Green Response: The Impact of Climate Risk Exposure on ESG Performance

Abstract

Climate risk’s effects on society and economic development are becoming more pronounced, and enterprises have to seize the opportunity for green transformation. Based on public company data from 2011 to 2022, this study explores the causal relationship between climate risk exposure (CRE) and ESG performance by using a two-way fixed effect mode. The results indicate that CRE significantly enhances firms’ ESG performance, which makes improvements in environmental practices. The impact of the promotion is particularly pronounced in state-owned and low-polluting businesses. In addition, it can improve ESG through potential impact channels, such as employing environmental executives, improving environmental protection, and boosting green innovation. Meanwhile, the digital level and financing constraints of enterprises play an effective moderating role. Further discussion shows that the increase in CRE has prompted firms to fulfill environmental responsibilities and reduce carbon emissions. This study provides new quantitative evidence on how firms respond to climate risk, expanding the existing research on ESG performance. It further examines the specific impact path of climate risk on companies’ and green transformation and provides more firm-level insights for policymakers to address climate change. These results enrich the theoretical system of climate risk management and help enterprises strengthen awareness of climate risk to cope with sustainable development.

1. Introduction

With the frequent occurrence of extreme weather events, climate risk has become a challenge that cannot be ignored. Climate risk refers to the uncertainties caused by climate change that affect socio-economic and financial activities, as well as the resulting financial risks. This type of risk encompasses a wide range of economic, social, and environmental issues directly or indirectly induced by climate change, including the increased frequency and intensity of extreme weather events, rising sea levels, ecosystem degradation, and fluctuations in agricultural production. Such risks can be externally driven, for instance, through the imposition of stricter environmental regulations by governments in response to climate change, which places additional pressure on businesses. Internally, these risks may manifest through impacts on corporate assets, operations, and market performance, thereby heightening a company’s overall risk exposure. As the mainstay of social and economic activities, enterprises not only have to cope with the risks of natural disasters, resource shortages, and market fluctuations caused by climate change but also shoulder the heavy responsibility of promoting sustainable development. Given the escalating climate dangers, how to comprehensively improve ESG performance has become a core issue related to survival and long-term development. Therefore, a thorough discussion of the link between them is intended to provide practical support for risk management strategies and green transformation.

Climate risk’s impact on social development is complex and multidimensional, mainly including economic and environmental aspects. The former believes that climate risk could increase corporate equity cost [1], energy price [2], and the decrease of bond return rate [3]. The latter believes that climate risk may lead to an increase in regional drought severity [4] or inhibit firms’ environmental transformation measures [5]. Firstly, the discussion on climate risk exposure remains mostly at the macro market level, and the discussion on micro corporate decision-making is still lacking. Secondly, existing research has primarily focused on indirect factors affecting overall corporate performance, often overlooking whether firms assume direct environmental responsibilities. In fact, as climate risk events become more frequent, companies are increasingly burdened with higher operational costs, such as energy procurement and risk mitigation expenses. These costs can have a profound impact on a firm’s overall performance. Currently, ESG performance is closely linked to corporate environmental practices, social responsibility, and governance behaviors, gradually becoming a new benchmark for assessing corporate sustainability and potential for high-quality development. Within this framework, environmental governance practices are considered one of the core elements of ESG ratings, directly influencing overall ESG performance. As global awareness of climate risk has significantly increased, companies that demonstrate strong environmental governance often receive higher ESG ratings, thereby attracting greater interest and favor from investors. Conversely, companies with poor environmental performance may face the risk of declining ESG ratings, which can impose additional pressure on their operations. Therefore, exploring the intrinsic relationship between climate risk exposure and ESG is important. However, few studies have examined the impact of CRE on ESG performance, and the relationship between the two needs to be further explored.

In anticipation of significant losses due to climate risk, enterprises may take a range of measures to improve ESG rating [6]. First, companies are likely to employ managers with green backgrounds to develop effective green strategies [7]. Second, in the face of public and government pressure, enterprises may improve investment in environmental protection to solve environmental problems in the short term. From the perspective of long-term sustainable development, enterprises may be committed to green innovation activities, that is, to improve production processes to achieve green governance from the source [8]. In addition, since the improvement of ESG performance can bring positive effects to enterprises, the motivation of enterprises to improve ESG performance can also contain a potential benefit drive. This means that while pursuing environmental responsibility and social contribution, enterprises are also enhancing their market competitiveness and brand value by improving ESG performance [9].

Therefore, we explore the relationship between CRE and ESG. Firstly, the study investigates how exposure to climate risk might enhance ESG performance using a panel model. Secondly, we investigate the impact channels, including green innovation, green investment, and CEOs with environmental backgrounds, using the mediating effect model. At the same time, it also examines the moderation role of digitalization level and financing constraints. In addition, we investigate the heterogeneity of CRE’s impacts on different types of firms. Lastly, an in-depth examination reveals that climate risk exposure could prompt enterprises to fulfill their environmental responsibilities and reduce carbon emissions effectively.

There are three marginal contributions in this paper: First, the enterprise climate risk exposure index is constructed in this study using a textual analysis approach based on the annual report of public firms. This innovative approach provides new insights for the quantification of climate risk exposure at the firm level. Second, this study combines CRE with corporate ESG performance into a cohesive research framework, offering new micro-level evidence to enhance the understanding of the relationship between risk management and environmental transformation. Third, the study thoroughly examines the corporate decision-making process regarding climate risk and ESG performance, addressing both source and endpoint governance. It can improve ESG from potential impact channels such as employing environmental executives, improving environmental protection, and boosting green innovation. Fourth, the research explores the moderating effects of digital transformation and financing constraints, providing new perspectives and insights for managing corporate ESG performance and informing policy development.

The following section identifies the article’s primary structure: Section 2 summarizes the literature; Section 3 is related to the theory and hypothesis; Section 4 is the research design; Section 5 is the results of empirical results; Section 6 is a further discussion; Section 7 presents conclusions.

