From risk to resilience: Climate change risk, ESG investments engagement and Firm's value (2024)

2.1. Climate change risk, and firms value

It has long been acknowledged and thoroughly documented that climate has a significant impact on financial and economic outcomes, as evidenced by studies such as those conducted by Refs. [15,20,[36], [37], [38]].These studies have predominantly focused on scrutinizing the country-level climate-related risk at various geographic levels, ranging from nations to cities. The escalating global concern regarding climate change has spurred investigations into the ways in which the environment can influence the valuation of companies, with research contributions from scholars like [22,39,40]. Using a large sample of enterprises in 35 countries from 2001 to 2021, they found a negative correlation between climate risk and firms' performance [15]. In a related line of research, the researchers investigated climate change risk & firms' leverage adjustments and information efficiency. They concluded that firms in countries with more robust environmental protection and higher quality policies have a stronger favorable association [21]. Using a sample of 42 developing countries, they demonstrated a strong correlation between climate change risk and the unpredictability of monetary policy [20]. US firm-year sample from 2002 to 2018 documented that CSR mitigates climate change risk by employing regression-based modeling. It passes several econometric validation tests, including a difference-in-difference test, propensity score matching, entropy balancing, system GMM, and modified regression. CSR reduces FCCR more for enterprises with higher ESG disclosure. The study findings support CSR's value-enhancing paradigm [4]. A recent study was conducted to examine how corporations respond to natural disasters in terms of ESG disclosure. They demonstrated that corporations strategically raise their ESG disclosures after natural disasters to change investors' perceptions of the firm [41]. Some studies tested the linkage between bond returns and climate change-related news [42]. For instance, few studies demonstrated a mixed association [43].

Recently [44], investigate the impact of FCCR on FV, utilizing publicly listed US firms' data for the period 2012–2021. The results of this research suggest a negative relationship between FCCR and FV. In a related study within the energy industry [45], analyze panel data from 2010 to 2020, revealing a negative association between FCCR and market capitalization, while also noting a positive correlation between dividend yield and FV. In brief, the relationship between FCCR and FV is inadequately explored, underscoring the necessity to investigate the impact of FCCR on FV. We utilize an innovative FCCR developed by Ref. [3].This measure assesses a company's exposure to climate-related opportunities, physical impacts, and regulatory challenges. In addition, As our literature review reveals, past studies predominantly focus on a firm's existing performance metrics, such as ROA and ROE, subject to accounting limitations, rather than on FV [46]. In this study, we apply two measures two measure Value. First, we use Tobin's Q is often used as an indicator of investment opportunities [28,47]. Second, according to the real options approach, a company's overall value is determined by combining the value of its current businesses with the value associated with its growth opportunities, and it is a more direct measure of GV [23,28,48,49]. To address first gap, we formulate our first hypotheses is as under.

2.2. Environmental social and governance (ESG) investments and firms’ value

Sustainable finance entails integrating ESG investments into a company's business strategy. Investors with a social conscience evaluate potential investments by examining a company's alignment with a set of standards about Environmental, Social, and Governance (ESG) factors. This approach, commonly referred to as Environmental, Social, and Governance investment/practices or performance in the literature, allows investors to assess a company's dedication to sustainable economic development and the fulfillment of its social responsibilities [44,50,51]. The environmental aspect (E) of ESG cover a company's environmental performance, including areas such as emissions, energy efficiency, renewable energy, pollution, greenhouse gases, fossil fuel, and biodiversity [50,52]. The governance facet (G) encompasses a broad spectrum of practices, including openness, management structure, corporate board, policies, compliance with information disclosures, audit-related matters, board diversity, company standards, and risk management [[53], [54], [55]].

