FIRST COAST OUTER BELTWAY SOCIO-ECONOMIC ANALYSIS BY TRAFFIC ANALYSIS ZONE (DUVAL, ST. JOHNS & CLAY COUNTIES)

Transcription

1 FIRST COAST OUTER BELTWAY SOCIO-ECONOMIC ANALYSIS BY TRAFFIC ANALYSIS ZONE (DUVAL, ST. JOHNS & CLAY COUNTIES) December 16, 2009 Prepared for Jeff Arey, PE, VP Transportation Infrastructure Reynolds, Smith and Hills, Inc. Prepared by Fishkind & Associates, Inc Corporate Blvd. Orlando, Florida Fishkind and Associates, Inc.

2 Table of Contents Section Title Page 1.0 Introduction Dwelling Unit Forecast Methodology Beyond 2009 for Duval, St. Johns and Clay Counties Population Forecast Methodology Student Enrollment Forecast Methodology Hotel-Motel Room Forecast Methodology Employment Forecast Methodology Conclusions Appendix 1 Summary of Socio-Economic Data (County by County) Appendix 2 Summary of Population Forecast Changes Page i

3 1.0 Introduction Located in Northeast Florida, the First Coast Outer Beltway begins at Interstate 10 in Duval County and heads south through Clay County. The project turns east and after crossing the current site of the SR 16 Bridge from Clay County into St. Johns County, the project continues east until it terminates at I-95 in St. Johns County. As part of the analysis involved with the Traffic and Revenue Study, Reynolds, Smith and Hills, Inc. ( Client ) retained Fishkind and Associates, Inc. ( Consultant ) to conduct a socio-economic analysis of the project by Traffic Analysis Zone (TAZ) for Duval, St. Johns and Clay Counties. The socio-economic categories evaluated by the Consultant include the following: Dwelling Units Population Student Enrollment Hotel/Motel Rooms Manufacturing Employment Other Industrial Employment Commercial Employment Service Employment Each of these socio-economic categories was estimated by specific County TAZ for the years: 2009, 2010, 2015, 2020, 2025, 2030, 2035, 2040, 2045, 2060, 2075, and This data was provided to the Client for the traffic and revenue study in electronic format. 2.0 Dwelling Unit Forecast Methodology When evaluating dwelling unit counts for 2009, the Consultant gathered and analyzed property appraiser data via Geographic Information Systems (GIS) as of September 30, 2009 for Duval, St. Johns and Clay Counties. The Consultant overlaid the property appraiser data on the TAZ shape files for the three counties of interest. The Consultant compared the total dwelling unit estimates for each county to two sources: 1) the census American Community Survey (ACS) data and 2) the original base 2000 zdata plus census permit activity for each county. Comparison to these data sources provided guidance as to the overall accuracy of the property appraiser data with respect to total dwelling units as well as the mix of single family and multifamily units. Table 1 shows the comparison of the 2009 zdata, the ACS estimates and permits. Page 3 of 15

4 Table 1. Dwelling Unit Estimates by County ACS Data ACS Data 2009 Permits Analysis SF MF TOT SF MF TOT SF MF TOT Duval 310,492 92, , ,945 84, , ,191 95, ,926 SJ 74,617 14,043 88,660 69,374 13,350 82,724 72,767 14,043 86,810 Clay 66,600 11,435 78,035 65,383 5,862 71,245 66,600 11,483 78,083 Source: Property Appraiser (Duval, St. Johns & Clay County) ACS Data Census Residential Building Permits and 2000 ZDATA The ACS data provided a guide with respect to a past number of units, while the permits analysis provided a guide to overall accuracy of the property appraiser and Consultant s estimates of dwelling units for As the data shows, the Consultant s estimates in aggregate are in line with the permits analysis and greater than the ACS data providing a credible check of the conclusions with respect to the 2009 data. 2.1 Beyond 2009 for Duval, St. Johns and Clay Counties Beyond 2009, the Consultant estimated the number of single family and multi-family residential units in Duval, St. Johns and Clay Counties by TAZ as a function of the forecasted population and the forecasted mix of single family and multi-family units. Table 2 shows the single family - multi-family splits for Duval, St. Johns and Clay Counties. Table 2. County Specific Single Family Multi-Family Splits COUNTY Single Family Multi-Family Duval 78.18% 21.76% St. Johns 83.62% 16.09% Clay 91.70% 8.22% Source: ACS Data As part of the analysis, the Consultant evaluated the current status of ongoing, approved and projects currently involved in Developments of Regional Impact (DRIs) process on a county by county basis. The Consultant contacted the Northeast Florida Regional Council (NEFRC), which provided a listing of these projects and Geographic Information System (GIS) shape files which were overlaid on the TAZ files provided by the client. The residential entitlements associated with these DRIs were then identified and placed within the proper TAZ and forecasted accordingly. Page 4 of 15

