The concentration of income at the top in Brazil, 2006-2014

Produced by: 
United Nations Department of Economic and Social Affairs (UN/DESA)
Available from: 
November 2017
Paper author(s): 
Pedro Herculano Guimarães Ferreira de Souza
Marcelo Medeiros
Poverty - Inequality - Aid Effectiveness

Extreme inequality in Brazil is self-evident. The historian José Murilo de Carvalho emblematically chose to end his book on the history of citizenship in Brazil with the severe diagnosis that “inequality is the slavery of today, the new cancer that hinders the constitution of a democratic society” (Carvalho 2001, 229). Normative prescriptions aside, not even historical opponents of redistributive policies, such as Mário Henrique Simonsen, failed to recognise—even if reluctantly—income inequality as “undesirably high”, and as a source of “pained conscience” (Simonsen 1972, 57; 59). It is not a coincidence that empirical research on this theme in Brazil has had a rich tradition, since at least the famous 1970s controversy regarding the increase in inequality during the first years of the military dictatorship (Tolipan and Tinelly 1975). More recently, due to the greater availability of information, it has become possible to enrich this literature with data from personal income taxes (Imposto de renda de Pessoas Físicas—IRPF) which grant a new perspective of the top of the income distribution (Afonso 2014; Castro 2014; Gobetti and Orair 2016; Medeiros, Galvão, and Nazareno 2015; Medeiros, Souza, and Castro 2015a; 2015b; Morgan 2015; Souza 2014; 2016; Souza and Medeiros 2015). The purpose of this paper is to summarise and update the analyses by Medeiros, Souza and Castro (2015a; 2015b) and Souza and Medeiros (2015) of the concentration of income at the top and of the distribution of income in general. To that end, we assess the level and trajectory of top income shares—from the 0.1 per cent to the 10 per cent at the top—between 2006 and 2014, and contrast the results against those from the National Household Sample Survey (Pesquisa Nacional por Amostra de Domicílios—PNAD) and from the international literature. We then construct income distributions that merge data from the PNAD and the IRPF and compare the level and evolution of the ‘adjusted’ Gini indexes with the original ones, as well as changes in the respective Lorenz curves.



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