Does environmental information disclosure affect the performance of energy-intensive firms’ borrowing ability? Evidence from China

Abstract

In recent years, a growing strand of China’s listed companies chose to disclose environmental information, which may potentially affect their financial performance then further influence its performance of financial supports. To quantitatively investigate the impact of enterprise’s environmental information disclosure on the ability of firms’ borrowing in China, this paper divides the measurements of information disclosure into five categories and evaluates firms’ performance in capital market through its availability of a loan and the cost of capital. In total, 97 listed energy-intensive companies in China are selected and their data covering the period of 2000–2014 are utilized for empirical study. The empirical results indicate that enterprise’s environmental information disclosure appears to have a significantly positive effect on the loan size available, while the cost of capital is less sensitive to environmental information disclosure. The empirical evidence also suggests that, among the five aspects of information disclosure measurements, the future plan and monetary information are the most influential factors of the cost of capital.

Keywords

Environmental information disclosure green finance green credit China cost of capital capital market value

Introduction

As a large newly industrialized country, China was used to be heavily dependent on natural resources and energy in the process of development.^1,2 Over exploitation and excessive use of resources and energy have lasted for decades. The rapid economic growth during the past few decades was achieved at huge environment cost and the lives of many Chinese citizens were severely affected.^3,4 One prominent problem related with massive energy consumption is serious air pollution.^5,6 In December 2015, Beijing municipal government for the first time issued red alerts for severe air pollution since the emergency alert system⁷ was established in 2014.^a Nowadays, environmental degradation has posed a grave threaten for China’s sustainable economic growth, and Chinese government is currently facing various environmental catastrophes nearly on a daily basis, including air and water pollution, desertification, sharp decrease in biodiversity, and mounting environmental pressures caused by extensive growth of population and fast urbanization (Zhang et al., in press).^8,9b Pretty deregulated environmental oversight in China has given rise to its environmental problems, which are notorious at home and abroad. Although Chinese central government has acted affirmatively to deal with severe environmental pollution, the effect is still far from satisfactory until now. According to World Development Indicators 2006 profiled by the World Bank, 13 out of 20 of the world’s most polluted cities are found in China and government response is criticized as inadequate.

As Yuan et al.¹⁰ , Zhang YJ and Hao,¹¹ and Zhang et al.¹² argued, to avoid environmental degradation without sacrificing the standard of living, the importance of clean energy in energy mix and economic development must be increased sufficiently, which requires extensive adoption of clean energy technologies. Specifically, not only carbon-free energy but also energy-efficient technologies that reduce energy demand are in dire need.¹² Large-scale deployment of clean energy technology can be successful only when clean energy achieves competitive pricing. Fossil fuels are traditionally capable of providing cheaper energy than low- or carbon-neutral sources, which makes people tend to use fossil fuels like oil and coal. In this regard, it is of high priority to increase the investment of clean energy and reduce the cost of clean energy. The concept of green finance has therefore arisen and has shown early success. Green finance is now spread all over the world and is widely accepted by many commercial banks, which offer innovative clean energy financing mechanisms to reduce risk and help “standardize” clean energy investments. The core of the green finance for banks is to use loan structures rather than traditional government subsidies to promote clean energy project investment and accelerate the change to energy independence.¹³

Swim et al.¹⁴ found empirical evidence that changes in both population and consumption behaviors significantly contributed to the increase in carbon emissions over the last three decades in China. As the most directly affected victims, inhabitants in China have realized the severity of environmental pollution and began to try to battle against polluting activities, which causes the government to pay more attention to the balance between economic development and environment pollution. To further improve the environmental quality, Chinese central government had already formulated targeted policies to cut emissions of major pollutants and reduce the energy intensity (energy use per unit of GDP).⁸ In 2014, the Chinese government amended environment protection laws to make stricter regulations for pollution and to reverse environmental damage in the country. Nevertheless, it might be more efficient and straightforward to reduce environmental pollution by advocating or requiring pollution-intensive companies to take more environmental responsibilities. This is because enterprises in energy- and pollution-intensive industries are generally more responsible for most of the pollutant emissions than ordinary citizens.¹⁵ The big open question is how to ask high-polluting companies to impulsively take responsibilities for environmental pollution at the expense of their benefits.

