Corporate Environmental Disclosure, Corporate Governance, and the Cost of Equity: Evidence from Pharmaceutical Listed Companies in China

Abstract

As societal demand for sustainable development intensifies, corporate environmental performance has become a key consideration for investors in assessing risk and value. This study investigates the impact of corporate environmental disclosure on the cost of equity and the moderating role of corporate governance, using data from Chinese pharmaceutical listed companies between 2018 and 2022. Employing a firm- and time-fixed effects regression model, the results show that enhanced corporate environmental disclosure significantly reduces the cost of equity. Furthermore, corporate governance positively moderates this relationship, indicating that firms with more effective corporate governance experience a greater reduction in cost of equity from the enhanced disclosure. Robustness checks using a two-step system generalized method of moments and propensity score matching confirm these findings. This study provides empirical evidence on how corporate environmental disclosure improves capital market resource accessibility and underscores the critical role of corporate governance, offering practical implications for managers, investors, and policymakers.

1. Introduction

With the rapid development of China’s economy, environmental pollution has become increasingly severe. As the primary consumers of resources and major contributors to pollution, enterprises are facing growing environmental regulatory pressures from the government, the public, and capital markets. In response, China has progressively established a regulatory framework for corporate environmental disclosure (ED). According to the Guidelines for the Contents and Formats of Information Disclosure by Companies Offering Securities to the Public No. 2-Contents and Formats of Annual Reports (2017 Revision), the China Securities Regulatory Commission (CSRC) mandated partial compulsory disclosure for key polluting listed firms starting from 2018, marking a pivotal shift from voluntary to partly mandatory ED in China. This transition establishes a baseline level of disclosure but does not ensure uniform disclosure quality, as the guidelines provide limited guidance on the depth, comparability, and verification of disclosed information. Consequently, environmental disclosure quality remains uneven across firms, with some companies engaging in selective disclosure that conceals unfavorable environmental performance, thereby undermining information transparency and credibility, as documented in prior research on environmental disclosure practices in China [1].

The pharmaceutical industry is explicitly designated by CSRC as one of the heavily polluting sectors. Unlike many traditional heavy-polluting industries, pharmaceutical firms are characterized by intensive research and development activities, long innovation cycles, and heightened regulatory uncertainty related to both product safety and environmental compliance. These features exacerbate information asymmetry and increase firms’ dependence on external equity financing. With the intensifying pressures of population aging and public health demands, the industry has become increasingly reliant on capital markets [2]. Accordingly, findings derived from broad cross-industry samples may not be directly generalizable to the pharmaceutical context and may suffer from attenuation bias arising from heterogeneous disclosure incentives and regulatory exposures, making industry-specific evidence particularly relevant. Against this backdrop, whether pharmaceutical firms can reduce their cost of equity (COE) by enhancing ED and thereby strengthening investor confidence has become a critical issue that warrants further investigation.

Existing studies have shown that ED can improve corporate transparency, reduce information asymmetry, and foster investor trust, thereby lowering financing costs [3]. However, empirical evidence on the relationship between ED and COE remains mixed, with findings ranging from significantly negative effects to weak or insignificant associations. These inconsistencies indicate that the capital market consequences of ED are not automatic, but are likely contingent on institutional settings and firm-level characteristics, particularly the perceived credibility of disclosed information [4]. When environmental disclosure lacks credibility, its signaling effect in capital markets may be substantially weakened. Corporate governance plays a critical role in enhancing disclosure credibility [5], which helps limit managerial opportunism and strengthen monitoring effectiveness. Accordingly, corporate governance is expected to condition the extent to which environmental disclosure is reflected in firms’ financing costs, as under a partial mandatory disclosure regime, signaling value arises not from the act of disclosure itself, but from variations in disclosure quality and credibility beyond regulatory minima.

While prior research has examined the impact of ED on COE, several important research gaps remain. First, some existing evidence is based on broad firm samples or pooled analyses across multiple heavily polluting industries (e.g., Refs. [6,7]), and single-industry evidence for the pharmaceutical sector, particularly under the post-2018 partial mandatory disclosure regime, remains limited. Second, the ED-COE relationship is not yet settled in the literature, with findings ranging from significant negative effects (e.g., Ref. [7]) to non-significant relationships (e.g., Ref. [8]), highlighting the need for further context-specific validation. Third, prior studies often examine individual corporate governance variables (e.g., board size, independence, or ownership structure) in isolation, which may not capture overall governance effectiveness. As a result, prior evidence provides limited insight into whether overall governance effectiveness, rather than isolated governance mechanisms, systematically conditions the credibility channel through which environmental disclosure affects equity financing costs, leaving the moderating role of comprehensive corporate governance mechanisms insufficiently understood.

To address these gaps, this study focuses on Chinese listed pharmaceutical companies from 2018 to 2022 and investigates the impact of ED on the COE, and further explores whether corporate governance plays a strengthening role in this relationship. Given the post-2018 focus of the sample period, this study does not seek to identify the causal effect of the mandatory disclosure policy, but examines within-period variation in ED and COE. Drawing on signaling theory and agency theory, this study posits that ED serves as a positive signal of environmental compliance and risk management capabilities, while corporate governance enhances the credibility of this signal, thereby increasing the effectiveness of disclosure in capital markets.

This study provides context-specific evidence on the relationship between ED and COE by focusing on Chinese listed pharmaceutical firms under the post-2018 disclosure regime. By examining a highly regulated and environmentally sensitive industry characterized by elevated information asymmetry and financing dependence, the study helps clarify when and how environmental disclosure is reflected in equity financing costs. Methodologically, the analysis adopts a rigorous empirical design that combines two-way fixed-effects (FE) models, system generalized method of moments (GMM) estimation, and propensity score matching (PSM) to enhance robustness. In addition, the study employs a composite corporate governance index and the Hou–van Dijk–Zhang (HVZ) model to improve the measurement of governance effectiveness and COE in the Chinese capital market context.

