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Article

Unravelling the Missing Link: Climate Risk, ESG Performance and Debt Capital Cost in China

by
Yu Yan
1,
Xinman Cheng
1 and
Tricia Ong
2,*
1
School of Economics and Management, Harbin Normal University, Harbin 150025, China
2
School of Business and Law, Edith Cowan University, Joondalup, WA 6027, Australia
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(16), 7137; https://doi.org/10.3390/su16167137
Submission received: 28 May 2024 / Revised: 29 July 2024 / Accepted: 7 August 2024 / Published: 20 August 2024
Versions Notes

Abstract

:
The concept of sustainability has developed significantly from an unrealistic abstract ideology to a framework that can measure companies’ environment, society and corporate governance (ESG) performance. While extensive research has established some relational impacts of ESG performance on debt capital cost (DCC), this paper contends that a comprehensive review of these impacts is incomplete without screening them through the lens of climate risk (CR). Companies are subjected to CR that comprises physical and transition factors resulting from climate change. This paper aims to unravel the missing link between CR and ESG performance, and the consequent impacts on DCC. This paper illustrates using Chinese companies that operate in an emerging economy with robust industrial activities under intense global scrutiny to achieve emission reduction and meet carbon neutrality goals. Through considering CR, the impacts of ESG performance on DCC are explained using panel data and mediation effect tests with A-share listed enterprises on the Shanghai and Shenzhen stock exchanges from 2016 to 2020. The findings show that ESG performance significantly and negatively affects DCC, with debt default risk playing a mediating role. The negative effect of ESG performance on DCC is more significant in non-polluting enterprises and non-state-owned enterprises.

1. Introduction

The concept of sustainability has developed over many decades from an abstract ideology that is too complex for understanding and very challenging for realism to an initial conceptualized triple bottom line (TBL) theory coined by Elkington in 1994 that involves a company’s social, environmental and economic impact [1]. The TBL theory was introduced initially by Elkington as a win–win–win strategy that seeks to explain the importance for companies to consider beyond profit-making to include people and the planet to sustain long term value creation for their companies [2]. With increased awareness of environmental and pollution issues from industrialization, companies are subjected to an intense level of public scrutiny to ensure that they provide adequate disclosures on their business operations to stakeholders, especially if they are operating in environmentally sensitive industries [3]. Companies are now required to demonstrate their corporate social responsibility by being transparent about the impacts on the environment and society that result from their business operations [4]. Companies have responded through increased reporting on both financial and non-financial information that comprises three key components, namely, environment, society and corporate governance, and is now commonly referred to as ESG [5].
ESG provides a fundamental and comprehensive framework for consideration that affects companies’ financial and operations decisions [6]. Policymakers and regulators are incorporating factors relating to ESG when they formulate and implement policies and regulations [5,7], and investors are also considering these ESG factors when they review companies’ risks and returns to make investment decisions [5,8]. Consequently, it becomes increasingly vital for companies to provide ESG disclosures to their stakeholders. Despite the significant exponential increase in companies globally providing more ESG disclosures with detailed information, which are often guided by a comprehensive framework such as the Global Reporting Initiative (GRI) or other similar reputable reporting frameworks, critics are questioning the reliability of these disclosures [9]. More importantly, many have felt that these disclosures are still lacking the ability to evident real efforts to address climate issues [10].
Climate change that is propelled by human and companies’ operations through activities such as deforestation and pollution have great implications to companies’ ESG. These implications present significant threats that can result in both financial and physical crises with extensive socioeconomic consequences [11,12,13]. Companies’ climate risk (CR) is defined as a company’s “vulnerability to climate change, which may result in decreased financial performance” [14]. It is posited that this CR comprises both physical factors such as extreme weather conditions and scare resources and transition factors that include changes in regulations and market preference resulting from climate change [13]. Hence, the prior literature concludes that companies need to consider this CR as both the physical and transition factors of the CR have direct impact to companies’ assets and can cause productivity to decrease due to adverse impacts on companies’ operations from climate change [14].
