Corporate governance and financial performance: Reframing their relationship in the context of climate change

RESEARCH ARTICLE Corporate governance and financial performance: Reframing their relationship in the context of climate change Beatriz Aibar-Guzmán 1 | Nicola Raimo 2 | Filippo Vitolla 2 | Isabel-María García-Sánchez 3 1 Departamento de Economía Financiera y Contabilidad, Facultad de Ciencias Econ omicas y Empresariales, Universidad de Santiago de Compostela, Santiago Compostela, Spain 2 Department of Management, Finance and Technology, LUM University, Bari, Italy 3 IME - Instituto Multidisciplinar de Empresa, Universidad de Salamanca, Campus Miguel de Unamuno, Salamanca, Spain Correspondence Beatriz Aibar-Guzmán, Departamento de Economía Financiera y Contabilidad, Facultad de Ciencias Econ omicas y Empresariales, Universidad de Santiago de Compostela, Av. Burgo de las Naciones s/n. 15782, Santiago de Compostela, Spain. Email: [email protected] Funding information Consellería de Cultura, Educaci on e Ordenaci on Universitaria, Xunta de Galicia, Grant/Award Number: 2020 GPC GI2016; Junta de Castilla y Le on y Fondo Europeo de Desarrollo Regional, Grant/Award Number: CLU-2019-03 Unidad de Excelencia GECOS; Ministerio de Ciencia, Innovaci on y Universidades, Grant/Award Number: RTI2018-093423-B-I00 Abstract In addressing the challenges of climate change (CC), companies face the difficult task of reconciling long-term environmental goals and short-term financial interests. In this paper, we argue that that effective climate governance enables companies to balance both objectives, supporting a business case for CC action. For a sample of 832 multinationals for the period 2011–2020, the findings show that effective climate governance leads to higher corporate financial performance (FP) and this relationship is strengthen by better climate performance. Furthermore, effective climate governance is driven by the ownership of long-term institutional investors, whose positive influence is reinforced by homogeneous distribution of their ownership. We provide a broad analytical framework that considers the determinants and effects of climate governance, from which theoretical and practical implications can be derived. KEYWORDS business case, climate change, climate governance, corporate governance, financial performance, institutional ownership 1|INTRODUCTION Because of its destructive effects on the planet and human beings (IPCC, 2007), climate change (CC) is one of today's major concerns (Busch et al., 2022; Cosma et al., 2022). It poses significant risks for businesses that may affect their long-term survival (Charumathi & Rahman, 2019; Kavadis & Thomsen, 2023), facing increasing pressures to adopt actions to mitigate their adverse impacts on the environment (Daradkeh et al., 2023; Maris & Flouros, 2021). Especially, investors have particular interest in the effects of CC on their portfolio companies (Calvet et al., 2022; Krueger et al., 2020), urging them to address climate-related risks and opportunities (Damert & Baumgartner, 2018). Although combating CC has often wrongly seen as a long-term issue that collides with the traditional business emphasis on shortterm profit-making (Benjamin & Andreadakis, 2019), the reality is that it can have positive effects on firms' profitability and value in the short term (Aggarwal & Dow, 2012; Gull et al., 2022; Luo & Tang, 2021). Given the increasing importance of climate-related risks for businesses, Busch and Lewandowski (2018, p. 755) argue for a Received: 18 July 2023 Revised: 25 September 2023 Accepted: 9 October 2023 DOI: 10.1002/csr.2649 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2023 The Authors. Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd. Corp Soc Responsib Environ Manag. 2023;1–17. wileyonlinelibrary.com/journal/csr 1 “business case for CC strategies,”resulting from a “win-win”scenario aligning financial and environmental performance (Aibar-Guzmán et al., 2023). Several authors (e.g., Gull et al., 2022; Huang, 2021; Kim et al., 2019) have analyzed how corporate financial performance (FP) and environmental performance (EP) relate to each other, examining the external and internal factors that may impinge on this relationship (Nguyen et al., 2021). Among the latter, the role of corporate governance has deserved researchers' attention (Aguilera et al., 2021; Okafor et al., 2021). In this regard, under the premise that CC issues cannot be dealt with as something secondary (Tanthanongsakkun et al., 2023), the notion of climate governance has been gained ground in the last years because of the need to inculcate corporate governance with a long-term focus to address the challenges of CC and align the interests of shareholders and stakeholders (Benjamin & Andreadakis, 2019; Cosma et al., 2022). Overall, it is concerned to the incorporation of climate issues into governance processes and structures to improve the company's capability to cope with CC risks and opportunities (Goud, 2022;Haque et al., 2016; Kavadis & Thomsen, 2023). Thus, climate governance mirrors the firm's commitment to sustainability (Bui et al., 2020) and allows addressing the “tragedy of the horizons”(Benjamin, 2018, p. 