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Dynamics of Multidimensional Poverty and Uni-dimensional Income Poverty: An Evidence of Stability Analysis from China

  • Sabina Alkire
  • Yingfeng Fang
Article

Abstract

In this paper, we construct an illustrative multidimensional poverty index for China and compare it with income poverty using the panel data from multiple waves of the China Health and Nutrition Survey. We use first order stochastic dominance method and regression analysis to test the stability of multidimensional poverty measures and probe the often-observed mis-match between multidimensional measures and income measures. We find as expected that China’s multidimensional poverty is significantly higher in rural areas and in the less developed western provinces. But relative to the income poverty, the multidimensional poverty is less volatile. Also, the ranking of provinces by income and multidimensional poverty varies. The multidimensional poverty measures are somewhat sensitive to the large change of weight, but if we control the indicators’ weight, then the multidimensional poverty measures are stable to a change of indicators.

Keywords

Poverty measurement Multidimensional poverty Stability Weight Robustness tests Mis-match 

JEL Classification

I3 I32 O1 D63 

Notes

Acknowledgements

Funding was provided by the Research project in Humanities and Social Sciences by the Ministry of Education of China (Grant No. 14YJC790026).

References

  1. Alkire, S. (2007). The missing dimensions of poverty data: Introduction to the special issue. Oxford Development Studies, 35(4), 347–359.CrossRefGoogle Scholar
  2. Alkire, S. (2008). Choosing dimensions: The capability approach and multidimensional poverty. MPRA working paper No. 8862.Google Scholar
  3. Alkire, S., & Foster, J. (2007). Counting and multidimensional poverty measurement. OPHI working paper.Google Scholar
  4. Alkire, S., & Foster, J. (2011). Counting and multidimensional poverty measurement. Journal of Public Economics, 95(7–8), 476–487.CrossRefGoogle Scholar
  5. Alkire, S., Foster, J., Seth, S., Roche, J. M., & Ballon, P. (2015). Multidimensional poverty measurement and analysis. Oxford: Oxford University Press.CrossRefGoogle Scholar
  6. Alkire, S., Jindra, C., Robles, G., & Vaz, A. (2016). “Multidimensional Poverty Index-2016: Brief methodological note and results.” OPHI briefing 42. Oxford: Oxford University Press.Google Scholar
  7. Alkire, S., & Santos, M. E. (2010). Acute multidimensional poverty: A new index for developing countries. United Nations Development Programme Human Development Reports Research Paper.Google Scholar
  8. Alkire, S., & Santos, M. E. (2014). Measuring acute poverty in the developing world: Robustness and scope of the Multidimensional Poverty Index. World Development, 59, 251–274.CrossRefGoogle Scholar
  9. Alkire, S., & Seth, S. (2015). Multidimensional poverty reduction in India between 1999 and 2006: Where and How? World Development, 72, 93–108.CrossRefGoogle Scholar
  10. Anand, S. & Sen, A. (1997). Concepts of human development and poverty: A multidimensional perspective (pp. 1–20). United Nations Development Programme, Poverty and human development: Human development papers 1997. New York: United Nations.Google Scholar
  11. Atkinson, A. B. (2003). Multidimensional deprivation: Contrasting social welfare and counting approaches. Journal of Economic Inequality, 1(1), 51–65.CrossRefGoogle Scholar
  12. Banerjee, A. V., & Duflo, E. (2011). Poor economics: A radical rethinking of the way to fight global poverty. U.S.: Public Affairs.Google Scholar
  13. Bourguignon, F., & Chakravarty, S. R. (2003). The measurement of multidimensional poverty. Journal of Economic Inequality, 1(1), 25–49.CrossRefGoogle Scholar
  14. Davidson, R., & Duclos, J.-Y. (2000). Statistical inference for stochastic dominance and for the measurement of poverty and inequality. Econometrica, 68(6), 1435–1464.CrossRefGoogle Scholar
  15. Decancq, K., & Lugo, M. A. (2013). Weights in multidimensional indices of wellbeing: An overview. Econometric Reviews, 32(1), 7–34.CrossRefGoogle Scholar
