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Psychological Distress in Urbanizing China: How Does Local Government Effectiveness Matter?
Juan Chen1, Lin Gong1, Shenghua Xie2
1Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
Abstract:
Despite growing literature identifying key individual, family, community, and environmental factors as causes for mental disorders during the process of urbanization, the role played by local government has not been taken into account. In this article, we investigate how the effectiveness of local government affects residents' levels of psychological distress in areas of China undergoing urbanization. We measure the effectiveness of local governments according to their success in promoting access to the social security system through the distribution of social security cards among citizens. We hypothesize that higher local government effectiveness will reduce residents' psychological distress by alleviating worries about medical expenses and elder care. Drawing on data from the 2018 Urbanization and Quality of Life Survey (N = 3229) conducted in 40 localities undergoing rural-urban transition, we estimate three-level mixed-effects regression models to test the research hypotheses, allowing random effects at the township/county and neighborhood levels while controlling for a series of individual attributes. The results demonstrate that local government effectiveness is negatively associated with residents' psychological distress: effective local governments alleviate worries about medical expenses and elder care, and thereby reduce psychological distress. The findings indicate that, to reduce residents' worries and psychological distress during the process of rural-urban transition, it is essential to improve local government effectiveness, particularly in promoting residents' access to the social security system. Beyond demonstrating how local government effectiveness matters for residents' psychological distress, our research also illustrates how to properly model locational parameters in analyses of individual well-being.
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