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Empirical Likelihood-Based Inference for Poverty Measures with Relative Poverty Lines

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  • Brennan S. Thompson

Abstract

In this article, we propose an empirical likelihood-based method of inference for decomposable poverty measures utilizing poverty lines which are some fraction of the median of the underlying income distribution. Specifically, we focus on making poverty comparisons between two subgroups of the population which share the same poverty line. Our proposed method is assessed using a Monte Carlo simulation and is applied to some Canadian household income data.

Suggested Citation

  • Brennan S. Thompson, 2013. "Empirical Likelihood-Based Inference for Poverty Measures with Relative Poverty Lines," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 513-523, December.
  • Handle: RePEc:taf:emetrv:v:32:y:2013:i:4:p:513-523
    DOI: 10.1080/07474938.2012.690671
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    Cited by:

    1. Mehdi, Tahsin & Stengos, Thanasis, 2014. "Empirical likelihood-based inference for the generalized entropy class of inequality measures," Economics Letters, Elsevier, vol. 123(1), pages 54-57.

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