This research also offers practical implications. For firms, understanding how ED is associated with lower COE and how corporate governance conditions this relationship can help improve governance quality and information transparency, thereby facilitating more effective engagement with capital markets. For regulators, the findings provide context-specific evidence that may inform the refinement of disclosure requirements and the design of governance-oriented mechanisms aimed at improving the credibility and comparability of ED, thereby supporting the development of green finance initiatives.

The remainder of the paper is organized as follows: Section 2 reviews the relevant literature and develops the research hypotheses. Section 3 describes the research design, covering sample selection, data sources, variable measurement, and model specification. Section 4 reports and interprets the empirical findings, including baseline estimations and robustness analyses. Section 5 concludes with key findings, theoretical contributions, policy implications, study limitations, and directions for future research.

2. Literature Review and Hypothesis Development

2.1. Literature Review

In recent years, the impact of ED on capital market performance, particularly in relation to financing costs, has attracted growing academic attention. Existing studies generally suggest that ED helps mitigate information asymmetry, reduce investors’ perceptions of environmental risk, and send positive signals about firms’ sustainability, thereby lowering the expected return required by investors and ultimately reducing the COE [7,9]. However, empirical findings differ across institutional contexts, industry characteristics, and disclosure regimes, indicating that the capital market effects of ED are context-dependent and require careful interpretation.

International studies focusing on environmental responsibility and disclosure provide evidence of a negative association between environmental-related practices and the COE in several settings. For example, El Ghoul et al. [10], using panel data from manufacturing firms across 30 countries, found that corporate environmental responsibility helps reduce environmental risk exposure and optimizes investor preferences, thus lowering equity financing costs. In an emerging market context, Atasel et al. [11] found that voluntary ED by 39 non-financial firms listed in Turkey helped alleviate investor concerns and reputation-related risk premiums, leading to a lower COE. Similarly, Garzón-Jiménez and Zorio-Grima [9], drawing on data from 27 countries and 12 sectors in the Morgan Stanley Capital International Emerging Markets Index, reported that firms that actively disclosed environmental information to meet the expectations of key stakeholders could prevent reputational losses and conflict risks, reduce risk premiums, and consequently lower COE. Nevertheless, whether such associations hold consistently across industries remains subject to debate.

Industry-specific studies reveal more pronounced heterogeneity. Tarulli et al. [12], based on 73 agri-food companies across 30 countries, found no significant ED-COE relationship. Ime et al. [8], using a sample of seven listed pharmaceutical companies in Nigeria, reported a statistically insignificant positive ED-COE relationship. The authors attributed this to a limited sample size, low disclosure levels, and insufficient variable variability, which reduced the statistical power of their tests. They also suggested that in some emerging markets, capital markets may not fully recognize the value of environmental information, with investors placing greater emphasis on other dimensions of corporate social responsibility, such as employee welfare and community contributions.

In the Chinese context, empirical research on the ED–COE relationship has also produced mixed results. On the one hand, several studies support the view that ED reduces COE by mitigating information asymmetry and conveying positive signals, a mechanism explained by Hughes et al. [13], who argue that investors typically demand higher risk premiums under conditions of information asymmetry, thereby increasing the cost of capital. Specifically, Li and Zhang [14] and Yao and Liang [15], using samples from China’s marine and manufacturing sectors, respectively, found that enhanced ED helped reduce perceived risk and information asymmetry, thereby lowering the expected rate of return. Moreover, Lv et al. [7], focusing on heavily polluting industries, showed that high-quality ED serves as a costly and credible signal of sound environmental management and sustainable cash flows, which reduces reputational risks and, consequently, COE. In addition, Li and Liu [16], drawing on a large sample of listed firms in China, integrated perspectives from risk management, asymmetric information, and signaling theory, and demonstrated that under multi-stakeholder pressure and regulatory frameworks, ED significantly reduced COE, particularly among large and state-owned enterprises. Taken together, these findings suggest that the ED-COE relationship may be influenced by the credibility and informational content of the disclosed information.

On the other hand, some studies failed to identify a consistent cost-reducing impact of ED. For instance, Yan et al. [17], after constructing an ED index for Chinese firms, found no significant overall ED-COE relationship. They further observed that while ED was associated with lower costs in non-polluting industries, the opposite held in highly polluting sectors, where enhanced ED may heighten investor concerns about environmental risks. Similarly, Tian et al. [6], employing a difference-in-differences approach based on the 2010 mandatory disclosure regulation, reported that, following the policy implementation, ED did not significantly reduce COE. They attributed this outcome to the high degree of content homogeneity in corporate disclosures, which undermined their signaling effectiveness.

Collectively, these findings suggest that the capital market consequences of ED are sensitive to the informational content and credibility of disclosed information, rather than the mere presence of disclosure. Supporting this interpretation, Vitolla et al. [18] documented that higher integrated reporting quality is associated with a lower COE, indicating that the quality of broader nonfinancial reporting, beyond stand-alone environmental disclosure, may influence investors’ required returns. This evidence reinforces the view that disclosure credibility, rather than disclosure per se, is central to understanding capital market responses to ED.

