Has Urban and Rural Residence Insurance Crowded Out the Non-medical Consumption of Middle-aged and Elderly Residents?——The Analysis Based on Multiple Mediating Effect Model
As an important part of the expanded reproduction of society,consumption is not only an important strategic support for the new development pattern,but also an important direction for currently expanding domestic demand.Therefore,research on the relationship between medical insurance and consumption is of practical significance.This article uses CHARLS data and multiple mediating effect models to test whether urban and rural housing insurance crowds out the non-medical consumption of middle-aged and elderly farmers and urban residents.The research shows that urban and rural residence insurance has a certain crowding-out effect on non-medical consumption of middle-aged and elderly farmers as well as urban and rural residents,medical expenditure and savings are the complete mediating variables for urban and rural residence insurance to crowd out non-medical consumption,and that as income rises,the crowding-out effect will disappear.In order to test the robustness of the conclusion,we discussed the endogeneity of the model from three aspects:bidirectional causation,measurement bias and omitted variables,as well as the adverse selection and moral hazard of the model.Heterogeneity analysis shows that urban and rural housing security has squeezed out the food and clothing expenditures of middle-aged and elderly farmers and urban residents.In order to promote economic growth and common prosperity,relevant departments should continue to pay attention to the medical behaviors of low-income middle-aged and elderly residents in urban and rural areas.To reduce the crowding out effect on non-medical consumption,the following measures should be taken:reducing the proportion of medical service expenditures in income by increasing income,increasing the reimbursement ratio,increasing the proportion of medical insurance subsidies and solving the problem of"expensive medical treatment"at the grassroots level.
Medical InsuranceMultiple Mediating Effect ModelCrowding out EffectNon-medical ConsumptionAdverse Selection
万方数据
