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From page 31... ... 4.1 Accuracy of ACS Data A key objective for the Census Bureau in migrating from decennial census Long Form data collection to the continuous data collection approach of ACS was to improve the quality of the data collected by improving the ways the data are collected and processed. To evaluate whether this objective is being achieved, the Census Bureau and other researchers have evaluated quality measures for the initial ACS effort and have compared the early ACS results to the decennial census Long Form. Read the entire page →
From page 32... ... Non-response due to inability or unwillingness of housing units to participate can cause bias if the characteristics of non-respondents are different from those of respondents. 32 A Guidebook for Using American Community Survey Data for Transportation Planning Read the entire page →
From page 33... ... Using ACS Data 33 13 U.S. Census Bureau, Meeting 21st Century Demographic Data Needs – Implementing the American Community Survey: Report 2: Demonstrating Survey Quality (May 2002) Read the entire page →
From page 34... ... With a sampling rate of 3 million housing units per year, data accumulated over ﬁve years will correspond to a sample size of less than threefourths of the roughly 16.7 percent sampling rate achieved with the Long Form Survey. Considering the effect of sample size alone on the standard error of the estimates and assuming a constant sampling rate of 2.5 percent, the ACS estimates will have a standard error equal to 2.8 times, 1.6 times, and 1.25 times that of the Long Form for annual estimates, three- and ﬁve-year moving averages, respectively.14 By examining the ACS test site data, the Census Bureau researchers drew the following conclusions: While the targeted levels of sampling error for single year estimates were met overall, differentials in levels of mail response for some population groups indicate that sampling error is disproportionately higher, suggesting the need for design changes.15 Even with improved survey follow-up procedures to address the problem of differential response to the initial mail surveys, the authors concluded that The ACS five-year averages are expected to have somewhat higher [relative standard error levels] Read the entire page →
From page 35... ... 15. Characteristic Self-Response Rate Total Housing Unit Non-Response Occupied Housing Unit Non-Response Rate Allocation Rates Population Item Total Allocation Rates Occupied Housing Unit Total Allocation Rates Vacant Housing Unit Total Allocation Rates Population and Occupied Housing Unit Total Allocation Rates Sample Completeness Rates Housing Sample Completeness Household Population Sample Completeness ACS 55.3% 4.4% 5.2% 6.5% 7.7% 23.2% 6.9% 92.9% 90.4% Census 2000 68.1% 9.7% 8.7% 11.2% 15.8% 19.8% 12.8% 90.3% 91.1% Source: United States Census Bureau, 2004. Read the entire page →
From page 36... ... The ACS development program -- supported by a complete and accurate address system -- will simplify the decennial design, resulting in improved coverage in 2010.20 The researchers also report that C2SS achieved the quality standards, budgets, and schedules that the Census Bureau had established. The C2SS effort came in slightly under budget, and most of the workload issues identiﬁed with the effort were attributed to the fact that the C2SS was 36 A Guidebook for Using American Community Survey Data for Transportation Planning 20 U.S. Read the entire page →
From page 37... ... This is done to improve the reliability of the data reported for small geographic levels, where the smaller annual sample sizes are associated with large standard errors. 4.2.1 Census Bureau Multiple-Year Estimation Once the ACS program is fully implemented for Census-deﬁned areas with population under 20,000, ﬁve-year moving averages will be released. Read the entire page →
From page 38... ... This, however, is at the expense of increasing the potential for problems with the inter38 A Guidebook for Using American Community Survey Data for Transportation Planning Figure 4.1. Minnesota counties with published 2004 ACS data. Read the entire page →
