Two Simple Methods to Improve Official Statistics for Small Subpopulations

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...

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Main Author: Nikolas Mittag
Format: Article
Language:English
Published: European Survey Research Association 2018-12-01
Series:Survey Research Methods
Subjects:
Online Access:https://ojs.ub.uni-konstanz.de/srm/article/view/7309
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author Nikolas Mittag
author_facet Nikolas Mittag
author_sort Nikolas Mittag
collection DOAJ
description 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.
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spelling doaj.art-b591f74593bc4172a58f7211ff4116ea2022-12-21T23:44:18ZengEuropean Survey Research AssociationSurvey Research Methods1864-33612018-12-0112310.18148/srm/2018.v12i3.7309Two Simple Methods to Improve Official Statistics for Small SubpopulationsNikolas Mittag0CERGE-EIMany 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.https://ojs.ub.uni-konstanz.de/srm/article/view/7309survey errorsmall populations food stampsgovernment transfersofficial statistics
spellingShingle Nikolas Mittag
Two Simple Methods to Improve Official Statistics for Small Subpopulations
Survey Research Methods
survey error
small populations food stamps
government transfers
official statistics
title Two Simple Methods to Improve Official Statistics for Small Subpopulations
title_full Two Simple Methods to Improve Official Statistics for Small Subpopulations
title_fullStr Two Simple Methods to Improve Official Statistics for Small Subpopulations
title_full_unstemmed Two Simple Methods to Improve Official Statistics for Small Subpopulations
title_short Two Simple Methods to Improve Official Statistics for Small Subpopulations
title_sort two simple methods to improve official statistics for small subpopulations
topic survey error
small populations food stamps
government transfers
official statistics
url https://ojs.ub.uni-konstanz.de/srm/article/view/7309
work_keys_str_mv AT nikolasmittag twosimplemethodstoimproveofficialstatisticsforsmallsubpopulations