Testing for Restricted Stochastic Dominance

Russell Davidson and Jean-Yves Duclos ()

No 36, Working Papers from ECINEQ, Society for the Study of Economic Inequality

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 non-dominance. 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.

Keywords: Stochastic dominance; empirical likelihood; bootstrap test (search for similar items in EconPapers)
JEL-codes: C10 C12 C15 I32 (search for similar items in EconPapers)
Date: 2006
View list of references

Downloads: (external link)
http://www.ecineq.org/milano/WP/ECINEQ2006-36.pdf First version, 2006 (application/pdf)

Related works:
Working Paper: TESTING FOR RESTRICTED STOCHASTIC DOMINANCE (2006)
Working Paper: Testing for Restricted Stochastic Dominance (2006)
Working Paper: Testing for Restricted Stochastic Dominance (2006)
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:inq:inqwps:ecineq2006-36

Access Statistics for this paper

More papers in Working Papers from ECINEQ, Society for the Study of Economic Inequality
Contact information at EDIRC.
Series data maintained by Maria Ana Lugo ().