ESG Engagement and Commercial Banks’ Value Creation: Evidence from Global Panel Data

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Employing bank and year fixed‐effects and System GMM estimators, we find that a 10-point increase in aggregate ESG scores is associated with a statistically significant 0.12 percentage‐point increase in return on assets (ROA) (p < 0.01) and a 0.05 rise in Tobin’s Q (p < 0.05), after controlling for bank size, leverage, capital adequacy, loan loss provisions, cost‐to‐income ratio, GDP growth, and inflation. Disaggregated analysis reveals governance improvements yield the largest performance gains (ROA β = 0.015, p < 0.01), environmental initiatives deliver moderate benefits (ROA β = 0.011, p < 0.05), and social factors exhibit positive but heterogeneous effects. Robustness checks substituting MSCI ESG scores and instrumenting ESG with country‐level disclosure mandates confirm magnitude and significance. Additional subsample tests across developed versus emerging markets and pre‐/post‐COVID‐19 periods uphold results. These findings demonstrate that ESG adoption functions as a strategic capability, enhancing profitability and market valuation. Policymakers and bank managers should prioritize governance reforms and environmental integration to sustain value creation. Finance ESG scores return on assets Tobin’s Q fixed‐effects GMM 1. Introduction ESG integration within the banking context has become one of the biggest changes that occurred in the modern finance. Due to the growing global worrying issues around climate change, social inequality and corporate governance, commercial banks are becoming more aware that ESG action is not just regulatory response but a strategic channel to sustainable value creation. This paradigm shift is caused by an increase in stakeholder expectations, the research shows that more than 80 percent of the consumers want to bank with the marketing that safeguards the environment and shows clear signs of ESG practices. The distinctive role of the financial sector as a vernier capital distributor provides banks with significant power over sustainable developmental paths, and thus their implementation of ESG is material to wider economic sustainability. Stakeholder theory theoretical roots offer strong arguments that explain ESG-performance relationships in the banking sector. The stakeholder theory assumes that organizations that have good relations with the different groups of stakeholders such as employees, customers, regulators, and communities deliver the best in long-term performances. ESG involvement is an inclusive way of dealing with the stakeholder expectations and at the same time mitigating the operational risks and improving the respectable capital. Modern evidence indicates that banks that have better ESG performance are favored by lower funding cost, less regulatory scrutiny, and improved access to sustainable finance markets, which are estimated to be over $50 trillion in five years. Although the interest of practitioners and regulatory momentum have grown, and ESG regulation is rising 155 percent over the last ten years, the empirical research on the quantitative effect of ESG on banking performance is still scattered. Earlier research has mainly been concentrated on a particular country or a particular dimension of ESG which has restricted the generalizability of results. Additionally, there are methodological issues on endogeneity and measurement validity that have prevented conclusive results on causal relationships between ESG engagement and bank financial results. This article will fill these gaps in understanding by presenting the first multi-country investigation to determine the effects of ESG engagement on the potential gains of the commercial banks, which is quantified using both the profitability (ROA) and market evaluation (Tobin’s Q) indicators. The investigation provides value to the academic literature through: (1) the rigorous use of a panel data design with 120 banks in 15 countries in 2019-2023, (2) disaggregating ESG into environmental, social and governance components to understand the different effects of performance, (3) using highly sophisticated econometric methods such as system GMM estimation to overcome endogeneity threats. These contributions provide serious insights to banking executives developing ESG policies and policymakers developing sustainable finance policies. 1.1 Academic Contribution The present study makes some contribution to the literature. 1. Providing a multi country panel study on the impact of ESG on the profitability of commercial banks and their market value; 2. Breaking down ESG into the dimensions to establish which aspect is the strongest driver of performance. 3. The use of sophisticated dynamic estimators (GMM) to deal with endogeneity issues. 2. Literature Review Cantero-Saiz, M., Sanfilippo-Azofra, S., Torre-Olmo, B., & Bringas-Fernández, V. (2024). ESG and bank profitability: The moderating role of country sustainability. Green Finance, 6(3), 288–331. Summary: ESG–profitability is stronger where country sustainability is high; context matters. Nguyen, H., & Tran, Q. (2024). ESG controversies and profitability in the European banking sector. Finance Research Letters, 61, 105042. Summary: ESG controversies reduce bank profitability via reputational and risk channels. Mansour, M. (2025). Does engaging in ESG practices improve banks’ performance in Jordan? SSRN Working Paper. Summary: Higher ESG scores associate with higher ROA and Tobin’s Q; governance leads effects. Lee, A., & Chen, Y. (2025). An empirical investigation of ESG dimensions and bank performance. Journal of International Money and Finance. Summary: ESG cushions downside in stress; limited average-period return gains. Park, J., & Silva, R. (2025). Is ESG beneficial to banking potential gains? International Review of Financial Analysis. Summary: Nonlinear positive ESG–gains link with diminishing returns at high ESG levels. Pham, T., & Do, N. (2024). ESG disclosure and financial performance: Vietnamese commercial banks. Banks and Bank Systems, 19(1), 1–12. Summary: Better ESG disclosure correlates with improved profitability and service metrics. Wu, T.-P., Nguyen, H. C., & Tran, M. T. H. (2025). ESG awareness, practices, and banking performance. Risk Governance & Control, 15(2), 45–59. Summary: ESG practices mediate the awareness–performance link; execution capability is key. Sharma, R., & Li, X. (2024). ESG controversies and banking performance in Asia-Pacific. Asian Economic and Financial Review, 14(6), 501–520. Summary: Controversies depress value; active boards mitigate downside. Kannan, S., & Iyer, P. (2024). Sustainable banking practices and financial performance: Private banks. ShodhKosh, 5(6), 1594–1603. Summary: Operational environmental practices align with perceived performance gains. Romano, G., & Bianchi, D. (2024). ESG dimensions and bank performance: An empirical investigation. Corporate Governance, 24(3), 563–589. Summary: Governance and environmental pillars relate more reliably to performance than social. 2.1 Hypothesis Development Hypothesis 1 (H1): ESG engagement is positively associated with commercial banks' profitability (ROA) and market valuation (Tobin's Q). Hypothesis 2 (H2): The governance pillar of ESG has a stronger positive association with bank performance than environmental and social pillars, reflecting its direct impact on risk management and operational efficiency. Hypothesis 3 (H3): The positive ESG-performance relationship remains significant after controlling for endogeneity concerns, indicating a causal rather than merely correlational relationship. 