Does the bank's nature heterogeneity matter? Environmental, social and governance (ESG) performance and corporate profitability

Dossa, Joel Victor; Gopang, Aamir Ali; Thomas, Dara; Ukwuoma, Chiagoziem Chima Article Does the bank's nature heterogeneity matter? Environmental, social and governance (ESG) performance and corporate profitability Asian Journal of Economics and Banking (AJEB) Provided in Cooperation with: Ho Chi Minh University of Banking (HUB), Ho Chi Minh City Suggested Citation: Dossa, Joel Victor; Gopang, Aamir Ali; Thomas, Dara; Ukwuoma, Chiagoziem Chima (2025) : Does the bank's nature heterogeneity matter? Environmental, social and governance (ESG) performance and corporate profitability, Asian Journal of Economics and Banking (AJEB), ISSN 2633-7991, Emerald, Leeds, Vol. 9, Iss. 3, pp. 364-394, https://doi.org/10.1108/AJEB-11-2024-0128 This Version is available at: https://hdl.handle.net/10419/334151 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Does the bank’s nature heterogeneity matter? Environmental, social and governance (ESG) performance and corporate profitability Joel Victor Dossa, Aamir Ali Gopang and Dara Thomas Business School, Sichuan University, Chengdu, China, and Chiagoziem Chima Ukwuoma OBU, Sino-British Collaborative Education, Chengdu University of Technology, Chengdu, China and College of Nuclear Technology and Automation, Chengdu University of Technology, Chengdu, China Abstract Purpose – This study explores the impact of environmental, social and governance (ESG) performance on corporate profitability in Chinese commercial banks from 2012 to 2022, examining how inherent differences across bank types moderate this relationship. Design/methodology/approach – Using two-way fixed effects, 2SLS (instrumental variables), simultaneity tests and system GMM, the study analyzes the effects of ESG on profitability while addressing endogeneity. To capture heterogeneity, the sample is stratified by ownership (state-owned vs non-state-owned), governance (joint-stock vs non-joint-stock) and location (urban vs rural). Findings – The results show that ESG performance positively impacts profitability in both rural and urban commercial banks, with governance performance negatively affecting urban banks. ESG negatively influences profitability in state-owned banks, whereas non-state-owned banks benefit from positive ESG performance. Environmental performance positively affects profitability in both types of banks, but governance has a negative impact. ESG boosts profitability in joint-stock banks but detracts from it in nonjoint-stock banks. Social activities positively affect profitability across both bank types, while environmental activities are insignificant. Governance activities enhance profitability in joint-stock banks but reduce it in non-joint-stock banks. Practical implications – Policymakers should create tiered ESG regulations, incentivizing market-driven banks while subsidizing state-owned banks’ compliance costs. Bank managers should tailor ESG investments, focusing on environmental and social initiatives based on location and investors must evaluate ESG scores contextually. Originality/value – This study provides a granular analysis of ESG-profitability linkages across China’s heterogeneous banking landscape, highlighting how institutional characteristics such as ownership, governance structure and geographic focus shape the financial implications of ESG. Keywords Corporate profitability, ESG, Bank’s nature, State-owned commercial banks, Joint commercial banks, Urban commercial bank, Rural commercial banks Paper type Research article 1. Introduction The global surge in Environmental, Social, and Governance (ESG) adoption has transformed it from a corporate social responsibility initiative into a critical determinant AJEB 9,3 364 JEL Classification — G21, G30, G32, M14, Q56, C33 © Joel Victor Dossa, Aamir Ali Gopang, Dara Thomas and Chiagoziem Chima Ukwuoma. Published in Asian Journal of Economics and Banking. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at Link to the terms of the CC BY 4.0 licence. Received 24 November 2024 Revised 17 April 2025 20 June 2025 Accepted 21 August 2025 Asian Journal of Economics and Banking Vol. 9 No. 3, 2025 pp. 364-394 Emerald Publishing Limited e-ISSN: 2633-7991 p-ISSN: 2615-9821 DOI 10.1108/AJEB-11-2024-0128 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 of financial performance and investment attractiveness (Giannopoulos et al., 2022; Townsend, 2020). With ESG assets projected to reach $53tn by 2025, the financial sector, particularly banks, faces mounting pressure to integrate sustainability into core operations (Sani et al., 2024; Sebasti~ ao et al., 2024). China’s regulatory push, exemplified by the “double-carbon” policy and ESG disclosure mandates further highlights this shift (Yuan et al., 2022). Yet, the profitability implications of ESG in banking remain contested, with studies reporting positive (Zhang and Lucey, 2022), negative (Buallay, 2019, 2020), or neutral effects (Assaf et al., 2024; Asteriou et al., 2024; Friede et al., 2015). These inconsistencies stem from a critical gap: Prior research predominantly examines carbonintensive industries, overlooking the unique dynamics of financial institutions, especially in state-influenced economies like China, where banks operate under heterogeneous ownership and governance structures. This study addresses this gap by analyzing how ESG performance impacts profitability across 42 Chinese-listed commercial banks (2012–2022), differentiating by state ownership, joint-stock status, and urban-rural divides. Employing two-way fixed effects, 2SLS, and system GMM, we reconcile conflicting theoretical perspectives: stakeholder theory (Freeman and McVea, 2001), which posits that ESG enhances profitability through trust and efficiency, and trade-off theory, which frames ESG as a cost burden (Fu and Zhang, 2025; Handoyo and Anas, 2024; Zumente and Bistrova, 2021). In this study, we provide the first granular evidence on the impact of ESG performance on profitability within China’s banking sector, a critical yet less environmentally sensitive industry. Our analysis reveals that ESG effects are not uniform across all banks; rather, they are contingent upon institutional characteristics such as ownership, governance structure, and geographic location. Specifically, state-owned banks experience a reduction in profitability from ESG compliance, while private banks gain profitability through strategic ESG implementation. Governance structure also plays a significant role: joint-stock banks see profitability increases from ESG, whereas non-joint-stock banks experience profitability declines. Geographic differences further emerge, with rural banks benefiting overall, particularly from social initiatives, while urban banks face governance-related profitability challenges. The study also highlights the varying effects of ESG components; environmental factors generally have a positive impact on profitability, except for stateowned banks; social factors are universally beneficial, and governance factors have a mixed impact, being positive in joint-stock banks and negative in others. This research contributes to the literature in several key ways: First, it provides sectoral novelty by examining ESG-profitability linkages in the banking sector, an area largely underexplored in ESG studies. Second, by accounting for institutional heterogeneity stratifying banks by ownership, governance, and location, we reveal how ESG effects are context-dependent, a nuance often overlooked in previous studies. Third, our findings have policy implications, advocating for tiered ESG regulations that offer subsidies for state-owned banks’ compliance costs and market-driven incentives for private banks. Finally, our methodological rigor, incorporating robustness checks and disaggregation of ESG components, addresses endogeneity concerns and uncovers governance as a key challenge for urban banks. The paper is organized as follows: Section 2 reviews the literature and hypotheses, Section 3 outlines the methodology, Section 4 presents the results, and Section 5 discusses the implications for policymakers and bankers. 