National Academies Press: OpenBook

A Guidebook for Using American Community Survey Data for Transportation Planning (2007)

Chapter: Appendix J - Seasonality Analyses Using ACS

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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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Suggested Citation:"Appendix J - Seasonality Analyses Using ACS." National Academies of Sciences, Engineering, and Medicine. 2007. A Guidebook for Using American Community Survey Data for Transportation Planning. Washington, DC: The National Academies Press. doi: 10.17226/13895.
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The datasets provided by the Census Bureau contained four universe tables designed to inves- tigate the availability of seasonal data from ACS. These data tables are listed in Table J.1. MPOs in both these areas were sent shape files with data on occupancy status from ACS, and were asked to provide inputs on seasonal units by TAZ. Variable Sampling Rates Over Three Years The ACS test sites were originally sampled at a high rate that allowed three-year averages to be compared to the Census 2000 at the tract and county level. However, many of the counties used for creating the ACS and Census 2000 data were not sampled at 15 percent. The final sam- pling rates per county are listed in Table J.2. Using Broward County as an example, the cumulative sampling rate was only 9.5 percent. With such a low-sampling rate, analysis at the TAZ level was not possible. Figure J.1 shows the sampling rate in Broward County TAZs with the ACS compared to the Census 2000. The sam- pling ratio of ACS to Census 2000 is lower than 75 percent in almost all TAZs and lower than 50 percent for over half the TAZs. Input from the Broward County MPO helped develop a process to identify Broward County TAZs with seasonal variation.1 Broward County has a population of 1.6 million people, and is divided into 898 TAZs. The average “seasonal” vacancy of housing units (741,000) is 6.3 percent for the county. TAZs with more than 10 percent “seasonal” vacancy status were defined as sea- sonal areas/TAZs. Data for several Census tables were then accumulated for seasonal TAZs, and compared to the rest of the county. Of the 898 TAZs in the county, 116 are classified as “sea- sonal.” By using this definition, most of coastal Broward County is classified as seasonal—areas where seasonal variation in vacancy would be expected. Figure J.2 shows the spatial distribution of the seasonal TAZs. Occupancy of Housing Units—Broward County, Florida Figure J.3 shows Broward County occupancy rates summarized by both seasonal TAZs and the rest of county (non-seasonal) TAZs. The occupancy rates for the rest of the county (non- seasonal) are consistent at about 92 percent, while the seasonal areas, as expected, fluctuate dur- 263 A P P E N D I X J Seasonality Analyses Using ACS 1 Personal correspondence with Ted Leonard, and Christine Heshmati, Broward MPO on April 29, 2004. Ted Leonard provided an MS Excel file with percentage of seasonal units by TAZ.

ing the year. The average occupancy for the ACS three-year average, and Census 2000 were nearly the same for both areas. In the seasonal areas, the average occupancy rate indicated by the ACS and CTPP data is similar at 71.3 percent and 72.1 percent, respectively. In the rest of the county (non-seasonal), the rates also are similar with 91.9 percent with the ACS and 92.5 percent with the CTPP. Civilian Employed Population—Broward County, Florida A review of employment data offers another way to confirm the seasonal nature of some areas of Broward County. Figures J.4 and J.5 show labor data aggregated for TAZs in seasonal areas, and the rest of the county (non-seasonal), respectively. Data on the Civilian Population (over 16 years of age), employment and population not in labor force are summarized. As reflected in the occupancy data, the ACS data show a decrease in the civilian population during Quarters 2 and 3 for the seasonal TAZs (Figure J.4), while the rest of the county does not show much variation (Figure J.5). A comparison of civilian employment data for the seasonal TAZs from the ACS and Census 2000 (shown in Figure J.6) shows that Quarters 2 and 3 of ACS data is closer to Census-derived 264 A Guidebook for Using American Community Survey Data for Transportation Planning Table Universe Content 5 Persons 16+ Calendar Quarter (5) by Employment Status (7) 22 Workers Means of Transportation (11) by Calendar Quarter (5) 38 Mean Household Income by Calendar Quarter (5) 39 Households Median Household Income by Calendar Quarter (5) 44 Number of housing units sampled by Calendar Quarter (5) 45 Housing Units Calendar Quarter( 5) by Occupancy Status (3) Census 2000 100 Percent Counts 1999-2001 ACS Sampling Rates Census 2000 Sampling Rates Housing Units Housing Units Housing Units Geography Total Occupied Population Total Occupied Population Total Occupied Population Pima County, Arizona 366,737 332,330 821,712 13.4% 9.4% 8.6% 12.5% 12.5% 13.7% San Francisco County, California 346,527 329,700 756,976 9.6% 6.1% 5.5% 11.7% 11.7% 11.8% Broward County, Florida 741,043 654,445 1,603,094 9.5% 6.7% 5.9% 11.7% 11.4% 11.5% Lake County, Illinois 225,919 216,297 623,378 10.3% 7.1% 6.6% 14.3% 14.3% 14.4% Hampden County, Massachusetts 185,876 175,288 441,799 14.6% 10.0% 9.4% 13.4% 13.5% 13.5% Douglas County, Nebraska 192,672 182,194 451,878 15.2% 11.0% 10.5% 13.9% 13.9% 13.9% Bronx County, New York 490,659 463,212 1,285415 10.2% 5.1% 4.4% 11.3% 11.5% 11.6% Franklin County, Ohio 471,016 438,778 1,046,872 9.4% 6.6% 6.2% 14.1% 14.1% 14.1% Multnomah County, Oregon 288,561 272,098 643,798 15.0% 10.7% 10.0% 14.1% 14.1% 14.0% Total for Nine Counties 3,309,010 3,064,362 7,674,922 11.2% 7.5% 6.8% 12.7% 12.7% 12.7% A Rates presented here are based on Decennial Census Totals. Table J.1. Seasonal tables included in the ACS dataset. Table J.2. Sampling rates in ACS compared to census 2000.

