Creating improved survey data products using linked administrative-survey data

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Creating improved survey data products using linked administrative-survey data

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Creating improved survey data products using linked administrative-survey data

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

<a href="/cs/project/GJ16-07603Y" target="_blank" >GJ16-07603Y: Příčiny a důsledky nesprávného vykazování ve výběrových šetřeních: Evidence z propojených administrativních dat</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Survey Statistics and Methodology

ISSN

2325-0984

e-ISSN

2325-0992

Svazek periodika

7

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

24

Strana od-do

440-463

Kód UT WoS článku

000493303500006

EID výsledku v databázi Scopus

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