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Evidence from the Dead: New Estimates of Wealth Inequality based on the Distribution of Estates

Author

Listed:
  • Facundo Alvaredo

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, WIL - World Inequality Lab)

  • Yonatan Berman

    (King‘s College London, LSE - London School of Economics and Political Science, IZA - Forschungsinstitut zur Zukunft der Arbeit - Institute of Labor Economics)

  • Salvatore Morelli

    (ROMA TRE - Università degli Studi Roma Tre = Roma Tre University, Stone Center on Socio-Economic Inequality, CUNY - City University of New York [New York])

Abstract

This paper examines the estimation of the distribution of wealth using estates left at death. We establish formal conditions for implementing a simplified version of the classic estate multiplier method, relying solely on minimal information about estates and mortality. These conditions are empirically validated, and the simplified approach is applied to produce new long-run top wealth share series for Belgium, Japan, and South Africa, where estate data have previously been underutilized. This method holds potential for expanding the range of countries and years in which wealth concentration can be estimated, especially where estate data exist but the standard method with heterogeneous multipliers is inapplicable.

Suggested Citation

  • Facundo Alvaredo & Yonatan Berman & Salvatore Morelli, 2025. "Evidence from the Dead: New Estimates of Wealth Inequality based on the Distribution of Estates," World Inequality Lab Working Papers halshs-04934624, HAL.
    • Handle: RePEc:hal:wilwps:halshs-04934624
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-04934624v1
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