China's multi-scale common prosperity dataset from 2000 to 2020

Common prosperity is one of the basic connotations of Chinese path to modernization, and geography has significant disciplinary advantages in the study of this topic. In response to the current research status of incomplete measurement methods for common prosperity and insufficient regional empirical research, this article improves the measurement method system based on geographical comprehensiveness, regionalism, processuality, and multi-agent characteristics, and conducts empirical analysis of multi-scale, multi-dimensional, and long-term time series. Research has found that: ① Common prosperity can be deconstructed from two aspects: prosperity and common prosperity. The level of prosperity is manifested as the comprehensive development level of the economy, society, environment, infrastructure, and other dimensions, while the level of common prosperity is manifested as the regional gap and multidimensional differentiation of the comprehensive development level. ② Under the background of regional coordinated development strategy, the level of common prosperity in China's regions continues to improve, manifested as a dual growth of prosperity and common level, but there is a certain degree of regional and dimensional heterogeneity. Among them, the national level of prosperity and common level have significantly improved, and the pattern of regional prosperity has undergone significant reshaping with increasingly obvious functional characteristics of the main body. The gap between regions has become more prominent compared to within regions, and the overall stability of the provincial prosperity pattern has dimensional trends. ③ The evolution of China's common prosperity has significant temporal and spatial correlations, with a strong response to the level of prosperity. The spatial pattern of agglomeration based common prosperity is gradually emerging, and the characteristics of prosperity dominated common prosperity are becoming increasingly prominent. The process, processing methods or steps, equipment and tools used to generate the dataset are associated with the paper.