Pensions and multidimensional elderly poverty and inequality: a comparative perspective on urban and rural non-compulsory pension insurance


(1.School of Economics, Shandong University)

【Abstract】This paper uses the panel data of 2012 and 2014 CFPS to build elderly’s Multidimensional Poverty Index (MPI) and Correlation Sensitive Poverty Index (CSPI) , which includes consumption, health, living conditions (housing) , life satisfaction and future confidence in China. It then evaluates the effect of two non-compulsory pensions insurances, new rural resident pension insurance system and urban resident pension insurance system, on multidimensional poverty and inequality using the 2SLS fuzzy Regression Discontinuity Design techniques to account for the issue of endogeneity. The results show that urban and rural elderly multidimensional poverty and inequality of 2014 were lower than those of 2012.The future confidence is the largest contribution to urban and rural multidimensional poverty in 2012, while in 2014 is the housing condition. New rural resident pension insurance system and urban resident pension insurance system have no significant effect on not only the decrease of multidimensional poverty and multidimensional inequality of the elderly but also each of dimension in multidimensional poverty and multidimensional inequality. Suggestions derived from these findings are to continue to expand the coverage of two kinds of old-age insurance, to improve the level of pensions for urban and rural residents, and to remove bundled attendance.

【Keywords】 the elderly population; multidimensional poverty; inequality; pension insurance;


【Funds】 The phased achievement of the National Natural Science Foundation of China (71673167).

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(Translated by HE wenshan)


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This Article


CN: 11-1043/C

Vol , No. 05, Pages 62-73+127

October 2017


Article Outline


  • 1 Introduction
  • 2 Data sources, index selection and multidimensional poverty and inequality measurement
  • 3 Breakpoint regression method
  • 4 Empirical analysis
  • 5 Conclusions and policy suggestions
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