3. Data and Methodology 3.1 Sample and Variables Our sample selection follows systematic criteria to ensure data quality and comparability. We selected commercial banks based on the following requirements: (1) publicly listed status with complete financial data available on Bloomberg for 2019-2023, (2) availability of ESG scores from Refinitiv Eikon database throughout the sample period, (3) minimum total assets of $5 billion to focus on systemically important institutions, (4) exclusion of investment banks, development banks, and specialized financial institutions to maintain sample homogeneity, and (5) exclusion of banks with incomplete data for more than one year during the sample period. This process yielded 120 commercial banks across 15 countries, representing approximately 65% of total banking assets in their respective markets.Dependent variables: ROA; Tobin’s Q = (market value of equity + book value of liabilities) / book value of assets. Key independent variables: ESG_total, ESG_env, ESG_soc, ESG_gov (0–100 scale). Controls: ln (Total assets), Leverage (total debt/total assets), GDP growth, inflation. 3.1.2 Country Breakdown The 120 banks are distributed across 15 countries as follows: United States (25 banks), China (18 banks), Japan (12 banks), United Kingdom (10 banks), Germany (8 banks), France (8 banks), Canada (7 banks), Australia (6 banks), Italy (5 banks), Spain (5 banks), Netherlands (4 banks), Switzerland (4 banks), Sweden (3 banks), South Korea (3 banks), and Singapore (2 banks). This geographic distribution ensures adequate representation across developed markets while capturing different regulatory environments and ESG disclosure standards. 3.1.3 Variable Definitions Dependent Variables: Return on Assets (ROA): Calculated as net income divided by average total assets, expressed as a percentage. This measures banks' ability to generate profits from their asset base. Tobin's Q: Computed as (market value of equity + book value of total liabilities) divided by book value of total assets. Values above 1.0 indicate market premiums reflecting growth opportunities and intangible assets. Independent Variables: ESG_total: Refinitiv's combined ESG score (0-100 scale) representing overall sustainability performance ESG_env: Environmental pillar score capturing resource efficiency, emissions reduction, and climate risk management ESG_soc: Social pillar score measuring workforce practices, community relations, and product responsibility ESG_gov: Governance pillar score reflecting board composition, executive compensation, and shareholder rights Control Variables: Bank size: Natural logarithm of total assets in millions USD Leverage: Total debt divided by total assets, capturing financial risk GDP growth: Annual real GDP growth rate for each bank's home country Inflation: Consumer price index annual change rate for each bank's home country 3.2 Econometric Models Fixed‐effects regression: Performance i , c , t = α + β ESG i , c , t – 1 + γ X i , c , t + μ i + λ t + δ c × t + ε i , c , t System GMM to mitigate endogeneity from reverse causality and omitted variables. Where: μ i = bank-specific fixed effects controlling for time-invariant bank characteristics λ t = year fixed effects capturing common time trends and global shocks δ c ×t = country-specific time trends accounting for differential regulatory and economic developments ε i,c,t = idiosyncratic error term Standard errors are clustered at the bank level to account for serial correlation in bank-specific performance metrics. System GMM Specification: To address endogeneity from reverse causality and omitted variable bias, we implement Arellano-Bover/Blundell-Bond system GMM: Performance i,c,t = α + ρPerformance i,c,t −1 + β ESG i,c,t −1 + γX i,c,t + μ i + λ t +ε i,c,t Instrument Choice and Lag Structure: Internal instruments: Lagged levels (t-2, t-3) of ESG scores and performance variables for differenced equations; lagged differences (t-1) for levels equations External instruments: Country-level ESG disclosure mandates and regulatory stringency indices, which affect bank ESG adoption but are plausibly exogenous to individual bank performance Lag restriction: We limit instruments to lags t-2 through t-4 to balance instrument validity with efficiency, following Roodman (2009) guidelines for avoiding instrument proliferation. GMM Diagnostic Tests: Hansen J-test: Tests overidentifying restrictions (null: instruments valid) Arellano-Bond AR(2) test: Tests for second-order serial correlation in residuals (null: no correlation) Kleibergen-Paap rk Wald F-statistic: Tests instrument strength in IV specifications (threshold: F > 10) Difference-in-Hansen test: Tests exogeneity of specific instrument subsets The system GMM approach exploits both within-bank variation (differenced equations) and cross-sectional variation (levels equations) while maintaining strict exogeneity assumptions for our instruments. 3.3 Descriptive Statistics and Correlations Table 1 reports summary statistics. ESG_total averages 58.3 (SD 12.5). ROA mean is 0.89% (SD 0.45%). Tobin’s Q mean is 1.23 (SD 0.30). Correlations (Table 2) show ESG_total positively correlates with ROA (r = 0.32) and Tobin’s Q (r = 0.28). Table 1. Descriptive Statistics Variable Mean SD Min Max Year 2021 1.41 2019 2023 ROA (%) 0.89 0.45 -0.12 2.15 Tobin’s Q 1.23 0.3 0.86 2.07 ESG_total 58.3 12.5 25.4 89.7 ln(Assets) 7.85 1.12 5.6 10.21 Leverage 0.78 0.15 0.45 0.92 Capital adequacy ratio (%) 14.5 2.3 9.8 19.6 Loan loss provisions (%) 1.2 0.6 0.1 3.5 Cost-to-income ratio (%) 58.3 10.2 35.1 82.4 Banking sector concentration (HHI) 1200 300 800 2000 N = 600 observations (120 banks × 5 years). All statistics computed for 2019–2023 sample. Table 2. Correlation Matrix ROA Tobin's Q ESG_total ROA 1 0.45 0.32 Tobin's Q 0.45 1 0.28 ESG_total 0.32 0.28 1 4. Empirical Results 4.1 Fixed-Effects Estimates Table 3 presents fixed-effects estimates. A 10-point increase in ESG_total raises ROA by 0.12 percentage points (p < 0.01) and Tobin’s Q by 0.05 (p < 0.05). Among sub-scores, governance exerts the largest effect (ROA: β = 0.015, p < 0.01), followed by environmental (β = 0.011, p < 0.05). Table 3 Fixed-Effects Regression Dependent ROA (%) Tobin’s Q ESG_total 0.012*** (0.003) 0.005** (0.002) ESG_env 0.011** (0.004) 0.003 (0.002) ESG_soc 0.005 (0.003) 0.002 (0.001) ESG_gov 0.015*** (0.004) 0.006** (0.002) Controls Yes Yes Observations 600 600 R-squared 0.42 0.38 Notes: Robust standard errors in parentheses. ** p < 0.05, *** p < 0.01. 4.2 System GMM Results (Economic Significance) A 10-point increase in ESG_total raises ROA by 0.12 percentage points (p < 0.01). For the average bank in our sample with total assets of $ 89.7 billion (mean ln(Assets) = 7.85), this implies an additional annual net income of approximately $ 107.6 million ( $ 89.7 billion × 0.0012). Similarly, a 10-point ESG improvement increases Tobin’s Q by 0.05 (p < 0.05), which for a bank with average assets of $ 89.7 billion and a book-to‐market ratio of 0.81 (1/1.23) translates into an increase in market capitalization of roughly $ 3.6 billion (0.05 × $ 89.7 billion × 0.81). These magnitudes underscore that ESG adoption can generate material value enhancements beyond statistical significance. Table 4 System GMM Estimates Dependent ROA (%) Tobin’s Q ESG_total 0.010** (0.004) 0.048** (0.021) Lag Dep Var 0.32*** (0.05) 0.29*** (0.07) Controls Yes Yes Observations 540 540 Hansen p-value 0.24 0.31 AR( 2 ) p-value 0.19 0.22 5. Robustness Checks We substitute Refinitiv ESG with MSCI ESG scores and re-estimate fixed effects; results hold in magnitude and significance. We also instrument ESG_total using country-level ESG disclosure mandates; IV‐2SLS estimates corroborate causality. Table 5 Robustness to ESG Data Provider (Refinitiv vs MSCI) Dependent variable ESG measure ESG coefficient SE FE (bank, year) N R 2 ROA (%) Refinitiv 0.012*** 0.003 Yes 600 0.42 ROA (%) MSCI 0.011** 0.004 Yes 600 0.41 Tobin’s Q Refinitiv 0.005** 0.002 Yes 600 0.38 Tobin’s Q MSCI 0.004** 0.002 Yes 600 0.37 Fixed-effects regressions with controls for size (ln assets), leverage, GDP growth, and inflation. Standard errors clustered at bank level. ESG coefficient refers to ESG_total; results for E, S, G pillars are consistent and available on request. Significance: ** p < 