To explain these inconsistencies, some scholars have turned their attention to corporate governance as a potential moderating factor influencing the financial effects of ED. Iqbal et al. [19], studying integrated reporting quality, found that effective corporate governance could mitigate agency conflicts, enhance transparency and credibility, and thus amplify the risk-mitigating effect of disclosures, which may strengthen capital market responses to nonfinancial information and support more favorable financing outcomes. From an international reporting perspective, sustainability reporting frameworks such as the Global Reporting Initiative (GRI) aim to enhance the comparability and credibility of environmental and social disclosures, and governance structures may influence firms’ adoption and implementation of such frameworks. Such frameworks, therefore, form an important institutional backdrop for understanding how governance affects the credibility of ED. Consistent with this view, Fuente et al. [20] showed that board characteristics and governance mechanisms are associated with sustainability reporting practices aligned with GRI guidelines. This suggests that corporate governance may shape how environmental information is perceived by capital market participants.

Several studies have already explored this possibility. Jafar et al. [21], using Indonesian listed companies, found that while Environmental, Social and Governance (ESG) disclosures generally reduced COE, the negative relationship was weakened in firms with higher board independence, larger board size, and greater gender diversity. This implies that an effective governance structure may partially substitute for the risk-reducing function of ESG disclosures. Additionally, Kiran et al. [22], based on data from Next-11 emerging economies, found an inverted U-shaped moderating effect of managerial ownership: moderate ownership enhanced the credibility of ESG signals and lowered COE, whereas excessive or insufficient ownership reduced incentive alignment and information reliability. In China, Meng et al. [23] showed that high-quality internal controls significantly strengthened the ability of ED to ease financing constraints by enhancing transparency and investor confidence.

In summary, while prior studies provide valuable insights into the ED-COE relationship, the existing evidence remains mixed and context-dependent. First, much of the existing literature focuses on multi-country samples or broad industrial sectors, while empirical evidence remains relatively limited for specific industries operating under evolving regulatory environments, such as China’s pharmaceutical sector following the post-2018 partial mandatory disclosure regime. Second, although prior studies examine individual corporate governance characteristics, fewer studies adopt composite measures that capture overall governance effectiveness. As a result, it remains unclear whether overall governance effectiveness, rather than isolated governance mechanisms, plays a consistent role in shaping the credibility of ED in capital markets.

Against this backdrop, this study focuses on listed pharmaceutical firms in China, examining the post-2018 regulatory context. In addition to investigating the direct relationship between ED and the COE, we construct a comprehensive corporate governance index using PCA and explore its moderating role in this relationship. By focusing on a specific industry and regulatory setting, this study seeks to provide more context-specific empirical evidence on the ED-COE relationship and the role of corporate governance, with implications that may be informative for future research and regulatory discussions.

2.2. Theoretical Framework and Hypotheses Development

In capital markets, a significant information asymmetry exists between firms and external investors [24]. Firms possess internal information about their operations and strategic direction, while investors and creditors rely primarily on publicly disclosed information to make informed decisions. Within this context, signaling theory [25] offers a useful theoretical lens, suggesting that information-advantaged parties (e.g., firms) may transmit costly and observable signals to external stakeholders (e.g., investors) to convey firm quality, thereby mitigating adverse selection and moral hazard and improving the efficiency of resource allocation.

ED constitutes one such signaling behavior. On the one hand, the disclosure of environmental information is inherently costly. Firms with favorable environmental performance and corporate social responsibility are more likely to voluntarily disclose their environmental initiatives and achievements to signal their high quality to potential investors, thereby enhancing market recognition and investor trust [7]. In contrast, poorly performing firms often lack the resources or willingness to bear the costs associated with high-quality ED, making it difficult for them to mimic such signals. On the other hand, the effectiveness of signaling is also reflected in a firm’s initiative and compliance in demonstrating its environmental responsibility, which helps shape a positive corporate reputation [26]. Such reputational effects may influence how firms are perceived by market participants and enhance investor confidence, without necessarily implying an automatic or direct reduction in financing costs.

Consistent with this reasoning, prior empirical studies document associations between ED and COE across different institutional settings [7,9,11,15,16]. However, as discussed in the preceding literature review, these associations are not uniform across contexts. Accordingly, the following hypothesis is proposed:

H1: 

Corporate environmental disclosure is negatively associated with the cost of equity.

However, under the current institutional context in China, issues such as selective disclosure [1] may weaken the signaling effectiveness of ED. In a partial mandatory disclosure regime, the mere act of disclosure may not be sufficient to convey firm quality, as investors may question the credibility and informational content of reported environmental information. From the perspective of agency theory [27], corporate governance serves as a key institutional mechanism for addressing information asymmetry, with one of its central roles being to enhance the credibility and reliability of corporate disclosures. Specifically, prior research showed that corporate governance mechanisms, such as board and audit committee oversight, are positively associated with disclosure quality and the use of credibility-enhancing mechanisms [28]. Through stronger oversight and expertise-based governance arrangements, firms may improve the transparency and credibility of disclosed information.

Given the limited empirical evidence focusing explicitly on the moderating role of corporate governance in the ED-COE relationship, some scholars have expanded the discussion through a broader ESG perspective. For example, Jafar et al. [21] found that board independence and board size significantly moderate the relationship between ESG disclosure and capital market responses. Although ESG encompasses social and governance dimensions, environmental disclosure constitutes a central component of ESG reporting, suggesting that governance mechanisms influencing ESG credibility may also be relevant for understanding the ED-COE relationship. Furthermore, Meng et al. [23] demonstrated that, in the Chinese context, the quality of internal controls significantly strengthens the alleviating effect of high-quality ED on financing constraints by improving information transparency and enhancing investor trust, indicating that governance-related mechanisms can condition the financial consequences of ED.

It is important to note that corporate governance is not merely the function of individual attributes but reflects the comprehensive institutional arrangement of governance practices [29]. A more effective governance system can enhance the credibility of disclosed information and strengthen its signaling value to investors. Accordingly, the following hypothesis is proposed:

H2: 

Corporate governance has a positive moderating effect on the impact of corporate environmental disclosure on the cost of equity.

