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ABSTRACT

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International Business Review
journal homepage: www.elsevier.com/locate/ibusrev
Valuing ESG: How financial markets respond to corporate sustainability
Le Chaua,b, Le Anhc, Vo Duc’’
a Lincoln International Business School, University of Lincoln, UK
b School of Banking, UEH University, Hochiminh City, Viet Nam
e Institute for Research Science and Banking Technology, Ho Chi Minh University of Banking, Viet Nam
d UWA Business School, The University of Western Australia, Australia
e Research Centre in Business, Economics & Resources, Ho Chi Minh City Open University, Viet Nam

Keywords:
ESG performance
Firm value
Corporate sustainability
Institutional quality
International business
JEL Classifications
G32
G34
M21
L25

This study explores how financial markets value corporate sustainability, using a comprehensive dataset of the largest publicly listed firms across 12 countries. Diverging from prior research that assumes a linear or quadratic relationship between ESG performance and firm value, we uncover a cubic response function, characterised by a horizontal-S-shaped effect. Firm value initially increases with ESG ratings up to a critical threshold, then declines as firms face rising costs and diminishing returns, before rising again once ESG ratings exceed a second threshold. We attribute this nonlinear dynamic to two key mechanisms: growth options and stakeholder influence capacity, which interact at different stages of ESG performance. Furthermore, our analysis highlights the moderating role of country-level institutional quality and environmental sustainability, demonstrating that national contexts significantly shape market responses to ESG ratings. By leveraging the Gaussian Copula approach to address endogeneity concerns, we ensure robust and reliable findings. This study advances the international business literature by offering a theoretical framework to explain cross-country variations in how financial markets price sustainability-linked assets. Our findings underscore the critical role of institutional factors in shaping investor sentiment and corporate strategies in a sustainability-focus global economy. These insights are invaluable for investors, policymakers, and corporate leaders navigating the evolving landscape of ESG-driven finance.

* Correspondence to: The Business School, The University of Western Australia, 35 Stirling Highway, Crawley, WA6009, Australia.
E-mail addresses: cle@lincoln.ac.uk (L. Chau), anhlh_vnc@hub.edu.vn (L. Anh), duc.vo@uwa.edu.au (V. Duc).
1 https://www.bloomberg.com/company/press/esg-may-surpass-41-trillion-assets-in-2022-but-not-without-challenges-finds-bloomberg-intelligence/
https://doi.org/!0.1016/j.ibusrev.2025.102418
Received 13 November 2023; Received in revised form 4 February 2025; Accepted 8 February 2025
Available online 15 February 2025
0969-5931/© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.0rg/licenses/by/4.0/).

