According to the “dual-carbon” goal, the solution to achieving balanced regional development and industrial structural optimization while promoting sustainable development goals lies in the synergistic evolution mechanism of carbon emission efficiency and green technological innovation. Using provincial panel data from China from 2000 to 2022, this study calculates industrial structural optimization coefficients for the “advanced,” “rationalization,” and “ecology” dimensions. The impact of green technological innovation on industrial structural optimization is experimentally explored using panel regression, threshold effect, and mediating effect methodologies, based on the constraint perspective of carbon emission efficiency. The findings show that (1) the optimization of the regional industrial structure is successfully driven by both carbon emission efficiency and green technological innovation; (2) the impact of green technological innovation on industrial structural optimization is positively regulated by carbon emission efficiency, which also helps to achieve sustainable economic transformation; and (3) this moderating effect exhibits significant regional heterogeneity and U-shaped nonlinear characteristics, in the order of “central > west > east”. This study reveals how green technological innovation affects industrial structural optimization under the constraint of carbon emission efficiency. It offers reference recommendations for the creation of sustainable development policies in the future.

Green technology innovation is one of the driving forces of industrial structure upgrading. This innovation is thought to be related to environmental regulation. The study uses panel data for 30 Chinese provinces and cities from 2009 to 2020 and presents a comprehensive research-based explanation of how environmental regulations impact green innovation. This study employs the spatial Durbin model to analyze the spillover effect of the region. The results show that the total impact of environmental regulations is 0.223%, of which the direct effect is 0.099%. This impact includes the effects of both formal and informal environmental regulation. It indicates that ecological regulations significantly enhance green technology innovation. Furthermore, the spatial spillover effect is significantly positive at the 1% level with a coefficient of 0.124. Such spillover effects represent a learning effect of regional environmental regulation. Based on the results, the study suggests a few policy measures based on the detailed outcomes.

The relationship between natural resource development and sustainable development has long been a focus in academia. In the context of a new global economic cooperation system, many scholars argue that such cooperation can lead to a “resource curse” effect in partner countries, hindering their sustainable development. This study analyzed panel data from 64 countries from 2008 to 2020, using the Belt and Road Initiative as a representative of multilateral economic cooperation (MEC) policies. The aim was to examine the actual impact of multilateral economic cooperation on the sustainable development levels of partner countries and to explore the underlying mechanisms influencing these outcomes. First, we measured and identified the sustainable development index (SDI) under natural resource development schemes and the “resource curse” effect in these countries. Then, we employed a double machine learning approach to evaluate the policy effects of MEC on sustainable resource development. We constructed an interactive double machine learning model to examine and validate the specific mechanisms of resource development effects. The results indicate that the level of sustainable resource development in MEC countries is relatively low, and a “resource curse” effect already exists. However, participating in MEC suppresses this “curse” effect. By promoting innovation cooperation, institutional improvement, structural optimization, trade openness, and pollution reduction, MEC effectively enhances the sustainable development levels of partner countries.

In the context of the carbon peaking and carbon neutrality policy, promoting the green and low-carbon transformation of the economic system is a major strategic arrangement for high-quality development, and green credit, as an important measure to promote sustainable economic development, has received widespread attention from all walks of life for its impact on carbon emissions. This paper examines the impact of green credit policies on carbon emissions using provincial panel data in China from 2011 to 2020. The empirical results show that green credit has a significant dampening effect on carbon emissions. This carbon reduction effect can be achieved through technological innovation in related industries and the alleviation of financial capital mismatch. The results of the heterogeneity test show that, under the regional differences, the green credit in the eastern and western regions is more effective in curbing carbon emissions than those in the central region; under the differences in energy consumption structure, the green credit in the low-coal-consuming regions is more effective in curbing carbon emissions than those in the high-coal-consuming regions. In addition, the results of the robustness tests conducted after replacing the indicators of the explanatory variables and core explanatory variables remain robust. On this basis, this paper provides some references on how to improve the carbon reduction effect of green credit.