3. Research Design

3.1. Sample and Data Considerations

To test the proposed hypotheses within a context characterized by both significant environmental impact and financing intensity, this study focuses on the pharmaceutical industry in China. The pharmaceutical industry is designated by the CSRC as a heavily polluting sector and is characterized by high information asymmetry and strong reliance on external equity financing, making it a suitable setting to examine how ED is reflected in COE while mitigating heterogeneity that may arise in cross-industry samples.

The initial sample comprises all listed pharmaceutical companies (Industry Code C27, as defined by the Guidelines for Industry Classification of Listed Companies) that were listed on the main boards of the Shanghai and Shenzhen Stock Exchanges between 2018 and 2022. The sample period starts in 2018, when partial mandatory environmental disclosure was introduced for key polluting firms in China; accordingly, this study focuses on within-period variation in disclosure quality rather than evaluating the causal effect of the policy itself.

Following prior studies [7,30], firms designated as ST or *ST, as well as those with missing values in key variables, were excluded to mitigate the influence of potential noise and enhance the comparability of observations. Specifically, firms designated as ST or *ST, referring to listed companies subject to special regulatory treatment due to consecutive losses, are excluded to mitigate potential bias arising from abnormal financial conditions. (In the Chinese capital market, ST firms refer to listed companies that have reported losses for two consecutive years and are placed under special regulatory treatment, while *ST firms have incurred losses for three consecutive years and face heightened delisting risk. These firms are typically under financial distress and subject to intensified regulatory scrutiny, which may affect their disclosure behavior and financing conditions.) After applying these screening criteria, the final sample consists of 308 listed pharmaceutical firms in China.

Accordingly, an unbalanced panel dataset was constructed for the period 2018–2022, yielding a total of 1042 firm-year observations. The unbalanced structure of the panel reflects several institutional and data-related factors, including time-varying industry classification under CSRC guidelines, changes in firm listing status (entry and exit) during the sample period, and the exclusion of firm-year observations with missing values for key variables required for empirical analysis. This structure does not affect the validity of the fixed-effects model or subsequent robustness estimations. To minimize the influence of outliers, all continuous variables were winsorized at the 1% and 99% levels.

3.2. Measures

3.2.1. Dependent Variable

The COE represents the minimum required rate of return expected by shareholders after assessing the firm’s operational risks and profitability prospects. In terms of estimation methods, ex ante models are generally considered less accurate than ex post models [31,32]. Within the Chinese capital market, empirical studies have shown that implied cost of equity models exhibit heterogeneous performance across institutional settings. In particular, evidence from China suggests that the PEG model, originally proposed by Easton [33], provides an effective reflection of market risks and firm growth expectations compared to alternative implied COE models [34], and has been adopted as a baseline specification in recent China-based studies [35]. Therefore, this study adopted the PEG model to estimate COE.

$${COE}_t=\sqrt{{\displaystyle \frac{({eps}_{t+2}-{eps}_{t+1})}{P_t}}}$$

(1)

In this formula, ${COE}_t$ represents the cost of equity of the company in period t. ${eps}_{t+2}$2 denotes the forecasted value of earnings per share at the end of period t + 2, while ${eps}_{t+1}$ represents the forecasted value of earnings per share at the end of period t + 1. $P_t$ indicates the company’s stock price at the end of period t. Since the model assumes ${eps}_{t+2}-{eps}_{t+1}>0$, observations with ${eps}_{t+2}\le {eps}_{t+1}$ are excluded to ensure consistency with the model’s underlying premise.

In the PEG model, forecasted earnings serve as the core input. However, analyst earnings forecasts are not suitable for this study’s context. Due to the relatively late development of the analyst industry in China, a substantial proportion of listed firms, particularly small-scale or financially distressed ones, receive limited or no analyst coverage. Furthermore, analysts seldom provide forecasts beyond a two-year horizon [34]. To address these limitations, recent studies have adopted cross-sectional regression-based forecasting models to generate firm-level earnings expectations, which provide broader coverage and mitigate sample selection bias associated with analyst forecasts [36,37].

Hou et al. [36] extended earlier statistical forecasting models and proposed the hybrid cross-sectional regression model, known as the HVZ model. The HVZ model addresses the data availability issue by generating earnings forecasts even in the absence of analyst coverage, and it enables longer-horizon earnings projections beyond the typical 1–2-year analyst forecast window. According to empirical tests by Zou et al. [38], the HVZ model demonstrates superior performance in terms of forecast coverage, forecast bias, and earnings response coefficients, which contribute to more reliable implied COE estimates for Chinese listed firms. Accordingly, this study applied the HVZ model to generate firm-level forecasted earnings for use in the PEG-based COE estimation. The HVZ model is specified as follows:

$${FE}_{i,t+n}={\alpha }_0+{\alpha }_1{A}_{i,t}+{\alpha }_2{D}_{i,t}+{\alpha }_{3}D{D}_{i,t}+{\alpha }_4{E}_{i,t}+{\alpha }_{5}Neg{E}_{i,t}+{\alpha }_{6}A{C}_{i,t}+{\epsilon }_{i,t+n}$$

(2)

In this formula, ${FE}_{i,t+n}$ represents the forecasted earnings before extraordinary items of company i in year t + n; n represents the future forecasting year (s). $A_{i,t}$ denotes the total assets of company i in year t. $D_{i,t}$ represents the dividends paid by company i in year t. $D{D}_{i,t}$ represents the dividend dummy variable, taking the value of 1 if company i pays dividends in year t, otherwise 0. $E_{i,t}$ denotes the net profit before extraordinary items of company i in year t. $Neg{E}_{i,t}$ represents the earnings dummy variable, taking the value of 1 if company i has negative earnings in year t, otherwise 0. $A{C}_{i,t}$ represents the accrued earnings of company i in year t. Following Hou et al. [36], accrued earnings are calculated using the cash flow method, defined as net profit minus cash flow from operating activities.

