Do Board Characteristics Affect Banks’ Environmental Performance?

Abstract

This study empirically investigates the relationship between board characteristics (board size, board independence, Corporate Social Responsibility sustainability committee, board gender diversity, CEO duality, board-specific skills) and environmental performance (emissions, environmental innovation and resource use) of a sample of banks from different countries. In detail, we use an unbalanced panel dataset of 1,644 observations for 311 banks from the United States, Europe, the UK and Canada, over the period between 2015 and 2020. Through the Fixed Effect panel model and the generalized method of moments system version of the Arellano-Bond estimator, we find that both the percentage of women on boards and the presence of the CSR sustainability committee enhance the banks’ environmental performance. These findings are confirmed by all three sub-pillars of environmental performance, that is, emissions, environmental innovation and resource use. Our results shed light on the role that certain board characteristics play in improving the environmental performance of banks.

Keywords

Banks board characteristics corporate governance environmental performance

Introduction

The effects of global warming are felt across all industries, modifying inevitably the way we live and the way we work. Nowadays, all businesses are threatened by the impacts of climate change (D’Angelo et al., 2022). For companies mulling over the ways climate change influences their activities, the risks could be classified into two main categories: physical and transitional risks. Major weather events such as hurricanes and wildfires are all symptoms of the climate crisis, which in turn cause physical damage to people and businesses such as the real estate industry and transport links. The agriculture industry is another sector exposed to physical risk, where flooding and drought represent a risk to crops and livestock, caused by extreme cold and heat. The leisure and tourism industry is also open to immediate physical damages, where wildfires and heat waves threaten popular sightseer regions making them unsafe.

Transitional risks are also another typology of risk derived from the climate crisis. Changes in technologies, laws, regulation and consumer trends sectors induce investors and shareholders to move away from those businesses that increase global warming, since some sectors are considered at risk of being left with stranded assets, such as land, property or equipment whose worth has deteriorated. In this context, the oil companies and mining sectors are those industries that suffer the most from transitional risks.

Considering all these factors, the financial sector is not left indifferent to financial climate-related risks too. Indeed, the impact of climate change on the health of the financial system is becoming one of the most urgent topics too, capturing the attention of policymakers, scholars and academics. Central banks, along with governments, also play an important role in managing climate change, helping the overall financial system move towards a low-carbon economy (Bank of England, 2021b; Brunetti et al., 2021; European Central Bank, 2021).

In this regulatory framework, some characteristics of the board of directors of financial institutions, such as its composition and its organizational model, could be conclusive in managing environmental issues and climate change risk. After the subprime crisis, bank governance issues have been monitored by scholars and regulators because ‘effective corporate governance is critical to the proper functioning of the banking sector and the economy as a whole’ (BCBS, 2015).

At the current state of academic research, despite the various studies explaining the relationship between governance practices and environmental performance at the firm-level, empirical studies on the banking industry are quite limited. Indeed, there is a scant strand of literature that takes into consideration the characteristics of the board concerning environmental performance in the banking sector. Until now, only a few relevant studies have been done on the topic (Cariola et al., 2020; La Rocca et al., 2022; Neville et al., 2019; Reguera-Alvarado et al., 2017).

By analysing a sample of 311 banks from the United States, Europe, the UK and Canada over the period 2015–2020, we aim to examine whether and to what extent the characteristics of the board are capable of influencing the climate policies of banks in terms of environmental performance. First, using the Fixed Effect panel model and then through the generalized method of moments (GMM)-system version of the Arellano-Bond estimator, we find strong evidence that two of the six corporate governance variables investigated (i.e., the percentage of women on the board of directors and the presence of the Corporate Social Responsibility (CSR) sustainability committee) can enhance banks environmental performance. Furthermore, we observe that these results are confirmed by all three sub-pillars of environmental performance, that is, emissions, environmental innovation and resource use. Accordingly, our contribution aims to fill the gap in the literature by answering the following research questions:

H₁: Ceteris paribus, board size is likely to have a positive impact on individual dimensions and the overall index of banks’ environmental performance.

H₂: Ceteris paribus, an independent board is likely to have a positive impact on individual dimensions and the overall index of banks’ environmental performance.

H₃: Ceteris paribus, the sustainability committee is likely to have a positive impact on individual dimensions and the overall index of banks’ environmental performance.

H₄: Ceteris paribus, board gender diversity is likely to have a positive impact on individual dimensions and the overall index of banks’ environmental performance.

H₅: Ceteris paribus, board-specific skills are likely to have a positive impact on individual dimensions and the overall index of banks’ environmental performance.

H₆: Ceteris paribus, CEO Duality is likely to have a positive impact on individual dimensions and the overall index of banks’ environmental performance.

To the best of our knowledge, this is the first study in the banking industry that explores the relationship between corporate governance variables (board size, board independence, CSR sustainability committee, board gender diversity, CEO duality, board-specific skills) and environmental performance, together with the three sub-pillars regarding emissions, environmental innovation and resource use.

The study offers significant contributions to the current state of the literature by presenting new understandings regarding the effects of governance structures on environmental performance. First, we examine the relationship between banks’ board characteristics and both aggregate and individual dimensions of environmental performance. In this view, the environmental performance is taken from the Refinitiv database, and it measures ‘a company’s impact on living and non-living natural systems, including the air, land and water, as well as complete ecosystems’ (Thomson Reuters Refinitiv database).

Employing comprehensive and granular information on the banks’ resources, emissions and innovation dimensions of environmental performance from the Refinitiv database, we examine how financial institutions’ board characteristics are correlated not only to the overall score of the environmental pillar but also with its three constitutive dimensions.

Second, although there is a wide strand of literature studying the association between corporate governance and environmental performance, academic studies focus on non-financial firms, leaving little room for the banking sector. Indeed, the topic of the corporate governance mechanism in the banking industry has not obtained the same level of attention from academics and researchers as other sectors, and therefore studies focusing on bank governance are narrow (Moussa, 2019). Lastly, considering the international differences in adopting corporate governance practices, we provide wider evidence on the governance-environment relationship.

The remainder of the article is organized as follows. We present a literature review and describe the methodology adopted. We then present the empirical results, reinforced by robustness checks. Finally, we propose some conclusions.

Literature Review

In recent years, CSR has become a debated topic among policymakers, practitioners and academics. CSR is a term typically used to refer to the sustainability-oriented managerial strategy of the firm to integrate environmental, social and governance (ESG) practices while still pursuing financial outcomes (Morea et al., 2022). In turn, according to the European Banking Authority (EBA), ESG practices are ‘environmental, social or governance characteristics that may have a positive or negative impact on the financial performance or solvency of an entity, sovereign or individual’ (EBA, 2021, p. 31).

