Carbon Emissions, Green Investment, and Firm Value: The Role of Integrating External and Internal Sustainability Governance Mechanisms? Evidence from the UK FTSE 350 Firms

Abstract

This article discusses the influence of carbon emissions, both direct and indirect, on firm value. It also takes into account the moderating variable of green investment and whether governance mechanisms—like external assurance of greenhouse gas (GHG) emissions and CSR/sustainability committees—affect these relationships. The hypotheses of the study were developed using the lens of the natural-resource-based view, legitimacy theory, and agency theory. This paper leverages panel data spanning 2017 to 2024 on firms in the UK FTSE 350 to examine the moderating role of green investment on the linkage between GHG emissions and firm value. We then conduct sub-sample analyses for firms with and without externally verified GHG disclosures and CSR/sustainability committees, respectively. Firm value is captured using enterprise value, shareholder value, and the price-to-book ratio as alternative proxies for robustness. The results reveal that GHG emissions have a significant negative impact on firm value, while green investment mitigates this adverse effect. This impact is driven by both Scope 1 and Scope 2 emissions. However, green investments are more likely to be interpreted as genuine, durable, and value-creating when (a) the firm’s emissions data are externally verified and (b) an active CSR/sustainability committee guides and monitors implementation. This study adds to the environmental accounting and corporate governance literature by providing empirical evidence that external assurance and internal sustainability oversight strengthen the relationship between environmental responsibility and firm value creation.

1. Introduction

In the context of firms, sustainability and carbon emissions are increasingly important to corporate strategy given the growing regulatory and stakeholder expectations for environmental responsibility (Al Frijat et al., 2025; Dmuchowski et al., 2023). Companies are now required to report and manage GHG emissions and incorporate sustainability into their governance and strategy. This trend highlights the need to explore the impact of environmental performance on firm value. The sustainable development idea has been expressed as an “investment strategy that meets and balances the needs of current and future generations” (K. H. Lee et al., 2015, p. 1). A firm’s good environmental performance, driven by the adoption of ‘green’ practices in its operations, is a significant factor affecting the environment and, as a result, firm value (Murwaningsari & Rachmawati, 2023). Recently, a greater worldwide emphasis has been placed on sustainability and environmental protection by stakeholders in society, including the academic community, policymakers, and regulators (Al Frijat et al., 2025; Gulluscio et al., 2020). This, in turn, has led to increased attention to climate change and green investment in academic research (Dmuchowski et al., 2023; Marie et al., 2025). Climate change, driven by GHG emissions that cause global warming, represents a critical challenge facing global society due to the need to achieve net-zero GHG emissions by 2050. As noted by Wan et al. (2025, p. 1258), global warming-related risks lead to “substantial damage to the natural ecological environment, with greenhouse gas emissions—primarily carbon dioxide from human activities—recognized as the main driver since the mid-20th century”. Consequently, global warming-related risks can hinder economic growth (Rabbani & Kiran, 2025), lead to the occurrence of floods and droughts (Al Rabab’a et al., 2023), and disrupt ecological and financial systems (Busch & Lewandowski, 2018; Al Frijat et al., 2025).

The UK is an appropriate context for this research as it is a mature market with sophisticated environmental regulation and GHG reporting requirements (DEFRA, 2013; UK Secretary of State, 2013). Recent regulatory changes have also enhanced climate reporting, and the UK is a suitable setting to study the relationship between emissions, governance, and firm value. This is because public awareness of the negative financial impacts of high carbon-related risks, especially among companies, is rising (Al Rabab’a et al., 2023). Since companies are major energy consumers and significant sources of environmental pollution (Huang & Lei, 2021), they face increasing pressure to reduce GHG emissions from their energy use. There has been a rising demand from society for financial institutions to take on environmental responsibilities and increase transparency regarding firms’ environmental footprints (Al Frijat et al., 2025). Globally, there have been shifts toward climate risk management. To mitigate GHG emissions and combat global warming, many countries ratified the Kyoto Protocol in 1997. The Kyoto Protocol of 1997 is recognized as an environmental regulation that increases firm value, combats global warming by mitigating GHG emissions, and promotes green investment (K. H. Lee et al., 2015). Numerous environment-related factors can influence a firm’s value, such as adjusting GHG emissions or incentivizing green investments (Murwaningsari & Rachmawati, 2023). Reducing or managing carbon-related risks and improving financial performance create new investment opportunities, thus increasing firm value as well as environmental performance (Prosperi & Zanin, 2024). Environmental and social responsibilities also impact company reputation (Machmuddah et al., 2020).

In practice, sustainability governance mechanisms play an important role in firms’ environmental strategies. External assurance increases the reliability of GHG reporting and decreases information asymmetry (Shen et al., 2020; Pizzi et al., 2024), while internal mechanisms like CSR/sustainability committees help monitor and implement sustainability strategies (Shokomi & Yahaya, 2024). These mechanisms shape market perceptions of environmental initiatives. Therefore, firms have begun to pursue sustainable development by adopting green economy strategies. It is therefore crucial to support organizations in their investment decisions regarding whether and how to invest in environmentally friendly projects, assisting in guiding the global economy towards higher levels of sustainability (Reitmaier et al., 2025). Investments in environmental protection are also called green investments. As defined by Eyraud et al. (2013, p. 853), green investment represents “the investment required to decrease greenhouse gas and air pollutant emissions while not very seriously compromising the production and consumption of non-energy products”. Thus, green investment (e.g., an environmentally friendly project) plays an important role in decreasing the negative environmental impacts of corporate activities (Q. Wang et al., 2015; K. Wang et al., 2018). In turn, it is argued that financial institutions facilitating the expansion of green investment constitute a strategic imperative for spearheading the global economic “green transformation” (Chen & Ma, 2021). Consequently, business regulations should support companies’ green initiatives in energy efficiency and GHG emissions reduction. However, economic benefits may significantly influence the growth of green investment if the balance between financial gains and environmental goals is considered (Chen & Ma, 2021). This leads us to question whether green investment can moderate the relationship between GHG emissions and firm value.

Furthermore, external verification of GHG emissions and the presence of a sustainability committee have received increasing interest from sustainability researchers. These variables demonstrate to relevant constituencies, such as external stockholders, that the firm is committed to sustainable practices and aims to improve the disclosure of all environmental activities. It has been stated that a sustainability committee improves a firm’s performance regarding sustainability (Shokomi & Yahaya, 2024). Likewise, external assurance is viewed as a practical tool for influencing firm value (Pizzi et al., 2024; Shen et al., 2020). Investors and management are likely to rely heavily on these factors when assessing a company’s value in the marketplace. In addition, these factors serve as effective tools to improve the transparency of the firm. They reflect better external and internal corporate governance structures that may also boost firm value. Shokomi and Yahaya (2024) and Rini (2024) highlighted the importance of the existence of a sustainability committee in enhancing firm value. This also applies to the external assurance of GHG emissions (Shen et al., 2020).

This research study examines the role of green investment as a moderator in the relationship between GHG emissions and firm value. The relationship between GHG emissions and firm value is mixed. The apparent paradoxes may be because previous studies have not considered the moderating effect of green investment; companies with high emissions but high green investment may be valued differently than companies with low emissions and low green investment. A further study is required to determine if the relationship between green investment and emissions is moderated and to understand when emissions are punished and when they are tolerated. The study examines GHG emissions and green investments in developed nations. This advancement contributes towards a more nuanced understanding of the relationship between environmental sustainability, sustainable development, and firm value, creating a stronger case for future work that could support findings regarding the fact that GHG emissions and green investments could frame development in a developing population that is experiencing a nexus of economic and environmental challenges.

This research has three contributions. First, it explores the link between GHG emissions and firm value and includes green investment as a moderator. Green investment is the key mechanism because it signals environmental commitment rather than mere pollution. Without it, high emissions signal regulatory risk and lower firm value. With it, investors price the firm on its transition trajectory rather than current emissions, resolving why prior studies find contradictory results. Second, it builds on existing research by considering both external assurance and CSR/sustainability committees. External assurance and CSR committees are considered together as complementary governance mechanisms. External assurance is a third-party verification mechanism based on market principles that increases the credibility of the emissions information. CSR committees are internal governance structures that embed environmental oversight into board-level decision-making. These mechanisms should be examined together since they represent the demand side (external pressure) and the supply side (environmental oversight) of corporate climate governance. Third, it presents evidence from UK FTSE 350 firms, contributing evidence from a mature market with sophisticated sustainability practices.

