE PAID Tampa, FL Permit No. 257 College of Business Administration Center for Economic Development Research 1101 Channelside Drive 2nd Floor North Tampa, FL 33602