In fact, the negative environmental impact of high-polluting companies has already been widely noticed and become a worldwide problem since the mid-20th century. In the meantime, various policies and measures have been taken to improve environmental quality, among which financial policies should be given particular attentions. This is because financial institutions could play an important role in supporting environmentally friendly projects and limiting those projects which have potential risks to damage the environment. In 2002, a group of financial experts established a set of guidelines on the basis of international financial company regulations in the field of project financing to fight against pollution. One year later, in 2003, the Equator Principles (EPs) were formally raised by 79 financial institutions in 35 countries, aiming at promoting financial institutions to take social and environmental responsibilities. The members of Equator Principles Financial Institutions (EPFIs) have increased from the original 10 to 78 in a decade after its establishment. Currently, 84 EPFIs in 35 countries have officially adopted the EPs, covering over 70% of international project finance debt in emerging markets.^c Many scholars have found that the EPs have indeed helped to enhance the awareness of environmental responsibilities of many enterprises and financial institutions since they were originally raised.^16–18 For instance, Scholtens and Dam¹⁶ found that financial institutions that adopted EPs tend to obtain significantly higher ratings of corporate social responsibilities than those of financial institutions which did not.

In recent years, Chinese government has gradually realized that administrative regulatory measures should be combined with market-based policies so that environmental protection policies can turn to achieve the maximum effect. Given the importance of green finance, Chinese government formally launched green credit policy in July 2007 through three agencies: Ministry of Environmental Protection, China Banking Regulatory Commission and People’s Bank of China. This policy, identifying the beginning of the implementation of EPs in China, contains dual purposes: (1) to guide financial resources away from highly polluting and high energy-consuming enterprises and projects and (2) to direct credits and loans toward energy conservation and emission reduction at preferential terms. The governor of China’s central bank, Zhou Xiaochuan, stated in 2006 that China’s financial system should play an increasingly important role in promoting the green transformation of China’s economy.^d In September of that same year, China hosted the G20 Summit, which listed “green finance” as one of the key issues to be discussed.

In China, the idea of “green finance” is developing rapidly with broader intension and extension. Many enterprises, especially those in high-polluting industries, respond to relevant policies via external disclosure of environmental information. Chinese companies used to disclose relevant environmental information only to meet requirements when they need to issue shares or when major environmental events occur. Under the background of serious environmental deterioration, an increasing number of firms have realized that they can benefit from environmental information disclosure because such disclosure can send positive signal to investors and therefore boost the confidence of potential investors of the company. In this regard, there exist some important questions to be answered: What are the impacts of corporate environmental disclosure behaviors? How do they function? To answer these questions, this study makes an innovative research in following aspects. First, to measure the quality of corporate environmental information disclosure accurately, the information disclosure is divided into five aspects so as to make the assessment more comprehensive. Second, the factor of environmental responsibility pressure is introduced into our model so as to compare the borrowing performance of the firms in capital market before and after the implementation of green finance policy. Third, to ensure the accuracy and the reasonability of estimation results, the data of 97 Chinese energy-intensive companies listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange for the period between 2000 and 2014 are collected, with total observations being 1470.^e This study focuses on energy-intensive companies because they are most representative energy consumers and consume the majority amount of energy in China.¹⁹ The usage of data at enterprise-level and therefore micro-level information help lead to more targeted and concrete results.

The rest of this paper is organized as follows. In the next section, the background of research and relevant literature review are given. Then, the methods and data utilized in this study are briefly introduced. Following this, the estimation results are reported and the corresponding discussions are given. Finally, conclusion and policy implications are given.

Background and literature review

At present, China is stepping up efforts to formulate and deploy environmental policies, including environmental tax policy, green credit policy, environmental pollution liability insurance policies, green securities, green trade policy, contract energy management, etc. Among which, the implementation of green finance policy a decade ago is an important breakthrough in environmental governance. In 2016, several institutions, the people’s bank of China, ministry of finance, the China banking regulatory commission and other seven ministries and commissions, jointly issued “guidance on building green financial system”, aiming at establishing a green financial system. And in the G20 summit at the same year, green finance was listed as an important topic for discussion and finally adopted.

Nowadays, more and more people gradually pay attention to environmental problems, thus further promote the government to formulate relevant policies. Meanwhile, high-polluting industries have received increasing attention and their operating activities are under restrictions today, resulting in increasing industry risks and costs for those enterprises as well. Environment protection has long been an important topic for high-polluting industries. For instance, Clarkson et al.²⁰ suggested that proactive environmental strategy and the signaling of such strategy to investors can raise a firm’s stock price. Enterprises’ environmental protection is requested by both environmental protection administration and financial institutions, especially commercial banks. For commercial banks and other lending institutions, they will be more careful in deciding whether to offer loans to firms in high-polluting industries or not because environmental pollution brings financial risks. This causality provides evidence for the hypothesis that environmental protection might be correlated with corporate financial risks.

Bank is served as one of the most important sources of corporate external financing. As an increasing number of international commercial banks have accepted the EPs, Chinese government decided to put emphasis on reality and comply with the international legislative tendency, as a consequence, green finance are finally proposed and implemented. China’s green credit mechanism not only combines sustainable development with economic development, at the same time, it also helps to optimize financial mechanisms and channel funds to green business.

