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Testing for Bivariate Stochastic Dominance Using Inequality Restrictions

Author

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  • Thanasis Stengos

    () (Department of Economics, University of Guelph)

  • Brennan S. Thompson

    () (Department of Economics, Ryerson University, Toronto)

Abstract

In this paper, we propose of a test of bivariate stochastic dominance using a generalized framework for testing inequality constraints. Unlike existing tests, this test has the advantage of utilizing the covariance structure of the estimates of the joint distribution functions. The performance of our proposed test is examined by way of a Monte Carlo experiment. We also consider an empirical example which utilizes household survey data on income and health status.

Suggested Citation

  • Thanasis Stengos & Brennan S. Thompson, 2011. "Testing for Bivariate Stochastic Dominance Using Inequality Restrictions," Working Paper series 32_11, Rimini Centre for Economic Analysis.
    • Handle: RePEc:rim:rimwps:32_11
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    References listed on IDEAS

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    18. Gordon Anderson, 2008. "The empirical assessment of multidimensional welfare, inequality and poverty: Sample weighted multivariate generalizations of the Kolmogorov–Smirnov two sample tests for stochastic dominance," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(1), pages 73-87, March.
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    Cited by:

    1. Mohamed Khaled & Paul Makdissi & Myra Yazbeck, 2016. "Income-Related Health Transfers Principles and Orderings of Joint Distributions of Income and Health," Discussion Papers Series 574, School of Economics, University of Queensland, Australia.

    More about this item

    Keywords

    Stochastic dominance; inequality restrictions; multidimensional welfare;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty

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