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Does a Universal Pension Reduce Elderly Poverty in China?

Anqi Zhang and Katsushi Imai
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Anqi Zhang: Department of Economics, The University of Manchester, UK and Institute of Belt and Road & Global Governance, Fudan University, CHINA

No DP2022-30, Discussion Paper Series from Research Institute for Economics & Business Administration, Kobe University

Abstract: This paper studies the impact of the universal pension programme on elderly poverty in both rural and urban China. Using the three rounds of panel data based on the Health and Retirement Longitudinal Study (CHARLS) in 2011-2015, we examine whether the universal pension programme reduced elderly poverty, comprehensively defined to cover both unidimensional and multidimensional poverty indices of the households and individuals. To utilise the longitudinal nature of the data, we apply the robust Fixed-Effects (FE) Model with Propensity Score Matching (PSM) and the FE Quantile Model with PSM taking into account the unobservable individual characteristics, such as entrepreneurship or risk preference. Our results show that the universal pension programme reduced poverty in monetary and non-monetary terms in both rural and urban areas. While rural people tend to continue to work in the labour market after the receipt of the pension, urban people work less due to the negative income effect of the programme. The panel quantile regression results suggest that the programme decreased the inequality in both monetary and non-monetary dimensions. Our results provide strong evidence to underscore the success of the Chinese universal pension programme in reducing poverty and inequality in both rural and urban areas.

Keywords: Poverty; Inequality; Multidimensional Poverty Index (MPI); Pension; Impact evaluation; China (search for similar items in EconPapers)
JEL-codes: C23 H75 I32 I38 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2022-06
New Economics Papers: this item is included in nep-age, nep-cna and nep-hea
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https://www.rieb.kobe-u.ac.jp/academic/ra/dp/English/DP2022-30.pdf First version, 2022 (application/pdf)

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