values. As shown in Figure J.7, for the rest of the county (non-seasonal) TAZs, the ACS data, Census 2000, and quarterly ACS data area similar. Means of Transportation to Work—Broward County, Florida Table J.3 shows a comparison of mode shares for ACS and Census 2000 by calendar quarter and area type for Broward County. In the seasonal TAZs, the ACS three-year average shows 3.6 percent fewer workers carpooling to work than in the rest of the county (non-seasonal). As shown in Figure J.8, there were fluctuations in carpool rates in Quarter 2 and Quarter 4. ACS also showed lower transit percentages in the seasonal TAZs. In the rest of the county (non-seasonal), the ACS data shows a gradual increase in carpooling rates throughout the four quarters from 12.1 percent to 13.6 percent. One of the issues with seasonality measurements from ACS is the use of intercensal estimates for weighting that are not seasonally adjusted. If possible, data for the four quarters must be weighted by intercensal estimates that are seasonally adjusted. The Short Form of the decennial census usually included a question on seasonal occupancy and estimates could be developed for housing unit counts by calendar quarter. Seasonality Analyses Using ACS 265 0.0000 - 0.2500 0.2501 - 0.5000 0.5001 - 0.7500 0.7501 - 1.0000 1.0001 - 2.0000 Figure J.1. Sampling ratio. ACS to Census 2000

266 A Guidebook for Using American Community Survey Data for Transportation Planning Figure J.2. Seasonal TAZs in Broward County, Florida. 40 50 60 70 80 90 100 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Seasonal Area Rest of County Occupancy Rate Figure J.3. Occupancy rates of housing units by calendar quarter.

Defining Seasonal TAZs—Pima County, Arizona Based on MPO input, we accumulated TAZs into those considered seasonal based on per- centage of housing units per TAZ that were seasonally occupied.2 Pima County has a population of 821,000 people, and is divided into 545 TAZs. The average vacancy of housing units (366,735) is 9.4 percent for the county. Of the 545 TAZs in Pima County, 42 were classified as “seasonal” Seasonality Analyses Using ACS 267 0 10,000 20,000 30,000 40,000 50,000 60,000 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Total Civilian Employed - At Work Not in Labor Force Figure J.4. Civilian employment (seasonal TAZs in Broward County, Florida). 0 50,000 100,000 150,000 200,000 250,000 300,000 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Total Civilian Employed - At Work Not in Labor Force Figure J.5. Civilian employment (rest of Broward County TAZs, non-seasonal). 2 Personal correspondence with Sandra White, and Karen Lamberton, Pima COG on August 25, 2004. Sandra White provided an MS Excel file defining seasonal TAZs by type of seasonality.