1.		Introduction
Sustainable investing, incorporating various environmental, social and governance (ESG) principles, has experienced exponential growth over the last decade. An increasing number of institutional investors are embracing sustainable investing by integrating ESG information into their investment decisions. This approach not only aims to enhance risk- adjusted returns but also contributes to the advancement of ESG practices. A report by Bloomberg Intelligence1 indicates that global ESG assets surpassed $41 trillion in 2022, up from $22.8 trillion in 2016, and are expected to exceed $50 trillion by 2025. Shifting real investment towards environmentally friendly firms through sustainable investing generates a positive social impact by making these companies greener (Pastor et al., 2021). Additionally, there has been a rise in the number of firms disclosing sustainability reports and ESG data. For instance, statistics from the Governance & Accountability Institute revealed that 86 per cent of S&P500 firms released sustainability or corporate
responsibility reports in 2018, compared with just under 20 per cent in 2011 (Gillan et al., 2021). Academic research findings demonstrate the significant economic effect of ESG ratings on a firm’s performance and market value (Amel-Zadeh & Serafeim, 2018). However, there is a risk associated with excessive expectations regarding the economic and nonpecuniary benefits of ESG and sustainability investing, which may lead to an accelerated push toward green transition. De Freitas Netto et al. (2020) argue that the proliferation of the green market is accompanied by the phenomenon of greenwashing, defined as the practice where firms rely on skilled communication to deliberately manipulate disclosed sustainability information to appear environmentally or socially responsible (Delmas & Burbano, 2011). While companies are engaging more in green activities, such as issuing green bonds to fund environmentally friendly projects, there is no guarantee that they will not pursue decidedly non-green activities using other sources of funding. Brandon et al. (2022) find that US institutional investors who are signatory members of the Principle for Responsible Investment (PRI signatories) have not incorporated any form of ESG considerations into their investment strategies and experienced significantly worse portfolios in terms of ESG performance compared to non-PRI signatories.
In a global survey among institutional investors, Amel-Zadeh & Serafeim (2018) find that ESG investing is primarily driven by financial motives rather than moral and social incentives. However, investors' return expectations and motives vary considerably across geographical regions (Giglio et al., 2025). Ethical motives are particularly important in Europe, where investors believe that engagement with socially responsible companies can drive change in the corporate sector to address ESG issues, unlike in the US. An article published in the Financial Times concludes that ESG ratings have been increasingly crucial for international investors engaging in Chinese equities. However, the sustainability rules and standards common in Western jurisdictions have not always aligned with the realities in China. Additionally, the lack of consistency of ESG information and standards across providers poses significant challenges for investors seeking to integrate ESG data for a competitive edge, making sustainable investing more complex (Avramov et al., 2022).
Numerous studies have examined the relationship between ESG ratings and firm market value, as well as the implications for investment returns. However, the findings remain largely mixed and inconclusive, complicating efforts to evaluate the impact of ESG on asset prices. Eccles et al. (2014) demonstrate that "high sustainability companies", which adopt elevated social and environmental standards beyond legal requirements, outperform “low sustainability companies" in terms of market and accounting performance. Conversely, Pastor et al. (2021) show that brown stocks - defined as shares of companies heavily involved in industries with significant environmental harm - outperform green stocks, which represent shares of companies operating in environmentally friendly industries. This finding suggests a negative relationship between ESG ratings and firm market value. A body of literature comparing the performance of self-labelled socially responsible investing (SRI) funds and conventional mutual funds fails to identify significant differences in investment performance (Bauer et al., 2007; Renneboog et al., 2008; Statman, 2000). Amel-Zadeh & Serafeim (2018) argue that the inclusive evidence about the ESG-firm market value relationship is likely due to the variety of investment strategies employed. For instance, some investors exclude certain companies based on ethical norms, while others apply positive or negative screening focused on material ESG issues, such as aggregate ESG measures or individual ESG metrics. Berg et al. (2022) further highlight the divergence of ESG ratings across six prominent ESG rating agencies, which complicates the evaluation of ESG performance for companies, funds, and portfolios. The ongoing debates and contrasting findings regarding the ESG-firm market value relationship underscore the need for further research to clarify these dynamics.
This study examines how financial markets value ESG performance, leveraging a comprehensive dataset of the largest publicly listed companies across 12 countries. This investigation indirectly assesses whether shareholders - who seek to maximise wealth - consistently prioritise moral and social incentives over financial motives, while also capturing the market’s responsiveness to sustainable business practices. We make two key contributions to the literature on ESG ratings and firm value.
First, we hypothesis and empirically validate a cubic relationship between ESG and firm value, characterised by a horizontal S-shaped curve. This cubic pattern is driven by two critical mechanisms: growth options and stakeholder influence capacity (SIC). Growth options reflect investment-driven benefits of ESG improvement, which create new
2 See	https://www.ft.com/content/55058f
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growth opportunities by enhancing trust and mitigating risks. SIC complements this mechanism by capturing the credibility and legitimacy firms gain among stakeholders, amplifying financial returns of ESG efforts. Together, these mechanisms explain the transition from an inverted U-shape at low ESG ratings to U-shape at higher ESG ratings. Firm value initially increases with ESG ratings up to a critical threshold, then declines until reaching a second threshold, beyond with firm value rises again. Building on Haans et al. (2016), we extend the theoretical foundations of nonlinear relationships in the ESG literature. While prior research in business and strategic management has predominantly examined U-shaped and inverted U-shaped relationships, it has often lacked a clear articulation of underlying theoretical mechanisms. Our framework addresses this gap by clarifying how growth opportunities and stakeholder influence interact, offering a structured explanation of how ESG performance evolves over time and affect firm value.
Second, we demonstrate that ESG-firm value relationship is moderated by country-specific institutional and market factors, such as regulatory framework, stakeholder expectations, resource availability, and market efficiency. Contrary to conventional expectations, our findings reveal that in developed markets with strong sustainability norms and efficient regulatory frameworks, the impacts of ESG on firm value is weaker. Drawing on signalling theory (Spence, 1973) and institutional theory (Campbell, 2007), we argue that in such contexts, ESG practices have become baseline expectations, diminishing their signalling power and market differentiation. This is consistent with the efficient market hypothesis (Fama, 1970), as ESG performance may already be priced into firm valuations. Conversely, in emerging or less regulated markets, superior ESG performance acts as a powerful signal of firm quality and sustainability, resulting in stronger effects on firm value.
By integrating these mechanisms, this study advances theoretical clarity in the ESG literature while offering practical insights for managers and investors navigating diverse institutional contexts. Our findings highlight the importance of tailoring ESG strategies to align with country-specific market conditions, providing a comprehensive understanding of how sustainable practices shape firm value in the global business landscape. This contribution is particularly relevant to the field of international business, where institutional heterogeneity plays a critical role in shaping firm behaviour and financial outcomes. As ESG considerations continue to reshape global business, understanding these context-specific dynamics is essential for firms seeking to maximise value while advancing sustainability goals.
The paper is structured as follows. Section 2 reviews the theoretical background from which the study's hypotheses were developed. Section 3 explains the data sample, variable descriptions, and methodology. Section 4 presents the testing results and discusses main findings of the study. Section 5 concludes the paper with theoretical and managerial implications from the study findings. It also addresses the limitations of the study and suggests avenues for future research.
2.		Theoretical background and hypothesis development
2.1.		ESG and firm value: theoretical framework and equilibrium model
The question of how the financial markets value corporate sustainability has been the subject of intense debate over the past decade. ESG refers to the integration and incorporation of environmental, social, and governance concerns into corporate and investment decision-making (Gillan et al., 2021). According to traditional asset pricing theories, such as the Modern Portfolio Theory and the Capital Asset Pricing Model (CAPM), a negative relationship exists between ESG performance and share value. Investors require higher compensation for riskier assets, which are often associated with low ESG ratings. In a two-factor asset pricing model, Pastor et al. (2021) theoretically demonstrate that green stocks have lower expected returns than brown stocks because ESG preferences are incorporated into asset prices, reducing expected returns for ESG investors. Agency theory (Jensen & Meckling, 1976) provides another explanation for the negative association between ESG and firm value, attributing to conflicts of interest between managers and shareholders. This perspective emphasizes that managers may prioritise ESG goals over shareholder value, either to enhance their personal reputation or to signal their commitment to social objectives (Feng et al., 2022). Such behaviour can result in excessive investments in non-profitable sustainability initiatives, aiming to bolster ESG ratings and corporate reputation. Neoclassic economists similarly argue that a firm’s commitment to ESG often increases unavoidable costs and reduces profitability. While socially desirable in the short term, these strategies may adversely affect shareholder value and overall financial performance (McWilliams et al., 2006).
Conversely, stakeholder theory (Freeman, 2010) supports a positive relationship between ESG performance and firm value. From this perspective, firms enhance legitimacy by aligning with stakeholder expectations. Stakeholders, defined as any group or individual influencing or being influenced by the firm’s objectives, are integral to corporate management, fostering value creation and maximising shareholder wealth (Donaldson & Preston, 1995). Ruf et al. (2001) find that when managers actively engage with stakeholders through negotiation and contracting, these interactions help monitor and enforce a focus on organizational financial goals. This reduces information asymmetry (Cui et al., 2018) and enhances managerial responsiveness to external demands, leading to greater organisational efficiency (Donaldson & Preston, 1995). Consequently, firms that leverage socially responsible actions often build stronger trust with stakeholders, making superior ESG performance synonymous with better financial outcomes.
Risk management theory (Godfrey, 2005) further suggests corporate social responsibilities (CSR) can generate positive moral capital among stakeholders, acting as an ’‘insurance-like'’ mechanism during crises. By reducing risk and stabilising cash flows, CSR engagement helps firms weather negative shocks more effectively. Supporting this view, Godfrey (2005) shows that firms actively engage in CSR experience smaller losses in shareholder value during periods of adversity.
Focusing on green returns, Pastor et al. (2022) theoretically establish that higher realised returns on green assets compared to brown ones results from unanticipated increases in environmental concerns. This heightened demand for sustainable assets drives profits and stock prices for green firms. However, these higher realised returns do not necessarily translate into higher expected returns, as the outperformance of green assets diminishes once climate shocks are mitigated.
2.2.		Literature review and hypothesis development
2.2.1.		The curvilinear impact of ESG on firm value
In line with the growing momentum toward greening the financial system and economy, the literature on CSR and ESG has significantly expanded over the past decade. While both concepts address sustainability and ethical business practices, CSR is a broader, encompassing a company's voluntary efforts to take responsibility for its social and environmental impact, whereas ESG is more specific, focusing on measurable factors. Although this study centers on ESG, we review CSR literature alongside ESG research to strengthen our arguments about market responses to firms’ sustainability performance. Numerous studies have explored the relationship between ESG performance and firm value, yet the findings remain controversial and inconclusive (Abdi et al., 2022; Fatemi et al., 2018; Giese et al., 2019; Gillan et al., 2021). These inconsistences may stem from various factors, such as stakeholder mismatching, the general neglect of contingency factors, and measurement errors (Orlitzky et al., 2003). Broadly, Breuer et al. (2024) argue that variations in investor motivations across business contexts and institutional settings contribute to mixed results regarding CSR’s impact on firm value.
An extensive literature supports the linear relationship between ESG performance and firm value, with higher ESG performance often associated with enhanced firm value. This perspective aligns with stakeholder theory, which posits that socially responsible activities boost financial performance through mechanisms such as: enhancing corporate reputation, increasing stakeholder reciprocation, reducing risks and costs of contracting, and strengthening innovation capacity (Vishwanathan et al., 2020). Seok et al. (2024) argue that strong ESG performance bolsters consumer satisfaction and brand valuation, ultimately enhancing firm value. Institutional investors frequently promote sustainable investment products by emphasizing their promising risk-adjusted returns, a view supported by empirical evidence (Gimeno & Gonzalez, 2022; In et al., 2019; Nagy et al., 2016). Additionally, research from Aydogmus et al. (2022), Naseem et al. (2020) and Fatemi et al. (2018) highlight how ESG performance enhance profitability and market value. However, Jia (2020) observes that this linear effect varies across industries with differing competitive pressures.
Conversely, much research provides the counterargument that ESG investments can harm firm value. In this view, ESG investments are associated with incurred costs, a potential waste of resources, and a tool that managers might use to extract private benefits from shareholders (Aouadi & Marsat, 2018). For instance, Brammer & Pavelin (2006) report that UK firms with low social score firms outperform the market on average, while Manchiraju & Rajgopal (2017) and Sciarelli et al. (2019) find that ESG engagement reduces stock prices of Indian firms. Marsat & Williams (2013) identify a negative ESG-firm value relationship value using worldwide MSCI ESG ratings.
In this study, we challenge the prevailing linear relationship, proposing that the impact of ESG performance on firm value is nonlinear and varies across different ESG rating levels. As De la Fuente et al. (2022) highlight, the ESG-firm value nexus reflects complex interactions with other value sources, transcending simplistic cost-benefit assessments. We hypothesise the cubic relationship between ESG ratings and firm value, driven by two latent mechanisms: (i) growth options, and (ii) stakeholder influence capacity (SIC).
Growth options: Rooted from real options theory (Miller & Modigliani, 1961), growth options explain a firm’s value as a combination of its current assets and future growth opportunities. ESG investments can be seen as a series of real options - incremental opportunities that vary in value based on firm's stage of ESG engagement and external conditions. This dynamic nature of ESG investments explains the nonlinear effect on firm value across different ESG rating levels.
Firm with low ESG scores often have untapped opportunities to engage in relatively low-cost, high-return sustainability initiatives. These activities - such as basic environmental disclosures, implementing recycling programs, or reducing single-use plastics - are inexpensive and accessible but generate substantial goodwill. Stakeholders are likely to perceive these initial efforts as genuine attempts to improve sustainability practices, fostering trust and loyalty. Such incremental investments enhance a firm’s reputation and social capital, encouraging stakeholders to commit resources or make firm-specific investments. For example, customers may choose sustainable brands, employees may align with the firm's values, and investors may reward the firm for its proactive ESG engagement. These effects cumulatively increase the firm's growth potential and market valuation, leading to a positive association between ESG ratings and firm value.
As firms progress in their ESG journey, the scope and complexity of subsequent investments increase. At this stage, firms may need to adopt advanced eco-friendly technologies, participate in large scale sustainability programs, or overhaul operational systems to meet higher ESG standards. These initiatives involve significant costs, uncertainty, and risks, as they often require substantial capital, specialised expertise, and long implementation timelines. The returns of these advanced ESG investments tend to diminish relative to the initial low-cost efforts. Stakeholders may also begin to experience resource constraints, slowing the incremental benefits of trust-building and reciprocation. Investors, in turn, may become sceptical of the escalating costs and uncertain payoffs, reassessing the growth potential of ESG-related initiatives. This reassessment contribute to a decline in firm value at moderate ESG scores, as diminishing returns and risk-aversion dominate (De la Fuente et al., 2022).
Firms with high ESG scores have successfully navigate the costly and uncertain middle phase of ESG investments, signalling their ability to integrate sustainability practices into their business models. At this stage, these firms achieve long-term stability, sustainable competitive advantage, and enhanced stakeholder trust. High ESG ratings reflect the firm’s maturity in sustainability engagement, demonstrating its resilience and capacity to manage ESG risks effectively. This clarity of benefits restores market confidence, encouraging investors to view these firms as secure and forward-looking. Consequently, the value of growth options tied to ESG engagement rebounds, re-establishing a positive relationship between ESG ratings and firm value.
Stakeholder Influence Capacity (SIC): SIC mechanism complements the growth options by emphasizing the role of stakeholder relationships. SIC, as defined by Barnett (2007), captures a firm’s ability to recognise, act upon, and derive value from opportunities to strengthen stakeholder relationships through socially responsible practices. Firms with low SIC may struggle to convert ESG efforts into tangible financial benefits. Stakeholders may perceive these firms’ actions as insincere and opportunistic - refer to as ‘’greenwashing" or "window-dressing” (Barnett & Salomon, 2012). Conversely, firms with high SIC are adept at leveraging ESG initiatives to strengthen stakeholder relationships and derive financial benefits. These firms effectively communicate their commitment to sustainability, gaining stakeholders' trust and support.
The interaction of growth options and SIC mechanisms explains the cubic relationship between ESG ratings and firm value. At low ESG scores, growth options mechanism dominates, as firm make low-cost, high return ESG investments, driving value creation. At moderate scores, diminishing returns from both growth options and SIC cause a decline in firm value. At high ESG scores, SIC becomes dominant, restoring firm value through competitive advantage and stakeholder trust. This dynamic produces a horizontal S-shaped curve, where firm value initially increases with ESG ratings up to a critical threshold, then declines before rising again beyond a second threshold.
Therefore, we formulated Hypothesis 1 as follows:
H1: The relationship between ESG ratings and firm value follows a cubic pattern, where firm value initially increases with ESG ratings up to a critical threshold, then declines before rising again beyond a second threshold
2.2.2.		The moderating effect of institutional environment on ESG- firm value relationship
In today’s interconnected business landscape, a company’s ESG conduct relies on its society's legitimacy, shaped by its governance structure and adherence to environmental and social standards (Lee & Raschke, 2023). Research highlights the importance of considering the institutional environment when examining the relationship between ESG performance and firm value. Institutional theory defines an institutional environment as a framework comprising regulatory mechanisms that establish specific participants and procedures, forming a shared system with representative and normative rules (Scott, 2008). Implicit or explicit rules are created across various areas, such as organizational structure and behaviour, which are critical for institutional members (Suchman, 1995). The strength of legal institutions, environmental regulations, and social norms vary significantly across countries, affecting how ESG practices implemented and perceived by stakeholders. In countries with strong governance institutions, firm are more likely to integrate ESG factors into their operations due to regulatory pressures and the need to conform to societal expectations (Ortiz-de-Mandojana et al., 2016). This integration reduces regulatory risk, ensures access to necessary external resources, and ultimately enhances firm value.
Stakeholder theory (Freeman, 2010) suggests that firms create value by balancing the interests of various stakeholders, including customers, employees, investors, and the broader society. The emphasis stakeholders place on ESG factors can differ significantly across countries due to cultural differences, levels of economic development, and social priorities. The resource-based view (RBV) (Barney, 1991) posits that firms achieve sustainable competitive advantages by leveraging unique resources and capabilities, including ESG practices. However, the value derived from ESG depends on the firm’s ability to effectively integrate these practices into its strategy, which is influenced by the availability of resources, technology, and expertise in different countries.
While stakeholder theory, institutional theory, and RBV imply crosscountry variations in ESG-firm value relationship, the efficient market hypothesis, signalling theory, and agency theory further explain how institutional factors moderate this nexus. The efficient market hypothesis (Fama, 1970) suggests that in highly efficient markets, all available information, including ESG ratings, is already reflected in stock prices. Developed markets, being more efficient, absorb ESG information more rapidly and incorporated into asset prices, reducing the potential for firms to derive additional value from improved ESG performance. Signalling theory (Spence, 1973) argues that firms use observable attributes, such as ESG performance, to signal quality to investors. In less developed and regulated markets, superior ESG performance serve as a powerful signal of a firm's quality, risk management, and long-term sustainability. However, in advanced economies where high ESG standards are expected, the informational advantage (or signalling effect) diminishes. Investors in these markets may no longer perceive ESG as a differentiating factor, leading to a weaker impact on firm value. Agency theory (Jensen & Meckling, 1976) provides additional insights. In developed countries with high sustainability and governance standards, shareholders and managers are more likely to have aligned incentives. As a result, ESG performance plays a less pronounced role in mitigating agency problems, such as excessive risk-taking or short-termism, compared to less developed markets.
Empirical evidence supports the moderating role of institutional factors in shaping the ESG-firm value relationship. For instance, Ghoul et al. (2017) show that social and environmental practices have a more positive impact on firm value in countries with weaker legal institutions and limited business freedom. Breuer et al. (2018) find that extensive engagement in socially responsible practices reduces the cost of equity in countries with strong investor protection, whereas a positive relationship between sustainability practices and the cost of capital exists in countries with poor investor protection. Breuer et al. (2024) extend this analysis, demonstrating that fostering long-term relationships with investors in low-regulation environments enhances the benefits of CSR. Similarly, Shin et al. (2023) argue that in weak institutional and governance contexts, high information asymmetries and agency costs limit firms’ access to external resources, making ESG investments more valuable. Karmani & Boussaada (2021) provide further evidence, highlighting corruption and government stability as critical institutional risk moderating the CSR-firm value relationship.
In summary, institutional differences lead to varied expectations and returns regarding ESG ratings. Firms operating in diverse environments and cultures often engage with a wide range of stakeholder groups (Rodriguez et al., 2006). As outlined in our H1, the effect of ESG on firm value follows a horizontal S-curve. The moderating role of institutional factors can be explained as follows: in the early stages of ESG adoption, firms operating in countries with low institutional quality benefit more from ESG due to strong signalling effect, which communicates the firm’s quality, risk management, and long-term sustainability to stakeholders. Conversely, the incremental benefits to firm value from early ESG adoption are less pronounced in developed markets, where high standards of ESG practices are already expected.
As firms enter the middle phase of ESG performance, diminishing returns begin to set in, where additional ESG efforts incur higher costs with relatively lower incremental benefits. In countries with stronger institutions, this decreasing effect is less pronounced due to more efficient governance structures, clearer regulatory frameworks, and better enforcement, which reduce the costs associated with ESG compliance. In contrast, in countries with weaker institutions, the effect is amplified due to higher inefficiencies, greater uncertainty, and weaker enforcement, making ESG investments more burdensome.
In the final phase, firms that reach advanced ESG ratings can leverage their practices for long-term competitive advantage. In weak institutional settings, the rising effect is further reinforced, as fewer firms are capable of implementing advanced ESG strategies. This allows those that do to stand out more clearly in the market, thereby gaining a competitive edge. However, this effect is less pronounced in advanced economies where high ESG standards are the norm, and most firms have already integrated sustainability practices into their operations. Consequently, ESG performance becomes less of a differentiator, reducing its impact on firm value. In these markets, the marginal value added by further ESG improvements is smaller, as stakeholders and investors already expect high levels of sustainability performance across the board.
Therefore, the second hypothesis is formulated as follows:
H2: Institutional quality moderates the nonlinear relationship between ESG rating and firm value, with stronger ESG impact observed in countries with weaker institutional frameworks.
In addition, Silva et al. (2024) highlight that countries with better institutional quality, characterised by improved human rights, liberty, and low corruption rates, tend to exhibit better environmental performance and more stringent environmental regulations. In this context, we argue that the effectiveness of ESG performance could be influenced by a country’s environmental sustainability similar to its institutional quality. According to Peiró-Signes et al. (2022), country risk score, widely used by investors in their decisions regarding international investments and business, is strongly correlated with a country’s environmental sustainability pro-activeness. In countries with weaker environmental sustainability, firms may face heightened environmental risks, such as climate change, resource scarcity, and pollution-related liabilities. These environmental uncertainties greatly amplify the complexities and transaction costs for firms as firms strive to adapt to the swiftly changing conditions (Lartey et al., 2021). Firms integrating ESG considerations into their business strategies can better manage these risks, thereby safeguarding long-term financial performance and enhancing their attractiveness to investors. Zhang et al. (2020) show that the benefit of CSR, especially in the domain of environmental performance, is greater for firms operating in high levels of environmental uncertainty, i.e. volatility and unpredictability of environmental changes. Furthermore, weaker environmental sustainability is usually associated with less stringent regulations and enforcement mechanisms regarding environmental protection. As a result, it is more difficult and costly for firms to implement environmental tasks, and for stakeholders to evaluate firms’ environmental performance (Zhang et al., 2020). In such an environment, firms that proactively adopt ESG practices may stand out more prominently and be rewarded by investors seeking to mitigate environmental risks and align their investments with sustainable principles. Yuan & Zhang (2020) demonstrate that environmental regulatory enforcement acts as a moderating factor in examining the institutional context driving industrial sustainable development in China. Specifically, flexible environmental policies can significantly stimulate the advancement of industrial sustainability via market signals.
In line with the above arguments, we propose that country’s environmental sustainability plays a critical role in shaping the extent and trajectory of ESG's influence on firm value, similar to the moderating effect of institutional quality discussed earlier. Therefore, the third hypothesis is formulated as follows:
Η3: Environmental sustainability moderates the nonlinear relationship between ESG performance and firm value, with a stronger ESG impact observed in countries with weaker environmental sustainability.
3.		Data and research methodology
3.1.		Data sample and definition of variables
We use a comprehensive dataset consisting of the largest publicly listed companies in 12 countries, encompassing both advanced economies and developing countries. These include S&P500 companies (US), FTSE100 companies (UK), constituents of CAC (France), DAX (Germany), SPI (Switzerland), OMX-30 (Sweden), BEL-20 (Belgium), PSI-20 (Portugal), Nikkei-225 (Japan), KRX-300 (Korea), CSI-300 (China), and IBX-100 (Brazil). Our selection criteria involve including only firms with ESG data available for at least three consecutive years. Consequently, our final sample comprises 1552 firms spanning the period from 2015 to 2021, resulting in 10,864 firm-year observations. However, some variables exhibit missing observations for specific years, leading to an unbalanced panel.
To test the nonlinear effects of ESG ratings on firm value and the moderating role of the institutional environment, we construct the following variable measurements.
Dependent variable: firm value, our dependent variable, is proxied by Tobin’s Q (commonly known as the Q ratio). This metric is derived by dividing the market value of a firm by the replacement value of its assets. Tobin’s Q captures the relationship between market valuation and intrinsic value, offering insights into whether a firm is overvalued or undervalued. A low Q ratio, typically falling between 0 and 1, indicates that the cost to replace a firm’s assets exceeds its market value, suggesting an undervalued stock. Conversely, a high Q (greater than 1) implies that a firm's stock is more expensive than the replacement cost of its assets, indicating an overvalued stock. Hence, equilibrium is attained when market value equals replacement cost. As our main focus is on examining how the financial markets value corporate sustainability, we prioritise market value over accounting performance metrics such as ROA, ROE, or ROS, which have already been extensively studied in prior research.
Independent variables: firm’s ESG performance is evaluated through the S&P Global ESG Rank (formerly known as RobecoSAM Corporate Sustainability Assessment). This ranking system assesses how well a company manages its environmental, social, and governance risks and opportunities, reflecting its overall sustainability performance rather than merely the extent of disclosure. To assess these dimensions, the evaluation draws from 62 industry-specific questionnaires, each containing around 100 - 130 questions covering an average of 23 key themes across economic, social, and environmental domains. The metrics, questions, and criteria underlying these ranks are weighted according to their significance and relevance within a specific subindustry. The Environmental (E) dimension percentile rank was converted from the total environmental score based on several criteria relating to environmental reporting, environmental policy and management, operational eco-efficiency, biodiversity, product stewardship and climate strategy. The Social (S) dimension percentile rank is based on criteria relating to general themes such as social reporting, corporate citizenship and philanthropy, human capital development, business and human rights, as well as cross-industry themes like stakeholder engagement and operational health and safety. The Governance (G) dimension percentile rank is derived from both governance and economic dimension scores, encompassing criteria like corporate governance, codes of business ethics, risk and crisis management, customer relationship management, brand management, and tax strategy. The total sustainability score is calculated by multiplying the number of points received for each question by its respective question weight and criterion weight.
We evaluate the moderating role of the institutional environment captured by the country’s institutional quality and environmental sustainability. We use six institutional quality metrics of the worldwide governance indicators from the World Bank, including: Voice and Accountability (VA), Political Stability and Absence of Violence (Political), Government Effectiveness (Goveff), Regulatory Quality (Re_quality), Control of Corruption (Corruption), and Rule of Law (Law).
A country’s environmental sustainability is measured by the environmental performance index (EPI), the Notre Dame Global Adaptation Initiative’s country index (ND-GAIN), and the climate risk index (CRI).
•		EPI developed by Wolf et al. (2022) ranks 180 countries on climate change, environmental health, and ecosystem vitality. EPI provides a gauge at a national scale of how close a country is to establishing environmental policy targets and practical guidance for countries that aspire to move toward a sustainable future. Data are collected from https://epi.yale.edu/
•		ND-GAIN country index measures a country’s vulnerability to climate change and other global challenges in combination with its readiness to improve resilience. Data are provided by the University of Notre Dame via: https://gain.nd.edU/our-work/country-index/r ankings/
•		Climate risk index (CRI) analyses and ranks a country’s level of exposure and vulnerability to extreme weather events (storms, flood, heatwaves etc.). The indices have been estimated and published by Germanwatch, an independent development, environmental, and human rights organisation. Data are available via: https://www.germanwatch.org/en/cri
Control variables: Following extensive literature on the relationship between ESG ratings and firm value, we include a set of variables to control for firm-specific characteristics such as firm size, profitability, operating efficiency, asset growth, financial leverage, liquidity risk, and default probability. Specifically, we measure firm size by the logarithm of total assets reported in the balance sheet. A firm’s profitability, a key factor that determines share value, is captured by earnings per share (EPS) growth. Operating efficiency is measured by the ratio of total sale revenue to total assets, indicating how efficiently the firm uses its assets to generate income. Asset growth is the percentage change of total assets by comparing the current period with the same period of the previous year. Financial leverage is measured by total average assets divided by total average common equity. Liquidity measure is proxied by the ratio between cash and cash equivalents to total current liabilities. Finally, a firm’s default risk is calculated by the Bloomberg Issue Risk model to estimate the probability of default of the corporate bond issuer over the next year. We also include GDP per capita, inflation, and financial development index as country-level control variables.
Although we utilise data from various sources, all data corresponds to the same time period on an annual basis to mitigate any potential issues related to time period mismatches or differing time zones among countries. All firm-level data, including ESG metrics, were collected from a reliable financial database: Bloomberg Terminal. Governance metrics and country-level control variables were obtained from the World Bank database. For country-specific environmental sustainability, we used three different sources to capture various aspects of environmental sustainability: the environmental performance index, country vulnerability to climate change and global challenges, and the climate risk index. Since no single variable adequately captures environmental sustainability, employing different proxies allows for a more comprehensive evaluation and robust findings.
Table 1 provides definitions of variables as well as their data sources, while Table 2 summarises their descriptive statistics. As shown in Table 2, the market value is approximately 2.15 times the book value, as reflected in the mean value of Tobin-Q. The ESG score and its components range from 0 to 100, with an average score of around 50. The environment metric (53.5) dominates the social and governance metrics (50.2 and 49.5) in terms of mean values. Firms differ across size, financial leverage, growth potential, liquidity, earning, and default risks. GDP per capita has a mean value of 10.430 and standard deviation of 0.716. Upon examining country-specific data, Switzerland has the highest GDP per capita, while Brazil has the lowest. The mean inflation
Table 1
Variable definitions and data source.
Variables	Definitions	Data source
Tobin-Q	The ratio between the market	Bloomberg Terminal
value of a firm over the replacement value of the firm’s assets.
ESG	S&P Global ESG rank measures a
company’s total sustainability score.
Environmental Environmental dimension
percentile rank in the S&P Global
ESG.
Social	Social dimension percentile rank in
the S&P Global ESG.
Governance	Governance dimension percentile
rank in the S&P Global ESG.
Firm-size	The natural logarithm of the book value of assets reported in the balance sheet.
Asset-	The ratio of total sale revenue to
turnover	total assets
Default	The probability of default of the issuer over the next year is estimated using the Bloomberg
Issue Risk model.
Leverage Financial leverage is measured by the average total assets divided by the average total common equity
Cash-ratio The ratio of the company’s cash and cash equivalents to its current liabilities.
Asset-growth Percentage change of total assets
by comparing the current period with the same period of a previous
year.
EPS	Percentage change in earning per
share by comparing the current period with the same period of a previous year.
GDPpc	GDP per capita in current US$ World Bank
collected from World Bank
national accounts data and OECD
National Accounts data file (in logarithm)
Inflation Inflation measured by the
consumer price index reflects the
annual percentage change in the
cost to the average consumer of
acquiring a basket of goods and
services that may be fixed or
changed yearly.
FD	Financial development index is
aggregated from nine indices that
summarise how developed
financial institutions and financial
markets are in terms of their depth,
access, and efficiency
Corruption Control of corruption captures
perceptions of the extent to which
public power is exercised for
private gain, as well as "capture" of
the state by elites and private
interests
Goveff	Governance effectiveness captures
perceptions of public service
quality, civil service independence
from political pressures, policy
formulation and implementation
quality, and government policy
commitment.
Re_quality Regulatory quality captures
perceptions of the ability of the
government to formulate and
implement sound policies and
regulations that permit and
(continued on next page)
Table 1 (continued)
Variables	Definitions	Data source	
	promote private sector development.		
Law
Political	Rule of law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, the quality of contract enforcement, property rights, the police, and the courts. Political stability and absence of violence measures perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including politically motivated violence and terrorism.		
VA	Voice and accountability captures perceptions of the extent to which a country’s citizens can participate in selecting their government, as well as freedom of expression, freedom of association, and free media.		
EPI	The environmental performance index was developed by Wolf et al. (2022) to measure a country’s state of sustainability based on climate change, environmental health, and ecosystem vitality.	Yale Center for Environmental Law & Policy: https://epi.yale. edu/	
ND-GAIN	The country index measures its vulnerability to climate change and other global challenges in combination with its readiness to improve resilience.	University of Notre Dame, Notre Dame Global Adaptation Initiative	
CRI	Climate risk index analyses and ranks a country’s level of exposure and vulnerability to extreme weather events (storms, floods, heatwave etc.)	Germanwatch
https://www.germanwatch. org/en/cri	