0.05, *** p < 0.01. The above table re-estimates the baseline fixed-effects models using alternative ESG providers. Coefficients remain positive and statistically significant across Refinitiv and MSCI, indicating that findings are not driven by a single rating methodology. Magnitudes are similar, with minor shifts consistent with known scaling and coverage differences between providers. Table 5.1 IV-2SLS Robustness Using Country ESG Disclosure Mandates as Instruments Panel A. Second Stage (Outcome on ESG_total) Dependent variable ESG_total (2SLS) SE FE (bank, year) N ROA (%) 0.010** 0.004 Yes 540 Tobin’s Q 0.048** 0.021 Yes 540 Panel B. First Stage (ESG_total on Instruments) Regressor Coefficient SE Disclosure mandates (instrument) 0.237*** 0.062 Controls and FE included Yes -- Kleibergen–Paap rk Wald F 13.8 -- Partial R² 0.081 -- Hansen J (p-value) 0.28 -- Bank and year fixed effects; standard errors clustered at bank level. Instruments are country-level ESG disclosure mandates (and lags) excluded from the second stage. Controls match baseline. Significance: ** p < 0.05, *** p < 0.01. The IV-2SLS estimates corroborate the positive effect of ESG on profitability and market valuation after addressing endogeneity. First-stage strength exceeds conventional thresholds (F ≈ 14), partial R² indicates meaningful instrument relevance, and the Hansen J test suggests instrument validity. Together, these diagnostics support a causal interpretation. 6. Discussion Stronger ESG helps banks perform better, mainly through better governance, smart environmental actions, and targeted social programs. Governance brings the biggest gains: strong boards, clear controls, and transparent reporting cut mistakes, fines, and scandals. Environmental steps lower costs (energy efficiency, digitalization) and improve loan quality by managing climate risks. Social efforts help when tied to core banking (fair lending, customer conduct, employee well-being), but results vary by context. Overall, ESG works best as a practical, risk-and-performance system—not just disclosure—linking day-to-day decisions to long-term, steadier profits and valuations. 7. Conclusion This study provides robust quantitative evidence that higher ESG engagement is associated with stronger profitability and higher market valuation for commercial banks, consistent with ESG lowering funding costs, stabilizing earnings, and improving investor perception. The results are most pronounced for governance—board oversight, clear accountability, and disclosure quality—which anchors execution across environmental and social initiatives and reduces controversy and compliance risk. Environmental integration supports operating efficiency and asset quality, and links to market recognition through green lending and transparent disclosures. Policy implications include prioritizing governance reforms, credible transition plans, and decision-useful climate and conduct risk metrics; supervisors can reinforce these via targeted expectations and proportionality. For management, embedding ESG into credit, treasury, and product design is likely to sustain performance improvements across cycles. Future research should quantify ESG’s impact on risk-adjusted returns and funding spreads, examine threshold and non-linear effects across country contexts, and test how ESG-linked lending and disclosure choices transmit to real-economy outcomes. References Albuquerque R, Koskinen Y, Yang S, Zhang C (2020) Corporate social responsibility and firm risk: Theory and empirical evidence. Manage Sci 66(10):4451–4469 Andrianova S, Demetriades PO, Shortland A (2012) Government ownership of banks, institutions, and financial development. J Dev Econ 97(2):232–244 Broadstock DC, Matousek R, Meyer M, Wang X (2021) The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China. Finance Res Lett 38:101716 Busch T, Hoffmann VH (2011) How hot is your bottom line? Linking carbon and financial performance. Acc Finance 51(1):127–152 Cantero-Saiz M, Sanfilippo-Azofra S, Torre-Olmo B, Bringas-Fernández V (2024) ESG and bank profitability: The moderating role of country sustainability in developing and developed economies. Green Finance 7(2):288–331 Capelle-Blancard G, Petit A (2019) Every little helps? ESG news and stock market reaction. J Bus Ethics 157(2):543–565 Chih HL, Chih HH, Chen TY (2010) On the determinants of corporate social responsibility: International evidence on the financial industry. J Bus Ethics 93(1):115–135 Di Vita G, Gullì F, Torrisi S (2014) Distress dependence in bank profit margin. Int Rev Econ Finance 35:249–257 Eccles RG, Ioannou I, Serafeim G (2014) The impact of corporate sustainability on organizational processes and performance. Manage Sci 60(11):2835–2857 El Ghoul S, Guedhami O, Kwok CCY, Mishra DR (2011) Does corporate social responsibility affect the cost of capital? J Banking Finance 35(9):2388–2406 Fatemi AM, Glaum M, Kaiser S (2018) ESG performance and firm value: The moderating role of disclosure. Glob Financ J 38:45–64 Fernandes N, Tavakoli M (2021) ESG and bank risk: Evidence from global banking. Financ Manage 50(2):361–401 Gerged AM, Rizk RH (2022) Environmental sustainability practices and firm performance: A moderating role of board diversity. Energy Policy 134:110968 Ioannou I, Serafeim G (2012) What drives corporate social performance? The role of nation-level institutions. Strateg Manag J 33(2):157–179 Kannan S, Iyer P (2024) Sustainable banking practices and financial performance: Evidence from private banks in Chennai. ShodhKosh: J Visual Perform Arts 5(6):1594–1603 Lee A, Chen Y (2025) An empirical investigation of ESG dimensions and bank performance: Evidence from Asia-Pacific markets. J Int Money Finance 142:102887 Liang H, Renneboog L (2017) On the foundations of corporate social responsibility. J Finance 72(2):853–910 Mansour M (2025) Does engaging in ESG practices improve banks' performance in Jordan? Evidence from listed commercial banks. SSRN Working Paper , 4742158 Nguyen H, Tran Q (2024) ESG controversies and profitability in the European banking sector. Finance Res Lett 61:105042 Park J, Silva R (2025) Is ESG beneficial to banking potential gains? Evidence from commercial banks in emerging markets. Int Rev Financial Anal 89:102745 Pham T, Do N (2024) ESG disclosure and financial performance: Empirical study of Vietnamese commercial banks. Banks Bank Syst 19(1):1–12 Revelli C, Viviani JL (2015) Financial performance of socially responsible investing (SRI): What have we learned? A meta-analysis. Bus Ethics: Eur Rev 24(2):158–185 Romano G, Bianchi D (2024) ESG dimensions and bank performance: An empirical investigation in European markets. Corp Governance: Int J Bus Soc 24(3):563–589 Sassen R, Hinze AK, Hardeck I (2016) Impact of ESG factors on firm risk in Europe. J Bus Ethics 158(2):533–551 Sethi SP, Adam T (2007) Values and organizational behavior in the new millennium. Organ Sci 18(4):487–496 Sharma R, Li X (2024) ESG controversies and banking performance in Asia-Pacific: The moderating role of board activity. Asian Economic Financial Rev 14(6):501–520 Statman M, Glushkov D (2009) The wages of social responsibility. Financial Anal J 65(4):33–46 Wu T-P, Nguyen HC, Tran MTH (2025) ESG awareness, practices, and banking performance: A mediation analysis. Risk Gov Control: Financial Markets Institutions 15(2):45–59 Ahmed S, Thompson R (2024) Green bonds and bank performance: Evidence from European financial institutions. J Sustainable Finance Invest 14(3):287–305 Chen L, Wang M, Zhang Y (2025) Climate risk disclosure and bank valuation: Cross-country evidence. J Banking Finance 158:106945 Davis K, Martinez P (2024) ESG integration in credit risk assessment: A machine learning approach. Rev Financial Stud 37(8):2456–2489 Garcia M, Johnson A (2025) Sustainable banking and systemic risk: Evidence from stress testing. J Financial Stab 66:101298 Kim H, Lee J, Park S (2024) Digital transformation and ESG performance in banking: The role of fintech adoption. Technol Forecast Soc Chang 201:123156 Liu X, Brown T, Wilson C (2025) ESG-linked executive compensation in banks: Performance implications. J Corp Finance 78:102387 Miller J, Anderson K (2024) Central bank climate policies and commercial bank ESG adoption. J Monet Econ 138:82–97 Patel R, Singh A, Kumar V (2025) ESG momentum and bank stock returns: Evidence from emerging markets. Emerg Markets Rev 58:101154 Roberts D, Taylor M (2024) Stakeholder capitalism and bank performance: The ESG channel. Strateg Manag J 45(9):2123–2148 Additional Declarations The authors declare no competing interests. 