While there is extensive research on ESG performance, there is still a lack of studies focusing on the effects of CR that arises from climate change that have significant influence on ESG performance [6]. This paper argues that it is vital to review the impacts of ESG performance on DCC through the lens of climate risk. Without considering ESG performance in the context of CR, ESG performance will remain a potential green-washing technique that companies may be inclined to adopt, with no tangible impact to help resolve the problems of climate change.
This paper has chosen to focus on China companies for several reasons. Firstly, China is a large emerging economy where there are competitive advantages over developed economies for cheaper factors of production such as labor and materials [15]. This has resulted in extensive growth of outsourcing businesses and compartmental production processes, making China an important part of the global production network’s supply chain [15,16]. Consequently, more industrialization in China means that there are more adverse ESG impacts on environmental and climate change issues due to more pollution and labor shortage causing more human rights abuses. Secondly, China, being the country with third largest economy in the world, has a large population and is highly reliant on energy use, accounting for 32.9% of global CO2 emissions [15], making it the world’s largest emitter of greenhouse gases (31% in 2020) [17]. China’s economic growth since the 1970s has seen its per capita income increase nearly thirtyfold, but this has consequently resulted in a more than tenfold increase in CO2 emissions over the same period [18]. These driving factors brought China under intense global scrutiny, encouraging active work towards the world’s target of net zero emissions, evidenced by China’s adoption of the Sendai Framework for Disaster Risk Reduction in 2015 and the Paris Agreement on climate change in 2016 [17]. Another fundamental reason is China’s increased vulnerability to climate change, which includes rising sea levels, severe weather events and melting glaciers. Natural disasters such as storm surges and coastal erosion pose high climate risks that threaten China’s densely populated low-elevated coastal cities, which account for one-fifth of China’s population and one-third of its gross domestic product [18]. According to the latest report produced by the World Bank Group [18] on China’s climate and development, these natural hazards have resulted in direct annual losses estimated at an average of USD 76 billion over the last five years. In 2022, China published the National Strategy on Climate Adoption 2035, demonstrating their motivation to strengthen efforts to improve climate resilience in their economic, health and social systems [17].
In addition, reporting of ESG performance started late in China and the effect associated with company ESG performance in China is still in its preliminary stages, with research evidence in China context remaining inadequate. The concept of ESG development was initially introduced by the United Nations Principles for Responsible Investment in 2006. However, it was not until 2015 when the Hong Kong Stock Exchange issued the Environmental, Social, and Governance Reporting Guide that the initial introduction of ESG principles to Chinese investors took place. This guide established a semi-mandatory requirement of “explanation if not disclosed” for ESG information disclosure. In September 2020, the Shenzhen Stock Exchange spearheaded a revision of the assessment measures of information disclosed by listed companies on the exchange. This revision marked the first instance of active and mandated ESG disclosure for listed companies, as well as an assessment of their fulfillment of social responsibility. The introduction of relevant regulations has led to the need for companies to include disclosures of their ESG performance in order for them to be listed on the stock exchanges to obtain funding. As a result, this paper investigates how ESG performance impacts DCC in the context of China by considering CR, as many prior studies have suggested that CR is priced into the equity market [19,20].
The World Bank Group report highlighted the necessity for China to manage the low-carbon transition of its power sector, the country’s largest source of emissions, to achieve a rapid decline in emissions over the next two decades and reach its goal of carbon neutrality. Policies implemented are likely to impact companies across different industries in various ways, highlighting the importance and timeliness of studying these effects in China and across different industry sectors [18].
Hence, this paper aims to contribute in the following ways: (1) establishing and explaining the missing link between CR and ESG performance to provide a comprehensive understanding of how climate change impacts DCC; (2) providing empirical evidence from an emerging economy, specifically China, on how CR affects economies that are particularly vulnerable to climate change; and (3) addressing China’s mandatory census on achieving net zero emissions by 2060 and (4) conforming to international environmental standards across different industry sectors to ensure its economic stability and growth in the global market.
The remainder of this paper is structured as follows: Section 2 analyzes the mechanism in the prior literature and establishes the research hypotheses. Section 3 provides the study design and Section 4 explains the empirical results. Section 5 concludes this paper by highlighting the implications of the findings and presents some suggestions for future research.

