Ordinal Welfare Comparisons with Multiple Discrete Indicators: A First Order Dominance Approach and Application to Child Poverty
We develop an approach for making welfare comparisons between populations with multidimensional discrete well-being indicators observed at the micro level. The approach is rooted in the concept of multidimensional first order dominance. It assumes that, for each indicator, the levels can be ranked ordinally from worse to better; however, no assumptions are made about relative importance of any dimension nor about complementarity/substitutability relationships between dimensions. We also introduce an efficient algorithm for determining dominance and employ a bootstrap approach that permits cardinal rankings of populations. These approaches are applied to household survey data from Vietnam and Mozambique.
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