Regardless of the favorable appraisal of investors, academia expands to engage in a lively discussion regarding the effect of ESG investment on FV [28]. Nevertheless, the link between ESG investment and FV remains a topic of rigorous debate. The relationship between ESG investment and FV presents a puzzle, ranging from a positive correlation [29,30], to a non-linear one [31]. Moreover, some studies find no statistically significant connection [32], while others even detect evidence of financial underperformance [33]. Besides, the conceptualization of growth option value (GV) originates from the foundational contributions of [56,57] in the field of financial economics [56]. formalized the theory of corporate valuation, suggesting that a firm's overall value comprises two fundamental elements: the value of existing assets and the potential value associated with future growth option (GO). Extending this framework [57], proposed that a firm's potential GO can be understood as GO, granting the firm the right, without obligation, to make decisions about investing in these opportunities in the future. Real options theory, as presented by Ref. [29], is derived from financial options and provides a strategic framework applicable to ESG practices. Emphasizing flexibility in ESG strategies, this theory allows companies to adapt initiatives in response to changing conditions and uncertainties, such as regulatory shifts or evolving industry standards. The timing of ESG practices is deemed crucial, with real options theory guiding companies to strategically implement initiatives when conditions are most favorable [58]. applied the principles of this theory in valuing ESG opportunities, assessing the long-term benefits and risks associated with specific ESG practices. Real options theory ¹proves instrumental in managing uncertainties tied to complex ESG challenges, aiding companies in making resilient and sustainable decisions. While many studies underscore the strategic significance of integrating ESG practices, recognizing their essential role in reinforcing core business functions and acting as a foundation for the growth of firms [59] the existing literature has predominantly focused on the impact of ESG on a firm's current operations. This focus has often neglected explicit consideration of ESG's influence on a firm's GO. Substantial evidence suggests that the value of numerous major strategies revolves around this particular value component [46]. In short, there is a growing repository of empirical work on CSR or ESG elements and corporate performance, although results are mixed. Some studies have found mixed or negative relationships between these characteristics and financial outcomes. Studies have found positive, negative, and neutral associations between CSR and corporate financial performance [60]. Meta-analyses showed that CSR improves accounting-based and market-based profits, although some studies found negative [61] or mixed results [62] ESG or CSR and corporate value are challenging, since empirical research shows inconsistent results. Some research revealed a favorable correlation, while others discovered a negative impact. This article relies on Refinitiv ESG Scores, which have set up collaborations with industry leaders like MSCI, Sustainalytics, and Bloomberg, thanks to their exceptional data integration capabilities. These scores play a pivotal role in evaluating a company's ESG performance. They empower investors, businesses, and stakeholders with valuable insights, enabling informed sustainability-related decisions [63]. We expect that ESG investments significantly affect a FV, acknowledging their potential to shape a firm's long-term prospects and opportunities. Building on this discussion, our second hypotheses is under.

2.3. The moderating role of ESG investments between FCCR-firms value association

Outside of the realm of CSR, there are several risk-mitigating strategies linked with these risk variables that might be researched [4]. CSR as ESG investments assess whether environmental, social, and governance factors are important to long-term portfolio performance. CSR as ESG investments has the potential to offset the adverse effect of firm-specific risk [4,15,34]. ESG investment is an integrated approach compared to CSR. It has the potential to reduce the impact of firm climate change risk on business performance and value. ESG investments can moderate the connection between climate change risk and market value, influencing a company's market performance. In this article, we argue that engaging in ESG investments can help mitigate climate-related risks, offering a comprehensive alternative to traditional CSR. The incorporation of ESG practices is suggested to potentially reduce FCCR while enhancing FV through proactive risk management, cost efficiencies, reputation improvement, access to capital, innovation, and alignment with sustainability goals. The article posits that ESG investments may function as a mechanism influencing the relationship between FCCR and FV, with the United States, as the world's largest economy, serving as the contextual backdrop. We propose two hypotheses.

