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New Tests for Richness and Poorness:A Stochastic Dominance Analysis of Income Distributions in Hong Kong

Author

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  • Sheung-Chi Chow
  • Ma. Rebecca Valenzuela
  • Wing-Keung Wong

Abstract

In this paper, we develop the theory of descending stochastic dominance for application to income distribution analysis. We show that conclusions of dominance obtained using our new tests of richness and poorness offer more accurate and more in-depth characterization of welfare inequality in any population. The empirical application of our proposed approach shows that, for Hong Kong, the distribution of total incomes in 2001 has less proportion of poor units in relatively lower income levels compared to that of 2006 at the same time that the distribution of total incomes in 2006 has a higher proportion of rich units in relatively higher income levels. Our analysis also suggests that there exist lower levels of household welfare in 2011 compared to both 2001 and 2006. In terms of age groups, the application of our new methods showed that the younger age cohorts tended to have lesser proportions of poor units in relatively lower income levels compared to those in the 65+ age group, while at the same time, those in the 65+ age group tended to have a higher proportion of rich units in the relatively higher income levels. These extreme concentrations of income units at the ‘bottom end’ for the younger households and at the ‘top end’ for the older households may help explain the overall high inequality level that has persisted in Hong Kong for several years now.

Suggested Citation

  • Sheung-Chi Chow & Ma. Rebecca Valenzuela & Wing-Keung Wong, 2016. "New Tests for Richness and Poorness:A Stochastic Dominance Analysis of Income Distributions in Hong Kong," Monash Economics Working Papers 25-16, Monash University, Department of Economics.
  • Handle: RePEc:mos:moswps:2016-25
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    References listed on IDEAS

    as
    1. Zhidong Bai & Hua Li & Michael McAleer & Wing-Keung Wong, 2015. "Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 889-900, May.
    2. Andreas Peichl & Thilo Schaefer & Christoph Scheicher, 2010. "Measuring Richness And Poverty: A Micro Data Application To Europe And Germany," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(3), pages 597-619, September.
    3. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 735-765.
    4. Francisco M. Gonzalez & Jean‐François Wen, 2015. "A Theory of Top Income Taxation and Social Insurance," Economic Journal, Royal Economic Society, vol. 125(587), pages 1474-1500, September.
    5. Bishop, John A & Formby, John P & Thistle, Paul D, 1992. "Convergence of the South and Non-South Income Distributions, 1969-1979," American Economic Review, American Economic Association, vol. 82(1), pages 262-272, March.
    6. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    7. Branko Milanovic, 2014. "The Return of "Patrimonial Capitalism": A Review of Thomas Piketty's Capital in the Twenty-First Century," Journal of Economic Literature, American Economic Association, vol. 52(2), pages 519-534, June.
    8. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    9. Moshe Levy & Haim Levy, 2002. "Prospect Theory: Much Ado About Nothing?," Management Science, INFORMS, vol. 48(10), pages 1334-1349, October.
    10. Thierry Post & Haim Levy, 2005. "Does Risk Seeking Drive Stock Prices? A Stochastic Dominance Analysis of Aggregate Investor Preferences and Beliefs," Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 925-953.
    11. Anderson, Gordon, 2004. "Toward an empirical analysis of polarization," Journal of Econometrics, Elsevier, vol. 122(1), pages 1-26, September.
    12. Fong, Wai Mun & Lean, Hooi Hooi & Wong, Wing Keung, 2008. "Stochastic dominance and behavior towards risk: The market for Internet stocks," Journal of Economic Behavior & Organization, Elsevier, vol. 68(1), pages 194-208, October.
    13. Dominic Gasbarro & Wing-Keung Wong & J. Kenton Zumwalt, 2007. "Stochastic Dominance Analysis of iShares," The European Journal of Finance, Taylor & Francis Journals, vol. 13(1), pages 89-101.
    14. Meyer, Jack, 1987. "Two-moment Decision Models and Expected Utility Maximization," American Economic Review, American Economic Association, vol. 77(3), pages 421-430, June.
    15. Wong, Wing-Keung, 2007. "Stochastic dominance and mean-variance measures of profit and loss for business planning and investment," European Journal of Operational Research, Elsevier, vol. 182(2), pages 829-843, October.
    16. Milton Friedman & L. J. Savage, 1948. "The Utility Analysis of Choices Involving Risk," Journal of Political Economy, University of Chicago Press, vol. 56, pages 279-279.
    17. Russell Davidson & Jean-Yves Duclos, 2000. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," Econometrica, Econometric Society, vol. 68(6), pages 1435-1464, November.
    18. Esfandiar Maasoumi & Almas Heshmati, 2013. "Analysis of Stochastic Dominance Ranking of Chinese Income Distributions by Household Attributes," Emory Economics 1308, Department of Economics, Emory University (Atlanta).
    19. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
    20. Almas Heshmati & Robert Rudolf, 2014. "Income versus Consumption Inequality in Korea: Evaluating Stochastic Dominance Rankings by Various Household Attributes," Asian Economic Journal, East Asian Economic Association, vol. 28(4), pages 413-436, December.
    21. Milanovic, Branko, 2013. "The return of “patrimonial capitalism”: review of Thomas Piketty’s Capital in the 21st century," MPRA Paper 52384, University Library of Munich, Germany.
    22. Lean, Hooi-Hooi & Wong, Wing-Keung & Zhang, Xibin, 2008. "The sizes and powers of some stochastic dominance tests: A Monte Carlo study for correlated and heteroskedastic distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(1), pages 30-48.
    23. Chan, Raymond H. & Clark, Ephraim & Wong, Wing-Keung, 2012. "On the Third Order Stochastic Dominance for Risk-Averse and Risk-Seeking Investors," MPRA Paper 42676, University Library of Munich, Germany.
    24. Wei, Steven X. & Zhang, Chu, 2003. "Statistical and economic significance of stock return predictability: a mean-variance analysis," Journal of Multinational Financial Management, Elsevier, vol. 13(4-5), pages 443-463, December.
    25. Blakorby, Charles & Donaldson, David, 1980. "Ethical Indices for the Measurement of Poverty," Econometrica, Econometric Society, vol. 48(4), pages 1053-1060, May.
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    Citations

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    Cited by:

    1. Chang, C-L. & McAleer, M.J. & Wong, W.-K., 2018. "Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections," Econometric Institute Research Papers 18-024/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(1), pages 1-29, March.
    3. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2016. "Management science, economics and finance: A connection," Documentos de Trabajo del ICAE 2016-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    4. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(1), pages 1-29, March.
    5. Valenzuela, Maria Rebecca & Wong, Wing-Keung & Zhen, Zhu Zhen, 2017. "Income and Consumption Inequality in the Philippines: A Stochastic Dominance Analysis of Household Unit Records," ADBI Working Papers 662, Asian Development Bank Institute.

    More about this item

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General

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