Table 2 -
Descriptive statistics of variables.
Variables	Mean	Std. dev.	ρ25	Median	p75	
Tobin-Q	2.150	2.496	1.046	1.404	2,359	
ESG	50.689	30.808	23.000	52.000	78.000	
Environmental	53.500	29.298	28.000	50.000	79.000	
Social	50.282	30.328	24.000	55.000	78.000	
Governance	49.509	31.082	21.000	50.000	77.000	
Firm-size	10.152	4.106	8.729	10.432	12.802	
Asset-turnover	0.646	1.073	0.261	0.515	0.828	
Default	0.028	0.203	0.000	0.000	0.001	
Leverage	2.086	11.463	0.002	0.003	0.008	
Cash-ratio	4.828	31.965	0.002	0.005	0.014	
Asset-growth	4.828	31.966	0.018	0.087	0.253	
EPS	57.874	1170.843	-13.039	12.985	56.213	
GDPpc	10.430	0.716	10.285	10.598	11.000	
Inflation	1.689	1.649	0.537	1.437	2.1301	
FD	0.825	0.110	0.780	0.850	0.920	
Corruption	0.964	0.737	0.476	1.212	1.464	
Goveff	1.221	0.552	1.059	1.406	1.556	
Re_quality	1.053	0.680	1.068	1.252	1.494	
Law	1.122	0.702	1.127	1.417	1.579	
Political	0.345	0.509	0.004	0.386	0.678	
VA	0.616	0.928	0.751	0.931	1.110	
EPI	68.267	14.007	62.300	70.610	79.890	
ND-GAIN	64.911	6,349	65.515	67.395	68.156	
CRI	0.6839	0.0648	0.6916	0.7113	0.7209	