5 As part of the residential analysis, the Consultant applied the same methodology as in the 2008 report by identifying vacant residential acreage using the property appraiser data for each county by TAZ. In addition, the Consultant gathered data on other land uses that have the potential to be used for continued residential growth via changes in land use. Table 3 summarizes the land use categories that were evaluated. Table 3. Property Appraiser Land Use Categories Land Use Code Description 0000 Vacant Residential 1000 Vacant Commercial 4000 Vacant Industries 5000 Improved agricultural 5100 Cropland soil capability Class I 5200 Cropland soil capability Class II 5300 Cropland soil capability Class III 5400 Timberland - site index 90 and above 5500 Timberland - site index 80 to Timberland - site index 70 to Timberland - site index 60 to Timberland- site index 50 to Timberland- not classified by site 6000 Grazing land soil capability Class I 6100 Grazing land soil capability Class II 6200 Grazing land soil capability Class III 6300 Grazing land soil capability Class IV 6400 Grazing land soil capability Class V 6500 Grazing land soil capability Class VI 6600 Orchard Groves,Citrus, etc Poultry, bees, tropical fish, rabbits, etc Dairies, feed lots 6900 Ornamental miscellaneous agricultural Source: Fishkind and Associates, Inc. Using the current land use, the Consultant calculated the acreage available less wetlands by TAZ. The acreage was than converted to a specific dwelling unit capacity by TAZ through 2040 and 2090 by applying a specific density to the vacant residential acreage and a specific density to the vacant agricultural acreage within specific sectors in each county. In addition, the Consultant applied specific buildout capacities for the vacant residential and vacant agricultural in 2040 and Page 5 of 15

6 Tables 4 through 6 summarize the densities applied to the various land use categories in each county and the level of buildout expected through 2040 and Table 6 summarizes Duval County, Table 7 summarizes St. Johns County and Table 8 summarizes Clay County. The development guidelines for each county established capacities by TAZ based on the developable acreage estimated in each TAZ. Table 4. Estimated Duval County Residential Density and Buildout Levels Res AG Description Density Density NE Quadrant of County % % % % NW Quadrant Outside of I-295 & SW Quadrant West of FCOB % % % % NW Quadrant Inside of I % % % % SE Quadrant of County % % % % SW Quadrant West of I-295 and East of FCOB % % % % SW Quadrant East of I % % % % Source: Fishkind and Associates, Inc. Table 5. Estimated St. Johns County Residential Density and Buildout Levels Res AG Description Density Density N of CR 208 & St. Augustine % % % % S of CR % % % % Source: Fishkind and Associates, Inc. Table 6. Estimated Clay County Residential Density and Buildout Levels Res AG Description Density Density Inside of FCOB % % % % Outside of FCOB % % % % Source: Fishkind and Associates, Inc. Tables 7 through 9 summarize the total dwelling units in each county and population associated with the dwelling unit type. Table 7 summarizes Duval County, Table 8 summarizes St. Johns County and Table 9 summarizes Clay County. This data is also provided as part of Appendix 1. Page 6 of 15

7 Table 7. Duval County Dwelling Units and Population SFDU MFDU TOTDU SF% MF% ,492 92, , % 23.0% ,261 98, , % 23.8% , , , % 23.7% , , , % 23.8% , , , % 23.8% , , , % 23.6% , , , % 23.5% , , , % 23.3% , , , % 23.0% , , , % 23.1% , , , % 23.2% , , , % 23.1% Source: Fishkind and Associates, Inc. Table 8. St. Johns County Dwelling Units and Population SFDU MFDU TOTDU SF% MF% ,617 14,043 88, % 15.8% ,273 15,567 92, % 16.8% ,810 20, , % 18.9% ,904 23, , % 18.2% ,549 26, , % 18.2% ,368 28, , % 18.2% ,960 31, , % 18.0% ,950 33, , % 18.0% ,343 36, , % 17.6% ,130 39, , % 17.5% ,492 42, , % 17.4% ,667 45, , % 17.3% Source: Fishkind and Associates, Inc. Page 7 of 15

8 Table 9. Clay County Dwelling Units and Population SFDU MFDU TOTDU SF% MF% ,600 11,435 78, % 14.7% ,955 12,411 83, % 14.9% ,586 14,095 92, % 15.2% ,440 16, , % 14.8% ,695 18, , % 14.9% ,697 22, , % 15.7% ,070 24, , % 15.7% ,466 26, , % 15.7% ,935 28, , % 15.7% ,621 34, , % 17.0% ,218 37, , % 17.0% ,744 41, , % 17.0% Source: Fishkind and Associates, Inc. 3.0 Population Forecast Methodology The Consultant updated the population forecast for the three counties as part of the revised TAZ analysis. The population forecast update was a function of the overall change in forecast levels as predicted by University of Florida BEBR. A summary of the revised population figures is provided in Appendix 2. As the data shows, if the updated BEBR projections in any given forecast Year went up or down, the original Consultant forecast was correspondingly adjusted up or down. This is the case for all of the population forecasts except for Duval and St. Johns Counties in In those cases, the Consultant defaulted to its population estimates based on the Consultant s Econocast model. It is important to note that upon reviewing the population forecast, the Consultant adjusted the 2015 population forecast for St. Johns County. Based on the timing of the FCOB and historic population growth, the forecast of 235,100 seemed aggressive and was adjusted down to 226,627. With respect to the population in each TAZ; a TAZ s population was a function of the previous forecast year s population plus the dwelling unit growth over the next five years, less the specific counties vacancy rate from the ACS census data, multiplied by the University of Florida s Bureau of Economic and Business Research (BEBR) persons per household number for the specific county. Table 10 summarizes the county vacancy rates and Table 11 summarizes each county s persons per household. Page 8 of 15

