Impact of digital economy development on energy mismatch:Empirical data from prefecture-level and above cities in China

[Objective] In the context of increasingly serious resources and environmental problems, improving the energy mismatch has an important role in promoting the supply-side reforms in China and achieving the carbon peaking and carbon neutrality goals. [Methods] Based on the panel data of 284 prefecture-level and above cities in China from 2011 to 2019, the extension C-D function of the energy factors was used to calculate the degree of energy mismatch, and the digital economy development index was calculated using the entropy weight-TOPSIS dual method. This study also analyzed the linear and nonlinear correlations between the digital economic development and energy mismatch using the benchmark model, the threshold model, and the spatial econometric model. [Results] The results show that: (1) At the national level, the digital economy development index has a significant negative effect on the degree of local energy mismatch, and the results of heterogeneity tests by region are highly consistent with the benchmark regression results. Among them, the digital economy development in the central region of China can best improve the local energy mismatch, followed by the western region and the eastern region. (2) Under the condition of threshold constraints, urban spreads and foreign investment presented a significant single threshold feature, that is, in areas with higher urban spread and higher foreign investment, the more the digital economy development can improve the local energy mismatch. (3) In terms of spatial effects, the degree of energy mismatch is significantly positively correlated in space, and so is the digital economic development index. Due to the existence of spatial spillover effects, the digital economy development not only improved the local energy mismatch but also played an inhibitory role on the increase of the degree of energy mismatch factors in the surrounding areas. [Conclusion] When developing the digital economy in the future, we should not only adapt to local conditions, but also consider spatial correlations. Relevant recommendations were put forward in terms of strengthening infrastructure, improving regional linkages, and promoting the digital transformation of enterprises.