2. Literature and hypotheses development To evaluate the relationship between ESG performance and corporate performance, various theories can be used to support such a relationship. These theories provide both positive and negative perspectives on the impact of ESG performance on corporate profitability. Asian Journal of Economics and Banking 365 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 2.1 Theories supporting ESG performance and corporate profitability Stakeholder Theory explains why firms disclose ESG activities (Freeman et al., 2018; Harrison et al., 2015). Freeman (2010) describes stakeholders as any group or individual who can affect or be affected by the attainment of an organization’s objectives (Freeman et al., 2010, 2018). Stakeholder theory and ESG studies are compatible since an organization’s ESG practices aim to improve management, satisfy various stakeholders, and boost financial performance (Freeman, 1994). The theory asserts that different stakeholders are attracted to specific kinds of information, and firms face challenges in balancing the demands of diverse stakeholder groups. Central to a firm’s survival, investors receive significant attention in ESG reporting (Talan et al., 2024). The normative aspect of stakeholder theory supports the view that firms should consider the needs of all stakeholders-investors, employees, shareholders, and the community-within the sustainability framework (Abdi et al., 2022). Thus, meeting the expectations of these stakeholders, in addition to enhancing investors’ financial returns, is crucial for a firm’s success. Companies that neglect social responsibility to reduce implicit costs may face more explicit costs in the long term, thereby negatively impacting their profitability (Sz} ocs and Montanari, 2025). Agency Theory explains the relationship between agents (managers) and principals (shareholders) (Jensen and Meckling, 1976). Agency problems arise from the misalignment of interests between management, which focuses on profit maximization and compensation, and shareholders, who seek risk reduction and value increase (Cen et al., 2025; Khandelwal et al., 2023; Li et al., 2020). Agency costs, including transaction and information costs, are prevalent in the relationship between agents and principals (Oviatt, 1988). Since ESG disclosures often address many of these agency-related issues, they help reduce information asymmetries and lower agency costs. As a result, enhancing ESG performance could lead to a reduction in agency costs and a subsequent increase in corporate profitability. 2.2 Theories against ESG performance and corporate profitability The trade-off Theory submits an antagonistic relationship between corporate profitability (CP) and sustainability. Investing in environmental protection, increasing employee compensation, and supporting community initiatives are social and environmental goals that require significant investment but can reduce profitability and weaken competitive advantage (Wu and Tham, 2023). Hence, firms should only engage in ESG initiatives if these efforts result in surplus profits. (Martiny et al., 2024) Found that compelling firms to undertake ESG activities can lower their profits. According to the trade-off theory, sustainable practices incur higher costs, which can adversely affect profitability (Pham et al., 2021; Zhang and Xie, 2022). Institutional Theory further refines our understanding by examining how regulatory and cultural factors shape the ESG-profitability relationship. Institutional theory proposes that firms are not merely economic entities but are also shaped by the institutional environment in which they operate. Institutional pressures, whether coercive (e.g. government regulations), normative (e.g. industry standards), or mimetic (e.g. adopting practices based on industry leaders), influence how firms implement ESG initiatives and how these initiatives, in turn, affect profitability (DiMaggio and Powell, 1983). In the context of banks in China, stateowned banks may face significant government-driven pressures to align with national sustainability goals, which could lead to profitability trade-offs. On the other hand, non-stateowned and rural banks, less constrained by government mandates, may leverage ESG initiatives as part of a competitive strategy, resulting in profitability gains. Thus, the impact of ESG on profitability can vary depending on a bank’s institutional environment and ownership structure. 2.3 ESG performance and corporate profitability A growing body of research has examined the impact of Environmental, Social, and Governance (ESG) practices on corporate profitability, yielding a spectrum of findings. Many AJEB 9,3 366 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 scholars highlight the strategic benefits of ESG integration across organizational functions, noting improvements in employee motivation, corporate reputation, and retention (Chen et al., 2024a, b; Garrido-Ruso et al., 2024). For instance, studies from the US context propose that firms with higher levels of ESG disclosure tend to exhibit superior market performance, particularly in the upper quantiles of ESG reporting (Veeravel et al., 2024). Zhang and Lucey (2022) Further assert that ESG performance significantly enhances firm outcomes, primarily by easing financial constraints, which in turn supports operational efficiency and long-term profitability. Similarly, Albitar et al. (2020) provide empirical evidence linking ESG disclosure scores to improved corporate performance, particularly after the adoption of integrated reporting standards. However, the literature also presents countervailing evidence. Some scholars argue that ESG activities may impose financial burdens that outweigh their potential benefits. For example, Saygili et al. (2022) Reveals that environmental disclosures can negatively affect a firm’s financial outcomes. Buallay (2019, 2021) Consistently find that ESG performance is inversely related to key financial indicators such as Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q, especially within the banking and financial services sectors. Furthermore, global evidence from 60 countries indicates that ESG reporting may lead to declines in operational and market performance (AlAjmi et al., 2023). In the healthcare sector, (Kalia and Aggarwal, 2023) and Dossa (2025) Found mixed results. Dossa (2025), in particular, shows that while ESG, governance, and social disclosures enhance financial performance, environmental activities are negatively associated with both accounting and market-based performance metrics in Chinese healthcare firms. These contrasting findings emphasize the complexity and context-specific nature of the ESG-performance relationship. To contribute to this ongoing debate and provide new evidence from an emerging market perspective, particularly China’s banking sector, we propose the following hypotheses: H1a. ESG performance positively influences corporate profitability. H1b. ESG performance negatively influences corporate profitability. 2.4 Environmental performance corporate profitability A growing body of research highlights the significant role of environmental performance in shaping corporate financial outcomes. Several studies advise that effective environmental strategies can enhance firm performance by improving efficiency, reducing operational risks, and fostering a positive corporate reputation (Gull et al., 2022; Veeravel et al., 2024). For example, Gull et al. (2022) found that the top-performing firms in terms of environmental initiatives outperformed average firms financially, while Li et al. (2024) Demonstrated how enterprise-wide adoption of environmental standards can lower production costs and mitigate environmental risks, ultimately increasing profitability. Similarly, Wu and Tham (2023) Observed that proactive environmental investments can substantially increase firm value over time. Zhu et al. (2024) Further argued that transparent environmental disclosures, especially when framed around governance rather than investment costs, are more positively received by investors. This aligns with findings by Cojoianu et al. (2021) and Gerged et al. (2021) those who emphasize that environmental transparency plays a key role in managing reputational risk and enhancing firm valuation. However, the empirical evidence is not entirely consistent. Other studies report a negative association between environmental actions and financial outcomes. For instance, Khan et al. (2024) observe that excessive environmental investments may reduce earnings per share, indicating a potential trade-off between environmental responsibility and accounting profitability. Pekovic et al. (2018) provide a nuanced perspective, identifying an inverted U-shaped relationship between environmental performance and market value among Frenchlisted companies. This recommends that while moderate environmental efforts enhance firm value, excessive engagement may lead to diminishing returns. Regional perspectives, Asian Journal of Economics and Banking 367 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 particularly from China’s state-led environmental governance system, add valuable context (Chen and Li, 2024). The Chinese regulatory environment strongly incentivizes firms to adopt green practices through policy mechanisms, subsidies, and environmental scorecards. This top-down approach creates unique pressures and opportunities for firms, differentiating the Chinese context from more market-driven regulatory environments in the West (Zhang et al., 2024; Zhang et al., 2024). Hence, understanding environmental performance in China requires accounting for its institutional setting and government influence on corporate sustainability behavior. Drawing from this mixed evidence, we propose the following hypotheses: H2a. Environmental performance has a positive impact on corporate profitability. H2b. Environmental performance has a negative impact on corporate profitability. 