. "Appendix C Alternatives to the Multiyear Period Estimation Strategy for the American Community Survey." Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press, 2007.
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Using the American Community Survey: Benefits and Challenges
A number of adjustments will then be made including nonresponse adjustments and poststratification adjustments to postcensal housing unit and population estimates produced by the Census Bureau’s Population Division. The housing and population controls are averages of the 1-year controls for the multiple years. Details of the weighting procedures are given in Chapters 5 and 6 of the panel’s report.
The multiyear estimates produced by the Census Bureau’s weighting scheme can be viewed as period estimates: they represent averages that reflect both changing characteristics and changes in the area’s populations across the years. The limitation of these estimates, and changes in them over time, is that they can be difficult to interpret and may not suit user needs. The panel therefore invited me to investigate other estimation strategies for the multiyear data, and in particular the use of several years of data to produce an estimate for a single year (e.g., year 3 or 5 from 5 years of ACS data) in place of the period estimate. The fact that any strategy that is adopted would have to implemented in a massive production environment imposes constraints: It needs to be simple and require no auxiliary data; and each unit (household or person) should have only one analysis weight within the given 3- or 5-year data set in order to enable a wide range of consistent analyses across variables and areas of different sizes.
There are strong arguments that one can make in support of a strategy that uses different weights for producing single-year estimates for areas of different sizes from multiyear data. For example, there are definite advantages to borrowing strength over more years for areas with small populations and for variables that are more stable in time. However, ACS data users would likely find the non-uniformity an unwelcome complication and possibly undesirable, at least during the start up phase of ACS. The paper therefore focuses exclusively on uniform strategies.
Two simplifying assumptions are made throughout the paper in order to convey the essence of a principled strategy for producing single-year estimates with desirable properties from multiyear data. The first is that the population size of an area does not change over the 3- or 5-year estimation period. This assumption may hold reasonably well for many areas, but there will be areas for which it does not hold. The second assumption is that the 1-year estimates for each of the years in the period have the same variance. With the assumption of a constant population size, the ACS sample size in an area is likely to be approximately the same each year. Thus, if the element variances are about the same across the years, the second assumption will hold approximately. While element variances may often be reasonably equal, that will not always be the case.
Under these two assumptions, and ignoring the nonresponse and calibration weighting adjustments, the Census Bureau’s period estimate reduces to a simple average of the 1-year estimates for the period. In order to produce