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Improving the Power of Tests of Stochastic Dominance

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We extend Hansen’s (2005) recentering method to a continuum of inequality constraints to construct new Kolmogorov-Smirnov tests for stochastic dominance of any pre-specified order. We show that our tests have correct size asymptotically, are consistent against fixed alternatives and are unbiased against some N−1/2 local alternatives. It is shown that by avoiding the use of the least favorable configuration, our tests are less conservative and more powerful than Barrett and Donald’s (2003) and in some simulation examples we consider, we find that our test can be more powerful than the subsampling test of Linton, Maasoumi and Whang (2005). We apply our method to test stochastic dominance relations between Canadian income distributions in 1978 and 1986 as considered in Barrett and Donald (2003) and find that some of the hypothesis test results are different using the new method.

Suggested Citation

  • Stephen G. Donald & Yu-Chin Hsu, 2012. "Improving the Power of Tests of Stochastic Dominance," IEAS Working Paper : academic research 12-A015, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Jun 2013.
  • Handle: RePEc:sin:wpaper:12-a015
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    Cited by:

    1. Chang, Chia-Lin & Jiménez-Martín, Juan-Ángel & Maasoumi, Esfandiar & Pérez-Amaral, Teodosio, 2015. "A stochastic dominance approach to financial risk management strategies," Journal of Econometrics, Elsevier, vol. 187(2), pages 472-485.
    2. Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Esfandiar Maasoumi & Michel McAleer & Teodosio Pérez-Amaral, 2015. "Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance," Tinbergen Institute Discussion Papers 15-133/III, Tinbergen Institute.
    3. Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Esfandiar Maasoumi & Michael McAleer & Teodosio Pérez-Amaral, 2015. "A Stochastic Dominance Approach to the Basel III Dilemma: Expected Shortfall or VaR?," Documentos de Trabajo del ICAE 2015-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    4. David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2017. "Bayesian assessment of Lorenz and stochastic dominance," Monash Econometrics and Business Statistics Working Papers 15/17, Monash University, Department of Econometrics and Business Statistics.
    5. repec:eee:econom:v:198:y:2017:i:2:p:253-270 is not listed on IDEAS
    6. David M. Kaplan & Matt Goldman, 2013. "Comparing distributions by multiple testing across quantiles," Working Papers 16-19, Department of Economics, University of Missouri, revised Nov 2016.
    7. Chuang, O-Chia & Kuan, Chung-Ming & Tzeng, Larry Y., 2017. "Testing for central dominance: Method and application," Journal of Econometrics, Elsevier, vol. 196(2), pages 368-378.
    8. Barrett, Garry F. & Donald, Stephen G. & Hsu, Yu-Chin, 2016. "Consistent tests for poverty dominance relations," Journal of Econometrics, Elsevier, vol. 191(2), pages 360-373.

    More about this item

    Keywords

    Stochastic dominance; test consistency; simulation; bootstrap; uniform inference;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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