Using the American Community Survey Benefits and Challenges (2007) / Chapter Skim
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PART II: Technical Issues, 4 Sample Design and Survey Operations
PART II: Technical Issues, 4 Sample Design and Survey Operations
Pages 139-183
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From page 139... ...
PART II Technical Issues
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The sections of this chapter address the following specific aspects of the ACS sample design and operations that, in the panel's judgment, require continued research, evaluation, and experimentation by the Census Bureau: • Sampling operations for housing units, including initial sampling using the Master Address File (MAF) as the sampling frame and subsampling for nonresponding housing units; • Data collection for housing units, including mode of data collection and residence rules; • Sampling and data collection for group quarters; and • Data preparation, including confidentiality protection, collapsing of tables for large sampling errors, inflation adjustments, tabula
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. 4-A.1 Developing the Initial Sample The initial ACS sample of housing unit addresses in the 50 states and the District of Columbia for 2005 and subsequent years consists of approximately 250,000 housing units per month and approximately 3 million housing unit addresses for the year (about 2.3 percent of 129.5 million housing units on the MAF in 2005)
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The first-phase segmentation of MAF addresses proceeds on a continuous basis in two waves each August and January. The process began in August 2004 when all of the housing unit addresses on the MAF at that time were assigned to equal segments for years 2005–2009.
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uses one of five different sampling rates for the addresses within each geographic block (an area of, on average, about 15–20 housing units)
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-- defined as eligible governments with an estimated fewer than 200 occupied housing units; 2. Blocks in smaller governmental units -- defined as eligible govern ments with an estimated 200 to fewer than 800 occupied housing units;
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The designation of initial sampling rates is based on estimates of occupied rather than total housing units because blocks in governmental units or census tracts with large numbers of seasonally vacant housing units would be undersampled if total housing units were the criterion. The estimates of occupied housing units are obtained from the current MAF address count times an estimate from the 2000 census of the proportion of occupied housing units for blocks in the governmental unit or census tract.
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rates are used to subsample nonresponding housing units in census tracts with predicted lower (higher) levels of mail and
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Delivery Sequence File (DSF) , along with housing units that were deleted in the 2000 census but continue to appear on the DSF;3 • new housing units added from ongoing listings of addresses in ar eas of new construction that are conducted for the Census Bureau's other household surveys; and • new housing units added from the Community Address Updating System (CAUS)
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These deficiencies in the DSF led to a decision by the Census Bureau for the 2000 census to conduct a complete canvass of all 8.2 million blocks in 1999 in order to bolster the completeness of the 2000 Decennial Master Address File. Previously, the Census Bureau had planned to conduct a complete canvass only in rural areas and to spot-check addresses in urban areas.
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Moreover, because the census-based housing unit controls are subject to error, there will likely be inconsistencies between ACS estimates of housing units for 2010 and the 2010 census results. 4-A.4.b The MAF in Rural Areas In rural areas, the CAUS was developed because of the difficulty of using the DSF to identify addresses that should be added to the MAF.
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(Research is under way to determine if there are effective ways to use the DSF for address updates in rural areas.) The identification of CAUS counties for listing is based on an algorithm that considers the address characteristics of existing MAF records for the county, changes in postcensal housing unit estimates for the county, and changes in the DSF tallies for the county.
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This program should include periodic field checks on MAF addresses, com parisons with housing unit estimates for specific areas, comparisons with the e-StARS database, and comparisons with the results of the 2009 complete block canvass that will be used to prepare the 2010 census MAF. The program should also include studies of methods to improve the listing of small multiunit addresses in urban areas, charac teristics of duplicate housing units, and characteristics of undeliverable mail addresses.
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2. The ACS sample of household members in year t represents people who lived in the January MAF housing stock at some time in the 5 Eachyear's ACS estimates actually pertain to responses obtained during that year, some of which may come from housing units that were included in the sample for November or December of the preceding year but did not provide data until January or February.