rate is relatively low, at 1.689, while the average financial development index is 0.825, indicating a high level of financial development. The six governance dimensions also exhibit significant cross-country heterogeneity. The EPI has a mean of 68.267, with 25th and 75th percentile values of 62.3 and 79.8, respectively. China has the lowest EPI score, while Sweden is the top performer. The mean values for the ND-GAIN and CRI are 64.9 and 0.68, respectively, with both indices varying across countries depending on their levels of exposure and vulnerability to climate change.
3.2.		Methodology and model specifications
We test our research hypotheses regarding the cubic relationship between ESG ratings and firm value using the polynomial regression and GC approach. The empirical models are set up as follows:
yu = «’ + E/X + oh Za+ n’Cet +4 (1)
n =1
N /
Jit = a2 + XX + Sustainability, + Yj(Sustainabilityct n=l
*X) +&%Z + +e# (2)
where : Vit is firm value proxied by the Tobin-Q; Xu is the ESG rating which is assumed to have a nonlinear effect on market value with η = 1, ..., N. When η = 1, the relationship is linear. If η = 2, it is quadratic. If η = 3, it is cubed; Zu is a set of control variables captured by firmspecific characteristics; Cct includes country-level control variables; Sustainability is a measure of the institutional environment captured by the country’s governance quality and environmental sustainability. This variable is interactive with the ESG metric to examine its moderating effect on firm value; Lit is the error term. The subscript c represents the country-level variable, whereas the subscript i represents the firm-level variable.
In the first step, we test hypothesis H1 regarding the nonlinear effects of ESG on firm value controlling for the firm- and country-specific characteristics (Model 1). Power polynomials provide a flexible approach to examine if significant non-linearity persists and identify the potential threshold value within a specific range of values of X without a priori assumption of the threshold effects (Finn, 2011). Initially, we estimate a linear model, then add the quadratic, cubic terms, and so on.
In the second step, we test the moderating effects of the country’s sustainability metrics on the ESG-firm value relationship in hypotheses H2 and H3 by including each of country's sustainability variable (Sustainabilitya) and the interactive term between Sustainability and ESG (Sustainabilityet *X,) as shown in Model 2. In all estimations, standard errors are clustered at the firm level.
Dealing with endogeneity has become a focal point of methodological discussions in empirical research in finance and management (Hill et al., 2021), especially when using firm-level data. The problem arises when independent variables (such as ESG metrics and firm characteristics in our study) are correlated with the error term, leading to biased estimates and potentially misleading interpretations regarding causal effects in linear regression. The most common method to address endogeneity is using instrumental variables. However, finding valid exogenous instruments is challenging due to limited data availability. Reeb et al. (2012) highlight that a common issue in empirical business and finance research is the selection of instruments, which may inadvertently include other endogenous variables. In this study, we adopt the GC approach suggested by Eckert & Hohberger (2022) to tackle the endogeneity problem without relying on instrumental variables. This methodology is more appealing than other instrument-free methods due to its flexibility to accommodate complex relationships in the application of nonlinear models, multiple endogenous regressors, as well as interactions (Eckert & Hohberger, 2022).
The CG method was introduced by Park & Gupta (2012) to address endogeneity concerns by modelling the joint distribution of variables separately from their marginal distributions. In simple terms, it allows to capture the interdependencies between variables without imposing
strong assumptions about their distributions. The starting point is to recognise the potential interdependencies between variables, including the endogenous variables and the error term. Once the Copula function is specified to capture the dependency structure, parameters are estimated using maximum likelihood estimation. By incorporating the joint distribution of variables in the estimation, the GC helps adjust the correlation between independent variables and the error term, mitigating the bias in parameter estimates. Eckert & Hohberger (2022) conduct a series of Monte Carlo simulations to evaluate the relative performance of the GC approach in terms of estimation bias under various sets of assumptions. Building upon their exploration of boundaries in the GC approach, they offer practical guidance for implementing GC in the research area of CSR. Following Eckert & Hohberger (2022), we carefully examine the distribution of endogenous regressors, combining the Shapiro-Wilk test and visual inspection. This examination allows us to verify whether the regressor is sufficiently non-normally distributed, a critical condition for the efficient application of the GC approach to bolster the robustness of our estimates.
4.		Empirical results and discussion
4.1.		The cubic relationship between ESG ratings and firm value
Table 3 presents the estimation results for Model 1, which examines the effect of ESG ratings on firm value. We first analyse the nonlinear impact of ESG scores on Tobin-Q (Column 1) and then separately estimate the effects of each ESG component (Columns 2 - 4). All estimations include year-fixed effects as controls. As shown in Table 3, our variable of interest, ESG, exhibits a cubic relationship with firm value across all specifications. Specifically, ESG has a positive effect on firm value up to a certain threshold, beyond which the relationship reverses, turning negative. This reversal is indicated by the negative and significant coefficients associated with the squared term of ESG (X2). Additionally, a cubic effect is observed, as evidenced by the significant coefficients of cubed ESG term (X3), confirming a horizontal-S-shaped relationship between ESG ratings and firm value.
The simulation illustrated in Fig. 1 further supports this cubic pattern, demonstrating that the impact of ESG rating on Tobin-Q is nonlinear and changes direction at two critical thresholds: ESG1 = 2.87 and ESG2 = 38.56. Initially, as ESG ratings increase from low levels, firm value also rises, suggesting that firms with low ESG scores benefit from early-stage sustainability improvement. This reflects investors' willingness to reward companies for taking initial steps toward ESG

