Effect of Environmental Information Disclosure on the Financing Efficiency of Enterprises—Evidence from China’s Listed Energy Companies

Abstract

In recent years, China has made it clear that the whole society should constantly enhance its awareness of ecological and environmental protection and promote the development of public safety and health. For listed energy enterprises, it is the responsibility of the enterprise to disclose the extent of environmental pollution in the development process to the whole society. The environmental information disclosure of energy enterprises not only promotes social and environmental protection but also has an impact on the financing efficiency of the enterprises themselves. After screening all A-share listed energy enterprises in China and eliminating the non-adoptable samples, 182 listed energy enterprises were finally selected as the research samples. Based on the data samples of 182 A-share listed energy industry enterprises in China from 2012 to 2019, this paper empirically tests the relationship between environmental information disclosure and corporate financing efficiency. The study finds that the environmental information disclosure has a significant positive impact on corporate financing efficiency, and the mediating effect model is used to analyze the intermediary role of corporate social responsibility in the impact of corporate environmental information disclosure on financing efficiency. This study expands the economic impact of corporate environmental information disclosure, improves the research framework on corporate financing efficiency, and provides informative suggestions for energy enterprises to improve financing efficiency and long-term development. In addition, the research shows that the environmental information disclosure and corporate social responsibility of listed energy enterprises in China still need to be improved, and the government and regulatory authorities should strengthen relevant policy constraints.

1. Introduction

With the vision of “carbon peak” in 2030 and “carbon neutrality” in 2060, as well as the proposal of the “14th Five-year Plan”, China’s ecological civilization construction has entered a new stage, and environmental issues have become a public topic of great concern. To achieve “new progress” in the construction of ecological civilization and continuously improve environmental quality, it is necessary to accelerate the development of a green economy and the innovation of energy technology, which also puts forward higher requirements for the development of Chinese enterprises. As the main consumers of natural resources and the sources of pollutant emissions, energy enterprises will face more severe development challenges while undertaking greater social responsibilities. Zhao Yang et al. (2019) [1] believe that the incongruity between enterprise development and environmental protection has become the main contradiction in Chinese environmental governance. Ruikun and Wang Feng (2021) [2] believe that the operation of enterprises cannot be separated from the environment and it also affects the environment. In environmental governance, corporate information disclosure plays an important role. Investors and the government also urgently need enterprises to disclose relevant environmental information. For enterprises to take the initiative to disclose environmental information, release effective environmental information, and make this information known to the relevant people, the environmental information disclosure system came into being.

As an effective means for the government to supervise the environmental behavior of enterprises, the environmental information disclosure policy is the basic content of building an ecological civilization system with Chinese characteristics. In recent years, the relevant systems for environmental information disclosure have been constantly improved, which is of great significance for accelerating the improvement of the modern environmental governance system with Chinese characteristics, ensuring the public’s right to supervision and information, and guiding the flow of market funds (Sun Zhenqing et al., 2022) [3]. In 2016, the People’s Bank of China and seven other departments jointly issued the Guidance on Building a Green Financial System, which requires the gradual establishment and improvement of the mandatory environmental information disclosure system of listed companies. In 2017, China Securities Regulatory Commission proposed to build a hierarchical environmental information disclosure system for listed companies and encouraged listed companies to disclose environmental information that is conducive to ecological protection. In 2019, the Opinions on Further Deepening Ecological and Environmental Supervision Services to Promote High-Quality Economic Development incorporated environmental protection information into the national credit-information sharing platform. In 2020, the Central Deep Reform Commission deliberated and adopted the Reform Plan for the Legal Disclosure System of Environmental Information, which proposed that the mandatory disclosure system of environmental information should be formed by 2025.

As a means of public participation in environmental regulation, environmental information disclosure will have a certain impact on enterprise innovation, enterprise performance, productivity, and enterprise value. Zhang Huiming et al. (2022) [4] took listed companies in China’s high-energy-consumption industry as the object and found that environmental information disclosure can alleviate financing constraints and thus effectively promote the green innovation of enterprises. Jiang et al. (2020) [5] believe that there is a significant positive interaction between environmental information disclosure and environmental management system certification, which has a positive impact on enterprise innovation investment. Wang Shanyong et al. (2020) [6] found that environmental information disclosure can directly promote the improvement of environmental performance by analyzing the data of Chinese listed companies, and good environmental performance will enhance the reputation of enterprises and enhance their attractiveness to potential investors. Zhan Hua and Hou Mengting (2021) [7] combined the micro data of 286 prefecture-level cities and A-share listed enterprises, finding that environmental information disclosure can alleviate financing constraints, improve enterprise financial performance, and promote enterprise innovation on this basis through empirical analysis. The research of Fan Dan and Fu Jiawei (2021) [8], based on the data of listed companies in the Shanghai and Shenzhen stock exchanges, shows that environmental information disclosure helps improve the total factor productivity of enterprises and finds that its main transmission path comes through alleviating the financing constraints of enterprises and promoting green technological innovation of enterprises. Previous studies by scholars Li et al. (2018) [9] and Alsayegh et al. (2020) [10] also confirmed the positive correlation between environmental information disclosure and enterprise value and performance. For the same amount of investment, investors can accept a lower investment return rate for enterprises that actively disclose environmental information, and for the invested enterprise itself, the cost of capital usage will be reduced, which increases the enterprise value. Fadi et al. (2022) [11] found that high-quality environmental information disclosure can help companies transition to Industry 4.0 while improving financial performance.

It is the social responsibility of enterprises to carry out environmental information disclosure in accordance with the law, and it is also the common practice of implementing corporate environmental responsibility internationally. At the same time, the fulfillment of corporate social responsibility (CSR) often brings good feedback to the operation and development of enterprises. With the increasing social responsibility of energy enterprises, how to better undertake social responsibility and fulfill their environmental responsibility is becoming the topic discussed by all walks of life. Zhang Zhe and Ge Shunqi (2021) [12] believed in their research that environmental information disclosure, as a manifestation of corporate social responsibility, directly improves the sense of identity and security of internal employees. Hamrouni et al. (2019) [13] took French companies as research samples and found that the disclosure of high-level environmental information by enterprises is a reflection of the fulfillment of social responsibility, and enterprises with a strong sense of social responsibility are more likely to get support from investors. Bhattacharyy and Rahman (2019) [14] found in their study of the impact of CSR expenditure on corporate performance that, regardless of the actual level of CSR expenditure relative to the mandatory level of CSR, CSR will make a positive contribution to corporate performance. Taliento et al. (2019) [15] argue that social, environmental, and governance responsibilities are important competitive factors for modern businesses for all stakeholders.

