School of Urban and Regional Science, Shanghai University of Finance and Economics, Shanghai, China.
School of Economics, Nanjing University of Finance and Economics, Jiangsu, Nanjing, China.
PLoS One. 2024 Oct 1;19(10):e0311291. doi: 10.1371/journal.pone.0311291. eCollection 2024.
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.
作为最大的发展中国家，中国自改革开放以来积累了巨大的物质财富。如何有效地评估中国的福祉水平已成为一项有意义的研究工作。本研究采用熵值法、Dagum基尼系数和对数平均迪氏指数（LMDI）分解方法，考察了 2007-2020 年中国省级福祉水平的时空分布特征、空间差异和驱动效应。研究结果表明，福祉水平整体以及东部、中部和西部地区在这一期间均显著提高，中国呈现出“东高西低”的分布格局。就省际分布格局而言，尽管中、西部地区福祉水平的提升速度较快，但东部地区的大多数省份始终处于民生发展道路上的领先队伍中。中、西部地区福祉水平仍有较大的提升空间。中国福祉发展的总体差异以及三大区域内部和区域间差异呈缩小趋势。西部区域福祉发展的区域内差异最大，东部和西部区域福祉发展的区域间差异最大。区域间差异是导致中国各省份福祉空间差异的主要原因。经济、社会、生态和技术效应的综合作用导致了样本期内福祉水平的逐步提高。其中，经济、社会和技术效应对福祉水平的提高具有明显的积极驱动作用，而生态效应则对福祉水平的提高具有一定的负向驱动作用。