2. Literature Review

2.1. The Economic and Social Impacts of Climate Risk

Climate risk has been recognized as one of the most serious challenges to global economic development [10]. The literature currently in publication concentrates on the environmental and economic impacts of CRE. In terms of economic impacts, climate risk can affect equity capital [1], stock return [11], bond return [3], bank loans [12], and agricultural prices [13]. For example, Rong et al. [11] argued that CRE has a U-shaped impact on both clean energy equities’ volatility and return. In terms of its environmental impact, climate risk could affect green innovation [14], carbon risk [15], green credit [16], green transition [17], clean energy use [18], and other aspects related to the environment. For example, Fang [17] employs textual analysis to construct a company-level climate risk exposure index and proposes it can accelerate the process of green transformation of firms by promoting funding in R&D and improving supply efficiency. Existing research has primarily focused on the indirect factors through which climate risk affects corporate overall performance without directly examining whether companies are assuming environmental responsibility. This gap highlights the need for further investigation.

2.2. Research on Factors Influencing ESG Performance

In exploring the factors that influence corporate ESG performance, one area of interest is the interaction between internal corporate governance and the external environment. The current research is mainly conducted from two dimensions: internal governance and external influence. In terms of internal governance, the research covers multiple elements such as technological innovation, digital transformation, board structure, and energy input. According to Zhang et al. [19], digital technology transformation can enhance the positive link between environmental protection regulations and ESG. Regarding outside influences, these studies looked at factors such as investor concern, market competition, environmental taxes, and economic uncertainty. Jiang et al. [20] pointed out that environmental tax policies may lead to false ESG behavior in enterprises. In addition, ESG performance itself is also an important indicator for evaluating corporate behavior. Studies by Ma and Ma [21] and Qian and Liu [22] highlight this point. Tsang et al. [23] found that hostile takeovers can be successfully avoided by enhancing ESG performance, while corporate “greenwashing” behavior, i.e., false ESG performance, can result in higher corporate debt financing expenses. Although research on ESG has been relatively comprehensive, studies examining how exposure to climate risk influences corporate environmental responsibility strategies remain limited. Moreover, existing research addresses ESG performance from a macro perspective, with insufficient exploration at the micro level.

To sum up, existing literature has explored climate risk and ESG performance, respectively, but there are still the following gaps: First, the economic impact of climate risk is mostly focused on the macro level, and research at the corporate level is lacking; second, the environmental impact of climate risk is mainly focused on indirect factors to improve the environment and few studies that quantify how exposure to climate risk directly affects a company’s environmental responsibilities; third, there is currently no consensus on the quantification of CRE indicators. There is still some room for debate about the accuracy and applicability of the indicators used in different studies to measure companies’ response to climate risk.

3. Theoretical Analysis and Research Hypothesis

Climate risk exposure (CRE) refers to the degree to which an enterprise is exposed to climate risks. CRE is closely linked to ESG performance, as it not only affects a company’s current financial performance but also impacts its long-term market competitiveness and survival prospects. From the perspective of sustainable development, climate risks not only directly influence a company’s economic interests but also exacerbate environmental regulations, thereby further restricting access to financial resources [24]. On the other hand, an increase in CRE may compel companies to bear higher compliance costs and expose them to legal and financial risks arising from changes in environmental regulations. According to the theory of corporate competitiveness, CRE is viewed as a driving force that motivates companies to adopt strategies aimed at avoiding potential economic losses. Specifically, to enhance investor confidence and broaden funding sources, corporate management may focus more on improving the company’s ESG performance as a means of building a positive corporate image [25]. From the perspective of policy expectations, enterprises send environmentally friendly signals to the government by improving ESG performance, aiming to avoid stricter regulatory measures and financing restrictions caused by environmental risks [26]. From the perspective of long-term governance, a company’s green innovation can reduce costs and resource waste, thereby enhancing production efficiency. According to the conclusions of Porter’s hypothesis, the long-term benefits derived from green innovation can offset the associated innovation costs while also potentially improving product quality and profitability. This leads to sustained productivity growth. Therefore, when corporate environmental responsibility is elevated, decision-makers, considering long-term benefits, are more likely to support green innovation initiatives, intending to limit pollution emissions at the production source and secure long-term production gains [27]. Considering the aforementioned analysis, we propose the following:

Hypothesis 1.

The CRE can improve ESG performance.

Faced with the triple pressures of risk exposure, declining valuations, and environmental regulations, companies urgently need to develop effective environmental governance strategies to address these crises. First, the inclusion of executives with an environmental background can support the company’s need for green transformation decisions. These executives, with their extensive environmental knowledge and professional expertise, can deeply understand both environmental risks and opportunities. This understanding helps guide the company in selecting more environmentally friendly business models during strategic decision-making, strengthening the sense of social responsibility within the corporate culture, and ultimately improving the company’s ESG rating. Furthermore, the presence of executives with an environmental background increases the likelihood of ESG-related proposals being approved at shareholder meetings, facilitates the establishment of robust environmental and social responsibility management systems, and ensures that the company’s business activities remain in compliance with ESG requirements over the long term [28]. Second, after defining green response strategies, enterprises may take a series of specific governance actions to deal with the current severe climate crisis [29]. Among these, environmental investment is the most direct green measure. Environmental investment primarily involves the construction and renovation of facilities for the treatment of industrial pollutants, such as wastewater and exhaust gases. This direct management of pollution not only holds companies accountable for their environmental responsibilities but also aligns with the growing market demand for green products. Such actions enhance the company’s green image and market competitiveness, thereby directly improving its ESG performance [30]. Finally, in consideration of long-term interests, corporate executives may be inclined to make green production decisions that align with the principles of sustainable development. Green production decisions refer to those adopted by management, such as the implementation of green production technologies, the promotion of eco-friendly product designs, or the establishment of long-term partnerships with environmentally conscious companies. These decisions can guide the overall industrial system toward a green transformation, thus achieving the sustainable goal of simultaneously realizing economic and environmental benefits. Therefore, we propose the following:

Hypothesis 2.