As the pillar of the national economy, the energy industry plays a vital role in the rapid development of China’s economy. The improvement of enterprise operation efficiency, especially financing efficiency, is the key to ensuring high-quality economic development. However, the natural “polluting” characteristics of energy industry enterprises often hurt the image and reputation of energy enterprises, thus bringing greater financing constraints to energy enterprises. Zhao Dandan (2021) [16] pointed out that in the context of “double carbon”, energy enterprises will undoubtedly face more urgent problems such as energy transformation, energy conservation, and emission reduction equipment investment if they want to achieve better development. On the other hand, financial institutions such as banks are also more cautious in providing financial support to energy enterprises, especially heavily polluting enterprises, thus increasing the financing pressure faced by such enterprises to a certain extent. With the development of the green economy and people’s increasing awareness of environmental protection, the social responsibility of energy enterprises is increasingly valued by all stakeholders. The environmental performance of enterprises is gradually becoming an important factor affecting the business risks and profitability of enterprises. The environmental information disclosed by enterprises is also becoming an important basis for investors and creditors to measure their investment risks. So for the energy enterprises themselves, does environmental information disclosure effectively improve the financing efficiency of enterprises? How does environmental information disclosure affect the financing efficiency of enterprises?

China regards the construction of an ecological civilization as important content. To implement the concept of green development and form a new pattern of modernization with the harmonious development of man and nature, it needs to be guided by the market and system. In this process, the society will encourage social resources to invest in green, low-carbon, emission reduction, and other fields. Therefore, in this context, it is of great significance to study the impact of environmental responsibility and social responsibility performance levels of energy enterprises on their financing efficiency. Among them, based on the research of existing scholars, this paper focuses on the impact of environmental information disclosure on the financing efficiency of energy enterprises, so as to put forward suggestions for improving the financing efficiency of energy enterprises and obtaining effective financial support. Based on the above starting points and questions, and considering that the epidemic situation in 2020 will bring great fluctuations to the economic situation of enterprises, this paper selects data related to energy enterprises of all A-share listed enterprises in China from 2012 to 2019 as the initial research sample, analyzes the overall environmental and social responsibility fulfillment level of energy enterprises in China, empirically explores the impact of environmental information disclosure on financing efficiency and its transmission mechanism, and puts forward relevant suggestions from the perspective of enterprises and supervision.

2. Literature Review and Theoretical Analysis

2.1. Environmental Information Disclosure and Financing Efficiency of Energy Enterprises

The financing efficiency of enterprises also depends on the financing cost generated by various financing methods and the financing allocation efficiency of enterprises. Liu Junhang and Zhang Lingling (2022) [17] also pointed out in their research that when enterprises use funds, they will allocate the funds raised through various financing methods to different value-creating activities. High financing allocation efficiency reflects the good operation and management ability of enterprises, which means that enterprises can accumulate more capital and invest it in reproduction under a certain amount of capital.

Environmental factors restrict the development of enterprises. To a certain extent, enterprises meet the needs of investors and stakeholders by disclosing information. As an important basis to assess the environmental risks of an enterprise, environmental information disclosure has increasingly become the focus of corporate creditors and investors. Luo et al. (2019) [18] believe that the quality of corporate environmental information disclosure has a significant negative impact on debt financing costs. Environmental information disclosure of energy enterprises can reduce enterprise financing costs. On the one hand, existing studies show that environmental information disclosure will reduce the debt financing cost of enterprises [19] and lead to easier access to long-term bank loans [20], and enterprise environmental information disclosure is an important factor influencing its bank loans. By alleviating the information asymmetry between banks and enterprises, banks can reduce the restrictive clauses of loans [21], thus reducing the debt financing cost of enterprises. The research of Sengupta [22] shows that timely and detailed environmental information disclosure can improve the social reputation of enterprises, thereby reducing the effective interest cost of debt issuance. On the other hand, there is a statistically significant negative correlation between environmental information disclosure and equity cost [23]. Enterprises with high-quality environmental information disclosure are often perceived by investors to be more powerful and socially responsible, thus enabling enterprises to obtain more risk discounts and reduce their equity capital costs [24]. Lu Guanyan (2021) [25], based on the data of 140 listed companies in the energy industry, empirically found that environmental information disclosure can reduce the cost of equity capital and improve the expected cash flow. Tang Yongjun et al. (2021) [26] found that from the perspective of corporate internal governance, environmental information disclosure can send a positive signal to the market. The higher the degree of environmental information disclosure, the lower the internal financing cost. Specific for the energy industry, research shows that the negative correlation between the quality of environmental information disclosure and the cost of equity capital of energy enterprises such as natural gas, thermal power, petroleum, and petrochemical is more significant than that of energy enterprises such as hydropower, solar energy, and others [27].

The disclosure of relevant environmental information by energy enterprises can attract financing and expand the source of financing. Chang Yuan et al. (2022) [28] believe that environmental information disclosure is an important channel for outsiders to understand the current situation of corporate environmental protection. The disclosure of environmental information can not only reduce the degree of information asymmetry but also help to strengthen the recognition of the public and relevant investors to the company, so as to attract investment. Based on the perspective of information theory [29], the disclosure of environmental information by enterprises can improve the external environment, reduce the information asymmetry between enterprises and the external environment, enhance the investment confidence of investors and creditors in enterprises and the market, and thus attract capital into enterprises. The research of Leng Jianfei and Gao Yun [30] shows that the environmental and responsibility information disclosure of enterprises can restrain financing and promote the sustainability of enterprise innovation.

The disclosure of relevant environmental information by energy enterprises can promote the improvement of their own operational efficiency and capital utilization efficiency: on the one hand, with the improvement of investors’ monitoring power over managers, enterprise managers are more likely to invest capital in innovative projects that are conducive to the long-term development of enterprises [31], thus promoting the high-quality development of enterprises. Yang Ye and Xie Jianguo (2020) [32] found that environmental information disclosure can significantly inhibit the mismatch of environmental resources, improve the utilization rate of resources, and have a positive impact on the financial performance of enterprises. According to the reputation theory [33], when enterprises actively disclose environmental information to improve their social reputation, they usually restrict their own behavior, reduce inefficient investment, and improve the efficiency of capital use. Jing Guowen and Tao Yuan (2022) [34] also believe in their research that enterprises will carry out equipment transformation and improve production efficiency, distribution efficiency, and resources under the constraints and supervision of environmental information disclosure. On the other hand, Jiang Yiji and Yao Shujie (2022) [35] believe that because of the large investments and long periods of environmental protection projects, it is often difficult to achieve results in the short term. The separation of enterprise ownership and management rights also makes it difficult for operators to turn to projects with a high return on investment to improve short-term financial performance, and the disclosure of environmental information will reduce the uncertainty of information acquisition and effectively reduce the generation of agency costs, improving the financial performance of enterprises (Dai Yue et al., 2019) [36]. Gao Fanya [37] and others also verified through empirical analysis that corporate social responsibility information disclosure can reduce their principal-agent costs, improve the internal governance structure of the companies, reduce the financing pressure faced by the enterprises, and alleviate the problem of “financing difficulties”. The disclosure of environmental information by enterprises can reduce the cash flow risk from the increased environmental supervision costs in the future and enhance the value effect of cash holdings of enterprises. In terms of corporate financial performance, Xie Yizhang and Tang Xinyi (2022) [38], based on the data of listed companies in the chemical industry and DuPont’s analysis system, found that environmental information disclosure has a significant positive correlation with financial performance and that environmental information disclosure is beneficial to improving financial performance. Aureli et al. (2020) [39] and Minutolo et al. (2019) [40] demonstrated that environmental information disclosure can help improve corporate financial efficiency from the perspectives of safety benefits and strategic choices, respectively. Other studies have shown that the disclosure of environmental-related information has a significant positive impact on the return on assets and return on net assets of enterprises [41,42,43]. In summary, environmental information disclosure by energy enterprises can improve the financing efficiency of enterprises in terms of reducing the financing cost, attracting financing, and improving the management level and capital use efficiency.

