Can ESG Performance Sustainably Reduce Corporate Financing Constraints Based on Sustainability Value Proposition?

Abstract

Under the pressure of global low-carbon transformation, the sustainable development initiative of the United Nations has gradually become an essential orientation of corporate Environmental, Social, and Governance (ESG) performance. Based on the integrated theoretical framework of sustainable development finance, this work explores the relationships among corporate ESG performance, its financing constraints in China, and its influencing mechanism, as well as the role played by green innovation in this relationship. Using a comprehensive panel dataset of 1038 A-share listed companies from 2013 to 2023, totaling 11,418 observations, we find that corporate ESG performance and financing constraints exhibit a significant negative relationship, indicating that strong corporate ESG performance can effectively alleviate corporate financing constraints. To address endogeneity concerns, we employ a systematic generalized method of moments (GMM) and a two-stage least squares regression using lagged instrumental variables. The results of the mechanism test show that ESG performance mitigates financing constraints by reducing perceived financial risks, improving information transparency, and increasing access to government green subsidies. Furthermore, moderating effect analysis reveals that green innovation strengthens the mitigating effect of corporate ESG performance on financing constraints in this process, based on SDG 9. Heterogeneity analysis reveals that this mitigating effect of corporate ESG performance on financing constraints is more pronounced for firms in China’s economically advanced eastern region, for companies facing harder budget constraints, and in the period following the implementation of the stringent new Environmental Protection Law. Distinguishing between genuine and symbolic corporate actions, we provide evidence that only substantive ESG improvements, as opposed to “greenwashing,” are rewarded by capital providers. The findings provide insights for the formulation of government policies and corporate sustainability strategies in emerging markets.

1. Introduction

The global economic paradigm is undergoing a profound transformation, driven by the dual imperatives of environmental sustainability and social equity [1]. The United Nations’ 2030 Agenda for Sustainable Development, with its 17 Sustainable Development Goals (SDGs), provides a universal blueprint for this transition. It serves as a global call to action to “eradicate poverty, protect the planet and create a blueprint for a better and more sustainable future for all by 2030”, urging all societal actors, particularly the corporate sector, to align their activities with these global priorities [2,3]. In response to the global drive for low-carbon development, nearly 150 countries have enacted and implemented carbon-neutral targets through legislation and policies, thus continuously reinforcing the concept of sustainable development. In parallel, the concept of Environmental, Social, and Governance (ESG) has evolved from a partial concern into a mainstream framework for evaluating corporate resilience, risk management, and long-term value creation. As countries worldwide, including China, with its ambitious “dual carbon” targets (peak emissions by 2030, carbon neutrality by 2060), legislate and incentivize a low-carbon economy, new development opportunities for ESG concepts are available, and therefore, the ESG framework has begun to be emphasized by all stakeholders.

In this context, green financing has become a critical catalyst for corporate transition. However, financing constraints, the frictions that prevent firms from funding all desired investments due to issues such as agency costs, remain a primary impediment to corporate growth, innovation, and ultimately, sustainable development. In the face of market volatility, exacerbated by events such as the impact of the COVID-19 epidemic and persistent economic pressure, enterprises are currently facing financing dilemmas including high credit thresholds, long financing chains, and the limitations of traditional financing models. These challenges represent critical bottlenecks to the sustainable development of enterprises [4,5]. Consequently, enterprises are increasingly seeking to expand financing channels, lower financing costs, and achieve a breakout via financial innovation and policy support. The emergence of the ESG concept progressively made corporate ESG performance a significant basis for assessing corporate value in the capital market. This has prompted corporations to integrate principles into their development strategies, with the potential to alleviate the constraints on corporate financing being a critical factor in determining whether corporations are willing to invest resources to improve their ESG performance [6].

A well-considered investment strategy should encompass multiple dimensions of sustainability. In terms of environmental sustainability, corporations will inevitably have an impact on the environment, while those with good ESG concepts can formulate policies to alleviate or eliminate the negative impacts brought by carbon emissions, energy, waste management, and pollution, among other aspects [3]. On social sustainability, establishing objective and scientific social standards would help the society to realize an inclusive space, which is consistent with the SDGs to achieve peace and prosperity for all stakeholders, such as businesses, communities, and agencies [7]. As for governance sustainability, the stronger the ESG concept of a corporation, the more effective the internal control and risk management in the decision-making, operation, and compliance process will be [8]. In terms of social sustainability, the construction of objective and scientific social standards is conducive to the realization of an inclusive space in society, which is in line with the SDGs and enables all stakeholders, including corporations, communities, and institutions, to achieve peace and prosperity. Once good corporate ESG performance can be beneficial to corporations, they will independently choose to increase their ESG investment, which in turn will promote the construction of the ESG framework. Therefore, it is crucial to explore whether corporate ESG performance can alleviate the financing constraints of corporations and clearly identify the mechanism of influence to promote the sustainable development of corporations.

While a growing body of literature suggests a negative relationship between ESG performance and financing constraints in developed markets, the evidence from emerging economies, particularly China, is more complex. China’s unique institutional environment, characterized by strong state guidance and a rapidly evolving regulatory landscape for ESG disclosure, creates powerful incentives for firms to improve their ESG credentials. However, this top-down pressure, combined with market imperfections, also creates a ground for “greenwashing”, symbolic compliance where firms improve their ESG disclosures without undertaking substantive changes in their operations.

This study brings several contributions to the existing literature on ESG performance and financing constraints based on the Sustainable Development Goals (SDGs). First, it takes an early step to discuss the impact of corporate ESG performance on corporate financing constraints from the framework of multidimensional goals of sustainable development, which expands the research related to the economic consequences of corporate ESG performance within the framework of SDGs. It provides a breakthrough from the existing limitations of the previous literature in studying the economic consequences of corporate ESG performance from the dimensions of earnings [9], market investor behavior [10], and other aspects. Second, it explores the influence mechanism of corporate ESG performance and the financing constraints from the perspective of the SDGs in light of established research, which reveals the multiple dimensions of corporate ESG performance as measured by the sustainable development degree of corporations. It evaluates the limiting influence of risk factors on corporate financing constraints from the perspectives of financial and non-financial risks, where the non-financial risks are measured from the perspective of the transparency of information regarding the government’s green subsidies, which represents the two types of influence mechanisms, i.e., degree of social acceptance [11,12] and the relationship between government and business [13], respectively, to argue that ESG performance affects the impact of corporate financing constraints, providing a new path to alleviate the problem of corporate financing constraints. Third, it considers the perspective of the green innovation level of enterprises and expands the analysis of the regulating effect of green innovation between ESG performance and corporate financing constraints based on SDG9, so as to provide policymaking and corporate decision-making for ESG advantages on financing constraints. Finally, it considers the regional differences in ESG performance on corporate financing constraints and the heterogeneity that exists before and after the implementation of the new environmental protection law, and it also analyzes the discrepancy characteristics concerning the relationship between “regional regulatory differences and policy effects”, which, to a certain extent, enriches the relevant research on the promotion of sustainable development by corporations.

