Urban climate adaptability and green total-factor productivity: Evidence from double dual machine learning and differences-in-differences techniques.

Climate change has increasingly become a significant challenge to sustainable socio-economic development, and climate adaptation is a key issue that relevant research focuses on regional sustainable development models. By employing panel data between 2007 and 2020 from 284 Chinese prefecture-level cities, this study adopts quasi-experimental methods, including a difference-in-differences design and double dual machine learning model, to study the impact of climate adaptability on green regional sustainable development. Empirical results confirm that the pilot policy of building climate-resilient cities significantly improves urban green total-factor productivity. Difference-in-difference models (derived from entropy-weight and propensity score matching) and double dual learning models also support the improving effect of regional green total-factor productivity after policy intervention. The digital economy has strengthened the green development effect of pilot policies for building climate-adaptive cities. In addition, policy interventions to build climate-adaptive cities promote green urban development by optimizing industrial development structures and enhancing economic growth resilience. In addition, climate adaptability can also attract highly skilled talent and high-quality enterprises, facilitate science and technological progress in urban areas, and thus promoting the green development of cities in China. This study objectively evaluates the effects of climate policies and provides insights for global adaptation to climate change and optimization of public policies.

The challenges of maturity mismatch in investment and financing for sustainable development of carbon-intensive enterprises.

To contribute to the research on the role of financial activities in corporate development, this study addresses the critical issue of short-term debt financing for long-term investment (SDFLI) and its impact on the sustainable development of carbon-intensive enterprises in China. By analyzing panel data from the A-share listed carbon-intensive enterprises in China spanning from 2010 to 2021, this study aims to shed light on the significance of this phenomenon and its implications. The empirical findings reveal the existence of a maturity mismatch between investment and financing in carbon-intensive enterprises, which exerts a significant negative impact on total factor productivity (TFP) and poses challenges to their sustainable development. Furthermore, the adverse effects of maturity mismatches vary across different types of enterprises based on factors such as ownership, industry characteristics, financing constraints, and internal controls. The results of the mediation effect model demonstrate that maturity mismatch hampers the sustainable development of carbon-intensive enterprises by reducing investment efficiency and increasing agency costs. Additionally, the moderating role of innovation in carbon-intensive enterprises between maturity mismatch and sustainable development is also examined. This research provides insights to establish policies for facilitating sustainable development in carbon-intensive enterprises.

Place-Based Policies and Carbon Emission Efficiency: Quasi-Experiment in China's Old Revolutionary Base Areas.

Regional imbalance is a typical feature of economic and social development in China, and place-based policies aimed at promoting balanced regional development may bring challenges to low-carbon goals. This study uses the panel data of China's prefecture-level cities from 2003 to 2019 to investigate the impact of place-based policies on carbon emission efficiency using a quasi-experimental method. Results indicate that place-based policies significantly reduce the regional total-factor carbon emission efficiency. The difference-in-differences method based on propensity score matching and entropy balancing matching consistently supports the finding that carbon emission efficiency decreases after policy intervention. Place-based policies lead to a significant decline in capital allocation efficiency but have an insignificant impact on labor allocation efficiency. Moreover, place-based policies result in the expansion of carbon-intensive industries but hinder the progress of the financial technology of financial institutions. Nevertheless, place-based policies do not lead to the deterioration of environmental quality. Among the advantages of these policies are the significant promotion of regional digitization and increased fiscal expenditure on science and technology. Political promotion, carbon regulation, trade policies, and other conditional factors may be optimally designed to promote low-carbon development in the old revolutionary areas.

Spatial spillover effect of the synergistic development of inward and outward foreign direct investment on ecological well-being performance in China.

Inward and outward foreign direct investment (FDI) can promote a country's economic growth, but the effect of inward and outward FDI on regional ecological well-being performance (EWP) is uncertain. Using the data of 30 Chinese provinces from 2004 to 2019, this study employs the spatial Dubin model to examine the spatial spillover effects of synergistic development of inward and outward FDI on regional ecological well-being performance and their mediating mechanisms. The result shows that the synergistic development of inward and outward FDI can significantly improve regional EWP and imply a positive spatial spillover effect. The dynamic effect analysis indicates that synergistic development of inward and outward FDI has a lag effect on the improvement of regional EWP. The mechanism test found that the synergistic development of inward and outward FDI can enhance the EWP of the region and the spatially related regions by promoting the rationalization, upgrading and technological innovation of the industrial structure. These findings have some insights into improving global ecological well-being in an open economy.

Increasing short-term lending for long-term investment under environmental pressure: evidence from China's energy-intensive firms.

To improve environmental quality and reduce pollutant emissions, China enacted the Environmental Protection Tax Law (EPTL) in 2018, leading to increase environmental pressure. Based on the data of energy-intensive firms listed in China's A-share market, this study examines firms' investment and financing behavior, increasing the short-term loans for long-term investment. Using the Difference-In-Differences (DID) method, empirical evidence supports the idea that environmental pressure causes energy-intensive firms to increase short-term lending for long-term investment (SLLI). Specifically, environmental pressure leads firms to increase long-term investment activities, such as fixed assets, environmental protection, and innovation. In contrast, long-term loans decrease, forcing firms to use short-term loans for long-term investments. Affected by rising environmental pressure, firms with low financing constraints are more likely to use short-term loans instead of long-term loans to support long-term investment activities, while firms with high financing constraints cannot obtain short-term loans. Our findings provide critical insights for promoting coordination between financial and environmental policies.