2. Literature Review and Hypotheses Development

2.1. Direct Impact of ESG Performance on Debt Capital Cost

The theory of asymmetric information posited by Akerlof [21] states that a lack of information or transparency will make investment decisions challenging and thus adversely affect the investment decision-making of enterprises [22]. While creditors conduct investigations and analyze debtors before granting loans, their limited resources can make it challenging to obtain complete information about the debtor. In such circumstances, voluntary disclosure of information by the debtors becomes a crucial source for creditors to gain insights into enterprises. In evaluating an enterprise, creditors not only consider the disclosed financial information but also review non-financial information, which can impact the creditors’ evaluation of the enterprise and its debt capital cost. ESG information disclosure can adequately provide relevant information to facilitate this process [23]. Many companies have included disclosures on climate risks as part of their voluntary disclosures [14]. Based on theory of asymmetric information, Zhang et al. [24] explained that companies with more ESG disclosures may reduce issues of information asymmetry and increase their attractiveness to investors, thus reducing their DCC.
Currently, enterprises primarily focus on “maximizing stockholders’ wealth”. However, stakeholder theory proposes that prioritizing the interests of major shareholders can potentially harm the interests of small and medium-sized ones, employees, and creditors [25]. The implementation of ESG management and information disclosure by enterprises can result in increased expenditures and reduced earnings for shareholders [26]. Yu et al.’s [26] longitudinal study, which spans over 13 years from 2010 to 2022 and focuses on BRICS countries, which includes China, find a negative relationship between ESG performance and environmental investments. They explain that their results signify potential trade-offs between companies’ financial profitability and commitment to environmental issues, especially in the initial ESG implementation period when companies’ long term benefits from ESG commitments were not realized yet. Their results identify the complexities and dilemma of companies to balance financial profit maximizing and ESG commitments.
Arian and Sands [14] found that stakeholders are expecting companies to include corporate climate risk disclosure for long-term success. ESG uncertainty may affect investor demand and risk–return trade-offs and reduce the economic welfare of ESG-sensitive organizations [24,27]. Nevertheless, such disclosures can potentially decrease information asymmetry [28], mitigate the price discrepancy between buyers and sellers [29], and reduce the risk of financial misconduct [30]. Furthermore, it can facilitate information exchange between enterprises and external stakeholders, enhance trust from external stakeholders, and promote the establishment of long-term and stable cooperative relations with these stakeholders [31]. Zhang et al. [24] posits that stakeholder theory prioritizes the interests of various stakeholder groups, suggesting that companies with better ESG performance can demonstrate better commitments to their stakeholders, thereby attracting more investment. Although stakeholder theory indicates that ESG performance could have varying impacts on companies’ investments, and consequently on DCC, our study argues that stakeholders generally value long-term benefits and will therefore prioritize ESG performance over shorter-term financial gains.
Resource dependence theory posits that resources are essential for enterprise survival [32]. Companies with more resources are viewed as having a competitive advantage that allows for them to improve ESG performance [24]. In line with the results of Zhang et al. [24], we hypothesize that companies that excel in ESG are able to manage their debt risk more effectively and therefore have access to a lower cost of debt capital. The disclosure of ESG information and the subsequent establishment of external trust can aid enterprises in obtaining long-term and stable sustainable resources conducive to their continual development. In addition, this can facilitate the acquisition of more dependable funding sources, reducing the risks associated with temporary borrowing for enterprises.
Reputation theory suggests that corporate reputation is a crucial intangible asset for enterprises, which is distinct from corporate goodwill. It is a valuable investment acquired through long-term accumulation. The study of [6] found that climate risk significantly affects companies’ ESG performance. Hence, an enterprise’s strong ESG performance serves as a signal to external stakeholders of its sound operational condition, indicating a commitment to reducing climate risks that is in compliance with state laws and regulations, and a commitment to social responsibility. This can help establish a favorable corporate image that promotes adherence to laws and regulations and enhances stakeholder engagement and loyalty [33].
ESG scores measure corporate sustainability in a way that provides an advantage to larger companies with more resources [34]. ESG factors are critical to achieving sustainability in corporate management and are used as a way to increase corporate value [35], which improves the profitability of companies [24]. In times of business crisis, a positive corporate image and strong stakeholder relationships can result in the enterprise obtaining loans at a lower capital cost due to the increased trust and credibility fostered with lenders. Therefore, basing our arguments on the various theories that have explained the relationships between ESG performance and DCC, the first hypothesis H1 is proposed as below:
H1. 
Enhancing an enterprise’s ESG performance can lower its debt capital cost.

2.2. Mediating Effect Based on Debt Default Risk

The primary objective of external borrowing by creditors is to recover the principal and accrue interest upon maturity. Drawing upon the signaling theory, the proactive management perspective on climate change issues and initiative to reduce climate risk will enhance ESG performance [36]; while this incurs certain costs, can serve as a communication tool to convey to creditors that the enterprise is in sound operational condition and possesses a positive outlook for the future. Resource dependence theory contends that companies with favorable business conditions typically possess greater financial resources and are better equipped to translate their social responsibility into tangible actions. Conversely, those with unfavorable business conditions may face constraints in contributing to environmental protection, despite their willingness to do so. Supported also by reputation theory, when creditors perceive that an enterprise can maintain sustainable operations, their confidence in its ability to make timely repayments increases. Consequently, this reduction in default risk can lead to a decrease in the required interest rate for the enterprise [37].
The agency theory by Jensen and Meckling [38] suggests that the role of governance structures in a company is crucial to mitigate agency conflict. An enterprise typically prepares and provides detailed information on the borrowing purpose and repayment plans according to their projected returns before succeeding in securing funds. However, major shareholders of the enterprise may seek to achieve higher returns with risker projects, leading them to potentially alter the use of the borrowed funds. ESG information disclosed by an enterprise can provide creditors with insights into the internal principal–agent system and the management level of the enterprise. As a result, creditors may develop greater trust in the enterprise and become more optimistic about its future development prospects. This can lead to a reduction in the default risk assessment, ultimately resulting in a lower required rate of return by creditors. Consequently, this study proposes hypothesis H2:
H2. 
Debt default risk plays a mediating role in the impact of ESG performance on debt capital cost.

2.3. Impact of ESG Performance on Debt Capital Cost from a Corporate Pollution Perspective

Within the context of pursuing a synergistic development of economy and environment, polluting enterprises are subjected to more stringent laws and regulations, as well as increased social attention. Suchman [39] defined legitimacy as “a generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions” (p. 574). This suggests that companies must operate in accordance with community expectations [40,41] and conduct their business activities within the boundaries of societal norms.
According to the legitimacy theory, companies operating within environmentally sensitive industries will respond to social expectations of corporate behavior by providing more sustainability disclosures to legitimize their business operations. In response to the pressure of legal and regulatory frameworks, polluting enterprises tend to prioritize the enhancement of their ESG performance, as they are deemed to be contributing adversely to climate change issues and thus higher climate risk [6]. When companies show their commitment to improving ESG performance, it can lead to reductions in litigation costs and environmental fines resulting from non-compliance with relevant laws and regulations. By doing so, these enterprises aim to avoid being forced to resort to higher-cost debt financing to meet sudden capital needs. Moreover, as a result of the increased social attention on environmental issues, polluting enterprises can enhance their social recognition by improving their ESG performance, which can potentially lead to a lower cost in debt financing. Thus, this study proposes hypothesis H3:
H3. 
The impact of corporate ESG performance on debt capital cost is more significant in polluting enterprises.