This study addresses these questions by using a comprehensive panel of 1038 Chinese A-share listed companies from 2013 to 2023. First, we provide robust causal evidence on the economic consequences of ESG performance in the world’s largest emerging market. The generalized method of momenta (GMM) and two-stage least squares (2SLS) approach are used as identification strategies, in contrast to prior studies that rely on weaker endogeneity tests. Second, we deepen the understanding of the transmission mechanisms, showing that ESG performance alleviates financing constraints, not only by reducing financial risk, enhancing information transparency, and obtaining government green subsidies, but also by directly improving corporate credit ratings. Third, we offer an analysis of the moderating role of green innovation. Finally, and most significantly, we contribute to the frontier of ESG research by exploring the substantive versus symbolic action concepts. The analysis and discussion on greenwashing provide evidence that the financial benefits of ESG are a result primarily for firms demonstrating genuine commitment, offering critical insights into the information quality and credibility challenges within the rapidly evolving ESG ecosystem.

This paper is structured as follows. Section 2 reviews the institutional context and the relevant literature. Section 3 develops the theoretical framework and hypotheses. Section 4 describes the research design, data, and methodology. Section 5 presents the empirical results. Section 6 discusses the findings and their implications, and Section 7 presents the conclusions and implications of the research.

2. Literature Review

2.1. The Evolution of ESG and Its Economic Consequences

The concept of ESG was first introduced in the “Who Cares Wins” report published by the United Nations in 2004 [14]. ESG concepts sprouted in the 1960s and 1970s, when the human rights movement and the public environmental protection movement had been growing, and a number of investors began to consider social responsibility as a criterion for their investment decision-making. In 2006, the United Nations Principles for Responsible Investment (PRI) proposed the ESG concept and evaluation mechanism for the first time, after which, the ESG concept came into the realm of investors and theoretical researchers. Numerous academics have focused their research on the factors that could affect the ESG performance of corporations and the economic consequences of corporate ESG performance [15,16].

Factors influencing corporate ESG performance can be classified into external and internal. External factors include governmental behavior, market attention, and regulatory pressures, for instance, the pilot policy of low-carbon cities [17], the institutional investor research [18], and the environmental protection tax levied on corporations for pollution emissions [19]. Internal factors are related to corporate management characteristics, the nature of ownership, and industry differences, such as female executives who may exhibit greater concern about ESG issues [20], and the level of digital transformation in state-owned enterprises (SOEs) [21] and corporations that are sensitive to the sustainable goals, such as oil and gas corporations, which may show superior ESG performance [22]. From the perspective of the economic consequences, several studies have found that corporate ESG performance significantly improves corporate financial performance [23]. Corporations with positive ESG track records can establish friendly relationships with relevant stakeholders, accumulate social capital [24], and lower exposure to the risk of financial difficulties and financial defaults [25]. All these positive signals can help to strengthen public confidence in the market, leading to increased market attention, lower financing costs, reduced financial stress, and improved book value and market value of the firm [26]. Furthermore, enhanced ESG performance necessitates greater disclosure of non-financial information, which improves transparency, alleviates information asymmetry, and thus enhances investors’ willingness to provide capital [27]. It also signals a firm’s active commitment to realizing SDG goals, thereby improving its corporate reputation.

2.2. Financing Constraints

Financing constraints present a major dilemma faced by many corporations in the process of operation, and these constraints stem from market imperfections caused by conflict of interest and information asymmetry between firms and investors [28]. When investors face information asymmetry, it is difficult for them to accurately anticipate and judge the future development of the enterprise and guarantee their own returns and capital security, which leads to investors being discouraged [11]. As a result, companies fail to obtain financing, which in turn inhibits their ability to innovate, affects their investment activities and places pressure on their operations [29,30]. As financing constraints are a critical bottleneck restricting the growth of enterprises and are one of the dilemmas that must be broken to promote economic development, research indicates that information disclosure is an effective way to solve the underlying factors of financing constraints. By disclosing non-financial information such as supply chain information [31], social responsibility information [32], and environmental protection information [33], the enterprises can effectively mitigate information asymmetry, thereby creating a favorable relationship of trust with relevant stakeholders, thus effectively mitigating financing constraints. External auditors [34], financial analysts [35], and other information transfer intermediaries also can play a crucial role by fulfilling their supervisory functions and also effectively reduce the information asymmetry gap between enterprises and investors.

2.3. Green Innovation as a Strategic Differentiator

In accordance with the United Nations SDG 9, “Innovation and Infrastructure Development”, green innovation has been a necessary choice for the development of corporations, and it can bring the potential of a win–win outcome for both the environment and the economy [36]. Corporations can reduce pollution and improve the environmental performance of the corporations through green innovation activities, such as the development of clean technologies and the provision of green products, with a potential of enhancing labor productivity [37]. This allows the corporation to receive higher economic benefits and also attract more consumers with a preference for green products, enhance the profitability of the corporation, reduce the financial risk of the corporation [38], and enhance the ability of endogenous financing. It integrates recent evidence on ESG, circular economy governance, and financing outcomes in emerging markets, providing strong support for related research and practice [39]. When firms actively practice ESG concepts, their green and innovative environmental initiatives align with society’s expectations for sustainable development and significantly enhance their attractiveness in the investment market. In a circular economy governance, enterprises promote recyclable and reusable products through green innovation, which not only reduces the cost of resources but also obtains green subsidies from the government for conforming to environmental protection trends and helps alleviate financing problems. In addition, when corporations face the risks associated with divergent ESG ratings, they will hedge this risk by improving their green innovation level [40]. Under the goal of promoting green and sustainable development, it is easier for enterprises actively engaging in green innovation to gain government green subsidies and support from investors [41], which increases the source of funds for enterprises and thus alleviates the financing problems of enterprises.

2.4. Integrated Corporate SDG Finance and Corporate Strategy

A review of the relevant literature reveals that most studies focus on the relationships among corporate ESG performance, financing constraints, and green innovation. Few studies have explored the role of green innovation from the perspective of the impact of corporate ESG performance on financing constraints. In this paper, we aim to incorporate the value concepts of multidimensional sustainability framework to develop the discussion on the impact of corporate ESG performance on financing constraints from the environmental, social, and corporate sustainability goals. The objective is to provide a comprehensive reference for corporations to overcome financing dilemmas and achieve sustainable development.

3. Theoretical Analysis and Hypothesis Development

3.1. The Framework of Theoretical Analysis

This work adopts the integrated corporate SDG finance framework as its primary theoretical basis. This modern framework reframes corporate sustainability not as a separate CSR activity but as a core element of financial strategy. It argues that firms should develop a holistic approach that links their capital structure and financing decisions directly to their strategic goals for contributing to the SDGs. This approach is central to new global reporting standards such as the EU Corporate Sustainability Reporting Directive (CSRD) and China’s emerging Corporate Sustainability Disclosure Standards (CSDS) [42]. Double materiality requires firms to report on both “outside-in” impacts (how sustainability issues affect the company’s financial performance) and “inside-out” impacts (how the company’s operations affect the environment and society).