The remainder of this study is organized as follows. Section 2 provides a literature review, the theoretical framework, and hypotheses development. Section 3 displays the study method. Section 4 explains the empirical analysis. Conclusions and policy implications are given in Section 5.

2. Literature Review, Theoretical Framework & Hypotheses Development

This research adopts a multi-theoretical approach to explain the proposed relationships. The natural-resource-based view and legitimacy theory are applied to explain the effects of environmental performance and green investment on firm value. Further, agency theory is used to explain how sustainability governance mechanisms, such as external assurance and CSR/sustainability committees, reduce information asymmetry and increase the reliability of environmental disclosures.

The UK has taken a leadership role in promoting climate-related disclosures by requiring that GHG emissions be disclosed in the annual reports of publicly listed companies since 30 September 2013, in accordance with the Carbon Disclosure Regulation (CDR) (DEFRA, 2013; UK Secretary of State, 2013). This has been further emphasized in the Financial Conduct Authority’s disclosure rules, taking effect in January 2022. Furthermore, UK firms are required to comply with the Taskforce for Climate-related Financial Disclosures rules from 2022. The country’s declining GHG emissions are critical to achieving the net-zero commitment mandated by the Climate Change Act 2008 and the 2050 Net Zero Strategy. Nonetheless, achieving climate goals remains a pressing challenge. In their report, Burnett et al. (2024) found ongoing advancements in the reduction in emissions, revealing that the territorial emissions levels for 2024 are 50.4% lower compared to those of 1990. The territorial emissions of the UK decreased by 2.5% in 2024, amounting to 413.7 metric tonnes of carbon dioxide equivalent (CO2e). The gap between ambition and reality remains significant, which requires more research in this regard to address this issue.

There is increasing public demand (for instance, from investors, customers, and regulators) to measure, manage, report, and minimize companies’ CO₂ emissions (Bolton & Kacperczyk, 2021). Stakeholders are concerned with the GHG emissions of firms for three main reasons. First, carbon assets materially inform risk exposure (Millar et al., 2018). Second, firms with higher GHG emissions may incur additional investment (risk) premiums on their cost of capital, thus lowering their valuation (Zheng & Jin, 2023). Third, GHG emissions may signal the quality of firms’ long-term carbon management capabilities and the urgency of governance decisions, which, in turn, reflect their commitment to sustainability (Herman, 2024).

To a large extent, GHG emissions relate to the production of firms, the amount of energy used, and other activities of firms—activities that lead to corporate mission success, stakeholder satisfaction, and financial performance success (J. H. Lee & Cho, 2021). However, GHG emissions will tend to increase material risk since they provide indicators of the potential for stranded assets, litigation, and operational fallouts, which impact the overall risk profile of firms. In this regard, the lower intensity of GHG emissions may be an indicator of higher operational efficiency and reduced funding needs in the future, which correlates with higher firm value and active investment in this direction (Zheng & Jin, 2023). Nevertheless, there is the possibility of a gap between real emission levels and official reporting, which indicates undisclosed carbon emissions (Zheng & Jin, 2023). Thus, firms may rely on green investment to cut emissions or enhance environmental performance. These projects can be described as a strategic reaction to the pressure from stakeholders and are becoming more and more a force behind future competitiveness and firm value.

The literature shows an unresolved tension: negative emissions–value links are based on reputational and regulatory risk arguments (Matthews et al., 2025; Perdichizzi et al., 2024), whereas null or positive links are based on emissions as a proxy for productive scale (Haque & Ntim, 2020; Haque, 2017). This paradox is probably due to unobserved credibility, i.e., the markets are unable to differentiate between true environmental risk and simply output intensity when disclosure quality is not uniform. A recent study in the UK finds that both the nature of strategy and the governance of the board have a significant impact on the outcomes of carbon performance (Issa & Zaid, 2026). National-level frameworks for measuring the impacts of emissions on the environment show how complex the institutional landscape is for measuring carbon at the firm level (Ou et al., 2026; Bose et al., 2026). This measurement noise is minimized by the UK’s compulsory SECR framework.

This study uses three theories as a complementary lens to develop hypotheses. The demand side is set by the stakeholder theory, which says that investors, regulators, and consumers will punish emissions for their unpriced environmental risk and social burden. Legitimacy theory focuses on the supply response; that is, firms invest in green projects to sustain their social license, but only if stakeholders believe that the investment is credible. Agency theory fills in the missing pieces by highlighting the governance structures that mitigate information asymmetry between managers and markets, making green spending a credible indicator of strategic intent: external assurance and CSR committees.

2.1. The Effect of GHG on Firm Value

There is an important scholarly debate that has emerged around the potential pros and cons associated with firms adopting environmental sustainability (Qiu et al., 2016). The natural-resource-based perspective (NRBV) proposed by Hart (1995) is often used to substantiate the idea that the environmental performance of a firm is positively related to its value. It claims that companies promoting environmental sustainability are able to increase their competitive advantage due to their ability to use scarce, valuable, and unique resources (Perdichizzi et al., 2024).

While reflecting their environmental performance, a firm’s GHG emissions intensity is an important consideration for firm value (J. H. Lee & Cho, 2021). An increase in GHG emissions or carbon intensity (i.e., emissions per unit of revenue or output) signifies that the firm imposes a more severe burden on society and the environment, thus increasing related liabilities/risks (Matthews et al., 2025; Perdichizzi et al., 2024; Baboukardos, 2017). Proactive emission reductions made by firms can likely alleviate this perceived environmental risk Potential liabilities may include increased regulatory scrutiny (Griffin et al., 2017); costs of capital (Kacperczyk & Peydro, 2021), including debt financing and equity financing (Safiullah et al., 2022); reputational damage (M. Lee et al., 2022); and ethical issues. Such liabilities create a negative market reaction and ultimately reduce firm value. These liabilities are more pronounced in constrained external environments with stricter regulatory policies and national GHG trading systems). By adopting pollution prevention practices, companies can drive costs down, comply with regulations, and repair their public image. Companies may also use pollution prevention strategies that can mitigate both costs associated with inefficiency as well as potential future environmental liabilities, thereby maximizing longer-term value creation and competitive advantage for firms.

The interplay of GHG emissions and firm value is complex, evidenced by disparate findings of existing research, reflecting a range of variables (e.g., real vs. symbolic carbon performance and divergent regulatory environments) (Haque & Ntim, 2020; Haque, 2017). On the one hand, prior research asserts that GHG emissions reduce firm value (Matthews et al., 2025; Perdichizzi et al., 2024; Baboukardos, 2017). A significant body of research indicates that market value is prioritized through symbolic carbon performance (i.e., the adoption of process-based carbon reduction methods rather than actual greenhouse gas reductions) (Haque & Ntim, 2020). As a result, we developed the following hypothesis:

H1. 

GHG emissions are likely to negatively affect firm value.

2.2. The Moderating Role of Green Investment

According to legitimacy theory, companies should improve their carbon performance to improve their legitimacy (Perdichizzi et al., 2024). Green investments provide a way for firms to convey and increase their value proposition with regard to GHG emissions and ultimately legitimize their practices Thus, green investments can mitigate climate risk and create value when stakeholders view such investments as material to the company’s performance (Rabbani et al., 2025). Green investment is a renewed focus on attempting to mitigate the environmental impact a company has on its growth and operations. Companies with a high GHG emissions history are more willing to pursue green technology and want to convert GHG-emitting technology due to social pressure (M. Lee et al., 2022). Such an investment may reduce profit margins; however, carbon-intensive firms face significant pressure that leads them to engage in extensive rehabilitation to generate a significant change towards low-carbon technology to maintain their social contract with the public (Perdichizzi et al., 2024). Pursuing such legitimacy may lead to an improvement in the firm value, thus altering the negative impact of GHG emissions. Also, investors value green investment not because of the expense, but because of the message it conveys: transition credibility. A high-emission company that invests in abatement projects has identified its exposure and has plans to address it, which lowers the uncertainty of future regulatory costs and stranded asset risk. If there are no governance measures to ensure the emission baseline is accurate and that investments are made with the intention of reducing emissions, the signal is ignored by markets as greenwashing (Mateo-Márquez et al., 2022). Higher green investments allow for greater environmental capacity and increased resilience to carbon reduction pressures. Green investment can also signal and accentuate the importance of acquired supporting technologies, augmenting returns on subsequent green investments (Zheng & Jin, 2023; J. H. Lee & Cho, 2021). Accordingly, we developed the following hypothesis:

H2. 

Green investment is likely to positively moderate the relationship between GHG and firm value.

