Do quality earnings management practices reduce corporate ESG performance? The moderating effect of corporate governance mechanisms: Empirical evidence from emerging economies

Do quality earnings management practices reduce corporate ESG performance? 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The moderating effect of corporate governance mechanisms: Empirical evidence from emerging economies Muhammad Safdar, Basuki Basuki, Dian Agustia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9311011/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Responding to call in both the quality of earning management practices and corporate sustainability initiative literature to investigate the moderating effect of corporate governance mechanisms such as board gender diversity, board independence, audit committee independence and institutional or foreign ownership, this research filled corporate sustainability initiatives literature gaps by shedding the light on moderating effect of CG mechanisms on the quality of earning management practices and corporate ESG performance nexus. By utilizing a sample of 292 publicly listed companies in the context of emerging economies, countries such as Pakistan, Indonesia, and Malaysia are covered through their listed corporations for the period from 2016 to 2024 (2628 firm-year observations). By utilizing fixed-effects panel regression analysis with two-way clustered standard errors and country, year, industry, and firm fixed effects, the findings demonstrate that the quality of earnings management practices significantly reduces corporate ESG performance practices. All governance mechanisms, EM and ESG performance linkages, and the moderating effect of board gender diversity, board independence, and institutional ownership show a positive and significant moderating influence in Pakistan, Indonesia, and Malaysia, whereas AC independence shows no positive and significant moderating effect. Our study supported agency theory, resource dependence theory and stakeholders’ theory, which states that CG mechanisms lessen managerial exploitation of the resources which required for corporate sustainable investment and corporate sustainability initiative practices. Accounting EM discretionary accrual environmental social and governance performance CG mechanisms agency theory stakeholders’ theory resource dependence theory emerging economies Introduction Most researchers examining the association between the quality of earnings manipulation (EM) practices and corporate sustainability performance generally adopt one of three well-established approaches. The most effective approach is grounded in stakeholder theory, which posits that a firm’s societal relations extend beyond creditors and investors to encompass a broad coalition of stakeholder groups. Addressing these groups’ needs and expectations is inherently challenging, particularly in contexts characterized by information asymmetry. These scholars argue that the managers disclose higher-quality reporting and information in order to mitigate information asymmetry (Aladwey et al. 2021b; Al-Shaer et al. 2018; Arayssi et al. 2019 ; Hussain et al. 2018 ; Husted and de Sousa-Filho 2019 ). Their research studies examine the relationship between various proxies of corporate sustainability initiatives, such as CSR disclosure and quality, EESG disclosure, ESG ratings, scores, and performance, and earnings management (EM). Two previous studies Velte ( 2021 a); (Yang and Tang 2022 ) find that environmental performance initiatives, including carbon performance, reduce accrual-based EM, with managers adopting income-decreasing EM to address environmental issues such as water, solid, and air pollution. This research examines the influence of the quality of EM on corporate ESG performance and further investigates the joint effect of corporate ESG performance and CG mechanisms, as a moderating factor, on EM quality in emerging economies such as Pakistan, Indonesia, and Malaysia. The second pathway remains relatively underexplored in studies examining the impact of EM quality on CSP initiatives from an agency theory perspective. According to this research stream, firms are expected to enhance reporting quality by emphasizing socially responsible activities, thereby reducing conflicts of interest through less opportunistic managerial behavior (Martínez-Ferrero et al. 2015 ; Al‐Shaer 2020). This research aims to explore how the quality of EM practices, including accrual- and real-based EM, constrains improved CSP, proxied by corporate ESG performance. Agency theory explains how EM practices hinder firms’ sustainable performance objectives. Agency theory–based studies document a negative EM–sustainability relationship, arguing that higher EM undermines sustainability goals and deteriorates FP (Choi et al. 2013 ; Prior et al. 2008 ; Scholtens and Kang 2013 ; Velte 2019 a; Almubarak et al. 2023 a). Regarding the resource function, whereby directors secure critical resources by reducing EM and preventing firm failure, the third section reviews the literature on the resources provision role of CG boards (Hillman et al. 2002 ; Peterson and Philpot 2007 ; Fitzsimmons 2012 ; Peterson et al. 2007 ; Hillman and Dalziel 2003 ). In order to lessen environmental uncertainty and co-opt important outside entities, directors manage internal relationships, structures, diversity, and specialization to mitigate manipulations and prevent corporate failure (Hillman and Dalziel 2003 ; Hillman et al. 2002 ; Nicholson and Kiel 2007 ). Although income manipulation may occur before CSP evaluation, current CSP initiatives can signal reduced future EM, consistent with signaling theory (Velte 2021 b; Litt et al. 2013 ). Theoretically, we examine how conflicts of interest arising from EM practices influence firms’ motivation toward sustainable performance. Responding to agency theorists, robust CG procedures that strengthen board oversight reduce agency problems by limiting opportunistic behavior in accounting discretion (Jensen 1986 ). We argue that integrating agency, resource dependence and stakeholder theories is more related for examining the association between the quality of EM practices, ESG performance, and CG mechanisms. Integrating these theories helps explain the research question of why CSP initiatives remain low despite substantial firm resources devoted to the sustainable investments’ decision. While stakeholder theory elucidates the link between the quality of EM practices and corporate ESG performance, agency theory asserts that robust CG procedures enable boards to effectively supervise firm operations. Many prior studies examining the influence of EM quality on corporate ESG performance are limited in scope and report varied results. Consequently, researchers have devoted increased attention to CSR and EM (Gaio et al. 2022 ; Dimitropoulos 2022b; Ahmad et al. 2023 b; Habbash and Haddad 2020 c; Buertey et al. 2020; Cho and Chun 2016 ; Gras-Gil et al. 2016 b; Palacios-Manzano et al. 2021 ; Kim et al. 2019 b; Tran et al. 2022 ; Martínez-Ferrero et al. 2015 ; Ben Amar and Chakroun 2018 ), ESG disclosure and EM (Almubarak et al. 2023 b; Gerged et al. 2023b; Sun et al. 2024 ; Borralho et al. 2022b), ESG performance and EM (Pathak and Gupta 2022 ; Kolsi et al. 2023 b; Velte 2019 b; Velte 2019 a), EM and ESG disclosure (Liu et al. 2023 c), EM and ESG performance, and FP (Habib 2023; Gargouri et al. 2010 a; Griffin et al. 2021 ; Fang et al. 2022 ; Velte 2021 a; Litt et al. 2013 ; Wang et al. 2022 ), and ESG disclosure and FP (Albitar et al. 2020 ; Alareeni and Hamdan 2020 ; Chen and Xie 2022 ; Khan 2022 ; Bruna et al. 2022 ; Alfalih 2023 ; Shakil 2021 a). We extend the understanding of the association between EM quality and ESG performance and discuss why CSP initiatives may decline and how effective board oversight can mitigate this. The agency and stakeholder theory literature remains limited in that it has not empirically addressed both conjectures. The influence of opportunistic behavior in accounting discretion (e.g., EM) on CSI (e.g., ESG performance) is mitigated by comprehensive monitoring functions (e.g., CG mechanisms). Regarding CG, prior studies examine its effect on EM (Xie et al. 2003 ; Yang and Krishnan 2005 ; Davidson et al. 2005 ; Kapoor and Goel 2017 ; Chen et al. 2015 ; Usman et al. 2022 ). Most of this previous research focused on board and AC characteristics. Although there is no consensus on specific governance factors, effective CG mechanisms are widely accepted as constraining EM. Gerged et al. ( 2023a ) indicated that previous research has not examined the joint influence of internal governance mechanisms and disclosure quality on the quality of EM practices. Their research examines this relationship in Jordan and reports a significant negative connection between EM practices and disclosure quality. Although their study finds an insignificant CG–EM association, it suggests that disclosure outperforms internal governance in constraining EM. Given the rising global emphasis on ESG performance, firms in emerging markets face increasing scrutiny regarding their financial and non-financial practices. The quality of EM is central to FRQ, with ongoing debate regarding its effects on corporate transparency and sustainability performance. “A critical question arises: Does EM quality negatively affect corporate ESG performance in emerging markets?” Furthermore, CG mechanisms, including board independence, audit committee independence, board gender diversity, and institutional ownership, mitigate opportunistic financial reporting behavior. Therefore, it is essential to examine whether CG mechanisms moderate the association between EM quality and corporate ESG performance. This study investigates the direct relationship between EM quality and corporate ESG performance in the context of emerging economies, namely Pakistan, Indonesia, and Malaysia. Moreover, it also examines the moderating effect of CG mechanisms in the association between EM quality and corporate ESG performance. Specifically, our research explores opportunistic and optimal hypotheses of corporate ESG performance using non-financial firms listed on emerging-market stock exchanges over the period 2016–2024. Our study makes four key contributions; first, it extends limited literature review on negative influence of the quality of EM practices on CSP. We find that tenacious managerial EM erodes CSP efforts. Most prior research focuses on the influence of CSD in reducing practices of EM (Mohmed et al. 2020 ; Habbash and Haddad 2020 a; Ehsan et al. 2022 b; Dimitropoulos 2022a ; Shi et al. 2024 ; Velte 2019 a). We adopt a reverse perspective, positing that EM quality may constrain sustainability performance practices (measured by ESG performance). Second, prior studies on EM and CSR have largely relied on the Jones and Modified Jones models Gras-Gil et al. ( 2016 a) ; (Palacios-Manzano et al. 2021 ; Dimitropoulos 2022a ; Yang and Tang 2022 ). Accordingly, to address empirical differences, this study adopts the performance-matching model of Kothari et al. ( 2005 a) to measure accrual-based EM in relation to ESG performance. The performance-matching model, in contrast to the modified Jones model, accounts for ROA since companies with abnormal performance would otherwise be mistakenly identified as manipulating earnings. As a result, Kothari's model reduces specification bias and heteroskedasticity in EM estimation. Third, our study examines CG mechanisms BIND, BGD, AC independence, and INSOWN as moderators of the EM–ESG performance relationship. Fourth, our study offers a new explanation for differences in corporate ESG performance. This study is among the first to integrate agency Jensen ( 1986 ), stakeholder Freeman ( 2010 ) ; (Freeman 1984 ), and resource dependence Hillman and Dalziel ( 2003 ) theories to examine EM quality and ESG performance in emerging markets such as Pakistan, Indonesia, and Malaysia. Our study finds partial evidence that BIND, BGD, and INSTOWN mitigate the negative influence of EM quality on corporate ESG performance. Contrasting previous research Zalata et al. ( 2022 b) ; (Alves 2023 ; Triki Damak 2018 ; Mnif and Cherif 2021 ; Lara et al. 2017 ), our findings show that BGD deters earnings manipulation and improves investment decisions. Agency theory emphasize that BGD reduces EM practices Arun et al. ( 2015 ) ; (Gull et al. 2018 ; Alves 2023 ), while stakeholder theory contends that it improves ESG performance by reducing financial risks and ESG controversies (Shakil 2021 b). According to our research, female board members have a moderating influence on the relationship between corporate ESG performance and EM quality. This indicates that companies with BGD are more expected to prevent managers’ manipulative behaviors. Consequently, more funds are allocated to value-added ESG activities. Findings indicate that BIND significantly constrains the quality of EM practices. Furthermore, BIND, as a governance mechanism, moderates the EM–ESG link, supporting findings of (Abdelfattah & Elfeky, 2021 ). Moreover, INSTOWN is positively associated with EM quality, emphasizing the passive role of institutional investors in emerging economies. Furthermore, INSTOWN moderates the EM–ESG performance link as a CG mechanism. These findings align with previous results by (Abdelfattah & Elfeky, 2021 ). Literature review and development of our hypothesis EM and ESG performance EM is employed through opportunistic behavior and short-term strategies to manipulate the quality of financial reports and mislead some stakeholders or serve contractual purposes (Healy and Wahlen 1999 ; Dechow et al. 1996 ; Xie et al. 2003 ; Gargouri et al. 2010 b; Choi et al. 2018 ). This practice is widely criticized for undermining firms’ long-term CSI and credibility of FRQ (Ehsan et al. 2022 a). Stakeholders thus become more vigilant and increasingly skeptical of FRQ information (Choi et al. 2013 ). Managers are involved in corporate ESG disclosure activities to gain stakeholders’ trust and build long-term relationships (Escrig-Olmedo et al. 2019a; Zumente and Lāce 2021 ). Previous studies by Gras-Gil et al. ( 2016 b); (Choi et al. 2018 ; Kim et al. 2019 b; Buertey et al. 2020; Ehsan et al. 2022 b; Palacios-Manzano et al. 2021 ; Yang and Tang 2022 ; Velte 2021 a) report varied findings on the impact of combined and individual ESG disclosure pillars and performance activities on EM quality. There is still limited empirical evidence on how EM quality influences corporate ESG initiatives. Most prior research on EM quality’s effect on CSR report mixed results. CSR has been viewed by some research, based on agency theory, as a managerial opportunistic tool to conceal manipulative behavior practices and mislead some of the stakeholders (Gras-Gil et al. 2016 b). According to Prior et al. ( 2008 ), CSR activities help managers mitigate the negative effects of EM quality by enhancing stakeholder satisfaction and reducing scrutiny and activism. By utilizing a sample of 593 companies from 26 different countries (2002–2004), these studies demonstrate a positive influence of EM quality on CSR (Gavana et al. ( 2017 a; (Borralho et al. 2022a ; Rahman and Zheng 2023 ). Managers engaging in EM quality may use CSR spending to distract stakeholders and to hide opportunistic behavior. However, prior studies indicate a negative effect of EM quality on CSR. Based on 1,960 non-financial listed firms from 26 different countries, Martínez-Ferrero et al. ( 2015 ) find greater stakeholder orientation and CSR adoption where the managers’ have less incentives to engage in EM. Ehsan et al. ( 2022 b) reported a negative association between CSR and EM quality in the context of Pakistani manufacturing sector companies. Hickman et al. ( 2021 ) found a negative influence of voluntary and mandatory CSR on EM in the context of non-financial companies listed on the BSE during 2012–2017. The authors argue that managers provide accurate, reliable, and transparent information to support a long-term stakeholder-oriented perspective. Managers using fewer deceptive tactics are more likely to pursue CSR to support high-quality reporting and sustain long-term stakeholder relationships. Meanwhile, the CSI literature has yet to resolve how EM quality reduces ESG performance. We argue that the managerial opportunism behavior in the context of income smoothing and ESG spending may alter the objectives of ESG performance. Firms often signal commitment to CSI through both symbolic and substantive practices (Eliwa et al. 2021 ; Maaloul et al. 2023 ). This substantive view proposes that firms use CSI to engage in greenwashing, masking poor earnings quality and reducing stakeholder scrutiny. This allows managers to conceal earnings irregularities due to weak ESG reporting regulation. Conversely, the symbolic view holds that firms opportunistically disclose high ESG commitment despite poorer performance to enhance ESG disclosure score (Nazari et al. 2017 ; Koh et al. 2023 ). Managers may engage in brownwashing by manipulating discretionary R&D and sustainability spending to understate ESG-related costs (Kim and Lyon 2015 ; Ma et al. 2024 ). Thus, manipulating ESG investment enables firms to involve in brownwashing or greenwashing, distorting true ESG performance through opportunistic behavior that increase or decrease corporate performance. Previous studies argue that firms’ false sustainability reporting to signal environmental responsibility makes greenwashing in the context of sustainable investments decisions a source of EM (Kim and Lyon 2015 ; Lyon and Montgomery 2015 ; Mohmed et al. 2020 ; Rezaee and Tuo 2019 ; Zharfpeykan 2021 ). Consequently, greenwashing or brownwashing in corporate sustainable investment decisions undermines sustainability goals and leads to poor ESG performance. Managerial opportunism theory suggests that managers and insiders overinvest in CSI to advance self-interests, resulting in value destruction (Choi et al. 2013 ; Harjoto and Jo 2011 ; Greiner and Sun 2021 ). Using German data Velte ( 2019 a) finds a negative effect of EM quality on corporate ESG performance, attributed to heightened risks of eroding stakeholder trust. Based on the preceding literature, this study proposes the first hypothesis. H1 EM quality is negatively related with corporate ESG performance. Board gender diversity as a moderator of EM quality–ESG performance relationship. Female board representation strengthens board oversight, curbing managerial opportunism and reducing EM. Gull et al. ( 2018 ) show that female board presence significantly reduces EM in French firms. Similarly, Zalata et al. ( 2022 a) find that female directors with financial expertise enhance earnings quality in U.S. firms. Likewise, Zalata et al. ( 2019 ), show that female supervisory directors reduce accrual-based EM in U.S. firms. However, evidence from the UK shows contrasting results. For instance, a research by Arun et al. ( 2015 ) find that greater female board representation in UK firms is linked to conservatism and potentially higher EM quality. Women directors enhance board transparency and stakeholder communication (Aladwey et al. 2021a; Elmarzouky et al. 2021 ). Their attendance brings diverse perspectives and improves decision-making quality (Albitar et al. 2020 ). This strengthens board oversight and enhances stakeholder-oriented decision-making and corporate sustainability performance. Women directors bring diverse experiences and communal traits such as, empathy, supportiveness, and attentiveness that enhance their ability to prioritize stakeholder needs compared to male counterparts (Manita et al. 2018 a; Alkhawaja et al. 2023 b; Khemakhem et al. 2023 ). A growing body of research shows that BGD enhances CSP (Fernandez-Feijoo et al. 2014 ; Ben-Amar et al. 2017 )(Aladwey et al. 2021a). Using data from Germany and Austria Velte ( 2016 ) finds that even a lower level of female board representation (about 20%) is positively and significantly associated with CSP, challenging the ‘critical mass’ view that at least three women are required on boards. Several studies attribute the positive influence of BGD on ESG performance to female directors’ unique experience, expertise, and regulatory influences (Yahya 2025 ; Khatri 2023 ; Cambrea et al. 2023 ; Cucari et al. 2018 ). Beyond reducing earnings manipulation, female directors tend to allocate surplus cash flows to CSI due to strong communication-related skills (Suttipun 2021 a), ethical commitment (Arayssi et al. 2019 ), and intellectual and interpersonal capabilities (Shakil 2021 b). Similarly, Van Hoang et al. ( 2021 ) show that greater female board representation in U.S. firms reduces manipulation in environmental disclosures and enhances the quality of environmental reporting. Prior research has examined links between BGD, CSP, and the quality of EM from multiple perspectives. Some studies examine BGD and EM practices (Arun et al. 2015 ; Zalata et al. 2022 b; Mnif and Cherif 2021 ; Alves 2023 ), while others focus on BGD and CSR (Manita et al. 2018 b; Alkhawaja et al. 2023 a; Wasiuzzaman and Subramaniam 2023 ; Khemakhem et al. 2023 ; Wasiuzzaman and Wan Mohammad 2020 ; Cucari et al. 2018 ; Al Fadli et al. 2019 ). However, these perspectives produce mixed findings. This research examines the dual role of female board members in mitigating EM in relation to corporate ESG performance. Women enhance board diversity and effectiveness by better addressing diverse stakeholder needs. Consequently, this enhances the firm’s sustainability performance. Moreover, stronger board effectiveness reduces agency costs and limits EM. Thus, BGD strengthens the negative connection between CSP and EM quality. This research examines whether women board representation moderates the relationship between EM quality and CSP. Drawing on theories and prior research on BGD role in reducing EM quality and strengthening the ESG–EM nexus in emerging markets, we propose the third hypothesis. H2 BGD moderates association between the quality of EM practices and corporate ESG performance nexus Board independence as a moderator of the EM quality–ESG performance relationship Consistent with agency theory, the board of directors plays a critical monitoring role (Hillman and Dalziel 2003 ). Board independent members exercise impartial judgment by objectively evaluating FP with minimal CEO influence (Jizi 2017 ). As external managers, independent directors seek to build reputation and protect human capital by signaling decision-making expertise to the market (Fama and Jensen 1983 ). Their presence strengthens board independence oversight (Beasley 1996 ; Fama and Jensen 1983 ), reduces asymmetric information, and enhances integrated reporting quality (Chouaibi et al. 2021 ; Hussainey et al. 2022 ; Albitar et al. 2023 ). Additionally, they play a key role in diminishing financial fraud (Beasley 1996 ). A higher proportion of board independent members strengthens oversight objectivity, curbs managerial opportunism, and reduces abnormal accruals and agency costs (Abdou et al. 2021 ; Klein 2002 ). Beekes et al. ( 2004 ) suggest that an independent board of directors must meet two key conditions to perform its monitoring responsibilities effectively. First, incentives such as share ownership are needed to sustain commitment to monitoring duties. Second, they must possess sufficient knowledge to understand how managerial decisions affect the financial reporting system. For example, they should recognize that reducing R&D expenses can temporarily increase current earnings. Experienced independent directors detect earnings manipulation through their expertise. Those with insights into greenwashing (Mohamad et al. 2019 ; Rezaee and Tuo 2019 ; Zharfpeykan 2021 ) and brown washing (Kim and Lyon 2015 ) help address overinvestment and insufficient sustainability cost disclosure, reducing EM practices and improving sustainability performance. Conversely, independent directors with limited understanding of firm- or industry-level sustainability practices face greater challenges in effective monitoring. They may offer less strategic guidance, thereby increasing information asymmetry due to limited access to relevant disclosures (Garcia Osma 2008 ). This lack of expertise may limit their ability to distinguish genuine from opportunistic sustainability initiatives, potentially undermining the firm’s sustainability goals. Additionally, Xie et al. ( 2003 ) identify circumstances in which independent directors may struggle to fulfill their oversight roles. For instance, infrequent board meetings and multiple board memberships can weaken directors’ effectiveness in mitigating sustainability-related manipulations. The issue worsens when overburdened directors have long tenures, reducing their focus on monitoring responsibilities. The independent board of directors plays a vital role in shaping CSR disclosure and initiating corporate social disclosure programs (Jizi 2017 ). Board independent members significantly contribute by increasing attention to sustainability and environmental problems (Shrivastava and Addas 2014 ). They also protect their reputations by promoting transparency in disclosing a company’s ESG activities. This signals to the market that the organization is committed not only to financial performance but also to advancing social welfare (Arayssi et al. 2019 ). Several studies Shrivastava and Addas ( 2014 ), (Jizi 2017 ), (Hussain et al. 2018 ), (Husted and de Sousa-Filho 2019 ), and (Lagasio and Cucari 2019 ), demonstrate a positive association between BIND and corporate ESG disclosure. Shrivastava and Addas ( 2014 ), using an international context sample (2010–2014), found that companies with higher proportions of independent board directors achieve stronger ESG disclosure scores and that appointing independent advisors with environmental and sustainability expertise enhances governance in these areas. Similarly, Jizi ( 2017 ), analyzing FTSE 350 UK firms (2007–2012), found a positively and significantly influence of BIND on CSR disclosure, underscoring the significance of board governance structures in shaping CSR disclosure score that benefit stakeholders. Additionally, Hussain et al. ( 2018 ), examining U.S. firms (2007–2011), showed that board independent members positively influence the individual ESG pillars of corporate ESG performance. By emphasizing the role of independent board members in limiting EM and encouraging CSI engagement, greater board independence is expected to weaken the negative relationship between EM quality and CSP. Thus, the following hypotheses for the fourth study are proposed: H3 BIND moderates the association between EM quality and corporate ESG performance Moderating effect of audit committee independence on the relationship between EM quality and corporate ESG performance According to resource dependence theory, which suggests that a primary responsibility of the board of directors is to provide essential resources to firms (Hillman and Dalziel 2003 ). The inclusion of independent board members on the audit committee enhances the diversity of resources accessible to organization. Compared with affiliated members, AC independent members are anticipated to exhibit greater impartiality and expertise (Carcello and Neal 2003 ). AC independence improves the effectiveness of financial reporting quality oversight. Additionally, independent committee members are motivated to uphold high oversight standards to protect or enhance their reputational capital (Abbott et al. 2004 ). Prior studies show that the independence of the AC influences FRQ Bhuiyan and D’Costa ( 2020 ) ; Oussii and Boulila Taktak 2018 ; De Vlaminck and Sarens 2015 ) and also directly affects performance and non-financial reporting. This includes mandatory and voluntary CSR disclosures Appuhami and Tashakor ( 2017 ) ; (Mohammadi et al. 2021 ; Arif et al. 2021 ) ESG reporting Buallay & Al-Ajmi (2020), and sustainability report assurance (Al-Shaer and Zaman 2018 ; Zaman et al. 2021 ). Mohammadi et al. ( 2021 ), find that AC size, independence, and financial expertise significantly enhance voluntary CSR disclosures in 150 Iranian listed firms. Arif et al. ( 2021 ) find that AC activism and independence are significantly and positively associated with corporate ESG disclosure, with the strongest effect on the environmental pillar relative to the social and governance pillars. Dwekat et al. ( 2022 ) find that AC independence, meeting frequency, financial expertise, and CSR committee presence significantly enhance CSR assurance adoption in STOXX 600 European firms. Conversely, Wang and Sun ( 2022 b) show that AC independence is not significantly related to CSR or environmental disclosures in China. They attributed this disparity to unique governance structures, cultural influences, and the political and social connections prevalent in Chinese companies, which can undermine the independence of audit committee members. Likewise, Pucheta-Martínez et al. ( 2023 ) explored the impact of AC characteristics (directors’ independence and the presence of executives and directors at AC meetings) on CSR disclosure by utilizing an international sample comprising a total of 13,264 firm-year observations of listed non-financial companies over the period 2007–2018. The findings showed that directors’ independence and executives on the AC have a negative influence on CSR disclosure, while directors’ presence at AC meetings is positively related to CSR disclosure. A substantial body of research grounded in agency theory highlights the importance of AC independence in mitigating fraudulent accounting activities. For instance, Klein ( 2002 ), using a large sample in the context of U.S. companies, identified a negative association between AC independence and abnormal discretionary accruals. Likewise, Mohd Saleh et al. ( 2007 ) reported that attendance of AC-independent members is related to a decrease in the EM quality. However, other related research, such as those by Choi et al. ( 2013 ), Xie et al. ( 2003 ), Abdullah and Nasir ( 2004 ), Baxter and Cotter ( 2009 ), He and Yang ( 2014 ) and Habbash et al. ( 2013 ), find no significant influence of AC independence on curbing EM. To address these mixed findings, meta-analytical research has been conducted to explore the relationship further. Previous studies by García-Sánchez et al. (2019a), Inaam and Khamoussi ( 2016 ), and Hasan et al. ( 2020 ) consistently conclude that AC independence is a key corporate governance mechanism for constraining EM. Overall, the presence of independent members on the AC plays a crucial role in overseeing and limiting earnings manipulation practices. Given the pivotal role of AC independence in curbing opportunistic behavior practices such as EM and fostering greater transparency through engagement in ESG activities, it is anticipated that AC independence moderates the connection between the quality of EM and corporate ESG performance. Accordingly, the following hypothesis is proposed: H4 The presence of AC independence moderates the association between the quality of EM practices and the corporate ESG performance nexus Moderating effect of institutional ownerships on the quality of EM practices and corporate ESG performance nexus The firms' ESG performance is significantly influenced by institutional investors, although empirical evidence on their influence varies. Previous studies like Dyck et al. ( 2019 ), Garcia and Orsato ( 2020 ) and Chen et al. ( 2020 ) highlight that institutional investors often drive stronger ESG practices and increase ESG-related activities. However, others, such as (Harjoto et al. 2017 ; Meng and Wang 2020 ), suggested that firms with higher institutional ownership may reduce investments in corporate social responsibility or experience declines in institutional ownership with improved ESG scores. This discrepancy arises due to variations in institutional investor types. Long-term investors tend to promote corporate sustainability by enhancing governance and restraining managerial misbehavior, aligning with long-term value creation (Harford et al. 2018 ; Kim et al. 2019 a; Velte 2022 ). Conversely, short-term investors prioritize short-term profits, leveraging informational advantages through active trading (Yan and Zhang 2009 ). Regarding the effective monitoring hypothesis, agency theory suggests that institutional ownership reduces opportunistic behavior (Al-Duais et al. 2022 ; Jenson and Meckling 1976 ). Nevertheless, prior evidence on the influence of institutional ownership on EM quality remains limited in emerging markets such as Pakistan, Indonesia, and Malaysia. Ramalingegowda et al. (2021) show that firms with higher institutional ownership are less likely to engage in EM due to the monitoring role of institutional investors. This study aligns with and supports the findings of Sakaki et al. ( 2017 ) and Ajay and Madhumathi ( 2015 ), showing that institutional ownership is associated with higher earnings quality (lower EM), suggesting that institutional investors constrain EM. Additionally, Al-Duais et al. ( 2022 ) report that institutional ownership provides stronger incentives to enhance FRQ and reduce REM, as this mechanism benefits the firm. Ahmad et al. ( 2023 a) find that institutional or foreign ownership prevents managers from engaging in EM practices. Nevertheless, other prior studies document that institutional or foreign ownership positively affects EM behavior (Debnath et al. 2021 ). Previous studies posit that institutional or foreign ownership is positively and significantly associated to corporate ESG performance (Wang et al. 2023 b; Liu et al. 2023 b; Jiang et al. 2022 ). Previous research indicates that while high ESG disclosure scores are often related to better sustainability practices, they do not always preclude real EM. Companies may still engage in real EM by manipulating operating cash flows, production levels, or discretionary expenditures for strategic purposes. For example, firms might increase sales through discounts to reduce the fixed cost per unit, overproduce, or cut discretionary expenses such as advertising and R&D, aligning with short-term financial goals even within a high ESG framework (Al Barrak and Kouaib 2024 ). Institutional or foreign ownership, measured by the percentage of outstanding shares held by organizations, is a key CG mechanism that reduces information asymmetry and monitors agents’ performance (Eissa et al. 2023). Institutional or foreign ownership is gradually focused on environmental, economic, social and governance problems. The effect of institutional or foreign ownership on ESG–EM connections is expected for numerous theoretical perspective reasons. Firstly, institutional or foreign ownership has greater responsibilities toward corporate outcomes. Since engagement in EM practices may lead to involvement in fraudulent actions and damage FRQ Md Nasir et al. ( 2018 ); Rahman et al. 2016 ), institutional ownership has strong inducements to alleviate such type of practices through proper monitoring of actions by management. Secondly, institutional or foreign ownership, the most powerful capital providers, has a stronger inducement to monitor companies (Rahman 2021 ). Empirical evidence shows that little is known about how firms having higher institutional or foreign ownership influence EM behavior, and previous research that examined this connection is limited (Ahmad et al. 2023 a; Mehrani et al. 2017 ; Al-Duais et al. 2022 ; Akter et al. 2024 ). This previous research has shown that companies with higher institutional or foreign ownership are positively and significantly associated with higher quality earnings, suggesting that institutional or foreign ownership curbs EM behavior. Nevertheless, no research study has considered examining the moderating influence of institutional or foreign ownership on the ESG–EM relationship. Therefore, this research attempts to extend prior studies by examining the moderating influence of institutional or foreign ownership on the ESG performance–EM nexus in Pakistani, Indonesian, and Malaysian companies. H5 Institutional or foreign ownership moderates the association between the quality of EM practices and the ESG performance nexus Table 1 List of representative sample firms and their respective industries Industries Final sample Observations (1) Pakistan Automobile Chemicals Fertilizer Oil & Gas Pharmaceutical Textile Foord & beverage Cement Telecommunication Financial services Engineering (2) Malaysia Automobile Chemicals Cement Energy Telecom Construction Healthcare Financial services Technology Consumer goods Real Estate Utilities Industrial goods Transportation Retails (3) Indonesia Automobile Chemicals Cements & Cements Products Energy Telecom Mining Construction Consumer Goods Financial services Healthcare Real Estate Technology Transportation Utilities Total 8 6 5 5 5 4 4 3 4 3 3 12 10 9 9 8 8 7 9 9 8 9 9 8 9 8 8 6 7 8 8 7 8 8 7 6 7 9 8 7 6 292 72 54 45 45 45 36 36 27 36 27 36 54 36 27 54 54 54 36 54 63 54 63 45 54 45 45 36 27 18 54 27 27 36 45 36 54 45 63 45 27 18 2628 Source : Information collected from Bloomberg Database Methodology and Research Design The data, study models, variable descriptions, and measurement techniques are presented in this section. The research provides empirical models to ensure the testing of the study hypothesis. Data sources and samples Panel data estimation approaches were used in this study. Time-series and cross-sectional units (firms) are combined in panel data estimation, enabling a longitudinal design to assess changes in organizational variables over time. This contrasts with cross-sectional designs, which lack time dynamics in variables (Sekaran 2016 ). Using purposive sampling, the study covers 50 Pakistani, 110 Indonesian, and 132 Malaysian firms over 2016–2024, totaling 2628 firm-year observations. Purposive sampling is appropriate as it allows researchers to select firms meeting specific inclusion criteria with testable data (Sekaran 2016 ). Following this approach, two inclusion criteria are applied. First, due to their unique reporting regulations and accounting principles, financial firms are not included. Second, firms without ESG performance data are not included. The Bloomberg database provided the data for every CG mechanism variable. ESG performance data for sampled Pakistani, Indonesian, and Malaysian firms were sourced from Bloomberg. The ESG performance score from Bloomberg spans 0–100, where 0 indicates the lowest and 100 the highest rating. Disclosure of environmental pollution and greenhouse gas emissions is reflected in the environmental pillar score. The environmental, social, and governance pillar scores have 68, 62, and 56 data points, respectively. Emissions (12%), resource usage (11%), and innovation (11%), make up the environmental disclosure pillar, according to Bloomberg. The social disclosure pillar includes human rights (4.5%), community (8%), workforce (16%), and product responsibility (7%), while the governance disclosure pillar covers shareholders (7%), management (19%), and CSR strategy (4.5%). Estimating Empirical Models This study models the mathematical association between variables in the formulated hypotheses, with the first model examining the association between the quality of EM practices and corporate ESG performance. The second model examines the association between the mechanisms of CG and ESG performance, while the third model analyzes the interaction between the mechanisms of CG and the quality of EM on ESG performance. Control variables are included in each model. Equation No. 1 presents the direct association between the quality of EM practices and ESG performance, including the mechanisms of CG as an additional control variable. Equation No. 2 presents the moderating influence of the mechanisms of CG on the association between the quality of EM practices and ESG performance. The research also examines the influence of quality of EM practices on individual disclosure pillar rating scores (environmental, social, and governance scores), in addition to the dependent variable being ESG performance. ESG_ i,t = β 0 + β 1 DACC i,t + β 2 BoardSize i,t + β 3 IndepBM i.t + β 4 BGenderD i,t + β5AuditCommIndep i , t + β 6 InstiOwner i,t + β10ROA i , t + β 11 FSize i , t + β 12 Fage i,t + β 13 Leverage i , t + β 14 LOSS i , t + β 15 Year_dummies i,t + β 16 Industry_dummies i,t + ε i,t (1) ESG_ i,t = β 0 + β 1 DACC i,t + β 2 BoardSize i , t + β 3 IndepBM i , t + β 4 BGenderD i , t + β 5 AuditCommIndep i,t + β 6 InstiOwner i,t + β 7 DACC ∗ BoardSize i,t + β 8 DACC ∗ IndepBM i,t + β 9 DACC ∗ BGenderD i,t + β 10 DACC ∗ AuditCommIndep i,t + β 11 DACC i,t * β 12 InstiOwner i,t + β 13 ROAi , t + β 14 FSize i,t + β 15 Fage i,t + β 16 Leverage i,t + β 17 LOSS i,t + β 18 Year_dummies i,t + β 19 Industry_dummies i,t + ε i,t (2) Variable measurement Consistent with prior research, this study employs the performance-matching model of Kothari et al. ( 2005 ) to measure accrual- and real-based EM. Building on the Jones ( 1991 ) model, Kothari et al. ( 2005 b) incorporate a proxy for firms’ operating performance to reduce misspecification in samples with extreme FP; therefore, normal accruals are estimated using the following models. \(\:\left(\frac{TAit}{Ait-1}\right)=\beta\:\) 0i \(\:\left(\frac{1}{Ait-1}\right)+\:\beta\:\) 1i + \(\:\frac{\varDelta\:Sales}{Ait-1}\) + β 2i \(\:\left(\frac{\varDelta\:Rev\:it-Rec\:it}{Ait-1}\right)+\:\beta\:\) 3i \(\:\left(\frac{PPE\:it}{Ait-1}\right)\) + α ε it (3) \(\:\frac{TAit}{Ait-1}\) = \(\:\alpha\:\) 0 \(\:\:\left(\frac{1}{Ait-1}\right)\) + \(\:\alpha\:\) 1 \(\:\left(\frac{\varDelta\:REVit-\varDelta\:RECit}{Ait-1}\right)\) + α 2 \(\:\left(\frac{PPEit}{Ait-1}\right)\) + α 3 (ROA i, t ) + ε i,t (4) TA represents total accruals, are calculated as the difference between operational cash flows and earnings before extraordinary items and discontinued operations. All variables are scaled by lagged total assets to reduce heteroscedasticity. A stand for total assets in year t; Δsales is the change in sales; PPE is the gross value of property, plant, and equipment in year t; ROA is return on assets; and t is the time period. Furthermore, in order to account for extreme values, all continuous variables are winsorized at the 1% and 99% levels. The residual from the above models serves as the proxy for the quality of EM, henceforth denoted as DACC (Table 2 ). Table 2 Variables Definitions and Measurements Variables Proxies Database (source) Accrual EM Audit Committee Independence Board independence Board gender diversity Institutional ownership ESG ESG Firm size Firm age ROA Leverage Countries dummies Year dummies Performance-matching model of Kothari et al. ( 2005 ) The percentage of independent directors to the audit committee's size Percentage of strictly independent board members to total members on the board The ratio of female directors to the total number of directors The number of institutional shares/Total outstanding share *100 ESG Disclosure Score Environmental pillar Social pillar Governance pillar Natural logarithm of total assets The natural logarithm of the number of years since the company's founding It is the percentage of net income to total assets The proportion of total debt scaled by total assets Dummy variable for the countries, Pakistan, Indonesia, Malaysia, Dummy variable for the years 2016, 2017, 2018, 2019,2020, 2021, 2022, 2023, 2024 Osiris database Bloomberg database Bloomberg database Bloomberg database Bloomberg database Bloomberg database Bloomberg database Bloomberg database Bloomberg database Bloomberg database Osiris database Osiris database Osiris database Osiris database Osiris database Osiris database Control variables We include several control variable factors commonly utilized as reliable indicators of ESG performance in CSR disclosure literature. Hence, we included profitability (ROA) Helfaya and Moussa ( 2017 ), firm size D'Amico et al. ( 2016 ) ; Helfaya and Moussa ( 2017 ), firm leverage D'Amico et al. ( 2016 ) ; (Helfaya and Moussa 2017 ), firm age Ngoc and Manh (2024), and loss Chen et al. (2018) to mitigate model misspecification, omitted variable bias (OVB), and spurious regression analysis estimates. Results We report results from descriptive statistics and the correlation matrix (Tables 3 – 4 ), main regression and moderation analyses (Tables 5 – 6 ), and robustness tests (Tables 7 – 9 ). Results for the descriptive statistics Table 3 reports descriptive statistics for corporate ESG disclosure scores, the quality of EM, the mechanisms of CG, and the control variables, presented in Panels A, B, C, and D, respectively. Corporate ESG disclosure scores are measured on a total scale of 100%. The sample mean ESG disclosure scores are 52.07% overall, 43.00% for the environmental disclosure pillar, 56.62% for the social disclosure pillar, and 55.87% for the governance disclosure pillar. This shows that the environmental disclosure pillar score is the lowest among ESG disclosure pillars, suggesting that the sampled Indonesian firms perform below average in managing environmental disclosure issues and sustaining corporate environmental policy agendas. The sampled Indonesian listed firms exhibit a mean EM value of − 0.007 (approximately zero), with minimum and maximum values of − 1.323 and 2.657, respectively. This suggests that, on average, Indonesian companies show a lower tendency to use income-increasing DACC to boost earnings quality reporting, although some firms remain more engaged in EM practices. Board independent members average 56.48%, demonstrating that more than half (i.e., 50%) of board members in Indonesian listed firms are independent directors. The audit committee comprises approximately three members, with over 79% being independent. Female directors constitute, on average, 14.9% of boards in Indonesia, 27.4% in Malaysia, and 9.2% in Pakistan, with a maximum percentage of 54% across sampled listed firms. Therefore, approximately one in four board independent members is a woman director in sampled listed firms across Indonesia, Malaysia, and Pakistan. Leverage, calculated as total debt divided by total assets, averages 4.33%, and 57.5% of sampled firms in Indonesia, Malaysia, and Pakistan report losses in at least one year during the sample period. Firm size has a mean value of 23.51, while sampled listed firms in Indonesia, Malaysia, and Pakistan exhibit an average profitability (ROA) of 7.22%. Table 3 Descriptive statistics Variables Obs Mean Std. Dev Min Max Panel A: ESG disclosure score ESG Score Environmental pillar score Social pillar score Governance pillar score Panel B: EM Earning manipulation (DACC) Panel C: Corporate governance mechanisms Board Independent Members Board Gender Diversity Audit Committee Independence Institutional Ownership Panel D: Control variables Profitability (ROA) Firm size Firm age Leverage Loss 2628 2628 2628 2828 2828 2828 2628 2828 2828 2828 2828 2828 2828 2828 52.062 43.00 56.62 55.87 -0.007 56.48 26.182 88.772 17.81 6.215 22.428 6.259 5.238 0.665 18.648 24.459 21.480 20.140 1.267 13.448 12.642 15.238 10.72 9.607 2.669 2.473 0.559 0.469 1.065 0.000 1.763 0.223 -1.323 6.153 0 12.276 0.00 -34.876 14.484 0 0 0 93.239 95.051 95.637 96.736 2.657 100 50 100 70.56 46.590 28.436 10.205 1 1 Correlation results Table 4 reports the Pearson correlation matrix for ESD indicators, accrual EM, the mechanisms of CG, and the control variables. As anticipated, the social and environmental disclosure pillars show a strong positive relationship with the corporate ESG disclosure score. The governance disclosure pillar score also demonstrates a positive relationship with the corporate ESG disclosure score. Nevertheless, this does not affect the issue of multicollinearity, as the ESG disclosure score and individual ESG disclosure pillar score serve as separate dependent variables in Tables 5 – 7 . EM reveals a negative connection with overall ESG disclosure and individual ESG pillars. CG mechanisms are positively connected with overall ESG disclosure and individual pillar scores, as strong CG is expected to improve sustainability practices and stakeholder outcomes. Profitability shows a negative relationship with the overall ESG disclosure score and social and governance disclosure pillar scores among all control variables. Loss and firm size are negatively associated with environmental and governance pillar disclosure scores, respectively. Leverage is positively connected with corporate ESG disclosure and its individual pillars’ scores, implying lower debt costs for ESG-engaged firms. IND board and AC independence are moderately positively correlated (r = 0.486), implying notable membership overlap. AC independence is more strongly correlated with the governance disclosure pillar score than with the environmental and social disclosure pillars. Table 4 Pearson correlation matrix (1) ESG (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) 1.00 (2) ENV 0.833*** 1.00 (3) SOC 0.874*** 0.684*** 1.00 (4) GOV 0.678*** 0.388*** 0.406*** 1.00 (5) EM -0.060** -0.066** -0.075** -0.043* 1.00 (6) IBM 0.33*** 0.203 *** 0.197** 0.461*** -0.033 0.068** 1.00 (7) BGD 0.354*** 0.229*** 0.302*** 0.287*** -0.037 0.077** 0.009 1.00 (8) ACI 0.282*** 0.148*** 0.123*** 0.427*** 0.041 0.134** 0.055** 0.078** 1.00 (9) IO -0.003 0.007 -0.029 0.249*** 0.302 0.288** -0.023 0.068** 0.321*** 1.00 (10) ROA 0.033* -0.012 -0.018 -0.003 -0.068* 0.427 -0.036** 0.125** 0.486 0.083 1.00 (11) FSIZE 0.363** 0.345*** 0.342*** 0.108** 0.009 -0.004 0.032 -0.024 0.014 0.007 0.012 1.00 (12) FAGE 0.025 0.051 0.034 -0.014 0.014 0.109 -0.079** -0.005 0.038 0.074 0.065 0.014 1.00 (13) LEV 0.373 0.355*** 0.074 0.223*** 0.341 0.223 0.008 0.376 0.136 0.129 0.055 -0.037 -0.134** 1.00 (14) Loss 0.045 0.061* 0.064** -0.061** 0.065** 0.-0.052 0.234*** 0.074 -0.047 0.048** -0.053 0.012 -0.029 0.068** 1.00 Regressions results Table 5 shows the multivariate EM–ESG disclosure or performance relationship with mechanisms of CG as control variables. The random effects model is supported by the results of the Hausman test. Random effects are used to accommodate dummy and time-invariant variables. EM shows a significant (5%) negative relationship with ESG performance, implying lower ESG outcomes among firms manipulating financial reports. Higher EM corresponds to lower ESG disclosure, aligning with agency theory on managerial opportunism and shareholder conflict. Thus, H1 is supported and confirmed. The negative association between the quality of EM and corporate ESG performance is also confirmed across individual ESG disclosure pillars. The quality of EM shows a negative and significant coefficient for the social and environmental disclosure pillar. The results align with prior research indicating that EM engagement undermines socially responsible practices Ehsan et al. ( 2022 b) ; (Hickman et al. 2021 ; Martínez-Ferrero et al. 2015 ; Adeneye et al. 2024 b; Abdelfattah and Elfeky 2021 ), and diminishes stakeholder satisfaction and trust (Gavana et al. 2017 b; Kolsi et al. 2023 a; Velte 2019 a). Among all the control variables, mechanisms of CG are positively connected with ESG disclosure score, demonstrating that strong mechanisms of CG enhance CSP through higher ESG disclosure. It is also confirmed that CG mechanisms effectively moderate the connection between the quality of EM and corporate ESG performance. BGD is positively and significantly associated with corporate ESG performance and its individual disclosure pillars at the 1% level, supporting past results on the positive effect of female board members on sustainability initiatives (Nuhu and Alam 2024 ; Chebbi and Ammer 2022 ; Kamaludin et al. 2022 a; Wasiuzzaman and Wan Mohammad 2020 ; Khemakhem et al. 2023 ; Alkhawaja et al. 2023 a). In accordance with resource dependence theory byHillman et al. ( 2002 ), more women on the board, with their skills and gender-based characteristics, enhance firm resources and improve corporate ESG performance. The results are supported by and consistent with the studies of Velte ( 2016 ) and Romano et al. ( 2020 ), whose studies were conducted in the context of European countries. Our study findings contradict those of Cucari et al. ( 2018 ), who reported that female board members reduce ESG disclosure, suggesting that regulatory pressures may hinder their board gender equality goals toward corporate sustainable performance. Board independent members show a positive and significant association with ESG disclosure and its individual disclosure pillars. The board’s oversight and monitoring function enhances CSRD. Our results align with Chebbi and Ammer ( 2022 ) ; (Kamaludin et al. 2022 b), suggesting board independent members support firms’ social and environmental activities. Previous studies report a positive link between board independent members and corporate ESG disclosure and performance Umar et al. ( 2024 ); (Ellili 2023 ), consistent with the agency theory perspective that board oversight and monitoring increase ESG-related efficiency (Chouaibi et al. 2021 ; Fama and Jensen 1983 ; Hillman and Dalziel 2003 ). These study findings contrast with Naciti ( 2019 ) who reported a negative connection between BIND and ESG performance. Our study results indicate that board independent members increase the governance disclosure pillar more than the social and environmental disclosure pillars, also contributing to overall ESG disclosure. Firms enhance ESG performance by having more independent director members on board. Descriptive statistics show that the governance pillar has the highest mean, indicating stronger monitoring roles in Pakistani, Indonesian, and Malaysian firms. AC independence positively and significantly affects overall ESG, environmental, and governance scores (1%, 5%, and 1%), supporting prior studies (Al-Shaer and Zaman 2018 ; Arif et al. 2021 ; Suttipun 2021 a; Tumwebaze et al. 2022 ; Erin et al. 2022 ). Our research findings show that resources and expertise of independent director members in AC increase ESG performance in Pakistani, Indonesian, and Malaysian firms, supporting resource dependence theory Hillman and Dalziel ( 2003 ). Our study results on AC independence contradict the study by Wang and Sun ( 2022 a) who revealed an insignificant connection with ESG disclosure, attributing it to country-specific culture and political ties of directors. The coefficient of institutional or foreign ownership is significantly positive at 1%, indicating that companies with higher IO show greater ESG performance. Business relationships and investment horizons are important for CG mechanisms (Harford et al. 2018 ). Our findings show that both long-term pressure-insensitive and short-term pressure-sensitive investors are responsible for the positive relationship between IO and ESG performance. Using their resources and expertise, long-term, pressure-insensitive institutional or foreign investors monitor management, leveraging ownership to improve governance and enhance ESG performance. This aligns with Kim et al. ( 2019 a), who found that active and long-term investors positively influence CSR disclosure activities. Similarly, our results align with Wang et al. ( 2023 a) ; (Liu et al. 2023 a), who found IO positively influences corporate ESG performance. Higher ESG companies typically yield higher returns Khan ( 2019 ), so short-term, pressure-sensitive institutional investors choose companies with strong ESG potential by using their informational advantage, leading to a positive and significant relationship. Leverage and firm size are positively and significantly associated with ESG performance, whereas firm age demonstrates a significant but negative connection with ESG performance. This proposes that large firms are more expected to adopt ESG disclosure, while older firms may resist modern ESG practices due to tradition, and newer firms prioritize ESG to stay competitive and attract stakeholders. Our results support prior studies showing positive links between firm size and ESG Fiandrino et al. ( 2019 ), debt and ESG Khanchel and Lassoued ( 2022 ), and age and ESG (Cicchiello et al. 2023 ). Table 5 Relationship between EM and ESG performance Variables (1) ESG score (2) Environmental pillar score (3) Governance pillar score (4) Social pillar score DACC -0.729** (0.384) -1.072** (0.534) -1.039** (0.471) -0.273 (0.446) Independent board members 0. 163*** (0.0395) 0.0879 (0.0561) 0.0708* (0.0484) 0.396*** (0.0479) Board gender diversity 0.341*** (0.0438) 0.312*** (0.0736) 0.412*** (0.0564) 0.333*** (0.0544) Audit committee independence 0.150*** 0.0347) 0.104** (0.0468) 0.0512 (0.0422) 0.315*** (0.0402) Institutional ownership 0.160*** 0.0437 0.205** (0.0378) 0.0412 (0.0424) 0.316*** (0.0405) Profitability (ROA) 0.0171 (0.0553) 0.0527 (0.0777) -0.0174 (0.0682 -0.00351 (0.0636) Firm size 1.166*** (0.307) 0.753* (0.445) 1.037*** (0.374) 1.736*** (0.367) Firm age 1.178*** (0.3050 0.673* (0.355) 1.047*** (0.346) 1.647*** (0.357) Leverage 2.034*** (0.222) 2.376*** (0.312) 2.239*** (0.267) 1.541*** (0.253) Loss 1.115 (1.046) 2.395 (1.471) 1.946 (1.297) -1.252− (1.242) Year dummies Y Y Y Y Industry dummies Y Y Y Y Constant -23.08*** (7.019) -21.59** (9.971) -5.982 (8.697) -44.34*** (8.362) Observation 1280 1280 1280 1280 R-squared 0.336 0.253 0.244 0.334 Standard errors are enclosed in parentheses. p < 0.1, p < 0.05, and p < 0.01. Results from the moderations test Our study further analyzes the effect of accrual EM on overall and individual ESG pillars, moderated by mechanisms of CG. The main purpose is to examine whether mechanisms of CG moderate the negative impact of quality of EM on ESG performance. Table 6 displays the study's results. The moderation effect results are shown in Table 6 . Table 6 shows how mechanisms of CG moderate the influence of DACC on overall and individual ESG disclosure scores. The positive BGD interaction term shows that female board members significantly reduce EM’s negative impact on ESG performance (β = 0.152, p0.0237). Therefore, the second hypothesis (H2) is confirmed and supported. The interaction term (DACC*BGD) shows a positive and significant connection with environmental (β = 0.151, p < 0.04) and social disclosure pillar scores (β = 0.181, p < 0.05). Conversely, the interaction term (DACC*BIND) is significant across overall ESG disclosure and individual pillars, but its coefficients are smaller than DACC in Table 5 , suggesting BIND reduces EM, but not sufficiently to curb EM activities. Therefore, there is no evidence to support hypothesis 3 (H3). This demonstrates that female board members are a stronger mechanism of CG than independent male directors on the board, in contrast to BGD, whose interaction terms have positive coefficients. This could suggest that male directors have two monitoring roles. They may attempt to constrain EM while also engaging in entrenchment opportunities, thereby reducing board monitoring effectiveness. Similarly, AC_IND shows no significant monitoring effect on ESG disclosure pillars, except for the governance disclosure pillar. Interaction term (DACC*AC_INDEP) is not significant for overall ESG disclosure in Model 1 (β = 0.0376, p > 0.10) but is significant for the governance disclosure pillar score. As our research hypotheses focus on aggregate ESG disclosure scores, hypothesis 4 (H4) is not confirmed or supported. All control variables of our study are statistically significant and positive, except for profitability, which is insignificant for overall ESG disclosure and individual pillars. Overall, when CG mechanisms condition the ESG–EM relationship, the DACC coefficient turns positive, suggesting CG may help conceal managerial opportunism by reducing stakeholder activism threats while increasing ESG performance. Table 6 The moderating effect of mechanisms of CG on the association between ESG performance and EM Variables (1) ESG score (2) Environmental pillar score (3) Governance pillar score (4) Social pillar score DACC 1.842** (1.691) 1.521** (3.832) 3.523** (3.212) 1.062 (3.371) Independent board members 0.205*** (0.0387) 0.129** (0.0556) 0.105** (0.0486) 0.423*** (0.0461) DACC * independent board members 0.126*** (0.0317) -0.0639* (0.0448) -0.145*** (0.0374) -0.131*** (0.0354) Board gender diversity 0.473*** (0.0435) 0.361*** (0.0614) 0.328*** (0.0547) 0.380*** (0.0519) DACC * board gender diversity 0.152** (0.0337) 0.142** (0.0484) 0.181** (0.0445) 0.00166 (0.0412) Audit committee independence 0.136*** (0.0342) 0.0748* (0.0474) 0.0398 (0.0435) 0.310*** (0.0435) DACC * audit committee independence 0.0376 (0.0258) 0.0392 (0.0356) 0.0271 (0.0345) 0.0667** (0.0328) Institutional ownership 0.134*** (0.0340) 0.0838* (0.0484) 0.0288 (0.0455) 0.309*** (0.0403) DACC * institutional ownership 0.128*** (0.0268) 0.0365 (0.0384) 0.0270 (0.0335) 0.0666** (0.0319) Profitability (ROA) 0.00786 (0.0566) 0.0448 (0.0776) -0.0271 (0.0684) -0.0140 (0.0637) Firm size 0.783*** (0.287) 0.281 (0.433) 0.614* (0.381) 1.424*** (0.362) Firm age 0.673*** (0.247) 0.371** (0.382) 0.512* (0.281) 0.284 (0.272) Leverage 0.481*** (0.0645) 0.588*** (0.0923) 0.489*** (0.0719) 0.381*** (0.0667) Loss 1.425 (1.081) 2.8891 (1.415) 2.237 (1.242) -1.151 (1.235) Year dummies Y Y Y Y Industry dummies Y Y Y Y Constant -16.25** (6.869) -13.61 (9.814) 4.541 (8.610) -39.74*** (8.166) Observations 1280 1280 1280 1280 R-squared 0.336 0.235 0.225 0.238 Standard errors are enclosed in parenthesis. *p < 0.1, **p < 0.05, and ***p < 0.01 Robustness test To confirm robustness, we test whether quality of EM negatively affects ESG performance and whether ESG disclosure is positively associated to EM–CG, using additional robustness analyses discussed below. Overall, the robustness test results are in line with our main conclusions. Endogeneity concerns Many prior studies examine the ESG–EM relationship but report conflicting results (Ahmad et al. 2023 a; Wati and Malik 2021 ; Habbash and Haddad 2020 b), possibly due to methodological weaknesses such as endogeneity issues. Our study suggests potential endogeneity concerns in examining the impact of the quality of EM on ESG performance (Choi et al. 2013 ; Velte 2019 a). Our study addresses endogeneity by utilizing industry means as an instrumental variable and applies an estimator of two-stage least squares (2SLS), using the industry-average DACC as an instrument. Using industry averages as instruments is a long-term standing activities in corporate finance (Bacha and Ajina 2020 ; Chan et al. 2012 ). Our study assumes the exogenous component of quality of EM differs across all industries due to differences in accrual mixes, while the endogenous component varies within the industries (Barth et al. 2005 ; Dechow et al. 1998 ). For instance, Barth et al. ( 2005 ), report that manufacturing companies exhibit more persistent receivables due to similar accounting practices and economic conditions. Separating the endogenous and exogenous mechanisms of variables at the industry-average level helps classify valid instruments for addressing endogeneity problem. The 2SLS results in Tables 6 and 7 are consistent with the baseline findings. Table 6 demonstrates that quality of EM negatively affects overall ESG disclosure and individual pillars, in line with our main results. Table 7 shows that BGD and AC independence act as significant moderators, with improved baseline results for AC independence. This change is attributed to including industry-average DACC, which is related to the type of industry. Industry specialist auditors, if compared to non-specialists, are required to produce audits of a better quality (Abbott et al. 2004 ). Companies with higher AC independence are more expected to involve industry-specialist directors. Industry-specific EM is more likely to be mitigated by industry experts. Results for absolute discretionary accruals Prior research measures EM quality by using both signed and absolute discretionary accruals (Cohen and Malkogianni 2021 ; Jackson 2018 ). Since absolute (unsigned) discretionary accruals include managerial opportunistic usage of discretionary accruals, it is easier to identify companies engaged in income smoothing. The absolute value of the quality of EM detects whether companies are involved in income-increasing or decreasing accruals to meet the targets of earnings (Klein 2002 ; Wang 2006 ). Therefore, our study estimates the empirical model by using absolute (unsigned) discretionary accruals, as reported in Tables 8 and 9 . The outcomes in Table 8 are in line with the baseline association between signed quality of EM and ESG performance for ESG disclosure score and individual ESG disclosure pillar scores, excluding for the governance disclosure pillar score, which is negative and insignificant. The moderating effects of BGD and AC independence are consistent with Table 7 , except that BGD shows a negative effect. Our study attributes this outcome to the possibility that the sampled companies in this analysis may have an income-decreasing absolute DACC. Table 7 Moderating role of mechanisms of CG in ESG–EM association (using absolute discretionary accruals) Variables (1) ESG score (2) Environmental pillar score (3) Social pillar score (4) Governance pillar score ADA (unsigned) 1.890 (3.654) 0.791 (3.933) 3.035 (3.443) 0.534 (3.465) Independent board members 0.472*** (0.0437) 0.361*** (0.0605) 0.438*** (0.0534) 0.290*** (0.0508) ADA * independent board members 0.0321 (0.0445) 0.0417 (0.0481) 0.0807* (0.0441) 0.00187 (0.0355) Board gender diversity 0.202*** (0.0384) 0.129** (0.0493) 0.105** (0.0593) 0.423*** (0.0368) ADA * board gender diversity -0.118*** (0.045) -0.0629** (0.0335) -0.135*** (0.0384) -0.131*** (0.0352) Audit committee independence 0.0143 (0.0218) 0.0164 (0.0384) 0.0114 (0.0352) 0.0141 (0.0343) ADA * audit committee independence 0.144*** (0.0348) 0.0748** (0.0491) 0.0288 (0.0432) 0.308*** (0.0423) Institutional ownership 0.0233 (0.0328) 0.0275 (0.0354) 0.0212 (0.0367) 0.0241 (0.0434) ADA * institutional ownership 0.154*** (0.0338) 0.0638** (0.0381) 0.0278 (0.0442) 0.0309*** (0.0432) Profitability (ROA) 0.0376 (0.0256) 0.0345 (0.0369) 0.0380 (0.0444) 0.0777** (0.0216) Firm size 0.00786 (0.0532) 0.0358 (0.0662) -0.0251 (0.0658) -0.0131 (0.0653) Firm age 0.0255 (0.0289) 0.00689 (0.0434) 0.0351 (0.0549) 0.0245 (0.0523) Leverage 0.663*** (0.285) 0.281 (0.421) 0.612* (0.359) 1.433*** (0.352) Loss 2.154 (4.847) 4.580 (5.425) 2.771 (2.528) -3.887 (4.812) Year dummies Y Y Y Y Industry dummies Y Y Y Y Constant -16.25** (6.789) -13.41 (9.645) 1.532 (8.562) -39.74*** (8.112) Observations 1280 1280 1280 1280 R-squard 0.261 0.173 0.214 0.212 The parentheses surround the standard errors. p < 0.1, p < 0.05, and p < 0.01. Controlling for autocorrelation Our study further tests for potential autocorrelation issues. Our study addresses these issues using yearly sample analysis. Table 10 shows that quality of EM reduces the ESG disclosure score, in line with our baseline results. Therefore, the results of the research do not have autocorrelation problems. Table 8 Relationship between quality of EM and ESG disclosure (annual sample analysis) Variables (1) 2016 (2) 2017 (3) 2018 (4) 2019 (5) 2020 (6) 2021 (7) 2022 (8) 2023 (9) 2024 DACC -0.0610* (0.0323) -0.0787* (0.0271) -0.0773* (0.0327) -0.0832* (0.0189) -0.0639* (0.0253) -0.0842* (0.0327) -0.0539* (0.0237) -0.0349* (0.0423) -0.0255* (0.0112) Independent board members 0.00307 (0.00312) 0.00475** 0.00273 0.00791** (0.00235) -0.00337** (0.00182) 0.00139* (0.00168) 0.00408 (0.00412) 0.00365** (0.00263) 0.00365** (0.00336) 0.00472* (0.00247) Board gender diversity 0.00732** (0.00368) 0.00778** (0.00284) 0.00867*** (0.00255) 0.00983*** (0.00242) 0.00532*** (0.00198) 0.00722** (0.00238) 0.0532*** (0.00384) 0.00967*** (0.00365) 0.00657*** (0.00485) Audit committee independence 0.00582** (0.00267) 0.00275* (0.00231) 0.00506** (0.00198) 0.00403** (0.00152) 0.00310* (0.00172) 0.00462** (0.00377) 0.0375** (0.00321) 0.00301** (0.00164) 0.00412** (0.00214) Institutional ownership 0.00484** (0.00347) 0.00365** (0.00367) 0.00455** (0.00188) 0.00315* (0.00175) 0.00485** (0.00387 0.00305** (0.00174) 0.00385** (0.00341) 0.00355** (0.00277) 0.00272*** (0.00198) Profitability (ROA) 0.00410 (0.00351) 0.00112 (0.00449) 0.00288 (0.00305) -0.00369 (0.00371) -0.00116 (0.00263) 0.00310 (0.00252) 0.00125 (0.00359) 0.00278 (0.00405) 0.00168 (0.0035) Firm size 0.0119 (0.0233) 0.0378 (0.0287) 0.0127 (0.0198) 0.0114 (0.0154) 0.00490 (0.0139) 0.0129 (0.0243) 0.0288 (0.0177) 0.0237 (0.0288) 0.0112 (0.0256) Firm age 0.0149 (0.0342) 0.0268 (0.0147) 0.0237 (0.0248) 0.0387 (0.0243) 0.0480 (0.0249) 0.0229 (0.0344) 0.0298 (0.0287) 0.0447 (0.0378) 0.0278 (0.0267) Leverage 0.0108** (0.0507) -0.000677 (0.0569) 0.00875** (0.00363) 0.00887** (0.00415) 0.00559*** (0.0307) 0.0139*** (0.0214) 0.0372*** (0.0273) 0.0495*** (0.0372) 0.0486 (0.0376) Loss 0.152 (0.246) 0.0628 (0.217) 0.337 (0.284) 0.0782 (0.194) 0.0761 (0.185) 0.164 (0.248) 0.0538 (0.247) 0.0672 (0.284) 0.0552 (0.274) Industry dummies Y Y Y Y Y Y Y Y Y Constant 2.389*** (0.503) 2.039*** (0.436) 2.597*** (0.426) 2.834*** (0.346) 2.905*** (0.320) 2.399*** (0.605) 2.029*** (0.416) 2.487*** (0.506) 2.572 (0.214) Observation 195 175 220 210 177 187 230 200 250 Standard errors are enclosed in parentheses. p < 0.1, p < 0.05, and p < 0.001. Heterogeneity control To control for heterogeneity concerns in ESG performance, the study re-estimates the analysis by using quantile regression at the 25th, 50th, and 75th percentiles of ESG disclosure scores. Table 11 shows that EM quality and ESG results are in line across percentiles, with the negative effect of the quality of EM increasing at higher percentiles. Table 9 Testing the effect’s heterogeneity using quantile regression analysis Variables ESGD score 25th Percentile ESGD score 50th Percentile ESGD score 75th Percentile DACC -0.684* (0.333) -1.077** (0.468) -1.232** (0.558) Independent board members 0.163*** (0.0367) 0.183*** (0.0482) 0.172*** (0.0594) Board gender diversity 0.339*** (0.0420) 0.359*** (0.0569) 0.385*** (0.0655) Audit committee independence 0.160*** (0.0291) 0.167*** (0.0321) 0.168*** (0.0405) Institutional ownership 0.163*** (0.0481) 0.197*** (0.0325) 0.175*** (0.0389) Profitability (ROA) -0.0268 (0.0639) -0.0677 (0.0667) 0.0140 (0.0705) Firm size 1.267*** (0.365) 1.345*** (0.382) 2.005*** (0.464) Firm age 1.347*** (0.265) 1.245*** (0.282) 1.004*** (0.385) Leverage 1.905*** (0.266) 1.679*** (0.266) 1.611 (0.338) Loss 2.423** (1.300) 1.764 (1.293) 2.723* (1.545) Year dummies Y Y Y Industry dummies Y Y Y Constant -16.81* (9.144) -15.05* (8.739) -23.20** (10.41) Observation 1280 1280 1280 The standard errors are shown in parentheses p < 0.1, p < 0.05, and p < 0.01 Analysis of subsample In analysis of subsample, the EM–ESG disclosure score relationship is highly negative but statistically significant for loss companies, supporting that quality of EM lessens environmental sustainability and accounting performance. Most significantly, the study results remain in line after controlling for mechanisms of CG variables such as BIND, BGD, AC independence, and IO, since mechanisms of CG can influence ESG performance (Suttipun 2021 b; Nuhu and Alam 2024 ; Chebbi and Ammer 2022 ; Kamaludin et al. 2022 a; Umar et al. 2024 ; Khaireddine et al. 2020 ; Khalid et al. 2022b; Nicolo et al. 2023 ). Across ESG disclosure score percentiles, our CG mechanisms variables consistently act as potential moderators with a positive effect on corporate ESG performance. Because the first subsample analysis shows EM is insignificant, though negatively related to ESG performance, we also investigate the significance of ROA heterogeneity. Tables 12 and 13 present subsample outcomes for companies with higher and lower ROA. Our results consistently demonstrate a negative connection between quality of EM and ESG disclosure. Firms with the lowest ROA have more expected to experience negative effects of quality of EM, indicating the need for stronger mechanisms of CG. Across both analysis of subsample, mechanisms of CG are statistically positive and significant in increasing ESG disclosure. Table 10 Financial performance-based subsample analysis (firms with profit versus firms with loss; loss value = 0 or 1). Variables (1) Firms with Loss Firms with Profit DACC -2.178*** (0.762) -0.386 (0.351) Independent board member 0.0673*** (0.0669) 0.248*** (0.0383) Board gender diversity 0.447*** (0.0703) 0.305 (0.0537) Audit committee independence 0.158*** (0.0703) 0.147*** (0.0509) Profitability (ROA) 0.143 (0.0730) -0.0433 (0.0688) Firm size 2.181*** (0.527) 0.886** (0.372) Firm age 2.190** (0.475) 0.786** (0.483) Leverage 2.433*** (0.381) 1.953*** (0.265) Loss - - Constant -36.81*** (12.08) -12.05 (8.376) Observations 425 762 R-squard 0.405 0.349 The parentheses surround the standard errors. p < 0.1, p < 0.05, and p < 0.01. Table 11 Financial performance-based subsamples (firms with ROA mean). Variables (1) ESG score strong ROA, ROA > mean (2) ESG score weak ROA, ROA < mean DACC -0.538 (0.429) -1.108* (0.458) Independent board members 0.188*** (0.0556) 0.162*** (0.0566) Board gender diversity 0.344*** (0.0545) 0.369*** (0.0572) Audit committee independence 0.237*** (0.0350) 0.0475 0.0416 Institutional ownership 0.160*** (0.0381) 0.168*** (0.0400) Profitability (ROA) 0.0869 (0.112) 0.0396 (0.108) Firm size 1.471*** (0.438) 1.003*** (0.347 Firm age 2.187*** (0.329) 1.003*** (0.237) Leverage 2.198*** (0.329) 1.953*** (0.409) LOSS 1.734 (1.305) -0.0757 (1.529) Constant -31.61*** (9.820) -13.59 (10.26) Observations 536 491 R-squard 0.364 0.348 The parentheses surround the standard errors p < 0.01, p < 0.05, p < 0.1. Conclusion This research investigates the influence of the quality of EM on ESG performance. Our study also tests whether mechanisms of CG mitigate the influence of quality of EM on ESG performance. Longitudinal data from emerging economies listed firms (2016–2024) confirm that quality of EM decreases ESG performance. This research proposes that companies involved in the quality of EM practices through brownwashing, greenwashing, or managerial entrenchment strategies undermine ESG performance by manipulating sustainability investments. Our study finds that BGD significantly influences the impact of EM quality on ESG performance. This research finding is consistent across ESG disclosure and its three individual pillars; environmental, social, and governance. This result indicates that higher BGD mitigates the negative effect of EM quality on ESG performance, as female directors enhance board monitoring and reduce perceived opportunistic practices. Board independence and institutional or foreign ownership significantly mitigate negative effect of the quality of EM on ESG performance. AC independence does not significantly and positively moderate the impact of EM quality on ESG performance. Our study attributes significant moderating role of board independent members on EM quality–ESG performance to numerous factors. First, CEO duality weakens ability of independent directors to monitor managerial practices effectively. Firms with CEO duality often have independent directors influenced by the CEO’s decisions. Second, independent directors face over-boarding or board busyness risks. Independent directors’ members with manifold directorships attend fewer meetings, reducing their ability to monitor managers’ earnings-driven financial manipulations. Third, independent directors with limited sustainability expertise are less able to detect earnings manipulation in sustainability spending, reducing guidance on greenwashing and brownwashing practices. Thus, BIND moderates the influence of EM quality on ESG performance through their evaluation of economic, environmental, social, and governance sustainability initiatives. Consequently, managerial brownwashing or greenwashing in sustainability programs may go unchecked by independent directors, potentially increasing corporate value. Thus, it examines how ESG disclosure and IO affect EM quality. It also examines how IO moderates the EM–ESG performance relationship. Our study finds that higher EM quality reduces ESG performance, confirming a negative ESG–EM association. Regression results show that IO significantly reduces EM quality practices. Higher IO is linked to lower EM quality behavior. Institutional ownership positively moderates the EM–ESG performance relationship. Practical implication The findings support resource dependence, agency, and stakeholder theories, showing that female directors and CG mechanisms mitigate the impact of EM on corporate sustainability investments. Strong CG mechanisms enhance board diversity. Weak CG practices limit the effectiveness of CG attributes. Companies with stronger ESG performance can gain more from BGD. Increasing women on boards enhances ESG initiatives and performance. Nevertheless, some mechanisms of CG, like AC independence, affect only the governance score. Overall ESG disclosure and individual pillar scores depend on the mechanisms of CG ability to balance reducing EM quality and enhancing CSP. Higher IO limits the quality of EM practices. Higher IO in emerging market firms lowers EM practices. These findings benefit policymakers, regulators, stakeholders, and firm management. Policymakers and regulators should enhance ESG disclosure by updating CG codes. The research impulses regulators to strengthen market oversight, especially for companies with higher IO. The results encourage firms and stakeholders in Pakistan, Indonesia, and Malaysia to enhance ESG performance. Emerging economies should favor institutional investors, as they enhance non-financial disclosure transparency and reduce opportunistic behavior of managerial activity in FRQ. Our study results highlight FRQ as a consistent measure of asymmetric information for stakeholders. Companies with higher ESG disclosure are more likely to involve in quality EM practices. The study supports BIND members’ role in mitigating EM. The study demonstrates that BIND members act as a governance mechanism, mitigating the positive influence of quality of EM on ESG performance. High-quality EM practices, driven by managerial entrenchment, lead to overestimated sustainability investments, reducing corporate value. Firms with higher-quality practices of EM need strong mechanisms of CG to curb EM and limit managerial brownwashing or greenwashing in CSI. These mechanisms of CG inputs provide stakeholders with practical implications. In practice, managerial behavior of opportunism affects not only FP but also reduces resources and capital needed to improve ESG performance. The lower-carbon emission and lower environmental management scores are redirected for the personal use of managers. Without conditioning mechanisms of CG on the EM-ESG performance nexus to diminish the negative effect of quality of EM practices, our outcomes show CG mechanism positively contributes to ESG performance and individual ESG pillar scores, while EM quality practices retain a negative coefficient. Our findings show that BGD, BIND members, and IO have strong moderating effects on CSP, while AC_IND are weaker mechanism of CG. Our research also contributes to the understanding of the implications of heterogeneity of ESG performance. Robustness results reveal a negative relationship between three ESG percentile scores and the quality of EM practices. We make confirm that influence of quality of EM on ESG disclosure score is lower for companies in the lower percentiles and higher for those in higher percentile, showing that poor EM quality practices can disintegrate CSP. Companies participating in practices of EM, and also believing that some profits remain in books of accounts, might sooner experience of share price overvaluation or mispricing. We provide investors strong evidence that their socially responsible investment (SRI) decisions, which are in line with their ethical beliefs, should not be heavily influenced by the existence of profits. Investors should assess firms’ ROA relative to the industry, which suggests that investing in SRIs would be a better strategic move, and evaluate companies’ sustainability initiatives performance. Our findings demonstrate that companies with weaker ROA (below the companies’ ROA average) still face the constraint influence of EM quality practices on ESG performance, whereas companies with stronger ROA above the industry mean do not. Limitation and future research Similar to previous research, our research has several limitations. First, among the mechanisms of CG moderating the connection between quality of EM practices and corporate ESG performance, we discover consistent and strong support for BGD, BIND members, and IO, but not for AC_IND. We believe with full confidence that further better mechanisms of CG, such as concentrated ownership, shareholder activism, board expertise, and frequency of board meetings, could moderate the relationship between EM practices quality and corporate ESG performance. Future research can investigate these potential moderator variables. Second, we consider only sign and absolute discretionary accrual-EM, without including measurement of real-EM. Future studies may examine this, as mechanisms of CG may play different roles in accrual and real-based EM. As literature of CG suggests that experience and diversity of female board directors increase board performance, not considering female directors’ board capital attributes limits the explanation of the heterogeneous effect of BGD on EM practices quality and ESG performance. Future research could examine how women directors’ attributes of capital such as, experience, expertise, education, political ties, social interlocking and age heterogeneously affect quality of EM and corporate ESG performance. Future studies may also examine CG mechanisms such as, CEO duality, CEO power, board diligence, promoters’ equity holdings, external audit, internal audit, audit quality, ethical leadership, and risk management framework. Declarations Conflict of Interest The authors declare no conflict of interest. Funding This research received no external funding. 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Bus Strategy Environ 30(4):2209–2223 Zumente I, Lāce N (2021) ESG Rating—Necessity for the Investor or the Company? Sustainability 13 (16):8940 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9311011","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":617044501,"identity":"9803c390-7eec-4027-8074-36d997a23b6e","order_by":0,"name":"Muhammad Safdar","email":"","orcid":"","institution":"Universitas Airlangga, Surabaya, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Safdar","suffix":""},{"id":617048704,"identity":"e78022f9-a649-4437-9217-516bc9b61aad","order_by":1,"name":"Basuki Basuki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYBACAyBmbDCw4WeQAPMhJEMCG0EtaZINJGphOAzTAgN4tJizH38mOaPgvAS/dAObdEGNRT4D++EHDA/KcGux7Mkxk9xgcFtCcs4BNukZxyQsG3jSDBgSzuFx2IEcNskHBrfrDG4ksEnzsEkAXZrDwJDYhkfL+efPgFrOSdiDtfwDauF/Q0DLjQSQww5IGEgAtfC2AbVIELDFcsYbY8sZBskSEncONlvz9kkYsEk8MziAzy/m/OkPb/b8sZPgn9188DbPtzoDfv7khw9/4AkxJACMHhAAxcgBojSMglEwCkbBKMAJANweR3aNJ+b0AAAAAElFTkSuQmCC","orcid":"","institution":"Universitas Airlangga, Surabaya, Indonesia","correspondingAuthor":true,"prefix":"","firstName":"Basuki","middleName":"","lastName":"Basuki","suffix":""},{"id":617048705,"identity":"c4d1c7b0-bd84-4f0c-bc6c-9beb9b817213","order_by":2,"name":"Dian Agustia","email":"","orcid":"","institution":"Universitas Airlangga, Surabaya, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Dian","middleName":"","lastName":"Agustia","suffix":""}],"badges":[],"createdAt":"2026-04-03 08:59:01","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9311011/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9311011/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106403098,"identity":"ea7d8597-6a7d-4640-a158-9dce4a3061e4","added_by":"auto","created_at":"2026-04-08 09:13:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2178218,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9311011/v1/bd61d909-1eee-416f-a2cf-758d719e0da5.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eDo quality earnings management practices reduce corporate ESG performance? The moderating effect of corporate governance mechanisms: Empirical evidence from emerging economies\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMost researchers examining the association between the quality of earnings manipulation (EM) practices and corporate sustainability performance generally adopt one of three well-established approaches. The most effective approach is grounded in stakeholder theory, which posits that a firm\u0026rsquo;s societal relations extend beyond creditors and investors to encompass a broad coalition of stakeholder groups. Addressing these groups\u0026rsquo; needs and expectations is inherently challenging, particularly in contexts characterized by information asymmetry. These scholars argue that the managers disclose higher-quality reporting and information in order to mitigate information asymmetry (Aladwey et al. 2021b; Al-Shaer et al. 2018; Arayssi et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hussain et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Husted and de Sousa-Filho \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTheir research studies examine the relationship between various proxies of corporate sustainability initiatives, such as CSR disclosure and quality, EESG disclosure, ESG ratings, scores, and performance, and earnings management (EM). Two previous studies Velte (\u003cspan citationid=\"CR177\" class=\"CitationRef\"\u003e2021\u003c/span\u003ea); (Yang and Tang \u003cspan citationid=\"CR190\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) find that environmental performance initiatives, including carbon performance, reduce accrual-based EM, with managers adopting income-decreasing EM to address environmental issues such as water, solid, and air pollution. This research examines the influence of the quality of EM on corporate ESG performance and further investigates the joint effect of corporate ESG performance and CG mechanisms, as a moderating factor, on EM quality in emerging economies such as Pakistan, Indonesia, and Malaysia.\u003c/p\u003e \u003cp\u003eThe second pathway remains relatively underexplored in studies examining the impact of EM quality on CSP initiatives from an agency theory perspective. According to this research stream, firms are expected to enhance reporting quality by emphasizing socially responsible activities, thereby reducing conflicts of interest through less opportunistic managerial behavior (Mart\u0026iacute;nez-Ferrero et al. \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Al‐Shaer 2020). This research aims to explore how the quality of EM practices, including accrual- and real-based EM, constrains improved CSP, proxied by corporate ESG performance. Agency theory explains how EM practices hinder firms\u0026rsquo; sustainable performance objectives.\u003c/p\u003e \u003cp\u003eAgency theory\u0026ndash;based studies document a negative EM\u0026ndash;sustainability relationship, arguing that higher EM undermines sustainability goals and deteriorates FP (Choi et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Prior et al. \u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Scholtens and Kang \u003cspan citationid=\"CR162\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Velte \u003cspan citationid=\"CR176\" class=\"CitationRef\"\u003e2019\u003c/span\u003ea; Almubarak et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea). Regarding the resource function, whereby directors secure critical resources by reducing EM and preventing firm failure, the third section reviews the literature on the resources provision role of CG boards (Hillman et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Peterson and Philpot \u003cspan citationid=\"CR151\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Fitzsimmons \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Peterson et al. \u003cspan citationid=\"CR152\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Hillman and Dalziel \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). In order to lessen environmental uncertainty and co-opt important outside entities, directors manage internal relationships, structures, diversity, and specialization to mitigate manipulations and prevent corporate failure (Hillman and Dalziel \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Hillman et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Nicholson and Kiel \u003cspan citationid=\"CR145\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough income manipulation may occur before CSP evaluation, current CSP initiatives can signal reduced future EM, consistent with signaling theory (Velte \u003cspan citationid=\"CR177\" class=\"CitationRef\"\u003e2021\u003c/span\u003eb; Litt et al. \u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Theoretically, we examine how conflicts of interest arising from EM practices influence firms\u0026rsquo; motivation toward sustainable performance. Responding to agency theorists, robust CG procedures that strengthen board oversight reduce agency problems by limiting opportunistic behavior in accounting discretion (Jensen \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). We argue that integrating agency, resource dependence and stakeholder theories is more related for examining the association between the quality of EM practices, ESG performance, and CG mechanisms. Integrating these theories helps explain the research question of why CSP initiatives remain low despite substantial firm resources devoted to the sustainable investments\u0026rsquo; decision. While stakeholder theory elucidates the link between the quality of EM practices and corporate ESG performance, agency theory asserts that robust CG procedures enable boards to effectively supervise firm operations.\u003c/p\u003e \u003cp\u003eMany prior studies examining the influence of EM quality on corporate ESG performance are limited in scope and report varied results. Consequently, researchers have devoted increased attention to CSR and EM (Gaio et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Dimitropoulos 2022b; Ahmad et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003eb; Habbash and Haddad \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003ec; Buertey et al. 2020; Cho and Chun \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Gras-Gil et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003eb; Palacios-Manzano et al. \u003cspan citationid=\"CR149\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kim et al. \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2019\u003c/span\u003eb; Tran et al. \u003cspan citationid=\"CR169\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mart\u0026iacute;nez-Ferrero et al. \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ben Amar and Chakroun \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), ESG disclosure and EM (Almubarak et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003eb; Gerged et al. 2023b; Sun et al. \u003cspan citationid=\"CR167\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Borralho et al. 2022b), ESG performance and EM (Pathak and Gupta \u003cspan citationid=\"CR150\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kolsi et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2023\u003c/span\u003eb; Velte \u003cspan citationid=\"CR176\" class=\"CitationRef\"\u003e2019\u003c/span\u003eb; Velte \u003cspan citationid=\"CR176\" class=\"CitationRef\"\u003e2019\u003c/span\u003ea), EM and ESG disclosure (Liu et al. \u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e2023\u003c/span\u003ec), EM and ESG performance, and FP (Habib 2023; Gargouri et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003ea; Griffin et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fang et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Velte \u003cspan citationid=\"CR177\" class=\"CitationRef\"\u003e2021\u003c/span\u003ea; Litt et al. \u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR182\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and ESG disclosure and FP (Albitar et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Alareeni and Hamdan \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chen and Xie \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Khan \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Bruna et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Alfalih \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shakil \u003cspan citationid=\"CR164\" class=\"CitationRef\"\u003e2021\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eWe extend the understanding of the association between EM quality and ESG performance and discuss why CSP initiatives may decline and how effective board oversight can mitigate this. The agency and stakeholder theory literature remains limited in that it has not empirically addressed both conjectures. The influence of opportunistic behavior in accounting discretion (e.g., EM) on CSI (e.g., ESG performance) is mitigated by comprehensive monitoring functions (e.g., CG mechanisms).\u003c/p\u003e \u003cp\u003eRegarding CG, prior studies examine its effect on EM (Xie et al. \u003cspan citationid=\"CR186\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Yang and Krishnan \u003cspan citationid=\"CR189\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Davidson et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Kapoor and Goel \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Usman et al. \u003cspan citationid=\"CR173\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Most of this previous research focused on board and AC characteristics. Although there is no consensus on specific governance factors, effective CG mechanisms are widely accepted as constraining EM. Gerged et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e) indicated that previous research has not examined the joint influence of internal governance mechanisms and disclosure quality on the quality of EM practices. Their research examines this relationship in Jordan and reports a significant negative connection between EM practices and disclosure quality. Although their study finds an insignificant CG\u0026ndash;EM association, it suggests that disclosure outperforms internal governance in constraining EM.\u003c/p\u003e \u003cp\u003eGiven the rising global emphasis on ESG performance, firms in emerging markets face increasing scrutiny regarding their financial and non-financial practices. The quality of EM is central to FRQ, with ongoing debate regarding its effects on corporate transparency and sustainability performance. \u0026ldquo;A critical question arises: Does EM quality negatively affect corporate ESG performance in emerging markets?\u0026rdquo; Furthermore, CG mechanisms, including board independence, audit committee independence, board gender diversity, and institutional ownership, mitigate opportunistic financial reporting behavior. Therefore, it is essential to examine whether CG mechanisms moderate the association between EM quality and corporate ESG performance.\u003c/p\u003e \u003cp\u003eThis study investigates the direct relationship between EM quality and corporate ESG performance in the context of emerging economies, namely Pakistan, Indonesia, and Malaysia. Moreover, it also examines the moderating effect of CG mechanisms in the association between EM quality and corporate ESG performance. Specifically, our research explores opportunistic and optimal hypotheses of corporate ESG performance using non-financial firms listed on emerging-market stock exchanges over the period 2016\u0026ndash;2024.\u003c/p\u003e \u003cp\u003eOur study makes four key contributions; first, it extends limited literature review on negative influence of the quality of EM practices on CSP. We find that tenacious managerial EM erodes CSP efforts. Most prior research focuses on the influence of CSD in reducing practices of EM (Mohmed et al. \u003cspan citationid=\"CR141\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Habbash and Haddad \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003ea; Ehsan et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003eb; Dimitropoulos \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e; Shi et al. \u003cspan citationid=\"CR165\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Velte \u003cspan citationid=\"CR176\" class=\"CitationRef\"\u003e2019\u003c/span\u003ea). We adopt a reverse perspective, positing that EM quality may constrain sustainability performance practices (measured by ESG performance). Second, prior studies on EM and CSR have largely relied on the Jones and Modified Jones models Gras-Gil et al. (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003ea) ; (Palacios-Manzano et al. \u003cspan citationid=\"CR149\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dimitropoulos \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e; Yang and Tang \u003cspan citationid=\"CR190\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Accordingly, to address empirical differences, this study adopts the performance-matching model of Kothari et al. (\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2005\u003c/span\u003ea) to measure accrual-based EM in relation to ESG performance. The performance-matching model, in contrast to the modified Jones model, accounts for ROA since companies with abnormal performance would otherwise be mistakenly identified as manipulating earnings. As a result, Kothari's model reduces specification bias and heteroskedasticity in EM estimation.\u003c/p\u003e \u003cp\u003eThird, our study examines CG mechanisms BIND, BGD, AC independence, and INSOWN as moderators of the EM\u0026ndash;ESG performance relationship. Fourth, our study offers a new explanation for differences in corporate ESG performance. This study is among the first to integrate agency Jensen (\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e1986\u003c/span\u003e), stakeholder Freeman (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) ; (Freeman \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1984\u003c/span\u003e), and resource dependence Hillman and Dalziel (\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) theories to examine EM quality and ESG performance in emerging markets such as Pakistan, Indonesia, and Malaysia.\u003c/p\u003e \u003cp\u003eOur study finds partial evidence that BIND, BGD, and INSTOWN mitigate the negative influence of EM quality on corporate ESG performance. Contrasting previous research Zalata et al. (\u003cspan citationid=\"CR191\" class=\"CitationRef\"\u003e2022\u003c/span\u003eb) ; (Alves \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Triki Damak \u003cspan citationid=\"CR170\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mnif and Cherif \u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lara et al. \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), our findings show that BGD deters earnings manipulation and improves investment decisions. Agency theory emphasize that BGD reduces EM practices Arun et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) ; (Gull et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Alves \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), while stakeholder theory contends that it improves ESG performance by reducing financial risks and ESG controversies (Shakil \u003cspan citationid=\"CR164\" class=\"CitationRef\"\u003e2021\u003c/span\u003eb). According to our research, female board members have a moderating influence on the relationship between corporate ESG performance and EM quality. This indicates that companies with BGD are more expected to prevent managers\u0026rsquo; manipulative behaviors. Consequently, more funds are allocated to value-added ESG activities.\u003c/p\u003e \u003cp\u003eFindings indicate that BIND significantly constrains the quality of EM practices. Furthermore, BIND, as a governance mechanism, moderates the EM\u0026ndash;ESG link, supporting findings of (Abdelfattah \u0026amp; Elfeky, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, INSTOWN is positively associated with EM quality, emphasizing the passive role of institutional investors in emerging economies. Furthermore, INSTOWN moderates the EM\u0026ndash;ESG performance link as a CG mechanism. These findings align with previous results by (Abdelfattah \u0026amp; Elfeky, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e"},{"header":"Literature review and development of our hypothesis","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eEM and ESG performance\u003c/h2\u003e\n\u003cp\u003eEM is employed through opportunistic behavior and short-term strategies to manipulate the quality of financial reports and mislead some stakeholders or serve contractual purposes (Healy and Wahlen \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e; Dechow et al. \u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e; Xie et al. \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e; Gargouri et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003eb; Choi et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). This practice is widely criticized for undermining firms\u0026rsquo; long-term CSI and credibility of FRQ (Ehsan et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003ea). Stakeholders thus become more vigilant and increasingly skeptical of FRQ information (Choi et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Managers are involved in corporate ESG disclosure activities to gain stakeholders\u0026rsquo; trust and build long-term relationships (Escrig-Olmedo et al. 2019a; Zumente and Lāce \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003ePrevious studies by Gras-Gil et al. (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003eb); (Choi et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kim et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003eb; Buertey et al. 2020; Ehsan et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003eb; Palacios-Manzano et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yang and Tang \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Velte \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003ea) report varied findings on the impact of combined and individual ESG disclosure pillars and performance activities on EM quality. There is still limited empirical evidence on how EM quality influences corporate ESG initiatives. Most prior research on EM quality\u0026rsquo;s effect on CSR report mixed results. CSR has been viewed by some research, based on agency theory, as a managerial opportunistic tool to conceal manipulative behavior practices and mislead some of the stakeholders (Gras-Gil et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003eb). According to Prior et al. (\u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e), CSR activities help managers mitigate the negative effects of EM quality by enhancing stakeholder satisfaction and reducing scrutiny and activism. By utilizing a sample of 593 companies from 26 different countries (2002\u0026ndash;2004), these studies demonstrate a positive influence of EM quality on CSR (Gavana et al. (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003ea; (Borralho et al. \u003cspan class=\"CitationRef\"\u003e2022a\u003c/span\u003e; Rahman and Zheng \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Managers engaging in EM quality may use CSR spending to distract stakeholders and to hide opportunistic behavior.\u003c/p\u003e\n\u003cp\u003eHowever, prior studies indicate a negative effect of EM quality on CSR. Based on 1,960 non-financial listed firms from 26 different countries, Mart\u0026iacute;nez-Ferrero et al. (\u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) find greater stakeholder orientation and CSR adoption where the managers\u0026rsquo; have less incentives to engage in EM. Ehsan et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003eb) reported a negative association between CSR and EM quality in the context of Pakistani manufacturing sector companies. Hickman et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) found a negative influence of voluntary and mandatory CSR on EM in the context of non-financial companies listed on the BSE during 2012\u0026ndash;2017. The authors argue that managers provide accurate, reliable, and transparent information to support a long-term stakeholder-oriented perspective. Managers using fewer deceptive tactics are more likely to pursue CSR to support high-quality reporting and sustain long-term stakeholder relationships. Meanwhile, the CSI literature has yet to resolve how EM quality reduces ESG performance. We argue that the managerial opportunism behavior in the context of income smoothing and ESG spending may alter the objectives of ESG performance. Firms often signal commitment to CSI through both symbolic and substantive practices (Eliwa et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Maaloul et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). This substantive view proposes that firms use CSI to engage in greenwashing, masking poor earnings quality and reducing stakeholder scrutiny. This allows managers to conceal earnings irregularities due to weak ESG reporting regulation.\u003c/p\u003e\n\u003cp\u003eConversely, the symbolic view holds that firms opportunistically disclose high ESG commitment despite poorer performance to enhance ESG disclosure score (Nazari et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Koh et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Managers may engage in brownwashing by manipulating discretionary R\u0026amp;D and sustainability spending to understate ESG-related costs (Kim and Lyon \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ma et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Thus, manipulating ESG investment enables firms to involve in brownwashing or greenwashing, distorting true ESG performance through opportunistic behavior that increase or decrease corporate performance. Previous studies argue that firms\u0026rsquo; false sustainability reporting to signal environmental responsibility makes greenwashing in the context of sustainable investments decisions a source of EM (Kim and Lyon \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lyon and Montgomery \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Mohmed et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Rezaee and Tuo \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zharfpeykan \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eConsequently, greenwashing or brownwashing in corporate sustainable investment decisions undermines sustainability goals and leads to poor ESG performance. Managerial opportunism theory suggests that managers and insiders overinvest in CSI to advance self-interests, resulting in value destruction (Choi et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Harjoto and Jo \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e; Greiner and Sun \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Using German data Velte (\u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003ea) finds a negative effect of EM quality on corporate ESG performance, attributed to heightened risks of eroding stakeholder trust. Based on the preceding literature, this study proposes the first hypothesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEM quality is negatively related with corporate ESG performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBoard gender diversity as a moderator of EM quality\u0026ndash;ESG performance relationship.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFemale board representation strengthens board oversight, curbing managerial opportunism and reducing EM. Gull et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) show that female board presence significantly reduces EM in French firms. Similarly, Zalata et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003ea) find that female directors with financial expertise enhance earnings quality in U.S. firms. Likewise, Zalata et al. (\u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), show that female supervisory directors reduce accrual-based EM in U.S. firms. However, evidence from the UK shows contrasting results. For instance, a research by Arun et al. (\u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) find that greater female board representation in UK firms is linked to conservatism and potentially higher EM quality.\u003c/p\u003e\n\u003cp\u003eWomen directors enhance board transparency and stakeholder communication (Aladwey et al. 2021a; Elmarzouky et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Their attendance brings diverse perspectives and improves decision-making quality (Albitar et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). This strengthens board oversight and enhances stakeholder-oriented decision-making and corporate sustainability performance. Women directors bring diverse experiences and communal traits such as, empathy, supportiveness, and attentiveness that enhance their ability to prioritize stakeholder needs compared to male counterparts (Manita et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003ea; Alkhawaja et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003eb; Khemakhem et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eA growing body of research shows that BGD enhances CSP (Fernandez-Feijoo et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ben-Amar et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)(Aladwey et al. 2021a). Using data from Germany and Austria Velte (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) finds that even a lower level of female board representation (about 20%) is positively and significantly associated with CSP, challenging the \u0026lsquo;critical mass\u0026rsquo; view that at least three women are required on boards. Several studies attribute the positive influence of BGD on ESG performance to female directors\u0026rsquo; unique experience, expertise, and regulatory influences (Yahya \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e; Khatri \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cambrea et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cucari et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Beyond reducing earnings manipulation, female directors tend to allocate surplus cash flows to CSI due to strong communication-related skills (Suttipun \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003ea), ethical commitment (Arayssi et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), and intellectual and interpersonal capabilities (Shakil \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003eb). Similarly, Van Hoang et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) show that greater female board representation in U.S. firms reduces manipulation in environmental disclosures and enhances the quality of environmental reporting.\u003c/p\u003e\n\u003cp\u003ePrior research has examined links between BGD, CSP, and the quality of EM from multiple perspectives. Some studies examine BGD and EM practices (Arun et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zalata et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003eb; Mnif and Cherif \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Alves \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), while others focus on BGD and CSR (Manita et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003eb; Alkhawaja et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003ea; Wasiuzzaman and Subramaniam \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Khemakhem et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wasiuzzaman and Wan Mohammad \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Cucari et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Al Fadli et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, these perspectives produce mixed findings. This research examines the dual role of female board members in mitigating EM in relation to corporate ESG performance. Women enhance board diversity and effectiveness by better addressing diverse stakeholder needs. Consequently, this enhances the firm\u0026rsquo;s sustainability performance. Moreover, stronger board effectiveness reduces agency costs and limits EM. Thus, BGD strengthens the negative connection between CSP and EM quality. This research examines whether women board representation moderates the relationship between EM quality and CSP. Drawing on theories and prior research on BGD role in reducing EM quality and strengthening the ESG\u0026ndash;EM nexus in emerging markets, we propose the third hypothesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBGD moderates association between the quality of EM practices and corporate ESG performance nexus\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eBoard independence as a moderator of the EM quality\u0026ndash;ESG performance relationship\u003c/h3\u003e\n\u003cp\u003eConsistent with agency theory, the board of directors plays a critical monitoring role (Hillman and Dalziel \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e). Board independent members exercise impartial judgment by objectively evaluating FP with minimal CEO influence (Jizi \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). As external managers, independent directors seek to build reputation and protect human capital by signaling decision-making expertise to the market (Fama and Jensen \u003cspan class=\"CitationRef\"\u003e1983\u003c/span\u003e). Their presence strengthens board independence oversight (Beasley \u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e; Fama and Jensen \u003cspan class=\"CitationRef\"\u003e1983\u003c/span\u003e), reduces asymmetric information, and enhances integrated reporting quality (Chouaibi et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hussainey et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Albitar et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, they play a key role in diminishing financial fraud (Beasley \u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e). A higher proportion of board independent members strengthens oversight objectivity, curbs managerial opportunism, and reduces abnormal accruals and agency costs (Abdou et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Klein \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eBeekes et al. (\u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e) suggest that an independent board of directors must meet two key conditions to perform its monitoring responsibilities effectively. First, incentives such as share ownership are needed to sustain commitment to monitoring duties. Second, they must possess sufficient knowledge to understand how managerial decisions affect the financial reporting system. For example, they should recognize that reducing R\u0026amp;D expenses can temporarily increase current earnings. Experienced independent directors detect earnings manipulation through their expertise. Those with insights into greenwashing (Mohamad et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Rezaee and Tuo \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zharfpeykan \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) and brown washing (Kim and Lyon \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) help address overinvestment and insufficient sustainability cost disclosure, reducing EM practices and improving sustainability performance.\u003c/p\u003e\n\u003cp\u003eConversely, independent directors with limited understanding of firm- or industry-level sustainability practices face greater challenges in effective monitoring. They may offer less strategic guidance, thereby increasing information asymmetry due to limited access to relevant disclosures (Garcia Osma \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e). This lack of expertise may limit their ability to distinguish genuine from opportunistic sustainability initiatives, potentially undermining the firm\u0026rsquo;s sustainability goals. Additionally, Xie et al. (\u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) identify circumstances in which independent directors may struggle to fulfill their oversight roles. For instance, infrequent board meetings and multiple board memberships can weaken directors\u0026rsquo; effectiveness in mitigating sustainability-related manipulations. The issue worsens when overburdened directors have long tenures, reducing their focus on monitoring responsibilities.\u003c/p\u003e\n\u003cp\u003eThe independent board of directors plays a vital role in shaping CSR disclosure and initiating corporate social disclosure programs (Jizi \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Board independent members significantly contribute by increasing attention to sustainability and environmental problems (Shrivastava and Addas \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). They also protect their reputations by promoting transparency in disclosing a company\u0026rsquo;s ESG activities. This signals to the market that the organization is committed not only to financial performance but also to advancing social welfare (Arayssi et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eSeveral studies Shrivastava and Addas (\u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e), (Jizi \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Hussain et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), (Husted and de Sousa-Filho \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), and (Lagasio and Cucari \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), demonstrate a positive association between BIND and corporate ESG disclosure. Shrivastava and Addas (\u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e), using an international context sample (2010\u0026ndash;2014), found that companies with higher proportions of independent board directors achieve stronger ESG disclosure scores and that appointing independent advisors with environmental and sustainability expertise enhances governance in these areas. Similarly, Jizi (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), analyzing FTSE 350 UK firms (2007\u0026ndash;2012), found a positively and significantly influence of BIND on CSR disclosure, underscoring the significance of board governance structures in shaping CSR disclosure score that benefit stakeholders. Additionally, Hussain et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), examining U.S. firms (2007\u0026ndash;2011), showed that board independent members positively influence the individual ESG pillars of corporate ESG performance. By emphasizing the role of independent board members in limiting EM and encouraging CSI engagement, greater board independence is expected to weaken the negative relationship between EM quality and CSP. Thus, the following hypotheses for the fourth study are proposed:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBIND moderates the association between EM quality and corporate ESG performance\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModerating effect of audit committee independence on the relationship between EM quality and corporate ESG performance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to resource dependence theory, which suggests that a primary responsibility of the board of directors is to provide essential resources to firms (Hillman and Dalziel \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e). The inclusion of independent board members on the audit committee enhances the diversity of resources accessible to organization. Compared with affiliated members, AC independent members are anticipated to exhibit greater impartiality and expertise (Carcello and Neal \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e). AC independence improves the effectiveness of financial reporting quality oversight. Additionally, independent committee members are motivated to uphold high oversight standards to protect or enhance their reputational capital (Abbott et al. \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003ePrior studies show that the independence of the AC influences FRQ Bhuiyan and D\u0026rsquo;Costa (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) ; Oussii and Boulila Taktak \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; De Vlaminck and Sarens \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) and also directly affects performance and non-financial reporting. This includes mandatory and voluntary CSR disclosures Appuhami and Tashakor (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) ; (Mohammadi et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Arif et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) ESG reporting Buallay \u0026amp; Al-Ajmi (2020), and sustainability report assurance (Al-Shaer and Zaman \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zaman et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Mohammadi et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), find that AC size, independence, and financial expertise significantly enhance voluntary CSR disclosures in 150 Iranian listed firms. Arif et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) find that AC activism and independence are significantly and positively associated with corporate ESG disclosure, with the strongest effect on the environmental pillar relative to the social and governance pillars. Dwekat et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) find that AC independence, meeting frequency, financial expertise, and CSR committee presence significantly enhance CSR assurance adoption in STOXX 600 European firms.\u003c/p\u003e\n\u003cp\u003eConversely, Wang and Sun (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003eb) show that AC independence is not significantly related to CSR or environmental disclosures in China. They attributed this disparity to unique governance structures, cultural influences, and the political and social connections prevalent in Chinese companies, which can undermine the independence of audit committee members. Likewise, Pucheta-Mart\u0026iacute;nez et al. (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) explored the impact of AC characteristics (directors\u0026rsquo; independence and the presence of executives and directors at AC meetings) on CSR disclosure by utilizing an international sample comprising a total of 13,264 firm-year observations of listed non-financial companies over the period 2007\u0026ndash;2018. The findings showed that directors\u0026rsquo; independence and executives on the AC have a negative influence on CSR disclosure, while directors\u0026rsquo; presence at AC meetings is positively related to CSR disclosure.\u003c/p\u003e\n\u003cp\u003eA substantial body of research grounded in agency theory highlights the importance of AC independence in mitigating fraudulent accounting activities. For instance, Klein (\u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e), using a large sample in the context of U.S. companies, identified a negative association between AC independence and abnormal discretionary accruals. Likewise, Mohd Saleh et al. (\u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e) reported that attendance of AC-independent members is related to a decrease in the EM quality. However, other related research, such as those by Choi et al. (\u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e), Xie et al. (\u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), Abdullah and Nasir (\u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e), Baxter and Cotter (\u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e), He and Yang (\u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Habbash et al. (\u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e), find no significant influence of AC independence on curbing EM. To address these mixed findings, meta-analytical research has been conducted to explore the relationship further. Previous studies by Garc\u0026iacute;a-S\u0026aacute;nchez et al. (2019a), Inaam and Khamoussi (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e), and Hasan et al. (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) consistently conclude that AC independence is a key corporate governance mechanism for constraining EM. Overall, the presence of independent members on the AC plays a crucial role in overseeing and limiting earnings manipulation practices.\u003c/p\u003e\n\u003cp\u003eGiven the pivotal role of AC independence in curbing opportunistic behavior practices such as EM and fostering greater transparency through engagement in ESG activities, it is anticipated that AC independence moderates the connection between the quality of EM and corporate ESG performance. Accordingly, the following hypothesis is proposed:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH4\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe presence of AC independence moderates the association between the quality of EM practices and the corporate ESG performance nexus\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModerating effect of institutional ownerships on the quality of EM practices and corporate ESG performance nexus\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe firms' ESG performance is significantly influenced by institutional investors, although empirical evidence on their influence varies. Previous studies like Dyck et al. (\u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), Garcia and Orsato (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Chen et al. (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) highlight that institutional investors often drive stronger ESG practices and increase ESG-related activities. However, others, such as (Harjoto et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Meng and Wang \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), suggested that firms with higher institutional ownership may reduce investments in corporate social responsibility or experience declines in institutional ownership with improved ESG scores. This discrepancy arises due to variations in institutional investor types. Long-term investors tend to promote corporate sustainability by enhancing governance and restraining managerial misbehavior, aligning with long-term value creation (Harford et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kim et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003ea; Velte \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Conversely, short-term investors prioritize short-term profits, leveraging informational advantages through active trading (Yan and Zhang \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eRegarding the effective monitoring hypothesis, agency theory suggests that institutional ownership reduces opportunistic behavior (Al-Duais et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Jenson and Meckling \u003cspan class=\"CitationRef\"\u003e1976\u003c/span\u003e). Nevertheless, prior evidence on the influence of institutional ownership on EM quality remains limited in emerging markets such as Pakistan, Indonesia, and Malaysia. Ramalingegowda et al. (2021) show that firms with higher institutional ownership are less likely to engage in EM due to the monitoring role of institutional investors. This study aligns with and supports the findings of Sakaki et al. (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Ajay and Madhumathi (\u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), showing that institutional ownership is associated with higher earnings quality (lower EM), suggesting that institutional investors constrain EM. Additionally, Al-Duais et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) report that institutional ownership provides stronger incentives to enhance FRQ and reduce REM, as this mechanism benefits the firm. Ahmad et al. (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003ea) find that institutional or foreign ownership prevents managers from engaging in EM practices. Nevertheless, other prior studies document that institutional or foreign ownership positively affects EM behavior (Debnath et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003ePrevious studies posit that institutional or foreign ownership is positively and significantly associated to corporate ESG performance (Wang et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003eb; Liu et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003eb; Jiang et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Previous research indicates that while high ESG disclosure scores are often related to better sustainability practices, they do not always preclude real EM. Companies may still engage in real EM by manipulating operating cash flows, production levels, or discretionary expenditures for strategic purposes. For example, firms might increase sales through discounts to reduce the fixed cost per unit, overproduce, or cut discretionary expenses such as advertising and R\u0026amp;D, aligning with short-term financial goals even within a high ESG framework (Al Barrak and Kouaib \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eInstitutional or foreign ownership, measured by the percentage of outstanding shares held by organizations, is a key CG mechanism that reduces information asymmetry and monitors agents\u0026rsquo; performance (Eissa et al. 2023). Institutional or foreign ownership is gradually focused on environmental, economic, social and governance problems. The effect of institutional or foreign ownership on ESG\u0026ndash;EM connections is expected for numerous theoretical perspective reasons. Firstly, institutional or foreign ownership has greater responsibilities toward corporate outcomes. Since engagement in EM practices may lead to involvement in fraudulent actions and damage FRQ Md Nasir et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e); Rahman et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e), institutional ownership has strong inducements to alleviate such type of practices through proper monitoring of actions by management. Secondly, institutional or foreign ownership, the most powerful capital providers, has a stronger inducement to monitor companies (Rahman \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Empirical evidence shows that little is known about how firms having higher institutional or foreign ownership influence EM behavior, and previous research that examined this connection is limited (Ahmad et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003ea; Mehrani et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Al-Duais et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Akter et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). This previous research has shown that companies with higher institutional or foreign ownership are positively and significantly associated with higher quality earnings, suggesting that institutional or foreign ownership curbs EM behavior. Nevertheless, no research study has considered examining the moderating influence of institutional or foreign ownership on the ESG\u0026ndash;EM relationship. Therefore, this research attempts to extend prior studies by examining the moderating influence of institutional or foreign ownership on the ESG performance\u0026ndash;EM nexus in Pakistani, Indonesian, and Malaysian companies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH5\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitutional or foreign ownership moderates the association between the quality of EM practices and the ESG performance nexus\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eList of representative sample firms and their respective industries\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eIndustries\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFinal sample\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eObservations\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e(1) Pakistan\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAutomobile\u003c/p\u003e\n\u003cp\u003eChemicals\u003c/p\u003e\n\u003cp\u003eFertilizer\u003c/p\u003e\n\u003cp\u003eOil \u0026amp; Gas\u003c/p\u003e\n\u003cp\u003ePharmaceutical\u003c/p\u003e\n\u003cp\u003eTextile\u003c/p\u003e\n\u003cp\u003eFoord \u0026amp; beverage\u003c/p\u003e\n\u003cp\u003eCement\u003c/p\u003e\n\u003cp\u003eTelecommunication\u003c/p\u003e\n\u003cp\u003eFinancial services\u003c/p\u003e\n\u003cp\u003eEngineering\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(2) Malaysia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAutomobile\u003c/p\u003e\n\u003cp\u003eChemicals\u003c/p\u003e\n\u003cp\u003eCement\u003c/p\u003e\n\u003cp\u003eEnergy\u003c/p\u003e\n\u003cp\u003eTelecom\u003c/p\u003e\n\u003cp\u003eConstruction\u003c/p\u003e\n\u003cp\u003eHealthcare\u003c/p\u003e\n\u003cp\u003eFinancial services\u003c/p\u003e\n\u003cp\u003eTechnology\u003c/p\u003e\n\u003cp\u003eConsumer goods\u003c/p\u003e\n\u003cp\u003eReal Estate\u003c/p\u003e\n\u003cp\u003eUtilities\u003c/p\u003e\n\u003cp\u003eIndustrial goods\u003c/p\u003e\n\u003cp\u003eTransportation\u003c/p\u003e\n\u003cp\u003eRetails\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(3) Indonesia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAutomobile\u003c/p\u003e\n\u003cp\u003eChemicals\u003c/p\u003e\n\u003cp\u003eCements \u0026amp; Cements Products\u003c/p\u003e\n\u003cp\u003eEnergy\u003c/p\u003e\n\u003cp\u003eTelecom\u003c/p\u003e\n\u003cp\u003eMining\u003c/p\u003e\n\u003cp\u003eConstruction\u003c/p\u003e\n\u003cp\u003eConsumer Goods\u003c/p\u003e\n\u003cp\u003eFinancial services\u003c/p\u003e\n\u003cp\u003eHealthcare\u003c/p\u003e\n\u003cp\u003eReal Estate\u003c/p\u003e\n\u003cp\u003eTechnology\u003c/p\u003e\n\u003cp\u003eTransportation\u003c/p\u003e\n\u003cp\u003eUtilities\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e292\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2628\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\"\u003e\u003cstrong\u003eSource\u003c/strong\u003e: Information collected from Bloomberg Database\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003eMethodology and Research Design\u003c/h3\u003e\n\u003cp\u003eThe data, study models, variable descriptions, and measurement techniques are presented in this section. The research provides empirical models to ensure the testing of the study hypothesis.\u003c/p\u003e\n\u003ch3\u003eData sources and samples\u003c/h3\u003e\n\u003cp\u003ePanel data estimation approaches were used in this study. Time-series and cross-sectional units (firms) are combined in panel data estimation, enabling a longitudinal design to assess changes in organizational variables over time. This contrasts with cross-sectional designs, which lack time dynamics in variables (Sekaran \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). Using purposive sampling, the study covers 50 Pakistani, 110 Indonesian, and 132 Malaysian firms over 2016\u0026ndash;2024, totaling 2628 firm-year observations. Purposive sampling is appropriate as it allows researchers to select firms meeting specific inclusion criteria with testable data (Sekaran \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). Following this approach, two inclusion criteria are applied. First, due to their unique reporting regulations and accounting principles, financial firms are not included. Second, firms without ESG performance data are not included.\u003c/p\u003e\n\u003cp\u003eThe Bloomberg database provided the data for every CG mechanism variable. ESG performance data for sampled Pakistani, Indonesian, and Malaysian firms were sourced from Bloomberg. The ESG performance score from Bloomberg spans 0\u0026ndash;100, where 0 indicates the lowest and 100 the highest rating. Disclosure of environmental pollution and greenhouse gas emissions is reflected in the environmental pillar score. The environmental, social, and governance pillar scores have 68, 62, and 56 data points, respectively. Emissions (12%), resource usage (11%), and innovation (11%), make up the environmental disclosure pillar, according to Bloomberg. The social disclosure pillar includes human rights (4.5%), community (8%), workforce (16%), and product responsibility (7%), while the governance disclosure pillar covers shareholders (7%), management (19%), and CSR strategy (4.5%).\u003c/p\u003e\n\u003ch3\u003eEstimating Empirical Models\u003c/h3\u003e\n\u003cp\u003eThis study models the mathematical association between variables in the formulated hypotheses, with the first model examining the association between the quality of EM practices and corporate ESG performance. The second model examines the association between the mechanisms of CG and ESG performance, while the third model analyzes the interaction between the mechanisms of CG and the quality of EM on ESG performance. Control variables are included in each model. Equation No. 1 presents the direct association between the quality of EM practices and ESG performance, including the mechanisms of CG as an additional control variable. Equation No. 2 presents the moderating influence of the mechanisms of CG on the association between the quality of EM practices and ESG performance. The research also examines the influence of quality of EM practices on individual disclosure pillar rating scores (environmental, social, and governance scores), in addition to the dependent variable being ESG performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eESG_\u003c/strong\u003e \u003csub\u003e \u003cstrong\u003ei,t\u003c/strong\u003e \u003c/sub\u003e \u003cem\u003e= \u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eDACC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eBoardSize\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eIndepBM\u003c/em\u003e\u003csub\u003e\u003cem\u003ei.t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eBGenderD\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;5AuditCommIndep\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e,\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e 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\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e12\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eFage\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e13\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eLeverage\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e,\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e+ \u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e14\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eLOSS\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e,\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e+ \u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e15\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eYear_dummies\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eIndustry_dummies\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026epsilon;\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e \u003cstrong\u003e(1)\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eESG_\u003c/strong\u003e \u003csub\u003e \u003cstrong\u003ei,t\u003c/strong\u003e \u003c/sub\u003e \u003cem\u003e= \u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eDACC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eBoardSize\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e,\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e+ \u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eIndepBM\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e,\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e+ \u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eBGenderD\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e,\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e+ \u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e5\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eAuditCommIndep\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eInstiOwner\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e7\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eDACC \u0026lowast; BoardSize\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eDACC \u0026lowast; IndepBM\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e9\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eDACC \u0026lowast; BGenderD\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e10\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eDACC \u0026lowast; AuditCommIndep\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eDACC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e* \u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e12\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eInstiOwner\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e13\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eROAi\u003c/em\u003e\u003csub\u003e,\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e14\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eFSize\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e15\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eFage\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eLeverage\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e17\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eLOSS\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e18\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eYear_dummies\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e19\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eIndustry_dummies\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;\u0026epsilon;\u003c/em\u003e\u003csub\u003e\u003cem\u003ei,t\u0026nbsp;\u003c/em\u003e\u003c/sub\u003e(2)\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n\u003ch2\u003eVariable measurement\u003c/h2\u003e\n\u003cp\u003eConsistent with prior research, this study employs the performance-matching model of Kothari et al. (\u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e) to measure accrual- and real-based EM. Building on the Jones (\u003cspan class=\"CitationRef\"\u003e1991\u003c/span\u003e) model, Kothari et al. (\u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003eb) incorporate a proxy for firms\u0026rsquo; operating performance to reduce misspecification in samples with extreme FP; therefore, normal accruals are estimated using the following models.\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{TAit}{Ait-1}\\right)=\\beta\\:\\)\u003c/span\u003e \u003c/span\u003e \u003csub\u003e0i\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{1}{Ait-1}\\right)+\\:\\beta\\:\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003e1i\u003c/sub\u003e + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\varDelta\\:Sales}{Ait-1}\\)\u003c/span\u003e\u003c/span\u003e + \u0026beta;\u003csub\u003e2i\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{\\varDelta\\:Rev\\:it-Rec\\:it}{Ait-1}\\right)+\\:\\beta\\:\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003e3i\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{PPE\\:it}{Ait-1}\\right)\\)\u003c/span\u003e\u003c/span\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha; \u0026epsilon;\u003csub\u003eit\u003c/sub\u003e (3)\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{TAit}{Ait-1}\\)\u003c/span\u003e \u003c/span\u003e \u003cstrong\u003e=\u003c/strong\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\alpha\\:\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003e0\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\left(\\frac{1}{Ait-1}\\right)\\)\u003c/span\u003e\u003c/span\u003e + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\alpha\\:\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003e1\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{\\varDelta\\:REVit-\\varDelta\\:RECit}{Ait-1}\\right)\\)\u003c/span\u003e\u003c/span\u003e + \u0026alpha;\u003csub\u003e2\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{PPEit}{Ait-1}\\right)\\)\u003c/span\u003e\u003c/span\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha;\u003csub\u003e3\u003c/sub\u003e (ROA\u003csub\u003ei, t\u003c/sub\u003e) + \u0026epsilon;\u003csub\u003ei,t\u003c/sub\u003e (4)\u003c/p\u003e\n\u003cp\u003eTA represents total accruals, are calculated as the difference between operational cash flows and earnings before extraordinary items and discontinued operations. All variables are scaled by lagged total assets to reduce heteroscedasticity. A stand for total assets in year t; \u0026Delta;sales is the change in sales; PPE is the gross value of property, plant, and equipment in year t; ROA is return on assets; and t is the time period. Furthermore, in order to account for extreme values, all continuous variables are winsorized at the 1% and 99% levels. The residual from the above models serves as the proxy for the quality of EM, henceforth denoted as DACC (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eVariables Definitions and Measurements\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eProxies\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eDatabase (source)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAccrual EM\u003c/p\u003e\n\u003cp\u003eAudit Committee Independence\u003c/p\u003e\n\u003cp\u003eBoard independence\u003c/p\u003e\n\u003cp\u003eBoard gender diversity\u003c/p\u003e\n\u003cp\u003eInstitutional ownership\u003c/p\u003e\n\u003cp\u003eESG\u003c/p\u003e\n\u003cp\u003eESG\u003c/p\u003e\n\u003cp\u003eFirm size\u003c/p\u003e\n\u003cp\u003eFirm age\u003c/p\u003e\n\u003cp\u003eROA\u003c/p\u003e\n\u003cp\u003eLeverage\u003c/p\u003e\n\u003cp\u003eCountries dummies\u003c/p\u003e\n\u003cp\u003eYear dummies\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePerformance-matching model of Kothari et al. (\u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003eThe percentage of independent directors to the audit committee's size\u003c/p\u003e\n\u003cp\u003ePercentage of strictly independent board members to total members on the board\u003c/p\u003e\n\u003cp\u003eThe ratio of female directors to the total number of directors\u003c/p\u003e\n\u003cp\u003eThe number of institutional shares/Total outstanding share *100\u003c/p\u003e\n\u003cp\u003eESG Disclosure Score\u003c/p\u003e\n\u003cp\u003eEnvironmental pillar\u003c/p\u003e\n\u003cp\u003eSocial pillar\u003c/p\u003e\n\u003cp\u003eGovernance pillar\u003c/p\u003e\n\u003cp\u003eNatural logarithm of total assets\u003c/p\u003e\n\u003cp\u003eThe natural logarithm of the number of years since the company's founding\u003c/p\u003e\n\u003cp\u003eIt is the percentage of net income to total assets\u003c/p\u003e\n\u003cp\u003eThe proportion of total debt scaled by total assets\u003c/p\u003e\n\u003cp\u003eDummy variable for the countries, Pakistan, Indonesia, Malaysia,\u003c/p\u003e\n\u003cp\u003eDummy variable for the years 2016, 2017, 2018, 2019,2020, 2021, 2022, 2023, 2024\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOsiris database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eBloomberg database\u003c/p\u003e\n\u003cp\u003eOsiris database\u003c/p\u003e\n\u003cp\u003eOsiris database\u003c/p\u003e\n\u003cp\u003eOsiris database\u003c/p\u003e\n\u003cp\u003eOsiris database\u003c/p\u003e\n\u003cp\u003eOsiris database\u003c/p\u003e\n\u003cp\u003eOsiris database\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eControl variables\u003c/h3\u003e\n\u003cp\u003eWe include several control variable factors commonly utilized as reliable indicators of ESG performance in CSR disclosure literature. Hence, we included profitability (ROA) Helfaya and Moussa (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), firm size D'Amico et al. (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) ; Helfaya and Moussa (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), firm leverage D'Amico et al. (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) ; (Helfaya and Moussa \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), firm age Ngoc and Manh (2024), and loss Chen et al. (2018) to mitigate model misspecification, omitted variable bias (OVB), and spurious regression analysis estimates.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe report results from descriptive statistics and the correlation matrix (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), main regression and moderation analyses (Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), and robustness tests (Tables\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eResults for the descriptive statistics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e reports descriptive statistics for corporate ESG disclosure scores, the quality of EM, the mechanisms of CG, and the control variables, presented in Panels A, B, C, and D, respectively. Corporate ESG disclosure scores are measured on a total scale of 100%. The sample mean ESG disclosure scores are 52.07% overall, 43.00% for the environmental disclosure pillar, 56.62% for the social disclosure pillar, and 55.87% for the governance disclosure pillar. This shows that the environmental disclosure pillar score is the lowest among ESG disclosure pillars, suggesting that the sampled Indonesian firms perform below average in managing environmental disclosure issues and sustaining corporate environmental policy agendas. The sampled Indonesian listed firms exhibit a mean EM value of \u0026minus;\u0026thinsp;0.007 (approximately zero), with minimum and maximum values of \u0026minus;\u0026thinsp;1.323 and 2.657, respectively. This suggests that, on average, Indonesian companies show a lower tendency to use income-increasing DACC to boost earnings quality reporting, although some firms remain more engaged in EM practices.\u003c/p\u003e \u003cp\u003eBoard independent members average 56.48%, demonstrating that more than half (i.e., 50%) of board members in Indonesian listed firms are independent directors. The audit committee comprises approximately three members, with over 79% being independent. Female directors constitute, on average, 14.9% of boards in Indonesia, 27.4% in Malaysia, and 9.2% in Pakistan, with a maximum percentage of 54% across sampled listed firms. Therefore, approximately one in four board independent members is a woman director in sampled listed firms across Indonesia, Malaysia, and Pakistan. Leverage, calculated as total debt divided by total assets, averages 4.33%, and 57.5% of sampled firms in Indonesia, Malaysia, and Pakistan report losses in at least one year during the sample period. Firm size has a mean value of 23.51, while sampled listed firms in Indonesia, Malaysia, and Pakistan exhibit an average profitability (ROA) of 7.22%.\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\u003eDescriptive statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Dev\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePanel A: ESG disclosure score\u003c/em\u003e\u003c/p\u003e \u003cp\u003eESG Score\u003c/p\u003e \u003cp\u003eEnvironmental pillar score\u003c/p\u003e \u003cp\u003eSocial pillar score\u003c/p\u003e \u003cp\u003eGovernance pillar score\u003c/p\u003e \u003cp\u003e\u003cem\u003ePanel B: EM\u003c/em\u003e\u003c/p\u003e \u003cp\u003eEarning manipulation (DACC)\u003c/p\u003e \u003cp\u003e\u003cem\u003ePanel C: Corporate governance mechanisms\u003c/em\u003e\u003c/p\u003e \u003cp\u003eBoard Independent Members\u003c/p\u003e \u003cp\u003eBoard Gender Diversity\u003c/p\u003e \u003cp\u003eAudit Committee Independence\u003c/p\u003e \u003cp\u003eInstitutional Ownership\u003c/p\u003e \u003cp\u003e\u003cem\u003ePanel D: Control variables\u003c/em\u003e\u003c/p\u003e \u003cp\u003eProfitability (ROA)\u003c/p\u003e \u003cp\u003eFirm size\u003c/p\u003e \u003cp\u003eFirm age\u003c/p\u003e \u003cp\u003eLeverage\u003c/p\u003e \u003cp\u003eLoss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2628\u003c/p\u003e \u003cp\u003e2628\u003c/p\u003e \u003cp\u003e2628\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2628\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003cp\u003e2828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.062\u003c/p\u003e \u003cp\u003e43.00\u003c/p\u003e \u003cp\u003e56.62\u003c/p\u003e \u003cp\u003e55.87\u003c/p\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003cp\u003e56.48\u003c/p\u003e\u003cp\u003e26.182\u003c/p\u003e\u003cp\u003e88.772\u003c/p\u003e\u003cp\u003e17.81\u003c/p\u003e\u003cp\u003e6.215\u003c/p\u003e\u003cp\u003e22.428\u003c/p\u003e\u003cp\u003e6.259\u003c/p\u003e\u003cp\u003e5.238\u003c/p\u003e\u003cp\u003e0.665\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.648\u003c/p\u003e \u003cp\u003e24.459\u003c/p\u003e \u003cp\u003e21.480\u003c/p\u003e \u003cp\u003e20.140\u003c/p\u003e \u003cp\u003e1.267\u003c/p\u003e \u003cp\u003e13.448\u003c/p\u003e \u003cp\u003e12.642\u003c/p\u003e \u003cp\u003e15.238\u003c/p\u003e \u003cp\u003e10.72\u003c/p\u003e \u003cp\u003e9.607\u003c/p\u003e \u003cp\u003e2.669\u003c/p\u003e \u003cp\u003e2.473\u003c/p\u003e \u003cp\u003e0.559\u003c/p\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.065\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003cp\u003e1.763\u003c/p\u003e \u003cp\u003e0.223\u003c/p\u003e \u003cp\u003e-1.323\u003c/p\u003e \u003cp\u003e6.153\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e12.276\u003c/p\u003e \u003cp\u003e0.00\u003c/p\u003e \u003cp\u003e-34.876\u003c/p\u003e \u003cp\u003e14.484\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93.239\u003c/p\u003e \u003cp\u003e95.051\u003c/p\u003e \u003cp\u003e95.637\u003c/p\u003e \u003cp\u003e96.736\u003c/p\u003e \u003cp\u003e2.657\u003c/p\u003e \u003cp\u003e100\u003c/p\u003e \u003cp\u003e50\u003c/p\u003e \u003cp\u003e100\u003c/p\u003e \u003cp\u003e70.56\u003c/p\u003e \u003cp\u003e46.590\u003c/p\u003e \u003cp\u003e28.436\u003c/p\u003e \u003cp\u003e10.205\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1\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 \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation results\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e reports the Pearson correlation matrix for ESD indicators, accrual EM, the mechanisms of CG, and the control variables. As anticipated, the social and environmental disclosure pillars show a strong positive relationship with the corporate ESG disclosure score. The governance disclosure pillar score also demonstrates a positive relationship with the corporate ESG disclosure score. Nevertheless, this does not affect the issue of multicollinearity, as the ESG disclosure score and individual ESG disclosure pillar score serve as separate dependent variables in Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. EM reveals a negative connection with overall ESG disclosure and individual ESG pillars. CG mechanisms are positively connected with overall ESG disclosure and individual pillar scores, as strong CG is expected to improve sustainability practices and stakeholder outcomes. Profitability shows a negative relationship with the overall ESG disclosure score and social and governance disclosure pillar scores among all control variables. Loss and firm size are negatively associated with environmental and governance pillar disclosure scores, respectively. Leverage is positively connected with corporate ESG disclosure and its individual pillars\u0026rsquo; scores, implying lower debt costs for ESG-engaged firms. IND board and AC independence are moderately positively correlated (r\u0026thinsp;=\u0026thinsp;0.486), implying notable membership overlap. AC independence is more strongly correlated with the governance disclosure pillar score than with the environmental and social disclosure pillars.\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\u003ePearson correlation matrix\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e(1) ESG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e(12)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e(14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(2) ENV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.833***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(3) SOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.874***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.684***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(4) GOV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.678***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.388***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.406***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(5) EM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.060**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.066**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.075**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.043*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(6) IBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.33***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.203 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.197**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.461***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.068**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(7) BGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.354***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.229***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.302***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.287***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.077**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(8) ACI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.282***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.148***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.123***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.427***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.134**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.055**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.078**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(9) IO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.249***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.288**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.068**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.321***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(10) ROA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.033*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.068*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.036**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.125**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(11) FSIZE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.363**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.345***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.342***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.108**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(12) FAGE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.079**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(13) LEV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.355***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.223***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e-0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.134**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(14) Loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.061*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.064**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.061**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.065**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.-0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.234***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.048**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.068**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e1.00\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 \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRegressions results\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the multivariate EM\u0026ndash;ESG disclosure or performance relationship with mechanisms of CG as control variables. The random effects model is supported by the results of the Hausman test. Random effects are used to accommodate dummy and time-invariant variables. EM shows a significant (5%) negative relationship with ESG performance, implying lower ESG outcomes among firms manipulating financial reports. Higher EM corresponds to lower ESG disclosure, aligning with agency theory on managerial opportunism and shareholder conflict. Thus, H1 is supported and confirmed.\u003c/p\u003e \u003cp\u003eThe negative association between the quality of EM and corporate ESG performance is also confirmed across individual ESG disclosure pillars. The quality of EM shows a negative and significant coefficient for the social and environmental disclosure pillar. The results align with prior research indicating that EM engagement undermines socially responsible practices Ehsan et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003eb) ; (Hickman et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mart\u0026iacute;nez-Ferrero et al. \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Adeneye et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003eb; Abdelfattah and Elfeky \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and diminishes stakeholder satisfaction and trust (Gavana et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003eb; Kolsi et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea; Velte \u003cspan citationid=\"CR176\" class=\"CitationRef\"\u003e2019\u003c/span\u003ea). Among all the control variables, mechanisms of CG are positively connected with ESG disclosure score, demonstrating that strong mechanisms of CG enhance CSP through higher ESG disclosure. It is also confirmed that CG mechanisms effectively moderate the connection between the quality of EM and corporate ESG performance.\u003c/p\u003e \u003cp\u003eBGD is positively and significantly associated with corporate ESG performance and its individual disclosure pillars at the 1% level, supporting past results on the positive effect of female board members on sustainability initiatives (Nuhu and Alam \u003cspan citationid=\"CR147\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Chebbi and Ammer \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kamaludin et al. \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2022\u003c/span\u003ea; Wasiuzzaman and Wan Mohammad \u003cspan citationid=\"CR184\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Khemakhem et al. \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Alkhawaja et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea). In accordance with resource dependence theory byHillman et al. (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), more women on the board, with their skills and gender-based characteristics, enhance firm resources and improve corporate ESG performance. The results are supported by and consistent with the studies of Velte (\u003cspan citationid=\"CR175\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Romano et al. (\u003cspan citationid=\"CR160\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), whose studies were conducted in the context of European countries. Our study findings contradict those of Cucari et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), who reported that female board members reduce ESG disclosure, suggesting that regulatory pressures may hinder their board gender equality goals toward corporate sustainable performance.\u003c/p\u003e \u003cp\u003eBoard independent members show a positive and significant association with ESG disclosure and its individual disclosure pillars. The board\u0026rsquo;s oversight and monitoring function enhances CSRD. Our results align with Chebbi and Ammer (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) ; (Kamaludin et al. \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2022\u003c/span\u003eb), suggesting board independent members support firms\u0026rsquo; social and environmental activities. Previous studies report a positive link between board independent members and corporate ESG disclosure and performance Umar et al. (\u003cspan citationid=\"CR172\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); (Ellili \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), consistent with the agency theory perspective that board oversight and monitoring increase ESG-related efficiency (Chouaibi et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fama and Jensen \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Hillman and Dalziel \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). These study findings contrast with Naciti (\u003cspan citationid=\"CR142\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) who reported a negative connection between BIND and ESG performance. Our study results indicate that board independent members increase the governance disclosure pillar more than the social and environmental disclosure pillars, also contributing to overall ESG disclosure. Firms enhance ESG performance by having more independent director members on board. Descriptive statistics show that the governance pillar has the highest mean, indicating stronger monitoring roles in Pakistani, Indonesian, and Malaysian firms.\u003c/p\u003e \u003cp\u003eAC independence positively and significantly affects overall ESG, environmental, and governance scores (1%, 5%, and 1%), supporting prior studies (Al-Shaer and Zaman \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Arif et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Suttipun \u003cspan citationid=\"CR168\" class=\"CitationRef\"\u003e2021\u003c/span\u003ea; Tumwebaze et al. \u003cspan citationid=\"CR171\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Erin et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Our research findings show that resources and expertise of independent director members in AC increase ESG performance in Pakistani, Indonesian, and Malaysian firms, supporting resource dependence theory Hillman and Dalziel (\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Our study results on AC independence contradict the study by Wang and Sun (\u003cspan citationid=\"CR180\" class=\"CitationRef\"\u003e2022\u003c/span\u003ea) who revealed an insignificant connection with ESG disclosure, attributing it to country-specific culture and political ties of directors.\u003c/p\u003e \u003cp\u003eThe coefficient of institutional or foreign ownership is significantly positive at 1%, indicating that companies with higher IO show greater ESG performance. Business relationships and investment horizons are important for CG mechanisms (Harford et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Our findings show that both long-term pressure-insensitive and short-term pressure-sensitive investors are responsible for the positive relationship between IO and ESG performance. Using their resources and expertise, long-term, pressure-insensitive institutional or foreign investors monitor management, leveraging ownership to improve governance and enhance ESG performance. This aligns with Kim et al. (\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2019\u003c/span\u003ea), who found that active and long-term investors positively influence CSR disclosure activities. Similarly, our results align with Wang et al. (\u003cspan citationid=\"CR181\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea) ; (Liu et al. \u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea), who found IO positively influences corporate ESG performance. Higher ESG companies typically yield higher returns Khan (\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), so short-term, pressure-sensitive institutional investors choose companies with strong ESG potential by using their informational advantage, leading to a positive and significant relationship.\u003c/p\u003e \u003cp\u003eLeverage and firm size are positively and significantly associated with ESG performance, whereas firm age demonstrates a significant but negative connection with ESG performance. This proposes that large firms are more expected to adopt ESG disclosure, while older firms may resist modern ESG practices due to tradition, and newer firms prioritize ESG to stay competitive and attract stakeholders. Our results support prior studies showing positive links between firm size and ESG Fiandrino et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), debt and ESG Khanchel and Lassoued (\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and age and ESG (Cicchiello et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\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\u003eRelationship between EM and ESG performance\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) ESG score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2) Environmental pillar score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3) Governance pillar score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4) Social pillar score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.729**\u003c/p\u003e \u003cp\u003e(0.384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.072**\u003c/p\u003e \u003cp\u003e(0.534)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.039**\u003c/p\u003e \u003cp\u003e(0.471)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.273\u003c/p\u003e \u003cp\u003e(0.446)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent board members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0. 163***\u003c/p\u003e \u003cp\u003e(0.0395)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0879\u003c/p\u003e \u003cp\u003e(0.0561)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0708*\u003c/p\u003e \u003cp\u003e(0.0484)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.396***\u003c/p\u003e \u003cp\u003e(0.0479)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoard gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.341***\u003c/p\u003e \u003cp\u003e(0.0438)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.312***\u003c/p\u003e \u003cp\u003e(0.0736)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.412***\u003c/p\u003e \u003cp\u003e(0.0564)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.333***\u003c/p\u003e \u003cp\u003e(0.0544)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAudit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.150***\u003c/p\u003e \u003cp\u003e0.0347)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.104**\u003c/p\u003e \u003cp\u003e(0.0468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0512\u003c/p\u003e \u003cp\u003e(0.0422)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.315***\u003c/p\u003e \u003cp\u003e(0.0402)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.160***\u003c/p\u003e \u003cp\u003e0.0437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.205**\u003c/p\u003e \u003cp\u003e(0.0378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0412\u003c/p\u003e \u003cp\u003e(0.0424)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.316***\u003c/p\u003e \u003cp\u003e(0.0405)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability (ROA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0171\u003c/p\u003e \u003cp\u003e(0.0553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0527\u003c/p\u003e \u003cp\u003e(0.0777)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0174\u003c/p\u003e \u003cp\u003e(0.0682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.00351\u003c/p\u003e \u003cp\u003e(0.0636)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.166***\u003c/p\u003e \u003cp\u003e(0.307)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.753*\u003c/p\u003e \u003cp\u003e(0.445)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.037***\u003c/p\u003e \u003cp\u003e(0.374)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.736***\u003c/p\u003e \u003cp\u003e(0.367)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.178***\u003c/p\u003e \u003cp\u003e(0.3050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.673*\u003c/p\u003e \u003cp\u003e(0.355)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.047***\u003c/p\u003e \u003cp\u003e(0.346)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.647***\u003c/p\u003e \u003cp\u003e(0.357)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.034***\u003c/p\u003e \u003cp\u003e(0.222)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.376***\u003c/p\u003e \u003cp\u003e(0.312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.239***\u003c/p\u003e \u003cp\u003e(0.267)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.541***\u003c/p\u003e \u003cp\u003e(0.253)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.115\u003c/p\u003e \u003cp\u003e(1.046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.395\u003c/p\u003e \u003cp\u003e(1.471)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.946\u003c/p\u003e \u003cp\u003e(1.297)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.252\u0026minus;\u003c/p\u003e \u003cp\u003e(1.242)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-23.08***\u003c/p\u003e \u003cp\u003e(7.