1. Introduction
Shadow banking means various financial intermediary services beyond the conventional banking system, typically carried out by non-bank financial institutions. These institutions transform risks related to credit, liquidity, and maturity of financial assets, playing a “pseudo-bank” role. Starting in 2008, shadow banking in China has developed quickly. According to Moody’s data, at the beginning of 2017, China’s shadow banking scale reached a historical peak of 100.4 trillion yuan, accounting for over 80% of the GDP [
1], and by the end of 2021, it still amounted to 57 trillion yuan, nearly 50% of the GDP. In addition to regular financial institutions, small loan companies, and financing guarantee companies, an increasing number of non-financial sectors are utilizing diversified funding sources to engage in substantive lending activities, becoming important participants in the shadow credit market [
2]. On one hand, shadow banking operations are characterized by cross-market, cross-financial institutions, and cross-asset class transactions, intensifying the contagion and systemic risks in the financial system [
3]. On the other hand, the shadow banking activities probably lead to a crowding-out effect on their main businesses, inducing the risk of a downturn in the real economy through a siphoning effect [
3] and even lead to stock market crashes and financial crises [
4]. Therefore, understanding the motives and mechanisms behind non-financial companies’ shadow banking activities is crucial for curbing the rise of corporate shadow banking and guiding finance back to the real economy.
Corporate governance is a key factor in determining a company’s financial health, and the growing importance of climate risks should not be overlooked. As emphasized by Shahrour [
5], companies are crucial in tackling climate change, and their role in managing climate risks is indispensable. Indeed, the disruption caused by climate risks is one of the greatest challenges of this century [
6,
7]. Climate risks not only have a significant negative effect on business operations [
8] but also affect the overall stability of the financial system [
9,
10]. There is a growing trend among investors and borrowers to incorporate the impact of climate risks into their considerations during corporate financing and assessment [
11], and firms themselves are paying more attention to climate risks and their negative effects, treating them as one of the important factors in business decision-making [
12]. When considering climate risks’ impact, an important factor to note is highlighted by Roussel [
13]. The study indicates that shadow banking, as part of the financial system, is significantly affected by climate factors. Understanding this influence holds significant importance in the formulation of successful risk management tactics and policies. Due to the low short-term returns of the real economy, non-financial firms often opt for high-risk shadow banking activities, which offer relatively high returns and greater secrecy. It is worth considering how the shadow banking activities of companies are affected under the compounded impact of climate risks. The current literature primarily concentrates on the effect of climate change on corporate economic benefits [
14], risk exposure [
15], and environmental disclosure [
16], while the relationship between corporate climate risk perception and shadow banking activities of non-financial firms has yet to be explored. This study addresses this gap by focusing on the climate risk perception of non-financial firms and seeks to answer two key questions: (i) How do climate risks affect the shadow banking activities of non-financial firms? (ii) What are the underlying mechanisms?
To address the questions, we first collected Management Discussion and Analysis (MD&A) texts of all listed companies in China from 2010 to 2022 and conducted text analysis to form a corporate-level climate risk index. Using the index, we investigated the effect of climate risks on the shadow banking activities. The outcomes indicate a negative correlation between climate risks and shadow banking activities, and this conclusion holds even after addressing endogeneity issues. Furthermore, we explored two heterogeneous effects of climate risks on shadow banking activities, focusing on corporate financing constraints and profitability. The findings indicate that the impact of climate risks on shadow banking activities is more pronounced for firms with strong financing constraints and weaker profitability. Further, we found that for firms with weaker profitability, the relationship between climate risks and the credit intermediation of non-financial firms is closer than that with credit chains. This suggests that firms with weaker profitability are more susceptible to the impacts of climate change, leading to a deterioration in their credit status, and thereby increasing their costs and risks as credit intermediaries.
Additionally, we conducted robustness tests to further confirm the results. First, we further decomposed climate risks into physical risks and transition risks. Second, to address data skewness, we used the natural logarithm of shadow banking size as an alternative dependent variable in the model. Third, we changed the estimation method and used different fixed effects to control for unobservable heterogeneity. The results indicate that our conclusions passed all robustness tests.
