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Tampa Bay economy

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Title:
Tampa Bay economy
Physical Description:
Book
Language:
English
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University of South Florida -- Center for Economic Development Research
Publisher:
University of South Florida, College of Business Administration, Center for Economic Development Research.
Place of Publication:
Tampa, Fla

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Subjects / Keywords:
Economic conditions -- Periodicals -- Tampa Bay Region (Fla.)   ( lcsh )
Economic conditions -- Statistics -- Periodicals -- Tampa Bay Region (Fla.)   ( lcsh )
Commerce -- Periodicals -- Tampa Bay Region (Fla.)   ( lcsh )
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non-fiction   ( marcgt )

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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.
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usfldc doi - C63-00074
usfldc handle - c63.74
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SFS0000348:00001


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Volume 5, No. 2 Winter 2005/2006 Jobs and Wealth Creation in Florida and average high-tech wage. Table 1, Panel B By Norman Blake, Graduate Research Assistant, Center for E conomic Development Research depicts the percentage cha nge year over year for the average annual wage, the average manufacturing wage and the average high-tech wage. The purpose of this article is to update the Florida Technology Development Index which CEDR originally prom ulgated in October 2003. Here we complete the update of the portion of the Index titled Jobs and Wealth Creation. In previous issues of this journal Michael Bernabe reported on High-Tech Jobs in Florida (Winter 2004) and High-Tech Establishments in Florida (Summer 2005). Floridas average wage was $35,110 in 2004, an increase of $1,823 over 2003. The average annual wage grew 14.15% from 1997 to 2000 and 12.18% from 2001 to 2004. Floridas average wage has shown constant growth from 1997 through to 2004. The average manufacturing wage in Florida in 2004 was $42,473, a $1,547 or 3.78% increase over 2003. From 2001 to 2004, Floridas average m anufacturing wage grew at an average annual rate of 3.79%, which was 0.13% less that the average annual growth rate of Floridas overall average annual wage (3.91%). In his Winter 2004 article Bernabe points out that the or iginal Index relied on a list of high-tech industries compiled by the U.S. Bureau of Labor Statistics (BLS) and described by the BLS according to the Standard Industrial Classification (SIC) system. Subsequently, the SIC system was replaced by the North American Industry Classification System (NAICS). Hence, the Jobs and Wealth Creation metrics CEDR presented in the original Index for 1997 through 2000 are not directly comparable with the metrics of this update for 2001 through 2004. Floridas average high-tech wage was consistently higher than bot h the average annual wage and the average m anufacturing wage. The high-tech wage was 29.67% greater than average manufacturing wage and 56.86% greater than Floridas average overall wage in 2004. This translates to nearly a $20,000 difference compared to the average wage and a $12,604 difference as compared to the average manufacturing wage for that year. Wages are a measure of Floridas wealth creation potential. In th is update, we extend the assessm ent of the trend in Floridas average annual wages for all employees, for manufacturing jobs, and for high-tech jobs for the years 2001 through 2004. We base the average manufacturing wage on jobs in industries designated by NAICS codes 31, 32, and 33. We base the average high-tech wage on jobs in industries delineated in Bernabes Winter 2004 report. Chart 1 is a visual growth com parison of Floridas average annual wage, average manufacturing wage and average high tech wage. Measured in nominal dollars, Floridas average wage overall has increased consistently. Table 1, Panel A highlights Floridas overall average ann ual wage, average manufacturing wage (Continued on page 3)

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Table 1 From the Editor The Tampa Bay Economy This is the third issue of The Tampa Bay Economy (TBE) published solely in electronic form. Volume 5, No. 2 Winter 2005/2006 Jobs and Wealth Creation in Florida is the lead report in this issue. This article updates the Florida Technology Development Index spe cifically the portion of the Index titled Jobs and Wealth Creation, which was origin ally published by CEDR in October 2003. Table of Contents Jobs and Wealth Creation in Florida.......1 From the Editor........2 The article How to Do Economic Impact Studies for Events su mmarizes a presentation by Dr. Dennis Colie at the Florid a Festival and Events Associations 11 How to Do Economic Impact Studies for Events.......9 thAnnual Convention and Trade Show held in Sarasota on July 13-15, 2005. Housing Affordability in Central and Southwest Florida.... Another article Housing Affordability in Central and Southwest Fl orida addresses and measures home affordability in four major metropolitan statistical areas (MSAs) in Florida. They are Tampa-St Petersburg-Clearwater, SarasotaBradenton-Venice, Orlando, and Cape Coral-Fort Myers. Update on CEDRs Data Center CEDR Staff We conclude this issue of The Tampa Ba y Economy with an Update on CEDRs Data Center. Dr. Dennis Colie..Director Dodson Tong..Data Manager Nolan Kimball...Coordinator of To help us m ake the journal add even more value to Tampa Bays economic development community, we ask the journals readers to send their comments to cedr_tbe@coba.usf.edu with the subject line Journal Comments. Information/Publications Alex McPherson...Economist Anand Shah.Web Designer Carol Sumner.......Research Assistant Norman Blake......Graduate Research Assistant USFs Basic Economic Development Course The new dates for the Basic Economic Developm ent Course (BEDC) have been set. The BEDC will be held April 23 28, 2006 at Double Tree Guest Suites Tampa Bay. For more information on registration or any relate d question, please contact Nolan Kimball at (813) 905-5854. University of South Florida 2

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(Continued from page 1) Table 1 FLORIDA AVERAGE ANNUAL WAGES Panel A Wage & Salary Disbursement per Job (nominal $) NAICS North American Industry Classification Syste m SIC Standard Industrial Classification 1997 1998 1999 2000 2001 2002 2003 2004 Chart 1 Florida Average Annual Wages$0 $10,000 $20,000 $30,000 $40,000 $50,000 $60,000 1997199819992000 2001200220032004SIC NAICS A verage Annual Wages Overall Average Manufacturing Wages A verage High Tech Wages Avg Annual Wages Overall $26,539 $27,988 $28,714 $30,296 $31,297 $32,215 $33,287 $35,110 Avg Manufacturing Wages $33,491 $35,404 $36,217 $38,191 $37,985 $39,389 $40,926 $42,473 Avg High-Tech Wages $41,645 $45,672 $48,149 $51,352 $48,382 $50,957 $52,883 $55,077 Panel B Wage & Salary Disbursement per Job (year to year growth) NAICS North American Industry Classification Syste m SIC Standard Industrial Classification 1997 1998 1999 2000 2001 2002 2003 2004 Avg Annual Wages Overall 5.46% 2.59% 5.51% 2.93% 3.33% 5.48% Avg Manufacturing Wages 5.71% 2.30% 5.45% 3.70% 3.90% 3.78% Avg High-Tech Wages 9.67% 5.42% 6.65% 5.32% 3.78% 4.15% 3