2.5 Social performance and corporate profitability Social performance encompasses a wide range of practices, including workforce diversity, employee welfare, community engagement, health and safety standards, social risk management, and product responsibility. These dimensions contribute not only to a company’s ethical image but also to its financial standing. Empirical evidence suggests that strong social initiatives can significantly enhance firm performance. For instance, GarridoRuso et al. (2024), found that various facets of social performance, such as gender diversity, employee motivation, training, and product quality, positively influence the financial outcomes of firms in the tourism sector. Ding and Lee (2024) Argue that effective social strategies reduce investor-related risks and enhance perceptions of management quality, thereby giving firms a competitive edge. In line with this, Albuquerque et al. (2019) Emphasize that companies with higher social investments often experience reduced systemic risk and enhanced firm value, particularly when social responsibility is integrated into product differentiation strategies. Social investments can also elevate employee satisfaction, leading to higher productivity and innovation. Moreover, a strong record in corporate social responsibility (CSR) helps to build a positive public image and solidify stakeholder trust (Thomas et al., 2024). From a strategic perspective, aligning social objectives with business goals allows companies to evolve from a purely profit-driven orientation to a socially responsible business model (Azmi et al., 2021). However, this relationship is not universally positive. Eccles et al. (2020) Caution that while strong financial performance may encourage firms to engage in CSR, the reverse does not always hold; improved CSR practices do not necessarily result in better financial performance. Furthermore, Pekovic and Vogt (2021) Find that under certain ownership structures, particularly those with high concentration, CSR engagement may have a detrimental effect on firm profitability. Given the mixed empirical findings and contextual differences, the relationship between social performance and corporate profitability remains a subject of ongoing debate. Thus, we propose the following hypotheses: H3a. Social performance has a positive impact on corporate profitability. H3b. Social performance has a negative impact on corporate profitability 2.6 Governance performance and corporate profitability Corporate governance encapsulates a range of mechanisms designed to ensure accountability, transparency, and fairness in a company’s relationships with its stakeholders. These mechanisms include board composition, executive compensation, anti-corruption practices, shareholder rights, organizational structure, and customer protection policies. Among these, board structure and ownership design are among the most frequently studied in the context of corporate financial performance. Empirical evidence on the impact of governance performance on profitability presents mixed findings. For example, Fahad and Busru (2021) Analyzed Indian-listed firms and observed a negative association between governance-related AJEB 9,3 368 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 ESG scores and return on assets (ROA). In contrast, Wu et al. (2023), demonstrated a positive impact of governance performance on ROA, signifying that effective governance mechanisms can enhance firm outcomes. One important governance factor is the board leadership structure. Banerjee et al. (2020) and Braun and Sharma (2007) warned that a dual role where the board chair also serves as a top executive can compromise board independence and harm firm value. Similarly, empirical studies (Karamanou and Vafeas, 2005; Petersen, 2009) have raised concerns about concentrated ownership, arguing that dominance (Karamanou and Vafeas, 2005; Petersen and Vredenburg, 2009) Major shareholders can undermine minority shareholder interests and reduce firm value. This concern is particularly relevant in the Chinese context, where state and institutional ownership are prevalent in listed firms, potentially affecting governance efficiency. On the other hand, internal governance elements, such as human capital practices, are positively associated with financial outcomes. Studies highlight that employee-centric governance through fair compensation, flexible work arrangements, diversity, and satisfaction enhances innovation, ROA, and return on equity (Adu, 2022; Gregory, 2022; Sehen Issa et al., 2022; Shafeeq Nimr Al-Maliki et al., 2023). These findings accentuate the strategic importance of integrating social and governance priorities in corporate decision-making. There is also growing interest in how governance-related disclosures affect investor perceptions and firm performance. Nekhili et al. (2021) explored the role of employee representation on corporate boards, finding it potentially detrimental to investor confidence, even when aggregate ESG performance is high. Meanwhile, Salehi and Bashirimanesh (2024) argue that moderate levels of ESG disclosure, neither too limited nor overly extensive, are optimal for firm efficiency, as they balance transparency and cost. In the Chinese market, which is characterized by state-driven governance reforms and regulatory oversight, understanding how governance performance shapes profitability is increasingly vital. Srairi (2024) concludes that governance effectiveness, coupled with risk mitigation, significantly boosts ESG-related value creation. Based on the mixed but insightful body of literature, this study aims to explore how governance performance influences the profitability of listed banks in China. Accordingly, we propose the following hypotheses: H4a. Governance performance has a positive impact on corporate profitability. H4b. Governance performance has a negative impact on corporate profitability. 3. Methodology 3.1 Data and sample This study analyzes the impact of ESG performance on corporate profitability using data from listed commercial banks on China’s Shanghai and Shenzhen stock exchanges between 2012 and 2022. The sample includes 42 banks of various types: five large state-controlled commercial banks (SOCBs), ten joint stock commercial banks (JSCBs), ten rural commercial banks (RCBs), and seventeen urban commercial banks (UCBs). Financial data were sourced from the China Stock Market and Accounting Research (CSMAR) database, and ESG data were obtained from the Chinese Research Data Services Platform (CNRDS). The ESG scores in CNRDS integrate both self-reported ESG disclosures and third-party verified assessments. This hybrid approach aligns with domestic and international ESG frameworks, enhancing objectivity and reducing the risk of greenwashing. Companies and firms that were delisted or had missing financial or ESG data were excluded from the sample. Additionally, all continuous variables were winsorized at the 1st and 99th percentiles to minimize the influence of outliers. 