5), balancing the long-term implications of CC to business and the pursuit of short-term benefits (Ludwig & Sassen, 2022;Luo&Tang,2021). Although the link between corporate governance and firm performance (Bhagat & Bolton, 2019; Kyere & Ausloos, 2021) and between corporate governance and corporate sustainability (Enciso-Alfaro & García-Sánchez, 2023; Guerrero-Villegas et al., 2018; Ludwig & Sassen, 2022) has been the subject of numerous studies, empirical studies on the drivers of climate governance and its effect on FP are scant, and there is a need to improve understanding of how best to manage for environmental sustainability (Aguilera et al., 2021; Velte et al., 2020). With this in mind, and to fill this relevant gap in the literature, this research aims to delve deeper into the effect that climate governance has on FP by exploring the circumstances surrounding this relationship. Specifically, the objectives of this study are to examine whether internal corporate governance structures aimed at promoting corporate action on CC (i.e., climate governance) are conductive to better FP, and whether the adoption of these internal corporate governance structures is fostered by institutional ownership, a key external corporate governance element. Similarly, we aim to determine whether the relationship between climate governance and FP is affected by the company's climate performance. In particular, we seek answers to the following questions: (1) is climate governance associated with higher FP?; (2) does institutional ownership affect climate governance?; and (3) is the effect of climate governance on FP moderated by climate performance? To respond the above questions, a balanced panel of 8320 observations for 832 multinationals is analyzed. The data covers the period 2011–2020. The results indicate that effective climate governance leads to higher FP and this relationship is strengthen by better climate performance. Furthermore, effective climate governance is driven by the ownership of long-term (LT) institutional investors, whose positive influence is reinforced by homogeneous distribution of their ownership. The originality or novelty of this research lies in the fact that instead of focusing on traditional corporate governance mechanisms (e.g., board characteristics), we examine a specific corporate governance structure (a combination of individual internal governance mechanisms) designed to support the internalization of CC concerns into corporate strategies and decisions (i.e., climate governance). We show that this specific corporate governance structure constitutes a good practice (Cosma et al., 2022) that allows firms to address the CC challenge while increasing their FP, thus responding to recent calls (e.g., Kavadis & Thomsen, 2023; Ludwig & Sassen, 2022; Velte et al., 2020) to identify which corporate governance mechanisms can facilitate “profitable solutions to the problems of people and planet”(Mayer, 2019). In addition, according to Velte et al. (2020), the analysis of moderators and mediators is not frequent in CC research, existing “understudied relationships”that need to be analyzed. In this regard, our study provides original empirical evidence by analyzing the moderating effect of performance on the relationship between climate governance and FP. Thus, our research adds to the existing literature on corporate sustainability and corporate governance by offering a new perspective on the debate about “if”(Hart & Ahuja, 1996) and “when”(King & Lenox, 2001) corporate sustainability pays off for companies, looking at the role played by those corporate governance mechanisms related to CC. We complement prior research on the link between FP and climate governance by looking at a particular set of corporate governance mechanisms (i.e., those related to CC). As far as we know, our research is the first to investigate the association between climate governance and FP and its determinants. Instead of analyzing individual elements, we analyze the joint effect and, moreover, we adopt a different perspective since most previous studies analyze how corporate governance mechanisms moderate the relationship between FP and EP, while we study the effect of climate performance on the association between climate governance and FP. Finally, our study expands previous findings on the extent to which institutional ownership influences climate governance and management to firms' responses to CC (e.g., Aibar-Guzmán et al., 2023), thereby answering questions recently raised by Velte (2023) on the link between institutional ownership, corporate sustainability, and FP. We show that the type of institutional investors influences corporate sustainability, leading to better FP. The article is structured under the following sections. The next section defines climate governance and outlines its characteristics. The theoretical background on which the hypotheses are stablished is presented in Section 3. The research's empirical design is described in Section 4. Section 5displays and discusses the main findings. The final section summarizes the conclusions and limitations of the research, suggesting future extensions. 