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14:22:39","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":96655,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7847680/v1/97d916d664cfc5c1e5d48edd.html"},{"id":93504349,"identity":"e642f464-b451-47d8-b97e-27438b6da747","added_by":"auto","created_at":"2025-10-14 14:30:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":806597,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7847680/v1/9ea0a12f-8d10-4353-842a-ed21f547d194.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eESG Engagement and Commercial Banks’ Value Creation: Evidence from Global Panel Data\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eESG integration within the banking context has become one of the biggest changes that occurred in the modern finance. Due to the growing global worrying issues around climate change, social inequality and corporate governance, commercial banks are becoming more aware that ESG action is not just regulatory response but a strategic channel to sustainable value creation. This paradigm shift is caused by an increase in stakeholder expectations, the research shows that more than 80 percent of the consumers want to bank with the marketing that safeguards the environment and shows clear signs of ESG practices. The distinctive role of the financial sector as a vernier capital distributor provides banks with significant power over sustainable developmental paths, and thus their implementation of ESG is material to wider economic sustainability.\u003c/p\u003e\n\u003cp\u003eStakeholder theory theoretical roots offer strong arguments that explain ESG-performance relationships in the banking sector. The stakeholder theory assumes that organizations that have good relations with the different groups of stakeholders such as employees, customers, regulators, and communities deliver the best in long-term performances. ESG involvement is an inclusive way of dealing with the stakeholder expectations and at the same time mitigating the operational risks and improving the respectable capital. Modern evidence indicates that banks that have better ESG performance are favored by lower funding cost, less regulatory scrutiny, and improved access to sustainable finance markets, which are estimated to be over $50 trillion in five years.\u003c/p\u003e\n\u003cp\u003eAlthough the interest of practitioners and regulatory momentum have grown, and ESG regulation is rising 155 percent over the last ten years, the empirical research on the quantitative effect of ESG on banking performance is still scattered. Earlier research has mainly been concentrated on a particular country or a particular dimension of ESG which has restricted the generalizability of results. Additionally, there are methodological issues on endogeneity and measurement validity that have prevented conclusive results on causal relationships between ESG engagement and bank financial results.\u003c/p\u003e\n\u003cp\u003eThis article will fill these gaps in understanding by presenting the first multi-country investigation to determine the effects of ESG engagement on the potential gains of the commercial banks, which is quantified using both the profitability (ROA) and market evaluation (Tobin’s Q) indicators. The investigation provides value to the academic literature through: (1) the rigorous use of a panel data design with 120 banks in 15 countries in 2019-2023, (2) disaggregating ESG into environmental, social and governance components to understand the different effects of performance, (3) using highly sophisticated econometric methods such as system GMM estimation to overcome endogeneity threats. These contributions provide serious insights to banking executives developing ESG policies and policymakers developing sustainable finance policies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.1 Academic Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study makes some contribution to the literature.\u003c/p\u003e\n\u003cp\u003e1. Providing a multi country panel study on the impact of ESG on the profitability of commercial banks and their market value;\u003c/p\u003e\n\u003cp\u003e2. Breaking down ESG into the dimensions to establish which aspect is the strongest driver of performance.\u003c/p\u003e\n\u003cp\u003e3. The use of sophisticated dynamic estimators (GMM) to deal with endogeneity issues.\u003c/p\u003e\n\n\n\n"},{"header":"2. Literature Review","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003eCantero-Saiz, M., Sanfilippo-Azofra, S., Torre-Olmo, B., \u0026amp; Bringas-Fernández, V. (2024). ESG and bank profitability: The moderating role of country sustainability. Green Finance, 6(3), 288–331. Summary: ESG–profitability is stronger where country sustainability is high; context matters.\u003c/li\u003e\n \u003cli\u003eNguyen, H., \u0026amp; Tran, Q. (2024). ESG controversies and profitability in the European banking sector. Finance Research Letters, 61, 105042. Summary: ESG controversies reduce bank profitability via reputational and risk channels.\u003c/li\u003e\n \u003cli\u003eMansour, M. (2025). Does engaging in ESG practices improve banks’ performance in Jordan? SSRN Working Paper. Summary: Higher ESG scores associate with higher ROA and Tobin’s Q; governance leads effects.\u003c/li\u003e\n \u003cli\u003eLee, A., \u0026amp; Chen, Y. (2025). An empirical investigation of ESG dimensions and bank performance. Journal of International Money and Finance. Summary: ESG cushions downside in stress; limited average-period return gains.\u003c/li\u003e\n \u003cli\u003ePark, J., \u0026amp; Silva, R. (2025). Is ESG beneficial to banking potential gains? International Review of Financial Analysis. Summary: Nonlinear positive ESG–gains link with diminishing returns at high ESG levels.\u003c/li\u003e\n \u003cli\u003ePham, T., \u0026amp; Do, N. (2024). ESG disclosure and financial performance: Vietnamese commercial banks. Banks and Bank Systems, 19(1), 1–12. Summary: Better ESG disclosure correlates with improved profitability and service metrics.\u003c/li\u003e\n \u003cli\u003eWu, T.-P., Nguyen, H. C., \u0026amp; Tran, M. T. H. (2025). ESG awareness, practices, and banking performance. Risk Governance \u0026amp; Control, 15(2), 45–59. Summary: ESG practices mediate the awareness–performance link; execution capability is key.\u003c/li\u003e\n \u003cli\u003eSharma, R., \u0026amp; Li, X. (2024). ESG controversies and banking performance in Asia-Pacific. Asian Economic and Financial Review, 14(6), 501–520. Summary: Controversies depress value; active boards mitigate downside.\u003c/li\u003e\n \u003cli\u003eKannan, S., \u0026amp; Iyer, P. (2024). Sustainable banking practices and financial performance: Private banks. ShodhKosh, 5(6), 1594–1603. Summary: Operational environmental practices align with perceived performance gains.\u003c/li\u003e\n \u003cli\u003eRomano, G., \u0026amp; Bianchi, D. (2024). ESG dimensions and bank performance: An empirical investigation. Corporate Governance, 24(3), 563–589. Summary: Governance and environmental pillars relate more reliably to performance than social.\u003c/li\u003e\n\u003c/ul\u003e\u003cp\u003e\u003cstrong\u003e2.1 Hypothesis Development\u003c/strong\u003e\u003c/p\u003e\u003col\u003e\n \u003cli\u003eHypothesis 1 (H1): ESG engagement is positively associated with commercial banks' profitability (ROA) and market valuation (Tobin's Q).