An Improved Bootstrap Test of Stochastic Dominance

Oliver Linton, Kyungchul Song and Yoon-Jae Whang ()
Additional contact information
Oliver Linton: London School of Economics
Kyungchul Song: University of Pennsylvania

No 1713, Cowles Foundation Discussion Papers from Cowles Foundation, Yale University

Abstract: We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that the variables are allowed to be residuals from nonparametric and semiparametric models. The proposed bootstrap tests have asymptotic sizes that are less than or equal to the nominal level uniformly over probabilities in the null hypothesis under regularity conditions. This paper also characterizes the set of probabilities that the asymptotic size is exactly equal to the nominal level uniformly. As our simulation results show, these characteristics of our tests lead to an improved power property in general. The improvement stems from the design of the bootstrap test whose limiting behavior mimics the discontinuity of the original test's limiting distribution.

Keywords: Set estimation, Size of test, Similarity; Bootstrap, Subsampling (search for similar items in EconPapers)
JEL-codes: C12 C14 C52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ore
Date: 2009-07
View list of references

Downloads: (external link)
http://cowles.econ.yale.edu/P/cd/d17a/d1713.pdf (application/pdf)

Related works:
Working Paper: An improved bootstrap test of stochastic dominance (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cwl:cwldpp:1713

Ordering information: This working paper can be ordered from
Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
The price is None.

Access Statistics for this paper

More papers in Cowles Foundation Discussion Papers from Cowles Foundation, Yale University
Address: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Contact information at EDIRC.
Series data maintained by Glena Ames ().