2|CLIMATE GOVERNANCE The prevailing regulatory frames for corporate governance are mainly focused on the short term, which generates a “temporal dissonance” 2AIBAR-GUZM ´ AN ET AL. 15353966, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/csr.2649 by Universidade de Santiago de Compostela, Wiley Online Library on [22/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License in the case of governance in relation to CC (Benjamin & Andreadakis, 2019, p. 14). Indeed, although corporate governance plays a key role in supporting a firm's orientation toward CC issues (Gallego- ´ Alvarez & Pucheta-Martínez, 2022), the effectiveness of traditional governance mechanisms is proving to be limited (Cosma et al., 2022). Bui et al. (2020) found that conventional governance elements, like board diversity or independence, do not affect further integration of CC issues. Accordingly, CC objectives, impacts, risks, and opportunities need to be integrated into corporate governance (Goud, 2022), so that these sound structures are able to reconcile the seeking of short-term profits can be compatible with addressing CC, and state that “these new climate governance initiatives will be considered as broad, useful tools and principles which will assist directors in navigating the complex arena of climate impacts, climate risks and their financial implications”(Benjamin & Andreadakis, 2019, p. 14). Several authors (e.g., Bui et al., 2020; Cogan, 2006; Cosma et al., 2022) have provided indications on which elements characterize climate governance. In general, they highlighted the incorporation of CC into the board's responsibilities through the creation of a specialized board committee (Bui et al., 2020; Cosma et al., 2022; Luo & Tang, 2021; Principale & Pizzi, 2023); the attribution CC mitigation responsibilities to management, for example via an environmental management team (Damert & Baumgartner, 2018; Haque et al., 2016); establishing incentives linked to CC targets for executives and directors (Haque, 2017; Haque & Ntim, 2020; Kock et al., 2012; Ludwig & Sassen, 2022); establishing an environmental policy (Galbreath, 2010; Haque & Ntim, 2018); and improving the disclosure of information about CC, both internally and to stakeholders (Bui et al., 2020; Haque & Deegan, 2010). In addition, several organizations have been working on the relationship between climate governance and CC, identifying governance practices that could favor effective CC management or those that companies actually use for this purpose. In this regard, the following can be mentioned: the checklist elaborated by the CERES-Coalition for Environmentally Responsible Economies (Cogan, 2006); the climate governance principles proposed by the WEF-World Economic Forum (2019); and the trends identified by the OECD-Organization for Economic Co-operation and Development (OECD, 2022). In the context of the European Union, the European Commission has promoted a policy initiative on sustainable corporate governance— “Sustainable Corporate Governance and Directors' Duties”— (European Commission, 2020) aimed at countering short-termism in corporate environmental management (Kavadis & Thomsen, 2023). 3|THEORETICAL FOUNDATIONS, LITERATURE REVIEW AND RESEARCH HYPOTHESIS DEVELOPMENT Climate governance is a set of mechanisms, both internal and external, that govern a company's operations by performing two primary functions: resource provisioning and monitoring. Researchers have employed various theories to analyze its role in business management; among them, the RBV or resource-based-view and the agency theory stand out for their connection to the two roles mentioned above (e.g., Nguyen et al., 2021). According to RBV, the survival and success of a company depends on its distinctive capabilities and resources to build competitive advantages (Barney, 1991). In particular, the natural-resource-based view links business success to having the resources and skills to develop proactive strategies that can have a favorable impact on the environment (Hart, 1995). From this theoretical perspective, “the development and maintenance of unique and valuable environmental capabilities are the central elements allowing companies to gain financial benefit from their proactive environmental strategy”(Albertini, 2019,p.1163). Climate governance is connected with this perspective (Damert et al., 2017). On the one hand, climate governance mechanisms play a resource provisioning role by promoting environmental awareness and stakeholder orientation (Konadu et al., 2022) and providing strategic capabilities to address CC issues (Haque & Jones, 2020). On the other, climate governance mechanisms are in themselves unique and distinctive resources for a company, putting it in a stronger position to meet the challenges posed by CC (Konadu et al., 2022; Luo & Tang, 2021). Thus, effective climate governance enables firms to integrate CC- related risks and opportunities into strategic planning, risk management and decision-making processes (Benjamin & Andreadakis, 2019; Bui et al., 2020; Cosma et al., 2022), thereby providing tangible and intangible benefits such as enhanced stakeholder focus, improved image and reputation, risk mitigation, and cost savings (Damert et al., 2017; Gull et al., 