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Consistent testing for stochastic dominance: a subsampling approach

  • Oliver Linton

    ()

    (Institute for Fiscal Studies and cemmap and Cambridge)

  • Esfandiar Maasoumi

    (Institute for Fiscal Studies)

  • Yoon-Jae Wang

    (Institute for Fiscal Studies)

We propose a procedure for estimating the critical values of the extended Kolmogorov- Smirnov tests of First and Second Order Stochastic Dominance in the general K-prospect case. We allow for the observations to be serially dependent and, for the rst 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 N1=2 local alternatives. We also propose some heuristic methods for selecting subsample size and demonstrate in simulations that they perform reasonably.

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File URL: http://cemmap.ifs.org.uk/wps/cwp0203.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP03/02.

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Length: 42 pp.
Date of creation: Dec 2002
Date of revision:
Handle: RePEc:ifs:cemmap:03/02
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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.
  2. Daniel L. Millimet & Esfandiar Maasoumi, 2005. "Robust inference concerning recent trends in US environmental quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 55-77.
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