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Personal income is the current income received by persons from all sources, including investment income and transfer payments, minus their personal contributions for social insu rance. In this update, we extend the assessment of pe rsonal income per capita for all Florida versus all U.S. residents for the years 2001 through 2004. We also add a metric for Disposable Personal Income per Capita, which was not included in the original Index Personal income is a Bureau of Economic Analysis concept. It is the sum of wage and salary disbursements, other labor income, proprietors income, property income, i.e. rents, dividends and interest, a nd transfer payments, less personal contributions fo r social insurance. Disposable personal income is personal income less certain tax and non-tax payments. The tax payments are payments (excluding social insurance that is already deducted for calcul ation of personal income) for income tax, estate and gift taxes, and property taxes. Non-tax payments include passport fees, fines and penalties, donations, and tuition and fees paid to government schools and hospitals. Disposable personal income is generally associated with spending power and household consumption of private sector goods and services. Floridas personal income per capita continues to lag behind that of the United St ates. In fact, this p er capita income difference has grown over time; as growth in the U.S. income per capita has outstripped the growth in Floridas income per capita by 0.24% from 1997 to 2004. The overall differences in Floridas income per capita and U.S. income per capita grew from $832 in 1997 to $1,581 in 2004. From 2000 to 2001 and 2001 to 2002 Floridas personal income per capita gr ew an average of 0.46% faster than the U.S. personal income per capita for the same period. Excluding these years the U.S. personal income per capita grew an average of 0.51% faster than the growth in Floridas personal income per capita. The U.S. personal income per capita grew by 30.42% from 1997-2004. The fast est year over year gains occurred from 1999 to 2000, when income grew by 6.82%. In contrast, the slowest growth in income per capita occurred during the U.S. economic recession of 2002, when personal income per capita grew by 0.78% per year in th e country as a whole. Overall U.S. personal income per capita grew by an average or 3.89% from 1997 to 2004. Table 2 shows personal incom e per capita for the United States and Florida. Personal income per capita is an often-used meas ure of the wealth of the population of a geographic region. The personal income per capita for Florida is defined as Floridas total personal income divided by Floridas total population. There is a similar measurement for the personal income per capita for the United States. It is defined as the United States populations total personal income, divided by the total U.S. population. Chart 2 presents a visual growth comparison of Floridas and the United States personal incom e per capita. There has been a steady growth in both Floridas and U.S. personal income per capita from 1997 to 2004. The graph illustrates the lag in personal income per capita experienced by the average Floridian as compared to the average American. Table 3 provides a com parison of the disposable personal income per capita between the United States and Florida. Disposable personal income measures the remain ing income that household and non-corporate busine sses have after tax deductions. From 1997 and 2004, Floridas disposable personal income per capita increased by 32.79%, while disposable personal income per capita for the United States increased by 34.32%. The disposable personal income difference highlights the continuing disparities of the disposable income per person in Florida as compar ed to the United States. This difference more than doubled (110.98%) from 1997 to 2004. Floridas personal inco m e per capita grew by 28.40% from 1997 to 2004, or an increase of $6,958 during the period. The fastest growth occurred during the late 1990s economic boom. From 1999 to 2000, Floridas average personal income per capita increased by 6.01% or $1,614. This rate of increase slowed to 2.66% from 2000 to 2001, 1.48% from 2001 to 2002 and an even slower 1.40% from 2002 to 2003. This was followed by a 4.46% increase in Floridas personal income per capita from 2003 to 2004. 4

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Table 2 PERSONAL INCOME PER CAPITA Panel A Personal Income Per Capita (nominal $) 1997 1998 1999 2000 2001 2002 2003 2004% Change 97 04 USA $25,334 $26,883 $27,939 $29,845 $30,57 5 $30,814 $31,487 $33,041 30.42% Florida $24,502 $25,987 $26,894 $28,509 $29,26 8 $29,700 $30,116 $31,460 28.40% Difference (U.S. FLA) $832 $895 $1,045 $1,336 $1,307 $1,114 $1,371 $1,581 90.02% Panel B Personal Income Per Capita ( year to year growth) 1997 1998 1999 2000 2001 2002 2003 2004 USA 6.11% 3.93% 6.82% 2.45% 0.78% 2.19% 4.93% Florida 6.06% 3.49% 6.01% 2.66% 1.48% 1.40% 4.46% Difference (U.S. FLA) 0.05% 0.44% 0.82% -0.22% -0.70% 0.78% 0.47% Source: Complied by CEDR from U.S. Department of Commerce Bureau of Economic Analysis, Regional Accounts Data, Chart 2 Personal Income per Capita$0 $5,000 $10,000 $15,000 $20,000 $25,000 $30,000 $35,000 19971998199920002001200220032004Nominal USA Florida 5

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Table 3 Disposable Personal In come Per Capita 1997 1998 1999 2000 2001 2002 2003 2004 % Change 199 7 2004 United States $21,941 $23,163 $23,974 $25,471 $26,240 $27,165 $28,052 $29,472 34.32% Florida $21,513 $22,728 $23,509 $24,810 $25,612 $26,575 $27,325 $28,569 32.79% Income Difference (U.S. Florida) $428 $435 $465 $661 $628 $590 $727 $903 110.98% Florida's Disposable Perso nal Inc as % of U.S. 98.05% 98.12% 98.06% 97.40% 97.61% 97.83% 97.41% 96.94% -1.11% Chart 3 Florida's Personal and Disposable Income Per Capita as a Percenta g e of U.S. Personal and Disposable Income Per Capita 95.00% 95.50% 96.00% 96.50% 97.00% 97.50% 98.00% 98.50% 19971998199920002001200220032004 Per Capita Disposable Income Per Capita Personal Income 6

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Table 4 Comparisons of the Differences in Persona l and Disposable Income Per Capita 1997 1998 1999 2000 2001 2002 2003 2004 % Change 97 04 Difference U.S. Personal and Disposable Income Per Capita (U.S. Personal Income U.S. Disposable Income) $3,393 $3,720 $3,965 $4,374 $4, 335 $3,649 $3,435 $3,569 5.16% Difference Florida's Personal and Disposable Income Per Capita (FL Personal Income FL Disposable Income) $2,989 $3,259 $3,385 $3,699 $3, 656 $3,125 $2,791 $2,891 -3.28% Difference in Amount (U.S. Florida) $404 $460 $580 $675 $679 $524 $644 $678 67.57% Percentage Change in Difference of U.S. Pe rsonal and Disposable Income Per Capita 9.62% 6.60% 10.32% -0.90% -15.83% -5.85% 3.88% Percentage Change in Difference of Floridas Pe rsonal and Disposable Income Per Capita 9.05% 3.86% 9.28% -1.17% -14.53% -10.68% 3.57% Table 5 Disposable Income per Capita as Percentage of Personal Income Per Capita 1997 1998 1999 2000 2001 2002 2003 2004 % Change 97 4 USA 86.61% 86.16% 85.81% 85.34% 85.82% 88.16% 89.09% 89.20% 2.99% Florida 87.80% 87.46% 87.41% 87.02% 87.51% 89.48% 90.73% 90.81% 3.42% 7