2022; Kavadis & Thomsen, 2023) and leading to higher FP (Ludwig & Sassen, 2022). In this regard, Okafor et al. (2021) have shown that the implementation of corporate governance structures that promote corporate sustainability can also enhance FP. In a similar vein, Ntim and Soobaroyen (2013) found that those companies whose corporate governance structures favor proactive environmental agendas have better FP. Similarly, Busch and Hoffmann (2011) document a positive effect of effective carbon management on FP (Tobin's Qand ROE), while Cucchiella et al. (2017) document a positive effect of better carbon management on firm productivity, leading to profit growth. Aggarwal and Dow (2012) find that carbon mitigation strategies positively affect Tobin's Qand, more recently, Gull et al. (2022) showed that a company's environmental orientation has a positive effect on its FP (both ROA and Tobin's Q). On the basis of the previous discussion, our first hypothesis is that: H1. Effective climate governance is positively associated to FP. Although the sign of the association between climate performance and FP is unclear from past empirical evidence (Busch & Lewandowski, 2018; Velte et al., 2020), several studies contrast a positive impact of climate performance on both market-based (Iwata & Okada, 2011; Lee et al., 2015) and accounting-based (Gallego- ´ Alvarez AIBAR-GUZM ´ AN ET AL.3 15353966, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/csr.2649 by Universidade de Santiago de Compostela, Wiley Online Library on [22/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License et al., 2015; Ganda & Milondzo, 2018; Perez-Calderon et al., 2021). Companies with the best climate performance would not only benefit from the tangible and intangible advantages mentioned above (Albitar et al., 2023; Bui et al., 2020; Gull et al., 2022; He et al., 2023) but would also be rewarded by the financial market (Haque & Ntim, 2020; Vásquez-Ord oñez et al., 2023). Accordingly, climate performance could strengthen the impact of climate governance on FP, so that it would be stronger in companies with better climate performance. On the basis of the previous discussion, our second hypothesis is that: H2. The effect of effective climate governance on FP is strengthened by climate performance. Agency theory explains the problems that arise from the divergence of interests between shareholders and managers as a result of the dissociation between ownership and control in firms (Jensen & Meckling, 1976), as opportunistic managerial behavior is possible due to the existence of information asymmetries. Corporate governance plays an oversight role in this context, monitoring managers to act in shareholders' best interests (García-Sánchez et al., 2021; Vitolla et al., 2020). According to García-Sánchez et al. (2022), institutional investors are large specialized investors that typically pool the capital of many investors, making them key players in capital markets. Examples include mutual funds, pension funds, and insurance companies. Institutional investors have played a significant role in promoting corporate governance mechanisms (Aras & Crowther, 2008; Kavadis & Thomsen, 2023; Raimo et al., 2020). Likewise, they have also led several initiatives to combat CC (Akbas¸ & Canikli, 2018; Busch et al., 2022; Calvet et al., 2022;L  opez Arceiz et al., 2020; Serafeim, 2018; Velte et al., 2020), being considered “as catalysts in driving firms to reduce their carbon emissions and to prepare for a low-carbon economy”(Krueger et al., 2020, p. 1069). Thus, institutional investors will be interested in the corporate governance mechanisms in place at their investee firms with respect to CC (Kavadis & Thomsen, 2023; Ntim & Soobaroyen, 2013). Therefore, it could be argued that pressure from institutional investors may favor the integration of CC issues into corporate governance structures to reduce managerial entrenchment (Benjamin & Andreadakis, 2019). On the basis of the previous discussion, our third hypothesis is that: H3. The presence of institutional investors is associated with effective climate governance. However, it has been shown that institutional investors cannot be considered as “a uniform group”(García-Sánchez, Rodríguez-Ariza, et al., 2020); on the contrary, they have different investment objectives and investment horizons (Aibar-Guzmán et al., 2022), that may undermine their concern for and influence on corporate sustainability (Aibar-Guzmán et al., 2023; Kavadis & Thomsen, 2023). Depending on the time horizon in which they are looking at investment yields, institutional investors have been generally classified into LT investors and short-term (ST) investors. In general, the first group shows a greater preference for corporate sustainability and is more inclined to promote initiatives and practices in this direction (García-Sánchez, Aibar-Guzmán, & Aibar-Guzmán, 2020). In relation to CC, LT investors attach greater financial importance to climate risks and tend to encourage CC mitigation policies (Kavadis & Thomsen, 2023; Krueger et al., 2020). On the other hand, ST investors show less interest in corporate sustainability and tend to be less likely to support or hinder sustainability-related