2.3. Role of External and Internal Sustainability Governance

Market value is also expected to be affected by the credibility of the sustainability governance framework that firms adopt. According to the theory of legitimacy, the need for legitimacy may compel firms to disclose when there is a shift in social expectations; the disclosure should be credible to minimize information asymmetry, reputational risk (Perdichizzi et al., 2024), and greenwashing risk, which can be indicated by external assurance and the internal existence of a CSR committee (Mateo-Márquez et al., 2022). In practice, carbon performance has been associated with firm value, and markets penalize increased GHG emissions (e.g., Benkraiem et al., 2022). Green investments also have the potential to reduce climate-related risk and generate value when they are perceived as material, rather than symbolic (Rabbani et al., 2025; Perdichizzi et al., 2024).

The aforementioned governance mechanisms are central to converting green investment from a cost into a value-enhancing signal. Therefore, external assurance constitutes a key and formal governance mechanism that can enhance the credibility of GHG disclosures. Agency theory posits that assurance quality improves the credibility of such information and diminishes information asymmetry, especially for non-financial indicators that are not inherently subject to objective assessment (Iqbal & Keay, 2019). In this way, it reduces uncertainty for investors and increases the price sensitivity that investors have to reductions in emission actions (Pizzi et al., 2024; Elbardan et al., 2023). Empirical evidence indicates that when external assurance is applied, there is a greater environmental policy commitment to emission reductions and a greater likelihood of implementing an internationally recognized standard verification for GHG (Brooks & Oikonomou, 2018). In sum, external assurance reinforces confidence in the data measured, leading to stronger market responses to measured reductions (or increases) in emissions. This means that assurance enables investors to believe that firms actively manage their GHG emissions, which will reduce their negative impact on value.

Second, as an internal governance mechanism, the CSR committee institutionalizes the oversight, strategic coordination, and implementation of sustainability initiatives, and enhances firm credibility and ultimately firm performance (Bifulco et al., 2023). The CSR committee is considered vital for overseeing the establishment of strategic, measurable, and effective climate targets. Research shows that such committees strengthen the relationship between ESG activities and market outcomes by ensuring that environmental spending is strategic and monitored (Shokomi & Yahaya, 2024). Accordingly, board-level CSR committees signal internal commitment and the capability to translate green investment into a positive market reaction. Consequently, we developed the following hypothesis:

H3. 

The positive moderating effect of green investment is significantly stronger for firms that (i) have externally assured GHG disclosures and (ii) maintain an active CSR/sustainability committee.

3. Study Method

3.1. Research Design and Approach

This study adopts a quantitative research design where an annual panel data regression model is used for analysis. This study also focuses on a sample of UK FTSE 350 companies, which offers evidence from one of the most open and sustainability-oriented markets in the world. Firms are chosen from the FTSE 350 as the regulatory environment (SECR) requires companies to report GHG emissions consistently, which provides high-quality panel data for econometric estimation. They also have a large market capitalization and homogeneous reporting standards, which reduce measurement error and selection bias compared to a larger or smaller sample of firms. Secondary data utilized in this study are obtained from the Refinitiv Eikon/Thomson Reuters ESG database. The time frame examined is from 2017 to 2024, providing sufficient variability in the firms and time. The sample comprises FTSE 350 non-financial companies that have available data on firm value, greenhouse gas (GHG) emissions, and corporate governance indicators. All firms appearing in the FTSE 350 index at any time during the study period were included at the start. By design, financial sector firms were not included to avoid regulatory distortions that are unique to financial institutions, such as banks and insurers. Some observations were omitted because of missing values in important regression variables.

The first data set contains FTSE 350 non-financial companies between 2017 and 2024, which were acquired via Refinitiv Eikon. A listwise deletion method was used to remove observations with missing values for important variables (firm value, GHG emissions, green investment, and governance indicators) to achieve consistency across variables. Consequently, the end sample is an unbalanced panel, which captures variations in ESG disclosure by firms and years. Financial firms were not included because they have a different regulatory environment and capital structure. The data were not winsorized, but logarithmic transformations of some variables (e.g., GHG emissions and firm size) were used to reduce the impact of extreme values.

3.2. Variable Definition

The variables are quantitatively measured using standardized financial and environmental indicators derived from the Refinitiv Eikon ESG database for the FTSE 350 firms (

Table 1. Variable measurement.

Variable	Proxy/Measurement
Dependent variable Firm Value	Tobin’s Q (TA -BV + MV/Total Assets)
Independent variable GHG (Total GHG) Scope 1 Scope 2	Natural log of total GHG emissions (Scope 1 + Scope 2 + Scope 3) Natural log direct GHG Natural log of indirect GHG
Moderating variable Green Investment (Green Inv)	Dummy variable = 1 if firm reports specific green investment or capital expenditure; 0 otherwise This measure presents the disclosure of the current share or amount of green capital expenditure deployed to climate-related opportunities.
sub-sample classifications 1. Assured Subsample vs. Non-Assured Firms: Emphasizes credibility and verified reporting vs. Highlights lack of third-party verification 2. CSR/Sustainability Committee vs. Non-Committee Firms Emphasizes the presence of internal sustainability governance vs. indicates the absence of dedicated sustainability governance	Dummy = 1 if sustainability/ESG report is externally assured; 0 otherwise Dummy = 1 if firm has a CSR or sustainability committee; 0 otherwise
Control Variables Board size, board diversity (% female), board independence (% independent), audit committee independence (% independent directors), CEO duality, return on equity (ROE), cash holdings, leverage (Lev), and firm size (log of total assets)

).

Dependent Variable: Firm value is measured using Tobin’s Q ratio. Tobin’s Q reflects the market’s assessment of the firm’s future growth potential and investment efficiency.

Independent Variables: Total GHG emissions are measured as the natural logarithm of total greenhouse gas (GHG) emissions, including Scope 1 (direct) and Scope 2 and 3 (indirect energy-related) emissions, consistent with the GHG Protocol standards. The use of a logarithmic transformation mitigates skewness and allows for comparability across firms of different sizes.

Moderating variable: Green investment is measured as a binary (dummy) variable that takes the value of 1 if the firm reports green or environmental capital expenditures or projects, and 0 otherwise.

Assurance-Based Subsample and Committee-Based Subsample: To test the third hypothesis, the sample was subdivided into two governance-based subsamples: (1) assured vs. unassured firms, and (2) committee vs. non-committee firms. External assurance is a dummy variable that is equal to 1 when a firm has its sustainability or ESG report externally assured by an independent third party, and 0 otherwise. The presence of a CSR or sustainability committee is also a binary variable, coded as 1 if the firm has a dedicated board-level committee overseeing corporate social responsibility or sustainability activities, and 0 otherwise.

3.3. Research Model

This study tests how GHG emissions affect firm value and whether this relationship is moderated by green investment. The variables external assurance and CSR/sustainability committee serve as the basis for dividing the sample. A panel OLS regression was used to achieve the study’s goal. Year fixed effects were included to account for time-invariant factors across the study sample. Below are the formal econometric specifications used in the analysis.

$$\begin{array}{cc}{Firm Value}_{it}=& {\beta }_0{+\beta }_{1 }{GHG}_{it}+{\beta }_2{Green Inv}_{it}+{\beta }_3{({GHG}_{it} \times {Green Inv}_{it})}_{it}+{\beta }_4{Boardsize}_{it}+{\beta }_5{Boarddiv}_{it}\hfill \\ & +{\beta }_6{IndependD}_{it}+{\beta }_7{AuditComInd}_{it}+{\beta }_7{CEO duality}_{it}+{\beta }_8{ROE}_{it}+{\beta }_9{Cash}_{it}+{\beta }_{10}{Lev}_{it}\hfill \\ & +{\beta }_{11}{Size}_{it}+Y+{\epsilon }_{it}\hfill \end{array}$$

• ${Firm value}_{it}$ = Firm value of firm i at time t
• ${GHG}_{it}$ = carbon emission of firm i at time t
• ${Green Inv}_{it}$ = green investment of firm i at time t
• ${GHG}_{it} \times {Green Inv}_{it}$ = interaction term
• $T$ = Year fixed effect
• ${\epsilon }_{it}$ = error term

4. Empirical Analysis and Discussion

4.1. Descriptive Statistics

Table 2. Descriptive statistics.

