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Evaluating the effectiveness of the rural minimum living standard guarantee (Dibao) program in China

Nanak Kakwani, Shi Li (), Xiaobing Wang and Mengbing Zhu

China Economic Review, 2019, vol. 53, issue C, 1-14

Abstract: China's Rural Minimum Living Standard Guarantee program (Dibao) is the largest social safety-net program in the world. Given the scale and the popularity of Rural Dibao, it is necessary to rigorously evaluate it so that policymakers know the extent to which the program meets its intended objective of reducing poverty. This paper develops some new methods and uses data from the 2013 Chinese Household Income Project (CHIP2013) to examine the targeting performance of the rural Dibao program. The paper has found that the Rural Dibao program suffers from very low targeting accuracy, high exclusion error, and inclusion error, and yields a significant negative social rate of return. It discusses possible causes and argues that the fundamental mechanism has to be redesigned to increase the effectiveness of the program. The paper makes some recommendations to reform Dibao that will significantly improve targeting and reduce the cost of running the program. That will help China to achieve its goal of eradicating extreme poverty by 2020.

Keywords: Dibao; Policy effectiveness; Poverty reduction; Social rate of return; China (search for similar items in EconPapers)
JEL-codes: O11 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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Working Paper: Evaluating the effectiveness of the rural minimum living standard guarantee (Dibao) programme in China (2018) Downloads
Working Paper: Evaluating the effectiveness of the Rural Minimum Living Standard Guarantee (Dibao) program in China (2017) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chieco:v:53:y:2019:i:c:p:1-14

DOI: 10.1016/j.chieco.2018.07.010

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China Economic Review is currently edited by B.M. Fleisher, K. X. D. Huang, M.E. Lovely, Y. Wen, X. Zhang and X. Zhu

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