In this view, CSR can be considered as the precursor of ESG sustainable practices, with the only difference being that ESG activities include governance explicitly while CSR strategies do not (Gillan et al., 2021). Therefore, CSR orientation strategies can be implemented into ESG metrics, which in turn enhance indirectly companies’ environmental performances (Kapoor & Sandhu, 2010; Kraus et al., 2020).

Some authors have focused on the long-term evolution of this important concept (e.g., Carroll, 2021). At the corporate level, for example, companies are responding by adapting their governance structures and practices by introducing a dedicated CSR committee (Ricart et al., 2005) or by increasing board independence. Indeed, it has been demonstrated that a higher percentage of independent directors tends to stimulate companies to satisfy the requests of stakeholders and ESG criteria (Ortas et al., 2017).

Despite all of this, there is a large and rapidly growing literature examining the relationship between board composition and firms’ environmental performance. Referring to non-financial firms, Walls et al. (2012), through a sample of 313 U.S.-listed firms in the period 1997–2005, among other things find that board independence, environmental committee and board size are positively associated with environmental concerns, and the proportion of female directors on boards is weakly and negatively associated. More recently, García Martín and Herrero (2020) analysed the relationship between board characteristics and environmental performance of 644 companies based in the EU, over the period 2002–2017. They show that gender diversity and the existence of a CSR committee are positively associated with the firms’ environmental performance. Similarly, Orazalin and Mahmood (2021), using a sample of 3,023 firm-year observations from companies operating in 22 countries and 10 different industries for the period of 2009–2016, found that board gender diversity and the presence of a sustainability committee have a positive impact on environmental performance. Furthermore, Beji et al. (2021), using a sample of 120 French-listed companies in the period 2003–2016, showed among other things that boards’ age diversity, the percentage of foreign directors, and multiple directorships are positively associated with environmental issues. However, their findings show that the presence of directors with business education is negatively associated with environment and business ethics dimensions.

A body of literature research focuses on the relationship between the presence of women on the board and firms’ environmental performance. Ben-Amar et al. (2017) analysed a sample of publicly listed Canadian firms over the period 2008–2014 and showed that the likelihood of voluntary climate change disclosure increases with the women percentage on boards. Kyaw et al. (2022), using data from U.S. firms over 2002–2018 (6,764 firm-year observations), found that board gender diversity is positively associated with firms’ emission reduction performance. Similarly, Lu and Herremans (2019), exploring a sample of 837 firms headquartered in the United States for the years 2009–2015, affirmed that gender diversity is positively associated with firms’ environmental performance scores. On the same wave, Nadeem et al. (2020), analysing a large dataset of U.S.-listed firms over 2002–2018, argued that board gender diversity has a significant positive association with environmental innovation, measured as process innovation and product innovation. With specific reference to carbon emissions, Nuber and Velte (2021), using a large cross-country sample from non-financial firms in the European STOXX600 index over the 2009–2018 period, found a robust linear and positive relationship between board gender diversity and firms’ carbon performance. Other authors showed that firms with a higher share of women on the board have a greater propensity to disclose information on greenhouse gas emissions (Liao et al., 2015) and are less often sued for environmental infringements (Liu, 2018).

Orazalin (2020) instead focused on the impact of board sustainability committees on environmental and social performance. Analysing a dataset of 109 UK-listed firms for the period 2009–2016, the author suggested that the presence of a sustainability committee improves the effectiveness of CSR strategies. Relating to the banking industry, García-Meca et al. (2018) used a sample of 159 banks from different countries (Canada, France, Germany, Italy, the Netherlands, Spain, Sweden, the United Kingdom and the United States), over the period 2004–2010. They find that independent directors and gender diversity favour the disclosure of CSR information in the banking sector. Birindelli et al. (2019) investigated a sample of 96 listed banks in the EMEA region over 2011–2016 and highlighted how gender diversity is an important driver of environmental practices.

Nevertheless, concerning financial institutions, the related empirical literature on environmental performance is still very scarce. Most of all academic research on the relationship between board characteristics and environmental performance is conducted at the industry-firm level. However, financial institutions are not exempt from all the risks associated with climate change and proper dedicated studies are then required (Cappa et al., 2022; Fasano & Cappa, 2022). First, like all industry firms, banks contribute to climate change directly through their activities. Second, banks temper global warming through the financing of sustainable activities of non-financial firms that want to reduce GHG emissions and become environment friendly. Indeed, banks continue to be a major vehicle of green projects as principal financiers, speeding up the transition from an economy with high use of coal and fossil fuel to a green one. Therefore, financial institutions play a significant role in managing climate change, by helping not only the overall financial system but also commercial enterprises to move towards a net-zero carbon economy (Bank of England, 2021a; Brainard, 2021; European Central Bank, 2021).

Data

The dataset includes a large sample of listed banks headquartered in the United States, Europe, the UK and Canada, for the period 2015–2020. The selected countries were chosen mainly because they have a large data availability in terms of ESG information compared to other countries during the period taken into consideration.

Data on Environmental performance and corporate governance variables (percentage of women on the board, CEO Duality, board size, percentage of independent board members, CSR sustainability committee dummy and board-specific skills) are acquired from the Thomson Reuters Refinitiv database. The same holds for the following bank-specific financials: Debt on Equity, Loans to Deposits, Capital Adequacy and Return on Equity (ROE). Macro-variables such as governmental environment expenditures and environmental taxes are collected instead from the International Monetary Fund database.

For each year, a bank was included in the sample if we had information on the variables of interest. Specifically, missing data on Environmental sub-pillar factors, such as emission, environmental innovation and resource use score led to a sample of an unbalanced panel database of 1,644 observations for 311 banks.

