Incorporating Covariates in the Measurement of Welfare and Inequality: Methods and Applications
Stephen G. Donald
University of Texas at Austin - Department of Economics
affiliation not provided to SSRN
Garry F. Barrett
University of Sydney
The Econometrics Journal, Vol. 15, Issue 1, pp. C1-C30, 2012
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.
Number of Pages in PDF File: 30
Keywords: Semiparametric models, Statistical inference, Stochastic dominance, Welfare and inequalityAccepted Paper Series
Date posted: February 17, 2012
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