2.4. Impact of Corporate ESG Performance on Debt Capital Cost from an Equity Perspective

In China’s economic system, state-owned enterprises have a distinct relationship with the government, owing to their status as state-owned entities. As such, they are expected to serve as role models in implementing policies introduced by the state. These state-owned enterprises are estimated to generate half of China’s total greenhouse emissions [18]. With the Chinese government’s strong determination to work together with the world towards net zero emissions [17], these state-owned enterprises will have the motivation and capacity to implement low-carbon policies such as scaling up the use of renewable energy [18]. Given their reliance on state funding, the public will hold these state-owned enterprises accountable for positively responding to such policies. Conversely, non-state-owned enterprises, which prioritize profit maximization, can attract public attention by proactively undertaking ESG responsibilities and enhancing ESG performance through showing their commitment in climate change issues. Therefore, this paper proposes hypothesis H4:
H4. 
Corporate ESG performance has a more pronounced effect on debt capital cost for non-state-owned enterprises.

3. Study Design

3.1. Sample Selection and Data Sources

In order to ensure the representativeness and accuracy of this study, we selected a sample that included companies of different industries, sizes and ownerships; this study utilizes the samples of listed companies in Shanghai and Shenzhen A-shares from 2016 to 2020, and to enhance the reliability of upcoming conclusion, the data were processed as follows: (1) ST (special treatment stocks) and *ST, as well as samples with missing values during this period, were eliminated. This resulted in a balanced panel dataset with a cross-section number of N = 1260 and T = 5. (2) To eliminate the effect of extreme values, the continuous variables involved were Winsorized by 2%.
The companies included in this study operate in different industry sectors. Companies are classified as operating in the non-polluting sector if they operate in sectors such as finance, real estate, information transmission and IT services. Companies are classified as operating in polluting sector if they are involved in manufacturing, transportation and construction sector; 31% of our sample companies were operating in the polluting sector and 69% of the sample companies were operating in the non-polluting sector; 49% of our sample companies were state-owned companies, and the remaining 51% were non-state-owned.
The ESG performance data for the enterprises considered in this study were obtained from the China Securities ESG rating system, while the financial data were collected from the China Stock Market & Accounting Research Database (CSMAR). In addition, we used multiple regression analyses to control for variables that might have been of influence.

3.2. Definition of Variables

3.2.1. Explained Variables: Debt Capital Cost

Debt capital cost (DCC) refers to the cost incurred in acquiring and utilizing external funds. Currently, two primary academic methods are employed to quantify debt capital cost, namely, the debt rating approach and the expense ratio approach.
The debt rating method is a technique used to assess the estimated debt capital cost. This is achieved by combining the rating of corporate bonds issued by debt rating agencies with the average yield at maturity of bonds. The expense ratio approach is a quantitative technique used to evaluate the debt capital cost. This method calculates the cost by determining the ratio of expenses incurred through borrowing to the principal amount borrowed. Given the limited number of debt rating agencies in China and the predominant use of bank loans by Chinese enterprises for debt financing, the expense ratio approach is adopted in this study. Nonetheless, in China, it is not mandatory to include detailed information pertaining to debt interest in financial statements, resulting in a lack of disclosure of capitalized interest by Chinese enterprises. As such, this research draws on the approaches adopted by scholars such as Li and Liu [42]. Specifically, the ratio of financial expenses to the average debt at the beginning and end of the period was utilized to determine the debt capital cost in this study.

3.2.2. Explanatory Variables: Corporate ESG Performance

Presently, the evaluation of corporate ESG performance in Chinese academic circles mainly depends on third-party rating agencies. However, due to differences in social environments, technological development and other related factors, there are often significant discrepancies in evaluation systems and results between Chinese and foreign agencies. As this study focuses on listed companies in Shanghai and Shenzhen A-shares, it primarily relies on the assessments of domestic ESG rating agencies, such as Shanghai CSI, SynTao Green Finance, and RKS ESG Ratings. Shanghai CSI’s ESG assessment is particularly well suited, as it began earlier, is updated more frequently and has a much broader coverage, compared to other assessments. Therefore, following the practice of Xi et al. [43], this research adopts the ESG rating of Shanghai CSI to evaluate the ESG performance of enterprises, assigning the nine grades of CSI ESG rating, from AAA to C, a score of 9 to 1, respectively.

3.2.3. Control Variables

This study chooses several control variables, including enterprise size, growth, proportion of fixed assets, proportion of the largest shareholder, degree of equity balance and number of directors. Table 1 provides a definition of the variables used in this study.