3.2.2. Independent Variable

The term environmental refers to the potential impact of an organization’s operations on the natural environment [39]. ED refers to the process by which firms publicly communicate their environmental performance and the environmental responsibilities they are expected to fulfill, through various reporting channels. This study uses an ED score to measure the quality of the ED. To avoid the subjectivity associated with manual classification and scoring by researchers, and to ensure objectivity and replicability, the scoring system is based on the standardized indicators from the China Environmental Research Database provided by the China Stock Market Accounting Research (CSMAR) database, following the approach of Chen et al. [40].

The scoring process is as follows: First, each pharmaceutical listed company is evaluated using the environmental disclosure criteria outlined in the CSMAR database (see Appendix A for details). Second, each firm is assigned a total raw ED score by summing the values of 26 specific disclosure indicators. The minimum possible score is 0, and the maximum is 38. Finally, the raw score is standardized to obtain a disclosure index, calculated as: ED score = Actual Score of Firm/Maximum Score.

3.2.3. Moderating Variable

Corporate governance originates from the agency problem and refers to a set of institutional arrangements designed to coordinate the economic relationships among various stakeholders, including shareholders, boards of directors, creditors, managers, and employees. As such, analyzing a single corporate governance variable may not adequately capture the overall governance quality of a firm. Consequently, multiple corporate governance attributes are increasingly incorporated into the same research framework. However, this practice may lead to multicollinearity problems, which could undermine the reliability of regression results. To address this issue, PCA has been widely adopted to combine related variables into a comprehensive index, thereby reducing dimensionality [41], mitigating multicollinearity, and minimizing measurement errors [42].

Following the approach of Wang and Sun [43] and considering the institutional context of China, this study constructs a composite corporate governance index using PCA. The selected indicators are chosen based on their theoretical relevance and their ability to jointly capture key dimensions of internal governance mechanisms in the context of Chinese listed firms, rather than the effect of any single governance attribute. Specifically, nine variables across three dimensions are selected for analysis. First, under the dimension of ownership structure, four indicators are used: ownership balance, institutional shareholding ratio, managerial shareholding ratio, and ownership type (state vs. non-state). Second, for the board and supervisory structure, the selected indicators include the proportion of independent directors, board size, and supervisory board size. Third, regarding executive characteristics, CEO duality (whether the CEO also serves as chairman) and executive compensation are included.

PCA is applied to these nine variables based on the pooled sample to construct the index. The KMO test yields a value of 0.603, and Bartlett’s test of sphericity is significant at p < 0.001, indicating that the data meet the minimum adequacy requirements for factor extraction, as indicated in the methodological literature (e.g., Ref. [44]). While some guidelines suggest improving the KMO statistic by reducing partial correlations, we retain all corporate governance variables to preserve their theoretical relevance and accordingly use PCA for dimensionality reduction while interpreting the resulting components with appropriate caution. In addition, following the Kaiser criterion [45] as a commonly adopted heuristic, three principal components with eigenvalues greater than one were extracted, jointly explaining 56.40% of the total variance. The corresponding eigenvalues and scree plot are reported in Appendix B. A weighted average of the extracted components, based on their respective variance contributions, is then computed to generate the composite corporate governance score, consistent with prior studies employing PCA-based governance indices [46].

3.2.4. Control Variables

When examining the impact of ED on the COE, this study selects control variables based on prior literature, data availability, and the specific characteristics of the Chinese market. The selected control variables include profitability, financial leverage, asset turnover, operating cash flow to total assets ratio, book-to-market ratio, beta coefficient, and quick ratio. Definitions and measurements of the key variables are presented in

Table 1. The summary of variables.

Variables	Acronym	Definition	Measurement	Source
Cost of Equity	COE	The minimum required rate of return from shareholders	Calculated using the PEG model (Formula 1)	CSMAR Database
Corporate Environmental Disclosure	ED	Corporate Environmental Disclosure Index	Standardized Corporate Environmental Disclosure Score
Corporate Governance	CG	Corporate Governance Index	Included nine variables and constructed by PCA
Firm Profitability	ROE	A company’s ability to generate profits	Net profit divided by average equity
Financial Leverage	LEV	Asset liability ratio	Total liabilities divided by total assets
Asset Turnover Ratio	ATO	Operational efficiency in generating revenue from assets	Operating revenue divided by average total assets
Operating Cash Flow to Total Assets Ratio	CF	Operating cash flow scaled by total assets, reflecting firms’ operating cash-generating ability	Net cash flow from operating activities divided by total assets at the end of the period
Book-to-Market Ratio	BM	The ratio of book value to its total market value	Book value divided by the total market value
Beta Coefficient	BETA	The systematic risk of a company	ln (250 × annual standard deviation of daily individual stock returns of listed companies)
Quick Ratio	QUICK	Ratio of quick assets to current liabilities	(current assets minus inventories) divided by current liabilities

.

3.3. Model Specification

First, after determining the optimal model through the F-test, Breusch–Pagan test, and Hausman test, a FE model is employed as the baseline regression framework. Following Meng et al. [23], both firm fixed effects and year fixed effects are controlled to eliminate the influence of time-invariant unobservable heterogeneity and common time trends. Additionally, to address potential heteroskedasticity issues, robust standard errors clustered at the firm level are applied [47].

Second, to address potential endogeneity concerns in the static two-way FE framework, the system GMM estimator is adopted as a robustness check, employing lagged dependent variables as instruments to control for dynamic endogeneity and unobserved individual effects [10]. In addition, following Lv et al. [7], PSM is applied as an additional robustness check to address potential sample selection bias, thereby testing the stability of the estimated effects of ED and the moderating role of corporate governance.