Consistent with our research goal, our dependent variable is the environmental pillar score (E pillar), which reflects ‘how well a company uses best management practices to avoid environmental risks and capitalize on environmental opportunities to generate long-term shareholder value’ (Thomson Reuters Refinitiv database). The Refinitiv environmental score is the combination of three constitutive dimensions namely Emission, Innovation and Resource pillars (Tan et al., 2017), which reflect each bank’s footprint for emission reduction, product innovation and use of resources. The overall score and individual categories are computed based on the Refinitiv ESG scoring methodology (Refinitiv, 2022). In this regard, it is important to also consider the specific dimensions of environmental performance separately. Indeed, as noted by Bouslah et al. (2013), combining individual pillars of environmental performance into a comprehensive score may misperceive the effects of singular dimensions that are less important. For this reason, as robustness checks, we analyse in detail the individual dimensions of environmental performance to assess how banks’ board characteristics are related to the principal constituting categories and the overall level of the environmental pillar score. Following, Appendix A summarizes all the variables taken into consideration, whereas Table 1 presents the summary statistics. The environmental performance and its sub-categories range from a minimum of zero to a maximum of almost 100. On average, the Environmental Score registers a mean of 23.42. Emission Score, Environmental Innovation Score and Resource Use Score are 17.23, 14.05 and 16.51, respectively. Regarding the variable board gender diversity, women on the boards account for 19.39%. The Sustainable Committee dummy presents a mean of 0.24 if we consider that the range is between 0 and 1. Table 2 presents the correlation matrix for the variables included in our econometric models. The correlation between the sustainability committee and the environmental pillar score is 0.816. At the same time, the three sub-pillars also have a fairly important correlation with the dummy of the sustainability committee. The strong positive correlations indicate that both variables tend to go up in response to one another. This should not be surprizing, given that the presence of board sustainability committees improves the efficacy of CSR policies and impacts more effectively the sustainability-orientation strategies of the firm, which in turn leads to better environmental performances (Hillman & Dalziel, 2003; Orazalin, 2020). Even the Debt on Equity variable shows a quite positive association with the Environmental pillar and its sub-pillars. This is consistent with the trade-off view, according to which sustainable strategies represent a cost for the firm that, in turn, requires more debt to implement these practices (Friedman, 1970).

Table 1.

Dataset of the Sample of Banks Listed on the Largest Stock Exchanges in the United States, Europe, the UK and Canada for the Period 2015–2020.

	Mean	Standard Deviation	Minimum	Maximum	Observations
Environmental score	23.42	31.97	0	97.47	1,644
Emission score	17.23	30.07	0	99.89	1,644
Environmental innovation score	14.05	28.66	0	98.70	1,644
Resource use score	16.51	30.38	0	99.88	1,644
Board size	2.55	2.90	0	23	1,644
Independent board	77.40	16.02	0	100	1,644
Sustainability committee	0.24	0.42	0	1	1,445
Board gender diversity	19.39	11.56	0	57.14	1,445
Board-specific skills	45.91	18.63	0	100	1,374
CEO duality	1.69	0.80	0	1	1,644
Debt on equity	1.62	20.69	0	793.46	1,644
Loans to deposits	0.92	0.24	0.02	4.25	1,644
Capital adequacy	6.1e + 9	2.4e + 10	671.47	2.3e + 11	1,644
Return on equity	0.08	0.09	−1.59	0.76	1,644
Environmental taxes	1.11	0.83	0.66	4.70	1,644
Government expenses	22.69	0.90	17.65	23.91	1,644

Notes: Descriptive statistics. For the definition of the variables, see Appendix A.

Table 2.

Dataset of the Sample of Banks Listed on the Largest Stock Exchanges in the United States, Europe, the UK and Canada for the Period 2015–2020.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)	(16)
(1) Environmental pillar	1.000
(2) Emission score	0.888	1.000
(3) Environmental innovation	0.913	0.888	1.000
(4) Resource use	0.898	0.939	0.899	1.000
(5) Board size	0.356	0.343	0.319	0.346	1.000
(6) Independent board	−0.319	−0.348	−0.287	−0.310	−0.265	1.000
(7) Sustainability committee	0.816	0.844	0.807	0.867	0.302	−0.265	1.000
(8) Board gender diversity	0.459	0.490	0.515	0.499	0.113	−0.049	0.476	1.000
(9) Board-specific skills	−0.033	−0.033	−0.023	−0.012	−0.128	−0.014	−0.054	0.010	1.000
(10) CEO duality	−0.202	−0.220	−0.219	−0.204	−0.050	0.077	−0.187	−0.131	0.134	1.000
(11) Debt on equity	0.573	0.570	0.567	0.574	0.158	−0.329	0.506	0.349	−0.078	−0.160	1.000
(12) Loan to deposits	−0.089	−0.129	−0.081	−0.125	−0.074	−0.054	−0.092	−0.073	0.039	−0.078	0.130	1.000
(13) Capital adequacy	0.625	0.603	0.625	0.639	0.256	−0.010	0.558	0.348	0.124	−0.082	0.356	−0.159	1.000
(14) Return on equity	−0.314	−0.247	−0.238	−0.267	−0.156	0.150	−0.247	−0.087	0.012	0.174	−0.066	0.057	−0.141	1.000
(15) Environmental taxes	0.689	0.707	0.679	0.681	0.228	−0.496	0.623	0.373	−0.147	−0.320	0.657	0.047	0.258	−0.323	1.000
(16) Government expenses	−0.089	−0.108	−0.025	−0.108	−0.030	0.098	−0.113	0.023	0.123	0.073	−0.013	−0.086	0.106	0.099	−0.156	1.000

Notes: Correlation matrix. For the definition of the variables, see Appendix A.

Model Design

The empirical approach proposed in this work consists in panel regression, which exploits both the cross-section and the time series dimension of longitudinal data. The mixture of information from both cross-section dimensions and time allows a greater flexibility and more efficiency in modelling (Greene, 2005). The principal model design describes the standard estimation techniques required to make inferences in linear models (using cross-sectional data). As robustness checks instead, we employ the more complicated case of (linear) panel data models. The properties of the estimators are then reviewed, highlighting the diagnostic tests that may be used to corroborate model specifications. Finally, the specifications proposed for the empirical analysis are detailed. In our case, the panel data analysis takes the form of the model below:

Y_{i t} = β_{i} * {Board Characteristics}_{i t} + β_{i} * Bank Controls + β_{i} * Country Variables +_{i} +_{t} + u_{i t}

(1)

where $i = 1, \dots N; t = 1, \dots T$

where $Y_{i t}$ represents the Refinitiv Environmental Pillar, which measures ‘how well a company uses best management practices to avoid environmental risks and capitalize on environmental opportunities in order to generate long-term shareholder value’ (Thomson Reuters Refinitiv database). In addition to that, as dependent variables $Y_{i t}$ we also employ the sub-pillars of the Refinitiv Environmental Pillar, namely Emission Score, Environmental Innovation Score and Resource Use Score. The Emission sub-pillar score ‘measures a company’s commitment and effectiveness towards reducing environmental emission in the production and operational processes’, meanwhile Environmental Innovation Score ‘reflects a company’s capacity to reduce the environmental costs and burdens for its customers, and thereby creating new market opportunities through new environmental technologies and processes or eco-designed products’ (Thomson Reuters Refinitiv database). Lastly, Resource Use sub-pillar Score ‘reflects a company’s performance and capacity to reduce the use of materials, energy or water, and to find more eco-efficient solutions by improving supply chain management’ (Thomson Reuters Refinitiv database). The $B o a r d C h a r a c t e r i s t i c s_{i t}$ independent variables are the interested corporate governance variables taken into consideration in this study, that is, percentage of women on the board, CEO duality, the board size, percentage of independent board members, CSR sustainability committee dummy and board-specific skills. The explanatory variables related to the $B a n k C o n t r o l s$ , instead, refer to the bank-specific financials which are the Debt on Equity, Loans to Deposits, Capital Adequacy and ROE. In conclusion, the explanatory factors referred to the $C o u n t r y V a r i a b l e s$ are the governmental environment expenditures and environmental taxes.

