关键词: 数据要素流通, 区域差异, 动态演进, Dagum基尼系数, 方差分解, 核密度估计, Moran指数

Abstract: Data circulation is the key to promote the transformation of data into production factors, and its circulation level is the core index to measure the marketization allocation efficiency of data elements. Based on resource endowment theory and technology potential energy theory, this paper constructs an index system for evaluating the circulation level of data elements, measures the circulation level of data elements in various regions of China from 2019 to 2024, and deeply analyzes the regional differences, structural causes and spatio-temporal dynamic evolution characteristics by using Dagum Gini coefficient, variance decomposition method, kernel density estimation and Moran index. The conclusions indicate that: The circulation level of data elements in China generally presents a right-leaning distribution pattern, with obvious regional gradient characteristics of "eastern leading, central accelerating catch-up, western and northeast lagging"; the overall difference of data elements circulation level in each region is convergent, among which regional difference is the main source of overall difference, and the eastern region contributes the most to regional difference; there is obvious spatial positive aggregation characteristics in the circulation level of data elements in China, and the "low-low" aggregation characteristics in western regions are dominant. The conclusion reveals the regional differences and evolution characteristics of data elements circulation level in China, which has important value for realizing the deep circulation interaction of data elements and the integration of national data market.

Key words: Circulation of data elements, Regional differences, Dynamic evolution, Dagum Gini coefficient, Variance decomposition, Kernel density estimation, Moran index