Variable	Obs	Mean	Std. Dev.	Min	Max
Firm value	2677	1.778	3.133	0.206	62.953
Total GHG	1960	10.099	3.182	0	18.246
Scop 1	1963	9.017	3.582	0	18.106
Scop 2	1972	9.178	2.899	0	16.396
Green Inv	2335	0.03	0.169	0	1
Boardsize	2422	8.533	2.51	2	19
Boarddiv	2424	34.364	12.384	0	80
IndependD	2424	70.732	17.664	0	100
AuditComInd	2421	94.592	11.748	14.286	100
CEO duality	2425	0.049	0.216	0	1
ROE	1905	17.706	93.789	−2083.33	2023.21
Cash	2735	18.793	2.283	7.84	26.732
Lev	2543	0.21	0.176	0	1.283
Size	2754	21.971	1.797	16.861	28.742

presents the descriptive statistics for all variables used in the study. The mean firm value (Tobin Q) is equal to 1.778 with a large standard deviation (3.133), which reveals a significant dispersion in the market valuation of FTSE 350 firms. The overall mean of GHG emissions (10.099) is split into Scope 1 (mean = 9.017) and Scope 2 (mean = 9.178). The standard deviations of 3.182 and 2.899 are quite large, indicating heterogeneity in carbon production among firms. The mean of the green investment (Green Inv) variable is 0.03, meaning that only a relatively small proportion (3%) of the firms report explicit green investment activity, which is indicative of a relative lack of green capital allocation among the study sample. The governance indicators show that FTSE 350 boards comprise 8.53 directors on average, with board diversity averaging 34.36% female representation. The average board independence is 70.73%, and audit committee independence is particularly high (mean = 94.59%), indicating strong governance structures. CEO duality is rare (mean = 0.049), suggesting that most firms separate the roles of CEO and chairperson.

Among the financial controls, the firms show an average ROE of 17.7%, but the extremely large standard deviation (93.79) reflects a wide performance dispersion. Cash holdings average 18.79 (log value), and leverage averages 0.21, indicating moderate debt use. The average firm size (log of total assets) is 21.97, which is typical for large publicly listed UK companies.

All models employ listwise deletion, with observations excluded if any variable in that specific regression is missing. Sample sizes vary across models because different dependent variables have different data availability: GHG emissions data rely on voluntary firm disclosure and have lower coverage (n = 1960 for Total GHG) than financial statement variables such as green investment (n = 2335). Within each model, the same sample is used across all specifications.

Because high correlations between independent variables can inflate standard errors and jeopardize the reliability of coefficients, it is imperative to assess the multicollinearity among the variables. As shown in

Table 3. Matrix of correlations.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)
Firm value	1.000
Total GHG	−0.185	1.000
Scop 1	−0.154	0.967	1.000
Scop 2	−0.189	0.901	0.819	1.000
Boardsize	−0.107	0.329	0.268	0.364	1.000
Boarddiv	0.083	−0.013	−0.003	−0.009	0.093	1.000
IndependD	−0.038	0.072	0.042	0.078	0.155	0.344	1.000
AuditComInd	0.014	−0.030	−0.043	−0.026	0.079	0.120	0.466	1.000
CEO duality	0.016	−0.096	−0.092	−0.107	−0.036	−0.105	−0.134	0.009	1.000
ROE	0.347	−0.023	−0.015	−0.034	−0.019	0.055	0.006	0.007	−0.010	1.000
Cash	−0.156	0.369	0.300	0.383	0.527	0.078	0.272	0.113	−0.106	−0.012	1.000
Lev	−0.050	0.322	0.328	0.279	0.047	0.040	−0.056	−0.027	−0.006	−0.073	−0.043	1.000
Size	−0.288	0.442	0.367	0.471	0.603	0.125	0.302	0.156	−0.109	−0.040	0.076	−0.003	1.000

, none of the correlations surpass the frequently stated cutoff of 0.9, which is commonly used to denote severe multicollinearity, although some values remain relatively high.

4.2. Empirical Results

4.2.1. The Relationship Between Carbon Emissions, Green Investment, and Firm Value

Table 4. The relationship between GHG and firm value and the moderating role of green investment.

Variables	(1)	(2)	(3)	(4)	(5)	(6)
Total GHG	−0.112 ***			−0.128 ***
	[−3.62]			[−3.74]
Scop 1		−0.0702 ***			−0.0819 ***
		[−3.69]			[−3.85]
Scop 2			−0.121 ***			−0.138 ***
			[−2.67]			[−2.84]
Total GHG × Green Inv				0.328 ***
				[4.63]
Scop 1 × Green Inv					0.255 ***
					[4.46]
Scop 2 × Green Inv						0.372 ***
						[4.90]
Green Inv				−3.749 ***	−2.715 ***	−3.832 ***
				[−4.69]	[−4.45]	[−4.93]
Boardsize	0.178 ***	0.173 ***	0.184 ***	0.177 ***	0.171 ***	0.186 ***
	[4.58]	[4.54]	[4.54]	[4.46]	[4.40]	[4.47]
Boarddiv	0.0561 ***	0.0564 ***	0.0565 ***	0.0570 ***	0.0573 ***	0.0571 ***
	[4.09]	[4.09]	[4.09]	[4.08]	[4.07]	[4.06]
IndependD	−0.00324	−0.00362	−0.00302	−0.00296	−0.00317	−0.00335
	[−0.70]	[−0.78]	[−0.65]	[−0.61]	[−0.65]	[−0.69]
AuditComInd	0.0159 ***	0.0166 ***	0.0157 ***	0.0157 ***	0.0162 ***	0.0160 ***
	[2.80]	[2.88]	[2.75]	[2.65]	[2.70]	[2.65]
CEO duality	−0.113	−0.0986	−0.140	−0.118	−0.102	−0.159
	[−0.55]	[−0.49]	[−0.67]	[−0.56]	[−0.49]	[−0.74]
ROE	0.0122 *	0.0122 *	0.0121 *	0.0121 *	0.0121 *	0.0121 *
	[1.85]	[1.84]	[1.83]	[1.85]	[1.84]	[1.84]
Cash	0.259 ***	0.251 ***	0.253 ***	0.264 ***	0.257 ***	0.255 ***
	[5.62]	[5.65]	[5.47]	[5.53]	[5.55]	[5.35]
Lev	−0.00767	−0.171	−0.0868	0.0488	−0.117	−0.0757
	[−0.01]	[−0.30]	[−0.14]	[0.08]	[−0.20]	[−0.12]
Size	−0.867 ***	−0.886 ***	−0.862 ***	−0.885 ***	−0.904 ***	−0.877 ***
	[−7.10]	[−6.93]	[−7.34]	[−7.00]	[−6.84]	[−7.23]
Constant	13.41 ***	13.49 ***	13.38 ***	14.05 ***	14.08 ***	14.01 ***
	[8.56]	[8.42]	[8.66]	[8.22]	[8.12]	[8.32]
Robust St.E	Yes	Yes	Yes	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes	Yes	Yes	Yes
R-squared	0.241	0.239	0.241	0.244	0.242	0.244

*** p < 0.01, ** p < 0.05, * p < 0.1.

presents the results of the regression models examining the effect of GHG emissions on firm value and the moderating role of green investment among FTSE 350 firms. Models (1)–(3) test the direct effect of GHG emissions (measured by total GHG, Scope 1, and Scope 2 emissions, respectively), while Models (4)–(6) incorporate interaction terms between each emission measure and green investment to assess the moderation effects. All models include robust standard errors and year fixed effects. Across all models, GHG emissions are negatively and significantly associated with firm value, confirming that higher emission levels correspond to lower market valuation. In Model (1), total GHG emissions have a coefficient of −0.112 (t = −3.62), which is statistically significant at the 1% level, providing evidence for a negative relationship between total emissions and firm value. A one standard deviation increase in total GHG emissions reduces Tobin’s Q by approximately 17% relative to the sample mean, indicating a material valuation discount. In Model (2), Scope 1 emissions have a coefficient of −0.0702 (t = −3.69), which is also significant at the 1% level, showing a persistent negative relationship between firm value and direct emissions. The same pattern is observed in Model (3), with Scope 2 emissions having a coefficient of −0.121 (t = −2.67), indicating that firm value is negatively related to indirect emissions. These findings are in line with the concept that the market penalizes firms with greater carbon intensity, potentially due to reputational risk, regulatory exposure, and lower sustainability legitimacy. These results complement the environmental performance–firm value literature, indicating that carbon efficiency adds value to the firm (Matthews et al., 2025; Perdichizzi et al., 2024; Baboukardos, 2017).