Within this overarching framework, we integrate three foundational theories of corporate finance to explain the mechanisms at play: (i) Stakeholder theory, indicating that a firm’s long-term success depends on its ability to manage relationships with a wide range of stakeholders, not just shareholders. These include employees, customers, suppliers, communities, and regulators [43,44]. (ii) Signaling theory, important in markets characterized by information asymmetry, where firms can use certain actions to signal their underlying quality to external parties. A strong and consistent ESG performance acts as a powerful, credible signal to investors [6]. (iii) Agency theory, which focuses on the conflicts of interest between principals (e.g., shareholders) and agents (e.g., managers) [45]. ESG can have a dual role in this context. On the one hand, managers may engage in ESG activities for self-serving reasons (e.g., empire-building or reputation enhancement), which would increase agency costs. On the other hand, and more aligned with our hypothesis, a robust ESG framework, particularly the governance pillar, can serve as a powerful monitoring mechanism. The increased transparency and disclosure required for high-quality ESG reporting can reduce managerial discretion and align managers’ interests more closely with those of long-term investors, thereby reducing agency costs and making the firm a more attractive investment. As shown in Figure 1 below, stakeholder theory drives enterprises to improve ESG performance for approval, which builds the trust foundation for signaling theory, while signaling theory provides stakeholders with monitoring tools through ESG information disclosure, and agency theory regulates the behavior of management, guarantees the authenticity of information, and strengthens the basis of signal quality, and meanwhile, signaling provides the supervision basis for shareholders. These three theories create a circle of “external trust–signaling–supervision and identification–further trust”, which ultimately enhances trust, reduces information asymmetry, lowers agency costs, magnifies the value of ESG, improves the attractiveness of investment, and alleviates financing constraints.

3.2. Hypotheses Development

3.2.1. Corporate ESG Performance and Corporate Finance Constraints

ESG emphasizes the synergistic development of environment, social responsibility, and governance quality. High ESG performance delivers positive signals to the public that the enterprise is environmentally friendly, takes social responsibility actively, and has solid corporate governance, which can be recognized by the public and help the enterprise to improve its own reputation. In this way such corporations can utilize positive goodwill to enhance their sustained profitability and give them an advantageous position in market competition [46], which in turn attracts investors’ attention to the corporation. Besides, ESG ratings also discipline the financial irregularities of enterprises [47], which reduces the risk of investment and induces investors to consider them as a priority in their decision-making. Consequently, this helps enterprises to reduce the cost of equity capital [48] and have access to more equity financing, commercial credit, and financial credits, thus alleviating corporate financing constraints.

Based on this, this work proposes the following first hypothesis.

Hypothesis 1.

Corporate ESG performance is negatively associated with the extent of corporate finance constraints.

3.2.2. Corporate ESG Performance, Sustainable Development, and Corporate Finance Constraints

Following the increasing attention of the public and consumers to corporate social responsibility (CSR) and the rising demand for ESG disclosure by government regulators, more and more companies are incorporating ESG into their core strategic planning for sustainable development, while well-regulated and evaluated mechanisms provide corporations with a sound, stable, and transparent institutional environment by improving government–enterprise relations, enhancing consumer stickiness, establishing stable cooperative relationships with suppliers, and reducing investor concerns, which helps enterprises improve financial stability [49,50,51]. Positive feedback can thus be provided to the ESG ratings of enterprises, which is conducive to obtaining high-quality bank loans and further reducing the financing constraints of enterprises.

Being a tool for disclosing non-financial information, on one hand, positive corporate ESG performance reveals that corporations have strengthened information disclosure, improved information transparency, effectively mitigated information asymmetry [52], and alleviated the adverse selection and moral hazards associated with these issues. Moreover, enterprises with better ESG performance are usually more inclined to enhance information transparency, providing investors with more comprehensive and accurate information, so that investors can recognize the corporate status in a non-financial perspective, offering investors a reliable source for decision-making and enhancing investors’ confidence [53]. Therefore, it can effectively improve the inhibitory effect of corporate ESG performance on financing constraints by reducing corporate risk and enhancing corporate information transparency. On the other hand, government green subsidies, as an attractive policy tool for market-incentivized environmental regulation, usually show a positive association between an enterprise’s ESG rating and the probability of obtaining government green subsidies. Enterprises with high ESG ratings would focus more on the area of applying low-pollution technologies and activities, and government green subsidies provide special green funds issued by the government to promote the SDGs, such as R&D subsidies, and tax incentives. Thus, enterprises with high ESG ratings are more likely to receive government green subsidies, which assist enterprises in reducing the R&D costs required for sustainable development, and a favorable government–enterprise relationship may also release positive signals to stakeholders, attract more external investors, and help enterprises alleviate their financing constraints [13].

In accordance with this, the proposed second, third, and fourth hypotheses are the following:

Hypothesis 2.

Corporate ESG performance could alleviate corporate financing constraints by reducing corporate financial risk.

Hypothesis 3.

Corporate ESG performance alleviates corporate financing constraints by improving information transparency.

Hypothesis 4.

Corporate ESG performance can alleviate corporate financing constraints through access to government green subsidies.

3.2.3. Corporate ESG Performance, Green Innovation, and Corporate Finance Constraints

On the basis of signaling theory, a company’s ESG performance is essentially an ethical signal, yet its credibility is often limited by information asymmetry. Green innovation significantly reduces the risk of mis-signaling by translating abstract ESG commitments into concrete technological practices. Green product innovations obtained by companies are certified by third parties—for example, Li-Ning Company Limited’s green product innovation wins Product Carbon Footprint ISO/Dis 14067 certification [54]—and the technological spillover of green innovation consolidates the signaling effect. Enterprises contribute to the formation of an industry demonstration effect through green packaging technology, which improves their own ESG ratings and also promotes the green transformation of upstream and downstream enterprises by supply chain coordination. This technological empiricism shifts ESG signaling from “declarative” to “validating”, effectively alleviating the doubts of rating agencies about the “greenwashing” of corporate ESG information. Therefore, green innovation can generate an insurance effect to buffer the risk caused by divergent corporate ESG ratings [55], and it can also reduce corporate carbon emissions to satisfy the SDGs by improving energy efficiency and corporate managerial expertise and reduce the risk of environmental pollution during corporate operations and other aspects to improve the environmental benefits of firms, thus enhancing their ESG performance [56,57]. The presence of a robust green innovation portfolio can strengthen the negative relationship between ESG performance and financing constraints through several channels. First, it acts as a powerful, credible signal that a firm’s ESG commitments are substantive rather than merely symbolic or “greenwashing.” Patents for green technologies are verifiable signals of a firm’s capabilities and strategic direction, which can help buffer the risks associated with ESG ratings. Second, green innovations, particularly green process innovations, often lead to greater resource efficiency, lower pollution, and reduced operational costs, which directly reinforces the risk-reduction mechanism of ESG.

Accordingly, this paper proposes the fifth hypothesis:

Hypothesis 5.

Green innovation positively moderates the negative relationship between firms’ ESG performance and financing constraints, such that the mitigating effect of ESG on financing constraints is stronger for firms with higher levels of green innovation.

In summary, the overall theoretical hypothesis modeling framework in this paper is shown in Figure 2.

