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A new instrument to measure wealth inequality: distributional wealth accounts

Author

Listed:
  • Arthur B. Kennickell

    (City University of New York)

  • Peter Lindner

    (Economic Analysis Division)

  • Martin Schürz

    (Oesterreichische Nationalbank, Economic Analysis Division)

Abstract

In this study we investigate the sensitivity of different wealth measurement approaches. In this context, we analyze the alignment of Household Finance and Consumption Survey (HFCS) data with national accounts data and examine the production of distributional wealth accounts, which poses severe conceptual challenges. For a number of reasons, household surveys underestimate top wealth shares. We show that different assumptions generate a wide range of results for different wealth inequality indicators. In particular, the share of the top 1% of households in net wealth ranges from about 25% to about 50%, depending on the underlying assumption. Thus, while the true value of the wealth share held by the top 1% is unknown, all available information indicates that it is closer to 50% than to HFCS results. We call for caution in interpreting top shares as the underlying assumptions are mostly ad hoc choices made by data producers. Our study argues that we need better microdata on the top end of the net wealth distribution.

Suggested Citation

  • Arthur B. Kennickell & Peter Lindner & Martin Schürz, 2022. "A new instrument to measure wealth inequality: distributional wealth accounts," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/21.
    • Handle: RePEc:onb:oenbmp:y:2022:i:q4/21:b:3
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    References listed on IDEAS

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    Cited by:

    1. Engel, Janina & Ohlwerter, Dennis & Scherer, Matthias, 2023. "On the estimation of distributional household wealth: addressing under-reporting via optimization problems with invariant Gini coefficient," Working Paper Series 2865, European Central Bank.
    2. Michele Bavaro & Piotr Paradowski, 2025. "Missing Wealth Distribution, Wealth Inequality and Anti-inequality Policies," LWS Working papers 50, LIS Cross-National Data Center in Luxembourg.

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    Keywords

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    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • D30 - Microeconomics - - Distribution - - - General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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