English, Article, Journal or magazine article edition: An Improved Bootstrap Test of Stochastic Dominance Oliver Linton; Kyungchul Song; Yoon-Jae Whang

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Bookmark: http://trove.nla.gov.au/version/91921
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • An Improved Bootstrap Test of Stochastic Dominance
Author
  • Oliver Linton
  • Kyungchul Song
  • Yoon-Jae Whang
Physical Description
  • preprint
Notes
  • 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 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.
  • Set estimation, Size of test, Similarity; Bootstrap, Subsampling
  • RePEc:cwl:cwldpp:1713
Language
  • English
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