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Unpacking the Contribution of Birth Circumstances to Inequality Using a Shapley Decomposition: The Case of Chile

2026/03/20 by Carlos Gradín, Gabriela Zapata‐Román
Economics, Econometrics and Finance · Mathematics · Social Sciences · #Advanced Causal Inference Techniques #Economic and Technological Innovation #Economic inequality #Function (biology) #Generalized entropy index #Income inequality metrics #Income, Poverty, and Inequality #Index (typography) #Inequality #Population #Unpacking

paper · doi:10.1111/roiw.70064

published in Review of Income and Wealth 72(2) (Wiley)

openalex publication_date 2026/03/20 · openalex created_date 2026/03/22 · openalex updated_date 2026/08/02

Abstract

ABSTRACT This study examines the role of inherited circumstances in labor market inequality of opportunity in Chile. We estimate their contribution as the change in total inequality after removing their influence. Since this contribution may differ depending on whether it is measured before or after removing the influence of other factors, we use the Shapley decomposition method. Traditional path‐dependent decompositions misrepresent the role of circumstances by ignoring their interaction with inter‐ and intra‐group inequality—overstating (Gini) or understating (entropy‐based measures). Circumstances explained 27%–28% of inequality in 2022 using entropy measures, and 17% when emphasizing outcomes for the poorest. In contrast, the Gini index attributes 36% of inequality to circumstances. Despite some fluctuations, inequality of opportunity has remained persistent and a key driver of overall inequality since the financial crisis. We also apply a Recentered Influence Function decomposition to examine the specific contributions of different population groups.

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