This paper extends the Oaxaca-Blinder decomposition method to the quantile
regression random-coefficients framework. Mean-based decompositions are obtained as the
integration of the quantile regression decomposition process. This method allows identifying
if the observed differences between two groups differ across quantiles, and if so, what is
the contribution to the mean-based Oaxaca-Blinder decomposition. The proposed methodology
is applied to the analysis of caste discrimination in Nepal. The results indicate that
much of the discrimination occurs at the lowest quantiles, which implies that disadvantaged
groups are the ones who suffer the most caste discrimination

• Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination