Unlocking ESG Performance: How Qualified Foreign Institutional Investors Enhance Corporate Sustainability in China’s Capital Markets

Abstract

This study is motivated by the rising global demand for sustainable development and the increasingly important role of foreign institutional investors in shaping corporate behavior in emerging markets. It aims to investigate whether and how qualified foreign institutional investors (QFIIs) influence the Environmental, Social, Governance (ESG) performance of Chinese listed companies. Using panel data from Chinese A-share listed firms between 2009 and 2022, this study employs a two-way fixed-effects model to examine the impact of QFII shareholding on corporate ESG performance and its underlying mechanisms. The findings reveal that QFIIs significantly enhance ESG performance, primarily through promoting green technology innovation, green investment, and green expenses. Furthermore, a composite index of information transparency is developed to investigate its moderating effect, uncovering a substitution effect: QFIIs’ marginal governance impact diminishes in highly transparent firms. Notably, the mediation analysis reveals that QFIIs enhance ESG performance through multiple environmental investment pathways—green innovation, green investment, and green expenses—while the moderating effect of information transparency suggests that QFIIs exert greater influence in less transparent firms. This research advances the theoretical understanding of foreign institutional investors’ influence on sustainability in emerging markets and provides actionable insights for policymakers seeking to align foreign capital with green transition goals.

1. Introduction

Against the backdrop of accelerating global sustainable development agendas, green development has emerged as a policy priority across nations. In 2021, the United States introduced the Environmental, Social, Governance (ESG) Disclosure Simplification Act, empowering the Securities and Exchange Commission to strengthen supervision of corporate environmental and social responsibility disclosures [1]. The European Union adopted the Corporate Sustainability Reporting Directive (CSRD) in November 2022. Starting from fiscal year 2024, this directive mandates large enterprises to disclose standardized ESG information [2]. These policy initiatives indicate that ESG has become a critical consideration in mainstream international investment decisions. In contrast, China’s economy is undergoing a pivotal transformation and upgrading phase. Resource and environmental constraints are tightening, while ecological governance pressures are mounting. This renders the urgency of green development increasingly pronounced. To address these challenges, the Chinese government has successively introduced the 14th Five-Year Plan outline and the Dual Carbon Target Policy system. In 2022, the China Securities Regulatory Commission issued the Guidelines for Investor Relations Management of Listed Companies, while the State-owned Assets Supervision and Administration Commission released the Work Plan for Improving the Quality of Central SOE-controlled Listed Companies [3]. These documents consistently promote corporate social responsibility fulfillment and strengthen environmental information disclosure and green investment system construction. In April 2024, the Shanghai, Shenzhen, and Beijing Stock Exchanges jointly released the Guidelines for Sustainability Reporting of Listed Companies (Trial). This guideline stipulates that, starting from 2026, selected sample companies must mandatorily disclose ESG information. This further demonstrates the Chinese capital market’s emphasis on ESG governance.

Within this policy context, ESG has emerged as a crucial non-financial performance indicator reflecting corporate environmental responsibility, social value, and governance standards. It attracts increasing attention from investors. Simultaneously, the Chinese government provides comprehensive legal protections for foreign investors through laws such as the “Law of Sino-Foreign Equity Joint Ventures” and the “Law on Foreign-funded Enterprises,” aligned with WTO regulations to safeguard market access, intellectual property, and treatment equality. Although foreign ownership is limited in certain industries—for instance, ownership in automotive and aviation sectors is restricted to below 49%—preferential policies and the gradual opening of capital markets further encourage foreign investment. China’s capital market opening has accelerated continuously. Since the launch of the qualified foreign institutional investor (QFII) mechanism in 2002, foreign institutional investors have steadily increased their A-share holdings through various channels, including QFII, RQFII, and Stock Connect programs. Foreign capital holdings have grown significantly in recent years. According to WIND data, the number of A-share listed companies held by QFII increased from 144 in 2012 to 781 in 2024—a five-fold increase. The total market value of holdings surged from RMB 43.9 billion to RMB 117.1 billion. Foreign investors, particularly institutional investors from developed European and American capital markets, typically possess mature green investment concepts, sophisticated risk assessment capabilities, and established governance preferences. Their ESG-oriented investment behavior may exert positive constraints and incentives on portfolio companies [4]. As Garcia and Orsato noted, enterprises often bear substantial costs when implementing ESG strategies [5]. QFII investment may help alleviate financing constraints and enhance corporate information transparency to some extent. Therefore, examining the role of foreign institutional investors in promoting Chinese enterprises’ ESG performance serves multiple purposes. It helps reveal the incentive logic of market mechanisms for corporate sustainable development under global capital flows. It also addresses practical concerns about how Chinese enterprises can achieve high-quality development by optimizing external governance structures under the “dual carbon” goals. This research provides theoretical support and practical reference for improving China’s ESG policy framework. It also contributes to enhancing the green allocation efficiency of capital markets and guiding enterprises toward environmentally friendly, socially responsible, and governance-transparent development models.

Although active participation of foreign capital has become a vital force driving China’s capital market development, the academic definition of “foreign institutional investors” remains inconsistent. Some studies use QFII as the representative of foreign investors, examining its impact on corporate governance and green investment. Others rely on “Northbound Capital” or “Stock Connect” accounts as proxies for foreign investment. However, both approaches have limitations. While QFII is representative, it does not encompass all types of foreign capital. Stock Connect funds may include individual investors or short-term trading accounts, lacking institutional identification. Essentially, foreign institutional investors should possess dual attributes: “foreign origin” and “institutional nature”. Based on this understanding, this study selects QFII as the research subject. QFII qualifies as a foreign investment since it originates from outside mainland China. It also meets the definition of institutional investors, as it primarily comprises legal entities such as securities companies, fund management companies, and insurance companies. These entities possess strong information processing capabilities and long-term investment preferences. Compared to other foreign investment channels, QFII offers greater representativeness and clearer identification. This makes it suitable as an empirical vehicle for analyzing the impact mechanisms of foreign institutional investors.

As a distinctive and important class of investors, qualified foreign institutional investors’ shareholding behavior and its corporate impact have become a focal point of academic research. In corporate governance, studies have explored QFIIs’ influence on internal governance structures by strengthening monitoring and balancing mechanisms, thereby mitigating insider control problems [6,7,8]. In the context of corporate information disclosure, research suggests that QFII participation incentivizes firms to enhance the quality of disclosures and elevate information transparency, thereby reducing information asymmetry between internal and external stakeholders [9]. Studies by [10,11] demonstrate that QFII shareholding helps enterprises increase R&D investment, thereby improving innovation capacity and efficiency. Additionally, QFII participation affects corporate financing and investment decisions. It influences firms’ financing structures and investment choices, which subsequently impacts stock liquidity and market performance [12,13]. QFIIs also facilitate the fulfillment of corporate social responsibility by encouraging enterprises to integrate social and environmental considerations into their strategic objectives, thereby achieving a balance between sustainable development and economic performance [8,14,15]. These studies collectively reveal the multifaceted impact of QFIIs at the enterprise level from diverse perspectives, providing a robust theoretical and empirical foundation for understanding their role in shaping sustainable development in emerging markets.

ESG performance, as a crucial measure of corporate sustainable development, has attracted considerable scholarly attention. Existing research demonstrates that corporate ESG levels are influenced by multiple macro and micro factors. At the macroeconomic level, government fiscal policies [16], taxation [17], financial policies [18,19], and environmental and opening-up policies [20] generally provide positive incentives for enterprises to enhance ESG performance. However, factors such as government debt may inhibit such development [21,22]. External attention from media [23], public pressure, and customer demands [24] helps enhance corporate information transparency and responsibility awareness. Additionally, economic policy uncertainty [25,26] and capital market liberalization [4,27] stimulate enterprises to fulfill sustainable responsibilities more actively to some extent. At the micro-enterprise level, shareholder structure [28] and nature [29], board composition [30,31], financial capacity [32], and corporate digital transformation [33,34,35] all profoundly influence corporate ESG levels. These factors operate through governance mechanisms, information disclosure, and green innovation pathways. Overall, the driving mechanisms of ESG performance exhibit a multi-layered and diversified pattern.

Research by Han et al. [14,36,37] confirms that QFII shareholding exerts a significantly positive effect on corporate ESG performance. Regarding the underlying mechanisms, Wang et al. [14] demonstrate that QFII promotes long-term value creation and strengthens external governance mechanisms, thereby generating positive impacts on environmental performance, product responsibility, and corporate governance, although its effect on employee relations remains relatively limited. Building on internal governance perspectives, Li et al. [36] argue that QFIIs effectively enhance corporate ESG performance by curbing managerial myopia, alleviating financing constraints, and improving corporate risk-taking capacity, which further promotes exploratory innovation capabilities. In terms of heterogeneity analysis, Wang et al. [14] find that QFIIs’ ESG enhancement effects are more pronounced in non-state-owned enterprises and high-tech companies. This heterogeneity may arise from the distinct institutional contexts in China, where SOEs—due to their privileged resource access, less market-driven orientation, and rigid governance structures—are less responsive to external governance signals such as those from foreign institutional investors. Similarly, Li et al. [36] suggest that the positive impact of QFII on ESG performance is stronger in firms with high analyst coverage, intensive media monitoring, and stringent government regulation. However, the existing literature lacks a systematic examination of the specific mechanisms through which QFII promotes corporate ESG performance via environmental investment pathways, particularly regarding green technology innovation, green investment, and green expenses. Moreover, while information transparency serves as a crucial dimension of external governance, most studies rely on single indicators—such as analyst coverage or media attention intensity—which inadequately capture the multidimensional characteristics of information disclosure mechanisms.

Given the limitations of existing research, this study employs panel data from Shanghai and Shenzhen A-share listed companies spanning 2009–2022 and constructs a two-way fixed-effects model to systematically evaluate the direct impact of QFII shareholding on corporate ESG performance. In terms of mechanism identification, we further refine the “environmental investment” pathway by categorizing it into three distinct dimensions: green technology innovation, green investment, and green expenses. These categories, respectively, represent different strategic orientations in enterprises’ green transformation processes—technological breakthroughs, capital allocation, and operational resource deployment—thereby enabling the construction of mediation effect models to explore their transmission mechanisms in QFIIs’ influence on ESG performance. Simultaneously, this study constructs a composite information transparency index based on multi-source data, measuring corporate information disclosure environments from multiple dimensions to reveal the moderating effects in the QFII-ESG relationship. The empirical findings demonstrate that information transparency exhibits not only the traditional “complementary effects” emphasized in the existing literature, but also pronounced “substitution effects” under certain circumstances. This discovery provides a novel explanatory framework for understanding the relationship between information disclosure quality and governance effectiveness, while offering new perspectives and theoretical extensions for ESG governance mechanism research.

This study makes several marginal contributions. First, while existing research primarily focuses on QFIIs’ impact on financial performance or governance structures, this research extends the analysis to ESG performance, enriching perspectives on the relationship between international capital and sustainable corporate behavior. Second, this study disaggregates the “environmental investment” mechanism into green technology innovation, green investment, and green expenses, revealing heterogeneous mediating effects and expanding theoretical boundaries of ESG performance drivers. Third, by constructing a composite information transparency indicator, this research reveals dual moderating effects of “substitution” and “ complementarity”, deepening the understanding of ESG governance mechanisms. Fourth, based on China’s capital market data, this study provides policy insights for emerging markets on leveraging foreign investment to enhance corporate sustainability.

2. Research Hypotheses

2.1. QFII Shareholding and Corporate ESG Performance

The impact of QFII on corporate ESG performance stems from its dual characteristics as both institutional investors and foreign entities. These attributes complement each other, jointly shaping QFIIs’ motivation and capacity to drive ESG improvements.

Firstly, QFII possesses core characteristics typical of institutional investors: professional expertise, capital resources, and information advantages. These attributes enable and motivate them to actively participate in corporate governance and effectively monitor firm behavior. Their supervisory role encourages companies to enhance disclosure completeness, thereby reducing information asymmetries between firms and external investors [12], which establishes the foundation for influencing ESG. Improving ESG performance typically involves substantial implementation costs, resource constraints, and long-term commitments [35,38]. QFII shareholding provides valuable capital support, enabling companies to allocate more resources to environmental projects, employee welfare improvements, and governance structure optimization. Moreover, the rise of shareholder activism emphasizes institutional investors’ crucial role in optimizing corporate governance structures and enhancing governance capabilities [39,40]. As sophisticated rational investors, QFIIs adhere to long-term value investing principles [41]. Given the positive correlation between strong ESG performance and long-term financial performance, risk management, and strategic stability [42], QFIIs have natural incentives to incorporate ESG into investment decisions and generate returns through enhancing portfolio companies’ long-term value [43,44].

Secondly, QFIIs’ foreign identity is the key differentiator from domestic institutional investors, significantly strengthening their motivation and ability to influence corporate ESG performance. Li et al. [7] note that 95.83% of QFIIs originate from IMF-designated developed economies, such as Europe and North America, where corporate governance systems are mature and ESG concepts are well-developed. These investors have long-term exposure to authoritative ESG rating systems in their home countries and have accumulated extensive modern governance experience and high-standard ESG practices [7]. When QFIIs enter the Chinese market, which has a relatively weak institutional environment and incomplete internal controls, their investment philosophy and behavior are expected to introduce mature international governance frameworks and responsible investment standards, thereby promoting portfolio companies’ governance capabilities and ESG performance [4,7]. Their investment itself signals recognition and commitment to higher ESG standards [43], creating institutional pressure on companies to improve disclosure quality and social responsibility fulfillment, directly enhancing corporate ESG performance.

Recent policies such as the EU’s Corporate Sustainability Reporting Directive (CSRD) and the US ESG Information Disclosure Simplification Act have unified ESG disclosure requirements and clarified listed companies’ responsibilities in sustainable governance. QFIIs typically use such international standards as investment benchmarks, and under globalization competition and reputation management needs, they have strong incentives to drive portfolio companies to proactively improve ESG performance and align with international standards. Due to cultural and legal institutional differences and geographical distance constraints, foreign institutional investors often face information disadvantages compared to domestic investors [45]. According to signaling theory, high-quality ESG performance not only helps alleviate agency problems and cross-border investment risks that QFIIs face due to information asymmetries and cultural-legal differences [7,14] but also enhances companies’ reputation and resource acquisition capabilities in international capital markets [46]. Therefore, QFIIs have strong incentives to prioritize companies with good ESG performance to mitigate risks and actively promote portfolio companies to improve governance and enhance ESG transparency and performance as key strategies for overcoming information asymmetries, reducing agency costs, and protecting their investments [47]. Based on this analysis, we propose the following hypothesis:

H1. 

QFII shareholding has a positive impact on corporate ESG performance.

2.2. Mediating Mechanism of Green Technology Innovation

Externality theory suggests that corporate production activities often generate external costs such as environmental pollution and resource waste, which harm social welfare, damage the environment, and constrain sustainable development [48]. Green technology innovation refers to innovation activities related to green products or processes that help firms achieve energy conservation and emission reduction while building environmental reputation. Such innovations effectively mitigate the adverse effects caused by production externalities [49]. By introducing more efficient and environmentally friendly production technologies and management processes, companies can reduce the negative environmental impact of their operations, lower external costs, and thereby enhance their ESG performance [50].

Resource-based view (RBV) suggests that firms must cultivate and leverage strategic resources such as green technologies to achieve long-term competitiveness. Building on this, increased QFII shareholding can inject critical momentum into corporate green technology innovation. On one hand, QFIIs directly provide the capital and resources necessary for innovation, addressing the high investment requirements of green technology development. On the other hand, QFIIs influence corporate management decisions through stock price mechanisms and board governance systems to promote green innovation. Regarding stock price mechanisms, QFII investment behavior exhibits significant “leverage effects”. Investment from mature foreign capital markets serves as a market indicator, with their trading activities triggering market fluctuations several times larger than their actual holdings. When companies fail to meet QFII expectations, the herding effects triggered by divestment force management to abandon short-sighted decisions and prioritize long-term strategies like green technology innovation. At the board governance level, when QFII shareholding reaches a certain threshold, they can leverage voting rights and proposal rights to participate in corporate decision-making using their extensive governance experience, promoting green technology innovation, and facilitating corporate green transformation. QFIIs can also pursue collective litigation against management’s self-interested behavior. To protect their professional reputation, management proactively improves corporate governance, thereby enhancing ESG performance [49,51].

Furthermore, compared to domestic institutional investors, QFIIs hold distinct advantages in promoting corporate green technology innovation. Although both QFIIs and domestic institutional investors are professional investors, QFIIs exhibit a stronger preference for ESG due to their foreign origin. Institutional investors from developed markets are subject to more rigorous ESG compliance requirements and reputational accountability in their home countries. They bring international norms, long-termism, and external pressure mechanisms that may not be present or as strong in domestic investors. This foreignness magnifies their impact on green investment decisions. Green technology innovation is often avoided by management due to high risks and delayed returns. However, QFIIs possess a deep understanding of corporate governance and greater independence, enabling effective supervision management [49]. By promoting contractual management arrangements, QFIIs enhance management’s pay-performance sensitivity, risk-taking capacity, and tolerance for innovation failures, thereby stimulating innovative spirit. Simultaneously, leveraging their independence to collect information and monitor management, QFIIs suppress self-interested and short-sighted behavior while guiding companies toward green development strategies. Drawing on the preceding analysis, the following hypothesis is formulated:

H2. 

QFII shareholding enhances ESG performance through its impact on corporate green technology innovation.

2.3. Mediating Mechanism of Green Investment

According to resource allocation theory, companies must allocate limited resources to areas with maximum marginal benefits to achieve optimal value. In environmental governance contexts, companies can only undertake green investments when they possess sufficient financial resources and achieve high financial investment efficiency. Green investment is characterized by high capital, technology, and human resource requirements with lengthy payback periods. Poor resource allocation can lead to capital shortages and technological stagnation, hindering green investment progress. Conversely, rational resource allocation provides funding guarantees for green project development and environmental equipment procurement, serving as an important prerequisite for green investment implementation.

QFII shareholdings leverage the advantages of capital injections to promote the optimal allocation of corporate resources, thereby significantly improving the efficiency of green investment. As professional investors with substantial financial strength, QFII shareholding provides direct financial resources, alleviating the high capital barriers facing green investment [37,52]. Simultaneously, their professional teams, based on mature investment analysis systems, can accurately identify the potential value of green investment projects, helping companies screen high-return, low-risk green investment directions while avoiding resource misallocation. Additionally, from the lens of institutional theory, firms are embedded in a web of regulatory, normative, and cognitive pressures that shape strategic responses. QFIIs—originating from countries with stringent environmental regulations—transfer institutional norms that elevate environmental investment expectations in investee firms. Unlike domestic investors who may be more attuned to local compliance minima, QFII expectations are shaped by global environmental standards, thus amplifying their pressure on firms to engage in substantive green investment. QFII shareholding brings advanced international corporate governance experience, optimizing internal resource allocation processes through board participation and management oversight [37]. For example, they introduce scientific budget management mechanisms and performance evaluation systems to ensure efficient use of green investment funds. Furthermore, QFIIs’ long-term value investment philosophy encourages companies to abandon short-sighted behavior, providing stable resource support for green investment and ensuring project sustainability and continuity, thereby further enhancing green investment.

Cao et al.’s research demonstrates a significant positive correlation between green investment development and corporate ESG performance [53]. Corporate green investments such as clean production equipment procurement, green product development, and energy conservation and emission reduction technology applications may alter investment arrangements and occupy some productive capital in the short term. However, they can form fixed asset book value in the long term while effectively addressing pollution problems in production processes, reducing pollution control costs and environmental litigation costs. The saved funds can then be used to expand productive capital investment, thereby improving corporate ESG performance [54]. From an environmental performance perspective, high-efficiency green investment enables companies to adopt advanced environmental technologies and equipment, significantly improving resource utilization efficiency and reducing waste emissions, fundamentally improving environmental conditions [52,55]. Additionally, green investment projects generate environmental data that provide evidence for governments to formulate more precise environmental policies while meeting public demands for corporate environmental responsibility oversight, prompting companies to continuously strengthen environmental management under strict external supervision. Regarding social performance, the altruistic effects of green investment transmit positive signals externally, helping companies integrate social resources, deepen inter-company cooperation, and enhance customer loyalty and employee satisfaction. To achieve win-win outcomes for stakeholders, companies become more proactive in fulfilling social responsibilities. Strong social responsibility performance attracts sustainability-oriented investors, reduces regulatory compliance pressure, and promotes ESG performance. In terms of governance performance, enhanced green investment can reduce information asymmetries in corporate governance and suppress irrational management decisions [56], while promoting internal moral culture development and governance structure optimization, creating favorable conditions for sound internal control systems. Moreover, companies emphasizing social responsibility often focus on high-quality information disclosure, which aligns with internal control objectives and further enhances corporate governance performance. Therefore, we propose the following hypothesis:

H3. 

QFII shareholding promotes green investment, thereby enhancing corporate ESG performance.

2.4. Mediating Mechanism of Green Expenses

Existing research often conflates green investment and green expenses, failing to adequately distinguish their differential impacts on corporate environmental strategy choices and economic consequences. From an accounting perspective, green investment represents capitalized expenditures, specifically covering pollution prevention facility construction and ecological protection project investments. These expenditures are recorded on corporate balance sheets and embed environmental protection concepts deeply into production processes through fixed asset formation, reflecting proactive front-end governance strategies adopted by companies [57]. In contrast, green expenses constitute expensed expenditures, including river cleaning fees and environmental compensation payments. Such expenditures directly reduce net profit in income statements, reflecting passive end-of-pipe treatment behaviors [54].

As environmental expenditures of different natures, these two categories exhibit significant differences in their operating mechanisms. Green investment can generate “innovation compensation” effects through technological innovation, while green expenses merely increase current period costs without generating technological spillover benefits. This clear distinction is crucial for revealing the mechanisms underlying corporate environmental responsibility fulfillment.

Legitimacy theory posits that firms engage in symbolic or substantive actions to align with societal expectations and maintain legitimacy. Green expenses—though reducing short-term profitability—serve as visible signals of environmental responsibility. QFIIs pressure firms to incur such costs to preserve legitimacy, particularly under global scrutiny. QFII shareholding influences corporate green expense expenditures through dual pathways: compliance pressure transmission and reputation risk avoidance. Regarding compliance pressure transmission, QFIIs transform strict environmental regulatory requirements from their home countries into supervisory pressure on portfolio companies, prompting increased expenditures on pollution control to meet cross-border compliance requirements. In terms of reputation risk avoidance, given China’s relatively weak institutional environment, when QFIIs are dissatisfied with corporate operating performance or management misconduct occurs, they can directly “vote with their feet” to influence stock prices, using share divestment as a disciplinary mechanism to constrain environmentally non-compliant companies [49,58]. To avoid significant stock price declines and QFII divestment due to environmental issues, corporate management often passively increases end-of-pipe treatment investments, such as paying ecological environmental compensation [18]. Essentially, the growth in corporate green expenses driven by QFIIs represents defensive strategies for addressing cross-border regulatory pressure and reputation risks, rather than constructive behaviors aimed at enhancing corporate proactive innovation capabilities.

Although green expenses are cost items, they can serve as immediate response tools for corporate environmental responsibility, thereby enhancing ESG performance. Under strict environmental protection policies, corporate payments of excess emission fees and ecological restoration funds can mitigate ESG rating decline risks. Emergency investments in sudden pollution incidents can curb ecological damage and ensure stable environmental performance. Compensation for historical environmental issues (such as mining area ecological restoration funds) can repair social relationships, while sustained environmental expense expenditures signal responsibility to the public. This is particularly relevant in heavily polluting industries, where such expenses show significant positive correlation with ESG social contribution indicators [59]. From a governance perspective, precise measurement and disclosure of expensed expenditures compel companies to improve environmental accounting systems. Board review mechanisms for green expense budgets strengthen internal supervision, prevent environmental liability concealment, and enhance governance transparency [60,61]. So, we propose the following hypothesis:

H4. 

QFII shareholding enhances corporate ESG performance indirectly by increasing green expenses.

2.5. Moderating Mechanism of Information Transparency

While existing research generally acknowledges that information transparency helps improve corporate governance and social responsibility fulfillment [62,63], in the pathway where QFIIs influence corporate ESG performance, information transparency may not always serve as an “amplifier”. This moderating effect deserves deeper exploration.

Higher information transparency makes corporate ESG activities more easily identifiable and measurable, and institutional investors generally prefer companies with high information transparency and good ESG performance [64]. Yang et al. indicate that QFIIs are sensitive to information quality, particularly focusing on corporate financial statement transparency, information disclosure ratings, and analyst coverage [65]. As institutional investors from mature markets, QFIIs typically demonstrate significant preferences for well-governed, information-transparent companies. Information transparency can enhance QFIIs’ shareholding propensity [12], and since QFIIs are more sensitive to ESG information, while companies with good ESG performance also have higher information disclosure quality, QFII investment will prompt companies to further improve ESG performance, creating a virtuous cycle where information transparency plays a “complementary” moderating mechanism. However, information transparency essentially reduces information asymmetries and resource differences among investors, making it difficult for QFIIs’ unique professional analytical capabilities, international perspectives, and ESG screening standards to achieve competitive advantages. Therefore, information transparency may also exhibit a “substitution” moderating mechanism in QFIIs’ influence on corporate ESG performance. From an institutional theory perspective, firms are subject to both formal institutional pressures (e.g., laws, listing rules) and informal institutional pressures (e.g., reputational expectations, stakeholder norms). In environments with high information transparency, firms already respond to these pressures by strengthening governance and ESG practices, effectively fulfilling institutional expectations through internalized routines. As a result, external governance interventions from QFIIs become less necessary, explaining the observed substitution effect. Conversely, in low-transparency environments, QFIIs serve as external enforcers of institutional norms, complementing the firm’s weak internal systems.

When companies already possess high information transparency, the marginal utility of QFIIs acquiring corporate ESG information may decline accordingly. In such cases, companies can already adequately transmit positive ESG signals to the market through comprehensive information disclosure systems, effectively meeting investor information needs. The scope for QFIIs to further promote corporate ESG improvement becomes relatively limited, and its “governance effects” or “information transmission effects” are weakened [66]. From a signaling theory perspective, corporate information disclosure in highly transparent environments possesses strong signaling functions, demonstrating corporate advantages and achievements in ESG management to markets and investors, thereby reducing dependence on QFIIs’ external oversight and guidance [67]. This substitution effect is particularly pronounced under certain boundary conditions: (1) firms with strong internal governance structures, where internal control, board independence, and disclosure policies are already well developed; (2) industries under tight ESG regulatory oversight, such as finance or energy; and (3) enterprises with high reputational sensitivity, such as firms with international supply chains or foreign sales exposure. In these contexts, the incremental benefit from QFII monitoring is marginal, as the firm’s ESG agenda is already shaped by institutional conformity and stakeholder pressure.

Furthermore, as an important external governance force, QFIIs’ “monitoring role” exhibits significant differences across companies with varying information transparency levels. Liu et al.’s study demonstrates that pressure-resistant institutional investors show more significant effects on ESG performance improvement in companies with weaker information environments and poorer governance structures [68]. QFIIs typically maintain no business relationships with portfolio companies and adopt long-term value-oriented investment styles, qualifying as pressure-resistant institutional investors. In poorly governed, information-opaque companies, QFII intervention can exert significant governance effects through exercising shareholder rights and participating in corporate decisions, prompting companies to improve ESG practices, enhance information disclosure quality, and perfect corporate governance structures. Conversely, if companies already possess high transparency, this indicates relatively sound internal governance mechanisms and adequate ESG information disclosure. Under these circumstances, the incremental governance improvements that QFII intervention can bring are relatively limited, potentially causing their overall governance effects to exhibit diminishing trends. Wang et al. suggest that high ESG performance companies often possess more comprehensive governance structures, leaving relatively limited scope for external oversight (such as analysts and investors) [69]. This phenomenon aligns with the “diminishing marginal utility of governance” theory, where external investor influence gradually declines as internal governance levels improve [70]. In other words, once corporate internal governance and information transparency reach certain levels, QFIIs’ enhancement effects on corporate ESG performance will no longer be significant. Therefore, we propose the following hypothesis:

H5. 

Information transparency negatively moderates the impact of QFII shareholding on corporate ESG performance, meaning that in companies with high information transparency, QFIIs’ promotional effects on ESG are weakened.

Figure 1 shows the mechanisms of QFIIs’ effects on corporate ESG performance, including mediation and moderation.

3. Research Design

3.1. Model Construction

3.1.1. Baseline Model

To examine the impact of qualified foreign institutional investors (QFIIs) on corporate ESG performance, this study employs a two-way fixed-effects model. Firm fixed effects are included to control for unchanging characteristics that may influence a company’s ESG performance. Time fixed effects are added to remove the impact of broader macroeconomic changes, such as shifts in national policy or economic cycles. This helps reduce unobserved heterogeneity and improves the accuracy of estimating the net effect of QFIIs on ESG.

$${ESG}_{it+1}=a_0+a_1{QFII}_{it}+{\sum }_j{a}_{2j}{Control}_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(1)

In Model (1), the core explanatory variable ${QFII}_{it}$ refers to the shareholding level of QFII in firm i at time t. The dependent variable ${ESG}_{it+1}$ captures ESG performance in the next period. This design considers that firms often need time to respond to qualified foreign institutional investment. Strategic adjustments, resource allocation, and implementation of ESG practices usually cannot be completed in the current period. Using ESG in period t + 1 reflects the staged nature of ESG evaluation and helps avoid misjudging the causal relationship due to time lags. ${Control}_{jit}$ includes a set of control variables. ${\mu }_i$ represents firm fixed effects, ${\lambda }_t$ represents time fixed effects, and ${\epsilon }_{it}$ is the error term.

3.1.2. Mediation Effect Model

To test Hypotheses H2 to H4, this study follows the stepwise regression approach proposed by Wen Zhonglin [71]. Based on the baseline model in Equation (1), we extend the framework by introducing Equations (2) and (3) to construct the mediation effect model set:

$$M_{it}=b_0+b_1{QFII}_{it}+{\sum }_j{b}_{2j}{Control}_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(2)

$${ESG}_{it+1}=c_0+c_1{QFII}_{it}+c_2{M}_{it}+{\sum }_j{c}_{3j}{Control}_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(3)

In this framework, $M_{it}$ represents the mediating variables tested in this study. These include green technology innovation (GTI), green investment (GI), and green expenses (GE). Each mediator reflects a different mechanism through which QFIIs may influence ESG performance. The definitions of the other variables are consistent with those in the baseline model.

3.1.3. Moderation Effect Model

To examine the heterogeneous effects of information transparency on the relationship between QFII ownership and corporate ESG performance, this study constructs a moderating effect model, as shown in Equation (4), to test Hypothesis H5:

$${ESG}_{it+1}=d_0+d_1{QFII}_{it}+d_2{N}_{it}+d_3{{QFII}_{it}\times N}_{it}+{\sum }_j{d}_{4j}{Control}_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(4)

In this model, $N_{it}$ represents the moderating variable—information transparency (TRANS). The interaction term ${{QFII}_{it}\times N}_{it}$ captures how the effect of QFII on ESG performance changes with different levels of information transparency. The sign and magnitude of the interaction coefficient $d_3$ indicate the direction and strength of the moderating effect. The definitions of the remaining variables are consistent with those in the baseline regression model.

3.2. Variable Selection

3.2.1. Explained Variables

In the current literature on ESG, ESG rating scores are widely used as a mainstream measure of corporate ESG performance [72]. Their relevance to firm value largely depends on the actual level of ESG practices [73], and they have been extensively applied in empirical studies focusing on Chinese companies. This study uses ESG ratings provided by the Huazheng ESG index, available through the WIND database. As one of the earliest and most comprehensive ESG rating systems in China, it offers rich and consistent data. The system is built on a multi-layered structure, including 3 primary pillars, 16 secondary themes, 44 tertiary issues, and nearly 80 sub-indicators at the fourth level, supported by over 300 original data points. The ratings are generated using semantic analysis and natural language processing techniques, which makes them well-suited to the characteristics of listed firms in China.

Following the approach of [36], we take the quarterly average of the composite ESG rating scores and use it as the main explanatory variable, denoted as ESG1. A higher ESG1 value reflects stronger ESG performance. For robustness checks, we adopt a second measure (ESG2), based on the method used in [74,75], by converting the quarterly rating grades (ranging from C to AAA) into numerical values from 1 to 9, and calculating the quarterly average accordingly. To address potential lagged effects in ESG responses, all ESG variables used in the regressions are measured with a one-period lead.

3.2.2. Core Explanatory Variables

Some studies [14] use a dummy variable to indicate whether a firm is held by QFIIs. However, such binary treatment may fail to capture the overall investment effect of QFIIs as a group. To address this limitation, and following the research design of [36], this study adopts the quarterly average of the number of shares held by qualified foreign institutional investors (QFII1) as the main explanatory variable.

Given that the dependent variable is measured by quarterly average scores, the use of quarterly QFII data ensures consistency in data frequency. This alignment helps reduce estimation bias that may arise from mismatched time periods. Moreover, using quarterly data allows for a more dynamic observation of both short-term fluctuations and long-term trends in QFII investment behavior, thereby improving the reliability of causal inference.

For robustness analysis, this study further considers the relative influence of QFIIs on corporate decision-making. Compared to the absolute shareholding level, the ratio of QFII holdings to those of the largest shareholder may better reflect their governance power. Drawing on [76], we construct an alternative explanatory variable (QFII2) measured as the quarterly average ratio of QFII shareholding to the largest shareholder’s holdings. This variable serves as a proxy for QFII ownership concentration.

3.2.3. Mediating Variables

Green Technology Innovation

Following Lu et al. [49], this study uses the number of green patent applications filed by a company to measure its green technological innovation (GTI). Due to the inherent lag in the granting of green technology patents, by the time a company applies for such patents, the green technology has already been put into practice within the company. Patent application activities thus provide a more direct reflection of a company’s actual innovation outcomes and better reflect its proactive attitude toward green innovation compared to patent grants. We construct the mediating variable for green technology innovation by combining green invention patent applications and green utility model patents, consistent with previous studies. To address the right-skewed distribution where a few companies hold numerous patents while most have relatively few, we take the natural logarithm of (total green patents + 1) to represent corporate green technology innovation.

Green Investment

Previous studies often relied on corporate sustainability reports or social responsibility disclosures to obtain environmental investment data. However, not all firms publish such reports, and those that do frequently provide vague or incomplete information about environmental expenditures. This creates concerns about data reliability and accuracy. Following Zhang et al. [54,77], we adopt an alternative approach by extracting environmental investment data from detailed construction-in-progress accounts. We aggregate investment expenditures related to pollution prevention, ecological management, and green production activities. These include projects such as desulfurization and denitrification, wastewater treatment, energy conservation, dust removal, waste gas and residue treatment, environmental remediation, ecological restoration, and clean production technologies. The sum of these environmental investments represents the firm’s annual environmental expenditure. We then calculate green investment by dividing this total by year-end total assets. While green investment may indirectly contribute to innovation outcomes, it primarily reflects physical capital expenditures on environmental infrastructure and technologies. In contrast, green technology innovation captures intangible R&D outputs through patent applications. The two reflect distinct aspects of a firm’s environmental strategy and are treated separately to avoid conceptual and empirical conflation.

Green Expenses

Following Zhang et al. [54,78,79], we measure green expenses (GEs) using environmental management costs extracted from the “administrative expenses” section of firms’ income statements. These include greening fees, sanitation expenses, and other environmental treatment costs. A higher ratio suggests more severe green agency problems within the company.

3.2.4. Moderating Variables

This study employs information transparency as a moderating variable. Existing research typically relies on single measures such as information disclosure quality ratings (e.g., evaluations by Shanghai and Shenzhen stock exchanges) or analyst coverage to gauge corporate information transparency. However, these approaches have notable limitations. Disclosure quality ratings focus primarily on regulatory compliance, failing to capture voluntary disclosures and non-financial information quality. Analyst coverage is susceptible to market sentiment, corporate size, and other external factors, while also suffering from “selective attention” bias, creating endogeneity concerns in transparency measurement.

To address the limitations of single-indicator approaches, we follow [74,80] and adopt a multidimensional measurement framework. Our comprehensive transparency measure incorporates five variables across four dimensions: earnings quality (dd) reflects financial information reliability; disclosure compliance score (dscore) captures regulatory disclosure standards; analyst following (analyst) and forecast accuracy (accuracy) represent market interpretation depth; and Big Four auditor engagement (big4) measures external oversight intensity.

We construct the comprehensive information transparency index (TRANS) by calculating the sample percentile means of these variables. This approach systematically integrates both internal and external information characteristics, effectively reducing measurement errors inherent in single indicators and enhancing empirical robustness. Higher TRANS values indicate superior performance in the completeness, reliability, and market accessibility of both financial and non-financial information.

3.2.5. Control Variables

To minimize empirical bias by reducing omitted variable influences and accounting for alternative explanations, we control for factors that may influence corporate ESG performance. Following [14,36], we include three categories of control variables: firm characteristics, financial indicators, and corporate governance measures. For firm characteristics and financial performance, we control for corporate size (SIZE) to account for differences in market position, financial leverage (LEV), return on assets (ROA), fixed asset ratio (FAP), Tobin’s Q (TobinQ), cash flow ratio (CFR), and operating cash flow (CASH). These variables capture the effects of financial structure and profitability on ESG performance. We also include the ratio of independent directors (INDEP) to eliminate potential influences from corporate governance structures.

Given that qualified foreign institutional investors (QFIIs) possess dual characteristics as both foreign and institutional investors, we further control for domestic institutional investor shareholdings (DII). This ensures that any ESG performance improvements attributed to QFIIs stem from their foreign attributes rather than their institutional investor status. Finally, we include firm and year fixed effects to control for unobservable heterogeneity and macroeconomic factors. Detailed variable definitions are provided in

Table 1. Variable definitions and descriptions.

Types	Name	Variable	Description	Unit
Explained variable	Corporate ESG Performance	ESG1	Quarterly mean of the Huazheng ESG Score	-
		ESG2	Quarterly mean of Huazheng ESG Rating Scores assigned on a 1–9 scale	-
Core Explanatory Variable	Qualified Foreign Institutional Investor Shareholdings	QFII1	Quarterly mean of QFII shareholdings	million shares
		QFII2	Quarterly mean of (QFII ownership ratio/Largest shareholder’s ownership ratio)	%
Mediating Variables	Green Technology Innovation	GTI	ln(number of green invention patent applications and green utility model patents + 1)	-
	Green Investment	GI	Total green investment expenditure/Total assets	%
	Green Expenses	GE	Total environmental management costs	million RMB
Moderating Variable	Information Transparency	TRANS	Constructed from the percentile means of five transparency-related variables	-
Control variables	Domestic institutional investor shareholdings	DII	Shareholding of Domestic Institutional Investors/Total Shares Outstanding	%
	Return on Assets	ROA	Operating profit for the year/Total assets at the end of the year	%
	Ratio of Independent Directors	INDEP	Number of independent directors/Number of directors	%
	Fixed Assets Ratio	FAP	Net fixed assets/Total assets	%
	TobinQ	TobinQ	Market capitalization/(Total assets − Net intangible assets − Net goodwill)	-
	Financial Leverage	LEV	Total liabilities/Total assets	%
	Corporate Size	SIZE	Total assets	million RMB
	Cash Flow Ratio	CFR	Net cash flows from operating activities/Total assets

.

3.3. Sample Selection and Data Sources

This study examines Shanghai and Shenzhen A-share listed companies from 2009 to 2022, excluding financial companies. We exclude financial companies due to their distinct characteristics in financial structure, regulatory constraints, and information disclosure requirements, which make them incomparable to other industries. We also exclude companies with abnormal trading status (ST, *ST, and PT) and those with missing key variables. Our final sample comprises 4142 listed companies with 33,153 firm-year observations. To mitigate the influence of extreme values, we winsorize all variables at the 1% level on both tails.

Given the time lag in QFII shareholding effects on corporate ESG performance, we set the dependent variable ESG as a t + 1 indicator to better identify causal relationships. For robustness checks, we also use t + 2 ESG indicators. Accordingly, our sample period spans 2009–2022, with corresponding ESG data covering 2010–2024. This design ensures reasonable causal identification while maximizing sample size and research robustness.

Our explanatory variable QFII and control variables are sourced from the CSMAR database, while corporate ESG performance data come from the WIND database’s Huazheng ESG ratings. Information transparency data are manually compiled from the CSMAR database, and green patent application data are obtained from the CNRDS database. Industry classification follows the sector codes specified in the “Listed Company Industry Classification Guidelines” issued by the China Securities Regulatory Commission in 2012.

4. Empirical Results

4.1. Descriptive Statistics

Table 2. The description of variables.

VarName	Obs	Mean	SD	Min	Median	Max
ESG1	33,153	73.185	4.668	57.895	73.368	84.764
QFII1	33,153	0.097	0.384	0.000	0.000	2.708
DII	33,153	41.792	24.014	0.555	42.932	90.006
ROA	33,153	4.312	6.459	−23.464	4.130	21.846
INDEP	33,153	37.617	5.347	33.330	36.360	57.140
FAP	33,153	21.920	15.441	0.196	18.726	68.387
TobinQ	33,153	2.179	1.385	0.873	1.737	9.330
LEV	33,153	41.931	20.378	5.048	41.189	90.788
SIZE	33,153	1310.522	3278.351	39.478	373.614	25,073.168
CFR	33,153	4.837	6.753	−16.675	4.712	24.090
GTI	33,153	0.361	0.767	0.000	0.000	3.526
GI	33,153	8.324	10.891	0.000	4.281	57.564
GF	33,153	65.935	124.076	2.979	26.537	846.609
TRANS	33,153	0.303	0.193	0.005	0.285	1.000

presents the descriptive statistics of the core variables used in this study. The ESG score ranges from 57.895 to 84.764, with a mean of 73.185 and a standard deviation of 4.668, suggesting moderate differences in the companies’ ESG performance. The QFII variable exhibits a mean value of 0.097, with a standard deviation of 0.384. The median is 0, indicating that most companies in the sample do not have QFII shareholding in a given year, although the maximum value reaches 2.708, suggesting that in some cases, QFIIs hold significant stakes. These results preliminarily reveal that while ESG scores are relatively stable across companies, QFII ownership is highly skewed, concentrated in a subset of listed companies.

4.2. Baseline Model Regression

Table 3. Impact of QFII on ESG: baseline regression results.

	(1)	(2)	(3)	(4)	(5)
	OLS	OLS	Fixed-Effects	Fixed-Effects	Cluster (Firm)
QFII1	1.482 ***	0.658 ***	0.270 ***	0.251 ***	0.251 ***
	(22.390)	(10.391)	(4.187)	(4.016)	(2.765)
DII		0.007 ***		0.004	0.004
		(7.057)		(1.630)	(1.033)
ROA		0.192 ***		0.113 ***	0.113 ***
		(43.330)		(27.002)	(19.439)
INDEP		0.058 ***		0.038 ***	0.038 ***
		(13.157)		(7.026)	(5.059)
FAP		−0.025 ***		−0.015 ***	−0.015 ***
		(−15.336)		(−5.643)	(−3.769)
TobinQ		−0.443 ***		−0.143 ***	−0.143 ***
		(−24.790)		(−7.026)	(−5.058)
LEV		−0.024 ***		−0.028 ***	−0.028 ***
		(−17.708)		(−14.461)	(−9.239)
SIZE		0.000 ***		0.000 ***	0.000 ***
		(33.303)		(15.072)	(7.941)
CFR		0.007 *		−0.012 ***	−0.012 ***
		(1.763)		(−3.434)	(−2.891)
_cons	73.042 ***	71.924 ***	73.149 ***	72.607 ***	72.607 ***
	(2784.385)	(373.789)	(3894.260)	(287.519)	(198.987)
Firm fixed effect	Yes	Yes	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes	Yes	Yes
N	33,153	33,153	32,965	32,965	32,965
Adj. R2	0.015	0.164	0.526	0.555	0.555

Note: t-statistics in parentheses. * p < 0.1, *** p < 0.01.

presents the baseline regression results examining the relationship between QFII investment and corporate ESG performance. Column (1) employs ordinary least squares (OLS) estimation, revealing a positive and statistically significant coefficient for QFII at the 1% level, providing preliminary evidence that qualified foreign institutional investors enhance corporate ESG performance. In Column (2), we introduce control variables while maintaining the significance of the QFII coefficient. The variance inflation factor (VIF) test confirms the absence of multicollinearity concerns among explanatory variables. Subsequently, the Hausman test guides our selection of the fixed-effects model to control for both individual and time-invariant heterogeneity. After excluding 188 singleton observations, Columns (3) and (4) present results without and with control variables, respectively. The QFII coefficient remains significant at the 1% level. To address potential heteroskedasticity and within-group serial correlation, we employ firm-clustered robust standard errors in Column (5). The QFII coefficient maintains its positive significance, confirming that increased QFII shareholding effectively improves listed companies’ ESG performance. Economically, each additional million shares of QFII holdings is associated with an approximate 0.251-point increase in the Huazheng ESG Score, indicating that foreign institutional ownership exerts a meaningful upward influence on listed firms’ sustainability ratings. These findings provide robust empirical support for H1, demonstrating that qualified foreign institutional investment serves as a catalyst for enhanced corporate environmental, social, and governance practices.

4.3. Robustness Test

4.3.1. Alternative ESG Measurement

To ensure the robustness of our findings, we conduct additional analysis by replacing the dependent variable from the original Huazheng ESG scores with a nine-level rating system (ESG2). This alternative measurement approach transforms the continuous ESG scores into ordinal rankings, providing a different perspective on ESG performance assessment. As presented in Table 3, Column (1), the QFII coefficient remains positive and significant at the 5% level, confirming the reliability of our conclusions.

4.3.2. Lagged Dependent Variable Analysis

Considering that the impact of qualified foreign institutional investors on corporate ESG performance may involve time lags, as corporate ESG improvements may require processes such as strategic planning, organizational restructuring, and stakeholder engagement, which take time to implement, we further use the ESG performance indicators from the t + 2 period as the dependent variable to re-estimate our baseline model, aiming to reveal the persistence and evolution of QFII influence.

Table 4. Robustness test results.

	(1)	(2)	(3)	(4)	(5)	(6)
	Change Dependent Variable ESG2	Two-Period Lead ESG3	Two-Period Lead ESG4	Change Independent Variable ESG1	Change Model ESG1	Change Model ESG1
QFII1	0.049 **	0.238 **	0.048 **		0.245 ***	0.245 ***
	(2.573)	(2.144)	(2.134)		(2.700)	(2.699)
QFII2				0.601 **
				(2.514)
_cons	Yes	Yes	Yes	Yes	Yes	Yes
Controls	Yes	Yes	Yes	Yes	Yes	Yes
Firm fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
Industry fixed effect	No	No	No	No	Yes	Yes
Province fixed effect	No	No	No	No	No	Yes
N	32,965	32,965	32,965	32,965	32,965	32,952
Adj. R2	0.534	0.524	0.509	0.555	0.557	0.557

Note: t-statistics in parentheses. ** p < 0.05, *** p < 0.01.

, Column 2 uses the t + 2 period Huazheng ESG score for estimation, while Column 3 employs the corresponding nine-level rating system at the t + 2 time point for analysis. In both regression results, the QFII coefficient remains positive and significant, further reinforcing the evidence that QFIIs currently exert a substantial and enduring impact on corporate sustainable development practices.

4.3.3. Alternative Proxy for QFII Investment

To further validate the robustness of the core explanatory variable, we adopt an alternative proxy for QFII investment intensity. We construct QFII2 as the quarterly average ratio of qualified foreign institutional shareholding relative to the largest shareholder’s shareholding. This indicator reflects the bargaining power and supervisory capacity of qualified foreign institutional investors relative to the controlling shareholder. The regression results with the replaced independent variable are shown in Column (4) of Table 3. Consistent with the baseline findings, QFII2 has a positive and significant relationship with corporate ESG performance.

4.3.4. Extended Fixed-Effects Specifications

To address potential unobserved heterogeneity issues, we extend the benchmark two-way fixed-effects model to incorporate additional dimensions of variation. We adopt three-way and four-way fixed-effects models, controlling for industry and provincial characteristics, respectively, beyond the standard firm and time fixed effects.

The three-way fixed-effects model (Table 3, Column 5) adds industry fixed effects to reflect industry-specific investment preferences and ESG practices. Given that QFII investment patterns may exhibit systematic variability due to differences in growth prospects, regulatory environments, and the importance of ESG across industries, controlling for industry-level heterogeneity ensures that our estimates capture the variability in QFII effects within industries rather than differences in ESG performance across industries. The four-way fixed-effects model (Table 3, Column 6) further includes provincial fixed effects to address concerns about differences in location-specific factors such as local policies, institutional quality, or resource endowments.

The regression results of both models show that the QFII coefficients remain positively significant, confirming that foreign institutional investment can still enhance corporate ESG performance even after controlling for unobservable heterogeneity across multiple dimensions.

4.4. Addressing Endogeneity

4.4.1. Heckman Two-Stage Estimation

Our analysis faces potential endogeneity concerns due to QFII investment selection preferences and firm self-selection into ESG practices. Foreign investors typically favor firms with strong governance, transparent information disclosure, and ESG performance, while firms may enhance ESG practices to attract foreign investment. This bidirectional relationship may lead to sample selection bias.

We employ the Heckman two-stage estimation to address these concerns. We first construct a binary indicator (QFII_dum) that equals one if a firm receives QFII investment and zero otherwise. Following Liu and Zhao [81], we use the CSI 300 index membership (CSI300) as our instrumental variable. The CSI 300 index comprises the largest and most liquid stocks in the Chinese market, making these firms more visible and accessible to institutional investors. This visibility increases the likelihood of QFII investment, satisfying the relevance condition for instrumental variables. Importantly, CSI 300 membership is determined by market capitalization and liquidity rather than ESG performance. The index selection criteria do not directly consider sustainability factors, suggesting that any impact on ESG performance operates primarily through the QFII investment channel. This feature supports the exclusion restriction required for valid instrumental variables.

In the first stage, we estimate a probit model regressing the instrumental variable (CSI300) on the binary QFII indicator (QFII_dum), controlling for all baseline covariates. We then calculate the inverse Mills ratio (${IMR}_{it}$) from the first-stage results and include it in the second-stage regression to correct for selection bias.

Table 5. Heckman test results.

	(1)	(2)
	QFII_dum	ESG1
CSI300	0.315 ***
	(10.341)
imr		−3.428 ***
		(−2.607)
QFII1		0.269 **
		(2.105)
_cons	Yes	Yes
Controls	Yes	Yes
Firm fixed effect	Yes	Yes
Time fixed effect	Yes	Yes
N	32,616	6017
Adj. R2		0.716

Note: Robust z-statistics in parentheses ** p < 0.05, *** p < 0.01.

presents the Heckman two-stage estimation results. Column (1) shows the first-stage probit results, where the CSI300 coefficient is positive and statistically significant. This confirms that CSI 300 membership substantially increases the probability of QFII investment, validating the relevance of our instrumental variable. Column (2) reports the second-stage results. The inverse Mills ratio (${IMR}_{it}$) is positive and significant, indicating that sample selection bias is indeed present and non-negligible. Crucially, the QFII coefficient remains positive and significant after controlling for selection bias, confirming the robustness of our main findings even when accounting for potential endogeneity concerns.

4.4.2. Instrumental Variable Approach: GMM Estimation

While QFII investment may enhance corporate ESG performance through improved governance, reduced information asymmetry, and better sustainability practices, firms with strong ESG foundations may also attract more QFII investment. This creates potential reverse causality and endogeneity concerns. To address this issue, in this study, ESG indicators are set as leading indicators in the base model. Furthermore, the instrumental variable method (IV-GMM) is introduced to identify the net effect of QFIIs on ESG.

When selecting instrumental variables, we draw on the research approaches of Liu [81] and Fisman et al. [82], considering that the industry concentration of QFII investment behavior is greater than provincial concentration. We use the industry-year average QFII holdings of peer firms (IV_QFII) as the first instrumental variable. This variable captures industry-level QFII investment trends and strongly correlates with individual firm QFII holdings, satisfying the relevance condition. Since peer firms’ QFII investment does not directly affect individual firm ESG performance, this instrument meets the exclusion restriction. In addition, we include the one-period lag of QFII holdings (L.QFII1) as the second instrumental variable to mitigate dynamic endogeneity by utilizing its time-leading characteristic relative to ESG changes.

Table 6. GMM-2SLS test results.

	(1)	(2)	(3)	(4)
	First Stage QFII1	Second Stage ESG1	First Stage QFII1	Second Stage ESG1
L.QFII1	0.503 ***		0.503 ***
	(26.518)		(26.507)
IV_QFII	0.150 ***		0.150 ***
	(3.244)		(3.248)
IV2_QFII			0.114 *
			(1.806)
QFII1		0.487 **		0.485 **
		(2.429)		(2.417)
Underidentification test (Kleibergen–Paap rk LM statistic)		131.309 (Chi-sq(2) p-val = 0.0000)		131.462 (Chi-sq(3) p-val = 0.0000)
Weak identification test (Cragg-Donald Wald F statistic) (Kleibergen-Paap rk Wald F statistic):		3772.144 361.067		2515.429 246.345
Hansen J statistic (overidentification test)		0.010 (Chi-sq(1) p-val = 0.9193)		1.251 (Chi-sq(2) p-val = 0.5350)
_cons	Yes	No	Yes	No
Controls	Yes	Yes	Yes	Yes
Firm fixed effect	Yes	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes	Yes
N	27,629	27,121	27,617	27,109
Adj. R2	0.249	−0.078	0.249	−0.078

Note: (1) t-statistics in parentheses. (2) z-statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01.

presents the GMM estimation results. Column (1) shows the first-stage regression where both IV_QFII and L.QFII1 significantly predict current QFII holdings, indicating strong instrumental variable relevance. The underidentification test and the Cragg–Donald weak identification test confirm adequate instrument strength. The Hansen over-identification test yields a p-value of 0.9193, supporting instrument validity. The second-stage results demonstrate that QFII investment significantly enhances corporate ESG performance at the 5% level. These findings reinforce our main conclusions and strengthen the causal interpretation of the QFII-ESG relationship.

To further strengthen the identification strategy and address potential concerns that industry-level ESG trends may violate the exclusion restriction of peer-based instruments, we introduce a third instrumental variable: the province-year average QFII holdings of other listed firms (IV2_QFII), which captures spatial heterogeneity in QFII allocation and reflects regional investment patterns that are plausibly exogenous to individual firm ESG performance. This spatial instrument complements the industry-based IV by leveraging geographic variation that is less likely to be driven by sector-wide ESG dynamics. While IV2_QFII is marginally significant at the 10% level in the first stage, the three instruments jointly exhibit strong identification, as reflected in a high Kleibergen–Paap F statistic of 246.34. The overidentification test (Hansen J, p = 0.535) confirms instrument validity. Columns (3) and (4) of Table 6 report the estimation results using all three instruments. The positive effect of QFII on ESG remains statistically significant, confirming the robustness of our main findings.