Analysis and Results

Table 3 reports the fixed-panel results regarding the impact of board characteristics on the environmental performance of the large sample of banks analysed. First, the estimated coefficients for the board independence, board gender diversity, CSR sustainability committee and CEO duality are positively related to the environmental performance pillar at the 1% significance level, consistent with Hypotheses 2, 3, 4 and 6. Similarly, Debt on Equity is positively associated with the Environmental pillar at the 10% significance level. To reinforce our findings, we challenge our fixed panel econometric model including additional variables. We use the three sub-categories of the Environmental performance pillar as dependent variables. Specifically, Table 4 shows the scores of the Emission, Environmental Innovation and Resource Use sub-pillars.

Table 3.

Environmental Pillar.

	Environmental Pillar
Board size	−0.144 (0.196)
Independent board	−0.073 (0.044)^*
Sustainability committee	6.176 (1.906)^***
Board gender diversity	0.138 (0.050)^***
Board-specific skills	−0.030 (0.023)
CEO duality	−3.374 (1.226)^***
Debt on equity	−1.518 (0.830)^*
Loans to deposits	−4.589 (3.370)
Capital adequacy	0.000 (0.000)
Return on equity	−3.982 (5.670)
Environmental taxes	−0.025 (1.977)
Government expenses	−2.550 (10.592)
Cons	100.151 (240.713)
Time dummies	Yes
R ²	0.60
N	1,153

Notes: Fixed effects. Estimation results. Standard errors are shown below the coefficient estimates. For the definition of the variables, see Appendix A.

^*p < 0.1; ^**p < .05; ^***p < .01.

Table 4.

Emission Score, Environmental Innovation Score and Resource Use Score.

	Emission Score	Environmental Innovation Score	Resource Use Score
Board size	0.539	0.258	0.127
	(0.220)^**	(0.252)	(0.207)
Independent board	−0.116	−0.050	−0.055
	(0.049)^**	(0.056)	(0.046)
Sustainability committee	7.561	5.140	10.514
	(2.134)^***	(2.447)^**	(2.010)^***
Board gender diversity	0.177	0.187	0.097
	(0.056)^***	(0.065)^***	(0.053)^*
Board specific skills	0.050	−0.012	−0.024
	(0.025)^**	(0.029)	(0.024)
CEO duality	−1.140	−4.502	−2.033
	(1.373)	(1.574)^***	(1.293)
Debt on equity	−2.235	−0.226	−1.042
	(0.930)^**	(1.066)	(0.876)
Loans to deposits	6.195	−6.380	0.378
	(3.774)	(4.327)	(3.554)
Capital adequacy	0.000	−0.000	0.000
	(0.000)	(0.000)	(0.000)
Return on equity	27.210	1.877	19.091
	(6.350)^***	(7.281)	(5.980)^***
Environmental taxes	−4.316	−1.319	−8.268
	(2.214)^*	(2.539)	(2.086)^***
Government expenses	26.137	−0.753	8.623
	(11.861)^**	(13.601)	(11.172)
Cons	−581.028	48.032	−170.950
	(269.574)^**	(309.117)	(253.907)
Time dummies	Yes	Yes	Yes
R ²	0.26	0.13	0.25
N	1,153	1,153	1,153

Notes: Fixed effects. Estimation results. Endogenous variable, suitably instrumented. Standard errors are shown below the coefficient estimates. For the definition of the variables, see Appendix A.

^*p < .1; ^**p < .05; ^***p < .01.

These findings show that banks with a greater share of female directors on boards and where there is a CSR sustainability committee exhibit superior environmental performance in terms of emission reduction, environmental innovation and correct use of resources, thus supporting Hypotheses 3 and 4.

Robustness Checks

In recent times, dynamic models for panel data have grown a lot, also because of the expansion of the time dimension of the data.

To reinforce our findings and capture the impact of board characteristics on the environmental performance of banks, we use the GMM-system version of the Arellano-Bond estimator.

The basic panel data models such as ordinary least squares (OLS), random effects (RE) and fixed effects (FE) estimators could lead to inefficient and inconsistent estimators in the presence of endogeneity problems, which are quite possible in the context of corporate finance. Indeed, the estimation procedure based on GMM guarantees the assumptions of sequential exogeneity, overcoming all the problems of omitted variables, measurement errors and simultaneity. In analytical terms, the model is structured as follows:

Y_{t} = ρ Y_{t - 1} + X_{t} β + ε_{t}

(2)

where $Y_{t}$ represents the Environmental pillar as a proxy of the environmental performance, which is an $N \times 1$ N ×1 vector. $X_{t}$ is an $N \times K$ matrix and represents the list of covariates, meanwhile $β$ is the $K \times 1$ vector of the marginal effects. The vector of the error terms is represented by $ε_{t}$ . Instead, the variable $ρ$ denotes the effect of the autoregressive factor that takes into account the time inertia in the dependent variable.

In the context of dynamic panel data models, endogeneity may arise through two channels, potentially yielding inconsistent and biased estimates.

First, the existence of the lagged dependent variable ( $Y_{t - 1}$ ) on the right-hand side of the equation induces a correlation between the covariates and the error term. When the coefficient of the delayed dependent variable is of direct interest, a dynamic specification of the analysed process can be fundamental to obtain consistent estimates of the other parameters. The omission of this explanatory variable, when it is significant, can give rise to distorted estimates of the other parameters. This type of endogeneity may be addressed by instrumenting $Y_{t - 1}$ with its deeper lags. Moreover, the lagged values of the dependent variable could also be correlated with the individual specific fixed effects which are incorporated in the error term vector, creating the so-called Nickell bias (Nickell, 1981).

