Multidimensional Poverty Dominance: Statistical Inference and an Application to West Africa

Abstract

This paper tests for robust multidimensional poverty comparisons across six countries of the West African Economic and Monetary Union (WAEMU). Two dimensions are considered, nutritional status and assets. The estimation of the asset index is based on two factorial analysis methods. The first method uses Multiple Correspondence Analysis; the second is based on the maximization of a likelihood function and on bayesian analysis. Using Demographic and Health Surveys (DHS), pivotal bootstrap tests lead to statistically significant dominance relationships between 12 of the 15 possible pairs of the six WAEMU countries. Multidimensional poverty is also inferred to be more prevalent in rural than in urban areas. These results tend to support those derived from more restrictive unidimensional dominance tests.Stochastic dominance, factorial analysis, bayesian analysis, multidimensional poverty, empirical likelihood function, bootstrap tests