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The Review of Economics and Statistics 2026

Intergenerational Mobility in the Land of Inequality

Diogo G. C. Britto1; Alexandre Fonseca2; Paolo Pinotti3; Breno Sampaio4; Lucas Warwar5

1 Bocconi University, CLEAN Unit for the Economic Analysis of Crime, Prospera Lab, CEPR, IZA, INSPIRE, IGIER [email protected] · 2 Prospera Lab, CLEAN Unit for the Economic Analysis of Crime, Federal Revenue of Brazil [email protected] · 3 Bocconi University, CEPR, CESifo, CReAM, and BAFFI-CAREFIN Center, INSPIRE, CLEAN Unit for the Economic Analysis of Crime [email protected] · 4 Universidade Federal de Pernambuco, Prospera Lab, CLEAN Unit for the Economic Analysis of Crime, IZA [email protected] · 5 Stanford University [email protected]

open access

Abstract

We provide the first estimates of intergenerational income mobility using tax data for a large developing country, namely Brazil. We measure formal income from tax and payroll data, and we train machine learning models on census and survey data to predict informal income. We quantify the estimation bias resulting from income imputation and other sources of measurement error, and show that such bias remains negligible in our context. A 10 percentile increase in parental income rank is associated on average with a 5.5 percentile increase in child income rank, with considerable variation across sociodemographic groups and geographical areas.

DOI
10.1162/rest.a.1775
Pages
1-45
Language
en
Sources
openalex crossref

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