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Inheritances and wealth inequality: a machine learning approach

Pedro Salas Rojo and Juan Rodríguez

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: This paper explores the relationship between received inheritances and the distribution of wealth (financial, non-financial and total) in four developed countries: the United States, Canada, Italy and Spain. We follow the inequality of opportunity (IOp) literature and − considering inheritances as the only circumstance− we show that traditional IOp approaches can lead to non-robust and arbitrary measures of IOp depending on discretionary cut-off choices of a continuous circumstance such as inheritances. To overcome this limitation, we apply Machine Learning methods (‘random forest’ algorithm) to optimize the choice of cut-offs and we find that IOp explains over 60% of wealth inequality in the US and Spain (using the Gini coefficient), and more than 40% in Italy and Canada. Including parental education as an additional circumstance −available for the US and Italy− we find that inheritances are still the main contributor. Finally, using the S-Gini index with different parameters to weight different parts of the distribution, we find that the effect of inheritances is more prominent at the middle of the wealth distribution, while parental education is more important for the asset-poor.

Keywords: inequality of opportunity; inheritances; machine learning; parental education; wealth inequality (search for similar items in EconPapers)
JEL-codes: C60 D31 D63 G00 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2022-03-10
New Economics Papers: this item is included in nep-big, nep-cmp and nep-eur
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in Journal of Economic Inequality, 10, March, 2022, 20(1), pp. 27-51. ISSN: 1569-1721

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http://eprints.lse.ac.uk/120916/ Open access version. (application/pdf)

Related works:
Journal Article: Inheritances and wealth inequality: a machine learning approach (2022) Downloads
Working Paper: Inheritances and Wealth Inequality: a Machine Learning Approach (2020) Downloads
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