Fig. 1. The cubic relationship between ESG ratings and firm value.

integration. At this stage, ESG investments are relatively low-cost yet yield substantial returns by unlocking growth opportunities and enhancing market reputation. For firms with low ESG ratings, the benefits of improving ESG performance will outweigh the costs, possibly due to organizational learning, access to resources, and signalling effects (Zhang et al., 2020). This positive effect persist until ESG reaches the first critical threshold (ESG1 = 2.87).
Beyond this turning point, the relationship reverses, meaning that the marginal benefits of ESG investments begin to decline. Firms encounter rising costs and complexities associated with deeper ESG integration, leading to diminishing return. The negative association between ESG ratings and firm value aligns with agency theory (Jensen & Meckling, 1976). According to this theory, firms may allocate excessive resources and managerial attention to social issues, exacerbating the agency problem and ultimately reducing shareholder wealth. This perspective is supported by prior literature, which highlight a negative link between CSR and financial performance, as additional social programs often incur higher costs (Jensen, 2010; McWilliams & Siegel, 1997). Furthermore, the adverse effect of ESG on firm value is consistent with Giglio et al. (2021), who argue that traditional investment motives remains dominant in portfolio allocation decision, limiting the financial appeal of excessive ESG spending.

Variables	ESG	Environment	Social	Governance
(1)	(2)	(3)	(4)
Coef.	Std. err	Coef.	Std. err	Coef.	Std. err	Coef.	Std. err	
X
X2
X3
Firm-size
Asset-turnover Default Leverage Cash-ratio Asset-growth EPS GDPpc Inflation FD Intercept Year FEs	1.5188 * *	(0.6167)	1.4854 * **	(0.5307)	1.7423 * **	(0.5788)	0.7079	(0.5182)
-0.9278 * **	(0.2741)	-0.6531 * **	(0.2198)	-0.9325 * **	(0.2373)	-0.5299 * *	(0.2324)
0.1314 * **	(0.0400)	0.0751 * **	(0.0271)	0.1209 * **	(0.0293)	0.0757 = *	(0.0305)
-0.1559 * **	(0.0224)	-0.1546 * **	(0.0219)	-0.1592 * **	(0.0220)	-0.1627 * **	(0.0218)
0.1628 * *	(0.0785)	0.0961*	(0.0567)	0.1561**	(0.0764)	0.1000*	(0.0576)
-0.2629 **	(0.1114)	-0.3553 ***	(0.1181)	-0.3420 * **	(0.1068)	-0.3256* **	(0.1191)
-0.0150***	(0.0056)	-0.0159***	(0.0058)	-0.0154***	(0.0057)	-0.0173 ***	(0.0058)
-0.0002	(0.0017)	-0.0002	(0.0018)	-0.0002	(0.0018)	-0.0003	(0.0017)
-0.0001	(0.0001)	-0.0001	(0.0002)	-0.0001	(0.0002)	-0.0001	(0.0001)
0.0000	(0.0000)	0.0000	(0.0000)	0.0000	(0.0000)	0.0000	(0.0000)
0.2882 **	(0.1281)	0.1375	(0.1293)	0.1602	(0.1236)	0.3038 **	(0.1271)
0.0509	(0.0328)	0.0451	(0.0323)	0.0349	(0.0321)	0.0622 *	(0.0333)
-0.8827	(0.6287)	-0.6623	(0.6313)	-0.8459	(0.6163)	-0.7471	(0.6180)
1.7758	(1.5459)	2.6923 **	(1.3064)	3.0445 **	(1.2324)	2.0367	(1.2654)
YES	YES	YES	YES	

Table 3
The cubic relationship between ESG ratings and firm value.