3.3. Equation Construction

To test the impact of ESG performance on debt capital cost, this paper formulates Model (1):
D C C i , t = α 0 + α 1 E S G i , t + α 2 S i z e i , t + α 3 G r o w t h i , t + α 4 F i x i , t + α 5 L a r O w n i , t + α 6 B a l a n c e i , t + α 7 B o a r d i , t + ∑ Y e a r + ∑ I n d + ε i , t
Model (1) includes the following variables: i denotes the enterprise, t signifies time, ε represents the random error, α is the constant term and α 1 through α 7 represent the coefficients of each respective variable. Furthermore, in order to account for the effects of year and industry factors, year and an industry dummy variable (Ind) are incorporated as control variables.

4. Analysis of Empirical Results

4.1. Descriptive Statistics

Table 2 displays that the mean value of debt capital cost is 0.012, and the standard deviation is 0.022, indicating that there is certain variation in debt capital cost among the sample enterprises. The average and median values of ESG among the sample enterprises are 6.779 and 7.000, respectively. These results indicate that, on the whole, the enterprises in the sample exhibit a high level of ESG performance. However, the minimum and maximum values of ESG are 4.000 and 9.000, respectively, suggesting that there exist notable differences in ESG performance among the examined enterprises.

4.2. Correlation Analysis

Table 3 presents the Pearson correlation coefficient between the main variables. Table 3 demonstrates that the correlation coefficient between debt capital cost (DCC) and enterprise ESG performance (ESG) is −0.062, which is statistically significant at the 1% level. This finding tentatively suggests that a negative relationship exists between corporate ESG performance and debt capital cost, which is largely consistent with the original hypothesis. With the exception of the strong correlation between equity balance degree and the shareholding ratio of the first shareholder, the absolute values of the correlation coefficients among the remaining variables are below 0.5. Therefore, it can be concluded that there is no substantial multicollinearity among the relevant variables.

4.3. Regression Analysis

4.3.1. Analysis of Principal Regression Results

To estimate Model (1), this paper employs the fixed effect of control industry and time, and robust standard errors. The regression results are presented in Table 4. In Model (1), the correlation coefficient between enterprise ESG performance and debt capital cost is −0.001. This coefficient is statistically significant at the 1% level, indicating that improvements in ESG performance can significantly reduce debt capital costs for enterprises. Thus, hypothesis H1 is supported by the empirical evidence.
This result is in line with prior studies [6,24] that found similar negative relationship between ESG performance and climate risk [6] where climate risk is positively related to DCC, as explained in earlier sections of this paper. Our result is also aligned to Zhang et al. [24], where they found ESG performance and corporate investment were positively related. According to Zhang et al. [24], companies that have better performance in ESG are viewed favorably by investors and other stakeholders, making them attractive to potential investors and facilitating better access to funding, and consequently reduced DCC.

4.3.2. Robustness Test

(1)
Endogeneity test
Given the possible causal relationship between ESG performance and debt capital cost, the issue of endogeneity arises. To mitigate endogeneity concerns, this study addresses the potential lagged effects by regressing the original model with explanatory and control variables delayed by one period. The regression results, as presented in Table 5, and their significance remain robust, and these results suggest that the principal regression model was not impacted by significant endogeneity issues.
(2)
Replacement of independent variables
Adoption of replacement indicators for corporate ESG performance: A new explanatory variable (esg) is constructed by assigning a value of 1, 2 and 3 to C-CCC, B-BBB and A-AAA rating, respectively, as obtained from the CSI ESG rating. The regression analysis results are presented in Table 6, revealing no significant change in the regression results or significance.

4.3.3. Mechanism Analysis

The principal regression analysis demonstrates that enterprises with robust ESG performance may attain a reduction in their debt capital cost. However, the specific mechanisms by which this effect is achieved remain unclear, prompting the question: What is the underlying mechanism that links ESG performance to debt capital cost for enterprises? The primary focus of this paper is to analyze the risk in debt default. Chen et al. [44] utilized a binary variable method to measure debt default risk, based on a borrower’s ability to repay the principal amount within the specified timeframe and on any debt-related lawsuits in the current year. However, their method has inherent limitations. To address these limitations and provide a more comprehensive measure of debt default risk, this paper adopts the Z-value model, drawing on the approaches of Altman [45] and Xu and Chen [46]. The Z-value model assesses debt default risk by taking into account various factors, including the enterprise’s operational ability, development capacity, solvency and profitability. A higher Z-value indicates a greater risk of debt default for the enterprise. Debt default risk can be calculated using the following formula: debt default risk = − [1.2 × (working capital/total assets) + 1.4 × (retained earnings/total assets) + 3.3 × (earnings before interest and tax/total assets) + 0.6 × (market value of equity/book value of liabilities) + (sales revenue/total assets)]. For the empirical analysis, this paper employes Yang’s method [47] and Wen’s three-step mediating effect test method [48], along with the Sobel test. Based on Model (1), the following models are constructed:
Risk_(i, t) = β_0 + β_1 Size_(i, t) + β_2 Growth_(i, t) + β_3 Fix_(i, t) + β_4 LarOwn_(i, t) + β_5 Balance_(i, t) + β_6 Board_(i, t) + ∑Year + ∑Ind + ε_(i, t)
DCC_(i, t) = δ_0 + δ_1 ESG_(i, t) + δ_2 Risk_(i, t) + δ_3 Size_(i, t) + δ_4 Growth_(i, t) + δ_5 Fix_(i, t) + δ_6 LarOwn_(i, t) + δ_7 Balance_(i, t) + β_8 Board_(i, t) + ∑Year + ∑Ind + ε_(i, t)
Table 7 presents the results of the regression analysis. The first column demonstrates a significant negative correlation between ESG performance and risk, indicating that ESG can effectively reduce debt default risk. The second column shows that the inclusion of risk increases the risk coefficient to 0.002, which is significant at the 1% level. This finding suggests that debt default risk is a critical factor in determining debt capital cost. Additionally, the DCC coefficient is significantly negative, indicating that debt default risk serves as a partial mediator in the relationship between ESG performance and debt capital cost. Thus, hypothesis H2 is supported.
This result is similar to that of prior studies where Zhang et al. [24] found ESG performance has a moderating effect in economic policy uncertainty and corporate investment. Companies with better ESG performance affect corporate investment positively through enhancing their reputation and reduce their default risk [24]. Sun and Cui [49] also found a strong effect of ESG performance on reducing default risk. The reduction in companies’ default risk can thus help to mediate DCC, as shown in our study.