The CRE can improve ESG performance through hiring environmental executives, increasing environmental protection investment, and boosting green innovation.

Digital technology has triggered a comprehensive change in enterprises’ production and operation modes [31]. Specifically, companies can leverage 5G and industrial Internet infrastructure platforms to transform operational data into high-efficiency information flows. By utilizing digital technologies such as artificial intelligence, cloud computing, and blockchain, complex relationships between data can be evolved into a company’s knowledge system. This enables firms to gain a more accurate understanding of market demands and sales forecasts, facilitating the rapid alignment of product supply and demand. Consequently, unnecessary energy consumption and carbon emissions can be reduced, leading to the optimization of ESG performance. In addition, the introduction of digital information technology can save enterprise research and development costs, and the rapid flow of information enables enterprises to take small steps to trial and error and iterate quickly, strengthening green innovation capability [32]. Another important factor affecting enterprises’ green governance activities is financing constraints [33]. If the enterprise itself is faced with high financing constraints, then when it suffers from climate risk losses or has a high degree of environmental regulation, the enterprise lacks sufficient funds for source and end management, so it is difficult to improve its environmental condition and its ESG performance. In addition, high financing constraints may lead to “short-sighted” behaviors of enterprises, such as cutting long-term investments with high uncertainty (including green technology innovation) or false green behaviors to improve corporate performance in the short term [34]. Businesses will gain from this practice in the short term, but as information flows and banks’ environmental oversight gradually increases, businesses’ false greenwashing will impede their ability to improve their ESG performance and permanently harm their reputations in the wider community. Therefore, we propose the following:

Hypothesis 3.

Enterprise digitalization and financial limitations may limit CRE’s ability to improve business ESG performance.

The research framework for this paper is shown in Figure 1. Figure 1, from left to right, illustrates the research logic of this study. First, it examines the impact of CRE on the real economy from both economic and environmental perspectives. Building on existing research, it explores the role of CRE in enhancing corporate ESG performance (H1). Second, the study innovatively proposes three mediating channels—green innovation, the number of executives with an environmental background, and environmental investment (H2). It also investigates the moderating effects of digitalization and financing constraints (H3). Finally, the study extends its analysis by considering corporate heterogeneity and environmental governance performance.

4. Research Design

4.1. Data and Sample

This study takes the data of A-share listed enterprises from 2011 to 2022 as research samples, and all the information comes from CSMAR databases. To ensure the quality of sample data, ST* enterprises and sample enterprises with seriously missing data are excluded. To prevent extreme values from interfering with the calculated results, all data are indented by 1%. The final sample covered a total of 4809 companies, with a total of 37,015 data. Among them, enterprise ESG performance has a standard deviation of 0.968, a maximum of 6, and a minimum of 1.250. The data distribution fluctuates greatly. The range of corporate CRE is 0.274, with little fluctuation in data distribution.

Table 1. Descriptive statistics.

VarName	Unit	Obs	Mean	Median	SD	Min	Max
ESG	-	37,015	4.134	4.000	0.968	1.250	6.000
CRE	%	37,015	0.202	0.101	0.274	0.000	1.515
Age	year	37,015	10.948	9.000	7.801	1.000	29.000
Size	-	37,015	22.268	22.023	1.434	19.741	27.294
Roe	%	37,015	0.054	0.069	0.143	−0.837	0.333
Lev	%	37,015	0.426	0.413	0.216	0.051	0.941
Roa	%	37,015	0.036	0.037	0.065	−0.276	0.204
Tobin	%	37,015	1.977	1.564	1.336	0.000	8.744

below shows the descriptive statistics.

4.2. Variable Description

4.2.1. Independent Variable

The independent variable is CRE, which refers to the exposure and response of enterprises to climate events and the potential risks they pose. Referring to [35], we use the following procedures to build the CRE level:

Firstly, we crawl the corporate annual reports of the selected firm through the Juchao Information Website (http://www.cninfo.com.cn, accessed on 12 June 2024). Secondly, by referring to Loughran and Mcdonald [36], we use the dictionary method and extract seed dictionary text related to climate risk, combing with the China Meteorological Disaster Yearbook, the information disclosed by the National Data Center for Meteorological Sciences, the seed word set for climate risk exposure is developed. Specifically, we extracted words identified as meteorological hazards in the yearbook, such as “climate change”, “extreme weather”, “sea level rise”, and other words directly related to climate risks. Then, we refer to the information in the yearbook and add words about specific disaster types, such as “flood disaster”, “drought disaster”, and “typhoon disaster” into the seed dictionary. We also added descriptive words related to climate risk exposure, such as “affected area”, “disaster loss”, etc., to form a complete set of climate risk exposure seed words. To improve the comprehensiveness and objectivity of the dictionary, we draw on the natural language learning model based on the neural network method proposed by Mikolov et al. [37] to add more words that are comparable to the seed word set. Finally, we determine the proportion between the total word frequency of the extended word set “climate risk” and construct a firm-level CRE index. In addition, we take a long-term rolling average of weather measures every three years, which both preserves long-term effects, such as slow-changing weather risks, and offsets short-term disclosure incentives, increasing the reliability of the data. The greater a company’s CRE index, the stronger the enterprise’s climate risk exposure.

4.2.2. Dependent Variable

Referring to Huang [38], the annual average of the Chindices ESG is chosen as the dependent variable. Three primary dimensions are covered by the ESG scoring system. To be specific, it includes fourteen sub-dimensions, twenty-six detailed dimensions, and more than 130 underlying data indicators. These underlying indicators are weighted together by the industry weight matrix to form the final ESG performance for each company, which is then divided into nine grades. Compared with other ESG evaluation systems, the Chindices ESG index includes more indicators closely related to China’s reform period in China, such as the effectiveness of focused reduction of poverty and the transparency of information disclosure, which can better reflect the performance of Chinese enterprises in operation and management.