initiatives (Aibar-Guzmán et al., 2023; Caby et al., 2022). Furthermore, their short-term focus may lead these investors to under-estimate CC risks (Gilligan, 2018). Hence, the effect of institutional investors on the integration of CC issues into corporate governance structures will depend on their investment horizon (Kavadis & Thomsen, 2023). Additionally, dispersed ownership “prevents unanimous agreement over a single output level”(Hansen & Lott, 1996, p. 53), which suggests that institutional investors' influence will be higher in the case of homogeneity between the voting rights of each type of investor (García-Sánchez, Aibar-Guzmán, & Aibar-Guzmán, 2020). However, prior research on the link between ownership concentration and CC performance has yielded mixed results (Goud, 2022). Accordingly, hypothesis H3 has been split into two subhypotheses: H3a. Ownership by LT (ST) investors is positively (negatively) associated to effective climate governance. H3b. Homogeneous distribution of LT (ST) investors ownership is positively (negatively) associated to effective climate governance. The hypothesized relationships are summarized in Figure 1. 4|EMPIRICAL DESIGN 4.1 |Sample Following Aibar-Guzmán et al. (2023) and García-Sánchez et al. (2023), we focus on the largest companies worldwide. These FIGURE 1 Research model. 4AIBAR-GUZM ´ AN ET AL. 15353966, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/csr.2649 by Universidade de Santiago de Compostela, Wiley Online Library on [22/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License companies have the necessary resources and capabilities to address CC challenges related to current concerns and demands. Additionally, they support the main legal pressures that have arisen in the last decade. The sample was selected based on the sustainability (ESG) and economic-financial data needed to estimate the models in the Thomson Reuters EIKON database. The period of study runs from 2011 to 2020, a decade characterized by increasing awareness of global warming and greater consensus in terms of CC mitigation goals to be achieved (García-Sánchez et al., 2023). Thus, the sample consists of 832 multinationals, forming a balanced data panel of 8320 observations. As shown in Figure 2, these companies operate in nine different industries and are located in 45 geographic zones. 4.2 |Methodology Two model were devised, depicted in Equations (1) and (2). Hypotheses H1 and H2 are tested by means of the significance of the effect of the coefficients β1and β3of Equation (1). Thus, an effect of β1> 0 allows us to test hypothesis H1 on the effect that climate governance has on FP, while if β3> 0, the moderating impact of climate performance suggested by hypothesis H2 is confirmed, indicating that the impact of climate governance on FP (β 1 > 0) is enhanced by better climate performance. Fin_Perfi,t¼δ0þβ1ClimGovi,tþδ2EmissionScorei,t þβ3ClimGov EmissionScorei,tþδ4InstInvi,t þδ5Analystsi,t þδ6Fagei,t þδ7Fsizei,t þδ8ROAi,t þδ9Leveragei,t þδ10R&D_Invi,t þδ11AdverstInvi,t þδ12CapexInvi,t þδ13Bsizei,t þδ14Bactivityi,t þδ15Bindepi,t þδ16Dualityi,t þδ17Bdiversityi,t þδ18Btenurei,t þδ19ERRIi,t þδ20ERRIi,t þδ21EUi,t þδ22Covidtþδ23Countryiþδ24Industryi þδ25Yeartþεit þηi ð1Þ The testing of hypothesis H3, Equation (2) was designed. In relation to hypothesis H3a, the coefficients δ 1 > 0 and δ 3 >0 of Equation (2) would confirm the impact that the presence of LT investors would have on climate governance, considering the active engagement they exert through their voting rights and participation on the board of directors, respectively. In the case of ST investors, the test of the proposed relationship requires that δ 2 < 0 and δ 4 <0. Regarding hypothesis H3b, it is expected that δ 5 > 0 and δ 6 <0. ClimGovi,t¼δ0þδ1LT_InstInvi,tþδ2ST_InstInvi,tþδ3LT_InstDiri,t þST_InstDiri,tþδ5HomLT_InstInvi,t þδ6HomST_InstInvi,tþδ7EmmisionScorei,t þδ8Analystsi,t þδ9Fagei,t þδ10Fsizei,t þδ11ROAi,t þδ12Leveragei,t þδ13R&D_Invi,t þδ14AdverstInvi,t þδ15CapexInvi,t þδ16Bsizei,t þδ17Bactivityi,t þδ18Bindepi,t þδ19Dualityi,t þδ20Bdiversityi,t þδ21Btenurei,t þδ22ERRIi,t þδ23ERRIi,t þδ24EUi,t þδ25Covidtþδ26Countryiþδ27Industryi þδ28Yeartþεit þηi ð2Þ The nature of the dependent variables determines the methodology to be used. Thus, a linear regression for panel data will be used to estimate Equation (1) and an ordinal regression for panel data in the case of Equation (2). Lagged independent and control variables correct for endogeneity problems. Furthermore, in the case of Equation (1), the use of centered variables limits the multicollinearity caused by the interaction of variables. 