The implementation of green credit mechanism in China exerts impacts on activities of companies. Eiler et al.²¹ indicated that the information content of earnings announcements has increased in the new reporting environment, namely after the implementation of green credit mechanism. In addition to a growing number of environmentally friendly behaviors, more and more firms tend to attach great importance to environmental information disclosure in their annual reports. This behavior helps to increase the information transparency and simultaneously send positive messages to stakeholders. Many researchers start paying attention to the effect of environmental information disclosure for the foregoing realities. Specifically, the extant relevant studies can be classified into three main categories as follows:

The first category is the studies that major in context and motivation of corporate environmental information disclosure. Liu and Anbumozhi²² found that the present condition is that environmental information disclosure strategy of Chinese listed companies is oriented to fill up environmental concerns of government. The effort of corporate environmental information disclosure is significantly related to its environmental sensitivity. By using size-matched groups based on industry membership and environmental performance, Cho and Patten²³ tested the differences between implementation of monetary and non-monetary non-litigation related environmental disclosure and its empirical results provide additional support for the argument that companies use disclosure as a legitimizing tool. Based on 10-K reports from 1998 to 2012, Chen et al.²⁴ examined the potential motivations for US companies to disclose the amount of environmental liability in their financial statements.

The second group of researches intend to figure out factors affecting the level of environmental disclosure. By employing regression analysis to examine environmental information disclosure after a major accident in Canadian mining industry, Magness²⁵ found that companies that maintain themselves in the public eye through press release activity disclose more information than other companies, and companies that obtained external financing one year after accident made more disclosure than other companies. Liu and Anbumozhi²² concluded that the better the company’s economic performance, the more the information disclosure on environmental investment and pollution control cost. Tang and Li²⁶ investigated that whether companies are targeting at businesses or consumers has a bigger impact on their corporate social responsibility communication than whether companies are Chinese or global.

The last category of studies is focusing on the relationship between environmental information disclosure and corporate performance. For example, using a sample of 131 US companies, Patten²⁷ examined the relationship between 1990 annual report environmental disclosures and their environmental performance as based on toxics release data from 1988 and found there is a significantly negative relationship between environmental performance and environmental information disclosure for the sample firms. Al-Tuwaijri et al.²⁸ made an integrated analysis of the interrelations among environmental disclosure, environmental performance and economic performance, and their estimation results suggested that better environmental performance is significantly associated with better economic performance as well as more extensive environmental information disclosure of specific pollution measures. Murray et al.²⁹ found the longitudinal data revealed a convincing relationship between consistently high (low) returns and the predilection to high (low) disclosure. There is no single convincing theoretical explanation as to why this might be. Plumlee et al.³⁰ examined the relationship between the quality of a firm’s voluntary environmental disclosures and firm value by exploring the relationship between the components of firm value (expected future cash flows and cost of equity) and voluntary environmental disclosure quality. Their estimations provide evidence that increased voluntary environmental disclosure quality is associated with firm value via expected cash flow and cost of equity capital components. Arena et al.³¹ documented that the stakeholder orientation of the board plays a transparency role in communicating the firm’s superior performance.

Despite some preliminary studies on the related topics, the existent literature still has some flaws. For instance, the first two types merely focus on the environmental information disclosure behaviors of the companies. In general, these researches investigate the contexts, motivations and influential factors of environmental information disclosure. The third type of literature goes a little further and mainly examines how environment information disclosure affects the economic performance and value of a firm. However, the extant studies did not pay attention to the relationship between environmental information disclosure and important financial indicators especially borrowing ability. Moreover, the studies on Chinese firms are still scarce. In this regard, this study fills the academic gap by examining the influences of environmental information disclosure on firms’ borrowing ability using micro-level data of 97 listed companies in China.

The empirical methods and data

To investigate the impact of environmental information disclosure on capital market value under the background of China’s green finance mechanism, the capital market value is comprehensively measured from two perspectives: corporate borrow and equity capital cost. The scatter plots are produced to intuitively illustrate the trends between environmental information disclosure and capital market value. As shown in Figures 1 and 2, the preliminary conclusion could be drawn that the cost of equity capital and company total loan are positively related to the level of environmental information disclosure.

Figure 1.

The scatter diagram of Tloan against inform.

Figure 2.

The scatter diagram of Equi against inform.

Figure 3.

Industrial distribution of the companies in the sample.

The amount of loan borrowed by a company can to some extent reflect its borrowing capacity. Borrowing capacity of company can be further classified into three catalogs: short-term borrowing, long-term borrowing and total borrowing. In the estimation model of this paper, we conduct multiple regression analysis to determine the influence of environmental information disclosure on corporate borrowing ability.