4.2.3. Mediating Variables

Executives with Environmental Background (Eb). The personal characteristics of executives can affect their cognitive style, which in turn leads to different corporate decision-making. As a result, executives with an environmental background give greater weight to environmental goals in corporate decision-making. The study uses the text analysis method to determine whether the resumes of company executives contain “environment”, “green”, and other related terms [39]. If there are any, the value is assigned as 1. The proportion of environmental executives in each company was obtained as the index of the Eb.

Environmental Protection Investment (Ep). Ep is one of the most direct and effective ways to take part in environmental management, such as investment in environmental protection projects and the introduction of advanced pollution treatment technologies. Following Zhang et al. [40], we analyze the construction items in the firm’s annual reports to summarize the costs directly associated with protecting the environment. The total amount of foreign exchange is the growth data of the company’s environmental protection investment in the year. We make use of the proportion of total investment to total assets to measure Ep.

Green innovation (Gi). Enterprises’ green innovation refers to innovative activities carried out to meet environmental challenges and achieve specific environmental goals, including enterprises’ green product design and process innovation in waste recycling, pollution control, energy conservation, and other aspects, as well as organizational management support and innovative implementation. Following Ma et al. [41], we regarded the overall number of green patent applications it has filed as an index to quantify the level of green innovation. In addition, we regard the number of green invention patents granted by enterprises as the actual degree of green innovation of enterprises. Our purpose is to test whether enterprises achieve the expected environmental governance goals.

4.2.4. Control Variables

We controlled six ESG-related factors to guarantee the effect’s correctness. Following Niu et al. [42] and Tan et al. [43], the following variables are adopted as control variables:

Company age (Age) is measured by the logarithm of the number of years the company has been listed plus 1. The size of the enterprise (Size) is measured by the logarithm of the total assets of the enterprise. Return on equity (Roe) is the percentage of a company’s after-tax profits divided by its net assets. Corporate leverage (Lev) is expressed as the ratio of total liabilities to total assets. This indicator reflects the use of financial leverage and has a significant impact on financial risk. Return on assets (Roa) is a measure of the efficiency of the company’s operating return, usually expressed as the percentage of the company’s year-end net profit to total assets at the end of the year. Tobin (Tq) value is an important indicator for measuring the difference between the market value and the book value of the enterprise, reflecting the market’s expectations of the future profitability of the enterprise.

4.3. Model

4.3.1. Baseline Model

Referring to Gao et al. [44], this paper constructs a two-way fixed-effects panel model:

$${\mathrm{E}\mathrm{S}\mathrm{G}}_{\mathrm{i}\mathrm{t}}={\mathsf{\beta }}_0+{\mathsf{\beta }}_1{\mathrm{C}\mathrm{R}\mathrm{E}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\beta }}_2{\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\mu }}_{\mathrm{i}}+{\mathsf{\gamma }}_{\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$$

(1)

where ${\mathrm{E}\mathrm{S}\mathrm{G}}_{\mathrm{i}\mathrm{t}}$ is the explained variable, and subscripts i and t represent the firm $\mathrm{i}$ in the $\mathrm{t}$ period. The primary explanatory variable is ${\mathrm{C}\mathrm{R}\mathrm{E}}_{\mathrm{i}\mathrm{t}}$. ${\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i}\mathrm{t}}$ is the control variable, ${\mathsf{\beta }}_{\mathrm{i}}$ is the coefficient (including independent and control variables), while the residual term is ${\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$. Additionally, we account for time and individual-fixed influence to eliminate the influence of individual differences and time-varying factors, ${\mathsf{\mu }}_{\mathrm{i}}$ and ${\mathsf{\gamma }}_{\mathrm{t}}$.

4.3.2. Mediating Effect Model

The mediating effect model is constructed in this paper following Tan et al. [45].

$${\mathrm{M}}_{\mathrm{i}\mathrm{t}}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1{\mathrm{C}\mathrm{R}\mathrm{E}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\alpha }}_2{\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\mu }}_{2\mathrm{i}}+{\mathsf{\gamma }}_{2\mathrm{t}}+{\mathsf{\epsilon }}_{2\mathrm{i}\mathrm{t}}$$

(2)

$${\mathrm{E}\mathrm{S}\mathrm{G}}_{\mathrm{i}\mathrm{t}}={\mathsf{\rho }}_0+{\mathsf{\rho }}_1{\mathrm{C}\mathrm{R}\mathrm{E}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\rho }}_2{\mathrm{M}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\rho }}_3{\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\mu }}_{3\mathrm{i}}+{\mathsf{\gamma }}_{3\mathrm{t}}+{\mathsf{\epsilon }}_{3\mathrm{i}\mathrm{t}}$$

(3)

In the above formula, ${\mathrm{M}}_{\mathrm{i}\mathrm{t}}$ represents the mediation variables described in Section 4.2.3. According to the definition of the mediating effect model, Formula (3) examines the indirect relationship between the explanatory and mediation variables, while Formula (2) investigates the direct relationship between the explanatory and mediation variables. If the coefficients ${\mathsf{\beta }}_1$, ${\mathsf{\alpha }}_1$, and ${\mathsf{\rho }}_2$ are all significant, the impact channels are confirmed.

5. Empirical Results

The research logic of this section is as follows. First, we use panel models to investigate whether exposure to climate risk improves ESG performance and reconfirm conclusions with robustness tests. Second, we use the mediating effect model to examine the influence channels of green innovation, green investment, and managers with environmental backgrounds. At the same time, the moderation effects of digitization level and financing constraints are also investigated. The question of how to make an impact is answered. In addition, we also studied the heterogeneity of the impact of CRE on different types of firms. Finally, through in-depth research, it is found that climate risk exposure can motivate companies to reduce carbon emissions.

