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Evaluating the Utility of Linked Administrative Data for Nonresponse Bias Adjustment in a Piggyback Longitudinal Survey

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  • Büttner Tobias J.M.

    (Federal Employment Agency/Institute for Employment Research, 104 Regensburger Straße, Nuremberg 90478, Germany.)

  • Sakshaug Joseph W.

    (Federal Employment Agency/Institute for Employment Research, 104 Regensburger Straße, Nuremberg 90478, Germany.)

  • Vicari Basha

    (Federal Employment Agency/Institute for Employment Research, 104 Regensburger Straße, Nuremberg 90478, Germany.)

Abstract

Nearly all panel surveys suffer from unit nonresponse and the risk of nonresponse bias. Just as the analytic value of panel surveys increase with their length, so does cumulative attrition, which can adversely affect the representativeness of the resulting survey estimates. Auxiliary data can be useful for monitoring and adjusting for attrition bias, but traditional auxiliary sources have known limitations. We investigate the utility of linked-administrative data to adjust for attrition bias in a standard piggyback longitudinal design, where respondents from a preceding general population cross-sectional survey, which included a data linkage request, were recruited for a subsequent longitudinal survey. Using the linked-administrative data from the preceding survey, we estimate attrition biases for the first eight study waves of the longitudinal survey and investigate whether an augmented weighting scheme that incorporates the linked-administrative data reduces attrition biases. We find that adding the administrative information to the weighting scheme generally leads to a modest reduction in attrition bias compared to a standard weighting procedure and, in some cases, reduces variation in the point estimates. We conclude with a discussion of these results and remark on the practical implications of incorporating linked-administrative data in piggyback longitudinal designs.

Suggested Citation

  • Büttner Tobias J.M. & Sakshaug Joseph W. & Vicari Basha, 2021. "Evaluating the Utility of Linked Administrative Data for Nonresponse Bias Adjustment in a Piggyback Longitudinal Survey," Journal of Official Statistics, Sciendo, vol. 37(4), pages 837-864, December.
  • Handle: RePEc:vrs:offsta:v:37:y:2021:i:4:p:837-864:n:7
    DOI: 10.2478/jos-2021-0037
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    References listed on IDEAS

    as
    1. Bruce D. Meyer & Nikolas Mittag, 2019. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness, and Holes in the Safety Net," American Economic Journal: Applied Economics, American Economic Association, vol. 11(2), pages 176-204, April.
    2. Manfred Antoni & Stefan Seth, 2012. "ALWA-ADIAB – Linked Individual Survey and Administrative Data for Substantive and Methodological Research," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 132(1), pages 141-146.
    3. Martin Kroh, 2010. "Documentation of Sample Sizes and Panel Attrition in the German Socio Economic Panel (SOEP) (1984 until 2009)," Data Documentation 50, DIW Berlin, German Institute for Economic Research.
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    5. Martin Kroh, 2009. "Documentation of Sample Sizes and Panel Attrition in the German Socio Economic Panel (SOEP) (1984 until 2008)," Data Documentation 47, DIW Berlin, German Institute for Economic Research.
    6. John Karl Scholz & Ananth Seshadri & Surachai Khitatrakun, 2006. "Are Americans Saving "Optimally" for Retirement?," Journal of Political Economy, University of Chicago Press, vol. 114(4), pages 607-643, August.
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