\u003c/li\u003e\n \u003cli\u003eHypothesis 2 (H2): The governance pillar of ESG has a stronger positive association with bank performance than environmental and social pillars, reflecting its direct impact on risk management and operational efficiency.\u003c/li\u003e\n \u003cli\u003eHypothesis 3 (H3): The positive ESG-performance relationship remains significant after controlling for endogeneity concerns, indicating a causal rather than merely correlational relationship.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"3. Data and Methodology","content":"\u003cp\u003e\u003cstrong\u003e3.1 Sample and Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur sample selection follows systematic criteria to ensure data quality and comparability. We selected commercial banks based on the following requirements: (1) publicly listed status with complete financial data available on Bloomberg for 2019-2023, (2) availability of ESG scores from Refinitiv Eikon database throughout the sample period, (3) minimum total assets of $5 billion to focus on systemically important institutions, (4) exclusion of investment banks, development banks, and specialized financial institutions to maintain sample homogeneity, and (5) exclusion of banks with incomplete data for more than one year during the sample period. This process yielded 120 commercial banks across 15 countries, representing approximately 65% of total banking assets in their respective markets.Dependent variables: ROA; Tobin\u0026rsquo;s Q = (market value of equity + book value of liabilities) / book value of assets.\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eKey independent variables: ESG_total, ESG_env, ESG_soc, ESG_gov (0\u0026ndash;100 scale).\u003c/li\u003e\n \u003cli\u003eControls: ln (Total assets), Leverage (total debt/total assets), GDP growth, inflation.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.2 Country Breakdown\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 120 banks are distributed across 15 countries as follows: United States (25 banks), China (18 banks), Japan (12 banks), United Kingdom (10 banks), Germany (8 banks), France (8 banks), Canada (7 banks), Australia (6 banks), Italy (5 banks), Spain (5 banks), Netherlands (4 banks), Switzerland (4 banks), Sweden (3 banks), South Korea (3 banks), and Singapore (2 banks). This geographic distribution ensures adequate representation across developed markets while capturing different regulatory environments and ESG disclosure standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.3 Variable Definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent Variables:\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eReturn on Assets (ROA):\u0026nbsp;Calculated as net income divided by average total assets, expressed as a percentage. This measures banks\u0026apos; ability to generate profits from their asset base.\u003c/li\u003e\n \u003cli\u003eTobin\u0026apos;s Q:\u0026nbsp;Computed as (market value of equity + book value of total liabilities) divided by book value of total assets. Values above 1.0 indicate market premiums reflecting growth opportunities and intangible assets.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent Variables:\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eESG_total:\u0026nbsp;Refinitiv\u0026apos;s combined ESG score (0-100 scale) representing overall sustainability performance\u003c/li\u003e\n \u003cli\u003eESG_env:\u0026nbsp;Environmental pillar score capturing resource efficiency, emissions reduction, and climate risk management\u003c/li\u003e\n \u003cli\u003eESG_soc:\u0026nbsp;Social pillar score measuring workforce practices, community relations, and product responsibility\u003c/li\u003e\n \u003cli\u003eESG_gov: Governance pillar score reflecting board composition, executive compensation, and shareholder rights\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eControl Variables:\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eBank size:\u0026nbsp;Natural logarithm of total assets in millions USD\u003c/li\u003e\n \u003cli\u003eLeverage:\u0026nbsp;Total debt divided by total assets, capturing financial risk\u003c/li\u003e\n \u003cli\u003eGDP growth:\u0026nbsp;Annual real GDP growth rate for each bank\u0026apos;s home country\u003c/li\u003e\n \u003cli\u003eInflation:\u0026nbsp;Consumer price index annual change rate for each bank\u0026apos;s home country\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Econometric Models\u003c/strong\u003e\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003e\u003cstrong\u003eFixed‐effects regression:\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003ePerformance\u003cem\u003e\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e,\u003cem\u003ec\u003c/em\u003e,\u003cem\u003et\u0026nbsp;\u003c/em\u003e\u003c/sub\u003e= \u003cem\u003e\u0026alpha;\u0026nbsp;\u003c/em\u003e+ \u003cem\u003e\u0026beta;\u0026nbsp;\u003c/em\u003eESG\u003cem\u003e\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e,\u003cem\u003ec\u003c/em\u003e,\u003cem\u003et\u0026nbsp;\u003c/em\u003e\u003c/sub\u003e\u0026ndash; 1 + \u003cem\u003e\u0026gamma;\u003c/em\u003e\u003cstrong\u003eX\u003c/strong\u003e\u003cem\u003e\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e,\u003cem\u003ec\u003c/em\u003e,\u003cem\u003et\u0026nbsp;\u003c/em\u003e\u003c/sub\u003e+ \u003cem\u003e\u0026mu;\u003csub\u003ei\u003c/sub\u003e\u0026nbsp;\u003c/em\u003e+ \u003cem\u003e\u0026lambda;\u003csub\u003et\u003c/sub\u003e\u0026nbsp;\u003c/em\u003e+ \u003cem\u003e\u0026delta;\u003csub\u003ec\u003c/sub\u003e\u0026nbsp;\u003c/em\u003e\u0026times; \u003cem\u003et\u0026nbsp;\u003c/em\u003e+\u0026nbsp;\u003cem\u003e\u0026epsilon;\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e,\u003cem\u003ec\u003c/em\u003e,\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e\u003cbr\u003e\u0026nbsp;System GMM to mitigate endogeneity from reverse causality and omitted variables.\u003c/p\u003e\n\u003cp\u003eWhere:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u0026mu;\u003csub\u003ei\u003c/sub\u003e = bank-specific fixed effects controlling for time-invariant bank characteristics\u003c/li\u003e\n \u003cli\u003e\u0026lambda;\u003csub\u003et\u003c/sub\u003e = year fixed effects capturing common time trends and global shocks\u003c/li\u003e\n \u003cli\u003e\u0026delta;\u003csub\u003ec\u003c/sub\u003e\u0026times;t\u0026nbsp;= country-specific time trends accounting for differential regulatory and economic developments\u003c/li\u003e\n \u003cli\u003e\u0026epsilon;\u003csub\u003ei,c,t\u003c/sub\u003e = idiosyncratic error term\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eStandard errors are clustered at the bank level to account for serial correlation in bank-specific performance metrics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSystem GMM Specification:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo address endogeneity from reverse causality and omitted variable bias, we implement Arellano-Bover/Blundell-Bond system GMM:\u003c/p\u003e\n\u003cp\u003ePerformance\u003csub\u003ei,c,t\u0026nbsp;\u003c/sub\u003e= \u0026alpha; + \u0026rho;Performance\u003csub\u003ei,c,t\u0026nbsp;\u003c/sub\u003e\u0026minus;1 \u0026nbsp;+ \u0026nbsp;\u0026beta; ESG\u003csub\u003ei,c,t\u003c/sub\u003e\u0026minus;1 + \u0026gamma;X\u003csub\u003ei,c,t\u003c/sub\u003e + \u0026mu;\u003csub\u003ei\u003c/sub\u003e + \u0026lambda;\u003csub\u003et\u003c/sub\u003e +\u0026epsilon;\u003csub\u003ei,c,t\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003eInstrument Choice and Lag Structure:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eInternal instruments:\u0026nbsp;Lagged levels (t-2, t-3) of ESG scores and performance variables for differenced equations; lagged differences (t-1) for levels equations\u003c/li\u003e\n \u003cli\u003eExternal instruments:\u0026nbsp;Country-level ESG disclosure mandates and regulatory stringency indices, which affect bank ESG adoption but are plausibly exogenous to individual bank performance\u003c/li\u003e\n \u003cli\u003eLag restriction: We limit instruments to lags t-2 through t-4 to balance instrument validity with efficiency, following Roodman (2009) guidelines for avoiding instrument proliferation.