Assessing the determinants of corporate environmental investment: a machine learning approach

In recent years, experts and academics in the environmental management field have developed an interest in the factors and evaluation techniques that influence corporate environmental investment decisions. However, there are substantial differences between studies employing the most recent evaluation methodologies and those that use indicator systems. To explore the mechanisms that influence corporate environmental investment, this study investigated the determinants of environmental investment through the perspectives of firm, board, chair, and chief executive officer (CEO) characteristics using a machine learning approach. Based on a large-scale data sample from Chinese-listed companies, the results indicated that the extreme gradient boosting (XGBoost) model had an accuracy of up to 97.63%, thus performing the best. Additionally, the model that used SHapley Additive exPlanations (SHAP) to interpret XGBoost showed that a company's sales performance was the most important factor that influenced environmental investment, followed by CEO tenure, board independence, board gender diversity, chair academic experience, and the company's level of internationalization. Furthermore, when examining the sample of heavily polluting enterprises, sales, board gender diversity, CEO tenure, chair academic experience, board independence, and chair-CEO duality, all were found to play crucial roles in predicting environmental investment. Overall, this study aids in evaluating the factors that influence corporate environmental investment decisions and provides policymakers and practitioners with a machine learning approach for use when assessing these factors.

Can digital transformation change a firm's green innovation strategy? Evidence from China's heavily polluting industries

Enterprises are facing the superimposed challenges of digitalization and greening. The shift from reactive green technology innovation (RGT) to proactive green technology innovation (PGT) has special significance for sustainable economic development. Which strategies will companies choose? Can digital transformation (DT) motivate companies to transform their green innovation strategies? Enterprises' green innovation strategy choices must be explained with regard to digitalization. The purpose of this paper is to reveal how digitalization affects the choice of green innovation strategies and to provide a realistic basis for the sustainable development of heavily polluting enterprises. We formulated a "DT-capability-strategy" theoretical framework incorporating external constraints and internal attitudes to empirically test the microdata of 505 heavily polluting enterprises. The results show that: (1) DT can shift the heavily polluting enterprises' green innovation strategies from RGT to PGT. Endogenous tests and robustness tests support this conclusion. (2) A mechanism test shows that environmental regulations cannot significantly regulate a green innovation strategy. Only a company's capabilities and attitudes can influence PGT but their effects on RGT are not statistically significant. (3) The influence of DT on green innovation strategies shows multi-dimensional heterogeneity in the digital infrastructure, scale, and innovation level of the enterprise. The conclusions provide implications for enterprises to integrate their digital and green behaviors.

Catalyst or stumbling block: do green finance policies affect digital transformation of heavily polluting enterprises?

In recent years, China's green finance policies (GFP) have been successively introduced and continuously strengthened, and the effects have been widely observed. Using data from 2007 to 2021, this study employed a continuous double difference model to examine the impact of GFP on the digital transformation (DT) of heavily polluting enterprises (HPEs), as well as its underlying mechanisms. Our results show that GFP is a stumbling block rather than a catalyst that hinders the DT's enthusiasm of HPEs, and it plays an inhibitory role by increasing financing costs and financing constraints. Further analysis suggests that the GFP effect on HPEs exhibits asymmetry across regions and executive characteristics. HPEs in reform and innovation regions and with highly educated executive teams can mitigate the stumbling block effect. Our research offers fresh perspectives for enterprises to handle policy shocks, devise future development strategies, and establish a policy foundation for the advancement of green finance.

How does Fintech affect green innovation of Chinese heavily polluting enterprises? The mediating role of energy poverty

Corporate green innovation is the crucial driving force to promote green development and realize the construction goal of "Beautiful China." Meanwhile, the development of Fintech creates a more favorable external environment for corporate green innovation. Using the panel data of China's Digital Financial Inclusion Index and Energy Poverty Index at provincial level from 2011 to 2020, this paper studies the influence of Fintech on corporate green innovation by the evidence from Chinese heavily polluting enterprises. Based on stepwise regression, this paper further examines the mediating role of energy poverty, including energy consumption level, energy consumption capacity, and energy consumption structure, in the relationship between Fintech and corporate green innovation. The results show that (1) Fintech contributes to improving the level of green innovation of heavily polluting enterprises; (2) energy poverty acts as a mediator in the process of Fintech's influence on corporate green innovation; (3) Fintech can promote green innovation of heavily polluting enterprises by improving the level of regional energy consumption level, but it fails to influence corporate green innovation through energy consumption capacity and energy consumption structure. These results provide governments and companies with implications on facilitating corporate green innovation so as to further promote green development.

Does the greening of the tax system promote the green transformation of China's heavily polluting enterprises?