2.2. The Mediating Effect of Energy CSR

Li Xinfei and Li Fangfang (2022) [44] believe in their research that corporate social responsibility means that enterprises need to be responsible for the public and the environment while creating profits and bearing economic and legal responsibilities to shareholders, employees, and other stakeholders. Liu Bai and Liu Chang (2019) [45] found that for enterprises, environmental information disclosure also reflects their social responsibility image and good corporate social responsibility plays an important role in alleviating corporate financing constraints.

On the one hand, it is the social responsibility of enterprises to carry out environmental information disclosure in accordance with the law. This paper uses the professional evaluation system and the scores of social responsibility reports of listed companies published by Hexun.com to measure the performance of corporate social responsibility, in which the proportion of environmental responsibility accounts for 20%. Therefore, in its social responsibility report, the enterprise disclosed information on its capital investment, governance measures, and achievements in environmental control, which reflected that the enterprise had fulfilled its environmental responsibility better [46], thus improving the level of environmental responsibility and social responsibility of the enterprise. On the other hand, the disclosure of relevant environmental information by enterprises in their social responsibility reports can improve the quality of reports. Some studies have shown that the disclosure quality of corporate social responsibility reports has a positive effect on the investment efficiency of enterprises [47,48,49], while the improvement of investment efficiency is ultimately manifested in the improvement of financing efficiency. Li Yin (2019) [50] also verified and supported this research, which showed that the level of corporate social responsibility can significantly improve the total factor productivity of enterprises, and this is ultimately manifested in the improvement of corporate financing efficiency. In addition, the intermediary role of social responsibility between environmental information disclosure and financing efficiency can be reflected by signal theory [51]: environmental responsibility is an important part of social responsibility, and the environmental information disclosed by an enterprise is a manifestation of its fulfillment of environmental social responsibility, reflecting the importance of social responsibility and the ability to control environmental problems; while improving their social responsibility performance, enterprises have also formed a positive environmental image and good reputation to attract more investors and ease credit constraints, thus improving the financing efficiency of enterprises. In summary, the level of corporate social responsibility is enhanced by disclosing environmental aspects in social responsibility reports, and the level of corporate social responsibility is also conducive to the improvement of corporate financing efficiency.

3. Data Sources and Study Design

3.1. Sample Selection and Data Sources

In this paper, all A-share listed enterprises in China that disclosed social responsibility reports in the mining, electricity, heat, gas, and water production and supply industries (according to the industry classification of the China Securities Regulatory Commission in 2012) from 2012 to 2019 were selected as the initial research sample, and ST and ST* listed enterprises and those with incomplete disclosure in terms of financial data were excluded, and the data of 182 energy enterprises were finally selected. ST shares refer to the shares of domestic listed companies that have suffered losses for two consecutive years and have been specially treated. ST* shares refer to the stocks of domestic listed companies that have suffered losses for three consecutive years and have been warned of delisting risks. Although ST and ST* companies have not actually delisted, their profit and loss and operating cash flow have generally deteriorated significantly. If such companies are included, the analysis conclusion will be biased. The regression model based on panel data combines time series and cross-sectional observations. Panel data has more information and richer sources of variation, which will reduce the collinearity between variables, have more degrees of freedom, and obtain more effective and reliable parameter estimates. In this paper, the complete data of 182 enterprises for 8 consecutive years will be collected for analysis. A total of 13 variables will be used for regression analysis and the degree of freedom is 1442.

Due to the full outbreak of the COVID-19 in 2020, many energy companies suffered losses. The number of Chinese A-share listed energy companies that could collect complete financial data in 2020 fell to 161, and about half of them had negative financing efficiency, which was mainly caused by losses. Due to the impact of unpredictable emergencies such as COVID-19, the financing efficiency data of A-share listed energy companies in 2020 has experienced serious fluctuations compared with the data in 2019 and before, which has seriously affected the analysis under normal market conditions. At the same time, in 2020, under the attack of the global COVID-19, some Chinese A-share listed energy enterprises disclosed environmental-related information before 2020, but did not disclose it in 2020, such as Hunan Gold, Guozhong Water, Tongbao Energy, Petrochemical Oil Services, Zijin Mining, etc. Based on these special circumstances, the samples selected in this paper are up to 2019, and the complete data of 182 enterprises.

Due to the public emergencies, such as COVID-19 in 2020, which have brought a big blow to the operation and development of the energy industry, a considerable part of the financial data of energy enterprises and related research data have experienced large abnormal fluctuations. This is mainly because the energy industry chain spans from raw material manufacturing and processing to product consumption. Public emergencies, such as epidemics, will affect the upstream and downstream industrial chains of the energy sector, and the sector at the core hub of the industrial chain is likely to have a chain reaction because of limited capacity or shutdown. Interrupting or slowing down the energy production process not only leads to production stoppage at the energy supply end and a sharp decrease in demand at the consumer end, but also has an impact on the energy deep processing, transportation, and other links in the middle. Therefore, to ensure the continuity and robustness of the study and eliminate the influence of interference events on the research of the interaction between independent variables and dependent variables as far as possible, this paper selects the data before the emergence of COVID-19 for analysis.

From 8 February 2022, China implemented the Measures for the Administration of Legal Disclosure of Enterprise Environmental Information, which clearly stipulated that “enterprises must disclose environmental information in accordance with the law, in a timely, true, accurate and complete manner. The environmental information disclosed must be concise, clear, and easy to understand. There shall be no false records, misleading statements or major omissions.” In the future, under the official requirements of this document, more and more enterprises will disclose environmental information according to law, which is believed to enrich the research in this paper.

However, in recent years, China has attached great importance to the construction of an ecological civilization, identified and implemented the concept of green development, continued to promote the green development mode, constantly improved the system of ecological civilization, and changed the mode of economic development, so that economic growth is more based on efficient use of resources and reduction in environmental pollution. The information disclosure model based on the assessment of environmental gains and losses builds a bridge between environmental protection and enterprise development with its core of monetary valuation. Therefore, based on the analysis of data in previous years in this paper and related research, it can be preliminarily judged that environmental information disclosure still has a positive role in promoting corporate financing and development. For example, the following influential related studies have also adopted the same approach as Yan et al. (2022) [52], Shi et al. (2022) [53], and others [54,55,56].