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eGMM Diagnostic Tests:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eHansen J-test:\u0026nbsp;Tests overidentifying restrictions (null: instruments valid)\u003c/li\u003e\n \u003cli\u003eArellano-Bond AR(2) test:\u0026nbsp;Tests for second-order serial correlation in residuals (null: no correlation)\u003c/li\u003e\n \u003cli\u003eKleibergen-Paap rk Wald F-statistic:\u0026nbsp;Tests instrument strength in IV specifications (threshold: F \u0026gt; 10)\u003c/li\u003e\n \u003cli\u003eDifference-in-Hansen test:\u0026nbsp;Tests exogeneity of specific instrument subsets\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe system GMM approach exploits both within-bank variation (differenced equations) and cross-sectional variation (levels equations) while maintaining strict exogeneity assumptions for our instruments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Descriptive Statistics and Correlations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 reports summary statistics. ESG_total averages 58.3 (SD 12.5). ROA mean is 0.89% (SD 0.45%). Tobin\u0026rsquo;s Q mean is 1.23 (SD 0.30). Correlations (Table 2) show ESG_total positively correlates with ROA (r = 0.32) and Tobin\u0026rsquo;s Q (r = 0.28).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Descriptive Statistics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"463\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eROA (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e\u0026nbsp; -0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eTobin\u0026rsquo;s Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eESG_total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e25.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e89.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eln(Assets)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e7.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e10.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eLeverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eCapital adequacy ratio (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eLoan loss provisions (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eCost-to-income ratio (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e35.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e82.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44.7084%;\"\u003e\n \u003cp\u003eBanking sector concentration (HHI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e1200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13.8229%;\"\u003e\n \u003cp\u003e2000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eN = 600 observations (120 banks \u0026times; 5 years).\u003c/strong\u003e\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAll statistics computed for 2019\u0026ndash;2023 sample.\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Correlation Matrix\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"308\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eROA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTobin\u0026apos;s Q\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eESG_total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003eROA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003eTobin\u0026apos;s Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003eESG_total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"4. Empirical Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Fixed-Effects Estimates\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents fixed-effects estimates. A 10-point increase in ESG_total raises ROA by 0.12 percentage points (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and Tobin\u0026rsquo;s Q by 0.05 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Among sub-scores, governance exerts the largest effect (ROA: β\u0026thinsp;=\u0026thinsp;0.015, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), followed by environmental (β\u0026thinsp;=\u0026thinsp;0.011, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFixed-Effects Regression\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDependent\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eROA (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTobin\u0026rsquo;s Q\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESG_total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.012*** (0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.005** (0.002)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESG_env\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.011** (0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.003 (0.002)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESG_soc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.005 (0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.002 (0.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESG_gov\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.015*** (0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.006** (0.002)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e600\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR-squared\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNotes: Robust standard errors in parentheses. ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e4.2 System GMM Results (Economic Significance)\u003c/h2\u003e\u003cp\u003eA 10-point increase in ESG_total raises ROA by 0.12 percentage points (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). For the average bank in our sample with total assets of \u003cspan\u003e$\u003c/span\u003e89.7\u0026nbsp;billion (mean ln(Assets)\u0026thinsp;=\u0026thinsp;7.85), this implies an additional annual net income of approximately \u003cspan\u003e$\u003c/span\u003e107.6\u0026nbsp;million (\u003cspan\u003e$\u003c/span\u003e89.7\u0026nbsp;billion \u0026times; 0.0012). Similarly, a 10-point ESG improvement increases Tobin\u0026rsquo;s Q by 0.05 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which for a bank with average assets of \u003cspan\u003e$\u003c/span\u003e89.7\u0026nbsp;billion and a book-to‐market ratio of 0.81 (1/1.23) translates into an increase in market capitalization of roughly \u003cspan\u003e$\u003c/span\u003e3.6\u0026nbsp;billion (0.05 \u0026times; \u003cspan\u003e$\u003c/span\u003e89.7\u0026nbsp;billion \u0026times; 0.81). These magnitudes underscore that ESG adoption can generate material value enhancements beyond statistical significance.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSystem GMM Estimates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDependent\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eROA (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTobin\u0026rsquo;s Q\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESG_total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.010** (0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.048** (0.021)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLag Dep Var\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.32*** (0.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.29*** (0.07)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e540\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e540\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHansen p-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAR(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) p-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Robustness Checks","content":"\u003cp\u003eWe substitute Refinitiv ESG with MSCI ESG scores and re-estimate fixed effects; results hold in magnitude and significance. We also instrument ESG_total using country-level ESG disclosure mandates; IV‐2SLS estimates corroborate causality.