4. Research Design

4.1. Sample Selection and Data Sources

Based on the limitation of corporate ESG and related financial data, this study selects the data of Shanghai and Shenzhen A-share listed corporations from 2013 to 2023 as the original research samples, in which the related financial data of listed corporations were obtained from the CSMAR database, and the corporate ESG data were collected from HUAZHENG SMART ESG ratings data, a leading provider in China known for its comprehensive coverage and methodology tailored to the Chinese market context, to ensure the accuracy of the experimental results of the following treatments for the sample data in this work: (1) excluding the sample of listed companies in the financial sector (banks, insurance companies, etc.) due to their unique capital structures and regulatory environments; (2) removing listed corporations that had ST (Special Treatment), *ST (delisting risk warning), and other abnormal financial designations, which could generate deviations from the measurement of financing constraints; (3) excluding listed corporations with more missing data for the key variables and linearly interpolating the data with fewer missing values. After processing, the data of 1038 listed corporations from 2013 to 2023 are available, with a total of 11,418 observation samples, and the continuous variables are finally subjected to 1% and 99% Winsorized treatment in order to eliminate the effect of outliers. To address potential multicollinearity in the moderation analysis, all independent and moderating variables are centered before creating the interaction term.

4.2. Definition of Variables

(1) Dependent variable: the degree of corporate financing constraints (FC_degree). The SA index was selected by Hadlock and Pierce as our primary proxy for financing constraints [58]. The SA index is constructed based on two firm characteristics that are largely exogenous to firm investment and financing policies: firm size and age. It is calculated by listing years and enterprise size, has a higher exogenous nature, and can effectively avoid the issues of endogeneity and subjective choice, and the larger the absolute value of the SA value is, the more serious the FC_degree faced by the corporation is. The choice of the SA index is motivated by its advantages over other common indices like the KZ and WW indices, particularly in the Chinese context. As shown in

Table 1. Comparison of financing constraint indices.

Index	Components	Theoretical Basis	Limitations
SA index	Firm Size, Firm Age	Based on qualitative information from financial reports; smaller, younger firms are more constrained.	May not capture short-term shocks to financing access.
KZ index	Cash Flow, Tobin’s Q, Debt, Dividends, Cash Holdings	Based on investment–cash flow sensitivity and financial statement variables.	Highly endogenous; strongly correlated with financial distress, not just constraints.
WW index	Cash Flow, Tobin’s Q, Debt-to-Assets, Dividend Payout, Sales Growth	Based on Euler equation estimates of investment.	Endogenous components; less correlated with qualitative measures of constraints than SA.

, the KZ and WW indices include endogenous financial variables (e.g., cash flow, leverage, Tobin’s Q), which can be directly influenced by a firm’s ESG strategy, creating a mechanical correlation. The KZ index, in particular, has been shown to be a stronger proxy for financial distress than for financing constraints. The SA index, by relying on more exogenous characteristics, provides a cleaner measure of a firm’s structural access to external capital.

(2) Independent variable: the primary independent variable is corporate ESG performance (ESG_smart). The selection of Huazheng ESG ratings is based on the following considerations. Compared with well-known ESG rating providers such as MSCI and FTSE Russell, Huazheng ESG ratings are more in line with the regulatory requirements and unique characteristics of the Chinese market and can be better adapted to the domestic market environment [59]. When compared with other rating systems in the early stages of development, such as Business Gateway China, Huazheng’s ESG ratings have become a more suitable standard for the local market due to their mature methodology, extensive data coverage, high availability, and strong policy suitability. The Huazheng system is chosen for its extensive coverage of Chinese A-share firms and its methodology that incorporates China-specific factors, such as policies on “common prosperity” and “dual carbon” goals, making it highly relevant for our sample. This rating system evaluates firms across the three pillars (E, S, and G) and assigns a score of 1 to 9 to each of the nine levels from “C” to “AAA” in the HUAZHENG ESG rating scale, and the higher the value, the better the ESG_smart performance of the corporation.

(3) Mechanism variables: financial risk (FR_score), government green subsidies (Ges), and information transparency (IT_opaque). We measure financial risk using Altman’s Z-score model (Z_score). The model combines five financial ratios into a single score. A higher Z-score indicates lower financial risk, where a positive coefficient in the regression implies risk reduction. Government green subsidies draw on [60]’s approach of using the amount of government green subsidies received by firms each year, size-adjusted to measure the relative level of government green subsidies, expressed in percentage terms. We measure information transparency (or opacity) using the magnitude of discretionary accruals, following the modified Jones model (IT_Opaque) [61], following Dechow’s method [62]. We calculate the sum of the absolute value of the company’s discretionary accruals (DA) over the past three years. A larger value of this variable, IT_opaque, signifies greater earnings management and thus lower information transparency:

$$IT\_opaque=Abs\left({DA}_{i-1}\right)+Abs\left({DA}_{i-2}\right)+Abs\left({DA}_{i-3}\right)$$

(1)

Discretionary accruals (DA) are estimated by using the modified Jones model. The process is as follows: using model (2) to perform yearly and industry-specific regressions, the DA is estimated by substituting the calculated coefficients into model (3).

$${\displaystyle \frac{T{A}_{i,t}}{Asse{t}_{i,t-1}}}={\alpha }_1{\displaystyle \frac{1}{Asse{t}_{i,t-1}}}+{\alpha }_2{\displaystyle \frac{{\Delta SR}_{i,t}}{Asse{t}_{i,t-1}}}+{\alpha }_3{\displaystyle \frac{FA{V}_{i,t}}{Asse{t}_{i,t-1}}}+{\epsilon }_{i,t}$$

(2)

$$D{A}_{i,t}={\displaystyle \frac{T{A}_{i,t}}{Asse{t}_{i,t-1}}}-({\stackrel{\wedge }{\alpha }}_1{\displaystyle \frac{1}{Asse{t}_{i,t-1}}}+\stackrel{\wedge }{{\alpha }_2}{\displaystyle \frac{{\Delta SR}_{i,t}-{\Delta AR}_{i,t}}{Asse{t}_{i,t-1}}}+\stackrel{\wedge }{{\alpha }_3}{\displaystyle \frac{FA{V}_{i,t}}{Asse{t}_{i,t-1}}})$$

(3)

where TA is total accruals, Asset is total assets, ∆SR is the increase in sales revenue, ∆AR represents the increase in accounts receivable, and FAV is the original fixed asset value.

(4) Moderating variables: We measure green innovation (GI) using patent data from the CNRDS database, which classifies patents based on the International Patent Classification (IPC) Green Inventory. Currently, green patents are mainly used by scholars as a proxy variable to measure the GI_patent variable [63,64]. We measure the GI_patent by adding 1 to it to take the natural logarithm of the green patent data from the CNRDS database.

(5) Control variables: To isolate the effect of ESG performance, we include a comprehensive set of control variables known to influence corporate financing constraints, consistent with the prior literature. We selected asset–liability ratio, length of growth, ROA, proportion of shares held by the first largest shareholder, degree of equity checks and balances, integration of two positions, size of the board of directors, proportion of sole directors, Tobin’s Q value, and quality of ownership as the control variables and controlled for the fixed effects of time and industry. Detailed information on each variable is shown in

Table 2. Definitions of variables.