2.4. Theoretical framework

Theoretical framework for the study is drawn upon the interdisciplinary nature of ESG investment in the context of FCCR and its implications on FV. Extensive literature supports the exploration of these relationships, integrating insights from various theories such as resource-based view (RBV), institutional theory, and stakeholder theory [64]. Institutional theory [65] to examine how a firm's response to environmental risks, including climate change, influences its overall performance [66]. institutional theory emphasizes compliance with external expectations. The Resource-based view emphasizes adaptation to environmental changes for prosperity [[67], [68], [69]]. Stakeholder theory suggests that firms managing relationships with various stakeholders, including those concerned about climate change, can positively influence firm value [70]. In addition, building on established climate change research, we investigate the financial implications of FCCR on FV. Studies by Refs. [15,36,40] highlight the negative correlation between climate risk and firms' performance. Employing an innovative FCCR measure [3], and FV using Tobin's Q and GV we address gaps by evaluating FCCR's impact on FV. Second, building on sustainable finance, and stakeholder theory in this article we explore how ESG investment and FV are interconnected [[71], [72], [73]]. To enhance FV and ensure profitability, it is crucial to recognize the inverse relationship between ESG and FCCR. The literature, spanning [28,29,53], presents a mosaic of findings on the relationship between ESG investments and FV. Third, This awareness can be utilized for effective risk management, with researchers [48] argue that investing in CSR engagement functions as a form of insurance-like protection against firm-specific idiosyncratic risk, thereby contributing to improved FV. Together, these theories underscore the necessity for businesses to manage climate change risks for competitiveness [74]. The study literature indicates that beyond CSR, ESG investments are positioned as holistic risk-mitigating strategies and can moderate the association between FCCR and FV [4]. Based on substantial theoretical support lays the groundwork for the rest of the study Figure (1) provides an overview of the theoretical foundations.

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Fig. 1

Theoretical framework.

In summary, given the caveats above, this article fills this vacuum in the literature. It looks to deepen comprehension of the complex interplay between FCCR on US-listed FV and how ESG investment moderates this association by incorporating a unique perspective. This theoretical grounding directs our empirical research, expanding our understanding of sustainable business practices and their implications for businesses and other interested parties. More specifically, we expect to add to the ongoing discourse about the effects of FCCR on FV by introducing a potential strategic mechanism linking FCCR and FV, thereby aiding leaders in developing more environmentally and socially responsible practices within their organizations.

3.1. Data and sample construction

The study sample size made up 1771 US-listed firms with 19,443 yearly observations from 2006 to 2021. Given the US' status as the world's largest economy [4], its significance in global economic growth and stability is undeniable [44]. Furthermore, as one of the major contributors to pollution, particularly in terms of annual CO2 emissions, the US has become a pivotal starting point for understanding and addressing environmental concerns. This recognition stems from its role as the primary home to a substantial number of polluting entities, accentuating the importance of examining the intersection between corporate activities, environmental risks, and sustainable practices in this influential economic landscape. We applied sampling criteria to ensure a robust dataset, including the following steps: Firms included in the study were part of recent corporate conference calls on FCCR, firms with disclosed governance scores, filtering out observations with total negative assets or equity, excluding dysfunctional firms, financial or utility companies with distinct capital structures regulated by different agencies to avoid survivorship bias, and removing outliers. Data for this study was sourced from Refinitiv's Eikon platform, CompStat, and WDI, and the sample distribution is categorized by major sector and year according to the Standard Industrial Classification.

4.1. Summary statistics and correlation

Table (1) contains the standard statistical properties of the variables including total number of observations, the mean, and standard deviation, indicates that there is a sizable variation in the data, to determine the effect of firm-level climate change risk (FCCR) on the firms' value (FV) measure by Tobin's Q and growth options value (GV). FCCR is our primary explanatory variable of interest, and FV is an explained variable, while ESG investment acts as moderator. Our VIF and correlation are under an acceptable threshold. Our variables are free of multi-collinearity following the criteria IF>10. The description of the variables can be found in Appendix Table A. Table (2) and Fig. 2 reports correlations & VIF estimations. We employ VIF and correlations to identify multi-collinearity. Our VIF and correlation are under an acceptable threshold.

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Figure (2)

Visual presentation of the correlation matrix.

Appendix Table (2) presents the testing results for stationarity using both first- and second-generation unit root frameworks. The ADF-Fisher and IPS test for stationary is adequate for unbalanced panel data sets [82]. It presumes that cross-sectional units are entirely independent of one another. The second-generation PCIPS test accommodates cross-sectional reliance unit root results, thus solving the cross-sectionally unique problem. The findings confirm the hypothesized order of integration for the variables in the study. Therefore, in contrast to the cointegration method, we use OLS models based on the unit root.

4.2. Regression analysis results

Before heading to the baseline estimation, the study fulfills the prerequisites and avoids spurious regression, diagnostic and post-estimation tests presented in Table (3). To evaluate the hypothesis, we undertake baseline estimation. To decide whether OLS or panel effect estimate is appropriate, we employ the Breusch–Pagan (LM) test, assume no effect. The Breusch–Pagan test p-value is less than the threshold value showing that LM test is significant and indicates panel data estimate technique has merit, unlike.⁸ Next, we run fixed and random effects, and it is preferred to employ a fixed effect model as the Hausman test hypothesis is rejected. The Modified Wald and Wooldridge tests are significant indicate our models have serial/autocorrelation and heteroskedasticity. We employ a fixed effect with a robust function to deal with heteroskedasticity and serial/autocorrelation.

