Bootstrap Tests of Stochastic Dominance with Asymptotic Similarity on the Boundary

44 Pages Posted: 26 Feb 2008

See all articles by Oliver B. Linton

Oliver B. Linton

University of Cambridge

Kyungchul Song

University of British Columbia (UBC) - Department of Economics

Yoon-Jae Whang

Seoul National University - School of Economics

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Abstract

We propose a new method of testing stochastic dominance which improves on existing tests based on bootstrap or sub-sampling. Our test requires estimation of the contact sets between the marginal distributions. Our tests have asymptotic sizes that are exactly equal to the nominal level uniformly over the boundary points of the null hypothesis and are therefore valid over the whole null hypothesis. We also allow the prospects to be indexed by infinite as well as finite dimensional unknown parameters, so that the variables may be residuals from nonparametric and semi-parametric models. Our simulation results show that our tests are indeed more powerful than the existing sub-sampling and recentered bootstrap.

Keywords: Set estimation, Size of test, Unbiasedness, Similarity, Bootstrap, Subsampling

JEL Classification: C12, C14, C52

Suggested Citation

Linton, Oliver B. and Song, Kyungchul and Whang, Yoon-Jae, Bootstrap Tests of Stochastic Dominance with Asymptotic Similarity on the Boundary. Available at SSRN: https://ssrn.com/abstract=1097564

Oliver B. Linton

University of Cambridge ( email )

Faculty of Economics
Cambridge, CB3 9DD
United Kingdom

Kyungchul Song (Contact Author)

University of British Columbia (UBC) - Department of Economics

997-1873 East Mall
Vancouver, BC V6T 1Z1
Canada

Yoon-Jae Whang

Seoul National University - School of Economics ( email )

San 56-1, Silim-dong, Kwanak-ku
Seoul 151-742
Korea
+82 2 80 6362 (Phone)
+82 2 86 4231 (Fax)

HOME PAGE: http://plaza.snu.ac.kr/~whang

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