Public Attention, Government Subsidies and Corporate Environmental Disclosure: Empirical Evidence from Listed Chinese Enterprises in Heavy-Pollution Industries

In 2013, China suffered from the most severe haze in history, which thrusts carbon emissions and PM2.5 into the limelight. By the end of that year, PM2.5 testing systems began to operate in most cities of China. In the following year, the leader of the Chinese government pointed out at the APEC summit that, “Blue sky, green mountains and clear waters are essential to the Chinese dream.” This means, with the soaring economy, the Chinese government and the public are attaching greater importance to environmental issues.

Being the major economic players in society, enterprises have exerted a growing impact on social resources and eco-environment, while creating economic values. This calls for stricter environmental regulation by the government. So far, the environment departments have put forward a series of policies, rules and regulations, aiming to promote and improve corporate environmental disclosure.

However, the current laws and regulations in China have made it mandatory for enterprises to disclose environmental behaviors only under a few circumstances. In most cases, enterprises are merely guided or encouraged to disclose such behaviors. The methods, contents and quantities of the disclosure are all at the discretion of enterprises. As a result, the disclosure level varies greatly from enterprise to enterprise.

Facing the severe environmental pollution in China, many scholars have highlighted the importance of the public in environmental supervision. You and Yang [1] recommended making tip-offs from the public an information source of government supervision, suggesting that the pressure from the public, coupled with that from the central government, will force local governments to strengthen environmental regulation. Zhang et al. [2] analyzed how the efficiency of industrial pollution control is affected by public supervision and policies on public participation in environmental protection. In reality, however, the public has a limited access to pollution control, and their weak power is not highly recognized.

Compared with the public, the news media can spread information timely across a wide region, and effectively shape the public opinion. The news reports on the environmental issues of the enterprises will pressurize the society and the government to concern themselves with these issues. Through empirical analysis, Li et al. [3] discovered that it is external pressure, rather than internal pressure, that determines how willing and how much the heavy-pollution industries in China disclose environmental behaviors. Due to their strong externalities, environmental issues cannot be effectively solved by the market. Enhanced government regulation is an important way to eliminate environmental externalities.

The stakeholder theory holds that enterprises will not disclose environmental behaviors in the absence of the pressure from major stakeholders, namely, the government, major customers, suppliers, competitors, communities, the public, and the media. Among them, the government can directly apply a huge pressure on enterprises. The pressures from the public and the media are also considerably large. The former formulates a series of laws and regulations to standard and guide the environmental behavior of enterprises, while the latter pressurizes the enterprises through public opinion or media reports.

In China, corporate environmental disclosure does not bode well. The managers have the discretion to decide whether and how to make the disclosure. Many enterprises only choose to disclose the behaviors required to be public by laws and regulations. The selective disclosure often excludes important or negative behaviors. Many enterprises manipulate their information superiority over the public (potential investors), and send positive signals to the society about their sustainability through selective disclosure. Then, the public will overestimate their environmental performance, and buy their stocks in large quantities.

Against this backdrop, there are two unanswered questions: Facing public attention and media supervision, will enterprises actively disclose environmental behaviors to maintain a positive social image? Besides issuing mandatory rules, could the government encourage corporate environmental disclosure through incentive measures like government subsidies? To answer these questions, this paper explores the correlations between public attention, government subsidies and corporate environmental disclosure, and tries to explain the relationship between the disclosure motives of enterprises and stakeholders. The research findings enable enterprises to improve environmental disclosure and implement strategies of sustainable development, laying the basis for building an ecologically civilized country.

Based on the existing literature, this research mainly makes two major contributions. Firstly, this paper introduces new perspectives to the research into corporate environmental disclosure. The previous studies have focused on the passive disclosures, under the pressures from government regulation and negative media reports. Drawing on the signaling theory and stakeholder theory, this paper empirically verifies that positive incentives (e.g. government subsidies, public attention and media coverage) could encourage enterprises to actively disclose environmental behaviors.

Secondly, this paper probes deep into the impacts of report preference (positive, negative or neutral reports) on corporate environmental disclosure. With the growth in government regulation and environmental awareness of enterprises, there are fewer negative reports on environmental behaviors of enterprises. Our results show that corporate environmental disclosure can be promoted by positive reports, but suppressed by negative reports. By contrast, the previous research generally believes that negative reports spur on the disclosure of positive environmental behaviors.

