Conditional Stochastic Dominance Testing
نویسندگان
چکیده
This article proposes bootstrap-based stochastic dominance tests for nonparametric conditional distributions and their moments. We exploit the fact that a conditional distribution dominates the other if and only if the di¤erence between the marginal joint distributions is monotonic in the explanatory variable for each value of the dependent variable. The proposed test statistic compares restricted and unrestricted estimators of the di¤erence between the joint distributions, and can be implemented under minimal smoothness requirements on the underlying nonparametric curves and without resorting to smooth estimation. The nite sample properties of the proposed tests are examined by means of a Monte Carlo study. We report an application to studying the impact on post-intervention earnings of the National Supported Work Demonstration, a randomized labor training program carried out in the 1970s.
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