From page 39... ... Number of Geographic Areas Geography Nation Census Regions Census Divisions States Counties Minor Civil Divisions Places American Indian and Alaska Native Areas Metropolitan, Micropolitan, and Consolidated Statistical Areas Congressional Districts School Districts Census Tracts Block Groups Three-Year Estimates Population of 20,000 or More 1 4 9 51 1,811 592 1,983 41 905 436 3,290 Single Year Estimates Population of 65,000 or More 1 4 9 51 761 97 476 15 561 436 879 Five-Year Estimates 1 4 9 51 3,141 16,536 25,161 768 923 436 14,505 65,443 208,790 Source: United States Census Bureau, Design and Methodology: American Community Survey, Technical Paper 67 (May 2006) Read the entire page →
From page 40... ... Percent Who Carpool In Year 1 Number Who = =p1 Carpool In Year 1 Total Number of Workers In Year 1 = N T 1 1 40 A Guidebook for Using American Community Survey Data for Transportation Planning 22 U.S. Census Bureau, Design and Methodology: American Community Survey, Technical Paper 67 (May 2006) Read the entire page →
From page 41... ... For the ﬁrst year of the analysis, 2010, the city population is about 60,000, so threeand ﬁve-year ACS estimates will be available, and the two towns both have populations below 20,000, so only ﬁve-year estimates are available. Table 4.5 shows hypothetical ACS data and reported estimates for the county and its three county subdivision components for several years. Read the entire page →
From page 42... ... Estimates from ACS Collected Data Population Age 16+ Workers Percent of Workers Commuting More Than 60 Minutes Workers Commuting More than 60 Minutes Year Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County 2005 54,104 12,717 13,025 79,846 22,183 5,214 5,340 32,737 0.24 0.23 0.22 0.24 5,324 1,199 1,175 7,698 2006 55,186 13,607 13,416 82,209 22,074 5,715 5,366 33,155 0.24 0.24 0.22 0.24 5,298 1,372 1,181 7,851 2007 56,290 14,560 13,818 84,668 23,079 6,261 5,665 35,005 0.24 0.25 0.22 0.24 5,539 1,565 1,246 8,350 2008 57,416 15,579 14,233 87,227 22,966 6,699 5,693 35,358 0.24 0.26 0.23 0.24 5,512 1,742 1,309 8,563 2009 58,564 16,669 14,660 89,893 22,840 7,168 5,717 35,725 0.24 0.27 0.24 0.25 5,482 1,935 1,372 8,789 2010 59,735 17,836 15,100 92,671 23,894 7,848 6,040 37,782 0.24 0.28 0.25 0.25 5,735 2,197 1,510 9,442 2011 62,722 19,085 15,553 97,359 25,089 8,206 6,221 39,516 0.24 0.29 0.26 0.25 6,021 2,380 1,617 10,018 2012 65,858 19,466 16,019 101,344 27,002 8,565 6,568 42,135 0.25 0.30 0.27 0.26 6,751 2,570 1,773 11,094 2013 69,151 19,856 16,500 105,506 27,660 8,538 6,600 42,798 0.26 0.31 0.28 0.27 7,192 2,647 1,848 11,687 2014 72,608 20,253 16,995 109,856 29,769 8,709 6,968 45,446 0.27 0.32 0.29 0.28 8,038 2,787 2,021 12,846 ACS Annual Data Release Population Age 16+ Workers Percent of Workers Commuting More Than 60 Minutes Workers Commuting More than 60 Minutes Year Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County 2005 n n n 79,846 n n n 32,737 n n n 0.24 n n n 7,698 2006 n n n 82,209 n n n 33,155 n n n 0.24 n n n 7,851 2007 n n n 84,668 n n n 35,005 n n n 0.24 n n n 8,350 2008 n n n 87,227 n n n 35,358 n n n 0.24 n n n 8,563 2009 n n n 89,893 n n n 35,725 n n n 0.25 n n n 8,789 2010 n n n 92,671 n n n 37,782 n n n 0.25 n n n 9,442 2011 n n n 97,359 n n n 39,516 n n n 0.25 n n n 10,018 2012 65,858 n n 101,344 27,002 n n 42,135 0.25 n n 0.26 6,751 n n 11,094 2013 69,151 n n 105,506 27,660 n n 42,798 0.26 n n 0.27 7,192 n n 11,687 2014 72,608 n n 109,856 29,769 n n 45,446 0.27 n n 0.28 8,038 n n 12,846 Table 4.5. Hypothetical Data Releases for a County and Its City and Towns. Read the entire page →
From page 43... ... . ACS Three-Year Average Data Release Population Age 16+ Workers Percent of Workers Commuting More Than 60 Minutes Workers Commuting More than 60 Minutes Year Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County 2005 -- -- -- 79,846 - – - – - – - – -- -- -- -- - – - – - – - – 2006 -- -- -- 82,209 - – - – - – - – -- -- -- -- - – - – - – - – 2007 56,822 n n 84,668 23,108 n n 34,625 0.24 n n 0.24 5,546 n n 8,201 2008 57,976 n n 87,227 23,383 n n 35,535 0.24 n n 0.24 5,612 n n 8,501 2009 59,154 n n 89,893 23,654 n n 36,429 0.24 n n 0.24 5,677 n n 8,826 2010 60,356 n n 92,671 23,941 n n 37,394 0.24 n n 0.25 5,746 n n 9,203 2011 62,960 n n 97,359 24,980 n n 39,310 0.24 n n 0.25 5,995 n n 9,825 2012 65,498 n n 101,344 26,428 n n 41,540 0.24 n n 0.26 6,437 n n 10,627 2013 68,577 n n 105,506 27,659 n n 43,162 0.25 n n 0.26 6,924 n n 11,376 2014 72,016 20,665 n 109,856 29,286 8,953 n 45,225 0.26 0.31 n 0.27 7,624 2,776 n 12,358 ACS Five-Year Average Data