The remainder of this paper is organized as follows: Section 2 introduces the relevant theories and literature, and proposes several hypotheses; Section 3 explains data processing, variable design and model construction; Section 4 presents and analyzes the empirical results; Section 5 makes further discussion about relevant issues; Section 6 puts forward the conclusions and some countermeasures.

3.1 Sampling and data sources

Our samples were collected from the annual data of A-share listed enterprises in 16 heavy-pollution industries (thermal power, steel, cement, electrolytic aluminum, coal, metallurgy, chemicals, petrochemicals, building materials, papermaking, brewing, pharmaceuticals, fermentation, textiles, tanning, and mining) between 2016 and 2018. The original data were screened by the following criteria:

(1) Removing the stock data of special treatment (ST) enterprises, because the data of such enterprises usually have lots of anomalies;

(2) Removing the stock data of listed enterprises with abnormal transactions;

(3) Removing the samples with missing financial data and industry variables;

(4) Removing the enterprises with greater-than-100% asset-liability ratios, because such enterprises tend to be insolvent;

(5) Removing the enterprises with greater-than-150% sales growth rate, because the surge in sales is often the result of mergers and acquisitions;

(6) Removing the enterprises listed after 2015.

To obtain robust results, the continuous variables on the enterprise level were winsorized at 1% and 99% levels, producing 1,143 samples. The financial data of all the enterprises were downloaded from China Stock Market & Accounting Research Database (CSMAR) and Wind Database.

3.2 Research design

3.2.1 Explained variable: environmental disclosure index (EDI)

This paper relies on content analysis, the most important and popular research tool for social responsibility and environmental disclosure, to evaluate the EDI of the sample enterprises.

According to the Measures for Public Participation in Environmental Protection (Trial), China encourages enterprises to actively publicize nine kinds of environmental behaviors. On this basis, the environmental behaviors disclosed by the sample enterprises were divided into eight items, according to the features of annual reports of listed enterprises:

(1) Environmental investment and development of green technologies;

(2) Government grants, financial subsidies and tax reductions related to environmental protection;

(3) Pollutant emissions and emission reduction;

(4) ISO environmental certification;

(5) Measures to improve eco-environment;

(6) Impacts of the government’s environmental policies;

(7) Loans related to environmental protection;

(8) Legal actions, compensations, fines and rewards related to environmental protection.

Next, the EDI of each enterprise was assessed and rated in terms of quantity and quality. The quantity score equals the number of items mentioned in the annual report. The quality score was rated in three dimensions, namely, significance, quantifiability and timeliness, drawing on the strategies of Plumlee et al. [17], Chen and Qian [18], Sengupta [19]:

(1) Significance

The annual report was divided into financial part and non-financial part. If the items are disclosed in the financial part only, 1 point will be assigned; if the items are disclosed in the non-financial part only, 2 points will be assigned; if the items are disclosed in both parts, 3 points will be assigned.

(2) Quantifiability

If the items are described in text, 1 point will be assigned; if the items are quantified but non-financial, 2 points will be assigned; if the items are financial, 3 points will be assigned.

(3) Timeliness

If the items are about the status quo, 1 point will be assigned; if the items are about the future, 2 points will be assigned; if the current and past items are compared, 3 points will be assigned.

Finally, the quality score and quantity score of each enterprise were normalized by z-score, and then added up into the EDI score of the enterprise.

3.2.2 Explanatory variables: media reports and government subsidies

Despite the prevalence of online news, this paper measures the degree of public attention of corporate environmental performance by the number of reports on print media. This is because important news on printed media must also appear online, and excel online news in credibility and quality.

Sixteen newspapers were selected for our research, including China Securities Journal, China Environment News, People’s Daily, Guangming Daily, Securities Daily, Securities Times, Economic Daily, Shanghai Securities News, Financial News, China Economic Times, Business Times, China Business News, The Economic Observer, China Business Journal, Economic Information Daily, and 21^st Century Business Herald.

These influential newspapers have been widely recognized for their timely and high-quality reports. All of them are frequently used as data sources for media studies by scholars engaging in economics, management and business.

The authors searched for news reported by the above newspapers between 2016 and 2018 on the environmental behaviors of the sample enterprises in China Core Newspapers Full-Text Database (CCND). One point was assigned for each piece of news found. The points of each sample enterprise were added up into the total score of news reports on that enterprise.