Models (4)–(6) introduce interaction terms between GHG emissions and green investment. The interaction terms—Total GHG × Green Inv (β = 0.328, t = 4.63), Scope 1 × Green Inv (β = 0.255, t = 4.46), and Scope 2 × Green Inv (β = 0.372, t = 4.90)—are all positive and statistically significant at the 1% level. These results suggest that green investment mitigates the association between GHG and firm value, at least partially countering the negative effect. Specifically, companies that implement legitimate green initiatives can transform environmental liabilities into market value creation, as investors reward actions that are credible in terms of sustainability. The UK context is crucial to the empirical interpretation for three reasons. First, the UK is the first major economy to have legislation in place to achieve net-zero emissions by 2050. Second, Brexit has led to a regulatory divergence from the EU ETS, which has created a natural laboratory in which UK-specific carbon pricing and disclosure rules impact investor behavior differently from that in continental markets. Third, the FTSE 350 has a significant financial services and energy-intensive sector bias, which means that the sample represents sectors where emissions data are most relevant to valuation, thus increasing the external validity of the results for other jurisdictions where similar mandatory disclosure frameworks are in place.

Interestingly, although green investment as a sole parameter exhibits a negative main effect (b = ranges between −2.715 and −3.832, with all significant at the 1%), the trend indicates that green projects are associated with immediate monetary expenses or capital-intensive projects. The positive and strong interaction effects, however, suggest that when green investment is followed by an increase in emissions, it is seen as an effective mitigation or transition strategy, hence enhancing firm valuation. This dichotomy is congruent with the argument of a trade-off between costs and benefits in environmental finance, in which sustainability investments cause short-term losses in profits but improve the long-term legitimacy and confidence of the market. A logical explanation for this could have something to do with the complexity of the process of green investment. As Chen and Ma (2021) argued, the trade-offs between working towards ecological goals and financial gains are challenging, and this is often characterized as a “win-win”. Supporting this view, King and Lenox (2001, p. 7) noted that “To fully demonstrate that it ‘pays to be green’, research must demonstrate that environmental improvements produce financial gain.”

Board size and board diversity have consistently positive and significant impacts on firm value across all models. The independence of the audit committee is also positively associated with firm value, which underlines the significance of clear monitoring systems. In contrast, board independence and CEO duality have no meaningful correlation with firm value, thus, independence may not be a sufficient factor to ensure high performance, and role duality is not common in this sample. On the other hand, profitability and liquidity are two value-improving factors, as ROE and cash holdings, respectively, have a positive and significant influence on firm value. The size of firms is always negative and significant. Leverage is statistically insignificant across all models.

Our results directly relate to three contributions. First, we clarify the debate on GHG emissions and firm value, demonstrating that they do not form a uniform relationship, but rather one that depends on the credibility of disclosure and its governance. Second, we qualify the green investment narrative by showing that the emissions penalty is only mitigated when external assurance and board-level oversight are present, but not otherwise, and that green spending is even penalized in the absence of both. Third, we make sustainability governance a boundary condition rather than a peripheral control, and we examine the gap between environmental strategy and market value in the context of CSR committees and external verification.

4.2.2. Externally Verified GHG

Table 5. GHG-firm value link among firms with externally verified GHG vs. not verified GHG.

Variables	Firms with Not-Verified GHG			Firms with Verified GHG
	(1)	(2)	(3)	(1)	(2)	(3)
Total GHG	−0.0438			−0.147 **
	[−0.84]			[−2.45]
Scop 1		−0.0155			−0.106 ***
		[−0.35]			[−2.93]
Scop 2			−0.107 *			−0.127 *
			[−1.69]			[−1.82]
Total GHG × Green Inv	0.419			0.244 ***
	[1.33]			[2.81]
Scop 1 × Green Inv		0.377			0.189 ***
		[1.48]			[2.92]
Scop 2 × Green Inv			0.426			0.259 ***
			[1.26]			[2.79]
Green Inv	−5.274	−4.567 *	−4.983	−2.663 ***	−1.859 ***	−2.568 ***
	[−1.51]	[−1.70]	[−1.43]	[−2.90]	[−2.95]	[−2.93]
Boardsize	0.263 ***	0.259 ***	0.278 ***	0.209 ***	0.203 ***	0.216 ***
	[2.70]	[2.73]	[2.74]	[3.86]	[3.94]	[3.71]
Boarddiv	0.0351 **	0.0355 **	0.0339 **	0.0596 ***	0.0601 ***	0.0599 ***
	[2.47]	[2.50]	[2.45]	[2.84]	[2.82]	[2.82]
IndependD	0.00417	0.00511	0.00306	0.00333	0.00302	0.00248
	[0.34]	[0.40]	[0.26]	[0.41]	[0.38]	[0.31]
AuditComInd	0.0148	0.0146	0.0141	−0.000583	−0.000134	0.000758
	[1.36]	[1.35]	[1.30]	[−0.06]	[−0.01]	[0.08]
CEO duality	0.438	0.478	0.267	−0.176	−0.187	−0.270
	[0.59]	[0.63]	[0.38]	[−0.73]	[−0.78]	[−1.10]
ROE	0.0377 ***	0.0377 ***	0.0377 ***	0.00541	0.00543	0.00518
	[3.85]	[3.86]	[3.86]	[1.05]	[1.05]	[1.00]
Cash	0.198 **	0.195**	0.195**	0.192 **	0.186 **	0.168 **
	[2.47]	[2.40]	[2.42]	[2.09]	[2.11]	[1.97]
Lev	0.817	0.730	0.997	0.0580	−0.0997	−0.265
	[0.64]	[0.57]	[0.79]	[0.10]	[−0.15]	[−0.43]
Size	−1.240 ***	−1.255 ***	−1.195 ***	−0.675 ***	−0.692 ***	−0.672 ***
	[−6.11]	[−6.02]	[−6.31]	[−2.96]	[−2.91]	[−3.06]
Constant	20.36 ***	20.42 ***	20.00 ***	11.91 ***	11.80 ***	11.97 ***
	[5.64]	[5.61]	[5.73]	[3.59]	[3.60]	[3.56]
Robust St.E	Yes	Yes	Yes	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes	Yes	Yes	Yes
R-squared	0.567	0.566	0.567	0.139	0.136	0.136

*** p < 0.01, ** p < 0.05, * p < 0.1.

shows two subsamples, including firms with non-verified GHG emissions and firms with externally verified GHG emissions. Within the subsample of non-verified companies, the coefficients of total GHG, Scope 1, and Scope 2 are not statistically significant in models (1)–(3). This means that for companies without external verification of emission levels, GHG emissions do not seem to have any traceable effect on firm value. The insignificance can be an indication of the distrust that investors place in the accuracy of self-reported emissions or a reduced market focus on unconfirmed disclosures. The interaction terms are also not statistically significant (Total GHG × Green Inv = 0.419, Scope 1 × Green Inv = 0.377, Scope 2 × Green Inv = 0.426), implying that green investment in these firms does not play a significant moderating role in the relationship between emissions and value. The coefficients are positive; however, they do not attain traditional levels of significance, meaning that markets do not compensate green investment when the environmental information is not audited or credible to outside sources.

In contrast, the subsample of externally verified firms shows a different pattern. The coefficients for total GHG, Scope 1, and Scope 2 emissions are all negative and statistically significant (e.g., Total GHG β = −0.147, t = −2.45; Scope 1 β = −0.106, t = −2.93; Scope 2 β = −0.127, t = −1.82). This implies that investors react more negatively to increased emissions when these are reported by trusted and reliable parties. External assurance makes GHG data more reliable and enables markets to better price environmental risks. Notably, the interaction terms are positive and significant in all three models (Total GHG × Green Inv = 0.244, Scope 1 × Green Inv = 0.189, Scope 2 × Green Inv = 0.259; all significant at the 1% level). This affirms that green investment has significant negative valuation impacts on verified firms. In other words, when firms both verify their emissions data and commit to green investment, the market perceives these actions as credible signals of a sustainable transition, enhancing firm value despite higher carbon intensity.

4.2.3. CSR/Sustainability Committee

Table 6. GHG-firm value link among firms with a sustainability committee vs. no sustainability committee.