9 Table 10. County Vacancy Rates Duval County, Florida St. Johns County, Florida Clay County, Florida Occupied 86.80% 81.40% 90.16% Seasonal 2.53% 5.842% 1.61% Vacant 10.67% 12.76% 8.22% Source: U.S. Census ACS Table 11. County Persons Per Household COUNTY PPH Duval 2.50 St. Johns 2.43 Clay 2.71 Source: UF BEBR 2009 On a county by county aggregate basis, the Consultant then checked its population forecast estimates against the BEBR medium series for each county to verify that the forecast estimates were in-line with other credible population estimates through Table 12 provides a comparison of the Consultant s population estimates to BEBR medium estimates through As the data shows, the Consultant s estimates are similar to BEBR estimates of population through 2035 indicating that the overall population estimates are consistent with BEBR. Appendix 1 contains a detailed summary from 2009 through Table 12. Fishkind Population Forecast Estimates Compared to UF BEBR Duval St. Johns Clay Total FKA UF BEBR FKA UF BEBR FKA UF BEBR FKA UF BEBR , , , , , ,900 1,278,830 1,296, , , , , , ,400 1,393,368 1,406, ,023,367 1,041, , , , ,200 1,532,922 1,530, ,087,933 1,104, , , , ,200 1,661,062 1,651, ,151,931 1,165, , , , ,800 1,784,076 1,767, ,217,299 1,222, , , , ,200 1,905,430 1,877,500 Source: Fishkind and Associates and UF BEBR Projections of Florida Population by County (Feb 2009) Page 9 of 15

10 4.0 Student Enrollment Forecast Methodology The Consultant estimated student enrollment as a function of total dwelling units and assigning county-specific student generation rates to the single family and multi-family units found in each TAZ. The total student enrollment figures for each county were then distributed on a percentage basis to the same TAZs shown in the ZDATA data provided by the Client. Table 13 summarizes the student generation rates used by the Consultant to estimate overall student enrollment. Table 13. Student Generation Rates County Single Family Multi- Family All Unit Types Duval St. Johns Clay Source: Fishkind and Associates, Inc. 5.0 Hotel-Motel Room Forecast Methodology The location and number of hotel rooms as of 2009 was a function of November 2009 Smith Travel Research, Inc. reporting. The Consultant mapped the locations and number of rooms of the hotels. The forecast for the growth of hotel and motel units within each county was a function of historical growth of hotel and motel units within each county. The location of hotel and motel units by TAZ focused on current location of hotel and motel units as well as the development of specific DRIs that include hotel-motel entitlements. In addition the Consultant concentrated hotel and motel units at major interstate intersections and in areas with significant employment concentrations. In general the following annual average hotel and motel growth was applied: Duval County one 400-room hotel/motel annually St. Johns County one 450-room hotel/motel annually Clay County one 180-room hotel/motel annually Using the original 2000 ZDATA, Table 14 summarizes the Consultant assumptions used to estimate hotel/motel population for each county through Page 10 of 15

11 Table 14. Hotel/Motel Population Multipliers COUNTY HMUNITS HMPOP POP/HMUNIT Duval 14,347 13, St. Johns 5,239 8, Clay 1,201 1, Source: 2000 ZDATA 6.0 Employment Forecast Methodology When evaluating employment estimates for 2009, the Consultant gathered and analyzed property appraiser data via Geographic Information Systems (GIS) as of September 30, 2009 for Duval, St. Johns and Clay Counties. The Consultant overlaid the property appraiser data on the TAZ shape files for the three counties of interest. The Consultant calculated the square footage of the non-residential facilities by landuse code and estimated employment for each county. The Consultant then calibrated the employment to the most recent es-202 covered employment estimates for each county. In the case of Duval County, an additional 33,000 in employment associated with the military activity at NAS Jacksonville and Mayport. Using the es-202 as a control total with respect to current levels of employment provided guidance as to the overall accuracy of the employment figures in relation to the nonresidential square footage within each county. Beyond 2009, the Consultant estimated employment by the ZDATA categories in Duval, St. Johns and Clay Counties by TAZ through The Consultant evaluated the current status of ongoing, approved and projects currently involved in the DRIs process on a county by county basis. The NEFRC which provided the listing of these projects and Geographic Information System (GIS) shape files which were overlaid on the TAZ files provided by the client. The commercial entitlements associated with these DRIs were then identified and placed within the proper TAZ and forecasted accordingly. As part of the employment analysis, the Consultant identified vacant commercial and industrial acreage using the property appraiser data for each county by TAZ. In addition, the Consultant assumed that a percentage of the agricultural, timberland and grazing land has the potential to be used for future non-residential growth via changes in land use. Table 15 summarizes the land use categories that were evaluated. Page 11 of 15

12 Table 15. Property Appraiser Land Use Categories Land Use Code Description 0000 Vacant Residential 1000 Vacant Commercial 4000 Vacant Industries 5000 Improved agricultural 5100 Cropland soil capability Class I 5200 Cropland soil capability Class II 5300 Cropland soil capability Class III 5400 Timberland - site index 90 and above 5500 Timberland - site index 80 to Timberland - site index 70 to Timberland - site index 60 to Timberland- site index 50 to Timberland- not classified by site 6000 Grazing land soil capability Class I 6100 Grazing land soil capability Class II 6200 Grazing land soil capability Class III 6300 Grazing land soil capability Class IV 6400 Grazing land soil capability Class V 6500 Grazing land soil capability Class VI 6600 Orchard Groves,Citrus, etc Poultry, bees, tropical fish, rabbits, etc Dairies, feed lots 6900 Ornamental miscellaneous agricultural Source: Fishkind and Associates, Inc. The following assumptions were made regarding the percentage of the agricultural, timberland and grazing land having the potential to be used for future non-residential growth via changes in land use: Duval 10% for non-residential purposes St. Johns 5% for non-residential purposes Clay 10% for non-residential purposes Using the current land use, the Consultant calculated the acreage available less wetlands by TAZ. The acreage was than converted to a square footage per employment category using historical Floor Area Ratios (F.A.R.s). Table 16 summarizes the F.A.R.s used for each employment category in each county. Table 16. County F.A.R. Summary County Retail Service Mfg Clay Duval St Johns Source: Fishkind and Associates, Inc. & County Property Appraiser Data Page 12 of 15

