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The challenges of linking survey and administrative data

Author

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  • Steffen Künn

    (Maastricht University, Netherlands, and IZA, Germany)

Abstract

Using administrative records data and survey data to enhance each other offers huge potential for scientific and policy-related research. Two recent changes have expanded the potential for creating such linked data: the improved availability of data sources and progress in data-matching technology. These developments are reflected, among other ways, in the growing number of academic papers in labor economics that use linked survey and administrative data. While the number of studies using linked data is still small, the trend is clearly upward. Slowing the growth, however, are concerns about data security and privacy, which impede data access.

Suggested Citation

  • Steffen Künn, 2015. "The challenges of linking survey and administrative data," IZA World of Labor, Institute of Labor Economics (IZA), pages 214-214, December.
  • Handle: RePEc:iza:izawol:journl:y:2015:n:214
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    References listed on IDEAS

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    1. Lex Borghans & Angela Lee Duckworth & James J. Heckman & Bas ter Weel, 2008. "The Economics and Psychology of Personality Traits," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    2. Caliendo, Marco & Mahlstedt, Robert & Mitnik, Oscar A., 2017. "Unobservable, but unimportant? The relevance of usually unobserved variables for the evaluation of labor market policies," Labour Economics, Elsevier, vol. 46(C), pages 14-25.
    3. Joseph W. Sakshaug & Mick P. Couper & Mary Beth Ofstedal & David R. Weir, 2012. "Linking Survey and Administrative Records," Sociological Methods & Research, , vol. 41(4), pages 535-569, November.
    4. Patrick Arni & Marco Caliendo & Steffen Künn & Klaus Zimmermann, 2014. "The IZA evaluation dataset survey: a scientific use file," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 3(1), pages 1-20, December.
    5. Caliendo, Marco & Mahlstedt, Robert & Mitnik, Oscar, 2014. "Unobservable, but Unimportant? The Influence of Personality Traits (and Other Usually Unobserved Variables) for the Estimation of Treatment Effects," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100502, Verein für Socialpolitik / German Economic Association.
    6. Marco Caliendo & Robert Mahlstedt & Oscar A. Mitnik, 2014. "Unobservable, but Unimportant?: The Influence of Personality Traits (and Other Usually Unobserved Variables) for the Evaluation of Labor Market Policies," Discussion Papers of DIW Berlin 1407, DIW Berlin, German Institute for Economic Research.
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    Cited by:

    1. Warnke, Arne Jonas, 2017. "An investigation of record linkage refusal and its implications for empirical research," ZEW Discussion Papers 17-031, ZEW - Leibniz Centre for European Economic Research.
    2. Broszeit, Sandra & Laible, Marie-Christine, 2017. "The German Management and Organizational Practices (GMOP) Survey : Survey design and data quality," FDZ Methodenreport 201702_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    3. repec:iab:iabfme:201702(en is not listed on IDEAS
    4. Cuccaro-Alamin, Stephanie & Eastman, Andrea Lane & Foust, Regan & McCroskey, Jacquelyn & Nghiem, Huy Tran & Putnam-Hornstein, Emily, 2021. "Strategies for constructing household and family units with linked administrative records," Children and Youth Services Review, Elsevier, vol. 120(C).
    5. Lüthen Holger & Schröder Carsten & Grabka Markus M. & Goebel Jan & Mika Tatjana & Brüggmann Daniel & Ellert Sebastian & Penz Hannah, 2022. "SOEP-RV: Linking German Socio-Economic Panel Data to Pension Records," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 242(2), pages 291-307, April.

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    More about this item

    Keywords

    record linkage; administrative records; survey data;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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