4.4.3. Propensity Score Matching

Since QFII investment is not randomly assigned, we employ propensity score matching (PSM) to construct a comparable control group. This approach addresses selection bias by matching treated firms (with QFII investment) to similar untreated firms (without QFII investment) based on observable characteristics.

We first estimate a panel fixed-effects logit model using the binary QFII indicator (QFII_dum) as the dependent variable and all baseline control variables as covariates. Using the predicted propensity scores, we implement one-to-one nearest neighbor matching with a caliper of 0.05 to ensure high-quality matches.

Figure 2 demonstrates the matching effectiveness, showing a substantial reduction in covariate differences between treatment and control groups.

Table 7. Balance test.

	Unmatched	Mean			%Reduct	t-test
Variable	Matched	Treated	Control	%bias	|bias|	t	p > |t|
DII	U	44.66	40.97	15.20	11.64		0
	M	44.66	44.99	−1.400	91.10	−0.820	0.414
ROA	U	5.367	4.010	21	15.97		0
	M	5.371	5.258	1.700	91.70	1.060	0.288
INDEP	U	37.84	37.55	5.300	4.030		0
	M	37.84	37.90	−1.200	78.20	−0.670	0.500
FAP	U	22.26	21.82	2.800	2.160		0.0310
	M	22.26	22.29	−0.200	93.80	−0.100	0.917
TobinQ	U	2.213	2.169	3.200	2.410		0.0160
	M	2.213	2.218	−0.400	87.90	−0.230	0.820
LEV	U	41.28	42.12	−4.200	−3.120		0.00200
	M	41.27	41.55	−1.400	66.70	−0.850	0.397
SIZE	U	1539	1245	8.600	6.780		0
	M	1539	1643	−3.100	64.50	−1.630	0.102
CFR	U	5.986	4.508	21.70	16.64		0
	M	5.989	5.949	0.600	97.30	0.340	0.733

reports the balance tests, confirming that all standardized biases are below 10% and t-tests are statistically insignificant after matching. This indicates successful elimination of systematic differences between treatment and control groups.

Using the matched sample of 11,299 observations, we re-estimate our baseline model.

Table 8. PSM test results.

	(1)
	ESG1
QFII1	0.384 ***
	(2.882)
_cons	Yes
Controls	Yes
Firm fixed effect	Yes
Time fixed effect	Yes
ATT T-stat	4.72
N	11,299
Adj. R2	0.625

Note: t-statistics in parentheses. *** p < 0.01.

shows that the QFII coefficient remains positive and significant at the 1% level. The average treatment effect (ATT) yields a t-statistic of 4.72, well above the conventional threshold of 1.96, confirming that QFII investment significantly enhances corporate ESG performance even after controlling for selection bias. These results provide additional evidence for the robustness of our findings.

4.5. Mechanism Analysis

4.5.1. Mediating Effects

Mediating Effect of Green Technology Innovation

Table 9. Mechanism test for green technology innovation.

	(1)	(2)	(3)
	ESG1	GTI	ESG1
QFII1	0.251 ***	0.043 ***	0.240 ***
	(2.765)	(2.883)	(2.659)
GTI			0.249 ***
			(4.475)
_cons	Yes	Yes	Yes
Controls	Yes	Yes	Yes
Firm fixed effect	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes
N	32,965	32,965	32,965
Adj. R2	0.555	0.655	0.555
Bootstrap 95% conf. interval	[0.0026017, 0.0206865] (Percentile CI) [0.003616, 0.0224028] (BC Percentile CI)
Mediated proportion of total effect	4.313%

Note: t-statistics in parentheses. *** p < 0.01.

presents the results of the mediating role of green technology innovation (GTI). Column (2) shows that QFII investment significantly enhances corporate green technology innovation capabilities at the 1% level. In Column (3), when both QFII and GTI are included as explanatory variables, the QFII coefficient remains significant but decreases in magnitude compared to Column (1), while GTI exhibits a positive and significant coefficient at the 1% level.

These results indicate that QFII investment partially operates through green technology innovation to improve corporate ESG performance. The significant GTI coefficient suggests that enhanced green innovation capabilities serve as an important channel through which qualified foreign institutional investors promote corporate sustainability practices. This finding implies that QFIIs not only directly influence ESG outcomes through governance mechanisms but also indirectly drive improvements through innovation activities.

To ensure robustness of the mediation effect, we employ the product-of-coefficients test combined with bootstrap resampling (2000 iterations). Both the bias-corrected and percentile confidence intervals for the indirect effect of GTI excluded zero, confirming the robustness of the mediation pathway. Given the persistence of the direct effect, GTI functions as a partial mediator in the relationship between QFII and ESG performance. The mediation proportion analysis shows that GTI accounts for 4.313% of the total effect, providing a quantitative measure of its contribution. These results provide strong support for H2.

Mediating Effect of Green Investment

Table 10. Mechanism test for green investment.

	(1)	(2)	(3)
	ESG1	GI	ESG1
QFII1	0.251 ***	0.451 **	0.246 ***
	(2.765)	(2.306)	(2.714)
GI			0.011 ***
			(3.191)
_cons	Yes	Yes	Yes
Controls	Yes	Yes	Yes
Firm fixed effect	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes
N	32,965	32,965	32,965
Adj. R2	0.555	0.450	0.555
Bootstrap 95% conf. interval	[0.0004392, 0.0105106] (Percentile CI) [0.0008383, 0.0111028] (BC Percentile CI)
Mediated proportion of total effect	1.887%

Note: t-statistics in parentheses. ** p < 0.05, *** p < 0.01.

presents the mediation analysis for green investment. Column (2) shows that QFII investment significantly promotes corporate green investment at the 1% level. This finding suggests that qualified foreign institutional investors actively encourage firms to allocate more resources toward environmentally sustainable projects and assets. Through green investment activities, firms can more effectively integrate green resources, optimize production processes, and enhance their overall environmental, social, and governance performance.

Column (3) includes both QFII and GI in the regression model to test for mediation effects. Both coefficients are positive and significant at the 1% level, with the QFII coefficient showing a reduction in magnitude compared to Column (1). These results indicate that QFII investment enhances corporate ESG performance partially through increased green asset allocation. Therefore, H3 was verified.

The bootstrap test with 2000 random samples confirms the robustness of the mediation effect, as the confidence intervals for the indirect effect of green investment exclude zero. This validates that green investment serves as a significant mediating channel in the QFII-ESG relationship. The mediated proportion of the total effect is 1.887%, indicating that green investment accounts for a modest yet meaningful share of the overall impact of QFII on ESG performance. Given the continued significance of the direct effect, green investment functions as a partial mediator in this relationship, highlighting its role in channeling foreign institutional influence toward sustainable corporate practices.

Mediating Effect of Green Expenses

We also examine whether green expenses (GEs) serve as a mediating pathway for QFII’s impact on ESG performance.

Table 11. Mechanism test for green expenses.

	(1)	(2)	(3)
	ESG1	GE	ESG1
QFII1	0.251 ***	7.188 ***	0.240 ***
	(2.765)	(2.757)	(2.669)
GE			0.002 **
			(2.003)
_cons	Yes	Yes	Yes
Controls	Yes	Yes	Yes
Firm fixed effect	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes
N	32,965	32,965	32,965
Adj. R2	0.555	0.918	0.555
Bootstrap 95% conf. interval	[0.000274, 0.0279706] (Percentile CI) [0.0009159, 0.0296427] (BC Percentile CI)
Mediated proportion of total effect	4.516%

Note: t-statistics in parentheses. ** p < 0.05, *** p < 0.01.

presents the corresponding mediation analysis.

Column (2) shows that QFII investment significantly increases corporate green expenses at the 1% level. This finding suggests that qualified foreign institutional investors indirectly drive firms to incur additional costs related to pollution control and environmental compliance to meet regulatory requirements and stakeholder expectations.

In Column (3), QFII and green expenditure coefficients are significant, indicating that green expenses partially mediate the relationship between QFII investment and ESG performance. QFII implementation not only strengthens communication between firms and stakeholders but also reduces information asymmetries, providing greater support for corporate ESG practices. These end-of-pipe treatment costs ultimately enhance firms’ performance in social responsibility and environmental governance.

The results demonstrate that QFII investment indirectly promotes corporate ESG performance by increasing green expenses, supporting H4. Bootstrap testing with 2000 samples confirms the robustness of this mediation effect, as both bias-corrected percentile confidence intervals and percentile confidence intervals for the indirect effect exclude zero. The mediation proportion analysis indicates that the indirect effect through GEs accounts for 4.516% of the total effect, suggesting that green expenses function as a partial mediator in the relationship between QFII investment and ESG performance.

4.5.2. Moderating Effects

To test H5, which posits that information transparency negatively moderates the relationship between QFII ownership and corporate ESG performance, we present the regression results in

Table 12. Moderating effects test for information transparency.

	(1)	(2)
	ESG1	ESG1
QFII1	0.251 ***	0.586 ***
	(2.765)	(2.778)
TRANS		3.684 ***
		(15.895)
c.TRANS#c.QFII1		−0.745 **
		(−2.142)
_cons	Yes	Yes
Controls	Yes	Yes
Firm fixed effect	Yes	Yes
Time fixed effect	Yes	Yes
N	32,965	32,965
Adj. R2	0.555	0.562

Note: t-statistics in parentheses. ** p < 0.05, *** p < 0.01.

. Column (1) reports the baseline regression examining the direct impact of QFII holdings on ESG performance. Column (2) introduces the moderating variable—information transparency (TRANS)—and its interaction with QFII.

The results show that both QFII and TRANS are positively and significantly associated with ESG scores at the 1% significance level. Importantly, the interaction term between QFII and TRANS is significantly negative (coefficient = −0.745, p < 0.05), suggesting a negative moderating effect of information transparency. This indicates that the positive impact of QFII on ESG performance is stronger in firms with lower levels of information transparency. In contrast, for firms with higher transparency, the marginal effect of QFII on ESG improvement diminishes, thereby supporting Hypothesis 5.

To visually illustrate this moderating effect, Figure 3 plots the interaction between QFII and information transparency. The solid line represents firms with low information transparency, while the dashed line represents firms with high transparency. Low and high levels of information transparency are defined as one standard deviation below and above the mean of the transparency variable, respectively. Both lines exhibit a positive slope, confirming that QFII contributes to ESG improvement in both cases. However, the slope for low transparency firms is steeper, indicating that the ESG-enhancing role of QFII is more pronounced when firms disclose less transparent information.

These findings underscore the enabling role of QFIIs in enhancing ESG performance, particularly among firms with weaker information environments, highlighting QFIIs’ function as an external governance mechanism compensating for internal disclosure limitations.

5. Discussion

This study focuses on “foreign institutional investors” rather than “foreign investors” in a general sense, selecting QFII as a proxy variable to clearly demonstrate its dual characteristics of “institutional attributes” and “foreign attributes.” This distinction is critical, as prior research employing “Stock Connect” (Northbound capital) as a proxy for foreign investors [4] may include individual accounts and short-term trading, thus failing to accurately capture institutional attributes. In contrast, QFIIs are approved institutional entities with a long-term investment orientation. To rigorously examine QFIIs’ effect, we adopt both the quarterly average of shareholdings (absolute measure) and the balancing power index (relative measure). The baseline regressions confirm that QFII holdings significantly promote corporate ESG performance, extending the findings of [14,36,37].

In exploring the mechanisms, we deconstruct environmental investment into three categories—green technological innovation, green investment, and green expenses—to provide a nuanced understanding of QFIIs’ influence on ESG. This classification addresses prior studies’ tendency to conflate green investment and green expenses. From a theoretical standpoint, green investments—being capitalized expenditures—can yield “innovation compensation effects,” while green expenses, as expense-based items, increase immediate costs without long-term spillovers. Moreover, green technological innovation, a strategic long-term commitment, is treated as a distinct mediator. Our stepwise regression and bootstrap tests show that QFIIs significantly stimulate green technological innovation, supporting findings in [10,11,49], which in turn contributes to higher ESG performance. QFIIs also enhance green investment, aligning with Eliwa et al. [41], who emphasize institutional investors’ preference for long-term value creation. This facilitates firms’ ability to integrate green resources and optimize production processes. While green expenses are often reactive or compliance-driven, Parrino et al. [58] argue that institutional investors like QFIIs can exert pressure through “voting with their feet” to discipline environmentally non-compliant firms—a mechanism also confirmed by our empirical evidence.

Finally, we incorporate information transparency as a moderating variable to examine heterogeneity in the QFII–ESG relationship. The information transparency coefficient is positive, in line with Huang et al. [74], affirming that transparency supports ESG development. However, the interaction term between QFII and information transparency is negative, suggesting that QFIIs’ impact on ESG is weaker in high-information-transparency firms. This finding implied that regulatory efforts to mandate ESG disclosure—such as China’s 2024 Sustainability Reporting Guidelines—may substitute for the external governance role of foreign institutional investors. As mandatory disclosure becomes more widespread, the marginal value of QFIIs in improving ESG performance may decline, suggesting the need for coordination between disclosure reforms and foreign investment policy. This finding can be interpreted through signaling theory and the diminishing marginal utility of governance: firms with already strong governance structures have less room for additional oversight from external investors like QFIIs. This result is also consistent with Wang et al. [69], who document that high-ESG firms benefit less from external monitoring. While increased transparency may reduce the marginal role of QFII as an external monitor, it also enhances public scrutiny and reputational pressures. This trade-off suggests that firms in high-transparency environments may still face strong ESG accountability, albeit through different governance channels. Therefore, rather than viewing transparency as a substitute for institutional monitoring, it may be more accurate to consider them as complementary under certain conditions.

6. Conclusions and Policy Proposals

This study addresses the following research questions: (1) Does QFII shareholding affect corporate ESG performance? (2) What are the mechanisms of this effect? (3) Under what conditions is the impact stronger or weaker? Based on panel data of Chinese A-share listed firms from 2009 to 2022, this study systematically examines the impact of qualified foreign institutional investors (QFIIs) on corporate ESG performance, as well as the underlying mechanisms. The empirical results demonstrate that QFII holdings significantly improve firms’ overall ESG scores, primarily through three channels: fostering green technological innovation, enhancing the intensity of green investment, and guiding environmentally related green expenses. In the mechanism analysis, this paper distinguishes between capitalized and expensed forms of environmental investment and treats green innovation as an independent mediating variable, thereby highlighting QFIIs’ crucial role in driving firms’ long-term green strategic transformation. Furthermore, the moderation analysis shows that information transparency negatively moderates the relationship between QFII and ESG performance—QFII has a more pronounced effect in firms with lower transparency levels. This finding confirms QFII’s value in strengthening external governance and mitigating information asymmetries in firms operating within weaker information environments. In conclusion, QFII—as an investor type that embodies both institutional and foreign attributes—serves not only as a financial force supporting the green transformation of Chinese firms, but also as a reflection of the global shift in investment philosophy toward sustainable development. The findings of this study contribute to the theoretical understanding of the relationship between foreign institutional ownership and corporate non-financial performance, and offer policy insights for regulators seeking to optimize the path of capital market liberalization and improve the effectiveness of ESG governance in emerging markets.

Based on the empirical findings of this study, the following policy recommendations are proposed:

1. Refine the QFII regulatory framework to advance high-level capital market openness. Regulators should continue improving the QFII system by gradually relaxing investment quotas and expanding the scope of “connectivity mechanisms” such as Stock Connect. A more open capital market would attract long-term-oriented foreign institutional investors, bringing advanced investment philosophies and corporate governance practices that support firms in enhancing green innovation, environmental awareness, social responsibility, and governance efficiency.

2. Enforce environmental regulations and strengthen the ESG disclosure framework. Environmental policies should be strictly implemented to incorporate sustainability metrics into corporate performance evaluations and increase stakeholder attention to firms’ environmental and social conduct. Simultaneously, ESG disclosure standards should be improved and progressively made mandatory. Standardized and transparent reporting will reduce information asymmetry and enable foreign institutional investors to more effectively monitor and engage with firms post-investment.

3. Promote scientific allocation of environmental investments to align sustainability and profitability. Firms should optimize their environmental investment strategies by balancing green R&D, capitalized environmental projects, and operational environmental expenditures. Such alignment will ensure regulatory compliance while enhancing both environmental and financial outcomes. Policymakers can support this through targeted incentives—such as tax relief, direct subsidies, and green finance instruments like green bonds or loans—to encourage long-term investment in low-carbon technologies and foster a sustainable industrial ecosystem.

4. Strengthen engagement with foreign institutional investors to enhance firms’ ambidextrous innovation. Companies should establish structured and ongoing communication channels with foreign institutional investors to better understand their ESG expectations and governance preferences. By leveraging these investors’ long-term orientation and global governance expertise, firms can refine their ESG strategies and implementation pathways, thereby transforming external oversight into internal motivation and enhancing both exploitative and exploratory innovation capacity in the pursuit of sustainable, high-quality growth.

5. Optimize the QFII investment structure to advance national “dual carbon” strategic goals. Policymakers should consider channeling QFII quotas toward high-emission and environmentally sensitive industries, where the marginal impact of foreign capital on green innovation is more pronounced. This targeted allocation would enhance QFIIs’ environmental governance role and accelerate the green transformation of carbon-intensive sectors, thereby supporting China’s transition toward carbon peaking and carbon neutrality.

In summary, the findings of this study provide important insights into green sustainable development for policymakers and business managers. Beyond its policy implications, this study contributes to the academic literature by clarifying the mechanisms through which foreign institutional investors influence ESG performance in emerging markets. It identifies green technology innovation, green investment, and green expenses as distinct mediating channels and further reveals the substitutional moderating role of information transparency. These findings advance ESG research by deepening the understanding of foreign investor influence on firm-level sustainability. However, this study still has several limitations. First, although QFII is a representative proxy for foreign institutional investors, it does not encompass other foreign investor types, such as sovereign wealth funds or ETFs that enter via Stock Connect, potentially limiting the generalizability of the findings. Second, while this paper focuses on the environmental component of ESG to unpack mediation channels, the social and governance dimensions are only captured in aggregate scores, and their independent pathways remain underexplored. Third, while the study offers practical policy recommendations, future work should further explore its implications for comparative governance theory, as well as expand the scope to cross-country and cross-regime contexts. Future research is encouraged to investigate more diverse investor types, conduct multi-dimensional decomposition of ESG scores (e.g., labor standards, board diversity), and incorporate macro policy shocks and regional institutional variation to reveal deeper heterogeneities.