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Looking for the missing rich: tracing the top tail of the wealth distribution

Author

Listed:
  • Stefan Bach

    (German Institute for Economic Research (DIW Berlin)
    University of Potsdam)

  • Andreas Thiemann

    (European Commission, Joint Research Centre (JRC))

  • Aline Zucco

    (German Institute for Economic Research (DIW Berlin))

Abstract

We analyse the top tail of the wealth distribution in France, Germany, and Spain using the first and second waves of the Household Finance and Consumption Survey (HFCS). Since top wealth is likely to be under-represented in household surveys, we integrate big fortunes from rich lists, estimate a Pareto distribution, and impute the missing rich. In addition to the Forbes list, we rely on national rich lists since they represent a broader base of the big fortunes in those countries. As a result, the top 1% wealth share increases notably for the three selected countries after imputing the top wealth. We find that national rich lists can improve the estimation of the Pareto coefficient in particular when the list of national USD billionaires is short.

Suggested Citation

  • Stefan Bach & Andreas Thiemann & Aline Zucco, 2019. "Looking for the missing rich: tracing the top tail of the wealth distribution," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(6), pages 1234-1258, December.
    • Handle: RePEc:kap:itaxpf:v:26:y:2019:i:6:d:10.1007_s10797-019-09578-1
    DOI: 10.1007/s10797-019-09578-1
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    More about this item

    Keywords

    Wealth distribution; Missing rich; Pareto distribution; HFCS;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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