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Using Administrative Data to Evaluate Sampling Bias in a Business Panel Survey

Author

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  • D’Aurizio Leandro

    (Italian Authority for the Supervision of the Insurance Sector (IVASS), Research and Data Management Directorate, via del Quirinale 21, 00187Rome, Italy.)

  • Papadia Giuseppina

    (Bank of Italy, Economics and Statistics Department, via Nazionale 91, 00181Rome, Italy.)

Abstract

We examine two sources of bias for the Bank of Italy’s panel business survey of Industrial and Services Firms:1) the bias caused by panel attrition; and2) the bias created by delays in the distributional data on the reference population, needed for computing the survey weights.As for the first source of bias, the estimates strongly dependent on big firms’ values are less affected by panel attrition than those representing firms’ average behavior, independent of their sizes. Positive economic results make it easier to enroll new firms in the survey, in order to replace firms dropping out because of bad economic performances. However, the economic results of new entrances become more aligned to those of the population, once they enter the sample.A very different result emerges for the second source of bias, since, when the population size is highly variable, the information delays produce a bias for the estimates influenced by the contribution of great firms, but the effect is negligible for the estimates not dependent on firm size.

Suggested Citation

  • D’Aurizio Leandro & Papadia Giuseppina, 2019. "Using Administrative Data to Evaluate Sampling Bias in a Business Panel Survey," Journal of Official Statistics, Sciendo, vol. 35(1), pages 67-92, March.
    • Handle: RePEc:vrs:offsta:v:35:y:2019:i:1:p:67-92:n:4
    DOI: 10.2478/jos-2019-0004
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    References listed on IDEAS

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    1. Gary Solon & Steven J. Haider & Jeffrey M. Wooldridge, 2015. "What Are We Weighting For?," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 301-316.
    2. Ugo Trivellato, 1999. "Issues in the Design and Analysis of Panel Studies: A Cursory Review," Quality & Quantity: International Journal of Methodology, Springer, vol. 33(3), pages 339-351, August.
    3. Ivan Faiella, 2010. "The use of survey weights in regression analysis," Temi di discussione (Economic working papers) 739, Bank of Italy, Economic Research and International Relations Area.
    4. Knapp, Morris & Gart, Alan & Chaudhry, Mukesh, 2006. "The impact of mean reversion of bank profitability on post-merger performance in the banking industry," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3503-3517, December.
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    Cited by:

    1. Francesco D'Amuri & Salvatore Lattanzio & Benjamin S. Smith, 2023. "The anatomy of labor cost adjustment to demand shocks: Germany and Italy during the Great Recession," Temi di discussione (Economic working papers) 1411, Bank of Italy, Economic Research and International Relations Area.

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