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Using the American Community Survey: Benefits and Challenges
subareas of large cities (aggregations of census tracts or block groups) and counties (aggregations of places and towns).
Data Quality Review
Recommendation 4-14: The Census Bureau should increase its research and development on automated tools and standardized procedures to facilitate timely review and quality control of the large volume of ACS data products.
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.
Recommendation 5-2: The Census Bureau should evaluate the quality of the postcensal housing unit estimates and the MAF sampling frame in relation to one another. In the light of this evaluation, the Census Bureau should assess the suitability of the current housing unit control factor adjustment and modify it as necessary.
The Census Bureau should attempt to identify areas in which improvements can be made to the postcensal housing unit estimates and to the MAF sampling frame. In particular, it should investigate an integrated approach for developing the postcensal housing unit estimates and for continuously updating the MAF that would benefit both and reduce the variability in the housing unit control factor.
Recommendation 5-3: As a high priority, the Census Bureau should undertake research to evaluate the effect of the postcensal population controls on ACS estimates and to examine alternative methods of making the adjustment that may be superior to the one currently used (including dispensing with the population controls entirely). The Census Bureau should make users aware in ACS documentation that biases in the ACS estimates caused by errors in the population controls are not reflected in the margins of error reported with the estimates and should conduct research to examine the effects of these errors on ACS estimates.
The Census Bureau should also give priority to research on ways to improve the postcensal population estimates at the county level, including estimates of internal migration and international immigration and the classification of race and ethnicity.