Release Population Age 16+ Workers Percent of Workers Commuting More Than 60 Minutes Workers Commuting More than 60 Minutes Year Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County Acity Bee Town Cee Ville Alpha County 2005 -- -- -- 79,846 - – - – - – - – -- -- -- -- - – - – - – - – 2006 -- -- -- 82,209 - – - – - – - – -- -- -- -- - – - – - – - – 2007 -- -- -- 84,668 - – - – - – - – -- -- -- -- - – - – - – - – 2008 -- -- -- 87,227 - – - – - – - – -- -- -- -- - – - – - – - – 2009 59,716 15,511 14,666 89,893 23,996 6,587 5,892 36,475 0.24 0.25 0.23 0.24 5,759 1,657 1,333 8,749 2010 60,948 16,607 15,116 92,671 24,374 7,150 6,044 37,569 0.24 0.26 0.23 0.24 5,850 1,870 1,404 9,125 2011 63,509 18,042 15,808 97,359 25,399 7,797 6,321 39,517 0.24 0.27 0.24 0.25 6,096 2,116 1,520 9,732 2012 65,824 19,173 16,346 101,344 26,345 8,325 6,541 41,212 0.24 0.28 0.25 0.25 6,381 2,341 1,640 10,363 2013 68,498 20,139 16,870 105,506 27,415 8,741 6,751 42,906 0.25 0.29 0.26 0.26 6,758 2,542 1,760 11,061 2014 71,557 20,920 17,379 109,856 28,923 9,076 7,023 45,023 0.25 0.30 0.27 0.27 7,314 2,727 1,901 11,942 Read the entire page →
From page 44... ... sets the conﬁdentiality rules for all data releases.23 44 A Guidebook for Using American Community Survey Data for Transportation Planning 23 See www.census.gov/eos/www/sestats.html. Read the entire page →
From page 45... ... Using ACS Data 45 24 See www.census.gov/td/stf3/append_c.html. 25 Chuck Purvis, Metropolitan Transportation Commission, Oakland, California, e-mail posted to the CTPP news listserve on February 19, 2004. Read the entire page →
From page 46... ... Table 4.8 shows pairs of geographies 46 A Guidebook for Using American Community Survey Data for Transportation Planning 26 Summary File 3 consists of 813 detailed tables of Census 2000 social, economic, and housing characteristics compiled from a sample of approximately 19 million housing units (about 1 in 6 households) that received the Census 2000 Long Form questionnaire. Read the entire page →
From page 47... ... If the median of these covariances is Using ACS Data 47 29 See:www.statistics.gov.uk/census2001/. Part 3: Without Thresholds Part 3: With Thresholds Data Census 2000 ACS Total Geographic Pairs with Reported Work Flows 8,228 6,368 Total Workers with Reported Work Flows 207,120 181,563 Total Geographic Pairs with Reported Work Flows 2,644 1,673 Total Workers with Reported Work Flows 147,080 118,234 Part 1 Total Workers 199,220 202,024 Source: FHWA CTPP Status Report, April 2004. Read the entire page →
From page 48... ... – Mailable addresses ≥ 75% and predicted levels of completed interviews prior to subsampling > 60% – Mailable addresses < 75% and/or predicted levels of completed interviews prior to subsampling ≤ 60% All other blocks (estimated occupied housing units in block > 1200 and estimated occupied housing units in tract ≤ 2000) – Mailable addresses ≥ 75% and predicted levels of completed interviews prior to subsampling > 60% – Mailable addresses < 75% and/or predicted levels of completed interviews prior to subsampling ≤ 60% 2005 Final Sampling Rate 10.0% 6.9% 3.6% 1.6% 1.7% 2.1% 2.3% Source: United States Census Bureau, Design and Methodology: American Community Survey, Technical Paper 67 (May 2006) Read the entire page →
From page 49... ... Confidence intervals for a large sample parameter with a mean value X and a standard error Y Read the entire page →
From page 50... ... The Census Bureau calculates the standard errors for all estimates reported in ACS data products using procedures that account for the sample design and estimation methods. These procedures are described in the Census Bureau's Accuracy of the Data reports, which are updated annually (available at www.census.gov/acs/www/UseData/Accuracy/Accuracy1.htm) Read the entire page →
From page 51... ... of a sum Notes: The Census Bureau states that this method will underestimate the standard error if the items in a sum are highly positively correlated, and will overestimate the standard error if the items in the sum are highly negatively correlated. This equation also is valid for the standard error of the difference of ACS reported estimates: SE(Xˆ − Yˆ ) Read the entire page →
From page 52... ... 52 A Guidebook for Using American Community Survey Data for Transportation Planning Read the entire page →