To test Hypothesis H1 proposed in this chapter, Model 1 was constructed to examine the impact of ED on the COE among pharmaceutical listed firms. Furthermore, to test Hypothesis H2, Model 2 was developed to investigate the moderating effect of corporate governance on the ED-COE relationship among these firms.

$$\mathrm{C}\mathrm{O}\mathrm{E}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1\mathrm{E}\mathrm{D}+\sum {\mathsf{\alpha }}_2\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}\mathrm{s}+\mathsf{\epsilon }$$

(3)

$$\mathrm{C}\mathrm{O}\mathrm{E}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1\mathrm{E}\mathrm{D}+{\mathsf{\alpha }}_2\mathrm{E}\mathrm{D}\mathrm{C}\mathrm{G}+{\mathsf{\alpha }}_3\mathrm{C}\mathrm{G}+\sum {\mathsf{\alpha }}_4\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}\mathrm{s}+\mathsf{\epsilon }$$

(4)

COE represents the cost of equity, ED represents corporate environmental disclosure, EDCG represents the standardized interaction term between ED and CG, CG represents the comprehensive corporate governance index, and ε represents the random error term. Controls represent the control variables, including firm profitability (ROE), financial leverage (LEV), book-to-market ratio (BM), beta coefficient (BETA), asset turnover ratio (ATO), operating cash flow to total assets ratio (CF), and quick ratio (QUICK).

4. Empirical Results and Discussion

4.1. Descriptive Analysis

Table 2. Descriptive analysis results.

Variable	Mean	Min	Max	SD	p50
COE	0.073	0.012	0.196	0.033	0.070
ED	0.304	0.026	0.737	0.158	0.289
CG	0.024	−1.161	1.436	0.536	0.058
ROE	0.095	−0.253	0.414	0.092	0.091
LEV	0.283	0.042	0.699	0.153	0.261
BM	0.536	0.102	1.023	0.217	0.545
BETA	5.297	0.000	6.223	0.726	5.472
ATO	0.504	0.000	1.175	0.242	0.491
CF	0.081	−0.084	0.256	0.059	0.074
QUICK	3.078	0.426	16.899	3.051	2.041

reports the mean, standard deviation, minimum, maximum, and median values of the main variables. The average COE is 0.073, indicating an overall COE of approximately 7%, with some variation across firms. This distribution is generally consistent with prior studies. The mean value of ED is 0.304, with a standard deviation of 0.158, suggesting substantial differences in disclosure quality among sample firms. The distribution of corporate governance appears reasonable, though some firms exhibit relatively low governance scores. Control variables also fall within acceptable ranges, with some reflecting the pharmaceutical industry’s high volatility and capital-intensive nature. Overall, the variable distributions show no significant anomalies, supporting the validity of the subsequent empirical analysis.

4.2. Correlation and Multicollinearity Diagnostics

Table 3. Pairwise correlation.

	COE	ED	CG	ROE	LEV	BM	BETA	ATO	CF	QUICK
COE	1
ED	−0.169 ***	1
CG	−0.195 ***	0.244 ***	1
ROE	−0.315 ***	0.008	−0.013	1
LEV	0.244 ***	0.134 ***	−0.048	−0.150 ***	1
BM	0.456 ***	0.055	−0.021	−0.268 ***	0.094 **	1
BETA	−0.077 **	−0.001	0.005	0.053	−0.015	−0.054	1
ATO	0.062 *	0.120 ***	0.038	0.377 ***	0.264 ***	−0.062 *	0.168 ***	1
CF	−0.096 **	0.041	0.020	0.625 ***	−0.220 ***	−0.290 ***	0.057	0.367 ***	1
QUICK	−0.149 ***	−0.146 ***	0.061	0.096 ***	−0.662 ***	−0.075 **	−0.031	−0.341 ***	0.138 ***	1

***, **, and * represent null rejection at 1%, 5%, and 10% level of significance, respectively.

presents the pairwise correlation matrix of the main variables, providing a preliminary overview of the linear relationships among variables. The results reveal a significant negative correlation between ED and COE at the 1% level, offering preliminary evidence that is consistent with the hypothesis that enhanced environmental disclosure is associated with lower equity financing costs. Overall, the correlation coefficients are moderate in magnitude, suggesting that no strong bivariate associations are present among the main explanatory variables.

To further assess potential multicollinearity concerns, variance inflation factors (VIFs) are reported in

Table 4. Variance inflation factors.

Variable	VIF	1/VIF
ED	1.110	0.902
CG	1.080	0.924
ROE	1.790	0.560
LEV	1.890	0.529
BM	1.130	0.886
BETA	1.040	0.964
ATO	1.620	0.616
CF	1.880	0.532
QUICK	1.920	0.520
Mean VIF	1.500

. The VIF values for all explanatory variables are well below commonly used thresholds, with a mean VIF of 1.50, indicating that multicollinearity is unlikely to pose a serious concern for the subsequent regression analyses.

4.3. Baseline Results

In

Table 5. Baseline regression results.

	Panel I	Panel II
ED	−0.0309 ***	−0.0267 ***
	(−3.00)	(−2.61)
ED * CG		−0.0483 **
		(−2.17)
CG		−0.00454
		(−1.03)
ROE	−0.157 ***	−0.156 ***
	(−5.88)	(−5.87)
LEV	0.0632 ***	0.0623 ***
	(3.54)	(3.48)
BM	0.0778 ***	0.0768 ***
	(8.01)	(7.95)
BETA	−0.00286 *	−0.00251
	(−1.67)	(−1.45)
ATO	0.0398 ***	0.0366 ***
	(3.55)	(3.25)
CF	0.172 ***	0.177 ***
	(6.12)	(6.34)
QUICK	0.00202 **	0.00196 **
	(2.19)	(2.15)
_cons	0.0128	0.0125
	(0.76)	(0.76)
Firm Fixed Effects	Yes	Yes
Year Fixed Effects	Yes	Yes
N	718	718
adj. R2	0.274	0.280

***, **, and * represent null rejection at 1%, 5%, and 10% level of significance, respectively. Figures in brackets are t-values.

