On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty

MEHMET PINAR, THANASIS STENGOS, NIKOLAS TOPALOGLOU

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2 Citations (Scopus)

Abstract

There are infinitely many alternative benchmark weights that decision makers could choose to measure multidimensional poverty. To overcome the resulting uncertainty, we derive a feasible range of multidimensional poverty that considers all admissible weights within the chosen lower and upper bounds of weights. We use Kenyan and Canadian data to illustrate the use of our methodology, which is an adaptation of existing methods for portfolio analysis based on stochastic dominance. These two-empirical analyses suggest that different weights allocated to poverty dimensions can produce very different multidimensional poverty outcomes for a given population even in cases with small weight perturbations.
Original languageEnglish
Pages (from-to)415-427
Number of pages13
JournalEuropean Journal of Operational Research
Volume281
Issue number2
Early online date2 Sep 2019
DOIs
Publication statusPublished - 1 Mar 2020

Keywords

  • Multidimensional poverty measurement
  • Stochastic dominance
  • OR in societal problem analysis
  • Mixed integer programming

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