Measures of “Race” and the analysis of racial inequality in Brazil

Quantitative analyses of racial disparities typically rely on a single categorical measure to operationalize race. We demonstrate the value of an approach that compares results obtained using various measures of race. Using a national probability sample of the Brazilian population that captured race in six formats, we first show how the racial composition of Brazil can shift from majority white to majority black depending on the classification scheme. In addition, using quantile regression, we find that racial disparities are most severe at the upper end of the income distribution; that racial disparities in earnings are larger when race is defined by interviewers rather than self-identified; and that those classified as “black” suffer a greater wage penalty than those classified as “brown.” Our findings extend prior conclusions about racial inequality in Brazil. More generally, our analysis demonstrates that comparison of results across measures represents a neglected source of analytic leverage for advancing empirical knowledge and theoretical understanding of how race, as a multidimensional social construct, contributes to the production of social inequality.

► We explore income disparities in Brazil across six racial measurement schemes. ► Estimates of inequality are sensitive to researchers’ choice of race measure. ► Across-measure disparities are greatest at upper ends of the income distribution. ► Disparities are larger when race defined by interviewers rather than self-defined. ► Comparison across race measures can improve understandings of inequality.