4.3. Feasible generalized least square (FGLS) regression estimated results

Since the modified Wald and Wooldridge tests are significant, our fixed effect models are prone to serial/autocorrelation and heteroskedasticity issues. Although serial/autocorrelation and heteroskedasticity problems are addressed by fixed effect with robust function, it does not consider cross-sectional dependence. So, we ruled out the above-fixed effect robust and OLS-based technique and switched to generalized models. We implement a more effective framework named FGLS, a more superior framework as it considers (1) serial/auto-correlation, (2) heteroskedasticity issues, and (3) cross-sectional dependence [78]. FGLS results in Table (3) columns (1–2) offer similar insights. In the first stage, the negative and significant estimated coefficients values −0.0621, and −0.0570 of FCCR validate our H₁ that FV evaluated by TQR and GV decreases on average. The results agree with [41]. Next, we evaluate the direct effect of ESG investment on FV. The ESG-index has positive and significant coefficients are in Table (3) columns (3–4) suggest that ESG investment increases the TQR and GV and our findings are in line with [28,63,67]. In the third stage, we add the interaction term (FCCR*ESG index). Our findings, as illustrated by the substantial and statistically significant coefficient values of 0.0121 and 0.0102 in columns (5–6) of Table (3), provide strong affirmation for our H₃. This suggests that the interaction term consistently exerts a positive and significant moderating influence on the relationships between FCCR and FV. Our study demonstrates that ESG activities play a pivotal role in mitigating the negative impact of FCCR on FV, thereby substantiating H₃. Furthermore, our results align with the notion that enterprises facing higher climate risk stand to gain more from the value-enhancing potential of ESG, in line with the insights presented by Ref. [15]. This underscores the strategic importance of ESG initiatives in fostering resilience and value creation, particularly for businesses operating in environments marked by elevated climate-related challenges.

4.4. Dynamic panel 2-stage generalized method of moments: endogeneity concern

We acknowledge the potential existence of endogeneity and reverse causality in the empirical estimates provided. Even with the inclusion of diverse control variables, there is a possibility of oversight in our initial analysis. This includes the potential neglect of factors such as macro-level climate change risk or behavioral influences like climate change sentiments on both FCCR and FV. Considering the potential bias in our initial estimates, we address endogeneity using the generalized two-step method of moments, a robust econometric approach recognized for automatically generating instrumental variables and alleviating issues related to endogeneity and reverse causality.

The results obtained through the generalized two-step method of moments (GMM) are presented in Table (5) columns (1–2), revealing negative and significant estimated coefficient values of FCCR. This supports our initial hypothesis that TQR and GV, on average, decrease. Furthermore, Table (5) columns (3–4) highlight the positive and significant effect of ESG investment on FV. This finding aligns with our hypothesis and underscores the potential positive impact of ESG on FV. The interaction term positively and significantly moderates the FCCR and FV relationship. As demonstrated in Table (5) columns (5–6) further supports our initial model H₃, reinforcing the validity of our hypothesis. Additionally, the Autoregressive (AR) (2) test serves as a check for residual autocorrelation of the second order.¹¹ In conclusion, despite the acknowledged challenges of endogeneity and reverse causality, our study employs robust econometric methods like GMM to address these issues, providing meaningful insights into the relationships among FCCR, FV, and ESG investments.

The results are summed up: (1) We find FCCR negatively and significantly influences FV. (2) ESG investment positively and significantly affects FV, and (3) ESG investment moderates FCCR-value association and improves FV. Our results support H₁, H₂, and H_3,Figure (3) presents the visual summary of our empirical findings.

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Figure (3)

Visual summary of our main empirical findings.