Second, the endogeneity may arise from the columns of the X matrix. In presence of endogenous regressors (other than the lagged values of the dependent variable), it is also necessary to instrument them with their lags. To address the problem of endogeneity, Arellano and Bover (1995), Blundell and Bond (1998) developed the procedure of the system GMM-SYS estimator, which generates unbiased and consistent estimates. The idea behind the GMM-SYS estimator is to estimate a system of equations both in first differences and in the levels, where the instruments used in the level equations are the first lagged differences of the series. In addition to that, the two-step GMM-SYS approach is used, since it prevents unnecessary loss of observation and, according to Roodman (2009), is asymptotically more efficient than the one-step estimator.

As a rule, GMM-SYS estimators are designed for situations with few periods and many individual units (small T, large N panels), assuming a linear relationship between the covariates and the dependent variable and a dynamic structure of the dependent variable, so that it depends on its past realizations. Individual fixed effects, heteroskedasticity and autocorrelation are present within individual units’ errors, but not across them.

To check the validity of the GMM-SYS model, several tests need to be verified. The Sargan-Hansen test validates the choice of the instrumental variables employed, ensuring that moment conditions are met. Rejecting the null hypothesis implies that the instrumental set is inappropriate, due to overidentification. Moreover, no serial correlation of the second-order error terms should also be observed (AR(2)).

In summary, the GMM-SYS model offers suitable and adequate estimators in our research because of its treatment of both endogeneity and heterogeneity.

Discussion and Policy Implications

GMM results (Tables 5 and 6) confirmed our initial Hypotheses 3 and 4, both at overall environmental pillar and sub-pillar levels, reinforcing the findings obtained from the previous econometric fixed-effect panel model. What is found is that the percentage of women on the board plays an important role in the environmental performance of banks, which a p value significant at 1%. The inclusion of women on boards of directors then enhances environmental performance. In addition to that, we also find robust empirical results regarding the CSR sustainability committee, significant at 1%, showing that the presence of an internal board committee with advisory and propositional functions on sustainability issues has a significant positive impact on banks’ environmental performance. We show that these results are consistent at the level of environmental sub-pillars, that is, emission, environmental innovation and resource use scores. The outcomes obtained indicate several relevant implications. Nowadays banks are facing the issue of climate change, which affects their expectations (Buranatrakul & Swierczek, 2018). The world is changing fast, and consumers are more aware of climate change and more sensible of the impact of green practices. In this context, banks play a crucial role in fighting climate change and supporting climate-conscious lifestyles among their clients (Ahuja, 2015).

Table 5.

Environmental Pillar.

	Environmental Pillar
Lagged I dependant variable	0.244
	(0.075)^*
Board size	−0.088
	(0.816)
Independent board	−0.059
	(0.577)
Sustainability committee	22.251
	(0.001)^***
Board gender diversity	0.312
	(0.008)^***
Board-specific skills	−0.076
	(0.330)
CEO duality	3.840
	(0.071)^*
Debt on equity	3.082
	(0.586)
Loans to deposits	−12.410
	(0.724)
Capital adequacy	8.410
	(0.582)
Return on equity	−328.848
	(0.000)^***
Environmental taxes	−2.257
	(0.631)
Government expenses	4.124
	(0.167)
Cons	−48.727
	(0.529)
Time dummies	YES
Sargan test	10.41
	(0.405)
Hansen test	6.05
	(0.772)
AR(1)	2.14
	(0.032)^**
AR(2)	−0.585
	(0.449)
AR(3)	−1.08
	(0.278)
N	869

Notes: GMM-SYS two-step estimation results. Endogenous variable, suitably instrumented. Standard errors are shown below the coefficient estimates. For the definition of the variables, see Appendix A.

^*p < .1; ^**p < .05; ^***p < .01.

Table 6.

Emission Score, Environmental Innovation Score and Resource Use Score.

	Emission Score	Environmental Innovation Score	Resource Use Score
Lagged I dependant variable	0.465	0.932	0.350
	(0.035)^**	(0.000)^***	(0.051)^*
Board size	1.711	0.131	1.396
	(0.025)^**	(0.678)	(0.011)^*
Independent board	0.203	0.008	0.165
	(0.038)^**	(0.879)	( 0.053)^*
Sustainability committee	50.630	9.526	52.221
	(0.020)^**	( 0.074)^*	(0.000)^***
Board gender diversity	0.305	0.119	0.268
	(0.048)^**	(0.059)^*	(0.053)^*
Board-specific skills	0.266	0.034	0.249
	( 0.013)^**	(0.525)	(0.000)^***
CEO duality	−2.158	0.590	−0.788
	(0.355)	(0.753)	(0.714)
Debt on equity	−0.095	−5.159	0.364
	(0.986)	(0.377)	(0.930)
Loans to deposits	−39.375	0.104	−42.174
	(0.200)	(0.997)	(0.167)
Capital adequacy	−0.000	−0.000	−0.000
	(0.053)^*	(0.584)	(0.034)^**
Return on equity	18.935	28.367	−52.957
	(0.656)	(0.400)	(0.282)
Environmental taxes	7.858	6.145	5.707
	(0.112)	(0.191)	(0.183)
Gov. expenses	4.004	1.886	1.472
	(0.224)	(0.405)	(0.649)
Cons	−91.062	−54.470	−19.820
	(0.222)	(0.424)	(0.819)
Time dummies	YES	YES	YES
Sargan test	14.58	6.94	15.67
	(0.103)	(0.225)	(0.110)
Hansen test	4.90	5.94	6.47
	(0.843)	(0.312)	(0.775)
AR(1)	−2.80	−3.16	−2.90
	(0.005)	(0.002)	( 0.004)
AR(2)	−1.21	−0.85	−0.17
	(0.226)	(0.398)	(0.865)
AR(3)	−1.30	−0.92	−1.50
	(0.193)	(0.360)	( 0.133)
N	1,099	1,099	1,099

Notes: GMM-SYS two-step estimation results. Endogenous variable, suitably instrumented. Standard errors are shown below the coefficient estimates. For the definition of the variables, see Appendix A.

^*p < .1; ^**p < .05; ^***p < 0.01.

Promoting sustainable consumption and increasing environmental performance constitute the best way in which banks could future-proof themselves (Campiglio, 2016). Adopting sustainable practices, indeed, will in turn indirectly affect banks themselves, reducing their emissions, increasing green technology, and diminishing the exploitation of natural resources (Gangi et al., 2019).

Therefore, by addressing clients’ sustainability needs, financial institutions are responding not only to their current demands but also to those of the future (Zimmermann, 2019). To this end, alignment between organizational culture and strategic orientation within top management is important, as the board of directors is responsible to shareholders, depositors and regulators (Ahmed et al., 2021).