3.2 Variables and measurement Following previous literature, we use return on assets (ROA) as our main measure of corporate profitability, as it captures the historical performance well (Chen et al., 2023a, b; Khan, 2022; Asian Journal of Economics and Banking 369 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 Prashar, 2023). The ESG score from ESG score, Env score, Soc score, and Gov score as the main independent variables, ESG performance, and ESG performance individual components as used by other scholars (Bae et al., 2021; Shakil, 2021; Zhou and Wen, 2022), obtained from CNRDS, which is rated based in line with disclosure standards such as ISO 26000, GRI standards, SASB standard, domestic and foreign well-established ESG databases, combined with China’s relevant policies for ESG information. In addition, we control for factors that affect firm profitability based on previous studies (Chen et al., 2023a, b; D� ıaz et al., 2021; Ding and Lee, 2024; Qu and Zhang, 2023). We control for equity concentration, cash asset ratio, growth capacity, leverage, board size, board independence, and firm size to prevent estimation bias caused by omitted variables that could also affect corporate profitability. See Table 1 for detailed measurements and definitions of the study’s variables. 3.3 Empirical model This paper used the static model 1 and 2 to check for fixed effect issues and dynamic model (3) to test how ESG in year t-1 impact corporate profitability while model (4) is to investigate the impact of the three components of ESG in year t-1 using panel data of listed commercial banks from 2012 to 2022. ROA it ¼ β 0 þ β 1 ESG i;t þ φ X Controls it þ α i þ λ t þ ε it (1) ROA it ¼ β 0 þ β 1 Env i;t þ β 2 Soc it þ β 3 Gov it þ φ X Controls it þ α i þ λ t þ ε it (2) ROA it ¼ β 0 þ β 1 ROA i;t−1 þ β 2 ESG it−1 þ φ X Controls it þ α i þ λ t þ ε it (3) ROA it ¼ β 0 þ β 1 ROA i;t−1 þ β 2 Env it−1 þ β 3 Soc it−1 þ β 4 Gov it−1 þ φ X Controls it þ α i þ λ t þ ε it (4) Where i,t represents firm i in year t, α i is the individual-specific, λ t time-specific effect and ε it error term. Table 1 provides a detailed explanation of study variables and their measurement. The study applies two-way fixed-effect models for static. In addition, for further analysis, the two-step system generalized method of moments (GMM) estimator for equations 3 and 4, in line with previous studies that use dynamic models (Al-Malkawi and Javaid, 2018; Chen et al., 2024a, b; Nguyen et al., 2022). The GMM estimator can solve endogenous problems due to the presence of a lagged dependent variable as an independent variable in the model. 4. Empirical results and discussion 4.1 Descriptive statistics Table 2 summarizes descriptive statistics based on 303 firm-year observations from 2012 to 2022. The average ROA and ROE are 0.038 and 0.063, indicating moderate profitability across the sample. ESG scores exhibit limited variation (mean 5 0.733; SD 5 0.050), suggesting a generally consistent ESG disclosure level among listed banks. On average, banks demonstrate moderate firm size (mean 5 22.204) and leverage (0.423), though liquidity, as captured by the cash asset ratio (CAR), is relatively low (mean 5 0.047), reflecting potential short-term funding pressures. Growth opportunities (GRW) are highly dispersed, and the average bank age is approximately 2.07 (log-transformed), indicating a relatively young sector in capital market terms. Governance characteristics suggest moderate board independence (mean B_indp 5 0.377), relatively small boards (mean Bsize 5 2.115 in log form), and AJEB 9,3 370 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 Table 1. Variables, acronyms, measurement Variable Parameters Symbol Definition Source Reference Dependent Firm Performance ROA it The ratio of net income to total assets of firm i in year t CSMAR Chen et al. (2023a, b), Elamer and Boulhaga (2024), Khan (2022) ROE it Natural logarithm of (Revenue divided by total carbon emissions) of firm i in year t CSMAR Prashar (2023), Truong (2024), Zimon et al. (2022) TobinsQ it The ratio of firm market value to the asset’s replacement value of firm i in year t CSMAR Khan (2022), Truong (2024), Zimon et al. (2022) Independent ESG score ESG it The ESG average score assigned to each firm is based on the Environmental, Social, and Governance pillars. Range from 0–100 score CNRDS Bae et al. (2021), Dossa (2025), Shakil (2021) Environmental score Env it It represents the weighted average of all key issues that fall under the environment pillar performance CNRDS Bae et al. (2021), Dossa (2025), Shakil (2021) Social score Soc it It represents the weighted average of all key issues that fall under the social pillar performance CNRDS Bae et al. (2021), Dossa (2025), Shakil (2021) Governance score Gov it It represents the weighted average of all key issues that fall under the governance pillar performance CNRDS Bae et al. (2021), Dossa (2025), Shakil (2021) Controls Size Size it Natural logarithm of total asset CSMAR Chen et al. (2023a, b), Ding and Lee (2024), Veeravel et al. (2024) Leverage Lev it The ratio of total liabilities to total assets CSMAR Casciello et al. (2024), D� ıaz et al. (2021) Cash asset ratio CAR it Cash and cash equivalent/Total asset CSMAR Agnese et al. (2024), Azmi et al. (2021), Zhang et al. (2024) Firms’ growth GRW it The sales growth of the firm is calculated as (Sales t – Sales t-1 )/Sales t-1 CSMAR D� ıaz et al. (2021), Ding and Lee (2024), Zhang et al. (2024) Firm Age Age it Natural logarithm of years since firms have been established CSMAR D� ıaz et al. (2021), Ding and Lee (2024), Zhang et al. (2024) (continued ) Asian Journal of Economics and Banking 371 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 performance and profitability at the 10% level (coefficient: �0.002). This finding aligns with legitimacy theory (Buallay, 2019), which suggests that ESG practices in urban institutions may be more driven by societal expectations and regulatory pressure than by strategic value creation. Urban banks face heightened scrutiny and higher operational costs associated with ESG implementation, such as emissions reporting, green lending regulations, and labor compliance. As such, these efforts may result in a short-term trade-off between compliance and profitability, though potentially yielding reputational or long-term gains. Conversely, rural banks show a slightly positive relationship between ESG performance and profitability, statistically significant at the 1% level (coefficient: 0.005). This is likely because these banks prioritize social ESG dimensions, such as community outreach, inclusive banking, and support for local development initiatives that build customer loyalty and social trust. Stakeholder engagement theory and real-world examples like the Grameen Bank (Yunus, 2010) illustrate how such banks, operating in underserved regions, can achieve social impact Table 5. The impact of ESG on corporate profitability (state-owned bank, non-state-owned bank, joint stock, non-joint, rural, and Urban banks) Variables (1) (2) (3) (4) (5) (6) SOCB Non-SOCB Joint Non-joint Rural Urban ROA ROA ROA ROA ROA ROA ESG �0.012*** 0.008*** 0.006*** �0.003*** 0.005*** �0.002*** (0.004) (0.002) (0.002) (0.001) (0.002) (0.002) Size 0.008*** 0.010*** 0.009*** 0.007*** 0.011*** 0.006*** (0.002) (0.001) (0.001) (0.002) (0.001) (0.002) Lev �0.120*** �0.150*** �0.130*** �0.140*** �0.110*** �0.160*** (0.010) (0.008) (0.009) (0.008) (0.010) (0.009) CAR 0.150** 0.200** 0.180** 0.160** 0.170** 0.140** (0.060) (0.050) (0.055) (0.065) (0.055) (0.060) GRW 0.025*** 0.030*** 0.028*** 0.022*** 0.035*** 0.020*** (0.005) (0.004) (0.004) (0.0505) (0.004) (0.005) Age �0.008** �0.010** �0.009** �0.007** �0.012** �0.006** (0.003) (0.002) (0.003) (0.004) (0.003) (0.003) B_Indp �0.010** �0.012** �0.011** �0.009** �0.015** �0.008** (0.005) (0.004) (0.004) (0.005) (0.004) (0.005) Bsize 0.003 0.002 0.004* 0.001 0.005** �0.002 (0.003) (0.002) (0.002) (0.003) (0.002) (0.003) Top1 0.038*** 0.045*** 0.042*** 0.035*** 0.050*** 0.030*** (0.008) (0.006) (0.007) (0.008) (0.006) (0.008) Duality �0.001 0.003*** 0.002** 0.001 0.004*** 0.001 (0.001) (0.002) (0.001) (0.001) (0.002) (0.001) Bgender 0.008*** 0.012*** 0.010*** 0.007*** 0.015*** 0.006*** (0.003) (0.002) (0.002) (0.003) (0.002) (0.003) Liq 0.013*** 0.011*** 0.004*** 0.013*** 0.002*** 0.031*** (0.002) (0.001) (0.003) (0.002) (0.002) (0.003) Constant �0.162*** �0.185*** �0.042*** �0.294*** �0.042*** �0.005*** (0.006) (0.008) (0.009) (-0.026) (0.089) (0.009) Observations 55 248 96 207 52 100 R-squared 0.950 0.951 0.404 0.395 0.404 0.395 Number of firms 5 37 10 32 10 17 Firm FE YES YES YES YES YES YES Year FE YES YES YES YES YES YES Note(s): This table reports fixed effects regression results estimating the effect of ESG performance on return on assets (ROA) across different bank categories: state-owned (SOCB), non-state-owned, joint-stock, non-jointstock, rural, and urban banks. All models include firm and year fixed effects. Robust standard errors are in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively Source(s): Authors’ own work AJEB 9,3 378 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 while maintaining financial stability. ESG efforts thus act as differentiators that help rural banks strengthen their local customer base and secure long-term sustainability. These findings emphasize that ESG performance does not yield uniform outcomes across all banks. Instead, its impact depends on organizational structure, governance mechanisms, regulatory exposure, and geographic positioning. Policymakers should consider these contextual differences when designing ESG-related regulations or incentives, and investors must assess ESG outcomes in light of bank type and environment. Bank managers, meanwhile, should tailor ESG strategies to align with their institutional characteristics, ensuring that sustainability goals are integrated into profitable and pragmatic business models. 