Measurement, spatial differences and driving effects of well-being levels in China.

As the largest developing country, China has accumulated enormous material wealth since its reform and opening-up policy. How to effectively evaluate the level of well-being in China has become a meaningful research endeavor. Using the entropy method, Dagum Gini coefficient and Logarithmic Mean Divisia Index (LMDI) decomposition methods, the study examines the spatial and temporal distribution characteristics, spatial differences and driving effects of provincial well-being levels from 2007 to 2020. The results of this study suggest that the level of well-being as a whole, as well as in the eastern, central and western regions increased significantly over the period, with an "east-to-west decreasing" distribution in China. In terms of the pattern of inter-provincial distribution, although the level of well-being in the central and western regions has improved at a faster rate, most provinces in the eastern region have always been among the leading teams on the path of livelihood development. There is still enormous room for improvement in the level of well-being in the central and western provinces. The overall differences in the development of well-being in China, as well as intra-regional and inter-regional differences among the three major regions, showed a narrowing trend. Intra-regional differences in the development of well-being are greatest in the western region, and inter-regional differences in the development of well-being are greatest in the eastern and western regions. Inter-regional differences are the main reason for the spatial differences in well-being among China's provinces. The combination of economic, social, ecological and technological effects has led to a gradual increase in the level of well-being over the sample period. Among them, economic, social and technological effects have a clear positive driving effect on the increase of well-being levels, while ecological effect have a certain negative driving influence.