Health Insurance and Farm Labor Supply: Evidence from China's Urban and Rural Residents' Basic Medical Insurance Reform

Abstract

Background: In 2017, China launched the Urban and Rural Residents' Basic Medical Insurance program, with the primary goal of improving insurance benefits, particularly for those living in rural areas, and reducing rural-urban disparities. This study examined the impact of China’s Urban and Rural Residents' Basic Medical Insurance on the retirement decisions and labor market participation of individuals in rural areas aged 45 years and older. I hypothesized that the health insurance reform may increase the likelihood of retirement and reduce weekly working hours by alleviating their concerns about potential catastrophic medical expenditures in the future and motivating them to allocate more time towards managing their health conditions.Methods: To test this hypothesis, I used the nationally representative data from the China Health and Retirement Longitudinal Study, which comprises data from the waves conducted in 2011, 2013, 2015, and 2018. The final sample consisted of 6,536 rural participants aged 45 years and older who had complete data for outcome and control variables. The outcome variables examined in this study were retirement status, a binary variable that takes 1 if the participant is retired, and working hours per week, a continuous variable. This study controlled for individual-level variables including age, gender, marital status, education level, income, number of living children, number of living sons, and self-reported health, and city-level variables including GDP per capita and unemployment rate. To address potential endogeneity, this study employed the instrumental variable method, using whether the program was implemented before a given year as an instrument. Specifically, the Probit model with the IV as an independent variable was first implemented to estimate the probabilities of enrolling in the URRBMI. Subsequently, the fitted enrollment probability was included as an instrument for the endogenous variable along with exogenous covariates in a Two-stage Least-squares Regression. Results: In the final sample, 26.24% of the participants were in a retired status. The mean weekly working hours stood at 32.03 hours. The IV regression results indicated that the URRBMI increased the likelihood of retirement by 22.5% and led to a reduction of 13.51 hours in the working hours after adjusting for individual-level control variables and city-level control variables. The decrease in working hours was primarily driven by a decrease in labor supply among those who continue to work. Through heterogeneous analysis, I found that this behavioral shift could be primarily attributed to the reform's incentivization of individuals to allocate a greater portion of their time to healthcare management and its role in mitigating the probability of catastrophic health expenditure. Furthermore, I found suggestive evidence that after this reform individuals exhibited a 54% increased likelihood of engaging in self-employment and a 66% decreased likelihood of working off-farm. Conclusions: This study provided evidence that among those aged 45 and above in rural settings, the implementation of the URRBMI motivated them to retire earlier and reduced their working hours per week. Additionally, the URRBMI enhanced the likelihood of agricultural employment and self-employment, which is instrumental in curbing rural depopulation and fostering entrepreneurship within society.