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Chart 3 illustrates the disparity between Floridas disposable personal income and the U.S. disposable personal income. Floridas disposable income per capita was 98.05% of U.S. disposable income per capita in 1997; and fell to 96.94% in 2004. Over the 7 years the gap widened fell by 1.11%. However, Floridas personal income per capita outgrew that of the United States by 0.22% from 2000 to 2001 and 0.70% from 2001 to 2002. income was 87.80% of pers onal incom e, while the average Americans disposable income was 86.61% of personal income. This descending trend continued until 2001 when U.S disposable income was 85.82% of personal income and Floridas disposable income was 87.51% of personal income. By 2004 disposable income per capita as a percentage of personal incom e per capita had increased to 90.81% for Fl orida and 89.20% for the United States. From 1997 to 2004, disposable income as a percentage of personal income increased by 3.42% in Florida and 2.99% in the United States. Obviously, the amount of disposable personal incom e per capita closel y tracks the amount of personal income per capita. However, in Table 4, when we report the difference in the United States and Floridas disposable personal income per capita; this difference favors Floridians. In conclusion, measures of wealth creation in Florida differ from the overall U.S. during the period 1997 through 2004. Floridas average manufacturing wage, average high-tech wage and average annual wage have consistently increased from 1997 to 2004. During the same period, the fastest wage growth occurred in Floridas average high-tech wage. The average growth rate of Floridas average high-tech wage from 1997 to 2001 was 7.24% and from 2001 to 2004 the average growth rate was 4.52%. Floridas average annual wage grew at a slightly slower pace averaging 4.52% from 1997 to 2000, and 3.91% from 2001 to 2004. From 1997 to 2004 Floridas average manufacturing wage grew at a slower pace compared to both the average high-tech wage and the average annual wage; it grew an average of 4.49% from 1997 to 2000 and 3.80% from 2001 to 2004. Table 4 shows the difference in the Floridas and U.S. personal and disposable incom e per capita. The larger U.S. amount in the differences of personal and disposable income per capita means that the average Floridian retains a higher percentage of their personal income as compared to the average American. This difference represents the average amount personal income per capita is reduced by deductions. In 1997 the average Floridian retained $404 more of their personal income that the average American. That amount has increased to $678 in 2004, which is a 67.57% increase from 1997 to 2004. The average Floridian retained more personal income from 1997 to 2004 (5.16%); the average American retained less disposable income as a percentage of their personal income over the same period (-3.28%). From 1997 to 2000, the average American and the average Floridian both retained less disposable income From 1997 to 2004, Floridas personal income per capita w as on average 3.98% less than U.S. personal income per capita. During the same period, Floridas disposable income per capita was on average 2.32% less than the disposable income per capita for the U.S., but on average Flor idians retain a larger proportion of personal income than the national average. Both personal income per capita and disposable income per capita for the United States and Florida consistently in creased from 1997 through 2004. as a percentage of personal income. This began to change in 2001 as Florida received a 1.17% boost in disposable incom e as a percentage to personal income while the U.S. percentage increased by only 0.90%. The boost in disposable income as a percentage of personal income could be attr ibuted to the tax cuts in early 2001 and 2002. Table 5 rein forces the Table 4 findings that the average Floridian keeps a hi gher percentage of their personal income as compared to the average American. In 1997 the average Floridians disposable 8

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How to Do Economic Impa ct Studies for Events By Dennis G. Colie, Ph.D., Director, and Alex McPherson, Economist, Center for Economic Developmemt Research This article summarizes a presentation by Dr. Dennis Colie at the Flor ida Festival and Events Associations 11th Annual Convention and Trade Show held in Sarasota on July 13-15, 2005. Dr. Colie is the Director of the Center for Economic Development R esearch, College of Business Administration, University of South Florida. effect, plus the induced effect if included in the model. The total effect is the sum of the direct effect and the secondary effect. The total effect is often calculated as the product of the direct effect and a multiplier. Similarly, an implied multiplier is the total effect divided by the direct effect. Several widely-used models are available to estim ate the measures of economic contribution. These include RIMS II, IMPLAN Professional Social Accounting and Impact Analysis Software, and REMI Policy Insight. One purpose for preparing an Economic Impact Study is to demonstrate the level of economic contribution an event may bring to a region in order to gain local support and funding assistance. An Economic Impact Study answers the question: How much does a festival or event contribute to the local economy? The RIMS II Regional Input-Output Modeling System is a set of multiplier tables, which are customized for a particular region and produced by the Bureau of Economic Analysis (BEA), U.S. Department of Commerce. RI MS II yields estimates of indirect and total effects. The BEA updates its multipliers annually base d on national-average performance data for each industry. The two types of RIMS II multipliers are Final Demand Multipliers, which are used when expend itures or sales are known, and Direct Effect Multipliers, which are used when only the number of jobs is known. The price of a set of RIMS II multiplier tables for 473 detailed North American Industrial Classification System (NAICS) industries and 60 industry aggregations is $275 per region. One county is the sm allest region available. An impact is the effect of a well-defined change in the structure of a region. An economic impact refers to a change in production, distribution, or consumption in a region. Examples of a change in the structure of a region are the relocation of a business into or out of a region, the establishment of a festival or event, or an increase in the minimum wage. When an activity is already established in a region, application of the count er-factual approach to determining an economic impact is necessary. The counter-factual approach vi rtually removes the output of an established activity from the regional economy to measure the economic contribution. The NAICS was developed jointly by the U.S., Canada, an d Mexico to provide comparability in statistics about business activity across North America and defines all categori es of economic activity. The measures of economic contribution are jobs, labor income, and output (which is akin to sales). There are several le vels of effects that are measurable. The direct effect is the economic contribution of the activity of interest, or th e first round of output. The indirect effect is the second and subsequent rounds of output to supply factor inputs for lower numbered rounds. The induced effect is the second and subsequent rounds of output to supply households increased consumption demands resulting from labor income earned in the producti on of direct and indirect output. The secondary effect refers to the indirect Table 1 on page 10, depicts an exam ple applying RIMS II. In th e hypothetical MyRegion, USA, we use Final Demand Multipliers in Panel A to estimate the total effect of an Arts, Entertainment, or Recreation Event, where output (or sales) is $2,322,000. The RIMS II multiplier for output in this case is 1.6963, for earnings it is 0.3254, and for jobs it is 10.8068 per $1M of output. 9

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Table 1 Estimating Impact of Arts, Ent erta inment, or Recreation Event MyRegion, USA Final Demand Multipliers Measure of Impact SalesRIMS II multiplierImpact Output $2,322,000 1.6963$3,938,809 Earnings 0.3254$755,579 Jobs 10.806825.0934 Avg. Annual Wage $30,111 Output per Worker $156,966 Direct Effect Multipliers Measure of Impact JobsRIMS II multiplierImpact Jobs 10 2.50925.090 Avg. Annual Wage $30,111 Output per Worker $156,966 Earnings $755,477 Output $3,938,277 Panel A Panel B While the RIMS II multiplier concept is timeless, results are generally interpreted to represent one years economic activit y. An event can last for any length of time, but in this example, we suppose a one-week event, or 1/52 of a year. year. If all of the total output were produced during the week of the event, then about 1,305 workers (25.0934 workers x 52 weeks) are needed during the one-week production period. It is unlikely that all of the indirect output will be produced during the week of the event, so the 1,305 jobs form an upper bound of total jobs that are needed to produce the total output. We show the results using Final Demand Multip liers in the Impact column of Panel A of Table 1. Panel A shows that the events sales contribute total output of $3,938,809 in MyRegion, USA. Workers producing the $ 3,938,809 of output will earn $755,579 for their work. Most of the total output of $3,938,809 will be produced during the week of the event because the direct output of $2,322,000 in event sales occurs in the one -week event period. The indirect output of $1,616,809 ($3,938,809 minus $2,322,000) can be produced before, during, or after the event. The RIMS II multip lier results also indicate that to produce the $3,938,809 of output about 25.0934 workers will be required to work for a full We obtain the Average Annual Wage by dividing the total Earnings by total Jobs. Sim ilarly, Output per Worker is determined by dividing total Output by total Jobs. One drawback of the RIMS II method is that there is no determ ination of the industries that contribute to the indirect e ffects. Another drawback is there is no straightforward breakdown in the number of jobs that contribute to the direct and indirect effects. Only the total jobs required for the total (direct plus indirect) output are calculated. 10