Variables	Firms with No Sustainability Committee			Firms with a Sustainability Committee
	(1)	(2)	(3)	(1)	(2)	(3)
Total GHG	−0.624 ***			−0.0828 ***
	[−2.75]			[−3.06]
Scop 1		−0.370 ***			−0.0548 ***
		[−2.76]			[−3.60]
Scop 2			−0.762 ***			−0.0761 **
			[−2.63]			[−1.98]
Total GHG × Green Inv	−0.626			0.238 ***
	[−1.50]			[4.04]
Scop 1 × Green Inv		−0.457 *			0.189 ***
		[−1.68]			[4.06]
Scop 2 × Green Inv			−1.177 *			0.272 ***
			[−1.77]			[4.20]
Green Inv	9.375 *	6.161 **	15.25 **	−2.844 ***	−2.116 ***	−2.927 ***
	[1.91]	[2.00]	[2.11]	[−4.11]	[−4.05]	[−4.27]
Boardsize	0.523 ***	0.505 ***	0.523 ***	0.139 ***	0.135 ***	0.144 ***
	[2.83]	[2.72]	[2.85]	[4.05]	[4.09]	[3.86]
Boarddiv	0.103 **	0.101 **	0.105 **	0.0433 ***	0.0436 ***	0.0433 ***
	[2.09]	[2.02]	[2.13]	[3.62]	[3.61]	[3.58]
IndependD	−0.0611 **	−0.0492 *	−0.0613 **	0.000213	−4.69 × 10−6	−0.000152
	[−2.02]	[−1.86]	[−2.00]	[0.04]	[−0.00]	[−0.03]
AuditComInd	0.0562 **	0.0546 **	0.0542 **	0.0135 ***	0.0138 ***	0.0141 ***
	[2.02]	[2.02]	[1.98]	[3.05]	[3.01]	[3.15]
CEO duality	−2.582 *	−2.240 *	−2.528 *	0.0873	0.0911	0.0623
	[−1.83]	[−1.72]	[−1.81]	[0.51]	[0.54]	[0.35]
ROE	0.0166	0.0167	0.0165	0.00725	0.00727	0.00725
	[1.62]	[1.57]	[1.64]	[1.60]	[1.60]	[1.58]
Cash	0.225	0.253	0.281	0.197 ***	0.192 ***	0.188 ***
	[1.02]	[1.23]	[1.32]	[4.01]	[4.08]	[3.88]
Lev	3.903 **	3.529 **	4.141 **	−0.545	−0.654	−0.703
	[2.03]	[2.01]	[2.03]	[−1.34]	[−1.42]	[−1.64]
Size	−2.127 ***	−2.216 ***	−2.080 ***	−0.669 ***	−0.680 ***	−0.669 ***
	[−5.63]	[−5.46]	[−5.81]	[−5.21]	[−5.08]	[−5.44]
Constant	42.79 ***	40.94 ***	41.68 ***	10.43 ***	10.43 ***	10.42 ***
	[4.99]	[5.06]	[5.03]	[7.17]	[7.12]	[7.28]
Robust St.E	Yes	Yes	Yes	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes	Yes	Yes	Yes
R-squared	0.485	0.471	0.492	0.153	0.152	0.152

*** p < 0.01, ** p < 0.05, * p < 0.1.

presents the regression outcomes that examine how the presence of a CSR/sustainability committee affects the results. For firms that lack a dedicated CSR or sustainability committee, GHG emissions are significantly and negatively associated with firm value across all models. Specifically, the coefficients for total GHG (β = −0.624, t = −2.75), Scope 1 (β = −0.370, t = −2.76), and Scope 2 (β = −0.762, t = −2.63) are all statistically significant at the 1% level. This indicates that higher emissions lead to lower market valuation when firms lack formal internal oversight structures for sustainability issues. However, the interaction terms between green investment and GHG emissions are negative and mostly insignificant, except for Scope 1 and Scope 2, where they are weakly significant and negative (Scope 1 × Green Inv β = −0.457, p < 0.10; Scope 2 × Green Inv β = −1.177, p < 0.10). This implies that without a CSR/sustainability committee, green investment does not help reduce the negative valuation impact of emissions and even amplifies it. The absence of a governance mechanism may result in green investments being perceived as an expense or a form of symbolism, rather than a value-creating asset. Such expenditures will be seen by investors as inefficient or as window dressing, unless they are supported by an effective governance mechanism.

For firms that have a CSR or sustainability committee, the results reveal a different dynamic. The coefficients on total GHG, Scope 1, and Scope 2 emissions remain negative and significant, but their magnitudes are notably smaller (e.g., Total GHG β = −0.0828, t = −3.06; Scope 1 β = −0.0548, t = −3.60; Scope 2 β = −0.0761, t = −1.98). This shows that the adverse value effect of emissions is significantly lessened in the presence of a sustainability committee, which reflects improved controls, accountability, and transparency. More importantly, the terms of interaction between green investment and emissions are positive and significant in all cases (Total GHG × Green Inv b = 0.238, Scope 1 × Green Inv b = 0.189, Scope 2 × Green Inv b = 0.272; all at p < 0.01). This result proves that in the presence of good sustainability governance, green investment unquestionably mitigates the adverse association between emissions and firm value. This implies that sustainability committees are likely to ensure that green investments are strategic, well-executed, and believably reported to stakeholders, thereby improving investor confidence and firm valuation.

4.3. Robustness Test

4.3.1. Using Shareholder Value as an Alternative Proxy for Firm Value

Table 7. Robustness test using shareholder value as a proxy of firm value.

Variables	(1)	(2)	(3)	(4)	(5)
	Full Sample	Not-Verified GHG	Verified GHG	No Sustainability Committee	Sustainability Committee
Total GHG	−0.905 **	−0.285	−0.319 ***	−4.774 *	−0.235 ***
	[−2.42]	[−1.04]	[−2.81]	[−1.96]	[−4.21]
Total GHG × Green Inv	1.528 **	0.704	0.530 ***	−0.0882	0.459 ***
	[2.43]	[1.02]	[3.57]	[−0.03]	[3.41]
Green Inv	−15.99 **	−9.171	−5.750 ***	15.38	−4.973 ***
	[−2.42]	[−1.20]	[−3.67]	[0.38]	[−2.88]
Boardsize	0.0625	0.748 **	0.274 **	0.805	0.127 *
	[0.23]	[2.55]	[2.27]	[0.46]	[1.68]
Boarddiv	0.237 **	0.0779 **	0.0895 ***	0.897 *	0.0912 ***
	[2.02]	[1.97]	[2.65]	[1.87]	[4.17]
IndependD	−0.0449	0.00235	0.00175	−0.527 *	−0.0151
	[−1.60]	[0.06]	[0.09]	[−1.80]	[−1.33]
AuditComInd	0.0447	0.0366	0.0149	0.329	0.0448 ***
	[0.79]	[0.84]	[0.42]	[1.14]	[2.84]
CEO duality	2.671	0.601	0.442	−0.806	0.446
	[0.58]	[0.27]	[0.72]	[−0.03]	[1.17]
ROE	−0.0183	0.158 ***	0.00401	−0.0457	0.0128
	[−0.25]	[3.36]	[0.43]	[−0.40]	[1.18]
Cash	0.389 **	0.0352	0.00342	−0.986	0.235 **
	[2.46]	[0.11]	[0.02]	[−0.43]	[2.57]
Lev	13.77 *	12.32 **	0.280	49.86 **	0.382
	[1.86]	[2.26]	[0.13]	[2.30]	[0.29]
Size	−1.719 ***	−2.235 ***	−0.614 *	−7.460 ***	−0.844 ***
	[−3.53]	[−4.16]	[−1.72]	[−2.61]	[−4.05]
Constant	40.44 ***	40.10 ***	14.58 **	217.4 ***	13.22 ***
	[3.34]	[2.87]	[2.37]	[2.66]	[4.70]
Robust St.E	Yes	Yes	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes	Yes	Yes
R-squared	0.062	0.596	0.080	0.195	0.119

*** p < 0.01, ** p < 0.05, * p < 0.1.

reports results using shareholder value as an alternative proxy for firm value. For the full sample (Column 1), total GHG emissions remain negatively and significantly related to shareholder value (β = −0.905, t = −2.42), reinforcing earlier findings. The interaction term between total GHG and green investment is positive and significant (β = 1.528, p < 0.05), indicating the robustness of our analysis. For firms without externally verified GHG data, the results show that neither emissions (β = −0.285, n.s.) nor their interaction with green investment (β = 0.704, n.s.) significantly influences shareholder value—consistent with the earlier results in Table 5. Among firms with verified GHG data, the findings are both statistically and economically significant. Total GHG emissions are negatively related to shareholder value (β = −0.319, t = −2.81), while the interaction between emissions and green investment is positive and highly significant (β = 0.530, t = 3.57).

For firms without a CSR/sustainability committee, the results show that GHG emissions have a large negative coefficient (β = −4.774, t = −1.96), although only marginally significant. Neither the interaction term (β = −0.088, n.s.) nor green investment itself (β = 15.38, n.s.) has a significant impact on shareholder value. This finding mirrors Table 6. In contrast, firms with an established CSR or sustainability committee show a strong and significant pattern consistent with the main results. Total GHG emissions have a negative impact on shareholder value (β = −0.235, t = −4.21), but the interaction with green investment is positive and highly significant (β = 0.459, t = 3.41). Across all models, the control variables largely have the same effect.