Type	Variable Name	Variable Symbol	The Definitions of Variables
Dependent Variable	Financing constraints	FC_degree	The absolute value of SA index|
Independent Variable	ESG performance	ESG_smart	Huazheng ESG 9-tier rating (1 = CCC, 9 = AAA)
Mechanism Variables	Financial risk	FR_score	Using the Z-score model for measurement
	Enterprise information transparency	IT_opaque	The sum of the absolute value of the company’s discretionary accruals over the past three years
	Government green subsidies	Ges	(Government green subsidies/total assets) × 100
Moderating Variables	Green innovation	GI_paten	The natural logarithm of the number of green patent applications for company i in the year t + 1.
Control Variables	Asset liability ratio	Lev	The total debt/total assets
	The enterprise growth	Growth	Main business revenue growth/main revenue last year
	Return on total assets	ROA	Net income/total assets
	Ownership concentration	OC	The listed company’s largest shareholder’s shareholding
	Ownership restriction index	ORI	Sum of shareholding percentages of 2nd–5th largest shareholders/the listed company’s largest shareholder shareholding
	Directors and managers of situation	DS	Existence of Duality = 1, and vice in 0
	The size of board	Board	The natural logarithm of the number of directors on the board
	The independent director proportion	Indep	Number of independent directors divided by total board size
	Tobin’s Q	TobinQ	Market value/total assets
	Property rights	SOE	State-owned enterprises (SOEs) = 1, and vice in 0
	Year	Year	Annual fixed effect
	Industry	Industry	Industry fixed effects

.

4.3. Econometric Model Building

In order to test hypothesis 1 and explore whether corporate ESG performance can alleviate corporate financing constraints, this paper constructs model (4) and controls for industry and year fixed effects:

$$\begin{gathered} {FC\_degree}_{i,t}={\alpha }_0+{\alpha }_1{ESG\_smart}_{i,t}+{\alpha }_{2}Control{s}_{i,t} \\ +\sum Year+{\sum Industry+\epsilon }_{i,t} \end{gathered}$$

(4)

where i and t represent firms and years respectively, FC_degree denotes financing constraints, ESG_smart stands for ESG performance, Controls represents control variables, and Year and Industry represent the fixed effects of industry and year.

To validate the mechanism of corporate ESG’s impact on corporate financing constraints, i.e., to test the hypotheses H2, H3,and H4, we construct models (5), (6), and (7):

$$\begin{gathered} {FR\_score}_{i,t}={\alpha }_0+{\alpha }_1{ESG\_smart}_{i,t}+{\alpha }_{2}Control{s}_{i,t} \\ +\sum Year+\sum Industry+{\epsilon }_{i,t} \end{gathered}$$

(5)

$$\begin{gathered} {IT\_opaque}_{i,t}={\alpha }_0+{\alpha }_1{ESG\_smart}_{i,t}+{\alpha }_2{Controls}_{i,t} \\ +\sum Year+{\sum Industry+\epsilon }_{\mathrm{i},\mathrm{t}} \end{gathered}$$

(6)

$$\begin{gathered} {Ges}_{i,t}={\alpha }_0+{\alpha }_1{ESG\_smart}_{i,t}+{\alpha }_2{Controls}_{i,t} \\ +\sum Year+{\sum Industry+\epsilon }_{\mathrm{i},\mathrm{t}} \end{gathered}$$

(7)

where FR_score represents financial risk, and IT_opaque represents corporate information transparency.

In order to test hypothesis H4, whether green technological innovation can strengthen the mitigating effect of corporate ESG performance on corporate financing constraints, we build the intersection-multiplier term ESG_GI = ESG_smart*GI_patent to test the moderating effect of green innovation, and we set up model (8) as follows:

$$\begin{gathered} {FC\_degree}_{i,t}={\alpha }_0+{\alpha }_1{ESG\_smart}_{i,t}+{\alpha }_2{GI\_patent}_{i,t}+{\alpha }_3{ESG\_GI}_{i,t} \\ +{\alpha }_{4}Control{s}_{i,t}+{\sum Year+\sum Industry+\epsilon }_{i,t} \end{gathered}$$

(8)

where GI_patent stands for green innovation, and ESG_GI represents the interaction term between ESG performance and GI_patent, which would be used to test the moderating role that green innovation might exert in the relationship between firms’ ESG performance and financing constraints.

5. Empirical Findings and Analysis

5.1. Descriptive Statistics and Correlation Analysis

As shown in

Table 3. Descriptive statistics.

Variable	N	Mean	SD	Median	Min	Max
FC_degree	11,418	3.945	0.271	3.957	2.975	4.556
ESG_smart	11,418	4.261	1.039	4	1	8
Lev	11,418	0.476	0.189	0.486	0.074	0.857
Growth	11,418	0.119	0.332	0.072	−0.497	2.032
ROA	11,418	0.038	0.050	0.032	−0.11	0.216
OC	11,418	0.347	0.151	0.325	0.088	0.75
ORI	11,418	0.619	0.558	0.433	0.022	2.537
DS	11,418	0.166	0.372	0	0	1
Board	11,418	2.275	0.177	2.303	0	2.944
Indep	11,418	0.375	0.056	0.357	0.308	0.571
SOE	11,418	0.602	0.489	1	0	1
TobinQ	11,418	1.816	1.168	1.427	0.803	7.58
GI_patent	11,418	1.344	1.541	1.099	0	5.71
FR_score	11,418	4.042	4.567	2.586	0.342	30.076
IT_opaque	11,317	0.145	0.106	0.118	0.012	0.561
Ges	11,413	0.016	0.048	0	0	0.315

, the descriptive statistics of each variable, the mean value of financing constraints is 3.945, which is similar to the median 3.957, indicating that the overall data of financing constraints are in line with the normal distribution, and the standard deviation is 0.271, which indicates that the degree of the listed company’s financing constraints is higher and varies greatly; the mean value of the ESG_smart performance is 4.261, which is greater than the median of 4, reflecting that more than half of the companies do not reach the average level, and the maximum value is 8, while the highest ESG rating assignment is 9, indicating that the ESG performance of listed corporations needs to be further improved. Also, as shown in

Table 4. Testing for multicollinearity.

Variable	VIF	1/VIF
FR_score	3.82	0.261631
TobinQ	2.66	0.376151
Top1	2.04	0.490012
Lev	1.97	0.508408
Bal	1.94	0.515317
Board	1.44	0.693588
ROA	1.41	0.709499
Indep	1.38	0.725617
SOE	1.29	0.775363
GI_patent	1.13	0.882464
ESG_smart	1.12	0.896812
Dual	1.11	0.904077
Growth	1.08	0.927794
IT_opaque	1.05	0.927794
Ges	1.01	0.988925
Mean VIF	1.63

, the results of the multicollinearity test show that the variance expansion coefficient of each variable is well below 10, indicating that there is no multicollinearity.

And further through the correlation test, as shown in

Table 5. Correlation analysis.

	FC_Degreee	ESG_Samrt	GI_Patent
FC_degree	1
ESG_smart	−0.1320 ***	1
GI_patent	−0.2171 ***	0.1907 ***	1

Note: *** indicate statistical significance at the 1% level.

, the degree of corporate financing constraints is significantly negatively correlated with both ESG performance and green innovation, which is consistent with the initial findings of our study.

5.2. Benchmark Regression

Table 6. Regression analysis results.

Variable	FC_Degree
ESG_smart	−0.039 ***
	(−8.45)
Controls	Yes
_cons	4.804 ***
	(37.88)
Year	Yes
Industry	Yes
N	11,418
Adj. R2	0.35

Note: *** indicate statistical significance at the 1% level.

shows the regression results of the degree of corporate financing constraints and ESG performance, and the results reveal that the regression coefficient of ESG performance on financing constraints is −0.039, which is significantly negative at the 1% level, indicating that better ESG performance of enterprises can alleviate the degree of corporate financing constraints, that is, the corporations may enhance their financing capability by further strengthening their ESG performance, which proves hypothesis 1.

