The Inequality (or the Growth) we Measure: Data Gaps and the Distribution of Incomes

Facundo Alvaredo (), Mauricio de Rosa, Ignacio Flores and Marc Morgan
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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, INET - Institut National des Etudes Territoriales
Mauricio de Rosa: 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, UDELAR - Universidad de la República [Montevideo]
Marc Morgan: 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, UNIGE - Université de Genève = University of Geneva

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Abstract: There is a large gap between income estimates used in inequality studies and macroeconomic statistics. This makes it hard to assess how economic growth is distributed across the population, and to what extent mainstream distributional statistics are an accurate representation of income flows. We take stock of these discrepancies by confronting estimates of the income distribution from surveys, administrative records and aggregates from the system of national accounts, thoroughly documenting them over the past two decades for ten Latin American countries. We find that surveys only account for around half of the macroeconomic income in the region. Measurement gaps account for just over half of the overall gap on average, while the rest is due to conceptual differences across data sets. Measurement gaps have been growing fast for many countries, the bulk being due to non-covered capital income. We also compare the top tails in administrative data and surveys, finding diverging averages-especially for non-wage incomes-and different shapes. We discuss the degree to which inequality levels and trends could be affected.

Keywords: Surveys; national accounts; administrative data; data gaps; income distribution; Latin America (search for similar items in EconPapers)
Date: 2022-06-10
New Economics Papers: this item is included in nep-lam
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Related works:
Working Paper: The Inequality (or the Growth) we Measure: Data Gaps and the Distribution of Incomes (2022)
Working Paper: The Inequality (or the Growth) we Measure: Data Gaps and the Distribution of Incomes (2022)
Working Paper: The Inequality (or the Growth) We Measure: Data Gaps and the Distribution of Incomes (2022)
Working Paper: The Inequality (or the Growth) We Measure: Data Gaps and the Distribution of Incomes (2022)
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