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Improving total factor productivity (TFP) is essential to achieving high‐quality and sustainable economic development. The existing literature mainly focuses on the impact of traditional infrastructure on TFP but generally ignores the role of new digital infrastructure in TFP and does not test impact mechanisms and whether there is heterogeneity in effects. Using panel data of 30 regions in China from 2006 to 2017, this paper analyzes the impact of new digital infrastructure on TFP and its mechanisms. The results are as follows: (1) New digital infrastructure can significantly improve regional TFP. After the robustness test, the results still support the findings. (2) New digital infrastructure can promote technological innovation, optimize factor allocation, and achieve economies of scale, thus improving TFP. (3) Further analysis shows that the positive effect of new digital infrastructure on TFP shows significant heterogeneity. In regions with high economic development levels, high research and development (R&D) levels, and high traditional infrastructure development levels, the positive effect of new digital infrastructure on TFP is more obvious. These findings not only enrich the literature on digital infrastructure and economic growth but also serve as a reference for governmental departments as they optimize their strategy for developing digital infrastructure and realizing sustainable economic development.

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Carbon peak and carbon neutrality are important development goals for China so the issue of carbon emissions from cultural and related manufacturing has received increasing attention. The objective of this paper is to clearly present the current status and historical evolution of the carbon emissions and carbon emissions efficiency of cultural and related manufacturing (CEECM) in 17 provinces in the Yangtze River Basin in China from 2012 to 2019. This paper mainly uses two research methods: the super-efficiency DEA analysis method is used to measure the CEECM in the various regions and the Theil index analysis method is used to study the regional differences in the CEECM in these regions. It was found that there were large differences in the carbon emissions of cultural and related manufacturing in the various regions and the energy consumption also varied greatly. In 2019, Guangdong province had the highest amount of carbon emissions from cultural and related manufacturing industries in the Yangtze River Basin, followed by Jiangsu and Fujian. On the whole, the eastern part of the Yangtze River Basin had more emissions than the central and western parts. From 2012 to 2019, the carbon emissions of cultural and related manufacturing industries in the Yangtze River Basin showed an overall downward trend. In 2019, the city with the highest CEECM in the Yangtze River Basin was Shanghai, followed by Fujian and Sichuan. From 2012 to 2019, the average CEECM for the whole Yangtze River basin, the provinces of the main stream of the Yangtze River, and the provinces of the tributaries of the Yangtze River all showed a downward trend. According to the calculation, the average value of the Theil index from 2012 to 2019 was 0.905, which indicated that the regional differences in the CEECM among the provinces in the Yangtze River Basin were large. From 2012 to 2019, the regional differences in the CEECM for the Yangtze River basin as a whole, the provinces of the main stream of the Yangtze River, and the provinces of the tributaries of the Yangtze River all showed an inverted U-shaped development trend. The regional differences in the CEECM in 2013 were the largest and then showed a decreasing trend. After 2015, the fluctuation of the differences was relatively flat.

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