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A nonparametric test of mth-degree inverse stochastic dominance

Author

Listed:
  • Jiang, Hongyi
  • Sun, Zhenting
  • Hu, Shiyun

Abstract

This paper proposes a nonparametric test for mth-degree inverse stochastic dominance which is a powerful tool for ranking distribution functions according to social welfare. We construct the test based on empirical process theory. The test is shown to be asymptotically size controlled and consistent. The good finite sample properties of the test are illustrated via Monte Carlo simulations. We apply our test to the inequality growth in the United Kingdom from 1995 to 2010, and obtain a more complete ranking of the income distributions.

Suggested Citation

  • Jiang, Hongyi & Sun, Zhenting & Hu, Shiyun, 2024. "A nonparametric test of mth-degree inverse stochastic dominance," Economics Letters, Elsevier, vol. 244(C).
    • Handle: RePEc:eee:ecolet:v:244:y:2024:i:c:s0165176524004622
    DOI: 10.1016/j.econlet.2024.111978
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    References listed on IDEAS

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    7. Rolf Aaberge & Tarjei Havnes & Magne Mogstad, 2021. "Ranking intersecting distribution functions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 639-662, September.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Inverse stochastic dominance; Social welfare; Nonparametric test; Ranking distribution functions;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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