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We exemplify the Direct Effect Multiplier for jobs in Panel B of Table 1. In this case, the analyst knows the number of annualized direct jobs required for the event. The RIMS II Direct Effect Multiplier is 2.509, so total annualized jobs created by the event will be slightly more than 25 (2.509 x 10 jobs). Supposing that the event is held for a one-week period, about 25.090 x 52 = 1,304.68 (or about 1,305) jobs form an upper bound on total jobs. $1.7 million of labor income. Suppliers of inputs to the direct production process generate an additional $1.9 m illion of output. Just over 19 workers in these indirect industries would be needed to produce the $1.9 million of output. These 19 workers earn almost $700,000 of labor income. Spending of the income earned by the direct and indirect workers creates the induced effect. Almost 27 mo re jobs are induced by this spending to produce over $2.4 million of output. Workers in these 27 induced jobs earn over $850,000 of labor income. Total Employment, Labor Income, or Output isthe sum of the Direct, Indirect, and Induced effects for each measure. We show the implied multiplier below the total effect of each measure. We calculate the implied multiplier by dividing the total effect by the direct effect. For instance, the Employment Multiplier of 1.76 shown in Table 2 is found by dividing Total Employment of 105.8 jobs by Direct Employment of 60 jobs. We can calculate the Average Annual Wage and Output per W orker based on the Final Demand Multipliers. Because of the way RIMS II is designed, for a given industry or in dustry aggregation, these amounts are constant at any level of sales. So, using any arbitrary sales le vel, say $1,000,000, will produce the amounts already shown in Panel A of Table 1. In our example, the Average Annual Wage is $30,111 and Output per Worker is $156,966. We enter these amounts in Panel B of Table 1. And, because the total jobs impact is 25.090 (annualized), total Output is 25.090 times $156,966 or $3,938,277. Like the RIMS II multiplier concept, IMPLAN is tim eless. IMPLAN multipliers are derived from annual data, so we must ad just employment for short duration events to use Employment as the input variable. Table 3 shows resu lts of analysis using 60 direct jobs as input for the model. The method we show in Table 3 is used when only direct jobs are known. In this case, due to rounding, the 60 workers (3,120 week-long jobs / 52 w eeks = 60 year-long jobs) can produce output of approximately $5 million. In Table 3, we develop implied multipliers of the total effect for each measure of economic contribution. The IMPLAN Professional Social Accounting and Impact Analysis Software is a closed, static input-output model yielding estimates of indirect, induced, and total effects. The model includes data for each county in a stat e. The current price of the Florida model, including all 67 counties, is $1,750. Data is updated annually, so an updated model can be purchased each year. We provide an example of the use of IMPLAN to estim ate the economic impact of an event in Table 2 and Table 3, on page 12. Table 2 shows IMPLAN results of an analysis usi ng anticipated sales as input to the model, similar to using RIMS II Final Demand Multipliers. IMPLAN results of analysis using predicted employment as input to the model, shown in Table 3, are comparable in concept to the use of RIMS II Direct Effect Multipliers. In these examples, we use IMPLAN Sector 478, Other Am usement, Gambling, and Recreation Industries to model the c ontributions of the event. This IMPLAN Sector includes NAICS industries 7131, 7132, 71391, 71392, 71393, and 71399. In Table 2, we report the economic contribution to Florida of a hypothetical week-long event with sales of $5,000,000. Direct output is the $5,000,000 sales. Sixty persons work year-long to produce the direct output. These 60 workers earn over 11

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Table 2 EmploymentLabor IncomeOutput (2002$)(2002$) Direct 60.01,704,991 $ 5,000,000 $ Indirect 19.1694,633 1,918,220 Induced 26.7854,716 2,439,345 Total 105.83,254,340 $ 9,357,565 $ Multiplier 1.761.911.87 Results of Analysis Week-long Event with Sales $5,000,000 in Florida IMPLAN Sector 478 Other Amusement, Gambling, and Recreation Industries Table 3 EmploymentLabor IncomeOutput (2002$)(2002$) Direct 60.01,705,702 $ 5,002,083 $ Indirect 19.1694,923 1,919,019 Induced 26.8855,072 2,440,361 Total 105.93,255,697 $ 9,361,463 $ Multiplier1.771.911.87 Results of Analysis Week-long Event with 60 Employees in Florida IMPLAN Sector 478 Other Amusement, Gambling, and Recreation Industries Other IMPLAN Sectors, with associated NAICS, which may be related to festivals and events are: An advantage of IMPLAN over RIMS II is that IMPLAN reports contributions by industry. W e show an example in Table 4 which indicates direct, indirect, and induced components of Output Impact for the week-long event w ith direct sales of $5,000,000 for industries aggregated to the 2-digit NAICS. Similar reports are available from IMPLAN for the Employment and Labor Income measures of economic contribution. More detailed reports are also available. We show a sample of these detailed results in Table 5 which indicates the direct, indirect, and induced components of the Output Impact to the Retail Trade Division of the economy. Sector 471, Perform ing Arts Companies, NAICS 7111 Sector 472, Spectator S ports, NAICS 7112 Sector 473, Independent Artists, W riters, and Performers, NAICS 7115 Sector 474, Prom oters of Performing Arts and Sports Agents, NAICS 7113 and 7114 Sector 475, Museum s, Historical Sites, Zoos, and Parks, NAICS 712 Sector 476, Fitness and Recreational Sports Centers, N AICS 71394 Sector 477, Bowling Centers, NAICS 71395 12

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Table 4 IMPLAN Output Results, Aggregated to 2-Digit NAICS FL02-Arts.iap IMPACT NAME: ArtsEvent$5m MULTIPLIER: Type II Aggregated Report Industry Direct* Indirect* Induced* Total* Deflator 1 11 Ag, Forestry, Fish & Hunting 0 7,595 12,929 20,524 1.00 19 21 Mining 0 6,418 4,288 10,706 1.00 30 22 Utilities 0 112,916 56,595 169,511 1.00 33 23 Construction 0 82,005 16,131 98,136 1.00 46 31-33 Manufacturing 0 88,289 112,758 201,047 1.00 390 42 Wholesale Trade 0 71,488 136,058 207,546 1.00 391 48-49 Transportation & Warehousing 0 94,411 73,359 167,770 1.00 401 44-45 Retail Trade 0 33,859 297,100 330,959 1.00 413 51 Information 0 181,799 89,777 271,576 1.00 425 52 Finance & Insuran ce 0 157,886 244,473 402,359 1.00 431 53 Real Estate & Rental 0 307,544 164,483 472,027 1.00 437 54 Professionalscientific & tech svc 0 244,114 97,299 341,413 1.00 451 55 Management of comp anies 0 86,019 26,523 112,542 1.00 452 56 Administrative & Waste Se rvices 0 160,926 58,721 219,647 1.00 461 61 Educational svcs 0 1,336 31,559 32,895 1.00 464 62 Health & Social Services 0 350 378,976 379,326 1.00 475 71 Artsentertainment & recrea tion 5,000,000 73,728 41,831 5,115,559 1.00 479 72 Accommodation & food services 0 24,863 139,516 164,379 1.00 482 81 Other services 0 87,690 124,367 212,058 1.00 495 92 Government & non NAI Cs 0 94,984 332,602 427,586 1.00 30001 Institutions 0 0 0 0 1.00 Total 5,000,000 1,918, 220 2,439,345 9,357,565 Output Impact Ma y 25 2005 Copyright MIG 2005 13

