This paper focuses on the total factor productivity (TFP) and high-quality economic development in China by examining 11 Chinese provinces and cities in the Yangtze River Economic Belt from 2007 to 2018. We use the Solow residual method to calculate the TFP growth rate of the 11 provinces and cities. Based on the panel data, we have analyzed the influencing factors of TFP theoretically and empirically from the overall region and upstream region, and midstream region and downstream region, respectively. The regression results show that: (1) The whole characteristics generally show the TFP growth trend of the upstream region, midstream region and downstream region are consistent with that of the overall region, and the growth rate of TFP slows down gradually. Meanwhile the differences in TFP growth between the upstream region, midstream region and downstream region show an increase at first and then a decrease. (2) Regarding the influencing factors, there are differences in the direction and extent of the impact of each factor such as the level of openness, R&D investment, industrial structure, government expenditure and human capital on the TFP of the overall region, upstream region, midstream region and downstream region. (3) Based on the results of the theoretical and empirical analysis, we have proposed a series of measures for the sustainable high-quality development of the Yangtze River Economic Belt.

Given the simultaneous background of growing ‘dual-carbon’ ambitions and the rapid expansion of the digital economy, it is critical to understand the mechanisms by which the digital economy influences carbon emissions. This understanding is critical for overcoming regional green development gaps and facilitating the implementation of the national ‘dual-carbon’ policy. Using panel data from 11 prefecture-level cities in Zhejiang Province from 2012 to 2023, this study employs a two-way fixed-effects model and a mediation effect model for empirical analyses to evaluate the carbon emission reduction effect of Zhejiang’s digital economy objectively. The findings show that the digital economy directly cuts carbon emissions and has a spatial spillover effect, while indirectly facilitating emission reduction via the intermediary pathway of innovation efficiency. However, the mediating effect of industrial structure alteration is statistically insignificant. Regional heterogeneity research suggests that carbon reduction impacts are more prominent in economically developed cities (e.g., Hangzhou and Ningbo), whereas the effects are modest in less-developed areas, despite the digital economy’s potential for reduction. This study provides an empirical framework for local governments to establish distinct carbon reduction policies, as well as practical insights into how to align the development of digital economy with low-carbon goals.