After the implementation of green credit policy in 2007, both commercial banks and corporations must take the responsibility for environmental pollution according to policy requirements, which brought additional risks and costs to these institutions. Taking year 2007 as time break point, we select environmental responsibility (Response) as another independent variable to distinguish environmental responsibility pressure during the time before and after 2007.

Another independent variable is the corporate environmental disclosures (Inform), which is evaluated according to the available information in corporate annual reports. To obtain an accurate and comprehensive evaluation of corporate information disclosure quality, we divide the information into five aspects: basic environmental information, plans of future environmental measures, the amount of pollutants, the amount of energy consumption and monetized information. Each criterion can be assigned value 1 or 0, which is depended on whether the companies have relative information disclosure. And the independent variable, corporate environmental disclosures, is calculated as the total scores of five aspects.

On the basis of previous studies as well as the basic knowledge of accounting, we define the major financial indexes as control variables to control the influence which is not caused by independent variables. The control variables in our model include the company size, leverage ratio, return on capital, return on total assets in cash, total assets growth rate, turnover of total capital.

The definition and computing methods of control variables and independent variables are listed in Table 1.

Table 1.

Major variables.

Variables	Definition (unit)
Size	The company size, the value of total assets (trillion yuan)
Lev	Leverage ratio
Roc	Return on capital
Recov	Return on total assets in cash
Growth	Total assets growth rate
Turnover	Turnover of total capital
Respons	Environmental responsibility: assign 0 before the year 2007 and assign 1 after the year 2007
Inform	The level of environmental information disclosure, combing scores of Basic, Future, Pollution, Energy, Moneti; 0–5
Basic	Basic environmental information, got 1 with the information, got 0 without the information
Future	Plans of future environmental measures, got 1 with the information, got 0 without the information
Pollution	The amounts of pollutants, got 1 with the information, got 0 without the information
Energy	The amounts of energy consumption, got 1 with the information, got 0 without the information
Moneti	Monetized information in disclosure, got 1 with the information, got 0 without the information

There are only two stock exchanges in the mainland of China (i.e. Shanghai and Shenzhen stock exchanges). The dataset is selected from both Shenzhen and Shanghai stock exchanges. Because the energy- and pollution-intensive industries are focused on in this study, the targeted industries include steel, electronic power, nonferrous metals, coal and oil, and paper printing. The data and information of the listed companies in these industries during the sample period of 2000–2014 are collected, and then the companies which have large amount of missing data especially those related with environmental information disclosure are excluded. In the process of filtering samples, the following criterions are taken into consideration:

New listed companies are ejected because the environmental information disclosure of those companies is not mature, which may be random and cause estimation biases even errors.

Some companies make great changes in their business scope after merger and reorganization, this kind of companies should be excluded.

Some listed companies are in extreme conditions, suggesting that some key financial indexes of these companies are inadequate or missing, and therefore, they have to be dropped from the sample.

After excluding unqualified firms and outliers, 97 energy- and pollution-intensive companies listed in China’s A-share market are chosen as the research sample. The detailed list of sample companies has been added in Table 6 of the AppendixFurthermore, the sample companies have beenclassified into five categories according to the industries they belong to. The shares of the five industrisare shown in Figure 3. Moreover, the distribution of the companies by industry is shown in Table 3. The scatterplot of the ratio of total loans to total assets (Tloan) against the level of information disclosure (inform) are shown intuitively in Figure 1.

There are in total 1470 valid observations in the sample. Financial index data are sourced from the database of Guotaian and Resset.^f The corporate annual reports are collected from the database of Wind and Tide of information network. Data analysis is provided by software Eviews 7. The descriptive statistics of the main variables used in this study are listed in Table 2.

Table 2.

Descriptive statistics of the major variables utilized in this study.

Variables	Definition	Mean	Max	Min	Std. Dev.
COE	Cost of equity	0.253	2.538	−0.763	0.721
Sloan	The ratio of total loans to total assets	1.076	147.05	0	5.193
Lloan	The ratio of long-term loans to total assets	1.131	91.77	0	5.434
Tloan	The ratio of short-term loans to total assets	2.135	206.54	0	9.630
Size	The company size	21.061	1451.37	0.319	957.674
Lev	Leverage ratio	0.552	46.159	0.012	1.206
Roc	Return on capital	0.185	127.612	−9.123	3.342
Recov	Return on total assets in cash	0.073	0.482	−0.238	0.079
Growth	Total assets growth rate	0.182	16.553	−0.800	0.609
Turnover	Turnover of total capital	0.735	6.250	0.050	0.593

It can be seen from Table 2 that the data distribution is balanced and suitable for regression analysis. The mean of company size is about 21 billion, indicating that most sample firms have high level assets scale. The means of short-term loan and long-term loan rates are both greater than one, implying the sample firms have high debt ratios, which can be blamed on characteristics of industries.