268 A Guidebook for Using American Community Survey Data for Transportation Planning 20 30 40 50 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Census 2000 (43.4%) ACS 5 Year Average (41.9 %) 20 30 40 50 60 70 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Census 2000 (61.3 %) ACS 3 Year Average (61.8 %) Figure J.6. Percent Civilian Employment-ACS versus Census 2000 (seasonal TAZs in Broward County, Florida). Figure J.7. Percent civilian employment-ACS versus Census 2000 (rest of Broward County, Florida TAZs, non-seasonal). Seasonal Area – Percent of Workers Drive Alone Carpool Transit Bike/Walk Others Quarter 1 80.2% 10.6% 1.4% 3.4% 4.4% Quarter 2 82.9% 7.1% 1.0% 2.8% 6.4% Quarter 3 79.7% 11.3% 1.7% 1.6% 5.6% Quarter 4 81.2% 7.9% 2.4% 2.3% 6.3% ACS Total 81.0% 9.2% 1.6% 2.5% 5.7% Census 2000 79.3% 10.8% 1.9% 2.5% 6.0% Rest of County (Non-Seasonal) – Percent of Workers Quarter 1 79.5% 12.1% 2.6% 1.7% 4.0% Quarter 2 78.9% 12.6% 2.6% 2.0% 4.0% Quarter 3 79.0% 12.9% 2.3% 1.5% 4.3% Quarter 4 78.4% 13.6% 2.2% 1.9% 3.9% ACS Total 79.0% 12.8% 2.4% 1.8% 4.0% Census 2000 80.2% 12.3% 2.2% 1.7% 3.9% Table J.3. Means of transportation to work in Broward County, florida.

and further categorized as retirement, university or vacation areas. Figure J.9 shows the spatial distribution of the TAZs with seasonal variation. Although Pima County was sampled at a rate of 13.4 percent of occupied housing units, most of the tracts in ACS were sampled at a rate less than three quarters that of the Census (see Figure J.10). Even when these tracts are aggregated, there are very few housing units classified as “vaca- tion” units. Table J.4 shows Census 2000 totals for housing units in the vacation, university and retirement seasonal areas and the rest of the county. Occupancy of Housing Units—Pima County, Arizona Figure J.11 shows occupancy status by seasonal area and rest of Pima County. The occupancy rates for the rest of the county are fairly consistent across the calendar quarters at 90.5 to 92.5 per- Seasonality Analyses Using ACS 269 0 2 4 6 8 10 12 14 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Seasonal Rest of County Figure J.8. Carpool to work percentage in Broward County, Florida. Vacation Retirement Retirement University Figure J.9. Seasonal TAZs in Pima County, Arizona.

cent, while the seasonal areas show fluctuations as expected. The occupancy is high for the first, third, and fourth calendar quarters and drops for the second quarter in the university area. Occu- pancy in vacation homes decreases in the fourth quarter but the number of vacation units are very small. Retirement areas show higher occupancy in the first and fourth quarters. Table J.5 shows the overall comparison of ACS and Census 2000 for the different types of areas. Civilian Employed Population—Pima County, Arizona Figures J.12 and J.13 show the civilian population over 16, workers at work, and population not in labor force for both the seasonal areas and the rest of the county (non-seasonal). Just like occupied housing units, the ACS data in seasonal areas show a decrease in the civil- ian employment during Quarter 2 and Quarter 3. The rest of the county does not show much 270 A Guidebook for Using American Community Survey Data for Transportation Planning Type of Seasonality Total Occupied Vacant Vacation 800 350 440 University 5,650 5,350 310 Retirement 25,960 19,460 6,540 Total Seasonal 32,410 25,160 7,290 Rest of County (Non-Seasonal) 334,390 307,440 27,370 Table J.4. Total housing units in seasonal and non-seasonal areas of Pima County, Arizona. Vacation Retirement Retirement University 0-0.125 0.126-0.25 0.25-0.5 0.5-0.75 >0.75 Figure J.10. Sampling ratio-ACS versus Census 2000 (Pima County, Arizona).

Seasonality Analyses Using ACS 271 20 30 40 50 60 70 80 90 100 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Rest of County Seasonal Area University Retirement Vacation Figure J.11. Occupancy rates of housing units by calendar quarter. 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Total: Civilian Employed - At Work Not in Labor Force Figure J.12. Civilian employment (seasonal TAZs in Pima County, Arizona). ACS Census 2000 Seasonal 78.0 77.6 University 83.9 94.7 Retirement 78.1 75.0 Vacation 45.1 43.8 Rest of the County 91.2 91.9 Table J.5. Occupancy rates-acs versus Census 2000.