4.3.4. Heterogeneity Analysis

To account for heterogeneity, the experimental data were regressed in groups using fixed effects for time and industry. Table 8 presents the results of the heterogeneity analysis conducted.
(1)
Analysis of pollution heterogeneity
The regression results in the first column indicate that there is no significant correlation between corporate ESG performance and debt capital cost for polluting enterprises. In contrast, the results in the second column reveal a significant negative correlation between ESG performance and debt capital cost for non-polluting enterprises. Specifically, the correlation coefficient is −0.001 and significant at the 1% level. This finding suggests that a higher level of ESG performance among non-polluting enterprises is associated with a lower debt capital cost. The finding is in contrast with hypothesis H3, and this unexpected result may be attributed to the current trend of promoting ecological civilization in China, which has resulted in more stringent laws and regulations for polluting enterprises. As a result, these enterprises may be more inclined to prioritize their environmental behavior and disclose relevant information due to increased regulatory pressure. Furthermore, polluting enterprises are regarded as having a greater responsibility and obligation to engage in environmental governance by outsiders [48]. Our results may suggest that companies in China, especially those that are operating in a pollutive industry, are already under heightened scrutiny and public supervision. Consequently, they are unable to demonstrate further comparative advantage, as explained in Dkhili [50], who found a moderating role of competitive advantage in companies’ ESG performance. Thus, the results suggest that improving ESG performance alone may not be sufficient to lower debt capital cost for polluting enterprises.
(2)
Heterogeneity analysis of property rights
The regression results in the third column indicate that there is no significant relationship between corporate ESG performance and debt capital cost for state-owned enterprises. In contrast, the results in the fourth column show that the negative association between ESG performance and the cost of debt capital is more significant among non-state-owned firms. This may be due to the fact that non-state-owned firms pay more attention to their ESG performance when facing the market and investors. The correlation coefficient is −0.001, and the relationship is statistically significant at the 1% level. Thus, the hypothesis H4 is supported by the findings.
Signaling theory, which was demonstrated in Jung and Song’s [36] study, may explain our findings, as non-state-owned companies are more likely to require better ESG performance to signal good corporate governance to attract investments to satisfy their funding needs.

5. Research Conclusions and Suggestions

This study empirically examines the effect of ESG performance through the consideration of climate risk on debt capital cost using a sample of Chinese A-share listed companies on stock markets of Shanghai and Shenzhen from 2016 to 2020. The findings suggest that corporate ESG performance is significantly associated with a reduction in debt capital cost for enterprises. The mediation analysis reveals that debt default risk partially mediates the relationship between corporate ESG performance and debt capital cost. Specifically, the results indicate that corporate ESG performance reduces debt capital cost by lowering its debt default risk. Additional heterogeneity analysis suggests that non-polluting enterprises and non-state-owned enterprises can effectively reduce their debt capital cost by enhancing their ESG performance.
Given the positive impact of ESG performance on reducing the cost of debt capital, this paper suggests that firms should strengthen their ESG practices, especially in environmental protection and social responsibility. Meanwhile, governments and regulators should promote more transparent and comprehensive ESG disclosure standards. The first recommendation is for companies to cultivate a comprehensive understanding of the ESG concept and integrate it into their daily corporate management practices. Simultaneously, expenditures associated with ESG management should be viewed as value investments, rather than simple cost outlays. Enterprises should develop an effective ESG management system that prioritizes the enhancement of corporate management capabilities and social responsibility awareness as essential components of high-quality corporate development. Furthermore, corporate internal audit departments should conduct rigorous evaluations of ESG information to effectively fulfill their internal governance responsibilities. The second recommendation pertains to the current state of China’s ESG system, which remains incomplete. In light of this, governments should establish and enhance a mandatory ESG information disclosure system that encourages companies to disclose ESG data transparently and accurately. Notably, the impact of ESG scores on extreme risks tends to be more pronounced following the implementation of mandatory disclosure regulations [51]. Moreover, regulatory bodies should intensify their oversight of relevant enterprises to promote continuous enhancement of ESG performance among these enterprises. Given that third-party rating agencies are responsible for conducting ESG assessment, and different agencies utilize varying evaluation criteria, it is critical for governments to promptly establish guiding evaluation criteria to ensure consistency and accuracy across ESG rating systems. The third recommendation pertains to the expanding influence of the ESG concept. As such, all investment institutions should adopt ESG investment practices and incorporate corporate ESG performance as a key evaluation factor when making investment decisions. This will bolster the recognition of ESG concept in the capital market. And the fourth recommendation relates to the current state of audit institutions in China, which primarily assess the authenticity, legality and rationality of financial information of enterprises but do not take into account their social responsibilities. Consequently, to encourage high-quality development among enterprises, these institutions should integrate the auditing of social responsibility into financial information and provide related reports. This may greatly contribute to the ongoing advancement of corporate social responsibility initiatives.
Our paper demonstrates several contributions by providing empirical evidence that (1) establishes the link between CR and ESG performance and their impacts on DCC, (2) enhances understanding about emerging economy such as China that are vulnerable to climate change, and (3) assists regulatory bodies in formulating policies to reduce DCC through reducing CR with better ESG performance. Our paper also contributes to the understanding of numerous theories, including legitimacy and stakeholders’ theory and signaling theory with empirical evidence.
The limitations of our research include studying a single country and being limited to a five-year period. Future research can further extend to studying other emerging economies to compare and contrast the results to improve our understanding of the influence of CR and ESG on DCC.

