Version 1
: Received: 26 December 2022 / Approved: 27 December 2022 / Online: 27 December 2022 (03:22:26 CET)
How to cite:
Lin, B.; Li, W.; Zhang, Y. Y.; Wu, J. The Role of Trust in Government in China’s Rural Pension Program. Preprints2022, 2022120508. https://doi.org/10.20944/preprints202212.0508.v1
Lin, B.; Li, W.; Zhang, Y. Y.; Wu, J. The Role of Trust in Government in China’s Rural Pension Program. Preprints 2022, 2022120508. https://doi.org/10.20944/preprints202212.0508.v1
Lin, B.; Li, W.; Zhang, Y. Y.; Wu, J. The Role of Trust in Government in China’s Rural Pension Program. Preprints2022, 2022120508. https://doi.org/10.20944/preprints202212.0508.v1
APA Style
Lin, B., Li, W., Zhang, Y. Y., & Wu, J. (2022). The Role of Trust in Government in China’s Rural Pension Program. Preprints. https://doi.org/10.20944/preprints202212.0508.v1
Chicago/Turabian Style
Lin, B., Yu Yvette Zhang and Junbiao Wu. 2022 "The Role of Trust in Government in China’s Rural Pension Program" Preprints. https://doi.org/10.20944/preprints202212.0508.v1
Abstract
This paper estimates the effect of trust in government on rural residents’ contributions in China’s rural pension program using the Propensity Score Matching (PSM) method. We construct an analytical framework for rural residents' decision-making in pension program and provide analysis using data from China Family Panel Studies (CFPS) and 25 provincial Departments of the Human Resources and Social Security (DOHRSS) in China. Our analysis shows that rural residents’ trust in government will influence their contributions to the pension programs by affecting their expected return of the investments. Our results suggest that the government should improve rural residents’ trust in government in order to develop a successful and sustainable rural pension program.
Keywords
China’s Rural Pension Program; Pension contribution; Trust in government; Propensity Score Matching method; Rural China
Subject
Business, Economics and Management, Economics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