In general, the legal system has become continuously improved in China, and there has been increasing environmental responsibility for Chinese enterprises. Before getting loans from commercial banks, the environmental performance of a company would be carefully evaluated because environmental risk is a part of financial risk that lending institutions should take into consideration. Corporate environmental performance exerts an increasing impact on the financial performance of companies, such as financing activity and the cost. Nowadays, high level of information asymmetry still exists between firms and investors, while corporate environmental information disclosure helps eliminate information asymmetry to a certain degree. Wu and Shen³² believed that firms which have good environmental performance will disclose more specific and verifiable information that helps to send an active signal to investors. But firms with poor environmental performance will disclose unverifiable and literal information. Based on this investigation, we thus further put forward two questions: What effect does environmental information disclosure have on enterprise value in capital market? Do verifiable information and literal information have a different impact on the capital market?

To examine the effects of environmental information disclosure on corporate borrowing, combing with the existing conclusion, the following regression model is designed

\begin{matrix} Loans = β + β_{1} ln (S i z e) + β_{2} L e v + β_{3} R o c + β_{4} R e c o v \\ + β_{5} G r o w t h + β_{6} T u r n o v e r + β_{7} R e s p o n s e + β_{8} I n f o r m \end{matrix}

(1)

where Loans contains three categories, which are Tloan (the ratio of total loans to total assets), Lloan (the ratio of long-term loans to total assets) and Sloan (the ratio of short-term loans to total assets), respectively. Some previous studies have utilized these ratios as the measurements of the borrowing ability of a company.³³

To test the effects of environmental information disclosure on the cost of equity capital, we design the regression model as follows

\begin{matrix} Equi = β + β_{1} ln (S i z e) + β_{2} L e v + β_{3} R o c + β_{4} R e c o v \\ + β_{5} G r o w t h + β_{6} T u r n o v e r + β_{7} R e s p o n s e + β_{8} I n f o r m \end{matrix}

(2)

where Equi denotes the cost of equity capital and is calculated according to the capital asset pricing model that is frequently used in recent studies like Da et al.³⁴

{Equi= R}_{f} + β (R_{m} - R_{f})

(3)

where R_m is the expected market return, while R_f is the risk-free return. Therefore, the difference between R_m and R_f is risk premium.

Except for the key regressors, some factors that may affect the performance of a company’s borrowing are also introduced as control variables. For instance, Size (the value of total asset) is a variable to measure the size of company. Lev is defined as the leverage ratio to measure the debt level. Roc is a variable of profitability. Recov (return on total assets in cash) is a variable to measure solvency and cash recovery capacity. Growth is defined as total assets growth rate to measure the potential for development. Turnover (turnover of total capital) is the performance of company operating efficiency. These variables were frequently utilized in the previous studies on companies’ borrowing ability.^35,36 Additionally, given that the regulations require Chinese companies to disclose environmental information after 2007 (although some companies did not fully comply with the regulations), a dummy variable (Response) is also introduced as another control variable to identify whether the time is before or after 2007.

Estimation results and discussion

The relationship between enterprise environmental disclosure and corporate borrowing

According to model 1, we conduct a multivariate regression with sample data to analyze relationship between dependent variables and environmental information disclosure. The results in Table 3 reveal that the levels of the share of short-term loans in total assets (Sloan), the share of long-term loans in total assets (Lloan) and the share of total loans in total assets (Tloan) are all significantly correlated to environmental information disclosure. The regression coefficients of the main independent variable, information disclosure (Inform), are 0.56, 0.74 and 1.32, respectively, in order and all results are statistically significant at the 1% level. The results reveal the regulation on corporate disclosure behavior can impact enterprise loans, namely enterprise is inclined to have higher loan rate with the increasing of environmental information disclosure performance. That is, abundant and high-qualified environmental disclosure brings company advantages in borrowing from commercial banks. It also indicates that lending institutions will take corporate environmental disclosure into account and the more information a firm discloses, the more loans it can get. The results provide the evidence for conclusion that corporate environmental information disclosure is an important factor that cannot be neglected in financial activities.

Table 3.

Regression results of equation (1).