Author Contributions

Conceptualization, Y.Y. and T.O.; Methodology, Y.Y.; Software, X.C.; Validation, X.C.; Formal analysis, X.C.; Investigation, X.C.; Writing—review & editing, T.O. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Research on the Innovation of Incentive Mechanism for Farmers’ Cooperative Organizations in the Context of Rural Revitalization (2019 National Social Science Fund of China, 19BJY143); the Research on the Construction of Practical Teaching System in the Context of First-class Economics Specialty Establishment (2020 General Project of Higher Education Teaching Reform in Heilongjiang Province, SJGY 20200374); and the Research on the Theory of Wealth Distribution in Marx’s Das Kapital (2020 Harbin Normal University Doctoral Research Start-up Fund Project).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Variable definition.
Table 1. Variable definition.
TypesVariableSymbolDefinition
Explained variableDebt capital costDCC Financial expenses Average of opening and closing liabilities
Explanatory variableCorporate ESG performanceESGAs per the CSI ESG rating system, scores 9 to 1 are assigned,
with 9 being the highest score.
Control variableEnterprise sizeSizeln (total assets of enterprise)
Enterprise growthGrowth ( Current operating income − operating income in the previous period ) Last operating income
Proportion of fixed assetsFix Total fixed assets Total assets
Largest shareholder’s shareholdingLarOwn Shares held by the largest shareholder Total shares
Equity balance degreeBalance Second largest shareholder’s shareholding ratio Largest shareholder’s shareholding ratio
Number of directorsBoardln (number of board members)
Table 2. Descriptive statistics.
Table 2. Descriptive statistics.
VariableSample SizeMean ValueMedianStandard DeviationMinimum ValueMaximum Value
DCC63000.0120.0140.022−0.0570.050
ESG63006.7797.0001.2224.0009.000
Size630022.90622.7511.26120.68126.183
Growth63000.2510.0191.007−1.6535.390
Fix63001.4181.4200.1961.0441.821
LarOwn63000.3300.3110.1430.1000.662
Balance63000.3440.2540.2830.0160.958
Board63002.1522.1970.1941.6092.639
Table 3. Pearson correlation coefficient.
Table 3. Pearson correlation coefficient.
VariableDCCESGSizeGrowthFixLarOwnBalanceBoard
DCC1
ESG−0.062 ***1
Size0.166 ***0.415 ***1
Growth−0.034 ***−0.041 ***−0.155 ***1
Fix0.462 ***0.083 ***0.452 ***−0.086 ***1
LarOwn−0.080 ***0.204 ***0.271 ***−0.011 ***0.075 **1
Balance0.019−0.058 ***0.010−0.030 ***−0.015−0.608 ***1
Board0.047 ***0.149 ***0.230 ***−0.033 ***0.087 ***0.057 ***0.055 ***1
Note: The symbols ** and *** represent significance at the 5% and 1% levels, respectively.
Table 4. Regression results of ESG performance and debt capital cost.
Table 4. Regression results of ESG performance and debt capital cost.
VariableDCC
ESG−0.001 ***
(−5.50)
Size0.001 **
(2.23)
Growth0.000
(1.41)
Fix−0.055 ***
(35.38)
LarOwn−0.024 ***
(−10.69)
Balance−0.006 ***
(−5.22)
Board−0.000
(−0.25)
YearCtrl
IndCtrl
Adj-R20.369
N6300
Note: The t-statistic is indicated in parentheses. The symbols ** and *** represent significance at the 5% and 1% levels, respectively.
Table 5. Regression results of endogeneity test.
Table 5. Regression results of endogeneity test.
VariableDCC
ESGt−1−0.001 ***
(−5.12)
Sizet−10.001 ***
(3.23)
Growtht−10.000
(1.19)
Fixt−10.051 ***
(28.78)
LarOwnt−1−0.025 ***
(−9.65)
Balancet−1−0.005 ***
(−3.70)
Boardt−1−0.001
(−0.43)
YearCtrl
IndCtrl
N5040
Adj-R20.348
