An improved bootstrap test of stochastic dominance

Oliver Linton, Kyungchul Song and Yoon-Jae Whang

Journal of Econometrics, 2010, vol. 154, issue 2, 186-202

Abstract: We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that the variables are allowed to be residuals from nonparametric and semiparametric models. The proposed bootstrap tests have asymptotic sizes that are less than or equal to the nominal level uniformly over probabilities in the null hypothesis under regularity conditions. This paper also characterizes the set of probabilities so that the asymptotic size is exactly equal to the nominal level uniformly. As our simulation results show, these characteristics of our tests lead to an improved power property in general. The improvement stems from the design of the bootstrap test whose limiting behavior mimics the discontinuity of the original test's limiting distribution.

Keywords: Stochastic; dominance; Inequality; restrictions; Bootstrap; Set; estimation (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (122)

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Related works:
Working Paper: An improved bootstrap test of stochastic dominance (2009)
Working Paper: An Improved Bootstrap Test of Stochastic Dominance (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:154:y:2010:i:2:p:186-202

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