  16. Deutsch, J., & Silber, J. (2005). Measuring multidimensional poverty: An empirical comparison of various approaches. Review of Income and Wealth, 51(1), 145–174.CrossRefGoogle Scholar
  17. Duclos, J.-Y., & Makdissi, P. (2005). Squential stochastic dominance and the robustness of poverty orderings. Review of Income and Wealth, 51(1), 63–87.CrossRefGoogle Scholar
  18. Duclos, J.-Y., Sahn, D., & Younger, S. D. (2006). Robust multidimensional poverty comparisons. The Economic Journal, 116(514), 943–968.CrossRefGoogle Scholar
  19. Duflo, E., Greenstone, M., Guiteras, R. & Clasen, T. (2015). Toilets can work: Short and medium run health impacts of addressing complementaries and externalities in water and sanitation. Working paper.Google Scholar
  20. Foster, J., Greer, J., & Thorbecke, E. (1984). A class of decomposable poverty measures. Econometrica, 52(3), 761–766.CrossRefGoogle Scholar
  21. Foster, J. E., McGillivray, M., & Seth, S. (2013). Rank robustness of composite indices. Econometric Reviews, 32(1), 33–56.CrossRefGoogle Scholar
  22. Khan, A. U., Saboor, A., Hussain, A., Sadiq, S., & Mohsin, A. Q. (2013). Investigating multidimensional poverty across regions in Sindh province of Pakistan. Social Indicators Research, 119(1), 515–532.Google Scholar
  23. Labar, K., & Bresson, F. (2011). A multidimensional analysis of poverty in China from 1991 to 2006. China Economic Review, 22(3), 646–668.CrossRefGoogle Scholar
  24. Montoya, A., & Teixeria, K. (2017). Multidimensional poverty in Nicargua: Are female headed households better off? Social Indicators Research, 132, 1037–1063.CrossRefGoogle Scholar
  25. Njong, M. A. & Ningaye, P. (2008). Characterizing weights in the measurement of multidimensional poverty: An application of data-driven approaches to Cameroonian data. OPHI working paper No. 21.Google Scholar
  26. Oginni, A., Ahonsi, B., & Ukwuije, F. (2013). Are female-headed households typically poorer than male-headed households in Nigeria. The Journal of Socio-Economics, 45, 132–137.CrossRefGoogle Scholar
  27. Putnam, H. (2004). The collapse of the fact/value dichotomy and other essays. Cambridge: Harvard University Press.Google Scholar
  28. Ravallion, M. (2011). On multidimensional indices of poverty. Journal of Economic Inequality, 9(2), 235–248.CrossRefGoogle Scholar
  29. Sen, A. K. (1967). The nature and classes of prescriptive judgements. The Philosophical Quarterly, 17(66), 46–62.CrossRefGoogle Scholar
  30. Sen, A. K. (1976). Poverty: An ordinal approach to measurement. Econometrica, 44(2), 219–231.CrossRefGoogle Scholar
  31. Sen, A. K. (1985). Commodities and Capabilities. Amsterdam: North Holland.Google Scholar
  32. Sen, A. K. (1999). Development as freedom. Oxfrod: Oxford University Press.Google Scholar
  33. Tsui, K. Y. (2002). Multidimensional poverty index. Social Choice and Welfare, 19(1), 69–93.CrossRefGoogle Scholar
  34. UN. (2003). Indicators for monitoring the Millennium Development Goals. New York: United Nations.Google Scholar
  35. UNESCO. (2010). Reaching the marginalized. Oxford: Oxford University Press.Google Scholar
  36. Wang, X. L., & Alkire, S. (2009). Measurement of multidimensional poverty in China: Estimation and policy implications. Chinese Rural Economy, 12, 4–23. (in Chinese).Google Scholar
  37. Wang, X., Feng, H., Xia, Q. & Alkire, S. (2009). On the relationship between income poverty and multidimensional poverty in China. OPHI Working paper, University of Oxford.Google Scholar
  38. Yu, J. (2013). Multidimensional poverty in China: Findings based on the CHNS. Social Indicators Research, 112(2), 315–336.CrossRefGoogle Scholar
  39. Zou, W., & Fang, Y. F. (2011). A multidimensional study of China’s poverty dynamics. Chinese Journal of Population Science, 6, 49–59. (in Chinese).Google Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Oxford Poverty and Human Development InitiativeUniversity of OxfordOxfordUK
  2. 2.Economics and Management SchoolWuhan UniversityWuhanChina

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