This article begins by examining the impact of firm-level climate change risk (FCCR) on firm value (FV) in the context of US-listed firms. Utilizing fixed-effect robust, FGLS, and GMM estimation techniques, we consistently observe a negative effect of FCCR on firm value, aligning with the prediction in H1. This finding is consistent with prior research by Refs. [15,44,84], supporting the notion that climate change risks may diminish corporate value due to associated environmental costs, as proposed by Ref. [85]. Next, we investigate the impact of Environmental, Social, and Governance (ESG) investments on firm value within the context of US-listed firms. Employing fixed-effect robust, FGLS, and GMM estimation techniques, we consistently find a positive effect of ESG investments on firm value, in line with H2 and supported by previous [63,67,[86], [87], [88]]. ESG can influence firm value through various channels, such as enhancing reputation, attracting customers and investors, or driving innovation and efficiency. In the third part of our analysis, we explore the moderating effect of ESG investment on the association between FCCR and FV. The results indicate a significant moderating effect, with the interaction term FCCR*ESG index positively and considerably influencing the relationship between FCCR and FV, demonstrating that ESG investments can mitigate the negative impact of climate change risk on firm value. Specifically, ESG investments decrease the FCCR and improve firms' value. Considering these findings, climate finance policies, including green subsidies and tax credits, could facilitate the transition to green investments.

According to Refs. [34,35] the advantages of risk management stemming from engagement in ESG investments are pertinent in alleviating the expenses linked to climate-related risks. ESG investments offer a comprehensive alternative to conventional CSR, effectively addressing ESG factors' materiality to long-term performance and risk mitigation.

Importantly, the results highlight the positive outcomes of ESG initiatives. Stakeholder-oriented companies can benefit from participating in such initiatives, as ESG factors have the potential to enhance a company's value through increased public trust, financial support, brand recognition, reputation, and a competitive edge that leads to enhanced sales and company value.

4.5. Robustness check

Assessing the resilience of our study primary outcome is a fundamental requirement. To ensure the robustness and credibility of our findings, we conducted a thorough evaluation. This involved employing alternative estimation methods, such as the Driscoll-Kraay robust technique and contemporaneous approaches. Additionally, we conducted sensitivity checks and examined alternative proxies. Additionally, we decomposed firm-level climate change exposure and E and S (environmental and governance components of ESG investment following [23] furthering more heterogeneity in analysis.

4.5.1. Ruling out with alternate estimator: simultaneous quantile bootstrap estimates

First, to incorporate diversity into our analysis, this research uses another estimator to broaden its heterogeneity. Since our OLS estimates may be biased due to heteroskedasticity and can be easily skewed by extremely outlier data points. Thus, we employ a simultaneous quantile bootstrap estimate¹²to gain more insight into the distribution of results by focusing on the 50th, 75th, and 90th percentiles as used by Ref. [81]. Figure (4), Figure (5) reports a stepwise visual demonstration of the direct effect of FCCR, on FV, and moderating effect of ESG investments on TQR. The quantile estimates indicate that the effect of FCCR, and (FCCR*ESG investment) is pronounced more variance at high and medium percentiles (90th and 75th, respectively) than at the low.

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See Also

Challenges and Opportunities to ESG Investing

Figure (4)

Direct effect dependent variable TQR.

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Figure (5)

Moderating effect dependent variable TQR.

Figure (6-7) reports a stepwise visual demonstration of the direct effect of FCCR, on FV, and moderating effect of ESG investments on GV. The quantile estimates indicate that the effect of FCCR, and (FCCR*ESG investment) is pronounced more variance at high and medium percentiles (90th and 75th, respectively) than at the low. The solid line represents the linear regression coefficient, while the dotted lines represent 95% confidence intervals. When comparing quantiles, a regression analysis's parameters and confidence intervals are always the same. The use of QR models rather than OLS ones is supported by this remark. Concisely, we quantify the differences in the conditional distribution of outcomes using high, moderate, and low regimes of FCCR on firms' value. FCCR reduces FV and displays more significant variance and stability at conditional (90th and 75th, respectively than at the low) distributions. Our robustness findings are unchanged, and the coefficient values confirm further evidence that the relationship is like the original.

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Figure (7)

Moderating effect dependent variable GV.

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Figure (6)

Direct effect dependent variable GV.