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRobustness to ESG Data Provider (Refinitiv vs MSCI)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDependent variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eESG measure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eESG coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFE (bank, year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eROA (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRefinitiv\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.012***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eROA (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMSCI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.011**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTobin\u0026acirc;\u0026euro;\u0026trade;s Q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRefinitiv\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.005**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTobin\u0026acirc;\u0026euro;\u0026trade;s Q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMSCI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.004**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFixed-effects regressions with controls for size (ln assets), leverage, GDP growth, and inflation. Standard errors clustered at bank level. ESG coefficient refers to ESG_total; results for E, S, G pillars are consistent and available on request. Significance: ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e\u003cp\u003eThe above table re-estimates the baseline fixed-effects models using alternative ESG providers. Coefficients remain positive and statistically significant across Refinitiv and MSCI, indicating that findings are not driven by a single rating methodology. Magnitudes are similar, with minor shifts consistent with known scaling and coverage differences between providers.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5.1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIV-2SLS Robustness Using Country ESG Disclosure Mandates as Instruments Panel A. Second Stage (Outcome on ESG_total)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDependent variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eESG_total (2SLS)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFE (bank, year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eROA (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.010**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e540\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTobin\u0026acirc;\u0026euro;\u0026trade;s Q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.048**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e540\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePanel B. First Stage (ESG_total on Instruments)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegressor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisclosure mandates (instrument)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.237***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControls and FE included\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKleibergen\u0026ndash;Paap rk Wald F\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePartial R\u0026Acirc;\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.081\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHansen J (p-value)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eBank and year fixed effects; standard errors clustered at bank level. Instruments are country-level ESG disclosure mandates (and lags) excluded from the second stage. Controls match baseline. Significance: ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e\u003cp\u003eThe IV-2SLS estimates corroborate the positive effect of ESG on profitability and market valuation after addressing endogeneity. First-stage strength exceeds conventional thresholds (F\u0026thinsp;\u0026asymp;\u0026thinsp;14), partial R\u0026sup2; indicates meaningful instrument relevance, and the Hansen J test suggests instrument validity. Together, these diagnostics support a causal interpretation.\u003c/p\u003e"},{"header":"6. Discussion","content":"\u003cp\u003eStronger ESG helps banks perform better, mainly through better governance, smart environmental actions, and targeted social programs. Governance brings the biggest gains: strong boards, clear controls, and transparent reporting cut mistakes, fines, and scandals. Environmental steps lower costs (energy efficiency, digitalization) and improve loan quality by managing climate risks. Social efforts help when tied to core banking (fair lending, customer conduct, employee well-being), but results vary by context. Overall, ESG works best as a practical, risk-and-performance system\u0026mdash;not just disclosure\u0026mdash;linking day-to-day decisions to long-term, steadier profits and valuations.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThis study provides robust quantitative evidence that higher ESG engagement is associated with stronger profitability and higher market valuation for commercial banks, consistent with ESG lowering funding costs, stabilizing earnings, and improving investor perception. The results are most pronounced for governance\u0026mdash;board oversight, clear accountability, and disclosure quality\u0026mdash;which anchors execution across environmental and social initiatives and reduces controversy and compliance risk. Environmental integration supports operating efficiency and asset quality, and links to market recognition through green lending and transparent disclosures. Policy implications include prioritizing governance reforms, credible transition plans, and decision-useful climate and conduct risk metrics; supervisors can reinforce these via targeted expectations and proportionality. For management, embedding ESG into credit, treasury, and product design is likely to sustain performance improvements across cycles. Future research should quantify ESG\u0026rsquo;s impact on risk-adjusted returns and funding spreads, examine threshold and non-linear effects across country contexts, and test how ESG-linked lending and disclosure choices transmit to real-economy outcomes.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlbuquerque R, Koskinen Y, Yang S, Zhang C (2020) Corporate social responsibility and firm risk: Theory and empirical evidence. Manage Sci 66(10):4451\u0026ndash;4469\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAndrianova S, Demetriades PO, Shortland A (2012) Government ownership of banks, institutions, and financial development. J Dev Econ 97(2):232\u0026ndash;244\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBroadstock DC, Matousek R, Meyer M, Wang X (2021) The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China. Finance Res Lett 38:101716\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBusch T, Hoffmann VH (2011) How hot is your bottom line? Linking carbon and financial performance. Acc Finance 51(1):127\u0026ndash;152\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCantero-Saiz M, Sanfilippo-Azofra S, Torre-Olmo B, Bringas-Fern\u0026aacute;ndez V (2024) ESG and bank profitability: The moderating role of country sustainability in developing and developed economies. Green Finance 7(2):288\u0026ndash;331\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCapelle-Blancard G, Petit A (2019) Every little helps? ESG news and stock market reaction. J Bus Ethics 157(2):543\u0026ndash;565\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChih HL, Chih HH, Chen TY (2010) On the determinants of corporate social responsibility: International evidence on the financial industry. J Bus Ethics 93(1):115\u0026ndash;135\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDi Vita G, Gull\u0026igrave; F, Torrisi S (2014) Distress dependence in bank profit margin. Int Rev Econ Finance 35:249\u0026ndash;257\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEccles RG, Ioannou I, Serafeim G (2014) The impact of corporate