From page 53... ... Imputation rate tables are available with the other base tables on the American FactFinder website. • Compare the Census 2000 and ACS questionnaires for the item(s) Read the entire page →
From page 54... ... at the county and census tract level for the 36 ACS test sites.31 54 A Guidebook for Using American Community Survey Data for Transportation Planning 30 See www.census.gov/acs/www/AdvMeth/Reports.htm. Read the entire page →
From page 55... ... • Economic estimates included – Employment status, – Commuting to work, – Occupation, – Industry, – Class of worker, – Income, and – Poverty status. • Housing estimates included – Units in structure, – Year structure built, – Rooms, – Year householder moved into unit, – Vehicles available, – House heating fuel, – Occupants per room, – Value, – Mortgage status and selected monthly owner costs, – Selected monthly owner costs as a percentage of household income, – Gross rent, and – Gross rent as a percentage of household income. Read the entire page →
From page 56... ... . Differences in race responses are partly traced to the use of permanent ﬁeld staff where the response "some other race" is not a response category in most other surveys and a much smaller number of these responses are observed in ACS than in Census 2000."34 Differences also were seen in labor force participation, mean travel time (Census 2000 estimates are consistently higher) Read the entire page →
From page 57... ... Estimate Category ACS – Census 2000 Difference Units in Structure Large Year Structure Built Large Number of Rooms Large Year Householder Moved into Unit Small Number of Vehicles Moderate House Heating fuel Moderate Selected Housing Characteristics Large Occupants per Room Large Housing Value Moderate Mortgage Status and Selected Owner Costs Small Selected Monthly Costs as a Percentage of Household Income Moderate Gross Rent Moderate Gross Rent as a Percentage of Household Income Large Source: United States Census Bureau, 2004. Table 4.12. Read the entire page →
From page 58... ... 37 "Meaningful" differences are deﬁned by the authors as statistically signiﬁcant differences of 2 percent or more between ACS results and Census 2000 results. Variable Population Aged 21-64 with Disability Commute Via Carpool Commute via Public Transportation Mean Travel Time to Work Civilian Employment Median Household Income Mean Earnings Poverty Status of Individuals Vehicles Available in Household = 1 ACS 19.0% 7.0% 57.0% 40.4 minutes 50.3% $26,185 $41,552 56.8% 30.1% Census 2000 31.8% 9.3% 53.9% 43.1 minutes 45.7% $27,611 $44,116 58.8% 28.8% Source: Salvo, Lobo, and Calabrese, 2004. Read the entire page →
From page 59... ... There were signiﬁcant differences in the percentage of foreign-born, educational attainment, and language spoken at home -- the author states that the rates of allocation in Census 2000 are the reason for the differences. Response rates were signiﬁcantly improved under the ACS for most difﬁcult items such as income. Read the entire page →
From page 60... ... Based on seasonality in these counties, the authors anticipate ACS values to be higher for older population, median age, occupied housing units, median income, and housing values, and lower for unemployment and average household size. Because rural census tracts are so large in geographic extent and encompass governmental units, the authors would like to have data at the minor civil division level, in addition to census tracts. Read the entire page →
From page 61... ... • When we correlated the differences that were found with other tract and TAZ variables, we detected some systematic biases in the residence-based estimates, most notably for the following variables: – Disability status; – Disability status by mode to work; – Tenure (speciﬁcally, the owned-with-mortgage category) ; – Number of workers in the household by vehicles available by household income; – Poverty status (speciﬁcally the category for incomes between 100 percent and less than 150 percent of poverty) Read the entire page →
From page 62... ... While the use of the current residence concept gives a more accurate picture of an area's population, it does present some challenges (for example, in integrating ACS data with intercensal population estimates, which employ the decennial census usual residence deﬁnition) .38 Reference Period Since ACS data are collected continuously, the annual ACS estimates represent cumulative data over the 12-month interview cycle, and thus average annual conditions. Read the entire page →