5.3. Robustness and Endogeneity Test

5.3.1. The Robustness Test

(1)

Replacing the measurement of independent variables

We replace the evaluation of ESG ratings with the measurement of explanatory variables and assign “A~AAA” as 3, “B~BBB” as 2, and “C~CCC” as 1 as the new explanatory variables, i.e., ESG_smart2. “C~CCC” is assigned as 1 as the new explanatory variable ESG_smart2, as shown in column (1) of

Table 7. Robustness checks.

	(1)	(2)	(3)
Variable	Model1: Replace Independent Variables	Model2: Reduce Sample Period	Model3: Replace Dependent Variable
	FC_Degree	FC_Degree	WW
ESG_smartnew	−0.047 ***
	(−5.30)
ESG_sh		−0.033 ***
		(−6.98)
ESG_smart			−0.014 ***
			(−16.77)
Controls	Yes	Yes	Yes
_cons	4.788 ***	4.681 ***	−0.736 ***
	(37.11)	(37.30)	(−34.98)
Year	Yes	Yes	Yes
Industry	Yes	Yes	Yes
N	11,418	7266	11,294
Adj. R2	0.34	0.28	0.59

Note: *** indicate statistical significance at the 1% level.

. After replacing the explanatory variables, corporate financing constraints are still significantly negatively correlated with ESG performance, which supports the robustness of the baseline regression results.

(2)

Reducing the sample period

With the consideration that most of the companies’ operations are affected by the impact of the COVID-19 epidemic starting from 2019, which may have a certain impact on the research results, our study reduces the length of the sample period to 2013–2019 and assigns the ESG_sh to the independent variable. The regression results are shown in Table 7, Column (2). The variable ESG is related to the degree of corporate financing constraints that are still significantly negatively correlated, which is basically consistent with the previous regression results, indicating that the research results are reliable.

(3)

Replace the dependent variable

Drawing on Whited and Wu’s method [65], the explanatory variable is replaced with the WW index to measure that the larger the WW index, the more severe the financing constraints faced by the firm. The regression results are shown in column (3) of Table 7. ESG performance still presents a significant negative correlation with the replacement variable WW index, indicating the robustness of the results.

5.3.2. Endogeneity Test

To address the endogeneity problem, we adopt two approaches in this paper to solve it. Since there might be mutual exogenous relationship between corporate financing constraints and corporate ESG performance, that is, companies with a lower degree of corporate financing constraints are more willing to enhance their corporate ESG performance, and thus they will show a better ESG performance, this paper from the first approach refers to the method from [21,66] and adopts a one-stage lagged ESG performance (L.ESG_smart) as an instrumental variable for a two-stage least squares regression to address the endogeneity of mutual causality, as shown in column (1) of

Table 8. Endogeneity test.

	(1)	(2)	(3)
Variable	Model4: Select Instrumental Variable		Model5: GMM Method
	ESG_Smart	FC_Degree	FC_Degree
L.ESG_smart	0.620 ***
	(0.00923)
ESG_smart		−0.0636 ***
		(0.00760)
L.FC_degree			0.980 ***
			(0.006)
ESG_smart			−0.003 **
			(0.001)
Controls	Yes	Yes	Yes
_cons			1.048 ***
			(0.249)
Year	Yes	Yes	-
Industry	Yes	Yes	-
N	10,377	10,377	10,380
Kleibergen–Paap rk LM statistic		457.853 ***
Kleibergen–Paap rk Wald F statistic		4509.458
Anderson–Rubin Wald test		68.92 ***
AR(2)			0.116
Hansen			0.258

Note: *** and ** indicate statistical significance at the 1% and 5% levels, respectively.

. The results of the first-stage regression show that there is a significant positive correlation between the instrumental variable, L.ESG_smart, and ESG_smart, and also that the Kleibergen-Paap rk LM statistic is 457.853, which is significant at the 1% level, and thus there are no identifiable instrumental variables. Kleibergen–Paap rk Wald F statistic of 4509.458 is much larger than the critical value at the Stock–Yogo weak ID test at the 10% level, so there are no weak instrumental variables, and the instrumental variable selection is reasonably illustrated, as shown in Column (2) of Table 8. The results of the second-stage regression show that the coefficient of ESG_smart is −0.0286, which is still significantly negative at the 1% level, which is consistent with the previous findings, and the results of this paper are reliable. In the second approach to which it refers [67], we use a systematic GMM method to regress the data in this paper, and the results are as shown in column (3) of Table 8. AR(1) is significant, AR(2) is insignificant and passes the test of absence of autocorrelation of the perturbation term, and the Hansen result is insignificant and passes the test of over-identification. Meanwhile, the explanatory variable ESG is still in a significant negative correlation, which is consistent with the previous findings and indicates that the research results are reliable.

5.4. Mechanism Test Results

Table 9. Mechanism test results.

	(1)	(2)	(3)
Variable	FR_Score	IT_Opaque	Ges
ESG_smart	0.134 ***	−0.005 ***	0.002 **
	(3.51)	(−3.60)	(2.17)
_cons	3.705 ***	0.253 ***	0.005
	(3.75)	(7.21)	(0.35)
Controls	Yes	Yes	Yes
Year	Yes	Yes	Yes
Industry	Yes	Yes	Yes
N	11,418	11,317	11,410
Adj. R2	0.76	0.17	0.09

Note: *** and ** indicate statistical significance at the 1% and 5% levels, respectively.

presents the regression results of the mechanism test. Column (1) examines the mechanism of corporate ESG performance to alleviate financing constraints by reducing financial risk. The regression coefficient is 0.134 and passes the significance test at the 1% level; i.e., the better the ESG performance of the enterprise, the larger the value of FR_score is, and the lower the financial risk is, which verifies that the ESG performance of the enterprise can effectively reduce the financial risk of the enterprise and boost the public confidence in the market, which can alleviate financing constraints, and hypothesis 2 has been verified. Column (2) tests the influence mechanism of corporate ESG performance through improving information transparency to alleviate financing constraints, and the results show a significant negative correlation, indicating that the smaller the IT_opaque is, the higher the information transparency is, which suggests that corporate ESG can significantly improve the transparency of corporate information, alleviate the problem of information asymmetry, and then help enterprises to alleviate financing constraints, and hypothesis 3 is verified. Column (3) tests the mechanism of corporate ESG performance and government green subsidies on corporate financing constraints, and the results show a significant positive correlation; i.e., corporate ESG performance can improve the relationship between government and enterprises and obtain more government subsidies, thus alleviating corporate financing constraints, and hypothesis 4 is verified.

5.5. Moderating Effect Test

Based on sustainability goal 9, whether the investment of increasing green innovation can strengthen the mitigating effect of corporate ESG performance on financing constraints, we utilize model (7) to conduct regression test to verify the regression results. As shown in

Table 10. Regression results of moderating effects.

Variable	FC_Degree
ESG_smart	−0.026 ***
	(−6.20)
GI_patent	−0.032 ***
	(−6.27)
ESG_GI	−0.017 ***
	(−5.56)
Controls	Yes
_cons	4.666 ***
	(38.75)
Year	Yes
Industry	Yes
N	11,418
Adj. R2	0.39

Note: *** indicate statistical significance at the 1% level.