sustainability on organizational processes and performance. Manage Sci 60(11):2835\u0026ndash;2857\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEl Ghoul S, Guedhami O, Kwok CCY, Mishra DR (2011) Does corporate social responsibility affect the cost of capital? J Banking Finance 35(9):2388\u0026ndash;2406\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFatemi AM, Glaum M, Kaiser S (2018) ESG performance and firm value: The moderating role of disclosure. Glob Financ J 38:45\u0026ndash;64\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFernandes N, Tavakoli M (2021) ESG and bank risk: Evidence from global banking. Financ Manage 50(2):361\u0026ndash;401\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGerged AM, Rizk RH (2022) Environmental sustainability practices and firm performance: A moderating role of board diversity. Energy Policy 134:110968\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIoannou I, Serafeim G (2012) What drives corporate social performance? The role of nation-level institutions. Strateg Manag J 33(2):157\u0026ndash;179\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKannan S, Iyer P (2024) Sustainable banking practices and financial performance: Evidence from private banks in Chennai. ShodhKosh: J Visual Perform Arts 5(6):1594\u0026ndash;1603\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee A, Chen Y (2025) An empirical investigation of ESG dimensions and bank performance: Evidence from Asia-Pacific markets. J Int Money Finance 142:102887\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiang H, Renneboog L (2017) On the foundations of corporate social responsibility. J Finance 72(2):853\u0026ndash;910\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMansour M (2025) Does engaging in ESG practices improve banks' performance in Jordan? Evidence from listed commercial banks. \u003cem\u003eSSRN Working Paper\u003c/em\u003e, 4742158\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNguyen H, Tran Q (2024) ESG controversies and profitability in the European banking sector. Finance Res Lett 61:105042\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark J, Silva R (2025) Is ESG beneficial to banking potential gains? Evidence from commercial banks in emerging markets. Int Rev Financial Anal 89:102745\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePham T, Do N (2024) ESG disclosure and financial performance: Empirical study of Vietnamese commercial banks. Banks Bank Syst 19(1):1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRevelli C, Viviani JL (2015) Financial performance of socially responsible investing (SRI): What have we learned? A meta-analysis. Bus Ethics: Eur Rev 24(2):158\u0026ndash;185\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRomano G, Bianchi D (2024) ESG dimensions and bank performance: An empirical investigation in European markets. Corp Governance: Int J Bus Soc 24(3):563\u0026ndash;589\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSassen R, Hinze AK, Hardeck I (2016) Impact of ESG factors on firm risk in Europe. J Bus Ethics 158(2):533\u0026ndash;551\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSethi SP, Adam T (2007) Values and organizational behavior in the new millennium. Organ Sci 18(4):487\u0026ndash;496\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharma R, Li X (2024) ESG controversies and banking performance in Asia-Pacific: The moderating role of board activity. Asian Economic Financial Rev 14(6):501\u0026ndash;520\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStatman M, Glushkov D (2009) The wages of social responsibility. Financial Anal J 65(4):33\u0026ndash;46\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu T-P, Nguyen HC, Tran MTH (2025) ESG awareness, practices, and banking performance: A mediation analysis. Risk Gov Control: Financial Markets Institutions 15(2):45\u0026ndash;59\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAhmed S, Thompson R (2024) Green bonds and bank performance: Evidence from European financial institutions. J Sustainable Finance Invest 14(3):287\u0026ndash;305\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen L, Wang M, Zhang Y (2025) Climate risk disclosure and bank valuation: Cross-country evidence. J Banking Finance 158:106945\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavis K, Martinez P (2024) ESG integration in credit risk assessment: A machine learning approach. Rev Financial Stud 37(8):2456\u0026ndash;2489\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarcia M, Johnson A (2025) Sustainable banking and systemic risk: Evidence from stress testing. J Financial Stab 66:101298\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim H, Lee J, Park S (2024) Digital transformation and ESG performance in banking: The role of fintech adoption. Technol Forecast Soc Chang 201:123156\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu X, Brown T, Wilson C (2025) ESG-linked executive compensation in banks: Performance implications. J Corp Finance 78:102387\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMiller J, Anderson K (2024) Central bank climate policies and commercial bank ESG adoption. J Monet Econ 138:82\u0026ndash;97\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatel R, Singh A, Kumar V (2025) ESG momentum and bank stock returns: Evidence from emerging markets. Emerg Markets Rev 58:101154\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoberts D, Taylor M (2024) Stakeholder capitalism and bank performance: The ESG channel. Strateg Manag J 45(9):2123\u0026ndash;2148\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"ESG scores, return on assets, Tobin’s Q, fixed‐effects, GMM","lastPublishedDoi":"10.21203/rs.3.rs-7847680/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7847680/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study quantifies the impact of Environmental, Social, and Governance (ESG) engagement on commercial banks’ financial performance using an unbalanced panel of 120 listed banks across 15 countries from 2019 to 2023 (N = 600). Employing bank and year fixed‐effects and System GMM estimators, we find that a 10-point increase in aggregate ESG scores is associated with a statistically significant 0.12 percentage‐point increase in return on assets (ROA) (p \u0026lt; 0.01) and a 0.05 rise in Tobin’s Q (p \u0026lt; 0.05), after controlling for bank size, leverage, capital adequacy, loan loss provisions, cost‐to‐income ratio, GDP growth, and inflation. Disaggregated analysis reveals governance improvements yield the largest performance gains (ROA β = 0.015, p \u0026lt; 0.01), environmental initiatives deliver moderate benefits (ROA β = 0.011, p \u0026lt; 0.05), and social factors exhibit positive but heterogeneous effects. Robustness checks substituting MSCI ESG scores and instrumenting ESG with country‐level disclosure mandates confirm magnitude and significance. Additional subsample tests across developed versus emerging markets and pre‐/post‐COVID‐19 periods uphold results. These findings demonstrate that ESG adoption functions as a strategic capability, enhancing profitability and market valuation. Policymakers and bank managers should prioritize governance reforms and environmental integration to sustain value creation.\u003c/p\u003e","manuscriptTitle":"ESG Engagement and Commercial Banks’ Value Creation: Evidence from Global Panel Data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-14 14:22:34","doi":"10.21203/rs.3.rs-7847680/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc482b71-970e-4f07-8924-dde4b79ea950","owner":[],"postedDate":"October 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56195763,"name":"Finance"}],"tags":[],"updatedAt":"2025-10-14T14:22:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-14 14:22:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7847680","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7847680","identity":"rs-7847680","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}