5.1. Baseline Regression

To exclude the potential interference of individual characteristics and time effects on the results, we investigate the relationship between CRE and corporate ESG performance by using a fixed-effects panel model. The empirical results are shown in

Table 2. The results of baseline regression.

	(1)	(2)	(3)	(4)	(5)	(6)
	ESG	ESG	ESG	ESG	ESG	ESG
CRE	0.183 ***	0.183 ***	0.112 ***	0.097 ***	0.071 **	0.071 **
	(0.031)	(0.031)	(0.031)	(0.031)	(0.031)	(0.031)
Age		−0.015	−0.012	−0.012	0.006	0.008
		(0.030)	(0.030)	(0.030)	(0.030)	(0.030)
Size			0.172 ***	0.166 ***	0.236 ***	0.229 ***
			(0.009)	(0.009)	(0.009)	(0.009)
Roe				0.289 ***	0.017	0.015
				(0.029)	(0.054)	(0.054)
Lev					−0.958 ***	−0.947 ***
					(0.038)	(0.038)
Roa					0.167	0.196
					(0.133)	(0.134)
Tobin						−0.013 ***
						(0.004)
Constant	4.184 ***	4.252 ***	0.546 **	0.643 ***	−0.546 **	−0.375
	(0.015)	(0.138)	(0.232)	(0.232)	(0.234)	(0.239)
Firm FE	YES	YES	YES	YES	YES	YES
Year FE	YES	YES	YES	YES	YES	YES
R2	0.122	0.132	0.214	0.276	0.427	0.483
N	37015	37015	37015	37015	37015	37015

Note: Standard errors in parentheses, *** p < 0.01, ** p < 0.05.

. Column (1) shows the baseline results without adding any control variables, while columns (2) to (6) show the empirical results after gradually introducing control variables. From the coefficient of the variable CRE, the coefficient of CRE is significant regardless of whether this control variable is included. In particular, the results in column (6) show that for every unit increase in climate risk exposure, firms’ ESG performance increases by an average of 0.071 units. These findings support hypothesis 1 that the increase in climate risk exposure can promote the improvement of enterprises’ ESG performance.

One possible explanation is that the environmental losses caused by climate risks have become key factors that decision-makers in corporations must take seriously, prompting them to reassess and adjust their company strategies to align with the long-term goal of sustainable development [46]. At the same time, the increasingly severe climate risk crisis has also drawn the attention of governments and the public to environmental issues, forcing companies to assume more environmental responsibility, thereby significantly improving ESG performance. From an economic perspective, this transformation not only helps companies mitigate potential climate-related risks but also enables them to attract more capital focused on sustainable investment by enhancing ESG performance. As a result, this can broaden financing channels and reduce financing costs. In the long run, it fosters a win-win situation, where both economic and environmental benefits are achieved, ultimately strengthening market competitiveness. The above conclusions are similar to Yu et al. [47].

5.2. Robustness Results

To test for robustness, we swap out the explanatory variable, exclude outlier data, and replace the estimation method. The results of the robustness tests are presented in

Table 3. Robustness tests.

	(1)	(2)	(3)	(4)	(5)
	Excluding Municipalities	ESG Median	Bloomberg ESG	Exclude 2015 to 2016	Replacing GMM
CRE	0.066 *	0.878 ***	0.012 ***	0.067 **	0.053 **
	(0.038)	(0.001)	(0.001)	(0.033)	(0.023)
L.CRE					0.038 **
					(0.016)
Constant	0.262	0.065	−0.610	−0.449 *	1.025 **
	(0.243)	(0.055)	(0.403)	(0.250)	(0.493)
Control	YES	YES	YES	YES	YES
Firm FE	YES	YES	YES	YES	YES
Year FE	YES	YES	YES	YES	YES
R2	0.413	0.375	0.252	0.418	0.492
N	26810	34261	10454	31773	33314

Note: Standard errors in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

.

First, compared to other cities, Beijing, Shanghai, Chongqing, and Tianjin have much greater levels of risk resilience in their municipalities. Therefore, the ESG performance of companies in these cities may be less affected by the impact of climate risks. To eliminate this estimation bias, we excluded the sample of companies registered in municipalities from the sample and conducted a robustness test. As shown in column (1) of Table 3, after excluding the sample of municipalities directly under the central government, the regression coefficient of CRE is still significant at the 10% level. This reconfirms that there is indeed a positive relationship between climate risk exposure and ESG after excluding the influence of municipalities, thus verifying the robustness of the baseline results.

Second, we also substituted the Bloomberg ESG index and the median of the ESG performances for the explanatory factors. As shown in columns (2) and (3) of Table 3, the coefficients of these alternative indicators are positive and significant. This further supports the positive relationship between CRE and firm ESG performance.

Third, referring to Liu et al. [48], we excluded all samples from 2015 to 2016 to exclude the possible impact of the stock market crash on corporate governance in these two years. As shown in column (4), even after removing these samples, the result is still valid; that is, the baseline regression results are robust.

Fourth, we have changed the estimation method of baseline regression and taken into account the impact of the lag term of CRE based on equation (1) due to its possible lag effect. Therefore, we use the Generalized Method of Moments (GMM) to regress the dynamic panel model, and the regression results are shown in column (5). It can be found that both CRE and its lag term are significantly positive at the level of 10%, which indicates that enterprises’ exposure to climate risk has a significant promoting effect on enterprises’ ESG performance. In summary, even considering the lag effect of CRE, these robustness tests further strengthen our confidence. These findings are similar to Naseer et al. [49].