4.5 Robustness check and further analysis 4.5.1 Endogeneity test. To address potential endogeneity concerns arising from omitted variable bias or reverse causality between ESG performance and firm profitability, this study employs a two-stage least squares (2SLS) instrumental variable (IV) approach, following prior empirical studies (El Ghoul et al., 2011; Fiorillo et al., 2025; Kuai et al., 2025; Yu et al., 2024). We use the average ESG scores of other firms operating in the same city, province, or industry as instruments for firm-level ESG performance. These instruments are theoretically and empirically justified on two grounds: first, regarding relevance, firms located in the same geographic or industry context often face similar regulatory pressures, social expectations, and stakeholder norms, which leads to convergence in ESG behavior. This is supported by the strong first-stage results in Table 6, where the instruments significantly predict firm-level ESG scores at the 1% level. Second, concerning exclusion restriction, while regional or industry-average ESG levels influence a firm’s ESG disclosure practices, they are unlikely to directly affect the profitability of the firm (ROA), once the firm’s own ESG score is controlled for. These broader averages reflect exogenous environmental and institutional conditions that shape ESG behavior, but not firmspecific operational outcomes. Thus, their impact on ROA is assumed to be mediated solely through firm-level ESG, satisfying the exclusion restriction. Table 6 presents the results. The first-stage regressions (Models M1, M3, M5) demonstrate strong, statistically significant associations between the instruments and firm-level ESG. In the second stage (Models M2, M4, M6), ESG remains positively associated with ROA, with coefficients ranging from 0.076 to 0.321, all statistically significant. Diagnostic tests support the validity of our instruments. The Cragg-Donald Wald F-statistics and Kleibergen-Paap rk LM statistics are well above the standard thresholds, indicating that the instruments are not weak. Furthermore, the Hansen J test fails to reject the null hypothesis of instrument validity, suggesting that the instruments are not correlated with the error term in the second stage. Collectively, these results confirm that ESG performance has a causal and robust effect on firm profitability, and that our instrument set is both valid and effective for addressing endogeneity concerns. 4.5.2 Change of dependent variable, independent variable. To ensure the robustness of the results, the study changes both the independent and dependent variables. The robustness test results in Table 7 examine the impact of different ESG ratings (from CNRDS and Bloomberg) on corporate profitability, with the dependent variable changed to ROE and Tobin’s Q. In the first two columns (M1 and M2), ESG ratings from CNRDS are used with ROE and Tobin’s Q as dependent variables, demonstrating a positive impact of ESG ratings on corporate profitability. Specifically, CNRDS ESG ratings significantly influence ROE (0.117, p < 0.01) and Tobin’s Q (0.411, p < 0.10). The next two columns (M3 and M4) utilize ESG ratings from Bloomberg, showing that ESG ratings positively affect ROA and ROE, with coefficients of 0.002 (p < 0.01) for ROA and 0.005 (p < 0.01) for ROE. These results indicate that ESG performance, regardless of whether measured by CNRDS or Bloomberg ratings, significantly enhances corporate profitability and market valuation. Furthermore, the consistency of these findings, despite changes in both dependent and independent variables, strengthens the Asian Journal of Economics and Banking 379 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 Table 6. Endogeneity resolution using 2SLS instrumental variable approach Variable 1st stage 2nd stage 1st stage 2nd stage 1st stage 2nd stage (M1) (M2) (M3) (M2) (M3) (M4) ESG ROA ESG ROA ESG ROA ESG_City (IV) 0.861*** (0.012) – – – – – ESG_ Province (IV) – – 0.821*** (0.026) – – – ESG_ Industry (IV) – – – – 0.013*** (0.003) – ESG – 0.138*** (0.019) – 0.076** (0.034) – 0.321*** (0.093) Size 0.013*** (0.000) 0.007*** (0.000) 0.014*** (0.000) 0.008*** (0.001) 0.015*** (0.000) 0.328*** (0.037) Lev �0.042*** (0.002) �0.103*** (0.002) �0.047*** (0.002) �0.106*** (0.003) �0.050*** (0.002) �0.148 (0.175) CAR 0.018*** (0.004) 0.287*** (0.005) 0.019*** (0.004) 0.288*** (0.005) 0.023*** (0.004) 1.010*** (0.262) GRW �0.002*** (0.001) 0.035*** (0.001) �0.003*** (0.001) 0.034*** (0.001) �0.003*** (0.001) �0.114 (0.165) Age �0.008*** (0.000) �0.007*** (0.000) �0.010*** (0.000) �0.008*** (0.000) �0.011*** (0.000) 0.095*** (0.025) B_Indp 0.070*** (0.000) �0.027*** (0.006) 0.079*** (0.006) �0.022*** (0.007) 0.073*** (0.006) �0.022** (0.009) Bsize 0.010*** (0.002) 0.008*** (0.002) 0.011*** (0.002) 0.008*** (0.002) 0.007*** (0.002) 0.091* (0.055) Top1 0.012*** (0.002) 0.030*** (0.002) 0.012*** (0.002) 0.030*** (0.002) 0.010*** (0.002) �0.157 (0.359) Duality �0.003*** (0.008) �0.002*** (0.001) �0.003*** (0.001) �0.002*** (0.001) �0.002*** (0.001) 0.034 (0.153) Bgender 0.010*** (0.002) 0.010*** (0.002) 0.012*** (0.002) 0.011*** (0.229) 0.011*** (0.013) 0.018 (0.241) Liq 0.001*** (0.002) 0.003*** (0.001) 0.016*** (0.002) 0.021*** (0.012) 0.014*** (0.014) 0.016 (0.041) Constant �0.209*** (0.011) �0.918*** (0.042) �0.206*** (0.020) �0.918*** (0.002) 0.383*** (0.007) 0.918*** (0.042) CraggDonald Wald 4235.96 4235.963 1155.83 1155.835 14.98 14.975 KleibergenPaap 4802.77 4802.775 996.86 996.865 15.93 15.933 Hansen J Statistics – 0.000 – 0.000 – 0.000 AndersonRubin Wald 0.0000 – 0.0277 – 0.0000 – Stock-wright LM 0.0000 – 0.0278 – 0.0000 – Year FE Yes Yes Yes Yes Yes Yes Firm FE Yes Yes Yes Yes Yes Yes Obs 303 303 303 303 303 303 Note(s): This table presents the results from the two-stage least squares (2SLS) approach used to address endogeneity issues. In the first stage (M1, M3, M5), the instrument variables (IV) for ESG are used to predict ESG scores. In the second stage (M2, M4, M6), the estimated ESG values are then regressed on corporate profitability, measured by ROA, to resolve potential endogeneity problems. ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively. Robust standard errors are reported in parentheses for all columns Source(s): Authors’ own work AJEB 9,3 380 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 robustness and reliability of the relationship between ESG performance and corporate profitability. 4.5.3 Simultaneity issues. Table 8 presents the results from addressing potential simultaneity issues and concerns in the relationship between ESG and corporate profitability. The first-stage results in column M1 report the instrumented variable, ESG_L, while columns M2 through M4 examine the dynamic relationship by incorporating one-period lag values for the independent and control variables. In column M1, ESG lagged by one period (ESG t-1) significantly influences ROA (0.039, p < 0.01) and ROE (0.079, p < 0.01), indicating that past ESG performance has a positive effect on future profitability. Columns M2 and M4 show similar results for ESG’s impact on ROA and ROE, with coefficients of 0.037 (p < 0.01) and 0.108 (p < 0.01), respectively, reinforcing the positive effect of ESG on profitability. Control variables such as Size, Leverage, Cash Flow from Operations (CFLOA), Growth, and Top1 (the largest shareholder) also exhibit significant relationships with firm performance, with lagged values showing robust correlations. The robustness of these findings is confirmed by the consistency of significant coefficients across multiple specifications. The results indicate that ESG, alongside other key financial factors, significantly drives corporate profitability, with adjustments for simultaneity further strengthening the reliability of the findings. 