4.3 |Variables In Equation (1), three dependent variables that represent FP (Fin_Perf). Two of these variables, MtoB and TobinQ, measure the companies' market value. MtoB corresponds to the ratio market price per share divided by the book value per share and TobinQ corresponds to the Tobin's Qratio, computed dividing the firm's market value by the replacement value of the assets (Salvi et al., 2020,2021). If these variables reach a value greater than 1, it would indicate that the company's market value is higher than its book value or replacement value, creating value for owners and investors. The third variable, ROA, measures the companies' financial profitability, which implies the inclusion of an accounting approach. It represents the company's economic profitability, calculated using the net income by total assets ratio. ClimGov is a composite indicator based on Bui et al. (2020) proposal and takes values between 0 and 6. This score is configured by adding the following components: (1) the company has an environment management team; (2) the company has an emissions policy to tackle CC; (3) the company has created a sustainability committee; (4) the company has an ESG remuneration policy; (5) the company has implemented executive compensation linked to sustainability performance; and (6) the company discloses information on CC in accordance with international standards which is verified by an external professional. Climate performance is depicted by EmissionScore variable. It is obtained from EIKON and measures the performance of the company in relation to the reduction of environmental emissions in operations and production. Regarding the independent variables related to the presence of institutional investors in Equation (2), we use the approach FIGURE 2 Sample description. AIBAR-GUZM ´ AN ET AL.5 15353966, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/csr.2649 by Universidade de Santiago de Compostela, Wiley Online Library on [22/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License of different authors (i.e., Brossard et al., 2013; García-Sánchez, Aibar- Guzmán, & Aibar-Guzmán, 2020; García-Sánchez et al., 2022). Thus, institutional investors were classified based on the horizon of their investment into LT investors—pension or endowment funds, family firms and government institutions—and ST investors—cross holdings, financial institutions, and other strategic holdings—. The active engagement of their presence is determined by the exercise of their voting rights, LT_InstInv and ST_InstInv, and their participation on the board, as the percentage of institutional directors, LT_InstDir and ST_InstDir. Additionally, we adopt the RAE fragmentation index to determine the level of homogeneity between the voting rights of each type of institutional investor within the two categories determined by the time horizon of their investment. Thus, the variable HomLT_InstInv and HomST_InstInv have been calculated using the formulas Hom_LTInstINvI,t ¼1P 3 i¼1 VR 2 i and Hom_STInstINvI,t ¼1P 3 i¼1 VR 2 i , where VR are the voting rights of each of the institutional investors included in the LT and ST categories. To limit biased results, we include a set of control variables related to the resources and capabilities of multinationals, indicators of good governance and institutional pressures with regard to environmental sustainability were included. These variables have been selected based on previous studies considering their influence on business sustainability strategies (Aibar-Guzmán et al., 2023; García- Sánchez et al., 2023). Table 1summarizes their definition and measurement. Additionally, the effects of the sector (Industry), country (Country), time (Year), and the relevance of the COVID-19 pandemic in the unforgettable year 2020 (Covid) are controlled. TABLE 1 Variables and statistics. Variable Definition Mean/freq. Std. dev. TobinQ Market price per share/book value per share 1.602 1.281 MtoB Market value/replacement value of the assets 1.532 1.192 ROA Net income by total assets 5.568 7.954 ClimGov Composite score of climate governance mechanisms 3.280 1.058 LT_InstInv Percentage of voting rights of LT institutional investors 0,077 0.169 ST_InstInv Percentage of voting rights of ST institutional investors 0.126 0.210 LT_InstDirec Percentage of institutional directors of LT institutional investors 0.199 0.298 ST_InstDirec Percentage of institutional directors of ST institutional investors 0.103 0.231 HomLT_InstInv Level of homogeneity of voting rights of LT institutional investors 0.335 0.103 HomST_InstInv Level of homogeneity of voting rights of ST institutional investors 0.593 0.137 EmissionScore Firms´ performance relating reduction of environmental emissions 68.443 24.078 Fage Logarithm of the firm's years 3.555 0.843 Fsize Logarithm of firms' total assets 16.339 1.619 Leverage Ratio between debt and total assets 0.684 0.563 R&D_Inv Investment intensity in R&D to sales 29,800 55,000 Advert_Inv Investment intensity in advertising to sales 21,000 19,600 CAPEX_Inv Investment intensity in capital to sales 13,700 120,000 Bsize Number of members (directors) 11.480 3.527 Bactivity Number of meetings of the board per year 10.041 5.577 Bindep Proportion of independent directors 0.507 0.386 Duality Dummy that takes value 1 if the CEO is the chair of the board 0.676 Bdiversity Percentage of female directors 0,190 0.136 Btenure Tenure of the directors 6.898 3.092 Analysts Number of financial analysts that cover the firm 17.309 8.627 ERRI The Environmental Regulatory Regime Index 0.923 0.689 EPI The Environmental Performance Index 60.847 8.939 EU Dummy coded 1 from EU countries from 2014 to 2020 (García-Sánchez et al., 2022) 0.294 6AIBAR-GUZM ´ AN ET AL. 15353966, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/csr.2649 by Universidade de Santiago de Compostela, Wiley Online Library on [22/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 2 Correlations matrix (***p< 0.01, **p< 0.05, *p< 0.1). 