, the coefficient of regression of the cross-multiplier term of corporate ESG performance and green innovation is −0.017, which is significantly negatively correlated at the 1% level, indicating that the green innovation enterprise ESG performance has a positive effect in alleviating the degree of financing constraints; i.e., the higher the level of corporate green innovation, the stronger the effect of corporate ESG performance on the degree of financing constraints, and the stronger the validation effect on the degree of financing constraints, which tests hypothesis 5.

5.6. Heterogeneity Analysis

5.6.1. Regional Heterogeneity Analysis

The economic consequences of corporate ESG performance may also be influenced by the economic growth status of the region where the company is located. To further investigate the impact of regional disparities on the relationship between firms’ ESG performance and financing constraints, we conduct group regressions in this paper by dividing the corporations into two groups of samples, i.e., the eastern region and the central-western region, in accordance with the provinces where the corporations are located. The results in columns (1) and (2) of

Table 11. Heterogeneity analysis results.

Variable	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	FC_Degree
					Before		After
	East	Midwest	Before	After	East	Midwest	East	MidWest
ESG_smart	−0.043 ***	−0.022 ***	−0.024 ***	−0.041 ***	−0.030 ***	−0.012	−0.046 ***	−0.023 ***
	(−7.14)	(−4.05)	(−4.59)	(−8.47)	(−4.40)	(−1.56)	(−7.14)	(−4.03)
Fisher’s Permutation Test	0.000		0.000		0.003		0.000
_cons	5.058 ***	4.408 ***	4.313 ***	4.879 ***	4.494 ***	3.961 ***	5.146 ***	4.460 ***
	(28.30)	(27.72)	(39.26)	(36.48)	(29.81)	(26.70)	(27.25)	(26.25)
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Industry	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
N	7663	3752	6228	9339	4171	2057	6270	3069
Adj. R2	0.37	0.51	0.30	0.32	0.33	0.41	0.34	0.46

Note: *** indicate statistical significance at the 1% level. The results presented in columns (3) to (8) are derived from data spanning the period 2009 to 2023.

show that the regression results of both the eastern region and the central-western region are significantly negatively correlated at the 1% level. Also the Fisher’s portfolio test shows that there is a significant difference between the regression coefficients of the two groups, and the absolute value of regression coefficients of the eastern region is higher than that of the central-western region, which indicates that the ESG performance of enterprises in the eastern region has stronger mitigating effects on the financing constraints of the enterprises. In the eastern region, the level of economic development and resource allocation efficiency is relatively better, and the financial regulatory system has been improved, which provides enterprises with a superior financing environment. In addition, the stricter environmental regulations in the eastern region have also prompted the companies in the eastern region to be more concerned about environmental protection, which can stimulate the companies in the eastern region to increase the investment in ESG, and the government’s abundant financial reserves can also provide stronger support for the companies with better ESG performance. The government’s abundant financial surplus can also offer powerful support to companies with better ESG performance. By contrast, the development of the central-western region may face the issue of imbalance and insufficiency; the government may be more concerned about economic development and neglect the environmental regulation of firms. The absence of regulatory pressure on enterprises toward sustainable development may lead to a situation where market participants in the central-western region are not as environmentally conscious as firms in the eastern region, and the mitigating effect of corporate ESG performance on financing constraints would be weakened.

5.6.2. Heterogeneous Effects of New Environmental Protection Law Policies

The new Environmental Protection Law (EPL) of China, which took effect on 1 January 2015, has been described as protecting the environment and promoting sustainable economic and social development. Since then, China’s environmental rule of law construction has entered into the period of the most stringent regulatory enforcement. The new EPL reinforces the responsibility of corporate pollution prevention and protection of the environment, increases the publicity of environmental protection, and raises the public’s awareness of environmental protection, which may affect the inhibitory effect of corporate ESG performance on corporate financing constraints; as a result, we use the grouping of pre- and post-implementation of the new EPL in this paper, and in order to avoid the impact of the imbalance of data spanning time before and after the implementation of the new EPL on the reliability of the results, we adopt the 2009–2023 sample data to analyze the heterogeneity of the policy effects of the new EPL and others, consistent with the previous paper. The results from columns (3) and (4) of Table 11 show that the absolute value of the regression coefficients after the implementation of the new EPL is significantly higher than that before the implementation of the new EPL, indicating that the implementation of the new EPL strengthens the mitigating effect of ESG performance on financing constraints, reflecting the improvement of the social awareness of environmental protection after the implementation of the new EPL, which urges the enterprises to pay attention to the environmental performance, and guides the relevant stakeholders to pay attention to the enterprises’ ESG performance. It helps corporations with high ESG performance to obtain more funds.

5.6.3. Regulatory Disparities in New EPL Policies Under Different Regions

To explore the disparity in the policy’s regulatory effects across different regions, this paper uses the implementation of the new EPL as a subgroup to examine regional heterogeneity. The results from columns (5) to (8) of Table 11 show that before the implementation of the policy, ESG mitigation of financing constraints was significant in the eastern region due to perfect regulation but not in the central-western, and after the implementation, ESG mitigation was strengthened in the eastern region, and a breakthrough was realized in the central-western region from none to some. This suggests that policies in the eastern region have synergistic effects, while policies in the central-western region should establish minimum regulatory standards in order to stimulate ESG. Although ESG in both regions has significantly eased financing constraints since then, there are still differences, reflecting that the benefits of ESG mitigation benefit from institutional convergence brought about by the policies and also are limited by differences in regional economic development.

6. Discussion

This study provides robust evidence that strong ESG performance can significantly alleviate corporate financing constraints in China. Our findings contribute to the literature by demonstrating not only that this relationship exists in a major emerging market, but also how and for whom it is most potent. Following the theoretical framework construction and empirical tests, our study systematically examines the impact of corporate ESG performance (ESG_smart) on alleviating corporate financing constraints (FC_degree). It also explores the role of the ESG_smart and FC_degree mechanisms from the extent of corporate sustainability, i.e., the improvement of corporate financial risk and information transparency, respectively, and analyzes the moderating effect of corporate green innovation on the relationship between ESG_smart and FC_degree based on the SDG9 conceptual background. In this paper, we further analyze the heterogeneity of the relationship between ESG_smart and FC_degree from the geographic perspective of different regions where enterprises are located, as well as before and after the implementation of the new Environmental Protection Law (EPL).