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As explained below, the July 1 controls, which derive from the previous census, are not consistent with the underlying ACS data. 4-A.5.b ACS Housing and Population Controls For 1-year period estimates from the ACS for housing, the application of a single control for total housing units -- assuming it is accurate -- will capture growth (or decline)
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The CAPI subsampling uses three different rates in order to approximately equalize the precision of estimates for areas with higher and lower mail/CATI response rates. The effect of the CAPI subsampling and the 8 percent reduction in the initial sample in census tracts expected to have high mail and telephone response is to reduce the size of the final sample to about 2.1 million housing units per year nationwide, or about 10.5 million housing units cumulated over 5 years.
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4-A.5.d Variable Initial Sampling Rates Similar to the long-form sample design, the ACS sample design specifies a limited set of variable initial sampling rates that are introduced in order to make the estimates for small governmental jurisdictions about as precise as the estimates for census tracts in larger jurisdictions. Yet many of the estimates for small areas will not meet commonly accepted statistical standards given the overall size limit of the ACS sample.
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255 (8) Standard errors for estimates based on an effective sample size of 255 housing units compared with an equally weighted sample of 340 units 15% larger (9)
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(This discussion ignores the effects of other weight adjustments, such as population and housing unit controls.) The wider variation in final sampling rates will increase the sampling error of ACS estimates relative to long-form-sample estimates for geographic areas and population groups that incorporate varying sampling rates -- either from the initial sampling, the CAPI subsampling, or both sources.
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This increase would provide a sample about 55 percent larger than the current ACS. To attain this larger final sample size would require an initial 5-year ACS sample size of about 23.5 million housing unit addresses instead of the current 15 million.6 Even with an increase in the ACS sample size of the magnitude just outlined, many small-area estimates, particularly for small population groups, 6 The originally planned initial ACS sample size over 5 years was 30 million housing units, which would have generated a final sample size of about 19 million housing units (see Section 1-B.3)
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. 4-B DATA COLLECTION FOR HOUSING UNITS 4-B.1 Mode of Collection The ACS, like many surveys, uses a mixed-mode data collection design in order to maximize response while containing costs.
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SAMPLE DESIGN AND SURVEY OPERATIONS 3. CAPI of a subsample of mail/CATI nonrespondents.
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(weighted) Mail CATI CAPI Response Predominantly white census tracts 60.5 7.4 28.1 96.0 Predominantly Asian census tracts 58.6 4.1 32.5 95.2 Predominantly black census tracts 34.9 8.9 48.6 92.4 Predominantly Hispanic census tracts 34.2 8.3 53.3 95.8 Predominantly American Indian and Alaska Native 16.6 2.6 69.9 89.1 census tracts Total housing units 56.2 7.3 31.9 95.4 NOTES: The distributions represent the percentages of housing units that responded by mail, CATI, and CAPI (with CAPI responses weighted to account for subsampling)
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There may also be important geographic area differences in response modes. Overall, the use of mailout-mailback, CATI, and CAPI interviewing results in high housing unit response rates to the ACS.
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USING THE ACS: BENEFITS AND CHALLENGES changed to a current residence concept, as is more common in polls and other person-based surveys. Specifically, the ACS residence concept is based on a "2-month rule:" people who live for more than 2 months at a sample address are assumed to be residents of that unit.
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SAMPLE DESIGN AND SURVEY OPERATIONS BOX 4-3 Residence Rule Guidance on the ACS Mail Questionnaire Page 1: Asks respondent to provide the number of people who "are living or staying at this address." Page 2, left-hand margin: Asks respondent to "READ THESE INSTRUCTIONS FIRST." • LIST everyone who is living or staying here for more than 2 months. • LIST anyone else staying here who does not have another usual place to stay.
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A possibly confounding effect could occur from the 3-month data collection window for each month's sample that is part of the ACS design. What is the effect, for example, on estimates of occupied versus vacant housing units when a seasonal resident does not respond by mail or CATI and has left the area by the time of the CAPI interview?