13 These square footages were then converted to employment by applying the applicable square footage per employee for specific employment categories for each county. These employment multipliers were calibrated to the Year 2000 and Year 2005 employment estimates for each county. In this way, the Consultant was able to generate employment capacities by TAZ and for each County. Table 17 summarizes the employment divisors for each employment category in each county. Table 17. Employment Multipliers for Each County Employment Category Duval St. Johns Clay Manufacturing Industrial Commercial Service Source: Fishkind and Associates, Inc. & County Property Appraiser Data The last factor that influenced overall employment growth in each county over the forecast horizon involved maintaining a proper employment to population ratio. In 2009, Duval County maintained an employment to population ratio of 53%; the Consultant believes that overall this employment to population ratio will continue to trend along this rate through 2090 as Duval County will remain the job center for Northeast Florida. Table 18 provides a summary of Duval County s total population, employment by category, total employment and employment to population ratio by county through the forecast horizon of Appendix 1 provides the detailed summary of the employment to population ratio. Table 18. Duval Co. Employment to Population Ratio Summary POP MFG Ind Other Ind Retail Service Total Emp Emp-Pop Ratio ,014 32, ,909 96, , , % ,512 36,660 79, , , , % ,240 42,765 89, , , , % ,023,367 47,831 97, , , , % ,087,933 51, , , , , % ,151,931 54, , , , , % ,217,299 57, , , , , % ,282,709 60, , , , , % ,319,649 62, , , , , % ,400,684 68, , , , , % ,482,492 73, , , , , % ,535,978 78, , , , , % Source: Fishkind and Associates, Inc. Page 13 of 15

14 In 2009, St. Johns County maintained an employment to population ratio of 30%; the Consultant believes that overall this employment to population ratio will grow to 41% through 2090 as northwest St. Johns County develops its two main job centers at the World Golf Village and World Commerce Center. The Consultant believes that St. Johns County will emerge as the secondary job center in Northeast Florida as the major DRIs in the region buildout over the next 20 years. Table 19 provides a summary of St. Johns County s total population, employment by category, total employment and employment to population ratio by county through the forecast horizon of Appendix 1 provides the detailed summary of the employment to population ratio. Table 19. St. Johns Co. Employment to Population Ratio Summary POP MFG Ind Other Ind Retail Service Total Emp Emp-Pop Ratio ,087 2,983 6,948 18,802 25,840 54, % ,718 3,678 7,046 21,603 23,812 56, % ,627 5,412 11,865 29,557 27,997 74, % ,768 7,308 15,272 38,688 32,924 94, % ,667 8,564 17,365 46,170 36, , % ,953 9,743 19,524 52,233 43, , % ,127 10,870 21,665 58,277 50, , % ,236 11,851 23,767 64,134 58, , % ,380 12,804 25,484 66,145 64, , % ,630 14,903 28,856 67,945 74, , % ,667 18,027 34,176 74,164 90, , % ,626 20,811 38,151 78,985 95, , % Source: Fishkind and Associates, Inc. Lastly, in 2009, Clay County maintained an employment to population ratio of 24%; the Consultant believes that overall this employment to population ratio will continue to grow to 32% through 2090, especially with the introduction of a major toll road through the region. The Consultant believed that of the three counties, Duval, St. Johns and Clay, Clay will remain more of a bedroom community serving Duval and St. Johns Counties. Table 20 provides a summary of Clay County s total population, employment by category, total employment and employment to population ratio by county through the forecast horizon of Appendix 1 provides the detailed summary of the employment to population ratio. Page 14 of 15

15 Table 20. Clay Co. Employment to Population Ratio Summary POP MFG Ind Other Ind Retail Service Total Emp Emp-Pop Ratio ,485 3,157 5,050 14,751 21,578 44, % ,600 3,436 5,819 17,657 18,565 45, % ,501 4,355 7,203 21,885 20,270 53, % ,787 5,228 7,860 26,032 22,584 61, % ,462 5,833 8,308 29,469 24,372 67, % ,192 6,620 9,110 31,762 27,182 74, % ,004 7,526 9,999 36,399 32,376 86, % ,357 8,298 10,814 40,906 37,420 97, % ,181 9,641 11,445 44,572 41, , % ,552 12,839 12,623 53,867 52, , % ,780 14,837 12,818 58,922 60, , % ,726 17,623 14,162 68,974 71, , % Source: Fishkind and Associates, Inc. 7.0 Conclusions The Consultant s revised analysis of TAZs focused on the updating of two main components: population and employment. As discussed in Section 3.0, population estimates were adjusted based on the forecasted change in BEBR s estimates of population. Employment estimates were a function of the forecasted employment to population ratio in the forecast years. The mix of employment categories generally was maintained with growth in commercial and service categories receiving the majority of total employment. The Consultant s revised analysis focused on additional detailed review of aerial photographs of TAZs. The combination of aerial review and additional reconciliation with property appraiser data led to some significant changes in TAZs population and/or employment estimates. Overall, the updated analysis is believed to be more accurate with respect to current location of population and employment in the counties of interest. Page 15 of 15