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Table 5 IMPLAN Detailed Output Results, Retail Trade Division Only Output Impact October 10 2005 Copyright MIG 2005 FL02-Arts.iap IMPACT NAME: ArtsEvent$5m MULTIPLIER: Type II Industry Direct* Indirect* Induced* Total* Deflator 401 Motor vehicle and parts d ealers 0 6,546 60,450 66,996 1.00 402 Furniture and home furnishi ngs store 0 1,546 13,908 15,454 1.00 403 Electronics and appliance stores 0 1,873 10,782 12,655 1.00 404 Building material and garden sup ply 0 2,854 26,886 29,740 1.00 405 Food and beverage stor es 0 4,753 47,842 52,595 1.00 406 Health and personal care stores 0 2,791 19,905 22,696 1.00 407 Gasoline stations 0 1,209 12,567 13,776 1.00 408 Clothing and clothing accesso ries sto 0 2,173 23,284 25,457 1.00 409 Sporting goodshobbybook and 0 662 8,534 9,196 1.00 410 General merchandise stores 0 4,954 38,678 43,632 1.00 411 Miscellaneous store reta ilers 0 2,736 15,889 18,625 1.00 412 Nonstore retailer s 0 1,763 18,375 20,138 1.00 REMI Policy Insight is a dynamic economic forecasting model for regions down to the county level. The total effect is th e sum of the direct effect and the secondary effect. Currently, the regional model licensed to USF-CEDR includes the 13 principal component counties of the Florida HighTech Corridor plus the Rest of Florida, and costs $12,100 per year. REMIs dynamic properties allow general equilibrium tendencies and adjustment time paths, so an analysis moves beyond the static approach of RIMS II and IMPLAN. and 3) Amusement, gambling, recreation. Continuing our exam ple, in Figure 2 we show the variable and industries selected for Sara sota County and input of sales of $3,000,000 in the Perf orm ing arts, spectator sports industry for the year 2005. Then, we run the model. We show results of this run in Figure 3, which indicates a total of 176 year-long jobs will be needed to produce about $5.1 million of total output. The $5.1 million of Total Output includes the event sales of $3 million. Workers in the 176 jobs will earn about $2.4 million of personal income in 2005. We show an example of the use of REMI by considering a week-long event with s ales of $3,000,000 in Sarasota County. To perform the analysis, we first select the Policy Variable where the $3 million sales is input. As illustrated in Figure 1 we can choose the variable Industry Sales/International Exports (amount) for a particular industry. For instance, we se lected three i ndustries: 1) Performing arts, spectator spor ts, 2) Museums et al, We also show a portion of the detailed em ployment results in Figure 4 which indicates that about 149 year-long jobs in the Performing Arts, spectator sports industry are created to primarily produce the direct event sale s. If this were a weeklong event, approximately 7,748 workers (149 yearlong jobs x 52 weeks = 7,748 week-long jobs) are needed to produce output of $3,000,000. 14

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If the event is planne d to occur annually over a period of years, we can use REMI to consider the long-term economic contribution of the event. In REMI, an analyst can consid er impacts in any year up to 2050. In Figure 5 we show REMI inputs for the illustrated event for the years 2005 through 2008. In this example, we presume that sales are the same in each year. Figure 6 shows REMI results in each year of the event. multipliers that an analyst uses to determine generalized estim ates of the total effect of an economic change to the level of jobs, income, and output. A set of RIMS II multipliers for a region, down to the county level, can be purchased from the U.S. Department of Commerce for a moderate price, and are applicable to a single year. IMPLAN is a static input-output model and is more elaborate, and more expensive to obtain, than the RIMS II model. A typical IMPLAN model consists of a series of inputoutput matrices that have been custom developed for each county in a state for a particular year. The IMPLAN model provides the analyst significant flexibility in the level of aggregation of input parameters and presentation of results. REMI is a dynamic general equilibrium model that is more powerful than the other two models, but costs more too. REMI provides the user with a substantial number of input variable options a nd very detailed analytical results. The significant variety of policy variables available for analys is and the level of detail of calculated results combine to make REMI a very powerful analytical tool. In conclusion, we present examples of three commonly used m odels for determining an economic contribution. These models are the RIMS II multiplier method, IMPLAN Professional Social Accounting and Impact Analysis Software, and REMI Policy Insight The RIMS II model consists of a series of 15

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Figure 1. REMI Policy Variable Selection 16

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Figure 2. REMI Policy Variable Values 17

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Figure 3. REMI Results 176 Jobs $2.4M Income $5.1M Output 18

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Figure 4. REMI Employment Results 19

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Figure 5. REMI Annual Event Input 20

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Figure 6. REMI Annual Event Results 21

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Housing Affordability in Central and Southwest Florida By Norman Blake, Graduate Research Assistant, Center for Economic Development Research existing single-family homes, median household incom es and compare the measures of prices and incomes, as well as their gr owth rates. In Section 2 we introduce measurements of housing affordability. Our conclusions are in S ection 3. The U.S. Department of Housing and Urban Developm ent (HUD) defines affordable as housing that costs no more than 30 percent of a household's monthly income. That means rent and utilities in an apartment or the principal and interest payments on a monthly mortgage for a homeowner should be less than 30 percent of a household's monthly income to be considered affordable. Families who dedicate more than 30 percent of their income for housing are considered cost burdened and may have difficulty affording necessities such as food, clothing, transportation and medical care. Section 1: Single-Family Home Prices and Median Household Incomes The purpose of this section is to provide historical inf ormation on median single-family home prices and median household incomes. Existing Home Prices and Median Household Incomes Table 1 highlights the m edian sales price of an existing single-family home in central and southwest Florida. The Sarasota-Bradenton-Venice MSA experienced the fastest increase in median home prices from 2002 to the 3 Low interest rates have boosted home ownership levels to reco rd highs. A vibrant job m arket, a growing population and an increasing investment attraction to real estate have converged in Floridas property markets, propelling prices to historic levels. These hi gh prices along with now increasing mortgage rates have eroded home affordability in many parts of the state. rd Quarter 2005. In SarasotaBradenton-Venice, the median price for a singlefamily home jumped by 110.22% ($185,500). A close second was the Cape Coral-Fort Myers MSA where home prices increased by 108.25% ($144,300). From 2002 to the 3 rdThis article addresse s and measures home affordability in four major metropolitan statistical areas (MSAs) in Florida. They are Tampa-St Petersburg-Clearwater, Sa rasota-Bradenton-Venice, Orlando, and Cape Coral-Fort Myers. Our data captures the latest information (3 Quarter of 2005 home prices rose 91.29% ($124,700) in the Orlando MSA and 59.93% ($80,000) in the Tam pa-St Petersburg-Clearwater MSA. rd Chart 1 is a graphical comparison of the growth of single-family ho me prices in central and southwest Florida. In the 3 Quarter 2005) from the Nation al Realtors Associations quarterly reports and the U.S. Census Bureau household incomes (2002-2004). Additionally, we use the median household incomes for the past four years (2000-2004) to project the median hous ehold income for 2005. This was done in order to have income data coincide with the available reports from the National Association of Realtors. CEDR projections are straight-line trends ba sed on historic values. rd Quarter of 2005, the median price of a single-family home in SarasotaBradenton-Venice was $76,200 greater than the median priced home in Cape Coral-Fort Myers, $92,500 greater than Orlandos prices and $140,300 greater than the median price home in Tampa-St Petersburg-Clearwater. This article proceeds as follows. In Section 1 we provide statistics on the m edian sales price of 22

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Table 1 Median Sales Price of Existing Single-Family Homes % Change 02-0 5 Q3 Metropolitan Statistical Area 2002 2003 2004 2005 Q3 $133,500 $138,100 $159,700 $213,500 59.93% Tampa-St Petersburg-Clearwater $168,300 $193,300 $255,700 $353,800 110.22% Sarasota-Bradenton-Venice $136,600 $145,100 $169,600 $261,300 91.29% Orlando $133,300 $151,900 $187,200 $277,600 108.25% Cape Coral-Fort Myers Source: National Association of Realtors Chart 1 Median Sales Price of Existing Single-Family Homes$50,000 $100,000 $150,000 $200,000 $250,000 $300,000 $350,000 $400,000 2002 2003 20042005 Q 3Source: National Association of Realtors Tampa-St Petersburg-Clearwater Orlando Cape Coral-Fort Myers Sarasota-Bradenton-Venice 23