From page 63... ... For this guidebook, the following variables were analyzed: • Mode to work, • Travel time to work, Using ACS Data 63 39 This method can consist, for example, of adjusting the weights used to obtain the ACS estimates so that the ACS weighted annual average for selected characteristics would be equal to that of the census. 40 In this method, a model (e.g., a regression) Read the entire page →
From page 64... ... Of course, these benchmarking factors are crude measures of the differences between Census 2000 and ACS, but analyses like these could help analysts understand and report trend data that rely on the different datasets. 64 A Guidebook for Using American Community Survey Data for Transportation Planning Mode Drove-Alone Carpool Pooled Sample 1.0099 0.9249 Public Transportation Walked MSA/CMSA < 1 Million 0.9701 0.7579 MSA/CMSA: 1-5 Million 1.0043 0.8496 MSA/CMSA > 5 Million 1.0861 0.9265 Vehicles Available Pooled Sample MSA/CMSA < 1 Million MSA/CMSA: 1-5 Million MSA/CMSA > 5 Million Zero 0.9164 0.8887 0.9617 Average Number 1.0182 Travel Time Pooled Sample Mean travel time 0.9552 Table 4.17 Means of transportation to work. Read the entire page →
From page 65... ... The type of estimate to use will depend on the purpose of the analysis, as follows: • Consistency -- If the characteristics of two populations in areas of similar geographic scales (e.g., populations of two counties or two states) are compared, it is important to use the same Using ACS Data 65 Travel Time Pooled Sample Percent of commuters with short commutes (< 20 minutes) Read the entire page →
From page 66... ... 66 A Guidebook for Using American Community Survey Data for Transportation Planning 42 See www.census.gov/acs/www/Downloads/ACS/accuracy2002change.pdf. Read the entire page →
From page 67... ... = 1.0 percent ME(DIFF) = 1.65 × 0.9 = 1.5 percent Lower bound = 1.0 percent – 1.5 percent = −0.5 percent Upper bound = 1.0 percent + 1.5 percent = 2.5 percent Discussion Since the lower bound and upper bound have different signs, the year-to-year difference is not signiﬁcant at the 90 percent conﬁdence level. Read the entire page →
From page 68... ... With the standard errors of 0.4 minutes for 2001 and 0.6 minutes for 2002, the difference in the mean travel time would have to had been more than 1.2 minutes for the difference to be statistically signiﬁcant. Alternatively, if the 2002 standard error were 0.27 minutes, the difference of 0.8 minutes would have been statistically signiﬁcant at the 90 percent conﬁdence level: DIFF = (41.8 − 41.0) Read the entire page →
From page 69... ... . 4.6.3 Multiyear Averaging/Analysis of Overlapping Averages The main advantage of moving averages, as compared to annual estimates, is that moving averages smooth the data and are thus more reliable (lower standard errors, less year-to-year variation) Read the entire page →
From page 70... ... 4.6.4 Seasonality Analysis Using ACS ACS data are collected throughout the year, as opposed to at a single point in time like the census Long Form data, so it will be important for data users to remember that analyses of other data in conjunction with ACS data will need to reﬂect the full year. Because seasonality is very interesting from a transportation planning perspective, as travel patterns can vary signiﬁcantly throughout the year, U.S. Read the entire page →
From page 71... ... Effect of Missing Data. Given the large standard errors of the ACS estimates, any further reduction in sample size will adversely impact the quality of its estimates, which will be reﬂected in larger standard errors. Read the entire page →
From page 72... ... 72 A Guidebook for Using American Community Survey Data for Transportation Planning Read the entire page →

From page 31...

... 4.1 Accuracy of ACS Data A key objective for the Census Bureau in migrating from decennial census Long Form data collection to the continuous data collection approach of ACS was to improve the quality of the data collected by improving the ways the data are collected and processed. To evaluate whether this objective is being achieved, the Census Bureau and other researchers have evaluated quality measures for the initial ACS effort and have compared the early ACS results to the decennial census Long Form.