4.3.2. Using Price-to-Book Value as an Alternative Proxy for Firm Value

Table 8. Robustness test using price-to-book value as a proxy of firm value.

Variables	(1)	(2)	(3)	(4)	(5)
	Full Sample	Not-Verified GHG	Verified GHG	No Sustainability Committee	Sustainability Committee
Total GHG	−0.930 **	−0.267	−0.293 ***	−4.978 **	−0.171 ***
	[−2.19]	[−0.78]	[−2.91]	[−2.02]	[−4.16]
Total GHG × Green Inv	1.683 **	0.566	0.437 **	−0.712	0.332 ***
	[2.14]	[0.89]	[2.10]	[−0.18]	[2.95]
Green Inv	−18.22 **	−7.640	−5.073 **	18.74	−4.062 ***
	[−2.20]	[−1.08]	[−2.11]	[0.44]	[−2.85]
Boardsize	0.0780	0.497 *	0.417 ***	0.507	0.207 ***
	[0.37]	[1.84]	[3.61]	[0.32]	[3.35]
Boarddiv	0.267 *	0.0609	0.108 **	0.907 **	0.0776 ***
	[1.92]	[1.26]	[2.19]	[2.07]	[3.52]
IndependD	−0.0519 *	−0.0312	−0.0442	−0.542 *	−0.00929
	[−1.92]	[−0.95]	[−0.85]	[−1.86]	[−0.83]
AuditComInd	0.0561	0.0680	0.0249	0.499 *	0.0122
	[0.97]	[1.61]	[0.53]	[1.70]	[0.97]
CEO duality	2.467	−1.184	−0.919	0.439	0.336
	[0.61]	[−0.74]	[−0.81]	[0.02]	[0.89]
ROE	−0.0352	0.174 ***	0.0354	−0.0588	0.0408
	[−0.32]	[3.17]	[0.69]	[−0.53]	[1.50]
Cash	0.586 ***	0.225	0.283	0.335	0.322 ***
	[3.49]	[0.69]	[1.44]	[0.17]	[3.59]
Lev	19.07 ***	11.85 *	10.50 *	72.68 ***	4.024 ***
	[2.87]	[1.87]	[1.94]	[2.92]	[5.28]
Size	−2.103 ***	−1.952 ***	−0.959 **	−9.776 ***	−0.940 ***
	[−3.55]	[−3.27]	[−2.49]	[−3.04]	[−4.89]
Constant	43.86 ***	31.70 *	12.36 ***	227.4 ***	14.68 ***
	[3.00]	[1.89]	[2.88]	[2.64]	[6.57]
Robust St.E	Yes	Yes	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes	Yes	Yes
R-squared	0.086	0.599	0.111	0.249	0.227

*** p < 0.01, ** p < 0.05, * p < 0.1.

presents regressions using the price-to-book value (P/BV) ratio as an alternative market-based proxy for firm value. A higher P/BV generally indicates stronger investor confidence and growth potential. The results show that total GHG emissions are negatively and significantly associated with the price-to-book value (β = −0.930, t = −2.19), confirming that higher GHG emissions reduce investors’ valuation of the firm. The interaction between total GHG and green investment is positive and significant (β = 1.683, t = 2.14). Among firms without verified GHG data, neither GHG emissions nor the moderating effect of green investment shows significant results. The coefficients for total GHG (β = −0.267) and the interaction term (β = 0.566) are statistically insignificant. For firms with verified GHG emissions, the results are strongly consistent with the main hypothesis. For firms without a CSR or sustainability committee, the total GHG variable has a strong negative effect (β = −4.978, t = −2.02), while both the green investment and interaction terms are statistically insignificant. The pattern of results is consistent with the earlier findings.

4.3.3. Robustness Checks Based on Lagged Specifications

To address potential endogeneity issues, especially reverse causality, the regression models are re-estimated with one-period lagged values of the key independent variables (

Table 9. Robustness Checks Based on Lagged Specifications.

Variables	(1)	(2)	(3)	(4)	(5)	(6)
L. Total GHG	−0.109 ***			−0.127 ***
	[−3.13]			[−3.24]
L. Scop 1		−0.0673 ***			−0.0792 ***
		[−3.16]			[−3.31]
L. Scop 2			−0.123 **			−0.143 ***
			[−2.44]			[−2.63]
L. Total GHG × Green Inv				0.290 ***
				[4.25]
L. Scop 1 × Green Inv					0.223 ***
					[4.09]
L. Scop 2 × Green Inv						0.349 ***
						[4.69]
L. Green Inv				−3.261 ***	−2.325 ***	−3.524 ***
				[−4.42]	[−4.18]	[−4.85]
L. Boardsize	0.175 ***	0.170 ***	0.180 ***	0.178 ***	0.172 ***	0.183 ***
	[4.12]	[4.08]	[4.07]	[4.13]	[4.08]	[4.06]
L. Boarddiv	0.0594 ***	0.0596 ***	0.0591 ***	0.0596 ***	0.0598 ***	0.0592 ***
	[3.87]	[3.87]	[3.82]	[3.86]	[3.86]	[3.80]
L. IndependD	−0.00218	−0.00272	−0.00187	−0.00217	−0.00262	−0.00226
	[−0.48]	[−0.60]	[−0.41]	[−0.47]	[−0.56]	[−0.49]
L. AuditComInd	0.0180 ***	0.0188 ***	0.0178 ***	0.0187 ***	0.0194 ***	0.0186 ***
	[3.08]	[3.13]	[3.06]	[3.09]	[3.13]	[3.09]
L. CEO duality	−0.127	−0.121	−0.106	−0.114	−0.111	−0.103
	[−0.64]	[−0.61]	[−0.52]	[−0.57]	[−0.56]	[−0.50]
L. ROE	0.0104	0.0104	0.0103	0.0103	0.0103	0.0103
	[1.63]	[1.63]	[1.62]	[1.63]	[1.63]	[1.62]
L. Cash	0.239 ***	0.231 ***	0.235 ***	0.242 ***	0.233 ***	0.234 ***
	[4.38]	[4.36]	[4.31]	[4.37]	[4.36]	[4.28]
L. Lev	0.0394	−0.119	−0.0215	0.104	−0.0664	0.0133
	[0.06]	[−0.19]	[−0.03]	[0.17]	[−0.11]	[0.02]
L. Size	−0.832 ***	−0.851 ***	−0.827 ***	−0.844 ***	−0.863 ***	−0.836 ***
	[−6.17]	[−6.01]	[−6.41]	[−6.14]	[−5.99]	[−6.37]
Constant	12.58 ***	12.65 ***	12.56 ***	12.93 ***	12.95 ***	12.93 ***
	[7.51]	[7.39]	[7.63]	[7.37]	[7.28]	[7.49]
Robust St.E	Yes	Yes	Yes	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes	Yes	Yes	Yes
R-squared	0.225	0.223	0.226	0.228	0.226	0.229

*** p < 0.01, ** p < 0.05, * p < 0.1.

). This methodology ensures that GHG emissions and green investment temporally lead firm value. The findings are similar to the baseline results: GHG emissions still have a negative and statistically significant relationship with firm value, and the interaction between GHG emissions and green investment is positive and significant. These results indicate that the primary findings are strong and not influenced by simultaneity bias.

4.3.4. Robustness Checks Using Instrumental Variable (2SLS) Estimation

An instrumental variable method (2SLS) is used to further deal with endogeneity issues (

Table 10. Robustness Checks Using Instrumental Variable (2SLS) Estimation.

