Creating improved survey data products using linked administrative-survey data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11640%2F19%3A00509294" target="_blank" >RIV/00216208:11640/19:00509294 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1093/jssam/smy017" target="_blank" >http://dx.doi.org/10.1093/jssam/smy017</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1093/jssam/smy017" target="_blank" >10.1093/jssam/smy017</a>
Alternative languages
Result language
angličtina
Original language name
Creating improved survey data products using linked administrative-survey data
Original language description
Recent research linking administrative to survey data has laid the groundwork for improvements in survey data products. However, the opportunities have not been fully realized yet. In this article, our main objective is to use administrative-survey linked microdata to demonstrate the potential of data linkage to reduce survey error through model-based blended imputation methods. We use parametric models based on the linked data to create imputed values of Medicaid enrollment and food stamp (SNAP) receipt. This approach to blending data from surveys and administrative data through models is less likely to compromise confidentiality or violate the terms of the data sharing agreements among the agencies than releasing the linked microdata, and we demonstrate that it can yield substantial improvements of estimate accuracy. Using the blended imputation approach reduces root mean squared error (RMSE) of estimates by 81 percent for state-level Medicaid enrollment and by 93 percent for substate area SNAP receipt compared with estimates based on the survey data alone. Given the high level of measurement error associated with these important programs in the United States, data producers should consider blended imputation methods like the ones we describe in this article to create improved estimates for policy research.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50202 - Applied Economics, Econometrics
Result continuities
Project
<a href="/en/project/GJ16-07603Y" target="_blank" >GJ16-07603Y: The Causes and Consequences of Survey Misreporting: Evidence From Linked Administrative Data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Survey Statistics and Methodology
ISSN
2325-0984
e-ISSN
2325-0992
Volume of the periodical
7
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
24
Pages from-to
440-463
UT code for WoS article
000493303500006
EID of the result in the Scopus database
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