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. 4-C.1 Group Quarters and the MAF For the 2000 census, the Census Bureau originally constructed separate MAFs for GQs and housing units using somewhat different procedures.
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It is likely that the ACS GQ population based on the current GQ MAF will differ in some respects from the 2010 census GQ population. 4-C.2 Sample Design for Group Quarters The sampling for GQs is different from the sampling for housing units (see Hefter, 2005b)
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to large GQs with more than one hit to select another group of 10 to be interviewed. The assignment to each month of the year of sampled small GQs and one or more sampled groups of 10 people in larger GQs is similar to the procedure for housing units, in that the sampled small GQs and sampled groups of 10 people in large GQs for a state are combined, sorted, and systematically assigned to months January–December.
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The individual GQ resident questionnaire contains the same person items as the household questionnaire but none of the housing unit questions, except for the question on receipt of food stamps. It is clear that field representatives cannot do all of the interviewing of GQ sample persons face to face, although that is the preferred procedure.
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Most national household surveys, in contrast, cover just the civilian noninstitutional population, including residents of housing units and noninstitutional GQs. The Current Population Survey Annual Social and Economic Supplement (CPS ASEC)
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A decision to alter the universe for the ACS by excluding some or all GQ residents would require the use of an appropriate set of population estimates to use as controls for the ACS estimates. For example, household population estimates are used in the 2005 ACS estimates, and noninstitutionalized population estimates are used in other household surveys.
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, the collapsing of tables because of large sampling errors (4-D.2) , inflation adjustments of income and housing value and costs (4-D.3)
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The report recommends research on techniques for providing useful, innovative public-use microdata sets that increase informational utility without increasing disclosure risk. In the context of ACS microdata, the panel encourages the Census Bureau to revisit its decision not to include month of data collection on the PUMS as a confidentiality protection measure.
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Thus, the fact that 60 months of data are averaged to provide 5-year period estimates for block groups, census tracts, and small governmental jurisdictions should go a long way toward protecting individual respondents, even without additional steps to protect confidentiality. The Census Bureau, of course, will not, and should not, rely solely on averaging as a protection, but it should carefully consider the costs and benefits of each additional protection procedure and conduct research to identify the most useful protection techniques.
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Collectively, the workers in a traffic analysis zone are unlikely to include the same individuals over the 5-year period because of changes in residence and employment. The Census Bureau has time before 5-year period estimates become available in which to develop appropriate confidentiality protection strategies and techniques for transportation tables and other data products.
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Whenever possible, the Census Bureau should prefer confidentiality protection procedures that preserve the ability to aggregate smaller geographic areas into larger, user-defined areas. 4-D.2 Collapsing Tables for Large Sampling Errors In addition to procedures to protect confidentiality, the Census Bureau applies collapsing (or suppression)
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After sufficient information has been gleaned about the extent of data collapsing, the Census Bureau, in consultation with data users, should assess whether its collapsing rules are sound or should be modified for one or more subject areas.
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One advantage is that 1year, 3-year, and 5-year period estimates for a large city or county will all be expressed in dollars for the same (latest) year -- for example, 2009 dollars in the case of estimates for 2009, 2007–2009, and 2005–2009.
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For example, by examining how well the trends in BLS county wage data estimate 1-year period income from the 5-year period estimates for large counties, a user might be able to develop a procedure for estimating latest-year incomes from the 5-year period estimates for small counties. To determine how to produce the most helpful data on income, housing costs, and housing value, the Census Bureau should initiate a two-part discussion with users.
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The full universe for ACS data products, beginning in 2006, will include the housing unit and GQ populations, although some tables may be published for subuniverses, such as households or the noninstitutional population. (Prior to 2006, tabulations included just the housing unit population.)
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period estimates for user-defined statistical subareas of large cities (aggregations of census tracts or block groups) and counties (aggregations of places and towns)
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As the time approaches when 1-year, 3-year, and 5-year period estimates must be provided for thousands of geographic areas every year (including 5-year estimates for over 200,000 individual block groups) , the immensity of the review task threatens to overwhelm the analyst staff.
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