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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 propose a procedure for estimating the critical values of the extended Kolmogorov- Smirnov tests of Stochastic Dominance of arbitrary order in the general K-prospect case. We allow for the observations to be 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 tests are consistent and powerful against some N −1/2 local alternatives. We also propose some heuristic methods for selecting subsample size and demonstrate in simulations that they perform reasonably. We describe an alternative method for obtaining critical values based on recentering the test statistic and using full sample bootstrap methods. We compare the two methods in theory and in practice.

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File URL: http://eprints.lse.ac.uk/24755/
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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 24755.

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Length: 51 pages
Date of creation: Sep 2004
Date of revision:
Handle: RePEc:ehl:lserod:24755

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References

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  1. Ian Crawford, 1999. "Nonparametric tests of stochastic dominance in bivariate distributions, with an application to UK data," IFS Working Papers W99/28, Institute for Fiscal Studies.
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