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Table 1A provides a comparison of the growth rates of existing single-family home prices in central and southwest Florida. According to the National Association of Realtors, from 3 The link between median home prices and m edian household income is strongest in the Tampa-St Petersburg-Clearwater MS A, which has both the lowest median household income and the lowest median home prices of all four MSA. In 2004, households in the Cape Co ral-Fort Myers MSA had the highest income of the four MSAs. This is projected to continue in 2005, when in Cape CoralFort Myers the median household income will be $1,706 greater than its closest counterpart, Orlando. rd Quarter 2004 to 3rd Quarter 2005 prices increased by an average of 34.71% for all four MSAs. The Orlando MSA had the greatest percentage price increase at 44.76%, which translates to an $80,800 increase in the median sales price. The TampaSt Petersburg-Clearwater MSA had the slowest increase in the median sales price of its homes. From the 3rd Quarter of 2004 to the 3 rdChart 2 highlights median household income in central and southwest Florida. From 2002 to 2005 all four MSAs, Tampa-St Petersburg-Clearwater (4.17%), Sarasota-Bradenton-Venice (4.43%), Cape Coral-Fort Myers (2.25 %) and Orlando (1.72%) are projected to have positive growth in their median household incomes. However, median household income in Cape Coral-Fort Myers declined by 7.88% ($3,406) from 2002 to 2003. Along with the greatest price per median single-family house ($353,800), Sarasota-Bradenton-Venice is also projected to have the highest annual growth rate of median household income (4.43%). Quarter of 2005 median home prices in the TampaSt Petersburg-Clearwate r MSA increased by $46,500. By also examining income levels and growth, we next demonstrate the growing dichotom y between median existing home prices and median household income. Table 2 shows the median household income for the four MSAs. The Sarasota-Bradenton-Venice MSA had the highest home prices, but the second lowest median household income. However, the Cape Coral-Fort Myers MSA, which had the second highest home prices, had the highest median household incom e. A comparison of both of these MSAs shows that the Sa rasota-Bradenton-Venice home prices are, at the median, 21.53% greater than those in Cape Coral-Fort Myers, but median household income is projected to be 5.58% less than the median household income in Cape Coral-Fort Myers. Table 1A Median Sales Price of Existing Single-Family Homes Metropolitan Statistical Area 2004 Q3 2005 Q3 % Annual Change Price Increase $167,000 $213,500 27.84% $46,500 Tampa-St Petersburg-Clearwater $285,900 $353,800 23.75% $67,900 Sarasota-Bradenton-Venice $180,500 $261,300 44.76% $80,800 Orlando $194,800 $277,600 42.51% $82,800 Cape Coral-Fort Myers Source: National Association of Realtors 24

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Table 2 Median Household Income Annual Groth w Rat e % Metropolitan Statistical Area 2002 2003 2004 2005* $36,930 $39,286 $40,508 $41,747 4.17% Tampa-St Petersburg-Clearwater $38,320 $40,027 $42,412 $43,642 4.43% Sarasota-Bradenton-Venice $42,293 $42,797 $43,885 $44,518 1.72% Orlando $43,242 $39,836 $45,077 $46,224 2.25% Cape Coral-Fort Myers *CEDR Projections, Sour ce: US Census Bureau Chart 2 Median Household Income by MSA's$20, 000 000 000 000 000 000 000 2002 2003 2004 2005*Source: US Census Bureau, *CEDR Projections$50, $45, $40, $35, $30, $25, Tampa-St Petersburg-Clearwater Orlando Cape Coral-Fort Myers Sarasota-Bradenton-Venice 25

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Annual Growth Rates and Income to Asset Ratios Coral-Fort Myers MSA has the greatest growth difference, Tam pa-St Petersburg-Clearwater is projected to have the le ast difference, 12.77%. The Sarasota-Bradenton-Venice MSA had the largest annual growth rate in both median household income (4.43%) and median single-family home price (28.10%). This still creates a difference of 23.67% in growth rates of both measurements. Orlando is close with a projected 22.41% difference in income and home price growth rates. Table 3 reports the annual growth rates of the price of a median single-fa mily home and median household income. The growth rates of house prices have significantly outpa ced the growth rates of incomes. Single digit gr owth rates of median household income pale in comparison to the doubledigit growth rates of the median priced single-family house. Cape Coral-Fort Myers is projected to have the greatest disparity between incom e growth and home price appreciation. From 2002 to 2005 Cape CoralFort Myers median household income is projected to grow by 2.25% annually, while the median sales price of an existing single-family home grows by 27.70% annually. This creates a 25.45% difference over the past 3 years as the growth of home prices outstrips the growth of median household income. While the Cape To further illustrate the divergence of median household income and the median price of an existing single-family home, we computed and compared the median home price to median household income ratio for the past four years. We show these ratios in Table 4. Table 3 Comparison of the Annual Growth Rates of Me dian Household Income and Median Price of Existing Single-Family Home Annual Growth Rate ( Housing) 02-05(Q3) A nnual Growth Rate (Income) 02-05* Difference Metropolitan Statistical Area (Housing-Income) 16.94% 4.17% 12.77% Tampa-St Petersburg-Clearwater 28.10% 4.43% 23.67% Sarasota-Bradenton-Venice 24.14% 1.72% 22.41% Orlando 27.70% 2.25% 25.45% Cape Coral-Fort Myers *Based on CEDR 2005 Income Projections Table 4 Median Home Price To Median Household Income Ratios Full Price (0% Down Payment) Growth Rat e Annual Gro wth Rate % Metropolitan Statistical Area 2002 2003 2004 2005* 04-05* 3.61 3.52 3.94 5.11 29.69% 12.26% Tampa-St Petersburg-Clearwater 4.39 4.83 6.03 8.11 34.49% 22.67% Sarasota-Bradenton-Venice 3.23 3.39 3.86 5.87 52.07% 22.03% Orlando 3.08 3.81 4.15 6.01 44.81% 24.89% Cape Coral-Fort Myers Average 3.57 3.88 4.49 6.27 39.91% 20.46% Based on CEDR 2005 Income Projections 26