5.3. Endogenous Test

To address potential endogeneity issues, such as bidirectional causality between variables, we adopt the method of Tian et al. [8] and choose the average climate risk exposure of other firms in the city where the firm is located as the instrumental variable (IV) (Iv_CRE). The reason for this is that, first, the average CRE of other firms in the same city satisfies the assumptions associated with the CRE of this firm since firms in the same region tend to face similar climate risks but may take different measures to manage them. In addition, the ESG performance of other companies cannot influence their exposure to climate risk. Therefore, Iv_CRE can be used as an instrumental variable. This is also an instrumental variable selection method commonly used in the existing literature. We used two-stage ordinary least squares for the estimation, and the specific results are shown in

Table 4. Endogenous tests.

	(1)	(2)
	First Stage	Second Stage
CRE		0.0844 ***
		(0.022)
IV_CRE	−0.2823 ***
	(0.001)
Constant	305.28 ***	0.198
	(0.611)	(0.215)
Control	YES	YES
Firm FE	YES	YES
Year FE	YES	YES
R2	0.904	0.166
N	32,759	32,759

Note: Standard errors in parentheses, *** p < 0.01.

. In column (1), the coefficient of the IV is significantly negative, indicating that there is an obvious negative relationship between it and CRE. Further, as shown in column (2), the coefficient on Iv_CRE remains positive, demonstrating that the positive effect of CRE on ESG remains robust even after addressing potential endogeneity issues. Overall, these results suggest that climate risk exposure continues to have a significant positive impact on firms’ ESG performance, even when endogeneity concerns are taken into account. The findings are similar to Feng et al. [50].

5.4. Mechanism Analysis

5.4.1. Impact Channels

The findings of the mechanism test are displayed in

Table 5. Mechanism tests.

	(1)	(2)	(3)	(4)	(5)	(6)
	Eb	ESG	Ep	ESG	Gi	ESG
CRE	0.117 ***	0.078 **	0.013 ***	0.055	0.132 ***	0.042
	(0.004)	(0.032)	(0.004)	(0.036)	(0.025)	(0.034)
Eb		0.107 **
		(0.050)
Ep				0.259 ***
				(0.062)
Gi						0.043 ***
						(0.008)
Constant	−0.045	−0.122	−0.125 ***	0.178	−0.862 ***	0.368 *
	(0.031)	(0.277)	(0.024)	(0.238)	(0.155)	(0.216)
Control	YES	YES	YES	YES	YES	YES
Firm FE	YES	YES	YES	YES	YES	YES
Year FE	YES	YES	YES	YES	YES	YES
R2	0.045	0.049	0.029	0.040	0.028	0.039
N	35,495	35,495	29,968	29,968	33,387	33,387

Note: Standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

. The estimation coefficient for environmental background executives (Eb) is positive and significant at the 1% confidence level in column (1). This finding suggests that increased CRE can expand the proportion of business executives with environmental backgrounds. The coefficient of Eb is also positive and significant, indicating that the increase in the proportion of executives with environmental backgrounds can actively promote ESG performance in column (2). A possible explanation is that under the multiple pressures brought by climate risk, enterprises may generate the need to develop environmental governance plans [29]. Consequently, companies tend to bring in executives with environmental experience who are more focused on ESG improvements. They can effectively enhance ESG performance by developing ESG strategies and reshaping the compensation incentive system [51]. The findings are similar to Qing et al. [52].

In column (3), the coefficient of Ep is positive and significant. The findings indicate that while the primary explanatory factors are not significant in column (4), the mediating variables are. This indicates that Ep plays a complete mediating role in the improvement of climate risk exposure to improving ESG performance. These results further confirm that CRE drives firms to increase environmental investments, thus improving their ESG performance. This may be because enterprises may adopt a series of governance measures after establishing a green response strategy. Among them, end treatment is the most direct green action, which involves environmental investment in heavily polluting projects, including desulfurization, waste gas treatment, and dust removal. These actions can lessen the direct impact of pollution emissions on the atmosphere and optimize corporate environmental performance. The findings are similar to Dutta et al. [2].

In column (5), the coefficient for CRE is significant, while the coefficient for green innovation is also significant in column (6). These results suggest that green innovation plays a fully mediating role in this process. The possible reason is that firms, motivated by preventive motivation and the pursuit of sustainable development, improve production processes or processes through independent research and development to achieve green governance at the source, thereby reducing pollution emissions in the course of production [53]. On another level, the application of green technology possesses the capacity to enhance resource use efficiency and productivity within firms in the long run, optimize business conditions, and thus improve enterprises’ ESG performance. The above conclusions are similar to Ren et al. [54]. In summary, hypothesis 2 is verified, that is, the improvement of CRE improves ESG performance through hiring environmental executives, encouraging green innovation, and investing more in environmental protection.

5.4.2. Moderation Effect

Following Tang et al. [55], we chose the Peking University Digital Financial Inclusion Index as a substitution variable to measure the level of digitalization (Dig). Specifically, column (1) of

Table 6. Moderation effect test.

	(1)	(2)
	ESG	ESG
CRE	0.024	2.934 ***
	(0.072)	(0.387)
Dig	−0.007
	(0.009)
CRE × Dig	0.080 **
	(0.037)
SA		−0.527 ***
		(0.077)
CRE × SA		−0.744 ***
		(0.099)
Constant	0.888 ***	2.277 ***
	(0.301)	(0.349)
Control	YES	YES
Firm FE	YES	YES
Year FE	YES	YES
R2	0.343	0.442
N	21,778	33,326

Note: Standard errors in parentheses, *** p < 0.01, ** p < 0.05.

shows the moderating role of a firm’s level of digitization. The interaction term’s coefficient is significant, suggesting that enterprise digitization level significantly enhances the positive link between CRE and enterprise ESG. A possible explanation is that the rapid development of digital technologies has facilitated the deep integration of technology with products and services, thereby innovating traditional management and innovation models. These advancements enable companies to better understand user needs, optimize decision-making, and enhance operational efficiency while also fostering cross-sector collaboration and innovation [56]. For instance, companies can leverage big data to analyze consumer purchasing habits, deliver targeted product recommendations, optimize inventory management, and reduce production redundancies and pollution emissions during manufacturing. Consequently, we may say that the more digitization there is, the greater the impact of CRE on ESG. The above conclusions are similar to Kwilinski et al. [57].