On this topic, the Basel Committee on Banking Supervision claimed the necessity to investigate, comprehend and improve good corporate governance practices in banks, not only to ensure the resilience of the banking system in presence of new risks (BCBS, 2015) but also to avoid those weaknesses in the system of governance that induce banks to financial crises (Hashagen et al., 2009).

Considering our findings, embedding sustainability into all aspects of the bank business is facilitated by the presence of a CSR committee, which in turn enhances environmental performance. The findings are consistent with resource dependency theory too, which states that the existence of board sustainability committees increases the orientation towards sustainability goals, the efficacy of CSR practices and sustainability-related strategies (Hussain et al., 2018; Qaderi et al., 2022).

In addition to that, the Basel Committee states that ‘the board should comprise individuals with a balance of skills, diversity, and expertise, who collectively possess the necessary qualifications commensurate with the size, complexity and risk profile of the bank’ (BCBS, 2015, p. 13).

In the current literature, gender diversity is undoubtedly one of the most widely debated topics of board characteristics, especially regarding environmental issues (Haque, 2017; Haque & Ntim, 2018). According to the stakeholder and resource dependency perspectives, a great percentage of female directors are expected to encourage different perspectives, expertise and knowledge to corporate boards, promoting more diverse visions (Elmagrhi et al., 2018).

Relating to industrial firms, it has been found that female directors influence positively a firm’s environmental innovation (Liao et al., 2019; Moreno-Ureba et al., 2022). The same happens for the firms’ emissions (Nuber & Velte, 2021). Lastly, female directors efficiently manage the firm’s natural resource reporting (Kiliç et al., 2015). In this context, our contribution adds understanding to the current state of knowledge of gender diversity not only at the firm level but also in the banking industry.

This study offers food for thoughts for both scholars and practitioners as well. From a managerial point of view, we provide a broad framework that allows financial institutions to design an efficient and effective board management to maximize their environmental performance. Our findings indeed suggest to financial institutions take into consideration the establishment of an ad hoc committee dealing with environmental practices. In all major financial institutions, appropriate committees are required to recognize, assess, monitor and manage specific and new risks, such as financial climate-related risks, preserving the correct functioning of the bank. In this context, our findings show that a sustainable committee within banks’ governance helps the shift to a low-carbon economy, tackling climate change.

In addition, our findings suggest the inclusion of a greater gender diversity percentage in the composition of bank boards. According to Farag and Mallin (2015), ‘the relationship between bank risk and board diversity may potentially have important implications on stability and confidence in the banking sector’. Appropriate levels of gender diversity standards diminish reputational risk (Bear et al., 2010), maintaining a bank’s credibility on the market and, at the same time, increasing financial performance levels (García-Meca et al., 2015). From an academic point of view, the goal of this study is intended to stimulate the debate of sustainable board characteristics within the structure of banks’ governance and to develop decisions towards CSR-oriented objectives. In sum, there is still room for further investigation of the discussion on board characteristics and environmental practices. Academics are encouraged to explore the role of the board of directors’ characteristics in fostering sustainability orientation, also by adopting alternative qualitative methods to allow a deeper and finer-grained understanding of the corporate governance characteristics and their influence on environmental performance in the banking industry.

Conclusions

Considering that the impact of climate change on the financial system is becoming increasingly important, our article analyses a topic scarcely explored by prior literature, especially regarding the banking industry. We focus on the relationship between the characteristics of banks’ boards (board size, board independence, CSR sustainability committee, board gender diversity, CEO duality and board-specific skills) and environmental performance. Our empirical analysis includes a large sample of financial institutions: 311 banks from the United States, Europe, the UK and Canada over the 2015–2020 period.

By applying the Fixed Effect panel model and the GMM-system version of the Arellano-Bond estimator, we find robust empirical evidence that both the percentage of women on the board of directors and the presence of the CSR sustainability committee play an important role in the environmental performance of banks. These results are confirmed by the three sub-pillars of the Environmental pillar: Emission Score; Environmental Innovation Score and Resource Use Score. Both the percentage of women on the board and the presence of the CSR sustainability committee enhance banks’ footprints in terms of reducing emissions, product innovation and the use of resources.

The findings of our article could bring suggestions and insights for companies, policymakers and supervisory authorities committed to tackling the adverse effects of climate change. Financial institutions engaged in healthy climate practices aimed at transitioning to a low-carbon society should consider the importance of women on their boards and the presence of the CSR sustainability committee with advisory and proactive powers within the board of directors.

This study comes not without limitations. Considering that the literature on the subject focuses on non-financial firms, we do not include other financial institutions other than banks.

In addition, nonetheless, our research includes advanced countries in the sample. The analysis could therefore be extended to other geographical settings, such as Asia, Australia or South America, so to provide more insights related to the role of corporate governance on environmental performance in the banking industry. Finally, we do not consider the business model and strategies of banks.

Appendix A.

Variables Included in the Econometric Analysis.

Variable	Description	Source
Dependent variables
Environmental score	It reflects how well a company uses best management practices to avoid environmental risks and capitalize on environmental opportunities to generate long-term shareholder value.	Refinitiv database
Emissions score	It measures a company’s commitment and effectiveness towards reducing environmental emissions in the production and operational processes.	Refinitiv database
Environmental innovation score	It reflects a company’s capacity to reduce environmental costs and burdens for its customers, thereby creating new market opportunities through new environmental technologies and processes or eco-designed products.	Refinitiv database
Resource use score	It reflects a company’s performance and capacity to reduce the use of materials, energy, or water, and to find more eco-efficient solutions by improving supply chain management.	Refinitiv database
Independent variables
Board size	Number of board members.	Refinitiv database
Board independence	Percentage of independent board members as reported by the company.	Refinitiv database
Sustainability committee	Dummy variable equals 1 if a sustainability committee exists and 0 otherwise.	Refinitiv database
Board gender diversity	Percentage of females on the board.	Refinitiv database
CEO duality	Dummy variable equals 1 if the CEO is also the chairman of the company and 0 otherwise.	Refinitiv database
Board specific skills	Percentage of board members who have industry-specific and/or financial backgrounds.	Refinitiv database
Bank-specific variables—control variables
Debt on equity	Ratio of Total Debt as of the end of the fiscal period to Total Equity for the same period expressed as a percentage.	Refinitiv database
Loans to deposits	It measures a bank’s funding by comparing a bank’s total loans to its total deposits for the same period expressed as a percentage.	Refinitiv database
Capital adequacy	It represents the value of total net capital sources of financing available to a bank or a financial institution, calculated in accordance with Basel accords or local capital risk regulations. Also referred to as total regulatory capital.	Refinitiv database
Return on equity	It measures the ability of a company to generate earnings from its stockholders’ investments in the company.	Refinitiv database
Country variables—control variables
Environmental taxes	A tax whose tax base is a physical unit (or a proxy of it) of something that has a proven, specific, negative impact on the environment.	International Monetary Fund database
Government expenditure on environmental protection	This represents how much money each government spends on environmental protection measures, as a percentage of the country’s GDP.	International Monetary Fund database