16 APPENDIX 1

17 DUVAL Summary SFDU SFPOP MFDU MFPOP TOTDU TOTPOP HMUNITS HMPOP EMPMFG EMPIND EMPCOM EMPSVC EMPTOT SCHENR EMP - POP Ratio , ,377 92, , , ,014 17,345 29,158 32, ,909 96, , , , % , ,628 98, , , ,512 18,982 31,911 36,660 79, , , , , % , , , , , ,240 21,037 35,364 42,765 89, , , , , % , , , , ,776 1,023,367 22,159 37,249 47,831 97, , , , , % , , , , ,840 1,087,933 23,477 39,463 51, , , , , , % , , , , ,770 1,151,931 24,473 41,138 54, , , , , , % , , , , ,598 1,217,299 25,304 42,536 57, , , , , , % , , , , ,173 1,282,709 25,974 43,661 60, , , , , , % ,332 1,016, , , ,717 1,319,649 27,069 45,501 62, , , , , , % ,707 1,076, , , ,139 1,400,684 31,321 52,650 68, , , , , , % ,295 1,137, , , ,873 1,482,492 35,846 60,255 73, , , , , , % ,050 1,180, , , ,159 1,535,978 39,558 66,495 78, , , , , , % ST. JOHNS Summary SFDU SFPOP MFDU MFPOP TOTDU TOTPOP HMUNITS HMPOP EMPMFG EMPIND EMPCOM EMPSVC EMPTOT SCHENR EMP - POP Ratio , ,929 14,043 29,158 88, ,087 6,112 10,112 2,983 6,948 18,802 25,840 54,573 40, % , ,253 15,567 31,465 92, ,718 6,173 10,213 3,678 7,046 21,603 23,812 56,139 50, % , ,667 20,686 42, , ,627 7,585 12,554 5,412 11,865 29,557 27,997 74,831 57, % , ,703 23,599 50, , ,768 9,870 16,336 7,308 15,272 38,688 32,924 94,193 68, % , ,049 26,318 56, , ,667 13,158 21,780 8,564 17,365 46,170 36, ,015 76, % , ,122 28,806 62, , ,953 15,479 25,620 9,743 19,524 52,233 43, ,249 83, % , ,459 31,145 67, , ,127 17,974 29,752 10,870 21,665 58,277 50, ,643 91, % , ,331 33,342 72, , ,236 20,050 33,188 11,851 23,767 64,134 58, ,841 97, % , ,444 36,147 77, , ,380 21,536 35,650 12,804 25,484 66,145 64, , , % , ,148 39,647 85, , ,630 24,763 40,994 14,903 28,856 67,945 74, , , % , ,594 42,666 92, , ,667 27,765 45,965 18,027 34,176 74,164 90, , , % , ,705 45,845 98, , ,626 30,545 50,568 20,811 38,151 78,985 95, , , % CLAY Summary SFDU SFPOP MFDU MFPOP TOTDU TOTPOP HMUNITS HMPOP EMPMFG EMPIND EMPCOM EMPSVC EMPTOT SCHENR EMP - POP Ratio , ,307 11,435 27,178 78, ,485 1,142 1,533 3,157 5,050 14,751 21,578 44,536 54, % , ,941 12,411 27,659 83, ,600 1,162 1,559 3,436 5,819 17,657 18,565 45,477 64, % , ,647 14,095 31,854 92, ,501 1,449 1,944 4,355 7,203 21,885 20,270 53,714 71, % , ,117 16,029 34, , ,787 1,902 2,552 5,228 7,860 26,032 22,584 61,703 83, % , ,547 18,149 38, , ,462 2,937 3,941 5,833 8,308 29,469 24,372 67,983 93, % , ,115 22,094 45, , ,192 3,387 4,544 6,620 9,110 31,762 27,182 74, , % , ,138 24,155 48, , ,004 3,999 5,365 7,526 9,999 36,399 32,376 86, , % , ,657 26,286 52, , ,357 4,624 6,204 8,298 10,814 40,906 37,420 97, , % , ,025 28,650 57, , ,181 5,174 6,941 9,641 11,445 44,572 41, , , % , ,877 34,418 73, , ,552 6,900 9,257 12,839 12,623 53,867 52, , , % , ,803 37,982 81, , ,780 8,695 11,663 14,837 12,818 58,922 60, , , % , ,395 41,199 89, , ,726 10,015 13,432 17,623 14,162 68,974 71, , , %

18 APPENDIX 2

19 County Projections, April 1 Extrapolated Projections and State CLAY Medium (2007) 194, , , , , , , , , , ,085 Medium (2008) 186, , , , , , , , , , ,483 Change '07 - '08-4% -7% -7% -7% -7% -7% -7% -7% -7% -7% -7% FKA (2008) 193, , , , , , , , , , ,272 FKA (2009) 185, , , , , , , , , , ,727 DUVAL Medium (2007) 922, ,900 1,051,800 1,111,400 1,167,100 1,218,000 1,265,114 1,308,519 1,348,337 1,384,728 1,417,876 Medium (2008) 917, ,500 1,041,000 1,104,700 1,165,000 1,222,400 1,276,726 1,327,906 1,375,920 1,420,796 1,462,594 Change '07 - ' % -1.45% -1.03% -0.60% -0.18% 0.36% 0.92% 1.48% 2.05% 2.60% 3.15% FKA (2008) 904, ,386 1,033,984 1,094,531 1,154,007 1,212,918 1,271,043 1,300,383 1,372,605 1,444,858 1,489,018 FKA (2009) 905, ,241 1,023,367 1,087,933 1,151,931 1,217,300 1,282,709 1,319,649 1,400,685 1,482,492 1,535,979 ST. JOHNS Medium (2007) 185, , , , , , , , , , ,747 Medium (2008) 192, , , , , , , , , , ,350 Change '07 - '08-1% 3% 6% 8% 10% 12% 13% 15% 16% 17% 18% FKA (2008) 190, , , , , , , , , , ,581 FKA (2009) 187, , , , , , , , , , ,626