, the regression results of Models 1 and 2 are presented. Specifically, Panel I reports the impact of ED on the COE, while Panel II further examines the moderating role of corporate governance in the ED-COE relationship. To eliminate the impact of multicollinearity and differences in scale, all variables were mean-centered before constructing the interaction terms between the independent and moderating variables. In addition, considering unobservable firm-level heterogeneity and systematic year-to-year variations, all regressions controlled for both the firms’ fixed effects and time’s fixed effects.

As shown in the regression results of Panel I, the estimated coefficient of ED is −0.0309, which is significantly and negatively associated with COE at the 1% level, indicating that an enhanced ED leads to a reduction in the COE. Thus, Hypothesis H1 is supported. This finding is consistent with [7,9,11,15,16]. One possible interpretation is that, as heavily polluting enterprises, pharmaceutical listed companies may face severe environmental issues and risks while also being subject to heightened public and governmental scrutiny and regulation. In this context, investors are particularly concerned about firms’ environmental risks [15], as such risks could lead to severe consequences, such as substantial environmental fines or operational shutdowns, which ultimately harm investors’ interests. With increased disclosure of environmental information, more comprehensive and positive signals may be transmitted to investors [7], thereby potentially reducing their risk assessments. Accordingly, the results suggest that enhanced ED is associated with a lower COE.

From the regression results in Panel II, the estimated coefficient of ED is −0.0267, which is also significantly and negatively associated with the COE at the 1% level. Moreover, the coefficient of the interaction term between ED and corporate governance (EDCG) is −0.0483, which is significantly and negatively associated with the COE at the 5% level. This suggests that corporate governance positively moderates the ED-COE relationship. Thus, Hypothesis H2 is supported. This finding clarifies the effect of corporate governance on the relationship, further extending the study by Jafar et al. [21] on the effects of the proportion of independent directors and board size on the relationship between ESG disclosure and COE. We argue that corporate governance serves as a positive moderator in this relationship, likely because China currently lacks a universally recognized and authoritative database for scoring ED [48], which causes investors to question whether such disclosure scores truly reflect the ED quality. Corporate governance can enhance the perceived quality and credibility of disclosure through strengthened internal monitoring mechanisms [28], which may help improve investors’ confidence in firms’ environmental commitments, reduce information asymmetry, and consequently lower the COE.

Among the control variables, profitability is significantly and negatively associated with the COE at the 1% level, indicating that higher profitability leads to lower equity financing costs. Meanwhile, financial leverage, market-to-book ratio, asset turnover, and operating cash flow to total assets ratio are all significantly and positively associated with the COE at the 1% level, and the quick ratio is significantly and positively associated with the COE at the 5% level, suggesting that higher financial leverage, a larger market-to-book ratio, higher asset turnover, an increase in operating cash flow to total assets ratio and a higher quick ratio all raise the COE. Finally, Beta and corporate governance are negatively associated with the COE, but their regression results are statistically insignificant.

4.4. Robustness Test

To verify the robustness of the research findings, two additional robustness tests were conducted (see

Table 6. Robustness test results.

	System GMM		PSM-FE
	Panel I	Panel II	Panel III	Panel IV
L.COE	0.331 ***	0.351 ***
	(4.00)	(3.36)
ED	−0.0563 ***	−0.0330 **	−0.0293 ***	−0.0255 **
	(−2.59)	(−1.98)	(−2.87)	(−2.51)
EDCG		−0.0738 **		−0.0446 **
		(−1.99)		(−2.01)
CG		−0.00382		−0.00465
		(−1.19)		(−1.06)
ROE	−0.128 **	−0.225 ***	−0.166 ***	−0.165 ***
	(−2.51)	(−4.90)	(−6.14)	(−6.08)
LEV	0.0939 ***	0.137 ***	0.0717 ***	0.0702 ***
	(3.06)	(4.17)	(4.14)	(4.03)
BM	0.0797 ***	0.0870 ***	0.0799 ***	0.0791 ***
	(5.81)	(4.57)	(8.41)	(8.35)
BETA	−0.00455	−0.00112	−0.00288 *	−0.00255
	(−1.35)	(−0.31)	(−1.68)	(−1.46)
ATO	0.0462 *	0.0567 **	0.0434 ***	0.0402 ***
	(1.75)	(2.07)	(3.82)	(3.51)
CF	0.189 ***	0.230 ***	0.182 ***	0.185 ***
	(4.12)	(4.76)	(6.27)	(6.41)
QUICK	0.00298 **	0.00487 ***	0.00240 **	0.00231 **
	(2.07)	(2.95)	(2.57)	(2.51)
_cons	−0.00981	−0.0522	0.00630	0.00641
	(−0.34)	(−1.30)	(0.38)	(0.39)
AR (1)	−2.32	−2.07
	(0.021)	(0.039)
AR (2)	−1.61	−1.58
	(0.107)	(0.115)
Hansen	59.19	39.59
	(0.325)	(0.577)
Firm Fixed Effects			Yes	Yes
Year Fixed Effects			Yes	Yes
adj. R2			0.283	0.288

***, **, and * represent null rejection at 1%, 5%, and 10% level of significance, respectively. z-statistics for GMM models and t-statistics for PSM models are reported in parentheses.

).

