Spatial pattern of the Chinese economy and spatial heterogeneity of its influential factors: An empirical study based on nighttime lighting data

China’s economy has developed rapidly since its reform and opening-up. However, the different rates of development in various places due to location and policies have led to significant economic differences. Based on the nighttime lighting data of 281 municipal spatial units in China from 2013 to 2021, this study uses spatial autocorrelation, center of gravity shift, and standard deviation ellipse (SDE) analysis to examine the evolution of the spatial pattern of China’s municipal economy. Based on these, it uses a geographically weighted regression (GWR) model to explore the factors influencing the differences in China’s municipal economy and its spatial heterogeneity. The paper reveals the following results. First, China’s municipal economy as a whole shows a growing trend. Second, the SDE shows a “north-south” distribution pattern, and the concentration of China’s economic development has slightly increased, with a significant centripetal distribution. Third, spatial correlation shows spatial positive correlation, the degree of which is increasing, with strong spatial heterogeneity and regional agglomeration. Finally, measuring the influencing factors according to GWR, the industrial structure and education expenditure coefficients generally show a decreasing trend from the southeast coast to the northwest and inland due to the degree of transformation of industrial structure and the lagging effect of education expenditure on economic growth. Conversely, the innovation driver and urban area coefficients show a decreasing trend from the northwest inland to the southeast coast due to the law of diminishing marginal utility of innovation drivers and differences in urbanization development. Government expenditure coefficients show a higher trend in the East and a lower trend in the West due to policy favoritism and market development level. This research can serve as a theoretical reference for China to achieve high-quality development and move toward common prosperity.

Abstract licence: CC BY-NC-ND

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.