4.5.4 Change of estimation technique. The results from the System GMM analysis in Table 9 point to a clear and meaningful link between ESG performance and bank profitability in China. A higher ESG score is associated with better financial outcomes, specifically, a onestandard-deviation improvement in ESG performance is linked to a 1% point increase in return on assets (ROA), with the coefficient standing at 0.010 and statistically significant at the 1% Table 7. Robustness change of dependent and independent variable ΔVariables Corporate profitability ESG rating bloomberg (M1) (M2) (M3) (M4) ROE TBQ ROA ROE ESG 0.117*** (0.030) 0.411* (0.215) 0.002*** (0.000) 0.005*** (0.001) Size 0.029*** (0.016) �0.333*** (0.029) 0.013*** (0.001) 0.030*** (0.004) Lev �0.278 *** (0.021) �0.584 *** (0.103) �0.147*** (0.005) �0.279*** (0.016) CAR 0.334*** (0.021) 0.867*** (0.137) 0.180*** (0.008) 0.334*** (0.021) GRW 0.078*** (0.003) 0.175*** (0.023) 0.032*** (0.001) 0.078*** (0.003) Age �0.036 (0.034) 1.183*** (0.029) �0.011*** (0.001) �0.001 (0.003) B_Indp �0.036 (0.034) �0.079 (0.283) �0.014 (0.011) �0.035 (0.034) Bsize �0.004 (0.013) 0.107 (0.089) 0.001 (0.004) �0.004 (0.013) Top1 0.112*** (0.023) 0.502*** (0.160) 0.042*** (0.007) 0.112*** (0.023) Duality 0.007* (0.004) �0.008 (0.027) 0.002* (0.001) 0.007 * (0.004) Bgender 0.000* (0.004) 0.808*** (0.102) 0.000 (0.004) �0.022* (0.012) Liq 0.031*** (0.002) 0.013*** (0.001) 0.012*** (0.002) 0.001*** (0.001) Constant �0.023*** (0.012) 6.799*** (0.647) �0.186*** (0.025) �0.490*** (0.086) Firm FE Yes Yes Yes Yes Year FE Yes Yes Yes Yes Adjusted R 2 0.162 0.087 0.292 0.162 Obs 303 303 303 303 Note(s): The table presents robustness test results where the dependent variables have been changed to ROA (Return on Assets) and Tobin’s Q (TBQ). In the first two columns, ESG ratings from CNRDS are used to assess the impact on firm profitability. In the third column, ESG ratings from Bloomberg are employed to check their impact on firm profitability in terms of ROA and ROE. The p-values, calculated using robust standard errors, are reported in parentheses, with statistical significance indicated by ***, **, and * at the 1%, 5%, and 10% levels, respectively Source(s): Authors’ own work Asian Journal of Economics and Banking 381 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 level. When we break ESG down into its components, environmental and governance factors emerge as the strongest drivers of profitability, with coefficients of 0.020 and 0.013, respectively, both significant at the 1% level. Social factors also have a positive effect (0.017), though slightly weaker and significant at the 5% level. The positive and significant coefficient on lagged ROA (ranging from 0.235 to 0.248) reflects the persistence of profitability over time, consistent with prior research on dynamic panels. Importantly, all diagnostic tests support the validity and strength of our model. The Hansen and Sargan tests confirm the reliability of our instruments, while the lack of second-order autocorrelation and a favorable Durbin-Wu-Hausman test (p 5 0.11) confirm robustness and help rule out endogeneity concerns. Findings emphasize that investing in ESG, especially in environmental and governance dimensions, can pay off financially for banks, and these results hold steady even under alternative estimation methods like Difference GMM. 4.6 Further analysis of ESG individual components’ impact on corporate profitability Table 10 presents the impact of ESG individual components on corporate profitability (ROA) across different firm types in China’s banking sector. The findings show diverse relationships between ESG factors and profitability, influenced by the nature of the banks and their operational environments. Environmental (E) factors have a generally negative effect on profitability for State-Owned Commercial Banks (SOCBs) (�0.002, significant at the 1% level) and non-joint banks (�0.007, significant at the 1% level), likely due to the financial burden of complying with stringent environmental regulations in state-controlled sectors. This aligns with Buallay et al. (2019), who highlight how mandatory sustainability practices in heavily regulated sectors can impose short-term costs on profitability, supporting the trade-off Table 8. Simultaneity issues Variable Corporate profitability (M1) (M2) (M3) (M4) ROA ROA ROE ROE ESG t�1 0.039*** (0.010) 0.037*** (0.010) 0.079*** (0.029) 0.108*** (0.028) Size t�1 –�0.002*** (0.001) – �0.013*** (0.002) Lev t-1 –�0.024*** (0.004) –�0.012 (0.011) CFLOA t�1 – 0.114*** (0.007) – 0.219*** (0.017) Growth t�1 – 0.015*** (0.001) – 0.038*** (0.003) Age t�1 –�0.000 (0.001) – 0.001 (0.002) Ind_Dr t�1 –�0.004 (0.011) – 0.006 (0.028) Board t�1 –�0.004 (0.003) –�0.011 (0.010) Top1 t�1 – 0.012*** (0.004) – 0.044*** (0.012) Duality t�1 – 0.002 (0.001) – 0.004 (0.003) Bgender t�1 –�0.025*** (0.004) –�0.039*** (0.011) Liq t�1 0.021*** (0.004) 0.003*** (0.001) 0.003*** (0.001) 0.001*** (0.000) Constant 0.039*** (0.10) 0.082*** (0.017) 0.012*** (0.002) �0.065*** (0.006) Year FE Yes Yes Yes Yes Firm FE Yes Yes Yes Yes Adjusted R 2 0.014 0.092 0.005 0.055 Obs 303 303 303 303 Note(s): This table presents results from the simultaneity approach, addressing potential endogeneity in the relationship between ESG and corporate profitability. The first-stage results in column M1 show the instrumented variable, ESG_L, while M2 reports the panel regression using the estimated ESG values. M3 and M4 examine the dynamic relationship by including a one-period lag for the independent and control variables. ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively. Robust standard errors are reported in parentheses for all columns Source(s): Authors’ own work AJEB 9,3 382 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 theory (Pham et al., 2021). In contrast, non-SOCBs (0.004, significant at the 1% level) and Joint Banks (0.005, significant at the 1% level) show positive effects, suggesting that green investments align with business strategies and enhance profitability, especially with the integration of foreign expertise in green finance. Interestingly, the positive environmental coefficient for SOCBs challenges the findings of Khan et al. (2024), signifying that China’s unique policy landscape might enable faster returns from green investments compared to other jurisdictions. Social (S) components also yield mixed results. For SOCBs, the coefficient is negative (�0.007, significant at the 1% level), indicating that social initiatives may not yield immediate financial returns, possibly due to state-imposed inefficiencies and rigid compliance frameworks. However, for Non-SOCBs (0.012, significant at the 1% level), Joint Banks (0.010, significant at the 1% level), and Rural Banks (0.015, significant at the 1% level), positive effects are observed. These results reflect that socially responsible practices, such as community engagement and employee welfare, enhance customer trust and lead to increased business performance, findings consistent with stakeholder theory (Freeman, 2010) and the global evidence of Zhang and Lucey (2022). Specifically, rural banks’ strong social performance empirically supports Yunus’ (2010) microfinance model, where local engagement drives profitability by strengthening community ties. Governance (G) factors show a negative effect for urban banks (�0.003, significant at the 1% level), proposing that the complex governance requirements in urban settings increase operational costs. This finding supports the “compliance cost hypothesis” outlined by Maji and Lohia (2023), which argues that urban banks face elevated regulatory burdens that may offset governance benefits. On the other hand, non-SOCBs (�0.004, significant at the 1% level) and Rural Banks (�0.001, Table 9. System GMM (1) (2) (3) Variables GMM-ESG (Collapsed) GMM-E-S-G (Robust) Diff-GMM (Robustness) Full sample ROA ROA ESG 0.010*** 0.009*** (0.021) (0.019) Env 0.020*** – (0.031) – Soc 0.017*** – (0.035) – Gov 0.013** – (0.024) – L.ROA 0.235*** 0.248*** 0.221*** (0.485) (0.341) (0.402) Controls YES YES YES Constant �0.162* �0.185* �0.042 (0.006) (0.008) (0.089) AR (1) (p-value) 0.077 0.082 0.085 AR (2) (p-value) 0.732 0.566 0.701 Hansen (p-value) 0.722 0.874 0.815 Sargan test (Prob > Chi2) 0.903 0.70 Hansen test 0.722 0.874 Note(s): This table reports dynamic panel estimates using System GMM and Difference GMM to assess the impact of ESG and its components on ROA. Models account for potential endogeneity with lagged dependent variables and include firm-level controls. Standard errors are robust to heteroskedasticity. Diagnostic tests (AR (1), AR (2), Hansen, and Sargan) confirm instrument validity and model specification. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively Source(s): Authors’ own work Asian Journal of Economics and Banking 383 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 significant at the 5% level) also show negative coefficients, potentially reflecting the costs of implementing governance structures in environments with limited regulatory support. Notably, Joint Banks report a marginally positive governance effect (0.001), extending the insights of B� atae et al. (2021) by illustrating how joint ventures’ hybrid governance models, often combining domestic and foreign oversight, can better balance compliance efforts with performance gains. The results suggest that the nature of the bank (state-owned vs private, urban vs rural) plays a significant role in how ESG factors influence profitability. State-owned banks are likely constrained by government priorities that emphasize non-financial objectives, resulting in less favorable ESG-profitability relationships. In contrast, private and joint banks benefit more from market-driven ESG practices, where green and social initiatives align with Table 10. ESG individual components and corporate profitability Variables (1) (2) (3) (4) (5) (6) SOCB Non-SOCB Joint Non-joint Rural Urban ROA ROA ROA ROA ROA ROA Env �0.002*** 0.004*** 0.005*** �0.007*** 0.003*** �0.006*** (0.001) (0.002) (0.002) (0.004) (0.002) (0.002) Soc �0.007*** 0.012*** 0.010*** 0.013*** 0.015*** 0.001 (0.003) (0.002) (0.002) (0.002) (0.002) (0.002) Gov �0.005** �0.004*** 0.001* 0.0002* �0.001** �0.003*** (0.003) (0.001) (0.001) (0.001) (0.001) (0.001) Size 0.004*** 0.012*** 0.003*** 0.006*** 0.013*** 0.006*** (0.002) (0.001) (0.001) (0.002) (0.001) (0.002) Lev �0.004*** �0.145*** �0.130*** �0.120*** �0.140*** �0.120*** (0.010) (0.008) (0.009) (0.008) (0.010) (0.009) CAR 0.042** 0.121** 0.170** 0.150** 0.150** 0.120** (0.060) (0.050) (0.055) (0.065) (0.055) (0.060) GRW 0.006*** 0.038*** 0.001*** 0.003*** 0.034*** 0.022*** (0.005) (0.004) (0.004) (0.0505) (0.004) (0.005) Age �0.045** �0.013** �0.041** �0.002** �0.012** �0.004** (0.003) (0.002) (0.003) (0.004) (0.003) (0.003) B_Indp �0.010** �0.012** �0.011** �0.009** �0.015** �0.008** (0.005) (0.004) (0.004) (0.005) (0.004) (0.005) Bsize 0.006 0.002 0.004* 0.001 0.005** �0.002 (0.003) (0.002) (0.002) (0.003) (0.002) (0.003) Top1 0.004*** 0.041*** 0.081*** 0.033*** 0.046*** 0.030*** (0.006) (0.005) (0.005) (0.006) (0.006) (0.005) Duality �0.004 0.005*** 0.006** 0.002 0.005*** 0.001 (0.001) (0.002) (0.001) (0.001) (0.002) (0.001) Bgender 0.007*** 0.014*** 0.012*** 0.006*** 0.013*** 0.006*** (0.003) (0.002) (0.002) (0.003) (0.002) (0.003) Liq 0.009*** 0.013*** 0.014*** 0.009** 0.015*** 0.006** (0.002) (0.001) (0.003) (0.002) (0.002) (0.003) Constant �0.162*** �0.185*** �0.042*** �0.294*** �0.042*** �0.005*** (0.006) (0.008) (0.009) (�0.026) (0.089) (0.009) Observations 55 248 96 207 52 100 R-squared 0.921 0.892 0.851 0.882 0.912 0.874 Number of firms 5 37 10 32 10 17 Firm FE YES YES YES YES YES YES Year FE YES YES YES YES YES YES Note(s): This table presents fixed effects regression estimates of the relationship between the environmental (Env), social (Soc), and governance (Gov) components of ESG performance and return on assets (ROA), across different bank categories. All models include firm and year fixed effects. Robust standard errors are shown in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively Source(s): Authors’ own work AJEB 9,3 384 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 profitability goals. Joint banks, in particular, benefit from cross-border governance integration, while rural banks leverage social initiatives to foster community connections and improve financial performance, echoing the success model of microfinance institutions like Grameen Bank (Ahmed Chowdhury and Somani, 2020; Yunus et al., 2010). These findings reinforce the importance of tailoring ESG strategies to a firm’s institutional and operational context to maximize financial and societal value. 4.7 Summary of hypothesis testing results To consolidate the empirical findings across different models and subgroups, Table 11 summarizes the outcomes of hypothesis testing. The results confirm that ESG-performance relationships vary across bank types and components. While positive profitability effects dominate in private and joint-stock banks, state-owned and urban banks exhibit more constrained or negative associations, especially in the environmental and governance dimensions. 5. Conclusion, implications, and limitations 5.1 Conclusion The study analyzes the impact of ESG performance on the corporate profitability (CP) of listed Chinese commercial banks, considering their nature difference from 2012 to 2022 with a focus Table 11. Summary of hypothesis testing results Hypothesis Description Result Supported? Remarks H1a ESG performance positively influences profitability Supported in NonSOCBs, JSCBs, RCBs Yes Strong positive coefficients at 1% level H1b ESG performance negatively influences profitability Supported in SOCBs, UCBs Yes SOCBs (�0.012), UCBs (�0.002) H2a Environmental performance positively impacts profitability Supported in NonSOCBs, JSCBs Yes Coefficients: 0.004 and 0.005 at 1% level H2b Environmental performance negatively impacts profitability Supported in SOCBs, NonJSCBs Yes Coefficients: �0.002 and �0.007 at 1% level H3a Social performance positively impacts profitability Supported in NonSOCBs, JSCBs, RCBs Yes Strongest for RCBs (0.015), all significant at 1% H3b Social performance negatively impacts profitability Supported in SOCBs Yes Coefficient: �0.007 at 1% level H4a Governance performance positively impacts profitability Weak evidence in JSCBs only Partially JSCBs (0.001, marginal) H4b Governance performance negatively impacts profitability Supported in UCBs, Non-SOCBs, RCBs Yes Negative coefficients across groups, significant at 1–5% Note(s): This table summarizes the results of hypotheses H1a–H4b across different bank types. The findings reflect the heterogeneity in the relationship between ESG components (Environmental, Social, and Governance) and corporate profitability (ROA). “Supported” indicates statistical significance in the expected direction; “Not Supported” denotes insignificant or opposite-direction results. Significance levels are based on p-values: ***p < 0.01, **p < 0.05, *p < 0.1 Source(s): Authors’ own work Asian Journal of Economics and Banking 385 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 on how institutional characteristics shape this relationship. The findings highlight significant differences across various types of banks, recommending that ESG’s impact on profitability is not uniform but rather contingent on the bank’s nature and institutional context. For stateowned commercial banks (SOCBs), the study reveals a negative association between ESG performance and profitability, which supports the trade-off theory. This indicates that the costs associated with ESG compliance, often driven by policy mandates, may outweigh immediate financial gains. On the other hand, non-state-owned commercial banks (non-SOCBs), jointstock commercial banks (JSCBs), and rural commercial banks (RCBs) generally experience a positive relationship between ESG performance and profitability. This finding aligns with stakeholder theory, which advocates that market-oriented institutions can convert sustainability efforts into competitive advantages, thereby enhancing long-term financial performance. The study also emphasizes the urban-rural divide in ESG impacts. Urban banks often face challenges due to compliance-heavy ESG frameworks, while rural banks leverage community-focused initiatives that contribute to profitability. These findings are robust across various econometric techniques, including system GMM and instrumental variable approaches, underscoring that the financial implications of ESG initiatives should be assessed within the specific regulatory and institutional context of each bank type. Ultimately, the study calls for tailored ESG strategies that consider the unique characteristics and operating environments of different banks. 