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Statistical Matching of Administrative and Survey Data

Author

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  • Anika Rasner
  • Joachim R. Frick
  • Markus M. Grabka

Abstract

Using population representative survey data from the German Socio-Economic Panel (SOEP) and administrative pension records from the Statutory Pension Insurance, the authors compare four statistical matching techniques to complement survey information on net worth with social security wealth (SSW) information from the administrative records. The unique properties of the linked data allow for a straight control of the quality of matches under each technique. Based on various evaluation criteria, Mahalanobis distance matching performs best. Exploiting the advantages of the newly assembled data, the authors include SSW in a wealth inequality analysis. Despite its quantitative relevance, SSW is thus far omitted from such analyses because adequate micro data are lacking. The inclusion of SSW doubles the level of net worth and decreases inequality by almost 25 percent. Moreover, the results reveal striking differences along occupational lines.

Suggested Citation

  • Anika Rasner & Joachim R. Frick & Markus M. Grabka, 2013. "Statistical Matching of Administrative and Survey Data," Sociological Methods & Research, , vol. 42(2), pages 192-224, May.
    • Handle: RePEc:sae:somere:v:42:y:2013:i:2:p:192-224
    DOI: 10.1177/0049124113486622
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    References listed on IDEAS

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    Cited by:

    1. Johannes Geyer & Salmai Qari & Hermann Buslei & Peter Haan, 2021. "DySiMo Dokumentation: Version 1.0," Data Documentation 101, DIW Berlin, German Institute for Economic Research.
    2. Markus Knell & Reinhard Koman, 2022. "Pension Entitlements and Net Wealth in Austria (Markus Knell, Reinhard Koman)," Working Papers 238, Oesterreichische Nationalbank (Austrian Central Bank).
    3. 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.
    4. Beatriz Larraz, 2015. "Decomposing the Gini Inequality Index," Sociological Methods & Research, , vol. 44(3), pages 508-533, August.

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