Notes: Estimation of Model 1 is based on the Gaussian Copula approach. Variable X represents ESG and each of ESG dimensions (Environment, Social, and Governance), which were log-transformed prior to estimation. Standard errors are clustered at the firm level. * ** , * *, * denote significance at 1 %, 5 % and 10 % levels, respectively.

However, the negative phase is temporary. Once ESG ratings surpass the second critical threshold (ESG2 = 38.56), the relationship turns positive again. At this level, firms that have successfully integrated advanced ESG strategies are not merely complying with industry norms but also innovating and differentiating themselves in the market. These firms leverage their strong ESG capabilities to develop long-term competitive advantages and unlock new growth opportunities. High-
ESG firms are often viewed favourably by investors, leading to higher valuation and increased market interest. Having demonstrated a firm commitment to ESG principles, these companies effectively communicate their long-term sustainability vision, further strengthening stakeholder trust and loyalty. The increasing firm value associated with high ESG ratings suggest that the market perceives these firms as leaders in sustainability, reinforcing their competitive positioning and market valuation.
Additionally, the market rewards firms with high ESG scores, as these firms have accumulated significant SIC, allowing them to earn superior returns that offset the costs of social responsibility investments. This phenomenon can also be attributed to investor preference for top ESG performers ("green taste"), as investors believe that engaging with these firms contributes to positive societal changes. Furthermore, the demand for green stocks has surged, as they are increasingly regraded as climate-hedging assets in the face of rising climate concerns (Pastor et al., 2022). Consequently, investors are willing to pay a premium for stocks with strong ESG ratings, leading to potential overvaluation of these firms. This finding echoes Zhang (2021), who suggests that firms with high ESG scores experience sentiment-driven price jumps, especially during periods of heightened public attention to sustainability. While this overvaluation may present challenges, long-term investors continue to hold these stocks, while short-sellers often hesitate to bet them, possibly due to the short-squeeze risk. Zhang (2021) further highlight reputation risk as a key factor discouraging short-selling of high-firms. Short sellers avoid targeting these stocks, fearing backlash from profiting off companies that contribute positively to social and environmental causes.
To further explore the effects of each ESG component, we recalibrate Model 1 by analysing the Environmental (Ε), Social (S), and Governance (G) scores separately. Our findings contrast with those of Bissoon- doyal-Bheenick et al. (2023) and Nollet et al. (2016), who report inconsistent effects of E, S, and G on firm value and emphasise the importance of viewing ESG practices as integrated form of sustainable capital rather than isolated factor. The results presented in Columns (2), (3) and (4) of Table 3 confirm a consistent cubic relationship between each ESG component and firm value. The horizontal S-shaped curves in Fig. 2 illustrate double thresholds for each ESG component, albeit with slightly varying marginal effects and transitional values. Tobin-Q increases with each of E, S, and G scores up to a critical threshold (ESG1), then declines until reaching a second threshold (ESG2), beyond which firm value rises again. Environment and Social factors exhibit higher optimal points before firm value starts to decline, suggesting that firms can invest more heavily in these areas before experiencing diminishing returns. However, Governance follows a slightly different trajectory, with firm value declining earlier than in the other two dimensions. A lower threshold for Governance underscores the importance of carefully balancing governance-related investments to maximise firm value.
Overall, the analysis strongly supports Hypothesis Hi, confirming that the relationship between ESG ratings and firm value follows a cubic pattern. The observed transition from growth to decline and subsequent recovery aligns with growth options and SIC, which offer a robust theoretical foundation for understanding these fluctuations. This finding suggests that investors’ perceptions of ESG ratings are complex, as the market does not uniformly reward or penalise ESG performance.
4.2.		The moderating effect of institutional environment on the ESG-firm value relationship
Our analysis has been extended to examine the moderating effects of a country's governance quality and environmental sustainability on the relationship between ESG ratings and firm value. This extension is motivated by the argument put forward by Bissoondoyal-Bheenick et al. (2023) that individual countries and regions have pursued different paths and responses to address the evolving demand for sustainable finance. According to Dyck et al. (2019), investors from countries with

Fig· 2. The cubic relationship between ESG dimensions (Environmental, Social, and Governance) and firm value.

high environmental and social norms tend to advocate more for sustainable practices in investment decision-making. A country’s sustainability status, particularly its focus on governance and environmental issues, can influence the impact of a firm's ESG ratings on its value. This is because investors may adopt varied investment strategies when allocating funds in different countries. The transition to a low-carbon economy has become a global norm, with countries worldwide committing to this goal. Consequently, both the public and governments have encouraged investors to include financial products promoting ESG values in their investment portfolios.
The hypothesis H2 is tested by estimating Model (2) with the institutional quality proxied by six governance indicators: Voice and accountability (VA), Control of Corruption (Corruption), Political stability and absence of violence (Political), Government effectiveness (Goveff), Regulatory quality (Re_quality), and Rule of law (Law). The estimated parameters are summarised in Table 4. The cubic relationship between ESG ratings and firm value are preserved in all specifications, and interactive terms associated with these governance metrics exhibit opposite coefficient signs of those of ESG, ESG2 and ESG3, respectively. Especially notable are those interactions with ESG3 and ESG2, which are significant for most governance indicators, except Political and Goveff. These findings suggest that the impact of ESG scores on firm value diminishes in countries with better institutional quality.
Fig. 3 simulates the moderating effects of the four significant governance factors (VA, Corruption, Re_quality, and Law), supporting our H2. The curves with moderating effects lie below the original curve, with the turning points shifting as well, confirming that both benefits and costs of ESG would be lower in countries with high levels of voice and accountability, low corruption, strong regulatory frameworks, and robust rule of law. Conversely, in countries where the regulatory framework, rule of laws, and voice and accountability are weak, and where corruption is high, compliance costs and investment risk elevate, reducing firms’ incentives and ability to make value-maximising investments. Ghoul et al. (2017) emphasise that the lack of enforcement through a legal system increases challenges faced by investors, customers, and suppliers in recovering losses if a firm fails to uphold its contractual obligations. In such scenarios, these stakeholders may be reluctant to engage in long-term relationship with the firm. Thus, ESG ratings serve as a signal of firm commitments and help build stronger relationships with external stakeholders, enhancing social capital and yielding stronger effects on firm value.
Similar results were observed in testing of hypothesis H3, as reported in Table 5, regarding the moderating effects of the country’s environmental sustainability on the cubic relationship between ESG ratings and firm value. The interaction terms for EPI, ND-GAIN, and CRI show diminishing effects in comparison to ESG, ESG2 and ESG3. The S-curves in Fig. 4, which illustrate the moderating role of these factors, shift downward, indicating that the impact of ESG scores on firm value is lower in countries with superior environmental performance. One possible explanation is that, in developed countries with high levels of environmental sustainability, investors have already factored ESG considerations into their equity allocations, reducing the incremental impact on firm value. In contrast, in countries with lower environmental sustainability, firms encounter higher complexities and transaction costs as they strive to adapt to rapidly changing conditions (Lartey et al., 2021). ESG investment is seen as a crucial indicator of management quality, risk mitigation, and long-term focus on sustainability. Consequently, international investors tend to classify ESG stocks more carefully and reward firms with high ESG scores more generously in markets with greater environmental uncertainty. This aligns with the perspective that investors demand a lower premium when supporting ESG engagement. The diminishing returns in the mid-range of ESG performance are less pronounced in countries less vulnerable to climate changes and environmental shocks. However, in countries with higher environmental uncertainties, market reactions are stronger.
co
O
co 0
0
o
CO o Ó
co CM
CO
Ó
00
o
Note: Estimation of Model 2 is based on the Gaussian Copula approach. ESG variable was log-transformed prior to estimation. Sustainability represents a set of governance quality variables (VA, Corruption, Re_quality, Law, Political & Goeff), respectively. Standard errors are clustered at the firm level. * ** , * *, * denote significance at 1 %, 5 % and 10 % levels, respectively.