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Section 2: Affordability Measurements The median home price to median household incom e ratios reveal how many years of median household income would be needed to purchase the median priced single-family home without a mortgage. The fastest annual growth in home price to household income ratio was in the Cape Coral-Fort Myers MSA (24.89%). In 2002 the median home price in Cape Coral-Fort Myers required 3.08 times the median household income, in 2005 it is projected to require 6.01 times medi an household income. The greatest ratios are projected to occur in 2005, with the Sarasota-Bradenton-Venice MSA (8.11) and the Cape Coral-Fort Myers MSA ( 6.01) leading; Orlando and Tampa-St Petersburg-Clearwater follow with 5.87 and 5.11 respectively. In the preceding section we compared median household incom e to the median price of an existing single-family home. In th is section we introduce two measurements of housing affordability. 1. Income for Housing Remaining Af ter Mortgage Payment We calculated the required apportioned amount for affordable housing as defined by HUD. We then deducted the required mortgage payment based on average mortgage interest rates and the median price of a single-family home from the affordable housing amount. The average ratio for all four MSAs in 2004 was 4.49 and is projected at 6.27 for 2005. Using the average ratio we note th at the median home price to income ratio in Sarasota-B radenton-Venice is 1.54 or 34.29% higher than the average for all four MSAs in 2004. This ratio is projecte d to increase to 1.84 or 29.34% higher than the average for all four MSAs in 2005. This suggests that although SarasotaBradenton-Venice had the greatest divergence of income to home prices, the ratios rate of growth has slowed. Conversely, the rati os rate of growth has increased in other MSAs, particularly Orlando and Cape Coral-Fort Myers wh ere there is a projected 52.07% and 44.81% increase from 2004 to 2005. Home affordability, which has declined in SarasotaBradenton-Venice, is also declining in both Orlando and Cape Coral-Fort Myers, but at a faster rate. 2. Mortgage Rates as An Affordability Measurement W e calculated the required mortgage interest rate a buyer would need based on the median household income and median single-family home price for the payments to be considered affordable. To derive our affordability measurements we assum e the buyer has already accumulated a 20% down payment for the home. The 20% down payment is a typical purchase requirement. For contrast, we also make measurements assuming 0% down payment. These amounts are the minimum cost to the borrower, because the amounts only include principal and interest payments on the loan. Additional costs, such as homeowners insurance and property taxes would increase homeowners periodic costs. A comparison of median home price to household incom e ratios for U.S. cities in 2003 by M.A. Anari at the Texas A&M Universitys Real Estate Center highlights the extremes of the national market Income for Housing Remaining After Mortgage Payment 1In Table 5 we show the calculation of the maximum amount of annual income available for housing based on HUDs affordability definition. According to HUD, the maximum allotted amount for housing expense is 30% of gross monthly income. In Table 5A we show the calculations of monthly income available for housing. They varied from a high of 8.95 for Santa Ana, CA, to low of 1.47 for Pittsburg h, PA. In 2003 San Francisco had the highest median house price ($597,493) but also one of th e nation's highest levels of household income ($67,809) with a resulting priceto-income ratio of 8.81. Nationwide, the average ratio of home prices to household income was 3.59 in 2003. The average for the four MSAs in 2003 was 3.88, 8.07% greater than the national average. 27

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Table 5 Annual Income Available For Housing Metropolitan Statistical Area 2002 2003 2004 2005* $11,079 $11,786 $12,152 $12,524 Tampa-St Petersburg-Clearwater $11,496 $12,008 $12,724 $13,093 Sarasota-Bradenton-Venice $12,688 $12,839 $13,166 $13,355 Orlando $12,973 $11,951 $13,523 $13,867 Cape Coral-Fort Myers *Based on CEDR 2005 Income Projections Table 5A Monthly Income Available For Housing Metropolitan Statistical Area 2002 2003 2004 2005* $923 $982 $1,013 $1,044 Tampa-St Petersburg-Clearwater $958 $1,001 $1,060 $1,091 Sarasota-Bradenton-Venice $1,057 $1,070 $1,097 $1,113 Orlando $1,081 $996 $1,127 $1,156 Cape Coral-Fort Myers *Based on CEDR 2005 Income Projections Table 5B Average Annual Mortgage Rates 2002 2003 2004 2005* 6.54% 5.83% 5.84% 5.83% *Average for 11 months Ending Nov, Source: Freddie Mac Table 5B lists national average annual mortgage rates based on data from the Federal Home Loan Mortgage Corporation ( Freddie Mac). We use these rates to calculate monthly mortgage payments based on the median price of an existing single-family home. Although there are regional differences in mortgage rates, historical regional rates were unavailable. rate mortgage at the national average mortgage rate. The am ounts in Table 6 are the minimum monthly payments required, if the pur chaser were to finance the full purchase price of a median single-family home. The amounts in Table 6A are the minimum monthly payments required if the purchaser finances 80% of the purchase price of the home. Table 6 and Table 6A show the m inimum required monthly payments based on a 30-year fixed 28

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Table 6 Monthly Mortgage Payments Based on Average Annual Mortgage Rates (Full Price) 0% Down Payment Metropolitan Statistical Area 2002 2003 2004 2005* $855 $822 $950 $1,269 Tampa-St Petersburg-Clearwater $1,078 $1,150 $1,522 $2,103 Sarasota-Bradenton-Venice $875 $863 $1,009 $1,553 Orlando $854 $903 $1,114 $1,650 Cape Coral-Fort Myers *Based on CEDR 2005 Income Projections Table 6A Monthly Mortgage Payments Based on Average Annual Mortgage Rates 20% Down Payment Metropolitan Statistical Area 2002 2003 2004 2005* $684 $657 $760 $1,015 Tampa-St Petersburg-Clearwater $863 $919 $1,217 $1,682 Sarasota-Bradenton-Venice $700 $690 $807 $1,242 Orlando $683 $722 $891 $1,320 Cape Coral-Fort Myers *Based on CEDR 2005 Income Projections Table 7 gives the remaining amount of income for housing after subtracting the minimum monthly mortgage payment. This is calculated by subtracting the monthly mortgage payment assuming no down payment (Table 6) from monthly income available for housing (Table 5A). The red figures signify the amount over the limit of monthly affordability a family earning the median household income would be required to spend for a median priced single-family home. Chart 3 displays our findings of affordability. A household in Sarasota-Bradenton-Venice with no down payment and earning the m edian income could not afford the median single-family home in that MSA. While affordability was evident in three of the four MSAs in 2002, they are all projected to loose the affordability attribute in 2005. Table 7A assum es the purchaser will pay 20% down and finance 80% of the homes price. As expected, the amounts show the median single-family home is more affordable after the down payment. The Sarasota-Bradenton-Venice MSA still has the least affordability based on median household income in 2004 and 2005. In the Tampa-St PetersburgClearwater MSA, the medi an price single-family home is projected to remain affordable to a household earning the median income and financing 80% of the purchase price. Note the remaining amount in SarasotaBradenton-Venice is red and negative for all years studied. In 2002, 2003, 2004 and 2005 a household with the m edian income in the Sarasota-BradentonVenice MSA could not afford the full mortgage payments on the median priced home based on HUDs affordability standard. They would spend $120 more per month than the allotted amount in 2002, $148 more in 2003, $461 more in 2004 and a projected $1 012 more p er month in 2005. 29

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Table 7 Income for Housing Remaining After Mortgage Payment (Full Price) 0% Down Payment Metropolitan Statistical Area 2002 2003 2004 2005* Tampa-St Petersburg-Clearwater $68 $160 $63 -$225 Sarasota-Bradenton-Venice -$120 -$149 -$462 -$1,012 Orlando $182 $207 $88 -$440 Cape Coral-Fort Myers $227 $93 $13 -$494 *Based on CEDR 2005 Income Projections Chart 3 Income for Housing Available After Mortgage Payment-$1,200 -$1,000 -$800 -$600 -$400 -$200 $0 $200 $4002002 2003 2004 2005* 0% Down Payment*Based on CEDR 2005 Income Projections Tampa-St Petersburg-Clearwater Sarasota-Bradenton-Venice Orlando Cape Coral-Fort Myers Table 7A Income for Housing Remaining After Mortgage Payment 20% Down Payment Metropolitan Statistical Area 2002 2003 2004 2005* Tampa-St Petersburg-Clearwater $239 $325 $253 $29 Sarasota-Bradenton-Venice $95 $82 -$157 -$591 Orlando $357 $380 $290 -$129 Cape Coral-Fort Myers $398 $274 $236 -$164 *Based on CEDR 2005 Income Projections 30