Footnotes

Acknowledgement

The authors are grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the article. Usual disclaimers apply.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Francesca Battaglia

References

Ahmed

, Ahmed

, Ismail

A. I.

, Rasool

, & Soomro

M. A.

(2021). Organizational performance in banking sector of Pakistan: Assessing the impacts of strategic orientation and organizational culture. Global Business Review . https://doi.org/10.1177/0972150921104430

Ahuja

(2015). Green banking in India: A review of literature. International Journal for Research in Management and Pharmacy , 4(1), 11–16.

Arellano

, & Bover

(1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics , 68(1), 29–51.

Bank of England. (2021a). Climate change . https://www.bankofengland.co.uk/climate-change

Bank of England. (2021b, June). The Bank of England’s climate-related financial disclosure 2021 . https://www.bankofengland.co.uk/prudential-regulation/publication/2021/june/climate-related-financial-disclosure-2020-21

BCBS. (2015, July). Basel Committee on Banking Supervision, guidelines. Corporate governance principles for banks . https://www.bis.org/bcbs/publ/d328.pdf

Bear

, Rahman

, & Post

(2010). The impact of board diversity and gender composition on corporate social responsibility and firm reputation. Journal of Business Ethics , 97(2), 207–221.

Beji

, Yousfi

, Loukil

, & Omri

(2021). Board diversity and corporate social responsibility: Empirical evidence from France. Journal of Business Ethics , 173, 133–155.

Ben-Amar

, Chang

, & McIlkenny

(2017). Board gender diversity and corporate response to sustainability initiatives: Evidence from the Carbon Disclosure Project. Journal of Business Ethics , 142, 369–383.

10.

Birindelli

, Iannuzzi

A. P.

, & Savioli

(2019). The impact of women leaders on environmental performance: Evidence on gender diversity in banks. Corporate Social Responsibility and Environmental Management , 26(6), 1485–1499.

11.

Blundell

, & Bond

(1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics , 87(1), 115–143.

12.

Bouslah

, Kryzanowski

, & M’Zali

(2013). The impact of the dimensions of social performance on firm risk. Journal of Banking and Finance , 37(4), 1258–1273.

13.

Brainard

(2021). Building climate scenario analysis on the foundations of economic research. Speech At the 2021 Federal Reserve Stress Testing Research Conference, Federal Reserve Bank of Boston, Boston, Massachusetts . https://www.federalreserve.gov/newsevents/speech/brainard20211007a.html

14.

Brunetti

, Dennis

, Gates

, Hancock

, Ignell

, Kiser

E. K.

, Kotta

, Kovner

, Rosen

R. J.

, & Tabor

N. K.

(2021 March 19). Climate change and financial stability. In FEDS Notes . Board of Governors of the Federal Reserve System. https://www.federalreserve.gov/econres/notes/feds-notes/climate-change-and-financial-stability-20210319.html

15.

Buranatrakul

, & Swierczek

F. W.

(2018). Climate change strategic actions in the international banking industry. Global Business Review , 19(1), 32–47.

16.

Campiglio

(2016). Beyond carbon pricing: The role of banking and monetary policy in financing the transition to a low-carbon economy. Ecological Economics , 121, 220–230.

17.

Cappa

, Collevecchio

, Oriani

, & Peruffo

(2022). Banks responding to the digital surge through Open Innovation: Stock market performance effects of M&As with fintech firms. Journal of Economics and Business , 121, 106079.

18.

Cariola

, Fasano

, La Rocca

, & Skatova

(2020). Environmental sustainability policies and the value of debt in EU SMEs: Empirical evidence from the energy sector. Journal of Cleaner Production , 275, 123133.

19.

Carroll

A. B.

(2021). Corporate social responsibility: Perspectives on the CSR construct’s development and future. Business & Society , 60(6), 1258–1278.

20.

D’Angelo

, Cappa

, & Peruffo

(2022). Green manufacturing for sustainable development: The positive effects of green activities, green investments, and non-green products on economic performance. Business Strategy and the Environment , 1–14.

21.

EBA (2021). EBA report on management and supervision of ESG risks for credit institutions and investment firms, EBA/REP/2021/18 . https://www.eba.europa.eu/sites/default/documents/files/document_library/Publications/Reports/2021/1015656/EBA%20Report%20on%20ESG%20risks%20management%20and%20supervision.pdf.

22.

Elmagrhi

M. H.

, Ntim

C. G.

, Elamer

A. A.

, & Zhang

(2018). A study of environmental policies and regulations, governance structures, and environmental performance: The role of female directors. Business Strategy and the Environment , 28(1), 206–220.

23.

European Central Bank. (2021, 8 July). ECB presents action plan to include climate change considerations in its monetary policy strategy, press release . https://www.ecb.europa.eu/press/pr/date/2021/html/ecb.pr210708_1~f104919225.en.html

24.

Farag

, & Mallin

(2015). Corporate governance and diversity in Chinese banks. In Cumming

, Firth

, Hou

, & Lee

, (Eds.), Sustainable entrepreneurship in China . Palgrave Macmillan.

25.

Fasano

, & Cappa

(2022). How do banking fintech services affect SME debt? Journal of Economics and Business , 121, 106070.

26.

Friedman

(1970). A Friedman doctrine: The social responsibility of business is to increase its profits. The New York Times Magazine , 13, 32–33.

27.

Gangi

, Meles

, D’Angelo

, & Daniele

L. M.

(2019). Sustainable development and corporate governance in the financial system: Are environmentally friendly banks less risky? Corporate Social Responsibility and Environmental Management , 26(3), 529–547.

28.

García Martín

C. J.

, & Herrero

(2020). Do board characteristics affect environmental performance? A study of EU firms. Corporate Social Responsibility and Environmental Management , 27(1), 74–94.

29.

García-Meca

, García-Sánchez

I. M.

, & Martínez-Ferrero

(2015). Board diversity and its effects on bank performance: An international analysis. Journal of Banking & Finance , 53, 202–214.

30.

