Analysis of the Spatiotemporal Evolution and Driving Factors of China’s Digital Economy Development Based on ESDA and GM-GWR Model

Abstract

Research on the geographical aspects of the digital economy is valuable. We base our study on 10 consecutive years of panel data from 2011–2020 for 31 Chinese provinces. First, we measure the Digital Economy Index using the entropy weight method and analyze its spatiotemporal heterogeneity characteristics using the Exploratory Spatial Data Analysis (ESDA) method. Next, the Grey Model (GM) is utilized to conduct time series predictions of each geographical unit. Finally, we use the GM predicted values and Geographic Weighted Regression (GWR) model to explore the spatial heterogeneity effects of external factors. This study finds that: (1) The overall development shows a trend of vigorous growth, with significant spatial heterogeneity. The gradient difference shows a decreasing trend from the eastern coastal areas to the western inland areas. (2) There is an obvious “digital divide” and a “Matthew effect” in regional development, with agglomeration and spillover effects gradually increasing. (3) Considering the influencing factors, technological progress has a positive impact, and the technology-oriented spatial spillover is obvious, showing a pattern of high in the south and low in the north. The industrial structure is significantly positive, and increases year by year, showing a distribution characteristic of high in the north and low in the south in general, with a clear effect of reducing the “bipolar” distribution. The marginal effects of government support and foreign investment are reduced and there is spatial non-stationarity. This study provides a scientific basis for further research on the spatial development of the digital economy.