Multidimensional measurement of poverty in Mexico: Statistical significance in the inclusion of non-monetary dimensions

Abstract

Identifying relevant variables for multidimensional poverty analysis depends on how different dimensions complement or substitute each other, given the existence of attributes highly correlated with household income. Dimensions weakly correlated with household income highlight the relevance of multidimensionality. By using the Mexican Family Life Survey, this article incorporates dimensions weakly correlated with income to show, firstly, the probability of falling into poverty given three sets of indicators; and secondly, the magnitude of the exclusion error when a monetary measure, against the aforesaid probability, is adopted. The article finds a large exclusion error, especially in the case of moderate poverty.