variation. A comparison of percent of civilian employed population for ACS quarterly data versus Census 2000 data (Figures J.14 and J.15) show that Quarter 2 of ACS data is closer to Census-derived values. The graphs are similar to those presented for Broward County showing that ACS data do measure seasonal variation. Means of Transportation to Work—Pima County, Arizona The most significant modes to work for Pima County are drove alone, carpool and bike/walk. Table J.6 shows mode shares for the chief modes by calendar quarter and area type. Figures J.16, J.17, and J.18 show the variability in modes for the four quarters. Vacation areas are not shown here because the numbers of workers are very small. 272 A Guidebook for Using American Community Survey Data for Transportation Planning 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Total: Civilian Employed - At Work Not in Labor Force Figure J.13. Civilian employment (rest of Pima County, Arizona TAZs, non-seasonal). 0 10 20 30 40 50 60 70 80 90 100 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Seasonal Vacation University Retirement Census 2000 = 30.3% ACS = 27.7% Figure J.14. Civilian employment percentage-ACS versus Census 2000 (seasonal in Pima County, Arizona TAZs).

Seasonality Analyses Using ACS 273 20 30 40 50 60 70 Quarter 1 Quarter 2 Quarter 3 Quarter 4 Census 2000 (58.7 %) ACS 3 Year Average (58.6 %) Figure J.15. Percentage civilian employment-ACS versus Census 2000 (rest of Pima County, Arizona TAZs, non-seasonal). Drove Alone Carpool Bike/Walk Quarter 1 University 47.0% 9.0% 33.9% Retirement 79.7% 10.5% 2.0% Seasonal 64.8% 10.0% 16.5% Rest of County 74.4% 14.7% 3.3% Total 74.1% 14.6% 3.8% Quarter 2 University 53.8% 3.0% 31.7% Retirement 81.1% 10.0% 1.7% Seasonal 69.4% 8.5% 13.7% Rest of County 75.9% 13.1% 3.6% Total 75.7% 12.9% 3.9% Quarter 3 University 51.9% 7.2% 30.4% Retirement 85.0% 4.0% 1.3% Seasonal 70.6% 5.5% 13.8% Rest of County 75.6% 13.4% 3.8% Total 75.5% 13.1% 4.1% Quarter 4 University 60.3% 9.7% 23.0% Retirement 70.2% 14.6% 4.6% Seasonal 65.9% 11.8% 13.7% Rest of County 76.5% 12.7% 3.2% Total 76.1% 12.6% 3.6% ACS-3 Year Average University 53.3% 7.9% 29.2% Retirement 78.5% 9.7% 2.4% Seasonal 67.4% 9.1% 14.3% Rest of County 75.6% 13.4% 3.5% Total 75.3% 13.3% 3.8% Census 2000 University 49.0% 8.5% 32.1% Retirement 76.0% 11.8% 4.1% Seasonal 63.8% 10.2% 16.7% Rest of County 74.8% 15.0% 3.1% Total 74.4% 14.8% 3.6% Table J.6. Means of transportation to work in Pima County, Arizona.

274 A Guidebook for Using American Community Survey Data for Transportation Planning 30 40 50 60 70 80 90 Quarter 1 Quarter 2 Quarter 3 Quarter 4 University Retirement All Seasonal Rest of County 0 2 4 6 8 10 12 14 16 18 20 Quarter 1 Quarter 2 Quarter 3 Quarter 4 University Retirement All Seasonal Rest of County Figure J.16. Drove alone to work percentage in Pima County, Arizona. Figure J.17. Carpool to work percentage in Pima County, Arizona. 0 5 10 15 20 25 30 35 40 Quarter 1 Quarter 2 Quarter 3 Quarter 4 University Retirement All Seasonal Rest of County Figure J.18. Bike/walk to work percentage in Pima County, Arizona.

There is a lot of variability across the seasonal areas and across calendar quarters. The ACS data show that many workers in the university area walk/bike to work in the first three quarters but drive alone or carpool in the last quarter. Similarly, workers in the retirement community are shown to have significant increase in carpool rates in the winter. The rest of the county does not show much variability in these modes to work. Seasonality Analyses Using ACS 275

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TRB's National Cooperative Highway Research Program (NCHRP) Report 588: A Guidebook for Using American Community Survey Data for Transportation Planning explores incorporating the U.S. Census Bureau's American Community Survey (ACS) data into the transportation planning processes at national, state, metropolitan, and local levels. The report examines ACS data and products and demonstrates their uses within a wide range of transportation planning applications.

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