Based on this, all continuous variables in this paper have been tail-shrunk before and after 1% scale to prevent outliers from affecting the research results. When the sample size is large, continuous variables are usually tail reduced to prevent the impact of abnormal values on the results. The main method is to replace a set of continuous data that exceeds the specified percentile (take 1% of the normal standard) with the adjacent value reserved for the specified percentile. As a method to deal with outliers, tail-shrinking processing is widely used in the research of corporate financial data; for example, the following latest related research has adopted tail-shrinking processing (Winsor processing) like Ma et al. (2022) [57], Wei et al. (2022) [58], and others [4,59,60,61]. In this paper, we eliminate the influence of outliers or outliers on the overall regression results by shrinking the tail of all explanatory variables at the 1% quantile level. Among them, the regression coefficients of some variables and explained variables are not very significant before shrinking the tail of the data but more significant after shrinking the tail, indicating that outliers have a certain impact on the regression results; it also shows that the regression results after 1% data shrinkage are more accurate and reliable.

The social responsibility report information and social responsibility report scores in the paper were obtained from the official website of Hexun.com, and the rest of the data were obtained from the CSMAR database. In addition, to solve the problem of the large disparity in the magnitude of indicators among sample enterprises and the possible influence of heteroskedasticity, the control variable enterprise size (Size) is processed by taking the natural logarithm in this paper. The data are organized and processed using Excel 2016 software, and stata16 is used for empirical analysis.

3.2. Variable Definition and Index Portrayal

(1) Explanatory variable: corporate financing efficiency

On the one hand, enterprise financing efficiency is affected by the costs of enterprise financing. In general, the lower the cost of enterprise financing, the higher the financing efficiency. On the other hand, affected by the efficiency of enterprise capital utilization, when the enterprise can improve the rate of return under the existing financing cost, the financing efficiency will be higher. This paper draws on the existing research on corporate financing efficiency and adopts the formula “financing efficiency = return on net assets × [1 − weighted average cost of capital (1 + financial leverage coefficient)] × 100%” calculation that represents the financing efficiency of the sample enterprises [62].

(2) Explanatory variables: corporate environmental information disclosure

According to the “Notice on the Preparation of 2008 Annual Reports of Listed Companies” jointly issued by Shanghai and Shenzhen stock exchanges in 2008, listed companies are required to publish CSR together with their annual reports. Unlike financial reports, CSR reports are the carrier for enterprises to demonstrate the fulfillment of social responsibility to their stakeholders. Among them, the corporate environmental information disclosure, as a resource-based disclosure project, contains the control cost, capital investment, and measures and results taken by the enterprise in environmental management. It can convey the development information and philosophy of the enterprise to investors, creditors, and consumers, thus influencing stakeholders’ views on the development of the enterprise [63]. According to the existing research, there is no unified measurement system and standard for the level of environmental information disclosure. Therefore, this paper takes the dichotomous variable of “whether the enterprises disclose environmental information in their social responsibility report” as the independent variable.

(3) Mediating variable: corporate social responsibility

This paper adopts the social responsibility score of listed companies published by Hexun.com to measure the performance of corporate social responsibility. The score is measured by the professional assessment system of social responsibility report, which quantifies the score from five categories: shareholder responsibility, employee responsibility, supplier, customer and consumer rights and interests’ responsibility, environmental responsibility, and social responsibility. Among them, the weight of environmental responsibility accounts for 20%, including the enterprise’s environmental awareness, environmental management system certification, environmental protection investment amount, pollutant discharge types, and energy conservation types. The secondary and tertiary indicators are set up for each item to evaluate social responsibility comprehensively, which can better reflect the level of corporate social responsibility.

(4) Control variables

To avoid the effect of firm characteristic level variables on the financing efficiency of enterprises, this paper selects audit institutions (Audit), concentration of equity (Cont), nature of ownership (Property), solvency (Lev), return on total assets (ROA), growth in main revenue (Growth), firm size (Size), and director size (Scale), and year (Year) and industry (Indus) are used as control variables. Cont is used to control and reflect the internal governance structure of the enterprises, the variable Lev measures the solvency of the enterprise through its internal capital composition and its ratio, and Growth measures the development potential of enterprises through the growth rate of main business income.

The sample set used in this paper is the relevant data of 1188 A-share listed energy enterprises for eight consecutive years, and the number of samples of observations is 9504, which is far greater than the number of parameters involved in the model. In addition, this paper adopts the double fixed-effect model of industry and year and sets the industry dummy variable (Indus) to control the impact of the industry, and the annual dummy variable (year) to control the impact of the year. For example, similar analysis methods have been used in the latest related studies by Zhang et al. (2022) [64], Nie et al. (2022) [65], and others [4,38,66]. The rest of the control variables and their measurement methods are detailed in

Table 1. Variable Definition.

Nature of Variables	Variable Name	Variable Symbols	Variable Description
Explained variables	Financing Efficiency	FE	Financing efficiency = return on net assets × [1 − weighted average cost of capital (1 + financial leverage coefficient)] × 100%
Explanatory variables	Corporate Environmental Information Disclosure	EID	Whether to disclose environment-related information in CSR report, yes take 1, no take 0
Intermediate variables	Corporate Social Responsibility	CSR	Hexun.com corporate social responsibility Score
Control variables	Auditors	Audit	An audit by the big four firms takes the value of 1, audit by other accounting firms takes the value of 0
	Shareholding Concentration	Cont	The shareholding ratio of top shareholders of listed companies
	Nature of ownership	Property	State-owned enterprises take the value of 1, non-state-owned enterprises take the value of 0
	Solvency	Lev	Enterprise year-end gearing ratio
	Return on Total Assets	ROA	Net income/total assets balance
	Main revenue growth rate	Growth	The growth rate of the enterprise’s main business income
	Enterprise size	Size	Substitute the natural logarithm of the enterprise’s total assets at the end of the year
	Director Size	Scale	Number of the corporate board of directors
	Year	Year	Year dummy variable
	Industry	Indus	According to the SEC’s 2012 industry classification standards

Note: the big four firms are PricewaterhouseCoopers, Deloitte Touche Tohmatsu, Klynveld Peat Marwick Goerdeler, Ernst & Young.

.

3.3. Research Hypotheses and Model Construction

To test the relationship between environmental-related information disclosure, corporate financing efficiency, and corporate social responsibility scores of energy enterprises more scientifically and reasonably, the data used in this paper are balanced panel data. According to the test results of SPSSAU by F, BP test, and Hausman test, the annual and industry double fixed-effects model is used. In addition, to control the influence of other factors affecting the financing efficiency of enterprises as much as possible, this paper directly includes the control variables described in the previous section. Referring to the procedure for testing mediating effects by Wen Zhonglin et al. [67], the following mediating effects model was constructed.