On the one hand, to help mitigate potential endogeneity issues such as reverse causality and omitted variable bias, the system GMM estimator was employed [49]. While the FE model focuses on contemporaneous relationships, the system GMM framework explicitly accounts for dynamic persistence by including the lagged dependent variable and using internal instruments, and is therefore used as a robustness check. The model diagnostics indicate that the p-values of the Hansen test for overidentifying restrictions are 0.325 and 0.577, both greater than 0.1, suggesting that the selected instruments are overall valid. Furthermore, the Arellano–Bond (AR) autocorrelation test shows significant first-order autocorrelation in the first-differenced residuals (AR (1): p < 0.001), but no evidence of second-order autocorrelation (AR (2): p > 0.1), meeting the assumptions of the system GMM estimator.

On the other hand, to address potential sample selection bias, PSM was applied to reconstruct the sample [50]. Specifically, all control variables and year dummies were used as matching covariates, and kernel matching with a bandwidth of 0.1 was performed. The matching diagnostics indicate that the standardized differences of covariates after matching are all within 5%, the pseudo R² approaches zero, and the differences between the treatment and control groups are substantially improved. Based on the matched sample, the PSM-FE was re-estimated. This analysis is conducted as a robustness check rather than as a primary identification strategy.

As reported in Table 6, the results of the two robustness tests indicate that the negative impact of ED on the COE and the positive moderating role of corporate governance remain significant in both the GMM and PSM-FE models, with coefficient directions consistent with the baseline regression and significance levels unchanged, further supporting the robustness of the main findings.

5. Conclusions

This study draws on data from Chinese pharmaceutical listed companies from 2018 to 2022, employing a two-way FE model as the baseline empirical framework to examine the impact of environmental disclosure (ED) on the cost of equity (COE) and the moderating role of corporate governance. To assess the robustness and to address potential endogeneity and sample selection concerns, additional analyses are conducted using the system GMM estimator and PSM-FE methods. The results indicate that ED is significantly and negatively associated with COE, suggesting that firms with enhanced disclosure quality experience a notable reduction in their COE. Further analysis reveals that corporate governance positively moderates the ED-COE relationship, implying that more effective corporate governance amplifies the capital market effects of the disclosure. Taken together, these findings suggest that the capital market benefits of ED do not arise solely from the disclosure itself, but are critically conditioned by corporate governance structures, which play a key role in shaping the effectiveness of ED in reducing equity financing costs.

From a theoretical perspective, this study draws on signaling theory and agency theory to interpret the relationship between ED and COE. The analysis provides context-specific empirical evidence on how information transparency is associated with lower perceived risk in capital markets, particularly in an emerging-market context. Drawing on signaling and agency theories, this study helps explain the conditional nature of the relationship between environmental disclosure and the cost of equity, as disclosure serves both as a signal of environmental commitment and as a governance-dependent process influencing information credibility. Moreover, the finding that corporate governance moderates the disclosure-financing cost relationship offers incremental insights into the role of internal corporate governance mechanisms in shaping the effectiveness of disclosure, thereby extending existing disclosure and agency-based arguments to a regulated, industry-specific context.

Practically, the findings offer implications for multiple stakeholders. First, for firms, the results suggest that greater attention to the ED may be associated with lower COE, particularly in environmentally sensitive industries. Rather than viewing ED solely as a compliance requirement, firms may benefit from improving internal disclosure and reporting practices, while effective corporate governance can support this process by strengthening internal oversight over disclosure activities. Second, for regulators, the findings indicate that partial mandatory disclosure alone may not ensure high-quality ED, highlighting the importance of complementary mechanisms that promote disclosure consistency and comparability. In this regard, the results suggest that governance-related mechanisms can play a complementary role in reinforcing the effectiveness of disclosure-oriented regulation, rather than replacing mandatory disclosure requirements. Finally, for investors, considering ED together with corporate governance characteristics may facilitate a more nuanced assessment of firms’ environmental risk exposure and equity financing conditions, as more effective corporate governance can enhance the extent to which disclosure information is reflected in equity pricing.

Nevertheless, this study has several limitations. First, the analysis focuses on Chinese pharmaceutical listed companies under a partial mandatory disclosure regime during the post-2018 period, which may limit the generalizability of the findings to other industries or institutional settings. In addition, the sample period coincides with the early implementation of the disclosure regulation and the COVID-19 pandemic, which may have influenced capital market conditions; although year fixed effects are included, these factors may still affect the estimates and should be interpreted with caution. Second, ED is measured using standardized indicators from the CSMAR database, which mainly capture formal disclosure channels and may not fully reflect nontraditional disclosure activities. Future research could build on this study in several directions. First, extending the analysis to other industries, different national or regional regulatory regimes, or longer time periods would help assess whether the observed disclosure-financing relationship holds under different regulatory environments and over extended horizons. Second, future studies may incorporate alternative disclosure channels, such as digital or media-based environmental communication, to provide a more comprehensive measure of disclosure practices. In addition, future research could further explore heterogeneity across firm characteristics, such as ownership structure, firm size, R&D intensity, or regional regulatory environments, to better understand how the effectiveness of environmental disclosure varies across different contexts.

Overall, this study demonstrates that ED is negatively associated with COE and that corporate governance positively moderates this relationship in the context of Chinese pharmaceutical listed firms. By focusing on a highly regulated and environmentally sensitive industry operating under a partial mandatory disclosure regime, the study offers context-specific evidence on the relationship between disclosure, governance, and equity financing costs. In addition, the findings are discussed within established signaling and agency perspectives, highlighting the role of corporate governance in enhancing how ED is reflected in capital markets in an emerging-market setting. The results may help firms, regulators, and investors better understand how disclosure and governance mechanisms are reflected in capital market assessments.