Note: The t-statistic is indicated in parentheses. The symbols *** represent significance at 1% levels.
Table 6. Robustness test results.
Table 6. Robustness test results.
VariableDCC
esg−0.003 ***
(−5.11)
Size0.000 ***
(1.75)
Growth0.000
(1.39)
Fix0.056 ***
(35.89)
LarOwn−0.024 ***
(−10.69)
Balance−0.006 ***
(−5.20)
Board−0.000
(−0.23)
YearCtrl
IndCtrl
N6300
Adj-R20.369
Note: The t-statistic is indicated in parentheses. The symbols *** represent significance at 1% levels.
Table 7. Mechanism analysis of the impact of corporate ESG performance on debt capital cost.
Table 7. Mechanism analysis of the impact of corporate ESG performance on debt capital cost.
VariableRiskDCC
ESG−0.201 ***
(−5.91)		−0.001 ***
(−4.17)
Risk 0.002 ***
(13.88)
Size0.635 ***
(14.64)		−0.000 *
(−1.95)
Growth−0.119 **
(−2.20)		0.000 **
(2.13)
Fix11.044 ***
(40.07)		0.038 ***
(21.65)
LarOwn−2.740 ***
(−7.00)		−0.020 ***
(−8.97)
Balance−1.057 ***
(−5.72)		−0.004 ***
(−3.82)
Board0.405 *
(1.94)		−0.001
(−0.80)
YearCtrlCtrl
IndCtrlCtrl
N63006300
Adj-R20.5190.420
Sobel test−0.000 ***
(Z = −5.599)
Goodman test 1−0.000 ***
(Z = −5.593)
Goodman test 2−0.000 ***
(Z = −5.605)
Mediating effect coefficient−0.000 ***
(Z = −5.599)
Direct effect coefficient−0.001 ***
(Z = −4.233)
Total effect coefficient−0.001 ***
(Z = −5.612)
Mediating effect ratio/%27.0
Note: The t-statistic is indicated in parentheses. The symbols *, ** and *** represent significance at the 10%, 5% and 1% levels, respectively.
Table 8. Heterogeneity regression analysis of corporate ESG performance on debt capital cost.
Table 8. Heterogeneity regression analysis of corporate ESG performance on debt capital cost.
IndustryPolluting EnterprisesNon-Polluting EnterprisesState-OwnedNon-State-Owned
VariableDCCDCCDCCDCC
ESG−0.000
(−1.06)		−0.001 ***
(−5.19)		0.000
(1.51)		−0.001 ***
(−3.52)
Size0.001 ***
(2.73)		0.000
(0.95)		0.000
(1.39)		0.001 **
(2.30)
Growth0.002 *
(1.86)		0.000
(0.17)		0.001
(1.63)		0.000
(0.88)
Fix0.068 ***
(23.87)		0.050 ***
(26.02)		0.047 ***
(23.04)		0.064 ***
(26.09)
LarOwn−0.019 ***
(−4.37)		−0.027 ***
(−9.94)		−0.014 ***
(−4.74)		−0.024 ***
(−6.21)
Balance−0.008 ***
(−3.75)		−0.005 ***
(−3.49)		−0.004 ***
(−2.86)		−0.009 ***
(−5.02)
Board0.000
(0.23)		−0.001
(−0.93)		0.003 *
(1.89)		0.002
(0.80)
YearCtrlCtrlCtrlCtrl
IndCtrlCtrlCtrlCtrl
N1930422529703090
Adj-R20.4300.3290.4750.363
Note: The t-statistic is indicated in parentheses. The symbols *, ** and *** represent significance at the 10%, 5% and 1% levels, respectively.
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Yan, Y.; Cheng, X.; Ong, T. Unravelling the Missing Link: Climate Risk, ESG Performance and Debt Capital Cost in China. Sustainability 2024, 16, 7137. https://doi.org/10.3390/su16167137

AMA Style

Yan Y, Cheng X, Ong T. Unravelling the Missing Link: Climate Risk, ESG Performance and Debt Capital Cost in China. Sustainability. 2024; 16(16):7137. https://doi.org/10.3390/su16167137

Chicago/Turabian Style

Yan, Yu, Xinman Cheng, and Tricia Ong. 2024. "Unravelling the Missing Link: Climate Risk, ESG Performance and Debt Capital Cost in China" Sustainability 16, no. 16: 7137. https://doi.org/10.3390/su16167137

APA Style

Yan, Y., Cheng, X., & Ong, T. (2024). Unravelling the Missing Link: Climate Risk, ESG Performance and Debt Capital Cost in China. Sustainability, 16(16), 7137. https://doi.org/10.3390/su16167137

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