Next, we conducted two mechanism analyses to explore the potential mechanisms through which climate risks affect the shadow banking activities. Diversified firms, typically involved in multiple business areas, have complex business connections and balance sheet entanglements compared to other firms. Under the impact of climate risks, firms with a higher degree of business diversification are more likely to trigger a more substantial cross-contagion effect with other firms due to the interconnectedness of their operations and balance sheets. Therefore, we expect to find that corporate climate risk perception reduces firms’ willingness to engage in shadow banking activities by increasing cross-risks. Second, climate risks may deteriorate the operational environment of firms, increasing operational costs and cash flow risks. To mitigate external risk shocks, firms may choose to hold more cash, thereby reducing leverage and shadow banking activities. We explored the inhibitory effects of cross-risk and cash holding preferences on the shadow banking activities. Both analyses yielded affirmative results, suggesting that our findings uncover the underlying mechanisms.
Our study makes three contributions. First, in the context of heightened climate risks in China, this study investigates how non-financial firms respond to these risks, thereby extending the existing research on the impact of climate risks [
17]. It provides empirical evidence from China on the relationship between extreme climate events and corporate investment and financing behaviors. Second, it enriches the research on the driving factors of shadow banking activities. A series of studies have analyzed these factors from the perspectives of economic policy [
18], corporate management [
19], and financial technology [
20]. Unlike previous research, our study focuses on the exploration of internal factors and, for the first time, investigates the impact of corporate climate risk perception on shadow banking activities, offering references for regulatory authorities to incorporate climate risks into decision-making during financial reform deepening. Lastly, by dissecting the internal mechanisms of firms’ behaviors in the face of climate risk challenges, our study reveals the essence of how climate risks impact corporate investment and financing behaviors. Our findings indicate that the root cause for non-financial firms reducing their shadow banking activities lies in the heightened uncertainty about the future economic environment due to climate risks, providing a comprehensive interpretation of the behavior of non-financial firms in the face of compounded risks.
The rest of this study is structured as follows:
Section 2 conducts a literature review and formulates research hypotheses.
Section 3 outlines the sample selection and research methodology.
Section 4 investigates the impact of climate risks on the shadow banking activities of non-financial firms.
Section 5 conducts robustness tests.
Section 6 performs a heterogeneous analysis.
Section 7 discusses potential mechanisms.
Section 8 concludes this study.
7. Mechanism Analysis
The preceding analyses offer direct evidence that rising climate risks can suppress the shadow banking activities of non-financial firms. We delve into the underlying mechanisms behind this relationship in this part.
Considering that an increasing number of studies indicate that the traditional three-stage mediation effect might have significant flaws [
68,
69], specifically, the three models involving three sets of variables could potentially face three endogeneity issues, which would require a minimum of two instrumental variables (IV1 for X→Y and X→M; IV2 for M→Y) and the assumption that the three error terms (e1, e2, and e3) are mutually uncorrelated. Since empirical research often relies on observational data, addressing these endogeneity issues can make the analysis highly complex. To resolve this, our study primarily adheres to the design method of Aguinis [
68]. First, we increase the use of bootstrap-derived percentile confidence intervals, which is able to broaden the hypotheses in the Sobel test, where the mediation effect rests on the premise that the multiplication of coefficients follows a normal distribution [
70]. Second, we consider the link between the mediator and dependent variables in the mediation effect, aiding in enhancing the integrality of the empirical chain. Based on this, our study draws on the approach of Niu and employs a four-stage mediation effect model for testing [
71]. Following the four-stage mediation effect approach analyzed previously and in conjunction with the design of model (1) from earlier, we construct the following mediation effect models (2), (3), and (4):
In the aforementioned models, represents the mediator variable, which in this case are the cross-risks and cash holding preferences. The steps for testing the mediation effect are as follows: First, test whether in Equation (1) is significant; if it is significant, continue with the mediation effect test. Next, test whether in Equation (3) is significant, and also test whether in Equation (4) is significant. If both are significant, further test in Equation (5). If this is significant, it indicates a partial mediation effect; if it is not significant, it indicates a full mediation effect. If in either Equation (3) or Equation (4) is not significant, a Sobel test is required. A significant Z value in the Sobel test indicates a significant mediation effect; otherwise, the mediation effect is not significant.