20 Warrington College of Business Administration Bureau of Economic and Business Research Florida Population Studies Volume 42, Bulletin 153, March 2009 Projections of Florida Population by County, Stanley K. Smith, Director Stefan Rayer, Research Demographer Florida has been a rapidly growing state for many years, but that growth slowed considerably during the last two years. The state s population grew by approximately 3 million each decade between 1970 and Fueled by an expanding economy and a booming housing market, population increases between 2000 and 2006 were even larger, averaging 395,000 per year. As economic growth slowed and the housing market cooled, population growth declined to 331,000 in and 127,000 in The collapse of the housing market and the lingering effects of the worst economic crisis since the 1930s are likely to keep population growth at very low levels for the next few years. We project an increase of 74,000 between 2008 and 2010, an average of only 37,000 per year. This will be the smallest population increase in Florida since the mid 1940s, when large numbers of military personnel who moved to the state during World War II left after the war ended. Fourteen counties are projected to lose population between 2008 and 2010 and many others will grow very slowly. We expect population growth to increase early in the next decade, but for many counties future increases will be smaller than they have been in the past. The dramatic shifts in state and county population trends over the past few years illustrate the uncertain nature of population projections. To account for this uncertainty, we publish three series of projections. We believe the medium projections are likely to provide the most accurate forecasts of future population growth in most circumstances, but the high and low projections provide reasonable alternative scenarios. These alternative scenarios along with information from other data sources should be considered when using projections for planning purposes. Although population projections are useful tools for planning and analysis, they rarely provide perfect forecasts of future population change. State projections State-level projections were made using a cohort-component methodology in which births, deaths, and migration are projected separately for each age-sex cohort in Florida, by race (white, nonwhite) and ethnicity (Hispanic, non-hispanic). The starting point was the population of Florida on April 1, 2005, as estimated by the Bureau of Economic and Business Research at the University of Florida. Survival rates were applied to each age-sex-race-ethnicity cohort to project future deaths in the population. These rates were based on Florida Life Tables for , calculated by the Bureau of Economic and Business Research using mortality data published by the Office of Vital Statistics in the Florida Department of Health. The survival rates were adjusted upward in 2010, 2015, 2020, 2025, and 2030 to account for projected increases in life expectancy (U.S. Census Bureau, Population Division Working Paper No. 38, Series NP-05, 2000). Domestic migration rates by age, sex, and race/ethnicity were based on migration data for as reported in Census Domestic in-migration rates were calculated by dividing the number of persons moving to Florida from other states by the mid-decade population of the United States (minus Florida). Domestic out-migration rates were calculated by dividing the number of persons leaving Florida by Florida s mid-decade population. In both instances, rates were calculated separately for males and females by race and ethnicity for each five-year age group up to 85+. Florida Population Studies Volume 42 Bulletin 153 March 2009

21 These in- and out-migration rates were weighted to account for changes in migration patterns and to provide alternative scenarios of future population growth. For each of the three series, projections of domestic in-migration were made by applying weighted in-migration rates to the projected population of the United States (minus Florida), using the most recent set of national projections produced by the U.S. Census Bureau. Projections of out-migration were made by applying weighted out-migration rates to the Florida population. Projections of foreign immigration were also based on data from Census For the high projections, foreign immigration was projected to exceed the level by 30% during each five-year interval. For the medium projections, foreign immigration was projected to exceed the level by 10% during each five-year interval. For the low projections, foreign immigration was projected to be 10% less than the level for each five-year interval. Foreign emigration was assumed to equal 22.5% of foreign immigration for each series of projections. The distribution of foreign immigrants by age, sex, race, and ethnicity was based on the patterns observed between 1995 and Net migration is the difference between the number of inmigrants and the number of out-migrants. Reflecting the recent slowdown in migration to Florida, the medium projections imply net migration levels (including both domestic and foreign migrants) of 132,000 per year between 2005 and These levels are projected to rise to 176,000 per year between 2010 and 2015 and 210, ,000 thereafter. The low projections imply net migration levels of 55,000 per year between 2005 and 2010, 106,000 between 2010 and 2015, and 150, ,000 thereafter. The high projections imply net migration levels of 270, ,000 per year over the entire projection horizon. To put these numbers into perspective, net migration averaged 260, ,000 per year during the 1970s, 1980s, and 1990s. It should be noted that annual levels have fluctuated considerably over time, ranging between 107,000 and 450,000 for individual years. Projections were made in five-year intervals, with each projection serving as the base for the following projection. Projected in-migration for each five-year interval was added to the survived Florida population at the end of the interval and projected out-migration was subtracted, giving a projection of the population age five and older. Births were projected by applying age-specific birth rates (adjusted for child mortality) to the projected female population of each race/ethnicity group. These birth rates were based on Florida birth data for and imply a total fertility rate of approximately 1.8 births per woman for non-hispanic whites, 2.3 for non-hispanic nonwhites, and 2.4 for Hispanics. In the low and medium series, birth rates were projected to remain constant at levels for non-hispanic whites and to decline gradually over time for Hispanics and non-hispanic nonwhites. In the high series, birth rates were projected to remain constant at levels for all three race/ ethnicity groups. Natural increase is the excess of births over deaths. In Florida, natural increase rose steadily during the Baby Boom, reaching almost 70,000 by It fell to less than 20,000 per year in the mid-1970s, rose to 64,000 in 1990, fell to 35,000 in 2000, and rose again to 71,000 in Our low and medium projections imply that natural increase will decline slowly over time, reaching annual levels of 9,000 and 22,000, respectively, in Our high projections imply that natural increase will rise to 84,000 per year in and decline slowly thereafter, reaching 67,000 in As a final step in the projection process, projections for non- Hispanic whites, non-hispanic nonwhites, and Hispanics were added together to provide projections of the total population. The medium projections of total population for 2010 and 2015 were adjusted to be consistent with state population forecasts produced by the State of Florida s Demographic Estimating Conference. None of the projections after 2015 had any further adjustments. County projections The cohort-component method is a good way to make population projections at the state level, but is not necessarily the best way to make projections at the county level. Many counties in Florida are so small that the number of persons in each age-sex-race-ethnicity category is inadequate for making reliable cohort-component projections. Even more important, county growth patterns are so volatile that a single technique based on data from a single time period may provide misleading results. We believe more useful projections of total population can be made by using several different techniques and historical base periods. For counties, we started with the population estimate produced by the Bureau of Economic and Business Research for April 1, 2008 (Florida Estimates of Population: April 1, 2008, January 2009, Bureau of Economic and Business Research, University of Florida). These estimates were extrapolated forward to 2010 using data on population changes between 2006 and 2008, changes in monthly electric customer data between March 2008 and January 2009, and our judgment regarding likely future trends. For years after 2010, we made nine projections for each county using five different techniques and three historical base periods ( , , and ). The five techniques were: 1. Linear the population will change by the same number of persons in each future year as the average annual change during the base period. 2 Florida Population Studies Bureau of Economic and Business Research