H1: 

There is a positive correlation between the disclosure of environmental information in social responsibility reports by the surveyed energy enterprises and the financing efficiency of these enterprises. To test hypothesis H1, i.e., the relationship between environmental-related information disclosed by energy enterprises in social responsibility reports and enterprise financing efficiency, model (1) was established.

$$\begin{array}{ll}F{E}_{i,t}={\alpha }_0+& {\alpha }_{1}EI{D}_{i,t}+{\alpha }_{2}Audi{t}_{i,t}+{\alpha }_{3}Con{t}_{i,t}+{\alpha }_{4}Propert{y}_{i,t}+{\alpha }_{5}Le{v}_{i,t}\\ & +{\alpha }_{6}RO{A}_{i,t}+{\alpha }_{7}Growt{h}_{i,t}+{\alpha }_{8}Siz{e}_{i,t}+{\alpha }_{9}Scal{e}_{i,t}+{\displaystyle \sum }Year\\ & +{\displaystyle \sum }Indus+{\epsilon }_{i,t}\end{array}$$

(1)

H2: 

There is a positive correlation between the disclosure of environmental information in the social responsibility reports of the surveyed energy enterprises and the level of social responsibility of these enterprises. To test hypothesis H2, model (2) was built.

$$\begin{gathered} CS{R}_{i,t}={\beta }_0+{\beta }_{1}EI{D}_{i,t}+{\beta }_{2}Audi{t}_{i,t}+{\beta }_{3}Con{t}_{i,t}+{\beta }_{4}Propert{y}_{i,t}+{\beta }_{5}Le{v}_{i,t}+ \\ {\beta }_{6}RO{A}_{i,t}+{\beta }_{7}Growt{h}_{i,t}+{\beta }_{8}Siz{e}_{i,t}+{\beta }_{9}Scal{e}_{i,t}+{\displaystyle \sum }Year+{\displaystyle \sum }Indus+{\epsilon }_{i,t} \end{gathered}$$

(2)

H3: 

There is a positive correlation between the financing efficiency of the surveyed energy enterprises and the disclosure of environmental information in social responsibility reports and the level of social responsibility of these enterprises. Model (3) was built to verify hypothesis H3.

$$\begin{gathered} F{E}_{i,t}={\gamma }_0+{\gamma }_{1}EI{D}_{i,t}+{\gamma }_{2}CS{R}_{i,t}+{\gamma }_{3}Audi{t}_{i,t}+{\gamma }_{4}Con{t}_{i,t}+{\gamma }_{5}Propert{y}_{i,t}+ \\ {\gamma }_{6}Le{v}_{i,t}+{\gamma }_{7}RO{A}_{i,t}+{\gamma }_{8}Growt{h}_{i,t}+{\gamma }_{9}Siz{e}_{i,t}+{\gamma }_{10}Scal{e}_{i,t}+{\displaystyle \sum }Year+{\displaystyle \sum }Indus+{\epsilon }_{i,t} \end{gathered}$$

(3)

Among them, that represents the enterprise and represents the year. $\alpha$, $\beta$, $\gamma$ is the regression coefficient; $\epsilon$ is the error term.

The regression coefficients are tested sequentially. Model (1) verifies the relationship between corporate environmental information disclosure and corporate financing efficiency, where ${\alpha }_1$ reflects the total effect of corporate environmental information disclosure on financing efficiency. Model (2) tests the relationship between corporate environmental information disclosure and corporate social responsibility. Model (3) tests the mediating effect of corporate social responsibility as a mediating variable in the effect of corporate environmental information disclosure on corporate financing efficiency, which reflects ${\gamma }_1$, the direct effect of corporate environmental information disclosure on financing efficiency, and the ${\beta }_1$ and ${\gamma }_2$ reflect the mediating effect of the mediating variable, i.e., CSR.

4. Empirical Tests and Analysis of Results

4.1. Descriptive Statistical Analysis

The descriptive statistical results of the main variables are shown in

Table 2. Descriptive statistics of variables.

Variable Name	Number of Samples	Average Value	Standard Deviation	Minimum Value	Maximum Value
CSR	1188	27.80	17.22	−0.0600	77.72
Audit	1188	0.110	0.313	0	1
Property	1188	0.747	0.435	0	1
Lev	1188	0.517	0.185	0.0673	0.884
ROA	1188	0.0379	0.0352	−0.0138	0.196
Growth	1188	0.716	2.975	−0.682	24.24
Size	1188	23.22	1.587	19.62	28.04
Scale	1188	9.510	2.293	0	18
EID	1188	0.430	0.495	0	1
Cont	1188	41.46	17.11	10.80	83.43
FE	1188	0.0660	0.0627	−0.0776	0.355

. The mean value of the explanatory variable EID is 0.430 and the standard deviation is 0.495, indicating that the environmental information disclosure of A-share listed energy enterprises in China is not optimistic. Among them, only 43% of enterprises disclose environmental-related information in their social responsibility reports, which shows that the environmental awareness and social responsibility of most energy enterprises are still weak, or the environmental control work is not perfect. The average value of the intermediate variable CSR is 27.80, which is far from passing level. The maximum value of 77.72, the minimum value of −0.0600, and a standard deviation of 17.22 reflects to a certain extent the low overall social responsibility rating of A-share listed energy enterprises in China and the large gap in ratings between enterprises, which is basically in line with the hypothesis expectations. The maximum value of the explanatory variable EF is 0.355, the minimum value is −0.0776, and a standard deviation is 0.0627. The standard deviation is 0.0627, which indicates that the financing efficiency gap between China’s A-share listed energy enterprises is large, and even some of them are in loss, reflecting the overall low financing efficiency of the sample enterprises. The rest of the control variables, in general, are in a reasonable range and fluctuation, which ensures the reliability of the data in this paper to a certain extent.

4.2. Correlation Analysis

The results of the correlation analysis of each variable are shown in

Table 3. Test results of correlation coefficient of variables.

	FE	EID	CSR	Audit	Cont	Propery	Lev	ROA	Growth	Size	Scale
FE	1
EID	0.00500	1
CSR	0.265 ***	0.473 ***	1
Audit	0.00100	0.302 ***	0.186 ***	1
Cont	0.160 ***	0.167 ***	0.139 ***	0.213 ***	1
Property	−0.082 ***	0.256 ***	0.131 ***	0.143 ***	0.404 ***	1
Lev	−0.067 **	0.073 **	−0.029	0.015	0.005	0.248 ***	1
ROA	0.856 ***	−0.053 *	0.207 ***	−0.009	0.138 ***	−0.149 ***	−0.395 ***	1
Growth	−0.0330	−0.134 ***	−0.115 ***	−0.074 **	−0.059 **	−0.056 *	0.084 ***	−0.026	1
Size	−0.0050	0.412 ***	0.211 ***	0.427 ***	0.471 ***	0.375 ***	0.341 ***	−0.105 ***	−0.137 ***	1
Scale	0.0380	0.231 ***	0.194 ***	0.151 ***	0.156 ***	0.256 ***	0.237 ***	−0.044	−0.073 **	0.331 ***	1

Note: ***, **, * represent significant at 1%, 5%, 10% level of significance, respectively.

. The correlation coefficient between EID of environmental-related information disclosed by enterprises and FE of corporate financing efficiency is 0.00500, which can be preliminarily judged to have a linear correlation and a positive relationship, indicating that disclosure of environmental-related information in social responsibility reports of energy enterprises is conducive to improving the financing efficiency of enterprises, which preliminarily verifies hypothesis H1. The research shows that the correlation is positive; the surveyed companies that disclose environmental information in their social responsibility reports achieve better financing efficiency. Therefore, hypothesis H1 is considered confirmed. The correlation coefficient between EID and CSR rating is 0.473, which is significantly positive at the 1% level, indicating that disclosure of environment-related information in social responsibility reports of energy enterprises is conducive to improving CSR ratings, and is the preliminary verification of hypothesis $\mathrm{H}2$. Among the remaining variables, the correlation coefficients are less than 0.5, except for the correlation coefficient between ROA and FE, which is 0.856, tentatively indicating that there is no serious multicollinearity among the remaining variables.