Climate change and pollution are the major environmental problems facing the world today. The emission of industrial pollution is not only related to the development of low carbon and green economy but also affects the ecological environment and climate change of human beings. The greening of the tax system is an important reform to help China's green development. From the perspective of internal green innovation and external legal pressure of heavily polluting enterprises, this paper discusses the impact mechanism of implementing the greening of the tax system on the green transformation of heavily polluting enterprises in China and uses DID model to conduct a quasi-natural experiment on the green transformation of heavily polluting enterprises in China. This paper finds that the implementation of the greening of the tax system has a significant impact on the green transformation of China's heavily polluting enterprises; the greening of the tax system policy realizes the "win-win" situation of green environmental governance and the development of heavily polluting enterprises through green technology innovation and forces heavily polluting enterprises in China to conduct environmental protection through the environmental legitimacy pressure. The effect of the greening of the tax system policy has obvious heterogeneity: The greening of the tax system has a more obvious improvement effect on heavily polluting enterprises with low and high market concentration. Compared with state-owned holding enterprises, non-state-owned holding enterprises are more significantly affected by the greening of the tax system. The positive impact of the greening of the tax system on the green transformation of heavily polluting enterprises is mainly reflected in enterprises with low financing costs, while it is not significant in enterprises with high financing costs. This paper enriches the research on the effect of green tax policy, explores solutions based on quasi-nature, and provides policy references for the green transformation of heavily polluting enterprises.

Green credit policy and the net value crash risks of fund holding heavily polluting enterprise stocks: a quasi-natural experiment

Based on the data of China's open-end stock funds and partial stock funds from 2009 to 2020, we take the implementation of green credit guidelines (GCG) as a quasi-natural experiment and investigate the impact of green credit policies on the net value crash risks of fund holding heavily polluting enterprise stocks. The results show that green credit policies will significantly increase the net value crash risks of fund holding heavily polluting enterprise stocks. Green credit policies increase the net value crash risks of fund holding heavily polluting enterprise stocks by increasing investor redemptions. Further tests show that better fund performance and higher portfolio concentration weaken the positive impact of green credit policies on the net value crash risks of fund holding heavily polluting enterprise stocks, and higher proportion of institutional investors strengthens the positive impact of green credit policies on the net value crash risks of fund holding heavily polluting enterprise stocks. This study supplements the literature on green credit policies and funds, and provides policy guidance for regulators.

China green credit policy and corporate green technology innovation: from the perspective of performance gap

Green credit policy is an essential external driver of green transformation for companies, while the performance gap is a vital decision-making foundation for innovative reform for managers. Both work together and influence corporate green technology innovation. Based on this, this research examines the influence of green credit on corporate green technology innovation under the assumptions of "cost compliance" and "innovation compensation" from the perspective of the performance gap. It shows that green credit policy inhibits green technology innovation among heavy polluting firms. Still, after considering the performance gap, the inhibiting effects are only found in firms with performance deficits. In contrast, green credit policy promotes green technology innovation when firms have a performance surplus. The heterogeneity analysis finds that the boosting effect of performance surplus is more significant in non-state, large-scale, and financially developed regions.

How does China's green credit policy affect the green innovation of heavily polluting enterprises? The perspective of substantive and strategic innovations

Green credit policy is an important practice to guide green development through the rational allocation of credit funds. Using the promulgation of the "Green Credit Guidelines" policy in China as a quasi-natural experiment, this paper examines the impact of green credit policy on heavily polluting enterprises' substantive and strategic green innovations within a difference-in-differences framework. We find that green credit policy improves the overall and strategic green innovations but has no significant effect on substantive green innovation of heavily polluting enterprises. Moreover, this effect is more prominent for state-owned enterprises and enterprises in regions with lower levels of financial development. Further analysis demonstrates that the green innovation induced by green credit policy increases heavily polluting enterprises' loan availability but does not improve heavily polluting enterprises' value. This paper sheds new light on the relationship between green credit policy and corporate green innovation in China as a transition economy.

Does the green credit policy affect the scale of corporate debt financing? Evidence from listed companies in heavy pollution industries in China

The current study constructs a quasi-natural experiment based on China's 2012 Green Credit Guidelines and develops a difference-in-difference model using the financial data of listed companies from 2006 to 2018 to conduct empirical testing. The results reveal that the green credit policy has significantly reduced the short-term and long-term debt financing of heavily polluting enterprises; however, the restrictions on short-term debt financing are insufficient. At the same time, the decline in operating performance brings financial penalty effects, among which state-owned, large-scale, and heavily polluting enterprises in high-emission areas have strong financial penalty effects. The green credit policy encourages heavy-polluting companies to increase R&D investment and increase fixed assets investments to obtain long-term credit support with short-term investment. Furthermore, it is found that the green credit policies have significantly restrained the scale of debt financing of heavily polluting companies. The Chinese government should formulate green financial policies based on local conditions and provide credit resources to favor environmentally friendly companies. Financial institutions should strictly implement green credit standards and modify financial products and services. Companies should take the initiative to eliminate outdated production capacity to obtain green credit support.

Does green credit policy affect corporate debt financing? Evidence from China

Green finance is one of the most important ways to help companies achieve green transformation and development. We construct a quasi-natural experiment with the "Green Credit Guidelines" and establish a difference-in-differences model to empirically test the implementation effect of the green credit policy in China. The results show that after the implementation of China's green credit policy, the debt financing scale of listed companies in heavily polluting industries has decreased significantly, the debt financing cost has increased significantly, and the debt financing maturity has been shortened significantly, indicating that the green credit policy has inhibited the debt financing of heavily polluting enterprises. We further find that this inhibition has also been affected by the nature of controlling shareholders, environmental information disclosure levels, regional environmental regulations and regional financial development levels. China's green credit policy has played a role in guiding listed companies to go green through the redistribution of debt financing.