Testing for Restricted Stochastic Dominance

Jean-Yves Duclos () and Russell Davidson

No 430, LIS Working papers from LIS Cross-National Data Center in Luxembourg

Abstract: Asymptotic and bootstrap tests are studied for testing whether there is a relation of stochastic dominance between two distributions. These tests have a null hypothesis of nondominance, with the advantage that, if this null is rejected, then all that is left is dominance. This also leads us to define and focus on restricted stochastic dominance, the only empirically useful form of dominance relation that we can seek to infer in many settings. One testing procedure that we consider is based on an empirical likelihood ratio. The computations necessary for obtaining a test statistic also provide estimates of the distributions under study that satisfy the null hypothesis, on the frontier between dominance and nondominance. These estimates can be used to perform bootstrap tests that can turn out to provide much improved reliability of inference compared with the asymptotic tests so far proposed in the literature.

Pages: 39 pages
Date: 2006-03
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)

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http://www.lisdatacenter.org/wps/liswps/430.pdf (application/pdf)

Related works:
Working Paper: Testing for Restricted Stochastic Dominance (2013)
Working Paper: Testing for restricted stochastic dominance (2009)
Working Paper: Testing for Restricted Stochastic Dominance (2006)
Working Paper: Testing for Restricted Stochastic Dominance (2006)
Working Paper: Testing for Restricted Stochastic Dominance (2006)
Working Paper: TESTING FOR RESTRICTED STOCHASTIC DOMINANCE (2006)
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