Income Data for Policy Analysis: A Comparative Assessment of Eight Surveys. Income Post-Stratification

12/23/2008

As we have noted previously, the MEPS survey weights are post-stratified to poverty distributions observed in the CPS. Post-stratification to population totals by age, sex, and race/ethnicity is widely used as a means to correct for undercoverage and differential non-response, but as we demonstrated in Chapter III, it is important to ensure that the survey totals to be adjusted and the post-stratum totals to which they are adjusted reflect the same universe. When an income or poverty distribution obtained from one survey is used to post-stratify the weights for another survey, it is important that the concepts of income or poverty used in the two surveys agree. The survey descriptions presented in Chapter II underscore how difficult it may be to achieve such agreement, and the empirical findings presented in Chapter IV show how survey measures of income that are similar in some respects may be quite different in others.

In Chapter IV we also speculated that a portion of the difference between CPS and MEPS estimates of total families and people with earnings could have arisen from the post-stratification to the CPS poverty distribution. While this is not something that we can evaluate with a simulation, the MEPS survey contractors who perform the post-stratification have access to the requisite data to assess the impact of including the CPS poverty distribution among the post-stratum totals.  For such an assessment the preliminary MEPS weights prior to post-stratification would have to be post-stratified to CPS control totals that exclude the poverty distribution.  Estimates of total income, total earners, total families, and other characteristics could then be prepared using these alternative weights and the results compared to estimates using the person weights on the public use file. In our view, this could provide an extremely interesting methodological study that could shed light on the full range of consequences of post-stratifying the MEPS weights to the CPS poverty distribution. Such a study would be enhanced if the post-stratification itself were altered experimentally to test the impact of alternative refinements to the MEPS poverty estimates and the survey universe, including, in particular, the treatment of sample members in families with missing data on one or more family members.

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