7.1. Expansion of Cross-Risk
We examine whether the amplification of cross-risks serves as a potential mediating mechanism through which climate risks influence the shadow banking operations of non-financial companies. Diversified businesses typically involve multiple operational areas and have complex business connections and balance sheet entanglements with other enterprises, forming a tightly interconnected financial network. When such diversified firms face climate risks, these risks can be transmitted to other businesses through this complex network of business interconnections, thereby amplifying and impacting the entire system. This can lead to firms engaged in high-risk, high-leverage, and informationally asymmetrical shadow banking being unable to recover funds on time, increasing the risks of liquidity crises and stock price crashes. In summary, under the backdrop of climate risks, firms with a higher degree of business diversification, due to the interconnectedness of their operations and balance sheets, are more likely to trigger a more substantial cross-contagion effect with other businesses. Therefore, these firms tend to reduce their shadow banking activities.
Following the approach used by Han [
65], we measure a firm’s cross-risks based on whether the number of business areas covered by its main operating revenue exceeds or falls below the industry’s yearly average. When a firm’s main operating revenue covers more business areas than the average in its industry, we mark it as 1, indicating the presence of cross-risks; otherwise, it is marked as 0.
The detailed outcomes of the regression are presented in
Table 9. In column 1, the coefficient of
CC1 is remarkably positive, suggesting a remarkable positive link between climate risks and cross-risks. In column 3, the coefficient of
CC1 is remarkably negative, indicating a remarkable negative link between climate risks and shadow banking activities, with the absolute value of the
CC1 coefficient decreasing compared to the benchmark regression when using a stepwise regression method. Based on these findings, further Sobel tests were conducted, revealing a Z statistic of −2.12, significant at the 5% level. Additionally, this study conducted a Bootstrap (1000 replicates) test, finding that the 95% confidence interval for the mediation effect is [−0.0007, −0.00003], which does not include 0. These results indicate that cross-risks have a mediating effect. That is, climate risks diminish the shadow banking operations of non-financial companies by increasing corporate cross-risks, thus validating Hypothesis 1 of this study.
7.2. Preference for Cash Holding
In this study, we further examine the mediating mechanism of the preference for cash holding. First, climate change-related extreme weather and abnormal temperatures not only deteriorate a firm’s tangible assets but also increase operational costs [
72,
73], thereby elevating cash flow risks and increasing the risk of financial default. Existing research shows that companies choose to keep more cash on hand to mitigate external risk impacts [
74,
75,
76], and thus, an increase in climate risks can trigger a firm’s preference for holding cash. The definition of a firm’s cash holding is as follows: measurement of annual changes in cash holdings, scaled by total assets.
The regression data are presented in
Table 10. In column 1, the coefficient of CC1 is remarkably positive, indicating a remarkable positive link between climate risks and cash holdings. Column 2 shows a significant positive correlation between cash holdings and the shadow banking activities of non-financial firms. In column 3, the coefficient of CC1 is remarkably negative, demonstrating a significant negative relationship between climate risks and shadow banking activities. Additionally, the absolute value of the CC1 coefficient has increased compared to the benchmark regression when using the stepwise regression method. Based on these findings, a further Sobel test was conducted, yielding a Z statistic of −6.74, which is remarkable at the 1% level. A Bootstrap test with 1000 replicates also indicated that the 95% confidence interval for the mediation effect is [−0.0021, −0.0010], which does not include 0. These outcomes show that cash holdings possess a mediating effect, confirming that climate risks decrease the shadow banking operations of non-financial firms by increasing the cash reserves, thereby supporting Hypothesis 1 of this study.
8. Conclusions and Policy Recommendations
Our empirical results address the two questions posed earlier. First, the findings demonstrate that climate risks possess a markedly adverse effect on the shadow banking operations of non-financial firms. Specifically, as climate risks increase, there is a significant reduction in the extent of shadow banking activities conducted by these companies.
Second, this study identifies the mechanisms through which climate risks influence shadow banking activities. It shows that climate risks indirectly reduce non-financial companies’ engagement in shadow banking by amplifying cross-risk exposure and increasing their cash holdings. Climate risks enhance cross-risk exposure by introducing additional sources of risk, which affects firms’ risk tolerance and financial strategies. To mitigate the uncertainties and potential financial losses associated with climate change, firms are likely to reduce their involvement in high-risk shadow banking activities. Additionally, to address potential risks relating to climate, companies tend to have larger cash reserves, directly decreasing their reliance on shadow banking. Together, these elements lead to the observed decrease in shadow banking operations among non-financial firms.
