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Author Davidson, Russell ♦ Duclos, Jean-Yves
Source EconStor
Content type Text
Publisher Institute for the Study of Labor (IZA)
File Format PDF
Language English
Subject Domain (in DDC) Social sciences ♦ Economics
Subject Keyword stochastic dominance ♦ empirical likelihood ♦ bootstrap test ♦ Econometric and Statistical Methods and Methodology: General ♦ Hypothesis Testing: General ♦ Statistical Simulation Methods: General ♦ Measurement and Analysis of Poverty
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.
Part of series IZA Discussion Papers x2047
Learning Resource Type Article
Publisher Date 2006-01-01
Publisher Place Bonn
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