中国数字经济发展水平测度与时空演变分析——基于2013年至2020年30个省份的面板数据
Measurement of the Development Level of China’s Digital Economy and Analysis of Its Spatial and Temporal Evolution—Based on Panel Data for 30 Provinces from 2013 to 2020

文章基于2013年~2020年30个省份的面板数据，构建了中国数字经济发展水平指标体系，利用纵横向拉开档次法对中国数字经济发展水平进行了统计测度。结合测度结果得知，全国以及东、中、西部三大区域数字经济发展水平均呈稳步上升态势，三大地区间数字经济发展存在差异，呈现出东部 > 中部 > 西部的发展格局。运用Dagum基尼系数分析得出，中国各省份数字经济发展存在差距，差异主要来源于区域间差异。绘制核密度估计曲线分析得知，全国以及三大地区的数字经济发展水平均呈增长态势，但表现出较为明显的空间差异。利用莫兰指数分析可知，中国数字经济发展具有明显的空间集聚性且空间集聚相对稳定。利用传统与空间结合的马尔科夫链分析，结果显示，发展水平较高的省份对与其相邻的低水平省份具有模范带动作用，且发展水平越高，带动作用越明显。最终得出七条结论与四条建议，对于中国数字经济发展水平的提升具有重要意义。
In this paper, based on the panel data of 30 provinces from 2013 to 2020, the index system of China’s digital economy development level is constructed, and the vertical and horizontal slotting method is used to statistically measure China’s digital economy development level. Combined with the measurement results, it is learned that the development level of digital economy in the whole country as well as the three major regions of East, Central and West has shown a steady increase, and there are differences in the development of digital economy among the three major regions, presenting a development pattern of East > Central > West. Using Dagum’s Gini coefficient analysis, it is concluded that there are gaps in the development of digital economy in Chinese provinces, and the differences mainly come from inter-regional differences. Drawing the kernel density estimation curve analysis shows that the level of digital economy development in the whole country as well as the three major regions is all in a growth trend, but show more obvious spatial differences. The analysis of Moran index shows that China’s digital economy development has obvious spatial agglomeration and the spatial agglomeration is relatively stable. Using the traditional and spatial combination of Markov chain analysis, the results show that provinces with higher levels of development have an exemplary driving effect on their neighboring provinces with lower levels of development, and the higher the level of development, the more obvious the driving effect. Finally, seven conclusions and four recommendations are drawn, which are of great significance for the improvement of China’s digital economy development level.