In the actual modeling process, due to the large dataset and sample size, it is almost impossible to have a very strict linear relationship between some variables. Therefore, when there is a certain degree of correlation (approximately collinearity) between explanatory variables, it can also be called multicollinearity. When multicollinearity occurs, the result of parameter estimation is no longer valid. Therefore, we use a variance expansion factor (VIF) test to exclude some variables with multicollinearity before regression analysis. VIF refers to the ratio of the variance when there is multicollinearity between explanatory variables to the variance when there is no multicollinearity, which can reflect the increase in variance caused by multicollinearity.

When defining variables, this paper uses the formula “Return on equity × [1 − weighted average cost of capital × (1 + financial leverage coefficient)] × 100%” because ROA and the “Return on Equity” (ROE) in the formula have a certain positive correlation in the definition and calculation; it really makes the correlation coefficient between ROA and the final explained variable FE larger. Therefore, to further test the impact of multicollinearity among variables on the overall regression model, we conducted the variance inflation factor (VIF) test among variables. According to the test results in

Table 4. Variance expansion factor test.

Variable	VIF	1/VIF
Size	2.05	0.481
Count	1.51	0.647
Property	1.37	0.677
CSR	1.28	0.719
Audit	1.28	0.775
Lev	1.27	0.781
Scale	1.18	0.805
ROA	1.02	0.842
Growth	1.01	0.953
Mean VIF	1.33	-

, the mean VIF was 1.33, far less than 10, which can prove that there is no significant multicollinearity between model variables.

The commonly used indicators to judge multicollinearity are tolerance and variance inflation factor (VIF), which are reciprocal to each other. In general, the closer the tolerance is to 1, the weaker the multicollinearity. Theoretically, the minimum value of the variance inflation factor is 1. If it is greater than 10, it indicates that there is a serious multicollinearity. If it is less than or equal to 10, the multicollinearity is weak. The smaller the value, the weaker the multicollinearity. According to the test results in the table, the VIF value of each variable is less than 10, and the average VIF is 1.33, indicating that the multicollinearity among the explanatory variables is weak, and there is no serious multicollinearity.

To further test the effect of multicollinearity among the variables on the regression model, the VIF variance inflation factor test among the variables was conducted. According to the test results, the mean value of VIF is 1.33, which is much less than 10, and it can be proved that there is no multicollinearity among the model variables.

4.3. Regression Results and Analysis of Mediating Effects

From the regression results in

Table 5. Regression results of intermediate effects.

	(1)	(2)	(3)
Variable Name	FE	CSR	FE
EID	0.005 *	11.705 ***	0.002
	(1.81)	(4.82)	(0.78)
CSR	-	-	0.0003 ***
			(4.26)
Audit	−0.010	0.796	−0.010
	(−0.81)	(0.16)	(−0.90)
Cont	0.0002	0.025	0.0002
	(1.22)	(0.30)	(1.19)
Property	0.005	−0.191	0.005
	(0.81)	(−0.04)	(0.71)
Lev	0.133 ***	−6.648	0.135 ***
	(7.65)	(−1.14)	(7.80)
ROA	1.797 ***	104.960 ***	1.770 ***
	(26.58)	(5.08)	(26.97)
Growth	−0.001	−0.366 **	−0.0004
	(−1.48)	(−2.07)	(−1.18)
Size	−0.005	4.279 **	−0.006
	(−1.07)	(2.60)	(−1.33)
Scale	−0.001	0.181	−0.001
	(−0.83)	(0.41)	(−0.91)
Constant	0.062	−67.452	0.079
	(0.64)	(−1.55)	(0.84)
Observations	1188	1188	1188
Number of Stands	182	182	182
R-squared	0.831	0.356	0.834

Note: ***, **, * represent significant at 1%, 5%, 10% significance level respectively, t-value in parentheses.

, environment-related information disclosure (EID) is significantly and positively related to corporate financing efficiency (FE) at the 10% level, and the regression coefficient ${\beta }_1$ = 0.005 is the total effect of enterprise environment-related information disclosure on corporate financing efficiency, indicating that disclosure of environment-related information in social responsibility reports of China’s A-share listed energy enterprises has a significant positive impact on improving corporate financing efficiency. Hypothesis H1 has been verified. From the perspective of financing constraints, this result is also consistent with the research of Zhang Huiming et al. (2022), Wang Shanyong et al. (2020), Zhan Hua and Hou Mengting (2021), Li et al. (2018), and Alsayegh et al. (2020). Another scholar explained it from the perspective of bond issuance. From the perspective of corporate financial performance, Wang’s (2020) [6] and Xie’s (2019) [68] research also shows that environmental information disclosure has a direct impact on financial performance.

In model (2), the regression coefficient 𝛼₁ between environmental-related information disclosure (EID) and corporate social responsibility (CSR) is 11.705, which is significantly positive at the level of 1%, and hypothesis H2 is verified, indicating that the disclosure of environmental-related information by A-share listed energy enterprises in social responsibility reports can promote the improvement of social responsibility scores, which is consistent with the research of Zhang Zhe and Ge Shunqi (2021) [12]. It also conforms to the research assumption of Xu Wei and Gao Qinfeng (2022) [59] that “environmental information disclosure is an important channel for enterprises to fulfill their environmental responsibilities”. In the social responsibility report, energy enterprises disclose information on environmental costs, capital investment, measures taken, and results achieved by enterprises in environmental management, which, on the one hand, reduces the information asymmetry among enterprises, investors, and creditors, thus making it easier for enterprises to obtain financing loans; on the other hand, it improves the social public image and social credibility of enterprises, transmits positive signals of enterprise development to more stakeholders, strengthens the business cooperations and partnerships between energy enterprises and downstream enterprises, and improves the financing efficiency of enterprises.

In model (3), the regression coefficient between corporate social responsibility (CSR) and corporate financing efficiency (EF) is 𝛾₂ = 0.0003, which is significantly positive at the level of 1%, meaning that the improvement of corporate social responsibility score helps to improve corporate financing efficiency, which is consistent with the research results of Li Yin (2019). The improvement of the corporate social responsibility score reflects the comprehensive improvement of the five indicators of the enterprise in terms of shareholder responsibility, employee responsibility, supplier, customer and consumer rights and interests responsibility, environmental responsibility, and social responsibility, which may improve the financing efficiency of the enterprise while enhancing the corporate responsibility and reputation. Since the regression coefficients 𝛼₁ and 𝛾₂ are significantly positive, it indicates that the transmission path of “disclosure of relevant environmental information—social responsibility score—financing efficiency” of the intermediary role is established, and hypothesis H3 is verified. In this model, the regression coefficient between corporate environmental information disclosure (EID) and financing efficiency (FE) 𝛾₁, that is, the direct effect of the independent variable on the dependent variable, is no longer significant, while the mediating variable corporate social responsibility score (CSR) still has statistical significance, indicating that the mediating effect of China’s A-share listed energy corporate social responsibility (CSR) on the relationship between corporate environmental-related information disclosure and corporate financing efficiency is completely intermediary.