García-Meca

, Uribe-Bohórquez

M. V.

, & Cuadrado-Ballesteros

(2018). Culture, board composition and corporate social reporting in the banking sector. Administrative Sciences , 8(3), 41.

31.

Gillan

S. L.

, Koch

, & Starks

L. T.

(2021). Firms and social responsibility: A review of ESG and CSR research in corporate finance. Journal of Corporate Finance , 66, 101889.

32.

Greene

(2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics , 126, 269–303.

33.

Haque

(2017). The effects of board characteristics and sustainable compensation policy on carbon performance of UK firms. British Accounting Review , 49(3), 347–364.

34.

Haque

, & Ntim

C. G.

(2018). Environmental policy, sustainable development, governance mechanisms and environmental performance. Business Strategy and the Environment , 27(3), 415–435.

35.

Hashagen

, Harman

, Conover

, & Sharma

(2009). Risk management in banking: Beyond the credit crisis. The Journal of Structured Finance , 15(1), 92–103.

36.

Hillman

A. J.

, & Dalziel

(2003). Boards of directors and firm performance: Integrating agency and resource dependence perspectives. Academy of Management Review , 28(3), 383–396.

37.

Hussain

, Rigoni

, & Orij

R. P.

(2018). Corporate governance and sustainability performance: Analysis of triple bottom line performance. Journal of Business Ethics , 149(2), 411–432.

38.

Kapoor

, & Sandhu

H. S.

(2010). Does it pay to be socially responsible? An empirical examination of impact of corporate social responsibility on financial performance. Global Business Review , 11(2), 185–208.

39.

Kiliç

, Kuzey

, & Uyar

(2015). The impact of ownership and board structure on Corporate Social Responsibility (CSR) reporting in the Turkish banking industry. Corporate Governance , 15(3), 357–374.

40.

Kraus

, Rehman

S. U.

, & García

F. J. S.

(2020). Corporate social responsibility and environmental performance: The mediating role of environmental strategy and green innovation. Technological Forecasting and Social Change , 160, 120262.

41.

Kyaw

, Treepongkaruna

, & Jiraporn

(2022). Board gender diversity and environmental emissions. Business Strategy and the Environment , 31, 2871–2881.

42.

La Rocca

, Fasano

, Cappa

, & Neha

(2022). The relationship between political connections and firm performance: An empirical analysis in Europe. Finance Research Letters , 49, 103157.

43.

Liao

, Luo

, & Tang

(2015). Gender diversity, board independence, environmental committee and greenhouse gas disclosure. The British Accounting Review , 47, 409–424.

44.

Liao

, Zhang

, & Wang

(2019). Do female directors influence firms’ environmental innovation? The moderating role of ownership type. Corporate Social Responsibility and Environmental Management , 26(1), 257–263.

45.

Liu

(2018). Are women greener? Corporate gender diversity and environmental violations. Journal of Corporate Finance , 52, 118–142.

46.

, & Herremans

I. M.

(2019). Board gender diversity and environmental performance: An industries perspective. Business Strategy and the Environment , 28, 1449–1464.

47.

Morea

, Fortunati

, Cappa

, & Oriani

(2022). Corporate social responsibility as a catalyst of circular economy? A case study perspective in Agri-food. Journal of Knowledge Management (ahead-of-print on 8 November 2022). https://doi.org/10.1108/JKM-06-2022-0451

48.

Moreno-Ureba

, Bravo-Urquiza

, & Reguera-Alvarado

(2022). An analysis of the influence of female directors on environmental innovation: When are women greener? Journal of Cleaner Production , 374, 133871.

49.

Moussa

F. B.

(2019). The influence of internal corporate governance on bank credit risk: An empirical analysis for Tunisia. Global Business Review , 20(3), 640–667.

50.

Nadeem

, Bahadar

, Gull

A. A.

, & Iqbal

(2020). Are women eco-friendly? Board gender diversity and environmental innovation. Business Strategy and the Environment , 29(8), 3146–3161.

51.

Neville

, Byron

, Post

, & Ward

(2019). Board independence and corporate misconduct: A cross-national meta-analysis. Journal of Management , 45, 2538–2569.

52.

Nickell

(1981). Biases in dynamic models with fixed effects. Econometrica: Journal of the Econometric Society , 49(6), 1417–1426.

53.

Nuber

, & Velte

(2021). Board gender diversity and carbon emissions: European evidence on curvilinear relationships and critical mass. Business Strategy and the Environment , 30(4), 1958–1992.

54.

Orazalin

(2020). Do board sustainability committees contribute to corporate environmental and social performance? The mediating role of corporate social responsibility strategy. Business Strategy and the Environment , 29(1), 140–153.

55.

Orazalin

, & Mahmood

(2021). Toward sustainable development: Board characteristics, country governance quality, and environmental performance. Business Strategy and the Environment , 30(8), 3569–3588.

56.

Ortas

, Alvarez

, & Zubeltzu

(2017). Firms’ board independence and corporate social performance: A meta-analysis. Sustainability , 9(6), 1006.

57.

Qaderi

S. A.

, Ghaleb

B. A. A.

, Hashed

A. A.

, Chandren

, & Abdullah

(2022). Board characteristics and integrated reporting strategy: Does Sustainability Committee matter? Sustainability , 14(10), 6092.

58.

Refinitiv. (2022, May). Environmental, social and governance scores from Refinitiv. https://www.refinitiv.com/content/dam/marketing/en_us/documents/methodology/refinitiv-esg-scores-methodology.pdf

59.

Reguera-Alvarado

, de Fuentes

, & Laffarga

(2017). Does board gender diversity influence financial performance? Evidence from Spain. Journal of Business Ethics , 141, 337–350.

60.

Ricart

J. E.

, Rodríguez

M. A.

, & Sánchez

(2005). Sustainability in the boardroom: An empirical examination of Dow Jones sustainability world index leaders. Corporate Governance: The International Journal of Business in Society , 5(3), 24–41.

61.

Roodman

(2009). How to do xtabond2: An introduction to difference and system GMM in Stata. The Stata Journal , 9(1), 86–136.

62.

Tan

S. H.

, Habibullah

M. S.

, Tan

S. K.

, & Choon

S. W.

(2017). The impact of the dimensions of environmental performance on firm performance in travel and tourism industry. Journal of Environmental Management , 203, 603–611.

63.

Walls

J. L.

, Berrone

, & Phan

P. H.

(2012). Corporate governance and environmental performance: Is there really a link? Strategic Management Journal , 33, 885–913.

64.

Zimmermann

(2019). Same but different: How and why banks approach sustainability. Sustainability , 11(8), 2267.