Unlike previous studies that pay close attention to the activities of commercial banks not listed on the balance sheet, this research examines the “quasi-financial” behaviors of non-financial firms, exploring how these firms adjust their shadow banking activities as a response to climate risks. These findings reveal that rising climate risks lead to a reduction in the shadow banking operations of non-financial companies. On one hand, climate risks exacerbate cross-risks and expand sources of risk for companies, while on the other hand, to manage potential threats, firms increase their preference for holding cash. These two factors together contribute to the decline in shadow banking activities. The heterogeneity analysis shows that firms with weaker profitability and greater financing constraints are more sensitive to climate risks.
Drawing from findings, the research suggests these policy recommendations: First, both governments and enterprises need to be vigilant about the potential risk expansion brought about by climate risks. The research results suggest that the reason for non-financial firms reducing their shadow banking activities lies in the heightened uncertainty about the future economic environment due to climate risks, forcing them to embrace a more prudent strategy in investing as well as financial strategies involving high-risk and opaque shadow banking products. Therefore, for governments, formulating policies to respond to climate risks should focus not only on visible financial risks (such as the increased operating costs due to physical risks) but also on avoiding the creation of new risks in the process of risk prevention. Especially under economic downturn pressures, while reasonably boosting corporate confidence, it is important to prevent issues like the aggregation and interconnection of risks from a policy operation perspective. For enterprises confronted with climate risk challenges, they should develop more proactive and effective strategic transformations and supporting plans, allocating limited capital to their main businesses that have long-term developmental significance. This approach is critical to avoid pursuing high-risk shadow banking activities with relatively higher returns and greater obscurity due to the lower short-term returns of the real economy, especially to avoid falling into adverse cycles caused by intertwined risks.
Second, government policymakers should consider the additional impacts brought by climate risks when deepening financial reforms. For governments, it is crucial to improve the investment environment for real businesses, actively guiding the economic focus of non-financial firms from a “virtual economy” to a “real economy”. This means reversing the trend of capital shifting from tangible to intangible assets, enhancing investments in firms’ main operations and profits from these operations, which is important for reducing risk-bearing in extreme situations. When economic pressures caused by climate risks are significant, regulatory authorities should consider moderately increasing tolerance towards shadow banking operations of non-financial companies. This would encourage them to proactively disclose risk information, enabling regulatory bodies to take further measures to mitigate potential financial risks and avoid systemic financial risks and crises. At the same time, it would enhance the resilience of enterprises to climate risks.
Lastly, for enterprises, it is imperative to proactively reduce high-risk underground financial investment and financing activities and to improve the mechanism for disclosing climate risk information. The proverb “It is better to solve the root problem rather than treating the symptoms” aptly applies here. Allocating limited capital to main businesses with long-term developmental significance and enhancing operational resilience and capabilities are vital to better manage risk mutations in extreme situations. Our study’s findings indicate that enterprises with weaker profitability and stronger financing constraints are more sensitive in responding to climate risks. These more sensitive and vulnerable firms should especially avoid engaging in high-risk shadow banking operations. What is more, companies should enhance their mechanisms for disclosing climate risk information, thereby increasing corporate sensitivity to climate risks and curbing the possibility of risk accumulation among various stakeholders.
Despite providing a preliminary theoretical discussion and analysis of the relationship between climate risks and shadow banking activities among non-financial companies, the research has limitations that require further improvement. First, the methodology primarily relies on textual analysis for statistical evaluation and does not utilize more objective data such as carbon footprint or carbon emissions-adjusted loan sizes. This limitation stems mainly from the availability and accessibility of detailed data. We acknowledge this as a constraint of our study and hope to delve deeper into such analyses when data acquisition conditions improve. Second, our research is predominantly grounded in the data from Chinese listed companies, which may limit the general applicability of our conclusions. While these companies hold a significant position in the financial market, they may differ considerably from non-listed companies or businesses in other countries in terms of operations, financing structures, and market behavior. Thus, our findings may not fully apply to a broader group of non-financial firms or economic environments in other countries. Future research should consider employing a more diverse sample to enhance the universality and depth of the findings.