Using multiple correspondence analysis for the multidimensional and intersectional analysis of ethnic categories

Multiple correspondence analysis is a multivariate method for exploring the structure of the association among a set of categorical variables by identifying underlying dimensions, while retaining as much variability as possible. The approach employed here is inspired by the study of class structures proposed by Pierre Bourdieu, in which researchers take a multidimensional approach to inductively map the distribution of several indicators measuring economic and social capital. Despite its popularity for Bourdieu-inspired analysis and being widely available in statistical packages, MCA, at least in sociology, is rarely used beyond the study of class structures and culture. This research note illustrates the use of MCA for the analysis of multiple indicators of ethnic and national characteristics. A similar strategy can be taken to study any other social divisions, such as gender, age and disability. The ideas presented here invite readers to consider MCA for the quantitative research of intersectional inequalities, beyond Bourdieu.<p></p>