Dynamic Evolution, Spatial Differences, and Driving Factors of China’s Provincial Digital Economy

Run Luo and Nianxing Zhou
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Run Luo: School of Geography Science, Nanjing Normal University, Nanjing 210023, China
Nianxing Zhou: School of Geography Science, Nanjing Normal University, Nanjing 210023, China

Sustainability, 2022, vol. 14, issue 15, 1-16

Abstract: The digital economy is critical to national economic growth and high-quality economic development. It is theoretically and practically significant to measure the development level and spatial differences in the digital economy to promote the construction of a digital China. This study constructed a digital economy evaluation index and analyzed the dynamic evolution, spatial differences, and driving factors of China’s provincial digital economy from 2011 to 2020 using a spatial Markov chain, the Dagum Gini coefficient, and geographical detector methods. The results demonstrated that China’s provincial digital economy grew from 2011 to 2020. The spatial distribution of the digital economy was high in eastern provinces and municipalities such as Beijing, Shanghai, Guangdong, Jiangsu, and Zhejiang, and low in central and western provinces and autonomous regions. The probability of upward transfer in developing China’s provincial digital economy was greater than that of preserving the original state, and China’s provincial digital economy has great potential for development. A region with a medium-high level in the digital economy is more likely to achieve high-level development when neighboring regions are characterized by a medium-high or high level of digital economy development, as the spillover effects from the neighbors may be strongly favorable and the region takes advantage of its developed surroundings. There were significant spatial differences in the development of China’s provincial digital economy, caused primarily by inter-regional differences. The spatial differentiation of China’s provincial digital economy was caused by the interaction of multiple factors, led by economic conditions and R&D expenditure.

Keywords: digital economy; dynamic evolution; spatial differences; driving factors; spatial Markov chain; Dagum Gini coefficient; geographical detector (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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