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Adjusting imperfect data: overview and case studies

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  • Lars Vilhuber

Abstract

Research users of large administrative have to adjust their data for quirks, problems, and issues that are inevitable when working with these kinds of datasets. Not all solutions to these problems are identical, and how they differ may affect how the data is to be interpreted. Some elements of the data, such as the unit of observation, remain fundamentally different, and it is important to keep that in mind when comparing data across countries. In this paper (written for Lazear and Shaw, 2007), we focus on the differences in the underlying data for a selection of country datasets. We describe two data elements that remain fundamentally different across countries -- the sampling or data collection methodology, and the basic unit of analysis (establishment or firm) -- and the extent to which they differ. We then proceed to document some of the problems that affect longitudinally linked administrative data in general, and we describe some of the solutions analysts and statistical agencies have implemented, and explore, through a select set of case studies, how each adjustment or absence thereof might affect the data.
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Suggested Citation

  • Lars Vilhuber, 2004. "Adjusting imperfect data: overview and case studies," Longitudinal Employer-Household Dynamics Technical Papers 2004-05, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:tpaper:2004-05
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    Cited by:

    1. Hijzen, Alexander & Martins, Pedro S. & Schank, Thorsten & Upward, Richard, 2013. "Foreign-owned firms around the world: A comparative analysis of wages and employment at the micro-level," European Economic Review, Elsevier, vol. 60(C), pages 170-188.
    2. Chiara Criscuolo & Alexander Hijzen & Cyrille Schwellnus & Erling Barth & Wen-Hao Chen & Richard Fabling & Priscilla Fialho & Balazs Stadler & Richard Upward & Wouter Zwysen & Katarzyna Grabska-Romago, 2020. "Workforce composition, productivity and pay: the role of firms in wage inequality," OECD Economics Department Working Papers 1603, OECD Publishing.
    3. Criscuolo, Chiara & Gal, Peter N. & Menon, Carlo, 2014. "The dynamics of employment growth: new evidence from 18 countries," LSE Research Online Documents on Economics 60286, London School of Economics and Political Science, LSE Library.
    4. John M. Abowd & Kevin L. McKinney & Lars Vilhuber, 2009. "The Link between Human Capital, Mass Layoffs, and Firm Deaths," NBER Chapters, in: Producer Dynamics: New Evidence from Micro Data, pages 447-472, National Bureau of Economic Research, Inc.
    5. Tanja Hethey-Maier & Johannes F. Schmieder, 2013. "Does the Use of Worker Flows Improve the Analysis of Establishment Turnover? Evidence from German Administrative Data," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 133(4), pages 477-510.
    6. Hethey, Tanja & Schmieder, Johannes F., 2010. "Using worker flows in the analysis of establishment turnover : evidence from German administrative data," FDZ Methodenreport 201006_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    7. repec:iab:iabfme:201006(en is not listed on IDEAS

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    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • J0 - Labor and Demographic Economics - - General

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