The findings support the idea that ESG is not merely a compliance exercise but a strategic tool that can generate tangible financial value by aligning corporate activities with broader sustainability objectives. Based on the theoretical analysis, our empirical test starts by proving a significant negative relationship between ESG_smart and FC_degree, in which better corporate ESG performance effectively reduces the risk of corporate financing constraints, which is similar to the results of the majority of studies [68]. However, we note that although scholars have realized that corporate financing constraints cannot be separated from corporate ESG performance, it is also found that there may be differences in this positive feedback effect. Considering sustainable development demands, there are variations in the role of corporate ESG performance in the management of financial risk, information transparency, and government subsidies in mitigating corporate financing constraints. Based on the strategic requirements of sustainable development, a well-regulated environment is crucial to the sustainable development of companies. The authors of [11] indicated that ESG performance can effectively enhance the information transparency of companies, and companies with higher ESG ratings are more likely to display a full range of financial and non-financial information to the public and investors. This not only reduces the information asymmetry due to market inefficiency but also enhances investors’ access to full information on companies and has a positive effect on corporate financing constraints. This also provides a valid explanation for our findings. Within the context of sustainable development, there is a positive feedback effect between the ESG performance of enterprises and the attention of government departments, the public, investors, and other stakeholders. Companies with high ratings are more likely to obtain government green subsidies. As an important policy tool, green subsidies can not only provide funds for green technology research and development and production transformation but also strengthen the green development orientation through policy signals, effectively incentivizing enterprises to increase investment in green innovation. Also, a positive government–enterprise relationship conveys a positive signal to social investors that the enterprise’s operation is standardized, and its development direction is in line with the policy orientation, which enhances investor trust, reduces the difficulty of financing, and eases the financing constraints [60]. The sustainable development goals drive enterprises to strengthen the disclosure of financial and non-financial information, and the positive effect of good ESG performance of enterprises subject to social supervision can be strengthened [49], which will help to enhance the financial stability and risk control capacity and will also play a positive role in alleviating the financing constraints of enterprises effectively, which is consistent with the view of [51].

The mechanism analysis confirms these theoretical channels. We find that better ESG performance is associated with lower perceived financial risk (H2), greater information transparency (H3), and access to government green subsidies (H4), consistent with prior work. A novel finding that ESG performance also leads to higher credit ratings provides a direct and powerful link between non-financial performance and the cost of debt, a channel that deserves further exploration. This suggests that credit rating agencies in China are increasingly incorporating ESG factors into their risk assessments, reflecting a global trend. From the perspective of SDG 9, “Industry, Innovation, and Infrastructure”, the concept of green innovation and sustainable development has been increasingly emphasized by the public, which has led to an additional consideration of the social and environmental benefits of enterprises in the financing criteria of society. The impact of corporate ESG performance on corporate financing constraints inevitably increases the interference of whether or not there is green innovation investment, which means that enterprises with good ESG performance will take the initiative to increase their investment in green innovation due to the development requirements of the Sustainable Development Goal 9, to realize the ESG performance of the enterprise under the regulation of the high green innovation input and output efficiency, which will attract more social investment and can effectively inhibit the financing constraints of the enterprise, which coincides with [21]. The input of green innovation can effectively stimulate enterprises to continuously research and develop innovations and improve the efficiency of capital utilization and better improve the growth efficiency of the green economy. The moderating utility of green innovation in mitigating the financing constraints that companies may face in regional technological development and industrial upgrading can be maximized by those companies that are able to appeal to the innovative technologies required for modern development and that have a good ESG performance.

Based on the regional heterogeneity, we further analyze the inhibitory effect of ESG_smart on FC_degree for firms located in the eastern region and the central-western region, and we found that compared with firms in the central-western region, firms located in the eastern region have a stronger effect on mitigating FC_degree, which shows that firms in different regions that want to utilize the positive effect of ESG_smart on FC_degree should formulate different strategic plans according to the local environment and the enterprises’ own development, which cannot be directly applied [69]. Meanwhile, the introduction of the new EPL can also better highlight the positive effect of ESG_smart on FC_degree. In summary, our study enriches the theoretical research on the impact of ESG_smart on FC_degree and expands the development path of ESG_smart on mitigating FC_degree from the sustainable development framework.

Our findings correspond to the ongoing evolution of China’s ESG landscape. The recent rollout of the Corporate Sustainability Disclosure Standards (CSDS), which draw from international frameworks such as the Task Force on Climate-Related Financial Disclosures (TCFD) and the EU Corporate Sustainability Reporting Directive (CSRD), signals a clear regulatory push towards higher quality and more standardized disclosure. The results suggest that such policies are not just a regulatory burden but can create real economic value for firms that comply substantively, by improving their access to capital.

7. Conclusions and Implications

Based on sustainable goals and a “dual-carbon” strategy, the ESG performance of enterprises has become the priority of all industries. This work takes the data of China’s A-share listed companies from 2013 to 2023 as the research object, analyzes the impact of ESG performance on corporate financing constraints and the influence mechanism therein, and further explores the role played by green innovation in this process. The study shows the following: (1) High ESG performance could significantly alleviate the degree of financing constraints. (2) Corporate ESG performance can help reduce corporate financing constraints by effectively minimizing corporate financial risks, improving information transparency, and gaining government green subsidies. (3) Green innovation has a significant moderating effect on the relationship between corporate ESG performance and financing constraints and can strengthen the mitigating effect of corporate ESG performance on financing constraints. (4) Heterogeneity analysis finds that the mitigating effect of corporate ESG performance on financing constraints is better for enterprises in the eastern region and after the implementation of the new EPL. And also, there are differences in regulatory effects before and after the implementation of policies under the new EPL in different regions, which benefit from the institutional convergence brought about by the policies and are also limited by differences in regional economic development.

According to the conclusion of the above research, this paper reaches the following implications: Firstly, corporations are required to strengthen their understanding and research of ESG concepts and ensure that ESG concepts permeate all aspects of corporate operations. In this way, it helps to establish a good reputation of actively accepting ESG responsibility to the public which can attract the attention of relevant stakeholders to solve the problem of financing constraints and actively responds to the call for green development, increases the investment in green technology research and development, and also improves the level of green innovation, to play the leveraging role of green innovation, enhance the ESG performance of the enterprise to reduce the effect of financing constraints, and promote the realization of the enterprise’s sustainable development. Secondly, enterprises can combine digital technology to improve the financial risk early warning mechanism, improve the risk management system to reduce financial risks and enhance financial stability, and further improve the information disclosure mechanism to increase information transparency and provide more information for relevant stakeholders to enhance the trust of relevant stakeholders to alleviate financing constraints. Thirdly, the government can provide certain green subsidies, such as tax concessions and loans, to enterprises with better ESG performance by formulating and optimizing the legal mechanism on ESG performance, so as to effectively drive enterprises to improve their own ESG performance. In addition, corporations must raise environmental awareness, reinforce the publicity of ESG concepts, and guide investors to pay attention to the ESG performance of enterprises, which can not only help enterprises with better ESG performance to acquire more financial resources and overcome the financing constraints but also force corporations to pay attention to environmental performance, increase the investment in ESG, and promote the construction of the ESG system, which can contribute to the realization of the sustainable development of the society. Finally, the new EPL should be a “basic tool” to bridge the gap between regional systems, while taking into account the differences in the stages of regional development. The combination of “filling shortcomings” and “promoting synergies” should be used to promote the effective utilization of ESG in different regions.

Future research could leverage artificial intelligence (AI), machine learning (ML), and novel data sources to create more dynamic and objective measures of ESG performance. Also, as ESG standards diverge globally (e.g., the EU’s prescriptive CSRD versus the US’s more market-driven approach), future work could investigate how Chinese multinational corporations are navigating these conflicting demands. As China continues its transition towards a sustainable development model, a firm ESG performance will only become more critical to its financial health and long-term success. The present work shows that credible ESG commitment is rewarded with better access to capital, indicating that a synergy between sustainable practices and financial strategy is beneficial.