Testing for stochastic dominance among additive, multivariate welfare functions with discrete variable

This paper shows how to expand already existing conditions of stochastic dominance for additive welfare functions and proposes a test for multiple discrete variables based on Anderson's (1996) nonparametric test.

A flourishing literature on robustness in multidimensional welfare and poverty comparisons has aroused the interest on multidimensional stochastic dominance. By generalizing the dominance conditions of Atkinson and Bourguignon (1982) this paper offers complete conditions, alternative to those proposed by Duclos et al. (2006a,b). We also show how to test these conditions for discrete variables extending the non-parametric test by Anderson (1996) to multiple dimensions. An empirical application illustrates these tests.

Author: Gaston Yalonetzky

Year: 2009

Citation: Yalonetzky, G. (2009). 'Testing for stochastic dominance among additive, multivariate
welfare functions with discrete variables', OPHI Research in Progress 9a, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford.