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Consistent testing for stochastic dominance : a subsampling approach

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  • Oliver Linton
  • Esfandiar Maasoumi
  • Yoon-Jae Whang

Abstract

We study a very general setting, and propose a procedure for estimating the critical values of the extended Kolmogorov-Smirnov tests of First and Second Order Stochastic Dominance due to McFadden (1989) in the general k-prospect case. We allow for the observations to be generally serially dependent and, for the first time, we can accommodate general dependence amongst the prospects which are to be ranked. Also, the prospects may be the residuals from certain conditional models, opening the way for conditional ranking. We also propose a test of Prospect Stochastic Dominance. Our method is based on subsampling and we show that the resulting data tests are consistent.

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File URL: http://eprints.lse.ac.uk/2207/
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Bibliographic Info

Paper provided by London School of Economics and Political Science, LSE Library in its series LSE Research Online Documents on Economics with number 2207.

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Length: 30 pages
Date of creation: Mar 2002
Date of revision:
Handle: RePEc:ehl:lserod:2207

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Keywords: Prospect theory; stochastic dominance; stochastic equicontinuity; subsampling.;

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  1. Y.K. Tse & Xibin Zhang, 2003. "A Monte Carlo Investigation of Some Tests for Stochastic Dominance," Monash Econometrics and Business Statistics Working Papers 7/03, Monash University, Department of Econometrics and Business Statistics.
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