AUTHOR=Zhang Ming , Yuan Lan , Ke Zhanlian , Jian Juanfeng , Tan Hong , Lv Gangwu 

TITLE=How Does Social Insurance Affect the Social Interactions of Rural Residents in China: Study on the Impact of Rural Formal Social Security System on Informal Social Security Mechanism

JOURNAL=Frontiers in Psychology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.751946

DOI=10.3389/fpsyg.2022.751946

ISSN=1664-1078

ABSTRACT=With the increasing mobility of the rural population in China and the growing number of residents moving to the cities for work or study, rural society is forming a pluralistic, interest-centered, “open” social networks relations that follows the modern rule of law contract. Based on Chinese General Social Survey (CGSS) data, the results of the empirical study finds that social insurance can significantly enhance the social networks of rural residents in China, that is, formal social security system in rural areas promotes informal social security mechanisms such as social networks. In China, it is mainly due to the fact that social insurance has increased rural residents’ gift expenditure, education investment, and improved villagers’ sense of social equality, thus effectively enhancing villagers’ willingness and ability to interact socially. The results of the grouping test show that rural residents in China’s different regions, with different incomes and different ages, were affected by social insurance in different ways: social insurance has a greater impact on the social networks in the eastern region than in the middle and western regions; the promotion on social interaction among rural young residents is greater than that among rural middle-aged and old residents; basic medical insurance in social insurance can significantly enhance the ability and willingness to engage in social interaction among low-income residents, while the promotion of social interaction among high-income residents is more obvious with pension insurance. The propensity score matching method was used to reduce the sample selection bias, and the findings of the paper were found to be robust.