22 2. Exponential the population will change at the same percentage rate in each future year as the average annual rate during the base period. 3. Share of growth each county s share of state population growth in the future will be the same as its share during the base period. 4. Shift share each county s share of the state population will change by the same annual amount in the future as the average annual change during the base period. 5. Constant each county s population will remain constant at its 2010 value. For the linear and share-of-growth techniques we used base periods of five, ten, and fifteen years, yielding three sets of projections for each technique. For the exponential and shift-share techniques we used a single base period of ten years, yielding one set of projections for each technique. The constant technique was based on data for a single year. This methodology produced nine projections for each county for each projection year (2015, 2020, 2025, 2030, and 2035). We calculated three averages from these projections: one using all nine projections, one in which the highest and lowest were excluded, and one in which the two highest and two lowest were excluded. In most counties the medium projection was based on the latter, but in a few counties we chose a different projection series based on our evaluation of recent population trends and their implications for the future. In all counties, the projections were adjusted to be consistent with the total population change implied by the state projections. We also made adjustments in several counties to account for changes in institutional populations such as university students and prison inmates. Adjustments were made only in counties in which institutional populations account for a large proportion of total population or where changes in the institutional population have been substantially different than changes in the rest of the population. In the present set of projections, adjustments were made for Alachua, Baker, Bradford, Calhoun, Columbia, DeSoto, Dixie, Franklin, Gadsden, Gilchrist, Glades, Gulf, Hamilton, Hardee, Hendry, Holmes, Jackson, Jefferson, Lafayette, Leon, Liberty, Madison, Okeechobee, Santa Rosa, Sumter, Suwannee, Taylor, Union, Wakulla, Walton, and Washington counties. Range of projections surrounding the medium projections. The low and high projections were based on analyses of past population forecast errors for counties throughout the United States, broken down by population size and growth rate. The low and high projections indicate the range into which approximately half of future county populations will fall, if the future distribution of forecast errors in Florida is similar to the past distribution in the United States. The high and low projections themselves, however, do not have equal probabilities of occurring. In Florida, the probability that a county s future population will be above the high projection is greater than the probability that it will fall below the low projection. The range between the low and high projections varies according to the county s population size in 2008 (less than 25,000; 25,000 or more), rate of population growth between 1998 and 2008 (less than 15%; 15 29%; 30 49%; and 50% or more) and the length of the projection horizon (mean absolute percent errors grow about linearly with the length of the projection horizon). Our studies have found that the distribution of absolute percent errors tends to remain fairly stable over time, leading us to believe that the low and high projections provide a reasonable range of errors for most counties. It must be emphasized, however, that the actual future population of any given county could be above the high projection or below the low projection. For the medium series of projections, the sum of the county projections equals the state projection for each year (except for slight differences due to rounding). For the high and low series, however, the sum of the county projections does not equal the state projection. This occurs because potential variation around the medium projection is greater for counties than for the state as a whole. Thus, in most instances the sum of the low projections for counties is lower than the state s low projection and the sum of the high projections is higher than the state s high projection. Note: The projections published in this bulletin refer solely to permanent residents of Florida; they do not include tourists or seasonal residents. Acknowledgement Funding for these projections was provided by the Florida Legislature. The techniques described above were used to produce the medium series of county projections. This is the series we believe will generally provide the most accurate forecasts of future population change. We also produced a series of low and high projections to provide an indication of the uncertainty Bureau of Economic and Business Research Florida Population Studies 3