Following He et al. [58], we choose the absolute value of the SA index as a proxy variable to measure the financing status of firms. In the empirical analysis, we discussed the data in Table 6 in detail. Column (2) shows that the coefficient of the interaction term between financing constraints and climate risk level is negative, indicating that higher financing constraints have a weaker positive impact on ESG performance. According to the theory of resource allocation, the more abundant the firm’s capital, the more effectively the investment decision will be implemented, which is conducive to improving the firm’s financial performance. On the other hand, if a company faces high financing constraints, the financial crisis will be more pronounced. To protect their interests, investors will reduce investment or even not invest, which ultimately hinders the improvement of the firm’s financial performance. Companies with higher financial constraints may have insufficient cash flow to effectively cope with losses from climate risk. Even if these companies implement good governance measures, their governance effects may not be as effective as those of well-funded companies due to insufficient funds. According to risk management theory, ESG responsibility performance helps companies manage environmental and social risks effectively, and the intensification of funding constraints will limit companies’ access to capital and investment capabilities and affect companies’ response to and management of climate risks. We can, therefore, conclude that companies with fewer financial constraints benefit more from the positive effects of climate risk on ESG performance. This finding highlights the critical role that financial constraints play in how companies respond to climate risk and improve their ESG performance. The above conclusions are similar to Bai et al. [59].

6. Further Discussion

6.1. Heterogeneity Test

Differences in the nature of the industries in which companies operate have a significant impact on their ability to respond to climate change. Specifically, those enterprises with higher levels of pollution tend to produce a lot of pollutants in the production process, so they are more likely to be constrained and punished by environmental regulations. This situation could exacerbate financing constraints for these companies, which in turn could negatively impact their operations in the face of climate risks, limiting resource mobilization and the ability to make a green transition [60]. In addition, due to the high emission intensity of heavy polluters, the corresponding pollution control costs are also high, which further increases their operating pressure and affects their ESG performance. According to Shi et al. [61], companies can be classified into heavy polluters and non-heavy polluters based on their industry codes. In

Table 7. Heterogeneity tests.

	(1)	(2)	(3)	(4)
	Heavy Enterprises	Non-Heavy Enterprises	State-Owned Enterprises	Non-State-Owned Enterprises
	ESG	ESG	ESG	ESG
CRE	0.040	0.325 ***	0.159 **	−0.022
	(0.123)	(0.088)	(0.063)	(0.046)
Constant	1.198 *	0.178	−0.558	0.341
	(0.650)	(0.314)	(0.374)	(0.287)
Control	YES	YES	YES	YES
Firm FE	YES	YES	YES	YES
Year FE	YES	YES	YES	YES
R2	0.057	0.092	0.034	0.057
N	5565	15,027	12,790	21,048

Note: Standard errors in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

, the coefficient of (1) is 0.04, which is not statistically significant. However, at the 1% confidence level, the coefficient of (2) is 0.325 and statistically significant, indicating that non-heavy polluters are more likely than polluters to recognize the importance of CRE in improving ESG performance.

The impact of CRE on ESG is also different among enterprises of different ownership. Specifically, state-owned enterprises generally have relatively strong financial strength and sufficient capital sources and can invest a lot of money in green technology research and development, equipment renewal, and industrial upgrading. Secondly, state-owned enterprises have strong strengths in technology research and development and innovation and can dispatch better resources to carry out source and end management. Finally, soes can respond more quickly than non-soes to policy intentions, prepare for sustainable development earlier, and respond more quickly and flexibly to climate risks. Therefore, referring to Cheng and Wu. [62], we separated companies between entities that are state-owned or not and conducted empirical tests, respectively. In Table 7, (3) and (4) are listed as heterogeneity results. The coefficients of CRE in column (3) are positively significant, while those in column (4) are not. This result confirms the above viewpoint: in state-owned enterprises, CRE has a more significant effect.

6.2. Carbon Reduction Effect

When a firm’s ESG performance improves, a progressive increase can be observed in the number of environmental actions it undertakes [63]. However, a comprehensive assessment of whether a firm has achieved its stated environmental goals depends on specific carbon emissions data. Specifically, the main sources of carbon emissions may be separated into four parts: (1) carbon in combustion and energy fuels, including fossil fuels and biomass fuels; (2) emissions from the manufacturing process; (3) emissions from land use change; (4) emissions from solid waste incineration and wastewater treatment. Referring to Yan et al. [64], to verify whether the positive effect of CRE on companies’ ESG performance translates into environmental benefits rather than just an improvement in ESG performances, we introduced an interaction term between the level of CRE and ESG performance in the benchmark regression model. In addition, we perform a regression analysis on the company’s total carbon emissions and those of its four main sources.

Table 8. The result of further discussion.