4.6. Sensitivity analyses: change regression estimators and sub-sample period

We perform sensitivity analyses for further heterogeneity and stability of our main findings. We split the sample into subprime crisis years (2007–2008) and the covid-19 Pandemic period (2020–2021). Besides, we add additional control and alternate measures of our independent variable¹³ and change regression. We use firm-level climate change exposure (FCCEXPO) [3] alternative proxy of FCCR and it is given in the equation. In brief, b represents the values 0, 1, and so on. B i, t refers to the bigrams, which are two-word sequences, found in the earnings call transcript of firm i during quarter t. Function 1[·] is an indicator function. Transcripts are scored to determine three climate measurements: C Opportunity, C Regulatory, and C Physical. The subsequent action involves quantifying the climate bigrams C in the quarterly transcript of firm I at time t. Call length is determined by scaling the count using transcript bigrams. The annual measure of each firm is calculated as the average of its four quarterly measures. This paper employs equation (1) to represent FCCE as an alternative climate change risk variable, while equation (13) represents FCCR as the primary FCCR variable.

¹The roots of real options theory, originating from Miller & Modigliani (1961) and Myers (1977) in financial economics. This theory conceptualizes growth opportunities as options, granting flexibility for strategic decisions. Drawing from Bagh et al. (2024), Awaysheh et al. (2020) and Lins et al. (2017), we link real options theory to ESG practices, highlighting adaptability and the crucial role of timing. Insights from studies like Hart & Milstein (2003), Alessandri et al. (2012), and Estrada et al. (2010) stress the strategic importance of ESG, reinforcing core functions and contributing to firms' growth options. The real options perspective connects strategic and financial analyses, emphasizing the central role of Growth Options in managerial decision-making. We are Grateful for the feedback from an anonymous reviewer.

²The process utilizes a machine learning algorithm for keyword discovery to identify and capture exposures associated with climate change, including those related to opportunity, physical, and regulatory shocks. If the FCCR score is high, it is likely to suffer negative consequences due to climate change.

³Equation the calculation process for Tobin's Q ratio and equation, Growth option value is given in Appendix 1.

⁴We used a company's environmental, social, and governance performance -ESG overall index.

⁵We utilize Ordinary Least Squares (OLS) and implement Fixed Effects (FE) robust options to address concerns related to serial/autocorrelation and heteroskedasticity.

⁶To preserve space, we do not report OLS and FE robust Equations. The main reason for GMM models as they automatically create instrumental variables & and eliminate endogeneity/reveres-causality, unlike OLS and FE models.

⁷To explain variables behaving at varying levels, we utilized the simultaneous (QR) quantile regression bootstrap (20) method.

⁸We undertake OLS estimation as benchmark regression. To conserve space the OLS outcomes are not reported, and all OLS models' estimations are available upon request.

⁹Control variables are included in our all-empirical specifications see Table 3, Table 4, Table 5, Table 6, Table 7. Only a few control variables lose their significance. To preserve space the control variables explanation is not reported and are available upon request.

¹⁰All-empirical specifications grouped together into two parts (1) Direct effect: firm-level climate change risk (FCCR) and ESG investment on firm's value measured by TQR and GV Stage-wise estimates are presented in columns (1–4) and (2) Moderating effect: Effect of interaction term FCCR*ESG index on firms' value measured by TQR and GV & Stage-wise estimates are presented in columns (1–6). At the thresholds explained by the asterisks (***=0.01, **=0.05, and *=0.10), the outcomes are deemed statistically significant. Standard deviations typically cluster at the firm -level.

¹¹The joint null hypothesis asserts that the tested instruments are authentic, that the error term is unrelated to the instruments, and that the untested instruments have been properly eliminated from the equation.

¹²Provides an in-depth practice for drawing out the regression picture beyond just obtaining the conditional mean by allowing one to test the link between the response variable and the covariate at each quantile of the conditional distribution function. It can be a viable replacement for our earlier estimations.

¹³In endurance check the study replaced two control variables Cash flow and financial leverage with financial slack (FSLK) & and equity multiplier. Besides, we firm-level climate change risk measure with firm-level climate change exposure (FCCEXPO) data created by.

¹⁴We employ Driscoll and Kraay's approach to accommodate Heteroskedasticity—cross-sectional or "spatial" dependence issues. Our results are unchanged and consistent for the sub-sample as well.

Table A1

Variables Description

Table A2

Panel Unit Root Results _Cross-Sectional Dependence & Independence

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