Variables	(1)	(2)	(3)	(4)	(5)	(6)
Total GHG	−0.0818 ***			−0.0974 ***
	[−3.20]			[−3.37]
Scop 1		−0.0492 ***			−0.0602 ***
		[−2.92]			[−3.18]
Scop 2			−0.0965 **			−0.114 ***
			[−2.55]			[−2.84]
Total GHG × Green Inv				0.278 ***
				[4.22]
Scop 1 × Green Inv					0.215 ***
					[4.00]
Scop 2 × Green Inv						0.334 ***
						[4.95]
Green Inv				−3.236 ***	−2.337 ***	−3.490 ***
				[−4.38]	[−4.15]	[−4.96]
Boardsize	0.170 ***	0.165 ***	0.175 ***	0.172 ***	0.166 ***	0.179 ***
	[4.30]	[4.31]	[4.19]	[4.32]	[4.31]	[4.23]
Boarddiv	0.0537 ***	0.0539 ***	0.0530 ***	0.0540 ***	0.0542 ***	0.0529 ***
	[3.83]	[3.83]	[3.74]	[3.82]	[3.83]	[3.72]
IndependD	−0.00149	−0.00176	−0.00145	−0.00146	−0.00163	−0.00200
	[−0.31]	[−0.37]	[−0.30]	[−0.30]	[−0.34]	[−0.42]
AuditComInd	0.0121 *	0.0127 *	0.0120 *	0.0125 *	0.0130 **	0.0129 *
	[1.87]	[1.95]	[1.82]	[1.91]	[1.97]	[1.92]
CEO duality	−0.00297	0.0115	−0.0214	−0.0132	0.00214	−0.0456
	[−0.01]	[0.05]	[−0.09]	[−0.06]	[0.01]	[−0.20]
ROE	0.0159 *	0.0159 *	0.0158 *	0.0158 *	0.0158 *	0.0158 *
	[1.82]	[1.82]	[1.81]	[1.82]	[1.82]	[1.81]
Cash	0.254 ***	0.247 ***	0.249 ***	0.252 ***	0.245 ***	0.244 ***
	[5.12]	[5.14]	[4.96]	[5.07]	[5.10]	[4.89]
Lev	−0.451	−0.596	−0.476	−0.379	−0.535	−0.443
	[−0.86]	[−1.08]	[−0.77]	[−0.74]	[−0.98]	[−0.72]
Size	−0.829 ***	−0.843 ***	−0.823 ***	−0.836 ***	−0.850 ***	−0.828 ***
	[−6.55]	[−6.38]	[−6.83]	[−6.53]	[−6.37]	[−6.80]
Constant	12.25 ***	12.32 ***	12.26 ***	12.55 ***	12.56 ***	12.57 ***
	[8.28]	[8.14]	[8.40]	[8.17]	[8.07]	[8.30]
Robust St.E	Yes	Yes	Yes	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes	Yes	Yes	Yes
All variables in the main model	Yes	Yes	Yes	Yes	Yes	Yes
Kleibergen-Paap rk LM statistic	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
Hansen J (p-value)	0.2864	0.2253	0.2547	0.3450	0.2628	0.3151
Wu–Hausman (p-value)	0.3685	0.4138	0.1579	0.3917	0.4213	0.1484
R-squared	0.256	0.254	0.256	0.258	0.256	0.258

*** p < 0.01, ** p < 0.05, * p < 0.1.

). The potentially endogenous variables are instrumented in the first stage using the lagged main independent variables (e.g., Total GHG emissions, Scope 1, Scope 2) to control for serial correlation, the industry-year average of the main independent variables (e.g., Total GHG emissions, Scope 1, Scope 2), and the CSR/sustainability committee. The findings are in line with the baseline estimates in direction and significance. The validity of the instruments is supported by diagnostic tests: the Hansen J test shows that the instruments are exogenous, and the Kleibergen–Paap statistic shows that the instruments are relevant. Also, the Wu–Hausman test indicates that endogeneity does not exist. These results indicate that the findings are resistant to endogeneity issues.

5. Conclusions

As the emphasis on current concerns such as climate change and environmental protection has increased, green investment and sustainability governance mechanisms have received global attention. This study provides critical perspectives on how green investment and sustainability governance mechanisms act as moderators of the relationship between GHG emissions and firm value, using a sample of UK FTSE 350 firms over the period 2017–2024. The analysis yields five main outcomes. First, GHG emissions are significantly and negatively related to firm value measured by Tobin’s Q. In other words, the value of high-emitting firms decreases as emissions increase. This means that GHG emission reductions increase firm value and build a good reputation for environmental stewardship. Second, green investment plays a moderating role and mitigates the negative association of GHG emissions with firm value. This implies that firms that invest in green projects may experience improved market perception. Third, the results point to green investment on its own having a negative effect on firm value. Fourth, while emissions affect valuation negatively, green investment has a significant moderating effect on valuation among verified firms, whereas neither carbon emissions nor green investment data impact firm value for non-verified firms. Fifth, among firms that do not have a CSR/sustainability committee, GHG emissions diminish firm value, and green investment does not have a moderating effect. Among firms with a CSR/sustainability committee, GHG emissions diminish firm value, but green investment moderates this relationship and improves firm valuation.

This study contributes to the literature by developing an integrative framework for understanding the strategic importance of GHG emissions and green investment by combining the natural-resource-based view with legitimacy theory. The findings refine both theories by demonstrating how GHG emissions and green investment not only increase firm value but also increase legitimacy in the eyes of both internal and external stakeholders. The study adds to the ongoing debate regarding GHG emissions by investigating the role of green investment as a moderator and showing how both external and internal sustainability governance mechanisms increase firm value. This is particularly relevant in a global context where sustainability governance tools are increasingly viewed as a pathway to achieving both environmental stewardship and economic returns. This study also addresses an important gap in the literature by examining GHG emissions and green investment in developed countries. It deepens the understanding of the relationship between environmental sustainability, sustainable development, and firm value, adding to the existing literature on the topic and laying a foundation for future research, which may support findings concerning GHG emissions and green investment in a developing nation that faces a series of economic and environmental constraints.

This research has important implications. Our results extend stakeholder theory by proving that emissions affect firm value negatively, signaling theory by showing that green investment can only be an effective signal if supported by boards, and legitimacy theory by finding that disclosure is not enough without being embedded into institutions. These findings shift the focus of the literature from the question of whether emissions matter to how governance architecture affects their market perception. For policymakers, the research shows that motivating businesses to adopt practices that reduce GHG emissions can lead to sustainable development and financial gains. Laws regulating business conduct (such as GHG emission reductions, support for green investments, and the restructuring of corporate governance) are essential for improving environmental performance in the financial market. For company management, the research illustrates the strong reputation that can be built through integrating sustainable development and environmental protection into business operations. Specifically, companies can improve their financial health and enhance their position in global sustainability markets by implementing effective green initiatives.

Furthermore, regulators should be aware that environmental disclosure mandates have the maximum market impact when combined with governance requirements, such as the requirement to engage external assurance and have CSR oversight on the board, which can turn compliance reporting into credible signals that change capital allocation. Corporate managers should be aware that green investment and assurance mechanisms are not just about ticking boxes, but are also tools that can help to reduce valuation discounts for high emissions and help companies position carbon intensity as a part of their transition story, not a passive liability. Investors, on the other hand, can use these governance signals to further develop their ESG screening: a company that reports high emissions but has established green investment and internal controls could be a transition company, not a stranded asset, and therefore investment models should take into account the quality of governance as well as the absolute level of emissions.

This study has certain limitations. First, the sample only covers large companies in the United Kingdom (the FTSE 350), which might restrict the findings to companies of this size and nature. Therefore, future studies could analyze either a cross-country sample or focus on a single country, particularly a developing nation. Second, this study examines GHG emissions as an independent variable. While this provides useful information, GHG emissions may not capture the entire range of sustainability factors that can influence firm value. Future studies could consider other environmental factors that result from climate change. Third, there is a shortage of research on GHG emissions, green investment, and firm value. The need for more research on how to incentivize firms to adopt green initiatives that ensure regulatory compliance, fuel GHG reductions, and encourage green investments is imperative.

Furthermore, future studies may build upon this study by using other panel data methods, including fixed-effects or random-effects models, to further adjust for unobserved firm-specific heterogeneity. Although the present research uses pooled OLS because of the lack of within-firm variation in the main variables, future research with longer time horizons or more detailed data could implement these models more effectively. This would give further information about the strength of relationships and would assist in dealing with possible endogeneity issues. Finally, green investment is measured by a binary variable that indicates the existence of such activities but not their magnitude or intensity. Although this method is consistent when data are available in Refinitiv Eikon, it might not capture the variation in the scale of environmental investments made by firms. Thus, the findings should be understood as reflecting the impact of participation in green investment as opposed to the level of investment. More detailed continuous measures, where possible, could be used in future research to give more insight.

The study period (2017–2024) covers some key macroeconomic and geopolitical events, such as Brexit (2019–2020), the COVID-19 pandemic (2020–2021) and the European energy crisis (2022–2023). These events likely had an impact on both corporate GHG emissions and firm valuation via aggregate demand shocks, supply chain disruptions, and energy price volatility. The specifications account for common time-varying shocks by incorporating year fixed effects, but we do not explicitly model the interaction between these shocks and the firms. Consequently, the estimates should be interpreted as reflecting average relationships across the full sample period, net of aggregate year effects, rather than as stable structural parameters invariant to macroeconomic regime changes. Future studies could explore the differences in the emissions–firm value relationship for different macroeconomic periods.