Fig- 3. The moderating role of a country's governance quality on ESG - firm value relationship, Notes: The curves incorporating moderating effects lie below the original curve. The corresponding turning points (threshold values) for these moderators are ESG_VA (Voice and accountability), ESG_Corruption (Control of Corruption), ESG_Re-quality (Regulatory quality), and ESG_Law (Rule of law).
Table 5
The moderating role of a country's environmental sustainability on ESG ratings - firm value relationship.
Variables	EPI	ND-GAIN	CRI	
	(1)	(2)	(3)	
	Coef.	Std. err	Coef.	Std. err	Coef.	Std. err	
ESG	9.2209	(6.1137)	51.4193 * **	(19.1568)	15.6461 * **	(5.1064)	
ESG2	-5.9357 * *	(2.9468)	-23.0681 * **	(8.0907)	-7.3741 *44	(2.1855)	
ESG3	0.7645*	(0.3984)	2.7463 ***	(1.0196)	0.8958 ***	(0.2779)	
Sustainability	-3.0629 *44	(0.9553)	2.6405	(4.2138)	-2.4046	(7.2200)	
Sustainability*ESG	-1.9372	(1.4872)	-12.2653 * 44	(4.6708)	-22.5525 * 44	(7.9320)	
Sustainability*ESG2	1.2689 *	(0.7145)	5.4405 * 44	(1.9601)	10.2735 * 44	(3.3034)	
Sustainability*ESG3	-0.1624 *	(0.0966)	-0.6439 *-	(0.2462)	-1.2268 * 44	(0.4143)	
Firm-size	-0.1479 ***	(0.0202)	-0.1466 * **	(0.0192)	-0.1389 * 44	(0.0188)	
Asset-turnover	0.1599 * *	(0.0770)	0.1767 **	(0.0861)	0.1771 **	(0.0867)	
Default	-0.1525	(0.1096)	-0.4587 * **	(0.1730)	-0.4784 * **	(0.1749)	
Leverage	-0.0165 * 44	(0.0058)	-0.0164 * 44	(0.0062)	-0.0168 * **	(0.0063)	
Cash-ratio	-0.0002	(0.0018)	0.0016	(0.0012)	0.0015	(0.0012)	
Asset_ gr	-0.0001	(0.0002)	-0.0004 *44	(0.0001)	-0.0004 * 44	(0.0001)	
EPS	0.0000	(0.0000)	0.0000	(0.0000)	0.0000	(0.0000)	
GDPpc	0.5199 ***	(0.1164)	0.4913*	(0.2544)	1.1157 * **	(0.2749)	
Inflation	0.0450 * *	(0.0214)	0.0776 * 44	(0.0233)	0.04834*	(0.0226)	
FD	0.3991	(0.5670)	-0.4395	(0.7537)	-1.0061	(0.7639)	
Intercept	10.4254 * **	(3.9706)	-11.4560	(16.6844)	-4.9256	(4.4063)	

Note: Estimation of model 2 is based on the Gaussian Copula approach. ESG variable was log-transformed prior to estimation. Sustainability represents a set of country’s environmental metrics (EPI, ND-GAIN, CRI), respectively. Standard errors are clustered at the firm level. * ** , * * denote significance at 1 %, 5 % and 10 % levels, respectively.

4.3.		Robustness tests
We assess the robustness of our empirical findings through a series of sensitivity analysis, presenting the results in Table 6. First, we exclude all time-varying control variables to mitigate potential bias in the estimated impact when modelling the regression, focusing solely on key variables of interest, ESG (Column 1). Next, we incorporate only year- fixed effects and present the outcomes in Column 2. This approach allows us to account for time-specific influences, such as the impact of
COVID-19. In Column 3, we control for firm-specific characteristics alongside time-fixed effects. Subsequently, in Column 4, we introduce a country-specific control variable, GDP per capita, while excluding year- fixed effects. In the final Column (5), we incorporate additional countrylevel control variables, including inflation and financial development. Despite employing diverse econometric settings, our findings consistently align with our baseline results as reported in Table 3.
Another set of robustness test aims to confirm the significance of the horizontal-S-shaped effect. Following the recommendations by (Haans

Fig. 4. The moderating role of a country's environmental sustainability on ESG - firm value relationship, Notes: The curves incorporating moderating effects lie below the original curve. The corresponding turning points (threshold values) for these moderators are ESG_EPI, ESG_ND-GAIN, and ESG_CRI.

Table 6 - Robustness tests.
*	No control	Year FEs	Control for firm characteristics	Control for firm and country - No Year FEs	Add country-level control variables	
	(1)	(2)	(3)	(4)	(5)	
Variables	Coef.	Std. err	Coef.	Std. err	Coef.	Std. err	Coef.	Std. err	Coef.	Std.err	
ESG	1.0243 * *	(0.521)	1.1051 **	(0.518)	1.4570 Λ *	(0.617)	1.3462 * *	(0.620)	1.3418**	(0.616)	
ESG2	-0.5152 * *	(0.232)	-0.5323 * *	(0.231)	-0.8925 ***	(0.276)	-0.8675 * **	'(0.275)	-0.8667 ***	(0.274)	
ESG3	0.0662 *	(0.034)	0.0675 * *	(0.034)	0.1272 * **	(0.040)	0.1250 * *"	(0.040)	0.1242 *-	(0.040)	
Firm-size					-0.1724 * **	(0.018)	0.1662 * **	(0.019)	0.1523 * **	(0.021)	
Asset-turnover					0.1611 **	(0.078)	0.1554 * *	(0.740)	0.1592 * *	(0.075)	
Default					-0.2482 **	(0.116)	-0.3914 ***	(0.117)	-0.4384 * **	(0.119)	
Leverage					0.0154 * **	(0.006)	-0.0157 * **	(0.006)	-0.0150 * **	(0.005)	
Cash-ratio					-0.0002	(0.002)	-0.0001	(0.002)	-0.0002	(0.002)	
Asset-growth					-0.0001	(0.000)	0.0001	(0.000)	-0.0002	(0.002)	
EPS					0.0000	(0.000)	0.0000	(0.000)	0.0000	(0.000)	
GDPpc							0.0718	(0.077)	0.2942 * *	(0.120)	
Inflation									0.0687	(0.024)	
FD									-1.0941*	(0.636)	
Intercept	1.8622 * **	(0.657)	2.0822 * **	(0.654)	4.3558 * ^	(0.806)	3.3481 * **	(1.205)	1.7058	(1.426)	
Year FEs	NO		YES		YES		NO		NO		

Notes: Estimation of model 1 is based on the Gaussian Copula approach. ESG variable was log-transformed prior to estimation. Standard errors are clustered at the firm level. * ** ,* *, * denote significance at 1 %, 5 % and 10 % levels, respectively.

et al., 2016) to enhance empirical rigor and result interpretation in testing nonlinear relationships, we divide our data sample into two sub-samples based on the turning point of x = 2.3404 (corresponding ESG score of 10.39), when the effect of ESG transitions from an inverted U-shape to a U-shape, and re-estimate Model (1). The results for the two sub-samples are presented in Table 7. Sub-sample 1 includes observations with an ESG score (in logarithm form) below 2.3404, and sub-sample 2 comprising those with an ESG score above 2.3404. The main finding regarding the ESG-firm value relationship remains qualitatively unchanged. In sub-sample 1, the coefficient associated with ESG is significantly positive, while that of ESG2 is negative and significant, confirming the inverted U-shape. Conversely, in sub-sample 2, the coefficients reverse in sign, with ESG showing negative effect and ESG2 a
positive effect, consistent with U-shaped relationship.
Finally, hypotheses 2 and 3 suggest potential cross-country variations in the relationship between ESG ratings and firm value, contingent upon the moderating role of institutional quality, environment sustainability, and possibly unobservable country-specific factors. Therefore, we re-estimate Model (1) using various sub-samples: (i) advanced economies versus developing countries, and (ii) listed firms in Asian, American, and European countries. The estimated results are summarised in Table 8. Overall, we observe that the cubic relationship is consistent across all sub-samples. Results reported in Columns (1) and (2) suggest that the nonlinear effect of ESG is more pronounced in developing countries than in advanced economies. When comparing different regions, we find a more significant effect of ESG in Asia
Table 7 -
Estimation of ESG effect on firm value with sample breakdown.
	Sample 1 (Low ESG)	Sample 2 (High ESG)	
	(1)		(2)		
Variables	Coef.	Std. err	Coef.	Std. err	
ESG	2.6279 * **	(0.6684)	-2.3801 * **	(0.8532)	
ESG2	—1.1604 * **	(0.6684)	0.3104 * *	(0.1216)	
Firm-size	-0.2074 * **	(0.6684)	-0.1500 * **	(0.0237)	
Asset-turnover	0.3135	(0.6684)	0.1647 * *	(0.0796)	
Default	-12.8573 * *	(0.6684)	-0.2482 * *	(0.1054)	
Leverage	-0.0118	(0.6684)	-0.0149 * **	(0.0055)	
Asset-growth	-0.0024 *	(0.6684)	-0.0001	(0.0001)	
Cash-ratio	-0.0318 * *	(0.6684)	-0.0001	(0.0017)	
EPS	0.0000	(0.0000)	0.0000	(0.0000)	
GDPpc	2.0356 * *	(0.6684)	0.3301 * **	(0.1258)	
Inflation	0.0047	(0.6684)	0.0615 *	(0.0337)	
FD	-13.5713 * *	(0.6684)	-0.2618	(0.5898)	
Intercept	-5.3693	(0.6684)	4.9132 * *	(2.2275)	
Year FEs	YES		YES		
Notes: Estimation of Model 1 is based on the Gaussian Copula approach. ESG variable was log-transformed prior to estimation. The threshold value used to separate the data sample is log(ESG) = 2.3404. Standard errors are clustered at the firm level. 4 ** , 4 *, * denote significance at 1 %, 5 % and 10 % levels, respectively.

