Under the Belt and Road Initiative (BRI), promoting green innovation in enterprises has been the central focus of the developmental strategy for China and countries along the Belt and Road to ensure sustainable development in line with the UN Sustainable Development Goals (SDGs) related to the environment and development. This paper examines the driving factors and heterogeneous mechanisms of the BRI in green technology innovation, especially in collaborative vs. independent innovation modes, utilizing a multi-period difference-in-difference model (DID) and micro-level panel data of Chinese listed enterprises spanning from 2007 to 2021. We find that the BRI has significantly stimulated the number of green innovations of participating enterprises, primarily through the adoption of collaborative innovation mode, and the BRI policies are more likely to induce green innovation behavior of enterprises with high research and development (R&D), high quality of environmental information disclosure, and non-state-owned enterprises (SOEs), as well as in heavy-polluting industries. The implementation of the BRI has led to increased support from the government, financial institutions, and scientific research organizations to the participating enterprises, which helps alleviate their financial constraints and enhance patent transformation efficiency, and thus facilitate green innovation. These results are robust across different regression specifications. This study contributes to the existing literature on BRI’s environmental impact and green innovation with firm-level evidence, and has important policy implications for the Chinese government when promoting green innovation and internationalization of Chinese enterprises.

As a major destination of waste products, China implemented the National Sword Policy (NSP) to regulate the high pollution of waste imports. The existing literature primarily focuses on the motivations behind China’s waste imports and the policy implications of the NSP on China’s waste imports and the global recycling market. This study innovatively focuses on the extensive, intensive, price, and quantity marginal effects of the NSP on China’s waste imports using a difference-in-differences (DID) approach with 26 categories of waste products for 150 countries and regions from 2007 to 2021. The findings indicate that: (1) The NSP has led to declines in the intensive and quantity margins of regulated waste imports, while the price margin has increased. (2) In the years following the implementation of the NSP, the impacts continued to intensify. (3) The NSP has reduced the motivation for exporters to export highly polluting waste to China in search of a “Pollution Haven”. (4) Orientations implementing policies that place the responsibility for products’ environmental impact and encourage waste sorting can effectively alleviate the inhibitory effects of the NSP. These results suggest that the Chinese government needs to strengthen the control of high-polluting and low-value product imports. Waste-exporting countries should encourage enterprises to take responsibility for the entire lifecycle of products and promote waste sorting and treatment facilities. Enterprises should strengthen the environmental impact assessment of the entire product lifecycle and consider materials that are easy to sort and recycle.

Motivations behind a country’s importation of waste are categorized into the pollution haven hypothesis (PHH) and the resource hunting hypothesis (RHH). The importation of wastes can lead to environmental sustainability concerns, requiring governments to intervene when the market fails to reduce the negative externalities by strengthening and implementing environmental regulations. Motivated by China’s position within a rapidly growing but environmentally damaging sector of trade, this paper has three goals: (1) to classify the primary hypothesis that governs China’s flow of traded wastes; (2) to verify the heterogeneous impact of the pollution paradise motivation and resource demand motivation of waste imports from developed and developing countries, and across industries; (3) to assess the impact of domestic environmental regulations on the motives behind China’s waste imports. Using 28 imported waste-varieties from 20 of China’s major trade partners across 24 years, findings indicate that the flow of Chinese waste imports is relatively unresponsive under the pollution haven effect. However, the resource hunting effect from developing countries is significantly greater than what originates from developed countries, despite the laws of 2011 and 2017 established to restrict resource hunting activities. These results have important implications for improving the efficiency of China’s waste sorting and recycling systems.

This study empirically examines the impact of the Green Credit Guidelines Policy (GCGP) on carbon emission intensity in China’s manufacturing sector. Using a difference-in-differences (DID) model and panel data from A-share listed firms from 2008 to 2023, we treat the issuance of the GCGP in 2012 as a quasi-natural experiment. The results demonstrate that the GCGP significantly reduces the carbon emission intensity of manufacturing enterprises. Further analysis reveals that this effect operates through both macro and micro-level mechanisms. At the macro level, green credit promotes industrial structure upgrading and enhances energy utilization efficiency. At the micro level, it improves investment efficiency and the quality of environmental information disclosure, thereby supporting carbon reduction. Heterogeneity analysis shows that the carbon-reducing effect of green credit is more pronounced in firms with strong internal governance, low financing constraints, and a high degree of digital transformation. Additionally, the policy is more effective in regions with stricter environmental regulations, higher financial development, and a stronger orientation toward economically developed areas. These findings offer important theoretical insights and policy implications, underscoring the role of green finance in achieving low-carbon transformation and supporting sustainable development goals.

The rise of smart cities as systemic eco-innovations has leveraged advanced digital technologies to support green development and reduce carbon emission intensity in manufacturing. Using data on green technology innovations of A-share listed firms in Shanghai and Shenzhen from 2007 to 2022, this study applies a multi-period difference-in-differences design combined with a double machine learning method to assess how smart city pilot programmes influence enterprises’ low-carbon transitions. We find that (1) Smart city pilot programmes significantly increase the quantity, quality, and independence of green patenting, and these effects remain robust under alternative specifications; (2) mediation analysis shows that the pilots improve enterprise’ access to financial resources and strengthen external digital monitoring, which, in turn, enhances environmental disclosure and stimulates substantive green innovation; and (3) heterogeneity tests reveal that policy effects are strongest in regions with weaker environmental regulation, among firms with lower research and development (R&D) intensity, and in pollution-intensive industries, highlighting the contexts in which smart city initiatives are most effective. These findings provide empirically grounded insights into the contextual effectiveness of the smart city pilot and offer concrete evidence to inform its broader adoption and replication.