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-21.59**\u003c/p\u003e \u003cp\u003e(9.971)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5.982\u003c/p\u003e \u003cp\u003e(8.697)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-44.34***\u003c/p\u003e \u003cp\u003e(8.362)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1280\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\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.334\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\u003eStandard errors are enclosed in parentheses. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eResults from the moderations test\u003c/h2\u003e \u003cp\u003eOur study further analyzes the effect of accrual EM on overall and individual ESG pillars, moderated by mechanisms of CG. The main purpose is to examine whether mechanisms of CG moderate the negative impact of quality of EM on ESG performance. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e displays the study's results. The moderation effect results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows how mechanisms of CG moderate the influence of DACC on overall and individual ESG disclosure scores. The positive BGD interaction term shows that female board members significantly reduce EM\u0026rsquo;s negative impact on ESG performance (β\u0026thinsp;=\u0026thinsp;0.152, p0.0237). Therefore, the second hypothesis (H2) is confirmed and supported. The interaction term (DACC*BGD) shows a positive and significant connection with environmental (β\u0026thinsp;=\u0026thinsp;0.151, p\u0026thinsp;\u0026lt;\u0026thinsp;0.04) and social disclosure pillar scores (β\u0026thinsp;=\u0026thinsp;0.181, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eConversely, the interaction term (DACC*BIND) is significant across overall ESG disclosure and individual pillars, but its coefficients are smaller than DACC in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, suggesting BIND reduces EM, but not sufficiently to curb EM activities. Therefore, there is no evidence to support hypothesis 3 (H3). This demonstrates that female board members are a stronger mechanism of CG than independent male directors on the board, in contrast to BGD, whose interaction terms have positive coefficients. This could suggest that male directors have two monitoring roles. They may attempt to constrain EM while also engaging in entrenchment opportunities, thereby reducing board monitoring effectiveness.\u003c/p\u003e \u003cp\u003eSimilarly, AC_IND shows no significant monitoring effect on ESG disclosure pillars, except for the governance disclosure pillar. Interaction term (DACC*AC_INDEP) is not significant for overall ESG disclosure in Model 1 (β\u0026thinsp;=\u0026thinsp;0.0376, p\u0026thinsp;\u0026gt;\u0026thinsp;0.10) but is significant for the governance disclosure pillar score. As our research hypotheses focus on aggregate ESG disclosure scores, hypothesis 4 (H4) is not confirmed or supported. All control variables of our study are statistically significant and positive, except for profitability, which is insignificant for overall ESG disclosure and individual pillars. Overall, when CG mechanisms condition the ESG\u0026ndash;EM relationship, the DACC coefficient turns positive, suggesting CG may help conceal managerial opportunism by reducing stakeholder activism threats while increasing ESG performance.\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 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe moderating effect of mechanisms of CG on the association between ESG performance and EM\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) ESG score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2) Environmental pillar score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3) Governance pillar score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4) Social pillar score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.842**\u003c/p\u003e \u003cp\u003e(1.691)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.521**\u003c/p\u003e \u003cp\u003e(3.832)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.523**\u003c/p\u003e \u003cp\u003e(3.212)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.062\u003c/p\u003e \u003cp\u003e(3.371)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent board members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.205***\u003c/p\u003e \u003cp\u003e(0.0387)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.129**\u003c/p\u003e \u003cp\u003e(0.0556)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.105**\u003c/p\u003e \u003cp\u003e(0.0486)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.423***\u003c/p\u003e \u003cp\u003e(0.0461)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC * independent board members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.126***\u003c/p\u003e \u003cp\u003e(0.0317)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0639*\u003c/p\u003e \u003cp\u003e(0.0448)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.145***\u003c/p\u003e \u003cp\u003e(0.0374)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.131***\u003c/p\u003e \u003cp\u003e(0.0354)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoard gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.473***\u003c/p\u003e \u003cp\u003e(0.0435)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.361***\u003c/p\u003e \u003cp\u003e(0.0614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.328***\u003c/p\u003e \u003cp\u003e(0.0547)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.380***\u003c/p\u003e \u003cp\u003e(0.0519)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC * board gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.152**\u003c/p\u003e \u003cp\u003e(0.0337)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.142**\u003c/p\u003e \u003cp\u003e(0.0484)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.181**\u003c/p\u003e \u003cp\u003e(0.0445)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00166\u003c/p\u003e \u003cp\u003e(0.0412)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAudit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.136***\u003c/p\u003e \u003cp\u003e(0.0342)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0748*\u003c/p\u003e \u003cp\u003e(0.0474)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0398\u003c/p\u003e \u003cp\u003e(0.0435)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.310***\u003c/p\u003e \u003cp\u003e(0.0435)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC * audit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0376\u003c/p\u003e \u003cp\u003e(0.0258)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0392\u003c/p\u003e \u003cp\u003e(0.0356)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0271\u003c/p\u003e \u003cp\u003e(0.0345)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0667**\u003c/p\u003e \u003cp\u003e(0.0328)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.134***\u003c/p\u003e \u003cp\u003e(0.0340)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0838*\u003c/p\u003e \u003cp\u003e(0.0484)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0288\u003c/p\u003e \u003cp\u003e(0.0455)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.309***\u003c/p\u003e \u003cp\u003e(0.0403)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC * institutional ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.128***\u003c/p\u003e \u003cp\u003e(0.0268)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0365\u003c/p\u003e \u003cp\u003e(0.0384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0270\u003c/p\u003e \u003cp\u003e(0.0335)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0666**\u003c/p\u003e \u003cp\u003e(0.0319)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability (ROA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00786\u003c/p\u003e \u003cp\u003e(0.0566)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0448\u003c/p\u003e \u003cp\u003e(0.0776)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0271\u003c/p\u003e \u003cp\u003e(0.0684)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0140\u003c/p\u003e \u003cp\u003e(0.0637)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.783***\u003c/p\u003e \u003cp\u003e(0.287)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003cp\u003e(0.433)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.614*\u003c/p\u003e \u003cp\u003e(0.381)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.424***\u003c/p\u003e \u003cp\u003e(0.362)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.673***\u003c/p\u003e \u003cp\u003e(0.247)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.371**\u003c/p\u003e \u003cp\u003e(0.382)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.512*\u003c/p\u003e \u003cp\u003e(0.281)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003cp\u003e(0.272)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.481***\u003c/p\u003e \u003cp\u003e(0.0645)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.588***\u003c/p\u003e \u003cp\u003e(0.0923)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.489***\u003c/p\u003e \u003cp\u003e(0.0719)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.381***\u003c/p\u003e \u003cp\u003e(0.0667)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.425\u003c/p\u003e \u003cp\u003e(1.081)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8891\u003c/p\u003e \u003cp\u003e(1.415)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.237\u003c/p\u003e \u003cp\u003e(1.242)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.151\u003c/p\u003e \u003cp\u003e(1.235)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-16.25**\u003c/p\u003e \u003cp\u003e(6.869)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-13.61\u003c/p\u003e \u003cp\u003e(9.814)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.541\u003c/p\u003e \u003cp\u003e(8.610)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-39.74***\u003c/p\u003e \u003cp\u003e(8.166)\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\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1280\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\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.238\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\u003eStandard errors are enclosed in parenthesis. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.1, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRobustness test\u003c/h2\u003e \u003cp\u003eTo confirm robustness, we test whether quality of EM negatively affects ESG performance and whether ESG disclosure is positively associated to EM\u0026ndash;CG, using additional robustness analyses discussed below. Overall, the robustness test results are in line with our main conclusions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eEndogeneity concerns\u003c/h2\u003e \u003cp\u003eMany prior studies examine the ESG\u0026ndash;EM relationship but report conflicting results (Ahmad et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea; Wati and Malik \u003cspan citationid=\"CR185\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Habbash and Haddad \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003eb), possibly due to methodological weaknesses such as endogeneity issues. Our study suggests potential endogeneity concerns in examining the impact of the quality of EM on ESG performance (Choi et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Velte \u003cspan citationid=\"CR176\" class=\"CitationRef\"\u003e2019\u003c/span\u003ea). Our study addresses endogeneity by utilizing industry means as an instrumental variable and applies an estimator of two-stage least squares (2SLS), using the industry-average DACC as an instrument. Using industry averages as instruments is a long-term standing activities in corporate finance (Bacha and Ajina \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chan et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Our study assumes the exogenous component of quality of EM differs across all industries due to differences in accrual mixes, while the endogenous component varies within the industries (Barth et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Dechow et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). For instance, Barth et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), report that manufacturing companies exhibit more persistent receivables due to similar accounting practices and economic conditions. Separating the endogenous and exogenous mechanisms of variables at the industry-average level helps classify valid instruments for addressing endogeneity problem. The 2SLS results in Tables\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e are consistent with the baseline findings. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e demonstrates that quality of EM negatively affects overall ESG disclosure and individual pillars, in line with our main results. Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows that BGD and AC independence act as significant moderators, with improved baseline results for AC independence. This change is attributed to including industry-average DACC, which is related to the type of industry. Industry specialist auditors, if compared to non-specialists, are required to produce audits of a better quality (Abbott et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Companies with higher AC independence are more expected to involve industry-specialist directors. Industry-specific EM is more likely to be mitigated by industry experts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eResults for absolute discretionary accruals\u003c/h2\u003e \u003cp\u003ePrior research measures EM quality by using both signed and absolute discretionary accruals (Cohen and Malkogianni \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jackson \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Since absolute (unsigned) discretionary accruals include managerial opportunistic usage of discretionary accruals, it is easier to identify companies engaged in income smoothing. The absolute value of the quality of EM detects whether companies are involved in income-increasing or decreasing accruals to meet the targets of earnings (Klein \u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Wang \u003cspan citationid=\"CR179\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Therefore, our study estimates the empirical model by using absolute (unsigned) discretionary accruals, as reported in Tables\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. The outcomes in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e are in line with the baseline association between signed quality of EM and ESG performance for ESG disclosure score and individual ESG disclosure pillar scores, excluding for the governance disclosure pillar score, which is negative and insignificant. The moderating effects of BGD and AC independence are consistent with Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, except that BGD shows a negative effect. Our study attributes this outcome to the possibility that the sampled companies in this analysis may have an income-decreasing absolute DACC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModerating role of mechanisms of CG in ESG\u0026ndash;EM association (using absolute discretionary accruals)\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) ESG score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2) Environmental pillar score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3) Social pillar score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4) Governance pillar score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADA (unsigned)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.890\u003c/p\u003e \u003cp\u003e(3.654)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.791\u003c/p\u003e \u003cp\u003e(3.933)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.035\u003c/p\u003e \u003cp\u003e(3.443)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003cp\u003e(3.465)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent board members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.472***\u003c/p\u003e \u003cp\u003e(0.0437)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.361***\u003c/p\u003e \u003cp\u003e(0.0605)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.438***\u003c/p\u003e \u003cp\u003e(0.0534)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.290***\u003c/p\u003e \u003cp\u003e(0.0508)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADA * independent board members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0321\u003c/p\u003e \u003cp\u003e(0.0445)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0417\u003c/p\u003e \u003cp\u003e(0.0481)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0807*\u003c/p\u003e \u003cp\u003e(0.0441)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00187\u003c/p\u003e \u003cp\u003e(0.0355)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoard gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.202***\u003c/p\u003e \u003cp\u003e(0.0384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.129**\u003c/p\u003e \u003cp\u003e(0.0493)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.105**\u003c/p\u003e \u003cp\u003e(0.0593)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.423***\u003c/p\u003e \u003cp\u003e(0.0368)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADA * board gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.118***\u003c/p\u003e \u003cp\u003e(0.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0629**\u003c/p\u003e \u003cp\u003e(0.0335)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.135***\u003c/p\u003e \u003cp\u003e(0.0384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.131***\u003c/p\u003e \u003cp\u003e(0.0352)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAudit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0143\u003c/p\u003e \u003cp\u003e(0.0218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0164\u003c/p\u003e \u003cp\u003e(0.0384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0114\u003c/p\u003e \u003cp\u003e(0.0352)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0141\u003c/p\u003e \u003cp\u003e(0.0343)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADA * audit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.144***\u003c/p\u003e \u003cp\u003e(0.0348)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0748**\u003c/p\u003e \u003cp\u003e(0.0491)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0288\u003c/p\u003e \u003cp\u003e(0.0432)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.308***\u003c/p\u003e \u003cp\u003e(0.0423)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0233\u003c/p\u003e \u003cp\u003e(0.0328)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0275\u003c/p\u003e \u003cp\u003e(0.0354)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0212\u003c/p\u003e \u003cp\u003e(0.0367)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0241\u003c/p\u003e \u003cp\u003e(0.0434)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADA * institutional ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.154***\u003c/p\u003e \u003cp\u003e(0.0338)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0638**\u003c/p\u003e \u003cp\u003e(0.0381)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0278\u003c/p\u003e \u003cp\u003e(0.0442)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0309***\u003c/p\u003e \u003cp\u003e(0.0432)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability (ROA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0376\u003c/p\u003e \u003cp\u003e(0.0256)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0345\u003c/p\u003e \u003cp\u003e(0.0369)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0380\u003c/p\u003e \u003cp\u003e(0.0444)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0777**\u003c/p\u003e \u003cp\u003e(0.0216)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00786\u003c/p\u003e \u003cp\u003e(0.0532)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0358\u003c/p\u003e \u003cp\u003e(0.0662)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0251\u003c/p\u003e \u003cp\u003e(0.0658)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0131\u003c/p\u003e \u003cp\u003e(0.0653)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0255\u003c/p\u003e \u003cp\u003e(0.0289)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00689\u003c/p\u003e \u003cp\u003e(0.0434)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0351\u003c/p\u003e \u003cp\u003e(0.0549)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0245\u003c/p\u003e \u003cp\u003e(0.0523)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.663***\u003c/p\u003e \u003cp\u003e(0.285)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003cp\u003e(0.421)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.612*\u003c/p\u003e \u003cp\u003e(0.359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.433***\u003c/p\u003e \u003cp\u003e(0.352)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.154\u003c/p\u003e \u003cp\u003e(4.847)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.580\u003c/p\u003e \u003cp\u003e(5.425)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.771\u003c/p\u003e \u003cp\u003e(2.528)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.887\u003c/p\u003e \u003cp\u003e(4.812)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-16.25**\u003c/p\u003e \u003cp\u003e(6.789)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-13.41\u003c/p\u003e \u003cp\u003e(9.645)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.532\u003c/p\u003e \u003cp\u003e(8.562)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-39.74***\u003c/p\u003e \u003cp\u003e(8.112)\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\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.212\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\u003eThe parentheses surround the standard errors. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eControlling for autocorrelation\u003c/h2\u003e \u003cp\u003eOur study further tests for potential autocorrelation issues. Our study addresses these issues using yearly sample analysis. Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e shows that quality of EM reduces the ESG disclosure score, in line with our baseline results. Therefore, the results of the research do not have autocorrelation problems.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between quality of EM and ESG disclosure (annual sample analysis)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) 2016\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2) 2017\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3) 2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4) 2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5) 2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6) 2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7) 2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(8) 2023\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(9) 2024\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0610*\u003c/p\u003e \u003cp\u003e(0.0323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0787*\u003c/p\u003e \u003cp\u003e(0.0271)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0773*\u003c/p\u003e \u003cp\u003e(0.0327)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0832*\u003c/p\u003e \u003cp\u003e(0.0189)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.0639*\u003c/p\u003e \u003cp\u003e(0.0253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0842*\u003c/p\u003e \u003cp\u003e(0.0327)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.0539*\u003c/p\u003e \u003cp\u003e(0.0237)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.0349*\u003c/p\u003e \u003cp\u003e(0.0423)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.0255*\u003c/p\u003e \u003cp\u003e(0.0112)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent board members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00307\u003c/p\u003e \u003cp\u003e(0.00312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00475**\u003c/p\u003e \u003cp\u003e0.00273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00791**\u003c/p\u003e \u003cp\u003e(0.00235)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.00337**\u003c/p\u003e \u003cp\u003e(0.00182)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00139*\u003c/p\u003e \u003cp\u003e(0.00168)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00408\u003c/p\u003e \u003cp\u003e(0.00412)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00365**\u003c/p\u003e \u003cp\u003e(0.00263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00365**\u003c/p\u003e \u003cp\u003e(0.00336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00472*\u003c/p\u003e \u003cp\u003e(0.00247)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoard gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00732**\u003c/p\u003e \u003cp\u003e(0.00368)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00778**\u003c/p\u003e \u003cp\u003e(0.00284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00867***\u003c/p\u003e \u003cp\u003e(0.00255)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00983***\u003c/p\u003e \u003cp\u003e(0.00242)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00532***\u003c/p\u003e \u003cp\u003e(0.00198)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00722**\u003c/p\u003e \u003cp\u003e(0.00238)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0532***\u003c/p\u003e \u003cp\u003e(0.00384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00967***\u003c/p\u003e \u003cp\u003e(0.00365)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00657***\u003c/p\u003e \u003cp\u003e(0.00485)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAudit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00582**\u003c/p\u003e \u003cp\u003e(0.00267)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00275*\u003c/p\u003e \u003cp\u003e(0.00231)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00506**\u003c/p\u003e \u003cp\u003e(0.00198)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00403**\u003c/p\u003e \u003cp\u003e(0.00152)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00310*\u003c/p\u003e \u003cp\u003e(0.00172)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00462**\u003c/p\u003e \u003cp\u003e(0.00377)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0375**\u003c/p\u003e \u003cp\u003e(0.00321)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00301**\u003c/p\u003e \u003cp\u003e(0.00164)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00412**\u003c/p\u003e \u003cp\u003e(0.00214)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00484**\u003c/p\u003e \u003cp\u003e(0.00347)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00365**\u003c/p\u003e \u003cp\u003e(0.00367)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00455**\u003c/p\u003e \u003cp\u003e(0.00188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00315*\u003c/p\u003e \u003cp\u003e(0.00175)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00485**\u003c/p\u003e \u003cp\u003e(0.00387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00305**\u003c/p\u003e \u003cp\u003e(0.00174)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00385**\u003c/p\u003e \u003cp\u003e(0.00341)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00355**\u003c/p\u003e \u003cp\u003e(0.00277)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00272***\u003c/p\u003e \u003cp\u003e(0.00198)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability (ROA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00410\u003c/p\u003e \u003cp\u003e(0.00351)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00112\u003c/p\u003e \u003cp\u003e(0.00449)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00288\u003c/p\u003e \u003cp\u003e(0.00305)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.00369\u003c/p\u003e \u003cp\u003e(0.00371)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.00116\u003c/p\u003e \u003cp\u003e(0.00263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00310\u003c/p\u003e \u003cp\u003e(0.00252)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00125\u003c/p\u003e \u003cp\u003e(0.00359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00278\u003c/p\u003e \u003cp\u003e(0.00405)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00168\u003c/p\u003e \u003cp\u003e(0.0035)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0119\u003c/p\u003e \u003cp\u003e(0.0233)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0378\u003c/p\u003e \u003cp\u003e(0.0287)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0127\u003c/p\u003e \u003cp\u003e(0.0198)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0114\u003c/p\u003e \u003cp\u003e(0.0154)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00490\u003c/p\u003e \u003cp\u003e(0.0139)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0129\u003c/p\u003e \u003cp\u003e(0.0243)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0288\u003c/p\u003e \u003cp\u003e(0.0177)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0237\u003c/p\u003e \u003cp\u003e(0.0288)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0112\u003c/p\u003e \u003cp\u003e(0.0256)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0149\u003c/p\u003e \u003cp\u003e(0.0342)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0268\u003c/p\u003e \u003cp\u003e(0.0147)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0237\u003c/p\u003e \u003cp\u003e(0.0248)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0387\u003c/p\u003e \u003cp\u003e(0.0243)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0480\u003c/p\u003e \u003cp\u003e(0.0249)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0229\u003c/p\u003e \u003cp\u003e(0.0344)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0298\u003c/p\u003e \u003cp\u003e(0.0287)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0447\u003c/p\u003e \u003cp\u003e(0.0378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0278\u003c/p\u003e \u003cp\u003e(0.0267)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0108**\u003c/p\u003e \u003cp\u003e(0.0507)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.000677\u003c/p\u003e \u003cp\u003e(0.0569)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00875**\u003c/p\u003e \u003cp\u003e(0.00363)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00887**\u003c/p\u003e \u003cp\u003e(0.00415)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00559***\u003c/p\u003e \u003cp\u003e(0.0307)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0139***\u003c/p\u003e \u003cp\u003e(0.0214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0372***\u003c/p\u003e \u003cp\u003e(0.0273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0495***\u003c/p\u003e \u003cp\u003e(0.0372)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0486\u003c/p\u003e \u003cp\u003e(0.0376)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003cp\u003e(0.246)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0628\u003c/p\u003e \u003cp\u003e(0.217)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003cp\u003e(0.284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0782\u003c/p\u003e \u003cp\u003e(0.194)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0761\u003c/p\u003e \u003cp\u003e(0.185)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003cp\u003e(0.248)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0538\u003c/p\u003e \u003cp\u003e(0.247)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0672\u003c/p\u003e \u003cp\u003e(0.284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0552\u003c/p\u003e \u003cp\u003e(0.274)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.389***\u003c/p\u003e \u003cp\u003e(0.503)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.039***\u003c/p\u003e \u003cp\u003e(0.436)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.597***\u003c/p\u003e \u003cp\u003e(0.426)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.834***\u003c/p\u003e \u003cp\u003e(0.346)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.905***\u003c/p\u003e \u003cp\u003e(0.320)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.399***\u003c/p\u003e \u003cp\u003e(0.605)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.029***\u003c/p\u003e \u003cp\u003e(0.416)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.487***\u003c/p\u003e \u003cp\u003e(0.506)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.572\u003c/p\u003e \u003cp\u003e(0.214)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e250\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\u003eStandard errors are enclosed in parentheses. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eHeterogeneity control\u003c/h2\u003e \u003cp\u003eTo control for heterogeneity concerns in ESG performance, the study re-estimates the analysis by using quantile regression at the 25th, 50th, and 75th percentiles of ESG disclosure scores. Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e shows that EM quality and ESG results are in line across percentiles, with the negative effect of the quality of EM increasing at higher percentiles.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTesting the effect\u0026rsquo;s heterogeneity using quantile regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESGD score 25th Percentile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eESGD score 50th Percentile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eESGD score 75th Percentile\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.684*\u003c/p\u003e \u003cp\u003e(0.333)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.077**\u003c/p\u003e \u003cp\u003e(0.468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.232**\u003c/p\u003e \u003cp\u003e(0.558)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent board members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.163***\u003c/p\u003e \u003cp\u003e(0.0367)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.183***\u003c/p\u003e \u003cp\u003e(0.0482)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.172***\u003c/p\u003e \u003cp\u003e(0.0594)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoard gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.339***\u003c/p\u003e \u003cp\u003e(0.0420)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.359***\u003c/p\u003e \u003cp\u003e(0.0569)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.385***\u003c/p\u003e \u003cp\u003e(0.0655)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAudit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.160***\u003c/p\u003e \u003cp\u003e(0.0291)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.167***\u003c/p\u003e \u003cp\u003e(0.0321)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.168***\u003c/p\u003e \u003cp\u003e(0.0405)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.163***\u003c/p\u003e \u003cp\u003e(0.0481)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.197***\u003c/p\u003e \u003cp\u003e(0.0325)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.175***\u003c/p\u003e \u003cp\u003e(0.0389)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability (ROA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0268\u003c/p\u003e \u003cp\u003e(0.0639)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0677\u003c/p\u003e \u003cp\u003e(0.0667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0140\u003c/p\u003e \u003cp\u003e(0.0705)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.267***\u003c/p\u003e \u003cp\u003e(0.365)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.345***\u003c/p\u003e \u003cp\u003e(0.382)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.005***\u003c/p\u003e \u003cp\u003e(0.464)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.347***\u003c/p\u003e \u003cp\u003e(0.265)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.245***\u003c/p\u003e \u003cp\u003e(0.282)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.004***\u003c/p\u003e \u003cp\u003e(0.385)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.905***\u003c/p\u003e \u003cp\u003e(0.266)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.679***\u003c/p\u003e \u003cp\u003e(0.266)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.611\u003c/p\u003e \u003cp\u003e(0.338)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.423**\u003c/p\u003e \u003cp\u003e(1.300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.764\u003c/p\u003e \u003cp\u003e(1.293)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.723*\u003c/p\u003e \u003cp\u003e(1.545)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry dummies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-16.81*\u003c/p\u003e \u003cp\u003e(9.144)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-15.05*\u003c/p\u003e \u003cp\u003e(8.739)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-23.20**\u003c/p\u003e \u003cp\u003e(10.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1280\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\u003eThe standard errors are shown in parentheses p\u0026thinsp;\u0026lt;\u0026thinsp;0.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of subsample\u003c/h2\u003e \u003cp\u003eIn analysis of subsample, the EM\u0026ndash;ESG disclosure score relationship is highly negative but statistically significant for loss companies, supporting that quality of EM lessens environmental sustainability and accounting performance. Most significantly, the study results remain in line after controlling for mechanisms of CG variables such as BIND, BGD, AC independence, and IO, since mechanisms of CG can influence ESG performance (Suttipun \u003cspan citationid=\"CR168\" class=\"CitationRef\"\u003e2021\u003c/span\u003eb; Nuhu and Alam \u003cspan citationid=\"CR147\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Chebbi and Ammer \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kamaludin et al. \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2022\u003c/span\u003ea; Umar et al. \u003cspan citationid=\"CR172\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Khaireddine et al. \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Khalid et al. 2022b; Nicolo et al. \u003cspan citationid=\"CR146\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Across ESG disclosure score percentiles, our CG mechanisms variables consistently act as potential moderators with a positive effect on corporate ESG performance.\u003c/p\u003e \u003cp\u003eBecause the first subsample analysis shows EM is insignificant, though negatively related to ESG performance, we also investigate the significance of ROA heterogeneity. Tables\u0026nbsp;12 and 13 present subsample outcomes for companies with higher and lower ROA. Our results consistently demonstrate a negative connection between quality of EM and ESG disclosure. Firms with the lowest ROA have more expected to experience negative effects of quality of EM, indicating the need for stronger mechanisms of CG. Across both analysis of subsample, mechanisms of CG are statistically positive and significant in increasing ESG disclosure.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFinancial performance-based subsample analysis (firms with profit versus firms with loss; loss value\u0026thinsp;=\u0026thinsp;0 or 1).\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) Firms with Loss\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirms with Profit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.178***\u003c/p\u003e \u003cp\u003e(0.762)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.386\u003c/p\u003e \u003cp\u003e(0.351)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent board member\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0673***\u003c/p\u003e \u003cp\u003e(0.0669)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.248***\u003c/p\u003e \u003cp\u003e(0.0383)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoard gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.447***\u003c/p\u003e \u003cp\u003e(0.0703)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003cp\u003e(0.0537)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAudit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.158***\u003c/p\u003e \u003cp\u003e(0.0703)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.147***\u003c/p\u003e \u003cp\u003e(0.0509)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability (ROA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003cp\u003e(0.0730)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0433\u003c/p\u003e \u003cp\u003e(0.0688)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.181***\u003c/p\u003e \u003cp\u003e(0.527)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.886**\u003c/p\u003e \u003cp\u003e(0.372)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.190**\u003c/p\u003e \u003cp\u003e(0.475)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.786**\u003c/p\u003e \u003cp\u003e(0.483)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.433***\u003c/p\u003e \u003cp\u003e(0.381)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.953***\u003c/p\u003e \u003cp\u003e(0.265)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\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\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-36.81***\u003c/p\u003e \u003cp\u003e(12.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-12.05\u003c/p\u003e \u003cp\u003e(8.376)\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\u003e425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e762\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.349\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\u003eThe parentheses surround the standard errors. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFinancial performance-based subsamples (firms with ROA\u0026thinsp;\u0026lt;\u0026thinsp;mean vs. firms with ROA\u0026thinsp;\u0026gt;\u0026thinsp;mean).\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) ESG score strong ROA, ROA\u0026thinsp;\u0026gt;\u0026thinsp;mean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2) ESG score weak ROA, ROA\u0026thinsp;\u0026lt;\u0026thinsp;mean\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.538\u003c/p\u003e \u003cp\u003e(0.429)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.108*\u003c/p\u003e \u003cp\u003e(0.458)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent board members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.188***\u003c/p\u003e \u003cp\u003e(0.0556)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.162***\u003c/p\u003e \u003cp\u003e(0.0566)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoard gender diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.344***\u003c/p\u003e \u003cp\u003e(0.0545)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.369***\u003c/p\u003e \u003cp\u003e(0.0572)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAudit committee independence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.237***\u003c/p\u003e \u003cp\u003e(0.0350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0475\u003c/p\u003e \u003cp\u003e0.0416\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.160***\u003c/p\u003e \u003cp\u003e(0.0381)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.168***\u003c/p\u003e \u003cp\u003e(0.0400)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability (ROA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0869\u003c/p\u003e \u003cp\u003e(0.112)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0396\u003c/p\u003e \u003cp\u003e(0.108)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.471***\u003c/p\u003e \u003cp\u003e(0.438)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.003***\u003c/p\u003e \u003cp\u003e(0.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirm age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.187***\u003c/p\u003e \u003cp\u003e(0.329)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.003***\u003c/p\u003e \u003cp\u003e(0.237)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.198***\u003c/p\u003e \u003cp\u003e(0.329)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.953***\u003c/p\u003e \u003cp\u003e(0.409)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.734\u003c/p\u003e \u003cp\u003e(1.305)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0757\u003c/p\u003e \u003cp\u003e(1.529)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-31.61***\u003c/p\u003e \u003cp\u003e(9.820)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-13.59\u003c/p\u003e \u003cp\u003e(10.26)\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\u003e536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.348\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\u003eThe parentheses surround the standard errors \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis research investigates the influence of the quality of EM on ESG performance. Our study also tests whether mechanisms of CG mitigate the influence of quality of EM on ESG performance. Longitudinal data from emerging economies listed firms (2016\u0026ndash;2024) confirm that quality of EM decreases ESG performance. This research proposes that companies involved in the quality of EM practices through brownwashing, greenwashing, or managerial entrenchment strategies undermine ESG performance by manipulating sustainability investments. Our study finds that BGD significantly influences the impact of EM quality on ESG performance. This research finding is consistent across ESG disclosure and its three individual pillars; environmental, social, and governance. This result indicates that higher BGD mitigates the negative effect of EM quality on ESG performance, as female directors enhance board monitoring and reduce perceived opportunistic practices.\u003c/p\u003e \u003cp\u003eBoard independence and institutional or foreign ownership significantly mitigate negative effect of the quality of EM on ESG performance. AC independence does not significantly and positively moderate the impact of EM quality on ESG performance. Our study attributes significant moderating role of board independent members on EM quality\u0026ndash;ESG performance to numerous factors. First, CEO duality weakens ability of independent directors to monitor managerial practices effectively. Firms with CEO duality often have independent directors influenced by the CEO\u0026rsquo;s decisions. Second, independent directors face over-boarding or board busyness risks. Independent directors\u0026rsquo; members with manifold directorships attend fewer meetings, reducing their ability to monitor managers\u0026rsquo; earnings-driven financial manipulations. Third, independent directors with limited sustainability expertise are less able to detect earnings manipulation in sustainability spending, reducing guidance on greenwashing and brownwashing practices.\u003c/p\u003e \u003cp\u003eThus, BIND moderates the influence of EM quality on ESG performance through their evaluation of economic, environmental, social, and governance sustainability initiatives. Consequently, managerial brownwashing or greenwashing in sustainability programs may go unchecked by independent directors, potentially increasing corporate value. Thus, it examines how ESG disclosure and IO affect EM quality. It also examines how IO moderates the EM\u0026ndash;ESG performance relationship. Our study finds that higher EM quality reduces ESG performance, confirming a negative ESG\u0026ndash;EM association. Regression results show that IO significantly reduces EM quality practices. Higher IO is linked to lower EM quality behavior. Institutional ownership positively moderates the EM\u0026ndash;ESG performance relationship.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003ePractical implication\u003c/h2\u003e \u003cp\u003eThe findings support resource dependence, agency, and stakeholder theories, showing that female directors and CG mechanisms mitigate the impact of EM on corporate sustainability investments. Strong CG mechanisms enhance board diversity. Weak CG practices limit the effectiveness of CG attributes. Companies with stronger ESG performance can gain more from BGD. Increasing women on boards enhances ESG initiatives and performance. Nevertheless, some mechanisms of CG, like AC independence, affect only the governance score. Overall ESG disclosure and individual pillar scores depend on the mechanisms of CG ability to balance reducing EM quality and enhancing CSP.\u003c/p\u003e \u003cp\u003eHigher IO limits the quality of EM practices. Higher IO in emerging market firms lowers EM practices. These findings benefit policymakers, regulators, stakeholders, and firm management. Policymakers and regulators should enhance ESG disclosure by updating CG codes. The research impulses regulators to strengthen market oversight, especially for companies with higher IO. The results encourage firms and stakeholders in Pakistan, Indonesia, and Malaysia to enhance ESG performance. Emerging economies should favor institutional investors, as they enhance non-financial disclosure transparency and reduce opportunistic behavior of managerial activity in FRQ. Our study results highlight FRQ as a consistent measure of asymmetric information for stakeholders. Companies with higher ESG disclosure are more likely to involve in quality EM practices. The study supports BIND members\u0026rsquo; role in mitigating EM. The study demonstrates that BIND members act as a governance mechanism, mitigating the positive influence of quality of EM on ESG performance.\u003c/p\u003e \u003cp\u003eHigh-quality EM practices, driven by managerial entrenchment, lead to overestimated sustainability investments, reducing corporate value. Firms with higher-quality practices of EM need strong mechanisms of CG to curb EM and limit managerial brownwashing or greenwashing in CSI. These mechanisms of CG inputs provide stakeholders with practical implications. In practice, managerial behavior of opportunism affects not only FP but also reduces resources and capital needed to improve ESG performance. The lower-carbon emission and lower environmental management scores are redirected for the personal use of managers. Without conditioning mechanisms of CG on the EM-ESG performance nexus to diminish the negative effect of quality of EM practices, our outcomes show CG mechanism positively contributes to ESG performance and individual ESG pillar scores, while EM quality practices retain a negative coefficient. Our findings show that BGD, BIND members, and IO have strong moderating effects on CSP, while AC_IND are weaker mechanism of CG.\u003c/p\u003e \u003cp\u003eOur research also contributes to the understanding of the implications of heterogeneity of ESG performance. Robustness results reveal a negative relationship between three ESG percentile scores and the quality of EM practices. We make confirm that influence of quality of EM on ESG disclosure score is lower for companies in the lower percentiles and higher for those in higher percentile, showing that poor EM quality practices can disintegrate CSP. Companies participating in practices of EM, and also believing that some profits remain in books of accounts, might sooner experience of share price overvaluation or mispricing. We provide investors strong evidence that their socially responsible investment (SRI) decisions, which are in line with their ethical beliefs, should not be heavily influenced by the existence of profits. Investors should assess firms\u0026rsquo; ROA relative to the industry, which suggests that investing in SRIs would be a better strategic move, and evaluate companies\u0026rsquo; sustainability initiatives performance. Our findings demonstrate that companies with weaker ROA (below the companies\u0026rsquo; ROA average) still face the constraint influence of EM quality practices on ESG performance, whereas companies with stronger ROA above the industry mean do not.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eLimitation and future research\u003c/h2\u003e \u003cp\u003eSimilar to previous research, our research has several limitations. First, among the mechanisms of CG moderating the connection between quality of EM practices and corporate ESG performance, we discover consistent and strong support for BGD, BIND members, and IO, but not for AC_IND. We believe with full confidence that further better mechanisms of CG, such as concentrated ownership, shareholder activism, board expertise, and frequency of board meetings, could moderate the relationship between EM practices quality and corporate ESG performance. Future research can investigate these potential moderator variables. Second, we consider only sign and absolute discretionary accrual-EM, without including measurement of real-EM. Future studies may examine this, as mechanisms of CG may play different roles in accrual and real-based EM. As literature of CG suggests that experience and diversity of female board directors increase board performance, not considering female directors\u0026rsquo; board capital attributes limits the explanation of the heterogeneous effect of BGD on EM practices quality and ESG performance. Future research could examine how women directors\u0026rsquo; attributes of capital such as, experience, expertise, education, political ties, social interlocking and age heterogeneously affect quality of EM and corporate ESG performance. Future studies may also examine CG mechanisms such as, CEO duality, CEO power, board diligence, promoters\u0026rsquo; equity holdings, external audit, internal audit, audit quality, ethical leadership, and risk management framework.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e \u003cp\u003eAll authors contributed to the study\u0026rsquo;s design, analysis, and writing, and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e \u003cp\u003eThe authors thank their supervisors and institutions for their support and guidance.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbbott LJ, Parker S, Peters GF (2004) Audit committee characteristics and restatements. 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Bus Strategy Environ 30(4):2209\u0026ndash;2223\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZumente I, Lāce N (2021) ESG Rating\u0026mdash;Necessity for the Investor or the Company? \u003cem\u003eSustainability\u003c/em\u003e 13 (16):8940\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":"EM, discretionary accrual, environmental, social, and governance performance, CG mechanisms, agency theory, stakeholders’ theory, resource dependence theory, emerging economies","lastPublishedDoi":"10.21203/rs.3.rs-9311011/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9311011/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eResponding to call in both the quality of earning management practices and corporate sustainability initiative literature to investigate the moderating effect of corporate governance mechanisms such as board gender diversity, board independence, audit committee independence and institutional or foreign ownership, this research filled corporate sustainability initiatives literature gaps by shedding the light on moderating effect of CG mechanisms on the quality of earning management practices and corporate ESG performance nexus. By utilizing a sample of 292 publicly listed companies in the context of emerging economies, countries such as Pakistan, Indonesia, and Malaysia are covered through their listed corporations for the period from 2016 to 2024 (2628 firm-year observations). By utilizing fixed-effects panel regression analysis with two-way clustered standard errors and country, year, industry, and firm fixed effects, the findings demonstrate that the quality of earnings management practices significantly reduces corporate ESG performance practices. All governance mechanisms, EM and ESG performance linkages, and the moderating effect of board gender diversity, board independence, and institutional ownership show a positive and significant moderating influence in Pakistan, Indonesia, and Malaysia, whereas AC independence shows no positive and significant moderating effect. Our study supported agency theory, resource dependence theory and stakeholders\u0026rsquo; theory, which states that CG mechanisms lessen managerial exploitation of the resources which required for corporate sustainable investment and corporate sustainability initiative practices.\u003c/p\u003e","manuscriptTitle":"Do quality earnings management practices reduce corporate ESG performance? The moderating effect of corporate governance mechanisms: Empirical evidence from emerging economies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-06 05:34:35","doi":"10.21203/rs.3.rs-9311011/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":"41b5f656-28ac-4db4-93e0-a313767aae2a","owner":[],"postedDate":"April 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":65669111,"name":"Accounting"}],"tags":[],"updatedAt":"2026-04-06T05:34:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-06 05:34:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9311011","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9311011","identity":"rs-9311011","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}