Model	(1)	(2)	(3)
D.Var.	Sloan	Lloan	Tloan
Respons	0.4108	−0.0514	0.4573
	(0.3166)	(0.3323)	(0.5852)
Inform	0.5564***	0.7372***	1.3228***
	(0.1094)	(0.1148)	(0.2022)
Lev	0.0744	0.0900	0.1575
	(0.1104)	(0.1159)	(0.2041)
Roc	0.1538***	0.0726*	0.2256***
	(0.0398)	(0.0418)	(0.0736)
Recov	0.6810	4.7409***	4.7409
	(0.3928)	(1.8193)	(3.2042)
Growth	−0.1237	−0.0789	−0.1786
	(0.2190)	(0.2298)	(0.4047)
Turnover	0.4685**	−0.1039	0.3601
	(0.2274)	(0.2387)	(0.4204)
C	−0.2907	−0.0967	−0.4965
	(0.2861)	(0.3003)	(0.5289)
Obs.	1470	1470	1470
Adj-R²	0.0469	0.0431	0.0532

Note：***, ** and * represent the significance levels of 1%, 5% and 10%, respectively. The numbers in the bracket are standard errors of the corresponding estimated coefficients.

In addition to corporate environmental information disclosure, loan levels are considered to be correlated with corporate return on capital (Roc) as well. The results show that coefficient of Lloan is 0.0726 and is statistically significant at the 10% level while coefficients of Sloan and Tloan are 0.1538 and 0.2256, respectively, and both are statistically significant at the 1% level. As a result, the return on capital (Roc) is important to both short-term and long-term loans because to some extent it reflects the earning power. Besides, Sloan is correlated to turnover of total capital in the significance level of 5% and Lloan is correlated to Return on total assets in cash (Recov) in the significance level of 1%. Compared to the situation of long-term loan, commercial banks attach greater importance to liquidity than other factors when they loan out short-term loans. In contrast, value return and long-term value of the company are more important for lending institutions in terms of long-term loans.

In general, the level of information disclosure is estimated to be significantly and positively related to the ratio of loans to total assets, which reflect to some extent the ability of borrowing. As a result, the results indicate that the energy-intensive companies that are more transplant in environmental information are more likely to get loans from commercial banks and financial institutes, suggesting that higher level of environmental information disclosure would lead to stronger borrowing ability of energy-intensive companies. One possible explanation for this finding is that, as China takes environmental protection more seriously and Chinese citizens pay increasing attentions to the environmental quality, the traditionally energy- and pollution-intensive companies and firms that disclose more environmental information might be treated to be more responsible to the society and generally more confident to the fierce market competition. As for the commercial banks, the pressure from the government has become increasingly high as the government has announced a growing number of policies and regulations to encourage banks that give loans to environmentally friendly companies and limit loans to high-polluting firms. In general, the energy- and pollution-intensive companies are required to reasonably dispose and reduce waste. Otherwise, they would be punished and find it difficult to get new loans from commercial banks and financial institutions. Although the risk of lending money to energy- and pollution-intensive companies is relatively higher compared with other companies, the environment information disclosure would effectively reduce the level of information asymmetry and relevant risk. As such, the commercial banks and financial institutes are more willing to lend loans to these companies with relatively high level of environmental disclosure.

The relationship between enterprise environmental disclosure and the cost of equity

According to the research of Murray et al.,²⁹ there is no direct relationship between share returns and disclosure. However, the longitudinal data reveals a convincing relationship between consistently high (low) returns and the predilection to high (low) disclosure. Magness²⁵ indicated that the significance of external financing variable is evident when disclosure is restricted to discretionary or non-financial items, but disappears if the dependent variable represents mandatory financial items.

As such, another group of multivariable regressions are conducted to estimate equation (2), and then the key variable of inform is replaced by basic, future, pollution, energy and moneti, respectively. These indicators are different aspects of environment information disclosure, and the corresponding estimation results are presented in the six columns of Table 4. It can be seen from Table 4 that there is a significant relationship between cost of equity capital and disclosure of future environmental plan, and regression coefficient is 0.07 at the 10% significance level. Thus, the results imply that disclosure of future environmental plan causes increasing cost of equity. However, the cost of equity capital has significantly negative correlation with monetary environmental information disclosure, whose significance level is 1% and the regression coefficient is −0.19. The disclosure of other three aspects of environmental information does not have significant relationship with cost of equity. These results indicate that capital market investors are more sensitive to future and monetary information and we can conclude that investors do not respond to literal information in general. Moreover, excessive literal disclosure (future plan) may send a bad signal to investors and lead to rising cost. On the other hand, monetary information is easier to be understood by investors, while the information about pollution and energy consumption is usually too professional for ordinary investors to respond to.

Table 4.

Regression results of equation (2).

