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Joint hypothesis tests for multidimensional inequality indices

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  • Abul Naga, Ramses H.
  • Shen, Yajie
  • Yoo, Hong Il

Abstract

An inequality index over p dimensions of well-being is decomposable by attributes if it can expressed as a function of p unidimensional inequality indices and a measure of association between the various dimensions of well-being. We exploit this decomposition framework to derive joint hypothesis tests regarding the sources of multidimensional inequality, and present Monte Carlo evidence on their finite sample behavior.

Suggested Citation

  • Abul Naga, Ramses H. & Shen, Yajie & Yoo, Hong Il, 2016. "Joint hypothesis tests for multidimensional inequality indices," Economics Letters, Elsevier, vol. 141(C), pages 138-142.
    • Handle: RePEc:eee:ecolet:v:141:y:2016:i:c:p:138-142
    DOI: 10.1016/j.econlet.2016.02.010
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    1. Abul Naga, Ramses H. & Geoffard, Pierre-Yves, 2006. "Decomposition of bivariate inequality indices by attributes," Economics Letters, Elsevier, vol. 90(3), pages 362-367, March.
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    More about this item

    Keywords

    Multidimensional inequality indices; Large sample distributions; Joint hypothesis tests; Bootstrap;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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