Testing for restricted stochastic dominance: some further results
AbstractExtensions are presented to the results of Davidson and Duclos (2007), whereby the null hypothesis of restricted stochastic non dominance can be tested by both asymptotic and bootstrap tests, the latter having considerably better properties as regards both size and power. In this paper, the methodology is extended to tests of higherorder stochastic dominance. It is seen that, unlike the first-order case, a numerical nonlinear optimisation problem has to be solved in order to construct the bootstrap DGP. Conditions are provided for a solution to exist for this problem, and efficient numerical algorithms are laid out. The empirically important case in which the samples to be compared are correlated is also treated, both for first-order and for higher-order dominance. For all of these extensions, the bootstrap algorithm is presented. Simulation experiments show that the bootstrap tests perform considerably better than asymptotic tests, and yield reliable inference in moderately sized samples.
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Date of creation: 30 Dec 2009
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Higher-order stochastic dominance; empirical likelihood; bootstrap test; correlated samples;
Other versions of this item:
- Russell Davidson, 2009. "Testing for Restricted Stochastic Dominance: Some Further Results," Review of Economic Analysis, Rimini Centre for Economic Analysis, vol. 1(1), pages 34-59, September.
- Russell Davidson, 2007. "Testing For Restricted Stochastic Dominances: Some Further Results," Departmental Working Papers 2007-15, McGill University, Department of Economics.
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- I32 - Health, Education, and Welfare - - Welfare and Poverty - - - Measurement and Analysis of Poverty
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-01-16 (All new papers)
- NEP-ECM-2010-01-16 (Econometrics)
- NEP-ORE-2010-01-16 (Operations Research)
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