(1) Analysis of property right heterogeneity

To test the heterogeneous performance of environmental information disclosure of enterprises with different property rights on financing efficiency, the sample is divided into two groups: state-owned and non-state-owned. According to the regression results in

Table 6. Property right heterogeneity.

	(1)		(2)		(3)
Variable Name	FE		CSR		FE
Enterprise Nature	State-Owned Enterprise	Non-State-Owned Enterprise	State-Owned Enterprise	Non-State-Owned Enterprise	State-Owned Enterprise	Non-State-Owned Enterprise
EID	0.002 *	0.004 ***	11.953 ***	14.558 **	0.002	0.006
	(0.51)	(5.25)	(3.61)	(13.48)	(0.35)	(0.34)
CSR	—	—	—	—	0.0002 **	0.0003 ***
	—	—	—	—	(4.01)	(2.85)
Constant	0.13	0.05	−59.061	9.25	0.127	−0.536
	(1.15)	(2.27)	(−3.33)	(1.64)	(0.84)	(−2.34)
Observations	401	787	401	787	401	787
R-squared	0.873	0.831	0.327	0.480	0.872	0.837

Note: ***, **, * represent significant at 1%, 5%, 10% significance level respectively, t-value in parentheses; the industry dummy variable (Indus) to control the impact of the industry, and the annual dummy variable (year) to control the impact of the year.

, both state-owned and non-state-owned A-share listed energy enterprises, and the assumptions in this paper, are valid. The comparative effect can be found that environmental information disclosure plays a significant role in promoting the financing efficiency of non-state-owned energy enterprises than state-owned energy enterprises. From the perspective of intermediary effect, in non-state-owned enterprise groups, considering that different ownership of enterprises often leads to large differences in management structure, business philosophy and methods, as well as government intervention, the impact of corporate social responsibility performance on enterprises with different property rights is not the same. Higher corporate social responsibility is often conducive to enterprises seeking more financing from financial institutions and investors. The state-owned enterprises themselves have a strong sense of social responsibility, and the requirements for environmental information disclosure have less impact on them. However, they have strong constraints on non-state-owned enterprises, forcing non-state-owned enterprises to pay attention to environmental issues and invest more enterprise resources in environmental governance. Relatively excessive resource consumption is not conducive to enterprise financing. Therefore, the impact of environmental information disclosure on state-owned enterprises is relatively small, but it has a greater impact on non-state-owned enterprises.

(2) Heterogeneity analysis of industrial pollution degree

This paper refers to the Catalogue of Classified Management of Environmental Protection Verification Industries of Listed Companies issued by the Ministry of Environmental Protection in 2008, and further classifies the sample enterprises into heavy pollution industries and non-heavy pollution industries according to their industries and conducts a sample heterogeneity test. It can be seen from the regression results in

Table 7. Heterogeneity test of industrial pollution degree.

	(1)		(2)		(3)
Variable Name	FE		CSR		FE
Enterprise Nature	Enterprises in Heavily Polluting Industries	Enterprises in Non-Heavy Pollution Industries	Enterprises in Heavily Polluting Industries	Enterprises in Non-Heavy Pollution Industries	Enterprises in Heavily Polluting Industries	Enterprises in Non-Heavy Pollution Industries
EID	0.005 *	0.002 **	12.467 ***	10.523 *	0.007	0.006
	(0.62)	(3.15)	(4.11)	(10.28)	(0.35)	(0.34)
CSR	—	—	—	—	0.0012 **	0.0004 *
	—	—	—	—	(3.73)	(2.06)
Constant	0.26	0.13	−32.497	11.24	0.127	−0.536
	(1.15)	(2.27)	(−3.33)	(1.64)	(0.84)	(−2.34)
Observations	420	768	420	768	420	768
R-squared	0.623	0.734	0.446	0.531	0.642	0.730

Note: ***, **, * represent significant at 1%, 5%, 10% significance level respectively, t-value in parentheses; the industry dummy variable (Indus) to control the impact of the industry, and the annual dummy variable (year) to control the impact of the year.

that, in the sub-sample test, the overall conclusion is still consistent with the conclusion of the basic regression species, and compared with enterprises in non-heavily polluting industries, the positive impact of environmental information disclosure of enterprises in heavily polluting industries on their financing efficiency is more significant. To gain financing advantages in the fierce capital market competition, listed energy enterprises that belong to the highly polluting industries can reduce the degree of information asymmetry with various stakeholders and improve environmental reputation through more active environmental information disclosure.

According to the regression results of the above sample data, we believe that there is only an indirect promotion effect mediated by the social responsibility score for the impact of environmental-related information disclosure on corporate financing efficiency in the social responsibility report of China’s A-share listed energy enterprises. Corporate social responsibility is a kind of corporate behavior or commitment with positive significance to society. The corporate social responsibility score adopted in this paper can reflect corporate social responsibility in general, while the voluntary disclosure of relevant environmental information in the social responsibility report by energy enterprises can reflect that the enterprise has fulfilled its environmental responsibility and social responsibility better, which is manifested in the comprehensive improvement of the corporate social responsibility score, and even the enterprise, the improvement of enterprise value [69] and social recognition will ultimately be reflected in the improvement of enterprise financing efficiency.

4.4. Robustness Test

To further test the robustness of the model, this paper tests the main model by replacing the panel model (consider replacing the original double panel fixed-effect model with a multidimensional panel fixed-effect model that does not change over time and specific industries). The test results are shown in

Table 8. Regression results of multidimensional panel fixed-effects model.

Variable Name	FE
EID	0.006 ***
	(3.71)
Audit	−0.001
	(−0.48)
Cont	0.000 ***
	(3.77)
Property	−0.003
	(−1.23)
Lev	0.112 ***
	(21.61)
ROA	1.714 ***
	(72.79)
Growth	−0.001 **
	(−2.53)
Size	−0.001 *
	(−1.81)
Scale	0.000
	(0.05)
Constant	−0.034 **
	(−2.24)
Observations	1184
R-squared	0.855
F test	0
r2_a	0.850
F	637.1

Note: ***, **, * represent significant at 1%, 5%, 10% significance level respectively, t-value in parentheses.

. The intermediary effect of the corporate social responsibility test is represented by replacing the intermediary variable (replacing the intermediary variable with “corporate social responsibility rating”). The test results are shown in

Table 9. Regression results for substitution variables.