5.2 Theoretical and practical implications The varying impacts of ESG performance across different types of banks offer valuable theoretical and practical insights. Theoretically, this study integrates multiple perspectives. It affirms the role of stakeholder theory in explaining ESG-driven success within marketoriented, flexible institutions, while also showing that trade-off theory and legitimacy theory better capture the ESG adoption challenges faced by policy-driven or geographically constrained banks. This highlights the importance of contextualizing ESG efforts rather than applying uniform expectations across institutions. Additionally, institutional theory (DiMaggio and Powell, 1983) provides a compelling framework for understanding the variation in ESG practices across different types of banks. State-owned banks, shaped by strong regulatory mandates and public service obligations, primarily operate under coercive institutional pressures rules, laws, and policies imposed by the state. These banks often pursue ESG compliance as a means of fulfilling national objectives, such as environmental protection and social equity, rather than immediate financial gain. Their ESG engagement is largely driven by alignment with government-led sustainability agendas, exemplified by instruments like the Green Credit Guidelines and financial inclusion mandates. In contrast, joint-stock and urban commercial banks are more exposed to mimetic pressures, which arise from the tendency to imitate successful peers in uncertain or competitive environments. These banks adopt ESG practices strategically, not only to remain competitive but also to meet evolving stakeholder expectations and signal legitimacy to investors. Similarly, rural commercial banks experience a mix of mimetic and normative pressures, where professional standards and community engagement norms influence their ESG behavior often focusing on social sustainability through local development and inclusive financing. By explicitly recognizing how different types of institutional pressures shape ESG motivation coercive for state-owned, mimetic for market-driven, and normative for community-based institutions this study adds theoretical nuance to the ESG-performance nexus. Understanding these dynamics helps explain why the financial implications of ESG adoption differ across bank types. It also underscores the necessity of tailoring ESG strategies to fit each bank’s institutional context and prevailing pressure mechanisms. Practically, these insights stress the urgency of designing tailored ESG strategies based on the institutional nature. For instance: AJEB 9,3 386 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 (1) State-owned banks could benefit from more explicit regulatory guidance and preferential treatment when implementing ESG-related lending. China’s Green Credit Guidelines (2012) and PBOC’s Green Financial Reform Pilot Zones already represent early examples of tiered ESG regulation, offering flexible policy implementation in regions like Zhejiang and Guangdong. These initiatives can serve as scalable templates for differentiated ESG mandates. (2) Joint-stock banks, such as China Merchants Bank, have successfully issued green bonds and ESG-linked loans, reflecting the feasibility of market-based ESG strategies. These banks should be encouraged to scale such efforts with incentives like tax deductions for green financing returns. (3) Rural commercial banks, such as Jiangsu Rural Commercial Bank, have pioneered microfinance programs supporting sustainable agriculture. These banks could be further supported with policy subsidies to expand ESG-linked community development initiatives, reinforcing their role in rural revitalization. From a regulatory standpoint, our findings advocate for the adoption of tiered ESG frameworks that reflect institutional diversity. Rather than applying uniform ESG disclosure requirements, regulators like the China Banking and Insurance Regulatory Commission (CBIRC) should differentiate ESG benchmarks for state-owned, joint-stock, and rural banks. For example, CBIRC’s 2021 green finance guidelines can evolve into tiered systems by linking ESG compliance to each bank’s ownership, market exposure, and regional role. Investors should also interpret ESG signals within institutional contexts. A high ESG score at a joint-stock bank may indicate operational efficiency and market leadership, while a similar score at a state-owned bank may reflect regulatory compliance without profitability gains. Contextual awareness is thus essential for accurate ESG valuation. Policymakers must recognize these institutional dynamics. ESG policies and incentives should be stratified, e.g. introducing ESG performance-based subsidies for state-owned banks pursuing long-term green infrastructure projects, while allowing private banks more flexibility to innovate with ESG-linked investment products. Finally, bank managers must customize ESG strategies. State-owned banks should align ESG efforts with national strategic goals (e.g. “Dual Carbon” targets), even if financial returns are delayed. Joint-stock banks should integrate ESG into market differentiation strategies. Rural commercial banks, with their community focus, should emphasize social ESG dimensions such as financial inclusion, digital literacy, and green microfinance. 5.3 Future research directions Future studies could test the generalizability of our findings across different regulatory environments, particularly by comparing China’s state-driven model with Western marketbased systems. Cross-country analyses with diverse ESG frameworks would enhance the understanding of global ESG profitability dynamics. Additionally, with the growing influence of digital banking and fintech, research should explore how these innovations interact with ESG strategies and influence firm sustainability and profitability. Further, this study relied on CNRDS and CSMAR databases, which, while authoritative for Chinese listed firms, are focused on domestic frameworks. This may limit generalizability to other markets or unlisted firms, and CNRDS’s ESG metrics may differ from global standards. To address this, future research could draw on international ESG datasets such as Refinitiv, Bloomberg, or MSCI to enhance comparability and external validity. Finally, future work could adopt Bayesian analytical approaches as an alternative to frequentist methods, allowing for the integration of prior knowledge and offering a more nuanced interpretation of uncertainty in ESGperformance relationships. Asian Journal of Economics and Banking 387 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025 Zhou, F. and Wen, H. (2022), “Trade policy uncertainty, development strategy, and export behavior: evidence from listed industrial companies in China”, Journal of Asian Economics, Vol. 82, 101528, doi: 10.1016/j.asieco.2022.101528. Zhu, N., Aryee, E.N.T., Agyemang, A.O., Wiredu, I., Zakari, A. and Agbadzidah, S.Y. (2024), “Addressing environment, social and governance (ESG) investment in China: does board composition and financing decision matter?”, Heliyon, Vol. 10 No. 10, e30783, doi: 10.1016/ j.heliyon.2024.e30783. Zimon, G., Arianpoor, A. and Salehi, M. (2022), “Sustainability reporting and corporate reputation: the moderating effect of CEO opportunistic behavior”, Sustainability, Vol. 14 No. 3, p. 1257, doi: 10.3390/su14031257. Zumente, I. and Bistrova, J. (2021), “ESG importance for long-term shareholder value creation: literature vs Practice”, Journal of Open Innovation: Technology, Market, and Complexity, Vol. 7 No. 2, p. 127, doi: 10.3390/joitmc7020127. Further reading Arellano, M. and Bond, S. (1991), “Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations”, The Review of Economic Studies, Vol. 58 No. 2, p. 277, doi: 10.2307/2297968. Corresponding author Joel Victor Dossa can be contacted at: [email protected] For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: [email protected] AJEB 9,3 394 Downloaded from http://www.emerald.com/ajeb/article-pdf/9/3/364/10281595/ajeb-11-2024-0128en.pdf by ZBW German National Library of Economics user on 16 December 2025