Model	(1)	(2)	(3)	(4)	(5)	(6)
Respons	0.4335***	0.4279***	0.4022***	0.4442***	0.4270***	0.4575***
	（0.0432）	（0.0747）	（0.0406）	（0.0395）	（0.0390）	(0.0388)
Inform	−0.0099
	（0.0126）
Basic		0.0013
		（0.0438）
Future			0.0744*
			（0.0421）
Pollution				−0.0744
				（0.0555）
Energy					0.0091
					(0.0570)
Moneti						−0.1895***
						(0.0610)
Size	0.0012	−0.0009	−0.0030	−0.0002	−0.0008	−0.0007
	（0.0283）	（0.0284）	（0.0282）	（0.0282）	（0.0282）	（0.0281）
Lev	−0.0070	−0.1349	−0.1636	−0.1252	−0.1359	−0.1163
	（0.0150）	（0.0993）	（0.0997）	（0.0986）	（0.0988）	（0.0982）
Roc	−0.0074	−0.0071	−0.0069	−0.0072	−0.0071	−0.0072
	（0.0054）	（0.0054）	（0.0054）	（0.0054）	（0.0054）	（0.0054）
Recov	0.4540*	0.3951*	0.3528	0.4170*	0.3931*	0.4565*
	（0.2367）	（0.2387）	（0.2382）	（0.2375）	（0.2378）	（0.2372）
Growth	0.0286	0.0323	0.0332	0.0316	0.0324	0.0304
	（0.0299）	（0.0300）	（0.0299）	（0.0299）	（0.0300）	（0.0299）
Turnover	−0.0202	−0.0236	−0.0248	−0.0197	−0.0241	−0.0187
	（0.0310）	（0.0310）	（0.0309）	（0.0310）	（0.0312）	（0.0309）
C	0.0037	0.0866	0.1143	0.0732	0.0873	0.0719
	（0.2752）	（0.2821）	（0.2808）	（0.2806）	（0.2808）	（0.2798）
Obs.	1470	1470	1470	1470	1470	1470
Adj-R²	0.0831	0.0839	0.0859	0.0850	0.0839	0.0899

Note: ***, ** and * represent the significance levels of 1%, 5% and 10%, respectively. The numbers in the bracket is are standard errors of the corresponding estimated coefficients. The dependent variable of all regressions in Table 4 is Equi, which denotes the cost of equity capital and is defined by equation (3).

The cost of equity is significantly correlated with environmental responsibility at the 1% level with 0.43 coefficient, which means after the implementation of green credit mechanism, the pressure of environmental responsibility results in the rising cost in capital market.

As shown in Figure 1, the sample companies are distributed in five major industries. For further research on the environmental information disclosure in different industries, the whole sample is divided into five sub-samples, for which the multivariable regressions based on model 2 are conducted separately. The corresponding results are reported in Table 5.

Table 5.

Regression results of equation (2) for five individual industries.

Industry	(1)	(2)	(3)	(4)	(5)
Respons	0.6309***(0.0912)	1.7404**(0.7788）	0.3105**(0.1455）	0.4530***(0.1365）	1.9547***(0.5236）
Inform	−0.2655**(0.1164）	−0.4069(1.2044）	−0.0260(0.0400）	0.0393(0.0525）	1.9566***(0.6706）
Size	0.0091(0.0189）	−10.9529***(3.7460）	−0.5192(0.4461）	0.2857(0.2386）	−1.5509***(0.3441）
Lev	−0.2491(0.1720）	4.8213***(1.8263）	−0.3606(0.2493）	−0.2653(0.3552）	9.0156***(1.4599）
Roc	1.1305***(0.3956）	0.1899***(0.0456）	0.5061(0.5407）	0.2854(0.4545）	2.4577(2.2446）
Recov	−0.0096(0.5764）	6.3349(4.4506）	0.4302(0.7506）	1.9107(1.2698）	2.1182(3.0274）
Growth	−0.0088(0.0323）	−0.8790(1.1837）	0.0039(0.0358）	0.0721(0.2987）	0.0837(0.5656）
Turnover	−1.0841***(0.3725）	2.4061***(0.9088）	−0.6631*(0.3403）	−0.4072(0.2473）	−0.3898(1.9759）
C	0.6491***(0.2373）	−2.7059*(1.1680）	0.5093*(0.2461）	0.1677(0.2437)	−3.7148(1.9757*）
Obs.	450	255	255	165	345
Adj-R²	0.1257	0.2059	0.1152	0.1154	0.329934

Note: Columns (1)–(5) correspond to electronic power, nonferrous metals, coal and oil, paper printing and steel, respectively. The explanations for the other variables are the same as in Table 3.