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Chart 4 Income for Housing Remaining After Mortgage Payment-$800 -$600 -$400 -$200 $0 $200 $400 $6002002 2003 2004 2005* Chart 4 shows that all MSAs were affordable based on median household income and a 20% down payment in 2002 and 2003. This is partly due to the fact that as median home prices increased an average of 9.62%, mortgage rates fell an average of 0.71%. From 2002 to 2003 the decline in mortgage rates was a much more significant factor in home affordability than the increase in prices. In 2004 as home prices moved higher, the affordability measurement fell in all four MSAs. This trend continued into 2005. Based on 3rd Quarter single-family home prices, affordability will only be maintained in the Tampa-St PetersburgClearwater MSA. Mortgage Rates as An Affordability Measurement Our research highlights the three major variables that affect housi ng affordability. They are household incom es, price of homes and the mortgage rates. Holding constant median household income and the median price of a single family home, a reduction of mortgage rates w ould reintroduce more affordabilit y into central and southwest Florida. From 2002 to 2003 growth in home prices (9.62%) outpaced growth in incomes (1.04%) by 8.58%. Nevertheless, the fall in mortgage rates increased the affordability of home ownership. However, with projected increases in mortgage rates we can e xpect a further decline of housing affordability. Table 8 reports our second m easurement of housing affordability. Holding constant median single-family home prices and median household income, we use the required mortgage interest rate as the overall measurement of affordability. The interest rates colored red indicate unaffordable housing. For example, in Sarasota-Bradenton-Venice in 2004 a decline in the mortgage rate to 4.61% from the national average of 5.84% would restore affordability. Conversely in Tampa-St Petersburg-Clearwater in 2004, housing would remain affordable even if mortgage rate rose to 8.74%. According to mortgage rates as an affordability measurement, in 2005 only Tampa-St Petersburg-Clearwater remains an affordable housing market. 20 % Down Payment*Based on CEDR 2005 Income Projections Tampa-St Petersburg-Clearwater Sarasota-Bradenton-Venice Orlando Cape Coral-Fort Myers 31

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Table 8 Annual Mortgage Interest Rate Required for Affordable Housing Metropolitan Statistical Area 2002 2003 2004 2005 Tampa-St Petersburg-Clearwater 9.73% 10.07% 8.74% 6.09% Sarasota-Bradenton-Venice 7.59% 6.63% 4.61% 2.26% Orlando 11.12% 10.51% 8.96% 4.84% Cape Coral-Fort Myers 11.73% 9.12% 8.18% 4.64% Average Historic Mortgage Rates 6.54% 5.83% 5.84% 5.83%* Assuming 30yr Mortgage and 20% down payment *Average for 11 months Ending Nov, Source: Freddie Mac Chart 5 Mortgage Rates as an Affordability Measurement 0. 00% 00% 00% 00% 00% 10. 00% 12.00% 14.00% 2002 2003 2004 2005Source: Freddie Mac8. 6. 4. 2. Historical Mortgage Rates Tampa-St Petersburg-Clearwate r Sarasota-Bradenton-Venice Orlando Cape Coral-Fort Myers 32

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Chart 5 highlights the d ecline in home affordability in 2004 and 2005. The results illustrate the median price single-family home in Tampa-St Petersburg-Clearwater remains relatively affordable to a household with the median household income. This would require a 20% down payment on the full price of the home. Based on mortgage rates, home affordability became problematic in 2004 for the Sarasota-Bradenton-Venice MSA and is a growing problem in Cape Coral-Fort Myers and Orlando. Clearwater remains an affordable housing market in 2005 according to the HUD standard. Our research shows that, an increase in household incom es, decrease in mortgage rates or a decrease in house prices woul d increase affordability. Certainly, increasing HUDs 30% affordability threshold would also affect the findings presented in this article. While incomes, prices and mortgage rates are largely market driven variables, our research highlights the role of mort gage rates in determining housing affordability. This suggests that a plausible government solution for increasing affordability and encouraging home ownershi p is low interest or subsidized home loans for households at or below the median income level. Section 3: Conclusion After investigating housing affordability in four Florida MSAs, we conclude that housing af fordability is a major problem in three of the four MSAs. The Sarasota-Bradenton-Venice MSA leads the list, failing in both of our affordability assessments for 2004 and 2005. Housing affordability is a budding problem in Orlando and Cape Coral-Fort Myers. Presently the Tampa-St Petersburg-Clearwater MSA has a positive level of affordability. In 2005, a household earning the median household income in Sarasota-Bradenton-Venice, with a 20% down payment, would need to spend $591 more than the HUD affordable limit. In Cape Coral-Fort Myers the requirement is $164 more, while in Orlando the requirement is $130 more. Tampa-St PetersburgEndnote: 1Anari, M.A. Bubble Talk, Tierra Grande, Volume 12. No 3 (July 2005) Texas A&M University Real Estate Center. See http://recenter.tamu.edu/tgrande/vol12-3/1731.html. 33

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Update on CEDRs Data Center By Dennis G. Colie, Ph.D., Director, Center for Economic Development Research ES202. This data set is a Bureau of Labor Statistics (BLS) sponsored collection of job and wage data from all employers participating in Florida's unemployment insurance program. Statewide or county data is available for each month of a particular quarter, or annual averages can be obtained. The principal focus of CEDRs Data Center is a facility for self-serv ice, on-line queries of economic and demographic datasets. You can access the Data Center by going to http://cedr.coba.usf.edu and selecting Data Center from the menu on the left side of your screen. When you select Query CEDR Databases, you will see a list of available databases. In addition, we have recen tly added instructions for selecting a database and pasting the data into a spreadsheet on your computer. Gross and Taxable Sales. This data originates from the Florida Department of Revenue. Monthly gross sales and taxable sales, denominated in nominal dollars, are available, by county, and by category. Housing Pe rmits. The Manufacturing and Construction Division, Bureau of the Census distributes this dataset of construction authorized by building permits. The data is organized by county or MSA for each month of a year. Three national cost / price indices are available: Consum er Pr ice Index, Producer Price Index, and Employment Cost Index. We have improved the query boxes for these databases so that you can request more than one years data with a single query. The querys result is an index number for each month (price indices) or each quarter (cost index) for each year requested. LAUS. The Bureau of Labor Statistics (BLS) throu gh its Local Area Unemployment Statistics (LAUS) program gathers this monthly data that describes labor force participation, employment, unemployment, and unemployment rate by place of residence. We are currently working on improving the query boxes for our statewide datasets. W e have ten datasets with metrics for each of Floridas sixty-seven counties and metro-areas are also included in some of the datasets. The datasets available are: Unemployment Claims. The Florida Agency for Workforce Innovation' s Labor Market Statistics Department issues the initial Unemployment Claims report monthly. Cost of Living This dataset provides rela tive costs of living for Florida's counties and is released annually by the Florida Department of Education. The average cost of living in a given year is set at 100% and a Florida county's relative cost of living is expressed as a percentage of the average. Personal In come, Per Capita (Personal) Income, and Population. The Regional Economic Information System (REIS) of the Bureau of Economic Analysis (BEA) releases these three da tasets annually. The BEA defines Personal Income as the current income received by persons from all sources (including investment income and transfer payments) minus their personal contributions fo r social insurance. Per Capita Income is Personal Income divided by Population. Education Indicators The Education Indicators series has five m easures: average class size; drop out rates, graduation rates; per-pupil expenditures and SAT scores. The data is obtained from the Florida Department of Education for each of Florida's counties. 34

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If you do not find the data you want in the selfservice Data Center, you can send an email to CEDR to request specific data. In most cases we have the data or can direct you to a source for your data need. As of 11/30/05, Mr. Dodson Tong, CEDRs Data Manager, has responded on average to about one special data request per week. We continually look for ways to make CEDRs Data Center a m ore valuable resource, particularly for supporting Floridas economic development practitioners. Your comments or suggested improvements for the Data Center are always welcome. Send your emails to us at: cedr@coba.usf.edu. 35


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