	(1)	(1)
Variable Name	CSR	FE
EID	0.576 ***	0.003
	(16.46)	(1.59)
CSR	-	0.006 ***
		(4.04)
Audit	0.077	−0.002
	(1.40)	(−0.65)
Cont	−0.001	0.000 ***
	(−0.68)	(3.88)
Property	−0.023	−0.003
	(−0.52)	(−1.18)
Lev	−0.093	0.113***
	(−0.85)	(21.85)
ROA	1.178 **	1.708 ***
	(2.38)	(72.81)
Growth	−0.000	−0.001 **
	(−0.03)	(−2.55)
Size	0.010	−0.001*
	(0.66)	(−1.90)
Scale	0.002	0.000
	(0.26)	(0.01)
Constant	1.791 ***	−0.045 ***
	(5.55)	(−2.88)
Observations	1184	1184
R-squared	0.421	0.857
F test	0	0
r2_a	0.401	0.852
F	39.67	582.7

Note: ***, **, * represent significant at 1%, 5%, 10% significance level respectively, t-value in parentheses.

. The regression results support the original conclusion.

(1) Panel model replacement

To ensure the robustness of the empirical results, a multidimensional panel fixed-effects model that does not change over time and specific industries is considered to replace the original double panel fixed-effects model. The specific regression results are shown in Table 8, and the regression coefficients of the explanatory variables are still significantly positive, which is consistent with the original test results and proves the robustness of the empirical findings of this paper.

(2) Substitution of mediating variables

The mediating effects model adopted in this paper involves CSR as a mediating variable, which is quantified by taking the Hexun CSR score in the regression. Since there is no specific quantitative representation of CSR in the current study, this paper conducts robustness tests by replacing this mediating variable, considering the measurement error of CSR scores and the fact that CSR ratings tend to classify enterprises with the same level of social responsibility performance into different categories and grades, which can reflect the differences in social responsibility performance among enterprises at a larger level. Therefore, this paper replaces the mediating variable with “CSR rating” to represent CSR. The results of the robustness tests through model (2) and model (3) are shown in Table 9, which show that the main conclusions of the regression part still hold under the new variables and prove the robustness of the empirical findings of this paper.

4.5. Discussion

From the above empirical analysis, the research results of this paper verify hypothesis H1, hypothesis H2, and hypothesis H3. It is shown that disclosure of environment-related information in social responsibility reports by energy enterprises is proven to improve the financing efficiency of enterprises, and corporate social responsibility plays an intermediary role between the effects of corporate environmental disclosure on financing efficiency. At the same time, there is consistency with the research conclusions of some scholars, such as that disclosure of environment-related information in social responsibility reports by energy enterprises can improve the financing efficiency of enterprises, like Gerged et al. (2020) [42], Li Xinfei and Li Fangfang (2022) [44], Liu Bai and Liu Chang (2019) [45], and others, and corporate social responsibility plays an intermediary role between the effects of corporate environmental disclosure on financing efficiency, like Fadi et al. (2022) [11], Aureli et al. (2020) [39], Albuquerque et al. (2019) [47], Kraus et al. (2020) [48], Cho et al. (2019) [49], Li Yin (2019) [50], and others.

From the research, it is found that the environmental information disclosure of energy enterprises has a positive impact on improving their financing efficiency. Enterprises’ disclosure of environmental-related information is conducive to improving their social responsibility scores. The higher the social responsibility score, the higher the corporate social responsibility performance level. However, from the actual situation of China’s listed energy enterprises, some energy enterprises’ environmental information disclosure is relatively rough. If energy enterprises compare with each other, some energy enterprises’ social responsibility performance level is low, which also has a negative impact on their financing efficiency. Therefore, to effectively obtain financial support, it is necessary for energy enterprises to actively and effectively disclose environmental information.

5. Research Conclusions and Related Recommendations

5.1. Research Findings

This paper examines the relationship between corporate environmental information disclosure and corporate financing efficiency using data from all A-share listed energy enterprises from 2012 to 2019 as a sample. The research in this paper complements the economic effects of corporate environmental information disclosure and the influence pathways of corporate financing efficiency while expanding and exploring the research on the relationship between corporate environmental information disclosure and financing efficiency. The research results verify hypothesis H1, hypothesis H2, and hypothesis H3 that the surveyed companies that disclose environmental information and have higher CSR ratings achieve higher financing efficiency; the disclosure of environmental information in the social responsibility reports of the surveyed energy companies positively affects their CSR ratings, and CSR ratings positively affect financing efficiency, and CSR plays the role of an intermediary between the impact of the company’s environmental disclosures on the financing efficiency of the surveyed companies.

The study shows that: (1) the disclosure of environmental information by energy enterprises in China is less optimistic, and the level of social responsibility performance among energy enterprises varies greatly; (2) the disclosure of environment-related information in social responsibility reports by energy enterprises can significantly improve corporate financing efficiency; (3) the disclosure of environment-related information by enterprises can significantly promote the improvement of social responsibility scores, reflecting the improvement of the corporate social responsibility performance level; and (4) corporate social responsibility plays a fully intermediary role between environmental information disclosure and financing efficiency.

5.2. Research Recommendations

(1) Energy companies should pay attention to and actively disclose environmental information

Since the disclosure of environmental information is largely voluntary in China, the disclosure of environmental information often imposes certain costs on enterprises and may lead to a decline in their earnings. However, managers should focus on the long-term development of enterprises, the improvement of enterprise value, and the positive economic and social effects brought by environmental information disclosure. According to the results of the study, the active disclosure of environmental information by energy enterprises can not only win a good reputation for the enterprises but also alleviate the information asymmetry between the enterprises and various stakeholders, thus reducing the financing pressure faced by listed enterprises to a certain extent and enhancing the enterprise value. On the other hand, environmental information disclosure can also improve the efficiency of corporate financing and bring economic benefits to enterprises by improving their financial performance. In addition, enterprises should disclose environmental information in a timely, complete, and standardized manner to improve the quality of environmental information disclosure as much as possible.

(2) Energy enterprises should strengthen their social responsibility awareness and actively fulfill their social responsibility

The performance of CSR is reflected in the CSR score, which can convey corporate information to society and stakeholders, thus influencing business development. Especially for energy enterprises, their relative weakness in environmental responsibility often leads to greater external financing constraints and limits the development of the company. Therefore, energy enterprises should pay more attention to their social responsibility performance and increase their investment in technological innovation and research on “energy saving and emission reduction”.

(3) Suggestions on accelerating the policy requirements related to environmental information disclosure of enterprises in China

At present, environmental issues are still an important factor limiting the high-quality and sustainable development of China, and energy enterprises are highly concerned by society and the government because of their natural “pollution” characteristics, and therefore take more environmental responsibilities. From the sample data, the number of A-share listed energy enterprises disclosing environmental information in their social responsibility reports is still small, indicating that the environmental awareness and social responsibility of most energy enterprises are still unsatisfactory. It is recommended to strengthen the intensity of environmental regulation to restrain or to set separate regulatory constraints for energy industry enterprises.

The research verifies the hypothesis and reflects the effective research conclusions. However, due to the fact that some of the energy enterprises listed on the A-share market in China have not disclosed environmental information, and these enterprises are not in the study sample, the study sample data are limited. In the future, it is expected that the research in this field can obtain more comprehensive and effective data and conduct more in-depth research. At the same time, it will be very meaningful to explore the relationship between corporate social responsibility, environmental information disclosure, and financing efficiency from multiple perspectives.