The five industries investigated in the five columns of Table 5 are electronic power, nonferrous metals, coal and oil, paper printing and steel, respectively. According to the regression results, the environmental responsibility has significant effect on the cost of equity capital in all of these five industries. Except for nonferrous metals and coal and oil, the estimated coefficients for all the other industries are significant at 1% level. From these results it could be concluded that the equities of companies in all of these five energy- and pollution-intensive industries are indeed affected by environmental responsibility. As for environmental information disclosure, there are remarkable differences for these five industries. For steel industry, the information disclosure has significantly positive impact on the equity price. However, for the electronic power industry, the impact is estimated to be significantly negative, while for the other three industries the coefficients are insignificant. The differences of these results may reflect the specific characteristics of these industries. For instance, because steel industry is comparatively competitive,³⁷ the environmental information disclosure may have positive effect on the company’s image and boost the investors’ confidence and push up its equity price. However, because the electricity market is still not fully competitive as State Grid and China Southern Power Grid have dominant monopoly power to determine electricity price, more information disclosure may lead the investors to doubt the profitability of power plants and drag their equity prices down.

To test the robustness of results, different regressions are conducted and the estimation results are reported in Tables 3 and 4. We make some replacement on control variables, for example, applying cumulative rate of return in place of return on capital and the result does not change. Besides, the regression of sub-samples of industry also supports the result.

Conclusion and policy implication

This research applies the sample of 97 listed companies from high-polluting industry during the period from 2000 to 2014 to investigate the impact of environmental information disclosure on the ability of firms’ borrowing in China. The empirical results imply that lending institutions do take corporate environmental information disclosure into account in borrowing activities, namely more environmental information is disclosed, the scale of loans tend to getting more funding, which means the ability of borrowing is better. Moreover, the cost of equity is estimated to have limited influences on environmental information disclosure. Too much disclosed environmental information may have negative effect on investors, while monetary information disclosure decreases cost of equity. The results also indicate that cost of equity is increasing after the implementation of green credit mechanism, further prove the fact that green finance indeed makes a difference.

According to the data of environmental information disclosure, it is found out that quality and quantity of the environmental information disclosure differ across companies and firms. For the companies that tried to eliminate information asymmetry between themselves and stakeholders by disclosing information, the effect is not as much as expected. Partly because there are few regulations on the environmental information disclosure, the disclosure behaviors in different companies are in various ways and include different context. In general, the differences in environmental information disclosure across industries and companies to some extent reduced the efficiency of disclosure and sometimes even cause chaos and confusions to potential investors.

The abovementioned conclusions reflect the necessity and importance of implementing green finance mechanism in China, which may significantly improve the borrowing ability of listed companies. To promote the reform of green finance, the Chinese government should introduce appropriate policies and counter-measures to facilitate and enhance effective information delivery from companies to investors, which could help investors and regulatory authorities keep a close watch on the firms’ environmental behaviors. Moreover, the environmental information disclosure should be more standardized and the regulation on disclosure should be more rigorous, which helps to reduce the information asymmetry between companies and its stakeholders and therefore is conducive to reinforce the implementation of green financial mechanism.

This study makes preliminary research on the impact of environmental information disclosure on firms’ borrowing ability. However, due to data availability, the different types and characteristics of the environmental information disclosure could not be distinguished. In the future studies, as the context of environment information disclosure becomes richer and more standardized, it is possible to divide the disclosed information to different types and then test the influences of each specific type separately. Besides, the other important financial and economic variables that might be affected by the environmental information disclosure, including the revenue and share prices of the firms, could be further investigated.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Chun-Ping Chang is grateful to the Ministry of Science and Technology of Taiwan for financial support (MOST 106–2410-H-158–001); Yu Hao thanks for the financial support from the National Natural Science Foundation of China (Award Numbers: 71403015, 71761137001, 71521002), Beijing Municipal Natural Science Foundation (Award Number: 9162013), National Undergraduate Training Programs for Innovation and Entrepreneurship of Beijing institute of Technology (Award Numbers: 201510007082, 2016YFA0602603), and Joint Development Program of Beijing Municipal Commission of Education.

Notes

Haiqing Hu is currently dean and full professor at School of Economics and Management, Xi’an University of Technology.

Chun-Ping Chang is currently a professor at Department of Marketing Management, Shih Chien University at Kaohsiung and at Institute of China and Asia-Pacific Studies, National Sun Yat-Sen University.

Minyi Dong is currently a PhD student at School of Economics and Finance, Xi’an Jiaotong University.

Wei-Na Meng is currently a master student on applied economics at Sino-Danish College, University of Chinese Academy of Science.

Yu Hao is currently an associate professor at the Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology (BIT). He earned a PhD in Hamburg University in 2012. Currently, his main research interests include environmental policy, ecological economics and energy economics. So far, he has published over 30 papers in peer-reviewed journals in these fields of research.

Appendix 1

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