123 4567891011121314 1 TobinQ 1 2 MtoB 0.366*** 1 3 ROA 0.569*** 0.165*** 1 4 ClimGov 0.079*** 0.071*** 0.064*** 1 5 LT_InstInv 0.012 0.030** 0.009 0.048*** 1 6 ST_InstInv 0.015 0.004 0.035*** 0.125*** 0.142*** 1 7 HomLT_InstInv 0.003 0.022* 0.003 0.024** 0.931*** 0.138*** 1 8 HomoST_InstInv 0.011 0.014 0.043**** 0.109*** 0.136*** 0.947*** 0.119*** 1 9 LT_InstDirec 0.033*** 0.074*** 0.019 0.076*** 0.143*** 0.172*** 0.129*** 0.145*** 1 10 ST_InstDirec 0.034*** 0.049*** 0.015 0.093*** 0.206*** 0.500*** 0.147*** 0.419*** 0.482*** 1 11 EmissionScore 0.021* 0.000 0.024** 0.386*** 0.019 0.092*** 0.016 0.083*** 0.072*** 0.076*** 1 12 Fage 0.024** 0.021* 0.029** 0.015 0.090*** 0.158*** 0.080*** 0.147*** 0.032*** 0.081*** 0.146*** 1 13 Fsize 0.312*** 0.188*** 0.174*** 0.240*** 0.054*** 0.122*** 0.094*** 0.104*** 0.043*** 0.085*** 0.389*** 0.069*** 1 14 Leverage 0.001 0.020* 0.025** 0.085*** 0.073*** 0.128*** 0.075*** 0.121*** 0.136*** 0.095*** 0.111*** 0.003 0.072*** 1 15 R&D_Inv 0.004 0.008 0.022* 0.019 0.022* 0.003 0.016 0.012 0.015 0.013 0.025** 0.019 0.067*** 0.019* 16 Advert_Inv 0.007 0.007 0.031*** 0.060*** 0.006 0.056*** 0.003 0.039*** 0.037*** 0.078*** 0.015 0.019 0.057*** 0.331*** 17 CAPEX_Inv 0.015 0.022* 0.023** 0.052*** 0.067*** 0.050*** 0.092*** 0.037*** 0.039*** 0.054*** 0.022* 0.004 0.065*** 0.438*** 18 Bsize 0.185*** 0.119*** 0.112*** 0.105*** 0.106*** 0.055*** 0.093*** 0.049*** 0.030*** 0.011 0.206*** 0.107*** 0.440*** 0.103*** 19 Bactivity 0.133*** 0.069*** 0.077*** 0.021* 0.055*** 0.046*** 0.085*** 0.048*** 0.042*** 0.047 0.018 0.020* 0.123*** 0.047*** 20 Bindep 0.019 0.032*** 0.008 0.201*** 0.017 0.080*** 0.025** 0.060*** 0.799*** 0.389 0.124*** 0.097*** 0.111*** 0.068*** 21 Duality 0.038*** 0.066*** 0.021* 0.022* 0.048*** 0.049*** 0.035*** 0.060*** 0.045*** 0.011 0.105*** 0.076*** 0.147*** 0.063*** 22 Bdiversity 0.070*** 0.006 0.036*** 0.299*** 0.063*** 0.153*** 0.035*** 0.135*** 0.031*** 0.095 0.164*** 0.019 0.089*** 0.140*** 23 Btenure 0.092*** 0.035*** 0.057*** 0.059*** 0.077** 0.024** 0.072*** 0.011 0.120*** 0.091 0.028** 0.161*** 0.002 0.075*** 24 Analysts 0.151*** 0.009 0.100*** 0.157*** 0.004 0.042*** 0.005 0.065*** 0.015 0.016 0.304*** 0.052*** 0.452*** 0.006 25 ERRI 0.016 0.097*** 0.030** 0.124*** 0.130*** 0.395*** 0.112*** 0.375*** 0.071*** 0.108 0.118*** 0.033*** 0.030** 0.293*** 26 EPI 0.009 0.123*** 0.037*** 0.008 0.012 0.196*** 0.028** 0.175*** 0.064*** 0.051 0.059*** 0.050*** 0.046*** 0.107*** 27 EU 0.028** 0.118*** 0.034*** 0.195*** 0.156*** 0.019 0.114*** 0.024** 0.019 0.021 0.189*** 0.052*** 0.053*** 0.066*** 28 Covid 0.009 0.006 0.078*** 0.122*** 0.008 0.006 0.010 0.009 0.040*** 0.009 0.082*** 0.057*** 0.025** 0.006 15 16 17 18 19 20 21 22 23 24 25 26 27 28 15 R&D_Inv 1 16 Advert_Inv 0.886*** 1 17 CAPEX_Inv 0.781*** 0.891*** 1 18 Bsize 0.019 0.037*** 0.038*** 1 (Continues) AIBAR-GUZM ´ AN ET AL.7 15353966, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/csr.2649 by Universidade de Santiago de Compostela, Wiley Online Library on [22/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 5|RESULTS AND DISCUSSION 5.1 |Descriptive results Table 1shows the mean and the standard deviation of the variables proposed to estimate the empirical models reflected in Equations (1) and (2). As can be seen, the sample companies have an average economic return of 5.6% and a market value greater than 1.5 its book or replacement value. The level of development of climate governance is slightly above the average of the six items considered in its construction, reaching an average value of 3.280 within an interval between 0 and 6 points. The percentage of voting rights of ST and LT investors is 7.7 and 12.6, respectively, presenting a level of homogeneity of 0.335 and 0.593. The presence of institutional directors is higher for the representatives of investors with a long-term horizon (19.9%) than those with a short-term horizon (10.3%). The matrix of correlations between all variables required for the empirical analysis is presented in Table 2, not observing potential problems of collinearity between them. 5.2 |Results for Equation (1): The financial benefits of effective climate governance Panel A of Table 3shows the findings obtained from estimating Equation (1) for the testing of hypotheses H1 and H2, both being confirmed as β1> 0 and β3> 0 in all the estimated models. To the extent that the impact of effective climate governance on FP is analyzed with respect to two market variables (TobinQ and MtoB) and an accounting ratio (ROA), the robustness of the results is guaranteed. Additionally, the results of Equation (1) are presented in Table 3without and with the inclusion of the ClimGov*EmissionScore interaction in order to show the absence of multicollinearity problems that its inclusion may entail in the case of not having used centered variables. As regards hypothesis H1, the effect of climate governance (ClimGov) on FP is positive and significant for confidence levels of 99%. The impact is greater on economic profitability—ROA—(ClimGov: coeff. =1.675; p-value <0.01) than on market value, showing a greater impact on the TobinQ variable (ClimGov: coeff. =0.000172; p-value <0.01) than on MtoB (ClimGov: coeff. =0.00000106; p-value <0.01). On the basis of these findings, we can accept hypothesis H1, confirming that effective climate governance is positively associated to FP. These findings confirm those of Busch and Hoffmann (2011), Aggarwal and Dow (2012), and Ntim and Soobaroyen (2013), as well as those of Okafor et al. (2021) regarding corporate social responsibility. Regarding H2, climate performance (EmissionScore) variable has a positive and significant impact for confidence levels of 99% in the three variables that measure the companies' FP, showing the same order of impact as that mentioned for climate governance. Thus, the effect is greatest for ROA (EmissionScore: coeff. =0.0497; p-value <0.01), followed by TobinQ (EmissionScore: coeff =0.00000526; TABLE 2 (Continued) 15 16 17 18 19 20 21 22 23 24 25 26 27 28 19 Bactivity 0.002 0.027** 0.063*** 0.002 1 20 Bindep 0.006 0.037*** 0.020* 0.020* 0.085*** 1 21 Duality 0.045*** 0.027** 0.008 0.101*** 0.055*** 0.060*** 1 22 Bdiversity 0.052*** 0.097*** 0.114*** 0.001 0.142*** 0.257*** 0.001 1 23 Btenure 0.043*** 0.055*** 0.075*** 0.002 0.223*** 0.078*** 0.210*** 0.021 1 24 Analysts 0.117*** 0.105*** 0.094*** 0.194*** 0.115*** 0.106*** 0.155*** 0.075*** 0.047*** 1 25 ERRI 0.061*** 0.157*** 0.200*** 0.084*** 0.117*** 0.036*** 0.032*** 0.320*** 0.025** 0.011 1 26 EPI 0.014 0.046*** 0.060*** 0.088*** 0.038*** 0.007 0.045*** 0.122*** 0.131*** 0.055*** 0.643*** 1 27 EU 0.026** 0.050*** 0.055*** 0.106*** 0.032*** 0.134*** 0.007 0.396*** 0.033*** 0.077*** 0.241*** 0.326*** 1 28 Covid 0.006 0.007 0.004 0.040*** 0.004 0.067*** 0.026** 0.183*** 0.005 0.078*** 0.000 0.000 0.238*** 1 8AIBAR-GUZM ´ AN ET AL. 15353966, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/csr.2649 by Universidade de Santiago de Compostela, Wiley Online Library on [22/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 3 Results for Equation (1) (***p< 0.01, **p< 0.05, *p< 0.1). Panel A: Basic and robust results with linear regression Firms' FP TobinQ MtoB ROA Coeff. (std. error) Coeff. (std. error) Coeff. (std. error) Coeff. (std. error) Coeff. (std. error) Coeff. (std. error) ClimGov 2.30e-05* (1.34e-05) 0.000172*** (3.10e-05) 2.02e-07* (1.05e-07) 1.06e-06*** (4.00e-07) 0.390*** (0.123) 1.675*** (0.291) EmissionScore 1.38e-06** (6.82e-07) 5.26e-06*** (1.42e-06) 1.77e-08* (9.12e-09) 5.61e-08*** (1.85e-08) 0.00757* (0.00313) 0.0497*** (0.0133) ClimGov* EmissionScore 2.29e-06*** (4.31e-07) 1.33e-08** (5.56e-09) 0.0197*** (0.00404) InstInve 5.86e-07 (8.66e-07) 7.00e-07 (8.67e-07) 4.16e-08** (2.04e-08) 4.28e-08** (2.04e-08) 0.00534 (0.00587) 0.00462 (0.00587) Analysts 2.26e-05*** (2.44e-06) 2.19e-05*** (2.43e-06) 7.56e-08** (3.56e-08) 7.30e-08** (3.56e-08) 0.148*** (0.0202) 0.142*** (0.0202) Fage 2.10e-05 (3.06e-05) 3.03e-05 (3.06e-05) 3.36e-07 (6.00e-07) 4.17e-07 (6.01e-07) 0.106 (0.219) 0.171 (0.219) Fsize 0.000313*** (1.91e-05) 0.000316*** (1.91e-05) 1.65e-06*** (3.65e-07) 1.66e-06*** (3.65e-07) 1.524*** (0.141) 1.553*** (0.141) ROA 2.58e-05*** (1.33e-06) 2.56e-05*** (1.33e-06) 1.18e-07*** (1.70e-08) 1.17e-07*** (1.70e-08) Leverage 7.51e-08 (4.69e-08) 7.77e-08* (4.68e-08) 1.07e-10 (7.16e-10) 1.20e-10 (7.16e-10) 0.000845** (0.000382) 0.000888** (0.000382) R&D_Inv 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) 8.67e-10 (6.52e-10) 8.65e-10 (6.51e-10) Advert_Inv 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) 1.84e-10 (2.03e-10) 1.98e-10 (2.02e-10) CAPEX_Inv 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) 2.33e-10 (2.07e-10) 2.26e-10 (2.07e-10) Bsize 5.54e-06 (5.21e-06) 5.72e-06 (5.20e-06) 9.23e-08 (7.15e-08) 9.35e-08 (7.14e-08) 0.0103 (0.0456) 0.00912 (0.0455) Bactivity 2.64e-06 (2.77e-06) 2.45e-06 (2.77e-06) 2.50e-08 (3.69e-08) 2.46e-08 (3.69e-08) 0.0108 (0.0250) 0.0136 (0.0250) Bindep 2.21e-07 (3.17e-07) 2.49e-07 (3.17e-07) 1.94e-09 (4.10e-09) 2.02e-09 (4.10e-09) 0.00286 (0.00297) 0.00322 (0.00297) Duality 6.67e-05** (2.88e-05) 6.77e-05** (2.87e-05) 3.61e-07 (3.79e-07) 3.62e-07 (3.79e-07) 0.492* (0.263) 0.517** (0.263) Bdiversity 7.44e-07 (1.16e-06) 9.61e-07 (1.16e-06) 3.75e-08** (1.55e-08) 3.92e-08** (1.55e-08) 0.0228** (0.0106) 0.0238** (0.0106) Btenure 4.37e-08 (5.93e-06) 1.01e-06 (5.92e-06) 1.26e-07 (8.33e-08) 1.33e-07 (8.33e-08) 0.118** (0.0509) 0.111** (0.0509) ERRI 3.77e-05 (6.41e-05) 3.50e-05 (6.41e-05) 6.49e-07 (1.81e-06) 6.40e-07 (1.81e-06) 0.390 (0.430) 0.407 (0.430) EPI 3.14e-06 (4.62e-06) 2.84e-06 (4.62e-06) 3.52e-07*** (1.33e-07) 3.54e-07*** (1.33e-07) 0.0344 (0.0306) 0.0324 (0.0306) EU 3.10e-05*** (8.35e-06) 2.73e-05*** (8.36e-06) 3.21e-07*** (1.08e-07) 2.98e-07*** (1.09e-07) 0.223*** (0.0785) 0.195** (0.0786) Covid 9.47e-05*** (2.70e-05) 9.41e-05*** (2.69e-05) 4.56e-07 (3.41e-07) 4.44e-07 (3.41e-07) 1.788*** (0.262) 1.782*** (0.261) (Continues) AIBAR-GUZM ´ AN ET AL.9 15353966, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/csr.2649 by Universidade de Santiago de Compostela, Wiley Online Library on [22/02/2024]. 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See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License