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Econometric Analysis of Stochastic Dominance

Author

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  • Whang,Yoon-Jae

Abstract

This book offers an up-to-date, comprehensive coverage of stochastic dominance and its related concepts in a unified framework. A method for ordering probability distributions, stochastic dominance has grown in importance recently as a way to measure comparisons in welfare economics, inequality studies, health economics, insurance wages, and trade patterns. Whang pays particular attention to inferential methods and applications, citing and summarizing various empirical studies in order to relate the econometric methods with real applications and using computer codes to enable the practical implementation of these methods. Intuitive explanations throughout the book ensure that readers understand the basic technical tools of stochastic dominance.

Suggested Citation

  • Whang,Yoon-Jae, 2019. "Econometric Analysis of Stochastic Dominance," Cambridge Books, Cambridge University Press, number 9781108472791, January.
    • Handle: RePEc:cup:cbooks:9781108472791
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    Citations

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    Cited by:

    1. Almas Heshmati & Esfandiar Maasoumi & Guanghua Wan, 2019. "An Analysis of the Determinants of Household Consumption Expenditure and Poverty in India," Economies, MDPI, vol. 7(4), pages 1-27, September.
    2. Brendan K. Beare, 2023. "Optimal measure preserving derivatives revisited," Mathematical Finance, Wiley Blackwell, vol. 33(2), pages 370-388, April.
    3. Lok, Thomas M. & Tabri, Rami V., 2021. "An improved bootstrap test for restricted stochastic dominance," Journal of Econometrics, Elsevier, vol. 224(2), pages 371-393.
    4. Alkire, Sabina & Oldiges, Christian & Kanagaratnam, Usha, 2021. "Examining multidimensional poverty reduction in India 2005/6–2015/16: Insights and oversights of the headcount ratio," World Development, Elsevier, vol. 142(C).
    5. Lee, K. & Linton, O. & Whang, Y-J., 2020. "Testing for Time Stochastic Dominance," Cambridge Working Papers in Economics 20121, Faculty of Economics, University of Cambridge.
    6. Linton, O. & Seo, M. & Whang, Y-J., 2020. "Testing Stochastic Dominance with Many Conditioning Variables," Cambridge Working Papers in Economics 2004, Faculty of Economics, University of Cambridge.
    7. Feghhi Kashani , Mohammad & Mohebimajd , Ahmadreza, 2021. "Outperformance Testing of a Dynamic Assets Portfolio Selection Supplemented with a Continuous Paths Levy Process," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(2), pages 253-282, June.
    8. Rami V. Tabri & Christopher D. Walker, 2020. "Inference for Moment Inequalities: A Constrained Moment Selection Procedure," Papers 2008.09021, arXiv.org, revised Aug 2020.
    9. Fakih, Ali & Makdissi, Paul & Marrouch, Walid & Tabri, Rami V. & Yazbeck, Myra, 2022. "A stochastic dominance test under survey nonresponse with an application to comparing trust levels in Lebanese public institutions," Journal of Econometrics, Elsevier, vol. 228(2), pages 342-358.
    10. Anderson, Gordon & Fu, Rui & Leo, Teng Wah, 2022. "Health, loneliness and the ageing process in the absence of cardinal measure: Rendering intangibles tangible," The Journal of the Economics of Ageing, Elsevier, vol. 22(C).
    11. Mariusz Górajski & Zbigniew Kuchta, 2022. "Which hallmarks of optimal monetary policy rules matter in Poland? A stochastic dominance approach," Bank i Kredyt, Narodowy Bank Polski, vol. 53(2), pages 149-182.
    12. Anyfantaki, Sofia & Arvanitis, Stelios & Topaloglou, Nikolas, 2021. "Diversification benefits in the cryptocurrency market under mild explosivity," European Journal of Operational Research, Elsevier, vol. 295(1), pages 378-393.
    13. Wang, Dewei & Tang, Chuan-Fa & Tebbs, Joshua M., 2020. "More powerful goodness-of-fit tests for uniform stochastic ordering," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).

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