Two Simple Methods to Improve Official Statistics for Small Subpopulations

Nikolas Mittag

Abstract


Many important statistics are known from official records for the entire population, but have to be estimated for subpopulations. I describe two simple data combination methods that reduce the substantial sampling error of the commonly used direct survey estimates for small subpopulations. The first estimator incorporates information from repeated cross-sections, while the second estimator uses the knowledge of the statistic for the overall population to improve accuracy of the estimates for subpopulations. To evaluate the estimators, I compare the estimated number of female and elderly recipients of a government transfer program by county to the "true" number from administrative data on all recipients in New York. I find that even the simple estimators substantially improve survey error. Incorporating the statistic of interest for the overall population yields particularly large error reductions and can reduce non-sampling error.

Keywords


survey error, small populations food stamps, government transfers, official statistics

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DOI: http://dx.doi.org/10.18148/srm/2018.v12i3.7309

Copyright (c) 2018 Nikolas Mittag

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