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5 The Weighting of ACS 1-Year Period Estimates
Pages 184-208

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From page 184...
... responses are collected from a subsample of the housing units that have not yet responded. For purposes of analysis, the Census Bureau classifies a monthly sample as the sample units resolved in that month (the tabulation month)
From page 185...
... Given this definition of the monthly samples, all the data used for analysis for a 1-year or multiyear period are collected during the specified calendar year or years. (An attraction of using tabulation months is that data collection is completed at the end of the year; if the monthly samples were defined in terms of sample months, it would be necessary to wait until the following February before all the data were collected for a given year.)
From page 186...
... The person weights are adjusted to make the weighted person counts for major demographic subgroups in an estimation area conform to independent population subgroup estimates obtained by updating counts from the last census.
From page 187...
... In particular, substantial variation in the weighting adjustments can appreciably affect some ACS estimates, likely reducing bias, but probably also lowering precision. Information on the distribution of the weighting adjustments is provided below for some of the adjustments that were used with the 2004 ACS test survey.
From page 188...
... The variation in the initial selection probabilities resulted from the need to satisfy precision requirements for estimates for governmental units of different sizes. The subsampling rates for CAPI interviews were determined by cost factors and the need to retain adequate sample sizes for census tracts with lower expected mail and CATI response rates.
From page 189...
...  THE WEIGHTING OF ACS -YEAR PERIOD ESTIMATES Total weight of all units sampled for the month (excluding the CAPI factor) VMS = Total weight of all units resolved in the month (including the CAPI factor)
From page 190...
... Over all months of the 2004 ACS test survey, the value of the VMS factor for the 5th percentile is 0.87 and that for the 95th percentile is 1.24. The effect of this additional variation in the resulting weights on sampling errors is likely to be small.
From page 191...
... The first stage of the noninterview adjustment (NIF1) is carried out within cells created by the cross-classification of building type and census tract, with census tracts combined if the cells contain too few responding housing units.
From page 192...
... The MBF adjustments are generally small, with only 5 percent being 0.96 or less and 5 percent being 1.03 or more, but the combined effects of their use, together with the noninterview adjustment factors in step 3, on the biases and sampling errors of ACS estimates are not transparent. The MBF procedure, in essence, has three steps.
From page 193...
... For example, it is not clear that the NIFM weighting adjustments, which are confined to CAPI cases but drop the tract-level control, lead to less biased estimates for the cells in the cross-classification of the control variables, let alone estimates for other variables. Also, since the estimates of the cell totals for the control variables under the weights developed up to this point are equated to those using the NIFM-adjusted weights, their sampling errors are those of the latter estimates.
From page 194...
... There are several issues concerning the use of the housing unit control factor, including the quality of the PE housing unit estimates. These issues are taken up in Section 5-C below.
From page 195...
... is to identify any extremely large weight adjustments to the base weights over all the subsequent steps in the weighting process. To avoid large increases to sampling errors, the weighting adjustments are revised by collapsing adjustment cells if any overall weight adjustment factor exceeds 8.
From page 196...
... Recommendation 5-1: The Census Bureau should conduct an in-depth review of the weighting scheme used for producing ACS 1-year period estimates and assess a range of alternative schemes that might improve the quality of the estimates. 5-C HOUSING UNIT CONTROLS After step 4 in the weighting process, the weighted total number of all units sampled from the MAF for the year is equated to the number of units in the MAF from which the sample was selected.
From page 197...
... However, while the PE housing unit and population estimates both start from the last population census, they are developed independently thereafter, thus reducing the force of the argument for consistency. The PE program produces a postcensal estimate of the number of housing units in each county for July 1 of each year.
From page 198...
... for the housing unit county estimates for 2000 obtained in this evaluation by 1990 size of the county. Overall the MAPE was 4.6 percent, but it varied from 1.9 percent for the largest counties to 7.3 percent for the smallest counties.
From page 199...
... In the case of undercoverage, the factors increase the weights of MAF housing units to represent those not included in the MAF frame under an assumption that the missed housing units are missing at random. This assumption would be false if, for instance, the proportion of vacant units in the postcensal estimates is higher than in the MAF, as it might well be.
From page 200...
... Recent research by the Census Bureau (Reese, 2007) examined differences between the independent housing unit estimates for 2002–2005 and the housing unit addresses on the MAF used for the ACS in these years.
From page 201...
... As with the PE housing unit estimates, the population estimates start from the 2000 census counts and adjust for estimated changes between April 1, 2000, and July 1 of the year in question. At the outset, the 2000 census population is divided into the household population and the group quarters population.
From page 202...
... The Census Bureau has conducted an evaluation of the 2000 county total population estimates by comparing them with the 2000 census counts, in a similar way to the evaluation of the housing unit estimates described in the previous section (Blumerman and Simon, 2006)
From page 203...
... For this purpose we dropped the race classification because of the problems with the differences in that classification between the population estimates and the 2000 census, retaining only Hispanic versus non-Hispanic (equivalent to collapsing the first five of the six race/ethnicity categories listed above)
From page 204...
... TABLE 5-4 Mean Absolute Percentage Error (MAPE) of July 1, 1999, Estimation Area Population Estimates Compared with April 1, 2000, Census Counts, by Cells Based on Combinations of Sex, Ethnicity, and Age (Excludes Cells with Fewer Than 500 People in the 2000 Census)
From page 205...
... One strategy is to apply the cross-classification controls at a higher level of geography than estimation areas, with hopefully less error in the control totals. A drawback of this strategy is that ACS population estimates for counties and cities would not be consistent with the PE estimates for those areas.
From page 206...
... 0 TABLE 5-5 Percentage Ratio of July 1, 1999, Estimation Area Population Estimates to April 1, 2000, Census Counts, by Cells Based on Combinations of Sex, Ethnicity, and Age (Excludes Cells with Fewer Than 500 People in the 2000 Census) Number of Population Classification Cells 80%– 90%– 95%– 100%– 105%– 110%– 120%+ Total <80% No subclassification 1,950 0.1 2.4 14.6 61.4 20.6 0.7 0.2 0.0 100.0 Sex 3,900 0.1 2.9 15.0 58.9 21.8 0.9 0.2 0.0 100.0 Ethnicity 3,401 19.7 7.5 9.1 36.8 18.3 3.1 3.0 2.4 100.0 Age group 23,397 2.0 13.9 20.0 26.4 20.6 10.2 5.8 1.1 100.0 Sex by ethnicity 6,130 16.1 7.3 9.3 39.1 19.8 3.3 2.7 2.4 100.0 Sex by age group 46,430 2.5 14.8 19.2 24.8 19.7 11.0 6.6 1.3 100.0 Ethnicity by age group 28,553 8.5 13.1 16.9 22.4 19.2 10.3 7.0 2.5 100.0 Sex by ethnicity by age group 53,020 6.6 13.9 17.1 22.3 19.1 11.0 7.7 2.3 100.0 NOTE: Estimation areas are large counties and groups of smaller counties with at least 16,000 people; the median size is 55,000 people; the average size is 145,000 people; the District of Columbia is included as an estimation area (information from the U.S.
From page 207...
... . In contrast, the population controls used in the ACS are midyear population estimates based on different residence rules and different sources than the yearly accumulation of ACS monthly samples.
From page 208...
... Concomitantly, the panel views research on methods to improve the postcensal population estimates as a priority area for the Census Bureau. An important component of that research should be to investigate using ACS data more fully than currently in producing national estimates of international migration and particularly for estimating domestic migration.


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