Convergence Analysis of Cross-Province Human Well-Being in China: A Spatiotemporal Perspective

Abstract

China’s economy has been experiencing a new development mode that emphasizes an environmentally friendly green economy and high living standards. The concept of human well-being has become increasingly prominent in recent years to replace GDP per capita as an important indicator for evaluating happiness. In the context of the green economy, it is of great significance to incorporate environmental indicators for evaluating human well-being. To this end, this paper constructs a new human well-being evaluation indicator system including environmental sustainability, and then evaluates the well-being levels of 30 provinces in China from 2011 to 2020 using a comprehensive evaluation method. Then, various statistical methods and visualization methods are used to deeply analyze the spatiotemporal changes in the well-being scores of Chinese provinces during the sample period. Finally, the spatial convergence model was used to verify if cross-province well-being scores would converge to a common steady state. The findings are as follows. (1) The scores of the environmental sustainability subsystem greatly vary from province to province. This is because the local governments have attached great importance to the construction of green ecological civilization in recent years, thus increasing the investment in protecting the ecological environment. (2) From temporal dimensions, overall human well-being scores of 30 provinces slightly increased year after year. In geography, eastern provinces have the highest human well-being scores, followed by northeast, northwest, and southwest provinces. (3) In terms of the scores of the four subsystems, we find that nearly all provinces have their advantages and disadvantages. (4) From the results of the spatial convergence models, both absolute and conditional β convergence have been verified, indicating that the human well-being of all provinces will converge to the common steady state in the future.