Effects of public health insurance on labor supply in rural China

Abstract

Purpose Since the implementation of the New Cooperative Medical Scheme (NCMS) in 2003, this program has experienced rapid growth. Even so, little is known about the association between NCMS expansion and labor force supply among rural residents in China. The purpose of this paper is to examine the effects of the NCMS on labor force supply for rural Chinese populations. Design/methodology/approach Using data from the China Health and Nutrition Survey (CHNS), a difference-in-differences (DD) approach is employed to estimate the impact of NCMS expansion on labor supply outcomes, including hours of worked in agriculture, off-farm labor force participation, not working, and weeks off due to illness. A number of falsification tests are conducted to identify whether the assumption of common trends of DD analyses is satisfied. The robustness of results is checked through additional estimation, including panel fixed effects and instrumental variable approach. Findings Results show that the NCMS expansion has a positive effect on the hours of worked in agriculture and off-farm labor force participation, and reduces the likelihood of not working and weeks off due to illness. The effect on hours of agricultural production is larger for male adults, those aged 50 or more, and individuals in low-income families. This study demonstrates the importance of potential health improvements from public health insurance in promoting rural residents’ labor productivity. Originality/value Studies concerning the effects of public health insurance on labor supply in developing countries remain limited. The findings of this study provide important insights into how public health insurance programs, like the NCMS, may affect patterns of labor supply among rural residents, and can help policymakers improve health policies aimed to reduce the number of uninsured farmers while maintaining high levels of labor supply, productivity, and health status among the most vulnerable of populations.

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