Fuzzy chronic poverty: A proposed response to Measurement Error for Intertemporal Poverty Measurement

Catherine Porter, Gaston Yalonetzky

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Abstract

A number of chronic poverty measures are now empirically applied to quantify the prevalence and intensity of chronic poverty, vis-à-vis transient experiences, using panel data. Welfare trajectories over time are assessed in order to identify the chronically poor and distinguish them from the non-poor, or the transiently poor, and assess the extent and intensity of intertemporal poverty. We examine the implications of measurement error in the welfare outcome for some popular discontinuous chronic poverty measures, and propose corrections to these measures that seeks to minimize the consequences of measurement error. The approach is based on a novel criterion for the identification of chronic poverty that draws on fuzzy set theory. We illustrate the empirical relevance of the approach with a panel dataset from rural Ethiopia and some simulations.

Original languageEnglish
Pages (from-to)119-143
Number of pages25
JournalReview of Income and Wealth
Volume65
Issue number1
Early online date30 Aug 2017
DOIs
Publication statusPublished - Mar 2019

Keywords

  • fuzzy sets theory
  • intertemporal poverty
  • measurement error
  • poverty measurement

ASJC Scopus subject areas

  • Economics and Econometrics

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