Distribution-sensitive multidimensional poverty measures with an application to India
Gaurav Datt ()
No 06-17, Monash Economics Working Papers from Monash University, Department of Economics
This paper presents axiomatic arguments to make the case for distribution-sensitive multidimensional poverty measures. The commonly-used counting measures violate the strong transfer axiom which requires regressive transfers to be unambiguously poverty-increasing and they are also invariant to changes in the distribution of a given set of deprivations amongst the poor. The paper provides axiomatic justification for distribution-sensitive multidimensional poverty measures by appealing to the strong transfer axiom as well as an additional cross-dimensional convexity axiom. Given the nonlinear structure of these measures, the paper also shows how the problem of an exact dimensional decomposition can be solved using Shapley decomposition methods to assess dimensional contributions to the poverty measures. An empirical illustration for India highlights distinctive features of the distribution-sensitive measures.
Keywords: multidimensional poverty; poverty measurement; transfer axiom; cross-dimensional convexity; Shapley decomposition; India (search for similar items in EconPapers)
JEL-codes: I3 I32 D63 O1 (search for similar items in EconPapers)
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