Conditional stochastic dominance testing
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 difference 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 difference between the joint distributions, and can be implemented under minimal smoothness requirements on the underlying nonparametric curves and without resorting to smooth estimation. The finite 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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- Oliver Linton & Kyungchul Song & Yoon-Jae Whang, 2009.
"An improved bootstrap test of stochastic dominance,"
Economics Working Papers
we094827, Universidad Carlos III, Departamento de Economía.
- Linton, Oliver & Song, Kyungchul & Whang, Yoon-Jae, 2010. "An improved bootstrap test of stochastic dominance," Journal of Econometrics, Elsevier, vol. 154(2), pages 186-202, February.
- Oliver Linton & Kyungchul Song & Yoon-Jae Whang, 2009. "An Improved Bootstrap Test of Stochastic Dominance," Cowles Foundation Discussion Papers 1713, Cowles Foundation for Research in Economics, Yale University.
- Scaillet, Olivier & Topaloglou, Nikolas, 2010.
"Testing for Stochastic Dominance Efficiency,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 28(1), pages 169-180.
- Nikolas Topaloglou & Olivier Scaillet & University of Geneva, 2006. "Testing foe Stochastic Dominance Efficiency," Computing in Economics and Finance 2006 74, Society for Computational Economics.
- Olivier Scaillet & Nikolas Topaloglou, 2005. "Testing for Stochastic Dominance Efficiency," FAME Research Paper Series rp154, International Center for Financial Asset Management and Engineering.
- Yingcun Xia & Howell Tong & W. K. Li & Li-Xing Zhu, 2002. "An adaptive estimation of dimension reduction space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 363-410.
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