Incorporating covariates in the measurement of welfare and inequality: methods and applications

Abstract

Summary Methods for comparing social welfare and inequality across populations typically involve the entire distribution of economic wellbeing. Conditional analysis requires an estimate of the entire distribution conditional on a large set of covariates. In this paper, we present methods for estimating conditional distributions including flexible parametric, semiparametric and non-parametric approaches. We demonstrate how to use the statistical properties of the estimators to conduct inference for welfare and inequality comparisons conditional on covariates. Further, we consider how to use the results to perform counterfactual analysis.