compared to America, and more so in America compared to the EU. It is noteworthy that although the coefficient signs of ESG are maintained for the EU, they lose statistical significance. This may be attributed to the greater information efficiency of financial markets in advanced economies, where social and ethical considerations hold particular importance, especially in Europe. Consequently, these markets have already factored ESG criteria into asset pricing. These testing results support the assertions of Hypotheses 2 and 3 and are consistent with prior research, which suggests that investors from countries with stricter environmental and social standards tend to advocate more for sustainable practices in investment decision-making (Dyck et al., 2019). Consequently, financial markets in these regions tend to incorporate ESG factors into asset pricing, leading to a more attenuated effect of ESG on firm value.
5.		Conclusions and implications
5.1.		Summary of key findings
Since the introduction of ESG principles by the United Nation’s Principles of Responsible Investment in 2006, ESG factors have gained significant traction, accounting for over a third of the total global assets under management from 2016 to 2020. According to the Global Sustainable Investment Association, these assets totalled $35 trillion, representing over 36 % of total professionally managed assets. This growth was even more pronounced in mutual funds and exchange- traded funds explicitly reporting investments in ESG or socially responsible assets, whose assets under management grew more than tenfold, surpassing $2 trillion. Despite this widespread adoption, the motivations driving ESG investments - whether ethical, social, or financial - remain a subject of debate. Furthermore, inconsistencies in ESG ratings and ambiguous classification criteria present challenges for investors seeking to integrate ESG performance into their strategies. These complexities have fuelled concerns over greenwashing, complicating sustainable investment decisions.
While extensive research has examined the link between ESG performance and firm value, empirical findings remain inconclusive, reflecting substantial heterogeneity in investor motives and return expectations (Giglio et al., 2025). Using a comprehensive dataset of the largest listed firms across 12 countries and applying the GC method to address endogeneity concerns, this study investigates the influence of ESG ratings on firm value, the moderating role of the institutional environment, and the underlying mechanisms driving these effects. Our findings reveal a cubic relationship between ESG ratings and firm value, following a horizontal-S-shaped curve. Firm value initially increases with ESG ratings up to a critical threshold, then declines before rising again beyond a second threshold. This pattern holds across both composite ESG scores and individual ESG dimensions. We attribute this curvilinear relationship to the interplay between growth options and SIC mechanisms, which operate at different ESG stages to influence firm value.
Furthermore, our results highlight the role of institutional factors, such as governance quality and environmental sustainability, in shaping this relationship. In well-developed markets with strong governance, rigorous sustainability commitments, and stringent regulatory frameworks, the marginal benefits of ESG improvement diminish as these factors are already embedded in asset pricing. Consequently, the impact of ESG performance on firm value is less pronounced in such environments.
5.2.		Theoretical and managerial implications
Our empirical findings yield important theoretical and policy implications. Economic theory and historical financial markets suggest that assets linked to major economic and social transformations often experience significant price corrections following an initial investment surge. However, our analysis indicates that ESG asset valuations may be overstretched. The identification of cubic S-shaped relationship between

Table 8 - Cross-country analysis.
Variables	Advanced Economies (1)	Emerging Markets	Asia (4) Coef.	Std. err	America (3) Coef.	Std. err	Europe (5) Coef.	Std. err	
		(2) Coef.	Std. err							
	Coef.	Std. err									
ESG	1.2811 **	(0.523)	1.2246* *	(0.583)	1.4435 * *	(0.649)	1.6814*	(0.924)	0.9045	(0.733)	
ESG2	-0.5650 * *	(0.244)	-0.8777 * **	(0.268)	-0.9976 * **	(0.297)	-0.6956 *	(0.366)	-0.4468	(0.394)	
ESG3	0.0701 * *	(0.033)	0.1277 * **	(0.035)	0.1437 * -	(0.038)	0.0819*	(0.045)	0.0644	(0.056)	
Firm-size	-0.1366 * **	(0.031)	-0.1260 * **	(0.021)	-0.1334 * **	(0.024)	-0.0879 * **	(0.025)	0.3152 * **	(0.114)	
Asset-turnover	0.1552 *	(0.080)	0.5243 * **	(0.115)	0.5286 ***	(0.127)	0.0934 ***	(0.035)	1.5235	(0.953)	
Default	-0.0599	(0.150)	-10.0698 * **	(2.860)	-10.5938 * *	(4.343)	-20.6917 * **	(6.842)	-0.2549	(0.238)	
Leverage	-0.0162 * **	(0.006)	-0.2983	(4.317)	-17.1939	(15.683)	-0.0134 * *	(0.005)	10.3877	(6.417)	
Asset_growth	-0.0001	(0.000)	1.0259 * Λ*	(0.269)	1.5763 * **	(0.417)	-0.0001	(0.000)	0.1283	(0.141)	
Cash-ratio	-0.0004	(0.002)	70.4118 * **	(17.824)	80.8384 * **	(21.010)	0.0002	(0.002)	42.9009 * **	(16.384)	
EPS	0.0001	(0.000)	0.0000	(0.000)	0.0000	(0.000)	0.0000	(0.000)	-0.0001	(0.000)	
GDPpc	0.2987	(0.393)	1.4847 * **	(0.335)	3.2613***	(0.749)	0.8465 * **	(0.262)	-0.3088	(0.472)	
Inflation	0.1903 * **	(0.044)	-0.0800 * *	(0.035)	0.0271	(0.067)	-0.0032	(0.026)	0.0319	(0.075)	
FD	0.9600	(0.630)	-11.9685 * **	(2.191)	-22.0106 * **	(4.269)	-3.2543 *	(1.758)	2.624	(1.652)	
Intercept	-1.4162	(4.237)	-2.3906	(2,208)	-13.0253 * **	(4.537)	-3.4322 * *	(1.599)	4.7838	(4.434)	
Year FEs	YES		YES		YES		YES		YES		
Notes: Estimation of Model 1 is based on the Gaussian Copula approach. ESG variable was log-transformed prior to estimation. Standard errors are clustered at the firm level. * ** , * 4, 4 denote significance at 1 %, 5 % and 10 % levels, respectively.
ESG ratings and firm value underscores the complexity of investors' perceptions, as the market neither uniformly reward nor penalise ESG performance. Instead, sustainability-linked assets are priced dynamically based on their ESG positioning, reflecting varying degrees of investor preferences, sustainability-driven valuation effects, and evolving market sentiment. The differential pricing of ESG-oriented stocks influences firms’ cost of capital and, consequently their corporate behaviour. The observation that stocks with high ESG ratings may be overpriced suggests that market participants may be assigning excessive value to firms with strong sustainability credentials. Conversely, the higher risk premiums associated with low ESG-rating stocks highlights the complex dynamic of market demand and risk perception in ESG valuation. These insights can help refine asset pricing models that incorporate investors' diverse motives and expectations, enabling a more accurate assessment of ESG-related return variations across different investor profiles.
From a managerial perspective, the market's diverse response to ESG performance emphasises the importance of considering whether ESG ratings should be the ultimate goal in addressing environmental, social and governance issues. The presence of dual thresholds in the cubic response functions implies that there are optimal ranges of ESG scores where firms experience the greatest positive impact on market value. Firms at different stages of their ESG journey may require distinct strategies to attract investor attention regarding their commitment to delivering products that incorporate ESG values. Firms need to carefully assess the trade-off between ESG initiatives, aligning with stakeholders’ expectation and their impact on market valuation. Understanding these threshold values can help firms strategically manage their ESG performance to maximise shareholder value. The finding that a country's governance and environmental sustainability moderate the ESG-value relationship highlights the importance of the institutional environment in shaping market outcomes. Investors will closely scrutinise a country's sustainability commitment when allocating investment funds to different nations. Therefore, it is crucial for governments, particularly those in emerging markets, to create a supportive regulatory framework that incentivises firms to adopt sustainable practices and enhance market efficiency in the transition to a lower carbon economy.
5.3.		Limitations and future research
This study has certain limitations that should be acknowledged to pave the way for potential avenues in future research. First, we recognise the divergence of ESG ratings across different rating agencies. However, this study only utilises data from S&P Global ESG Rank as it is more comprehensive for our analysis setting compared to others. Although we attempted to include data from other providers, we encountered a significant number of missing observations. Future studies could extend our analysis by comparing ESG data from different agencies and extracting common factors from various sources to address the divergence issue. Second, it is argued that investment in ESG has delayed effects on firm value and long-term sustainability. However, due to data constraints, we could only analyse the period from 2015 to 2021. We anticipate that extending the time frame could provide insights into both short and long-term effects. Third, while we proposed and validated a horizontal S-shaped relationship between ESG performance and firm value, underpinned by growth options and SIC mechanisms, we did not fully explore the deeper drivers of this shift. Specifically, factors such as changes in investors' incentives and preferences influencing their decision-making were not thoroughly examined. Future research employing primary data or natural experiments could offer a more comprehensive understanding of the dynamics behind ESG’s impact on firm value.
Declaration of Generative AI and Al-assisted technologies in the writing process
During the preparation of this work the authors used ChatGPT to improve readability and language. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.
Declaration of Competing Interest
The authors would confirm that there are no conflicts of interest.
Data availability
Data will be made available on request.
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