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Tests for the Second Order Stochastic Dominance Based on L -Statistics

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  • José R. Berrendero
  • Javier Cárcamo

Abstract

We use some characterizations of convex and concave-type orders to define discrepancy measures useful in two testing problems involving stochastic dominance assumptions. The results are connected with the mean value of the order statistics and have a clear economic interpretation in terms of the expected cumulative resources of the poorest (or richest) in random samples. Our approach mainly consists of comparing the estimated means in ordered samples of the involved populations. The test statistics we derive are functions of L -statistics and are generated through estimators of the mean order statistics. We illustrate some properties of the procedures with simulation studies and an empirical example.

Suggested Citation

  • José R. Berrendero & Javier Cárcamo, 2011. "Tests for the Second Order Stochastic Dominance Based on L -Statistics," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 260-270, April.
    • Handle: RePEc:taf:jnlbes:v:29:y:2011:i:2:p:260-270
    DOI: 10.1198/jbes.2010.07224
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    Cited by:

    1. David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2020. "Bayesian assessment of Lorenz and stochastic dominance," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 767-799, May.
    2. Amparo Ba'illo & Javier C'arcamo & Carlos Mora-Corral, 2024. "Tests for almost stochastic dominance," Papers 2403.15258, arXiv.org.
    3. Amparo Ba'illo & Javier C'arcamo & Carlos Mora-Corral, 2021. "Extremal points of Lorenz curves and applications to inequality analysis," Papers 2103.03286, arXiv.org.
    4. David Lander & David Gunawan & William E. Griffiths & Duangkamon Chotikapanich, 2016. "Bayesian Assessment of Lorenz and Stochastic Dominance Using a Mixture of Gamma Densities," Department of Economics - Working Papers Series 2023, The University of Melbourne.

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