23 Projections of Florida Population by County, County Census Estimate Projections, April 1 and State April 1, 2000 April 1, ALACHUA 217, ,388 Low 245, , , , , ,500 Medium 256, , , , , ,400 High 266, , , , , ,900 BAKER 22,259 25,890 Low 25,200 25,800 26,300 26,700 26,900 27,000 Medium 26,300 28,000 29,900 31,800 33,600 35,200 High 27,300 30,300 33,500 36,900 40,400 44,000 BAY 148, ,307 Low 164, , , , , ,600 Medium 171, , , , , ,000 High 178, , , , , ,800 BRADFORD 26,088 29,059 Low 28,200 28,800 28,900 29,000 29,000 28,900 Medium 29,100 30,600 31,700 32,900 34,000 35,100 High 30,000 32,400 34,600 36,900 39,200 41,500 BREVARD 476, ,213 Low 534, , , , , ,900 Medium 556, , , , , ,800 High 579, , , , , ,700 BROWARD 1,623,018 1,758,494 Low 1,693,200 1,682,000 1,671,200 1,655,800 1,635,400 1,610,400 Medium 1,745,600 1,787,200 1,835,000 1,880,000 1,921,200 1,958,900 High 1,797,900 1,896,700 2,001,800 2,107,400 2,212,600 2,317,400 CALHOUN 13,017 14,310 Low 13,700 13,600 13,400 13,200 12,900 12,600 Medium 14,300 14,700 15,200 15,700 16,100 16,500 High 14,900 15,900 17,100 18,200 19,400 20,500 CHARLOTTE 141, ,781 Low 160, , , , , ,800 Medium 167, , , , , ,400 High 174, , , , , ,100 CITRUS 118, ,043 Low 138, , , , , ,800 Medium 144, , , , , ,800 High 150, , , , , ,900 CLAY 140, ,168 Low 177, , , , , ,600 Medium 186, , , , , ,200 High 196, , , , , ,800 COLLIER 251, ,854 Low 315, , , , , ,900 Medium 331, , , , , ,200 High 348, , , , , ,000 COLUMBIA 56,513 66,121 Low 65,000 66,400 67,600 68,500 68,800 68,700 Medium 67,800 71,900 76,700 81,300 85,700 89,900 High 70,500 77,900 86,100 94, , ,200 DESOTO 32,209 34,487 Low 34,000 34,500 35,000 35,300 35,600 35,700 Medium 35,100 36,600 38,400 40,100 41,800 43,300 High 36,100 38,900 41,900 45,000 48,100 51,400 DIXIE 13,827 15,963 Low 15,200 15,300 15,100 14,800 14,200 13,600 Medium 16,100 17,400 18,400 19,400 20,300 21,100 High 17,100 19,500 21,800 24,100 26,400 28,900 4 Florida Population Studies Bureau of Economic and Business Research

24 Projections of Florida Population by County, (continued) County Census Estimate Projections, April 1 and State April 1, 2000 April 1, DUVAL 778, ,971 Low 880, , , , , ,700 Medium 917, ,500 1,041,000 1,104,700 1,165,000 1,222,400 High 954,200 1,056,700 1,168,200 1,284,000 1,402,900 1,525,100 ESCAMBIA 294, ,480 Low 305, , , , , ,100 Medium 315, , , , , ,300 High 324, , , , , ,100 FLAGLER 49,832 95,512 Low 90, , , , , ,300 Medium 96, , , , , ,000 High 102, , , , , ,700 FRANKLIN 9,829 12,331 Low 11,900 12,200 12,100 11,800 11,600 11,300 Medium 12,400 13,300 13,700 14,100 14,400 14,800 High 12,900 14,400 15,300 16,300 17,300 18,400 GADSDEN 45,087 50,611 Low 50,400 51,200 51,900 52,600 53,100 53,400 Medium 51,900 54,300 57,000 59,700 62,200 64,700 High 53,500 57,700 62,200 66,900 71,800 76,800 GILCHRIST 14,437 17,256 Low 16,200 16,000 15,700 15,100 14,300 13,100 Medium 17,600 19,000 20,600 22,200 23,700 25,100 High 19,100 22,100 25,700 29,400 33,300 37,400 GLADES 10,576 11,323 Low 11,200 11,100 11,100 11,000 10,800 10,600 Medium 11,600 12,100 12,600 13,000 13,500 13,900 High 12,100 13,100 14,100 15,100 16,200 17,300 GULF 14,560 16,923 Low 15,800 15,300 14,700 14,000 13,300 12,400 Medium 16,800 17,300 17,900 18,400 18,900 19,400 High 17,900 19,400 21,100 22,800 24,600 26,400 HAMILTON 13,327 14,779 Low 14,200 13,900 13,700 13,400 13,100 12,800 Medium 14,800 15,100 15,600 16,000 16,400 16,700 High 15,400 16,400 17,400 18,500 19,700 20,800 HARDEE 26,938 27,909 Low 27,500 27,200 26,900 26,500 26,100 25,700 Medium 28,400 28,900 29,500 30,100 30,700 31,200 High 29,200 30,700 32,200 33,800 35,300 36,900 HENDRY 36,210 41,216 Low 41,000 42,200 43,400 44,400 45,100 45,300 Medium 42,700 45,700 49,200 52,700 56,100 59,200 High 44,400 49,600 55,300 61,300 67,600 74,000 HERNANDO 130, ,907 Low 161, , , , , ,100 Medium 170, , , , , ,500 High 178, , , , , ,600 HIGHLANDS 87, ,207 Low 97, , , , , ,100 Medium 101, , , , , ,400 High 106, , , , , ,500 HILLSBOROUGH 998,948 1,200,541 Low 1,157,100 1,191,300 1,228,200 1,255,400 1,271,300 1,276,800 Medium 1,205,300 1,290,600 1,392,500 1,491,200 1,583,000 1,668,800 High 1,253,500 1,398,500 1,563,200 1,733,700 1,907,000 2,083,300 Bureau of Economic and Business Research Florida Population Studies 5