Nonlinear and spatial spillover effects of the digital economy on green total factor energy efficiency: evidence from 281 cities in China.

Although the digital economy has become a new driving force for development worldwide, it is still unclear how digital economy development affects green total factor energy efficiency (GTFEE). Using panel data from 281 prefecture-level cities in China from 2003 to 2018, this study empirically analyzes the effect of digital economy development on GTFEE by adopting a dynamic panel model, a mediation effect model, a dynamic threshold panel model, and a spatial Durbin model. The empirical results show that digital economy development has a significantly negative direct effect on GTFEE. The digital economy can impact GTFEE by the mechanisms of electrification, hollowing out of industrial scale, and hollowing out of industrial efficiency. Neither innovation nor environmental regulations significantly change this negative impact. The dynamic threshold panel model shows a nonlinear relationship between digital economy development and GTFEE, which indicates that the effect of digital economy development on GTFEE significantly inverts from negative to positive as the digital economy develops. In addition, GTFEE has a significantly positive spatial correlation, and the digital economy has a positive spatial spillover effect on GTFEE.

The effects of the environmental protection tax law on heavily polluting firms in China.

In 2016, China implemented an environmental protection tax (EPTL2016) to promote the transformation and upgrading of heavily polluting industries through tax leverage. Using panel data of China's listed companies, this study assesses the treatment effects of the EPTL2016 on the transformation and upgrading of heavily polluting firms by incorporating the intermediary role of the financial market. The empirical findings show that the EPTL2016 significantly reduced the innovation investment and productivity of heavily polluting firms but had no significant effect on fixed-asset investment. Additionally, EPTL2016 reduced the supply of bank loans to heavily polluting firms and increased the value of growth options for private enterprises and the efficiency of the supply of long-term loans to heavily polluting firms. Although the environmental policy of EPTL2016 benefits the transformation and upgrading of heavily polluting industries in many aspects, it generally hinders the industrial upgrading because of the reduction of bank loans.

Impact of China's waste import policy on the scrap copper recovery pattern and environmental benefits.

The international trade weight of scrap copper has exceeded 6 million tons annually over the past two decades. China introduced the "National Sword" policy in 2017, which brought uncertainty to the international recycling of scrap copper. We use the international scrap copper trade figures from 1998 to 2019 in UN Comtrade, and seek to analyze the impact of China's import ban by setting up a difference-in-differences (DID) model based on the gravity model. The results show that 1) The ban has promoted the development of regional trade and improved the quality of scrap copper in international trade. The unit value of imported scrap copper in China has risen by 58%. 2) China's import ban has reduced the import weight of scrap copper by 68.6% and its value by 44.4% without the influence of other socioeconomic factors. 3) China's import of copper scrap is concentrated in coastal provinces. Guangdong Province has been most heavily affected. The imports of low-quality copper scrap in Guangdong have decreased by 94%. 4) The import ban reduced the environmental impact in China by 36.6%, but the global environmental impact has increased because of the gap in recycling technology, especially in developing countries. These discoveries will be beneficial to predict the future of international scrap copper recovery, and help rule makers formulate trade and environmental policies.

Digitalization and environment: how does ICT affect enterprise environmental performance?

Despite the increasing use of digital technology in industrial production, how industrial digitalization affects the environmental performance of production activities remains unclear. This research contributes to the literature on the relationship between industrial digitalization and enterprise environmental performance by employing a large sample of Chinese manufacturing enterprises. Results indicate that the environmental performance of manufacturing enterprises has been significantly improved in the process of industrial digital transformation. Structural and technology effects are the transmission channels; additionally, structural effect is the main contributor to the positive environmental effects of information and communications technology (ICT) penetration. Industrial digitalization reduces the production scale of heavy-polluting enterprises and improves product innovation and green total factor productivity, but it has an insignificant effect on total factor productivity. Moreover, industrial digitalization improves enterprise environmental performance by introducing front-end cleaner production technologies, rather than by increasing pipe-end pollutant treatment facilities.

Impact of fiscal decentralization on firm environmental performance: evidence from a county-level fiscal reform in China.

To promote county economic prosperity and social development, China enacted a fiscal reform known as "province governing county" (PGC) in the early 2000s. Using the difference-in-differences (DID) method and a massive sample of enterprises from 2003 to 2011, this study investigates the effect of PGC reform on firm environmental performance. The results show that enterprises in reformed counties have significantly decreased their pollution intensity since the fiscal reform. Our research reveals that the environmental effects of fiscal decentralization are related to changes in the political assessment metrics of local officials. It also shows that PGC fiscal reform has a significant positive effect on the environmental performance of large, small, and micro enterprises. Furthermore, it suggests that PGC fiscal reform benefits the environmental performance due to the informational advantages of county governments. In terms of environmental governance, although local governments have an information advantage in the allocation of green fiscal funds, well-designed mechanisms are needed to strengthen their motivation.