Improving the Power of Tests of Stochastic Dominance

Stephen G. Donald () and Yu-Chin Hsu
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Stephen G. Donald: Department of Economics, University of Texas at Austin

No 12-A015, IEAS Working Paper : academic research from Institute of Economics, Academia Sinica, Taipei, Taiwan

Abstract: We extend Hansen’s (2005) recentering method to a continuum of inequality constraints to construct new Kolmogorov-Smirnov tests for stochastic dominance of any pre-specified order. We show that our tests have correct size asymptotically, are consistent against fixed alternatives and are unbiased against some N−1/2 local alternatives. It is shown that by avoiding the use of the least favorable configuration, our tests are less conservative and more powerful than Barrett and Donald’s (2003) and in some simulation examples we consider, we find that our test can be more powerful than the subsampling test of Linton, Maasoumi and Whang (2005). We apply our method to test stochastic dominance relations between Canadian income distributions in 1978 and 1986 as considered in Barrett and Donald (2003) and find that some of the hypothesis test results are different using the new method.

Keywords: Stochastic dominance; test consistency; simulation; bootstrap; uniform inference (search for similar items in EconPapers)
JEL-codes: C01 C12 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2012-12, Revised 2013-06
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (10)

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Journal Article: Improving the Power of Tests of Stochastic Dominance (2016)
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