	(1)	(2)	(3)	(4)	(5)
	Total	Energy	Production	Land	Emission
CRE × ESG	−0.086 ***	−0.110 ***	−0.110 ***	−0.105 ***	−0.113 ***
	(0.021)	(0.024)	(0.024)	(0.025)	(0.025)
CRE	0.027 ***	0.033 ***	0.031 ***	0.036 ***	0.033 ***
	(0.006)	(0.007)	(0.007)	(0.007)	(0.007)
ESG	0.450 ***	0.539 ***	0.545 ***	0.519 ***	0.557 ***
	(0.091)	(0.103)	(0.106)	(0.111)	(0.107)
Constant	−11.927 ***	−4.755 ***	−6.360 ***	−6.285 ***	−6.226 ***
	(0.144)	(0.163)	(0.166)	(0.175)	(0.169)
Control	YES	YES	YES	YES	YES
Firm FE	YES	YES	YES	YES	YES
Year FE	YES	YES	YES	YES	YES
R2	0.472	0.455	0.444	0.417	0.435
N	27,411	27,411	27,411	27,411	27,411

Note: Standard errors in parentheses, *** p < 0.01.

shows the empirical regression results of total carbon emissions and its four sub-items. At the 1% significance level, the indices in columns (1)–(5) are all significantly negative, confirming that the driving effect of CRE on the firm’s green governance is indeed conducive to achieving the expected environmental protection goals. A possible explanation is as follows: First, CRE can facilitate the energy transition process within companies, promoting the use of clean energy and thereby reducing carbon emissions from an energy consumption perspective [65]. Second, the exposure to climate risk encourages green innovation activities within firms [66], enhancing production efficiency in manufacturing companies and optimizing land use efficiency in agricultural enterprises, which in turn helps reduce carbon emissions from both manufacturing processes and land use. Finally, the exposure to climate risk stimulates green investments and incentivizes end-of-pipe pollution control measures, further reducing carbon emissions from direct emissions sources.

7. Conclusions

Based on panel data of listed companies from 2011 to 2022, this study provides an in-depth discussion on the impact of climate risk exposure (CRE) on corporate ESG performance and how it works. The main findings of the study are as follows: First, there is a positive correlation between CRE and ESG performance, and this result remains significant after robustness tests. This suggests that increased climate risk may prompt companies to place more emphasis on ESG practices. Second, CRE can improve ESG performance by hiring executives with environmental backgrounds, increasing environmental investments, and enhancing green innovation capabilities. In addition, the level of digitization and financing constraints have a significant moderating effect on this promotion. Third, in non-heavy polluting enterprises and state-owned enterprises, the positive impact of climate risk exposure on ESG performance is more significant. This may be related to the regulatory environment and social responsibility these companies face, making them more focused on ESG practices in the face of climate risks. Finally, in the context of frequent climate risk events, enterprises have successfully achieved carbon reduction through effective environmental responsibility. This shows that companies can not only reduce their negative impacts dealing with climate risks but also promote green transformation and make a positive contribution to achieving the country’s two-carbon goal.

The limitations and future directions of this paper lie in the following three levels. First, the influence mechanism of this paper is not comprehensive enough. Factors influencing ESG performance are multidimensional, including but not limited to internal governance structure, corporate culture, industry characteristics, market environment, etc. Future studies may consider incorporating these factors into an analytical framework to gain a more comprehensive perspective. Second, the ESG performance of an enterprise is affected not only by its behavior but also by the behavior of other enterprises in its supply chain and industrial chain. For example, the environmental behavior and social responsibility performance of suppliers may indirectly affect the ESG evaluation of the purchasing company. Therefore, future studies can explore the mechanism of ESG performance transmission at the supply chain and industrial chain levels. Finally, future studies may subdivide CRE into three dimensions: climate perception, risk intervention, and governance behavior. Because the company may have inconsistent words and deeds, the impact of these three dimensions on the enterprise is worth exploring.

Therefore, we provide targeted policy recommendations from the perspectives of government, business, and society. Firstly, in the background of addressing climate change governance, the role of government is crucial, particularly in enhancing climate risk assessment and disclosure mechanisms. Governments should establish stringent policies requiring firms to conduct regular climate risk assessments and publicly disclose relevant information. This process necessitates that companies evaluate their operations’ sensitivity to climate change and assess the potential long-term impacts of climate change on their development. By establishing standardized evaluation criteria and disclosure frameworks, information asymmetry among businesses, the public, and financial institutions can be reduced. This not only enhances corporate transparency but also enables investors and consumers to make informed decisions based on comprehensive information. Furthermore, such mechanisms can encourage companies to adopt more proactive measures for adapting to and mitigating climate change, thereby steering the entire economic system toward more sustainable practices. Consequently, the government’s role in facilitating climate risk assessment and disclosure cannot be overlooked, as it is significant for encouraging the economy’s green transition and enhancing overall societal resilience to climate change. Governments also need to strengthen international cooperation, share climate risk assessment experience, jointly improve the effectiveness of global climate governance, and make greater contributions to addressing the challenge of climate change. Under the concept of a community with a shared future for mankind, governments also need to strengthen international cooperation, share climate risk assessment experience, jointly improve the effectiveness of global climate governance, and make greater contributions to addressing the challenge of climate change.

Secondly, companies should strengthen the prevention and management of climate risks. Corporate management must recognize the profound impact of climate risks on business operations and take proactive measures to address them. Climate risk management should be integrated into corporate strategic planning and daily operations, with regular assessments of its potential impact on business activities, supply chains, and financial performance. Efforts to drive green transformation should be intensified, including investments in clean energy and low-carbon technologies, optimization of energy structures, and the enhancement of product and service environmental performance to meet market demand for green products. Additionally, collaboration with supply chain partners should be reinforced to jointly address climate risks and promote the transition of the supply chain towards a low-carbon and environmentally friendly model. Finally, training and education programs should be implemented to increase employee awareness of climate risks and ESG performance, encouraging active participation in environmental initiatives and fostering a green culture within the organization. These measures will help improve ESG performance and strengthen the company’s ability to achieve sustainable development.

Thirdly, various sectors of society should strengthen oversight of corporate ESG practices, encouraging continuous improvement in environmental protection, social responsibility, and corporate governance. The public can actively promote ESG principles through media, social platforms, and other channels, advocating for green consumption and selecting products and services from companies with strong ESG performance. Simultaneously, investors and financial institutions should place greater emphasis on corporate ESG performance in their investment decisions, providing more support to companies committed to sustainable development and addressing climate risks. Furthermore, governments and relevant institutions should implement additional policies and measures to encourage companies to enhance their ESG performance, fostering a positive environment where all sectors of society collectively drive the advancement of corporate ESG initiatives.