In addition, this paper measures government subsidies of each sample enterprise by the total amount of government subsidies for environmental protection (including government grants, financial subsidies and tax reductions), which are sorted out by the CSMAR from the appendices of the annual report of each listed enterprise. Because the amount must be an absolute number, the subsidies of each sample enterprises were added up and then normalized by Z-score.

For accuracy, both news reports and government subsidies were winsorized at 1% and 99% levels, and then normalized by Z-score.

3.2.3 Control variables

According to the existing research, the relevant data on financial and governance structure of each sample enterprise was taken as control variables, including the return on equity (ROE), the asset-liability ratio (LEV), the size of enterprise (SIZE), the ownership property (State), the number of independent directors (IDR), and the education background of executives (BSS).

All the variables are explained in Table 1 below.

Table 1. Explanation of research variables

3.3 Model construction

Inspired by Steven Cahan et al. [20] and Wang et al. [21], this paper sets up the following multiple regression models to examine how media reports and government subsidies on environmental protection influence corporate environmental disclosure, and how government subsidies affect media reports:

$E D I_{i t}=\alpha+\beta_{1} N e w s_{i t}+\sum \beta_{i}$ Controls $_{i t}+\xi_{i t}$     (1)

$E D I_{i t}=\alpha+\beta_{2}$subsid$y_{i t}+\sum \beta_{i}$ Controls $_{i t}+\xi_{i t}$     (2)

$E D I_{i t}=\alpha+\beta_{1} N e w s_{i t}+\beta_{2} s u b s i d y_{i t}+\beta_{3} N e w s_{i t} *$subsid$y_{i t}+\sum \beta_{i}$ Controls $_{i t}+\xi_{i t}$     (3)

where, EDI is the index of corporate environmental disclosure; News is the number of reports on printed media on a listed enterprise; subsidy is the normalized total government subsidies on environmental protection received by a listed enterprise.

To further disclose the impacts of media reports and government subsidies on corporate environmental disclosure, new reports were divided into three categories based on preference: positive reports (POS), neutral reports (NEU) and negative reports (NEG). The number of each type of reports was counted. The numbers of POS, NEU and NEG were normalized by Z-score, such that the models are distributed independently yet identically.

Meanwhile, the EDI was also classified into three types: overall EDI (Adj_EDI), financial EDI (EDIF), and non-financial EDI (NEDIF). The Adj_EDI was calculated in three steps: dividing the disclosed environmental behaviors into the above-mentioned eight items; assigning 1 point to each item if it is qualified and 2 points if it is qualified and quantified; adding up all the points of all items and taking the average value.

The EDIF equals the mean of the quantity scores on the following aspects of corporate environmental disclosure: (1) emergency expenditures for major environmental issues; (2) pollutant charge and environmental tax; (3) environmental investment or borrowings; (4) emission reduction benefits; (5) waste utilization income; (6) government subsidies.

Similarly, the NEDIF equals the mean of the quality scores on the following aspects of corporate environmental disclosure: (1) environmental disclosure system; (2) environmental management objectives; (3) environmental measures and improvement; (4) implementation of certifications; (5) energy-saving measures and results; (6) compliance in the types and emissions of pollutants; (7) independent social responsibility report/ sustainable development report/ environmental report.

The descriptive statistics on the above variables are given in Table 4. On this basis, the following models were established for regression analysis:

$A d j_{-} E D I_{i t}=\alpha+\beta_{1} P O S_{i t}+\beta_{2} M E D_{i t}+\beta_{3} N E G_{i t}+\beta_{4} s u b s i d y_{i t}+\sum \beta_{i}$ Controls $_{i t}+\xi_{i t}$     (4)

$E D I F_{i t}=\alpha+\beta_{1} P O S_{i t}+\beta_{2} M E D_{i t}+\beta_{3} N E G_{i t}+\beta_{4} s u b s i d y_{i t}+\sum \beta_{i}$ Controls $_{i t}+\xi_{i t}$      (5)

$N E D I F_{i t}=\alpha+\beta_{1} P O S_{i t}+\beta_{2} M E D_{i t}+\beta_{3} N E G_{i t}+\beta_{4} s u b s i d y_{i t}+\sum \beta_{i}$ Controls $_{i t}+\xi_{i t}$     (6)

As shown in Table 4, the main explained variables Adj_EDI, EDIF and NEDIF were close in mean value. The mean EDIF was slightly lower than that of the other two variables, indicating that the sample enterprises should improve the EDIF and quantify their environmental behaviors.

In terms of media reports, the mean numbers of positive reports and neutral reports was far larger than the mean number of negative reports, but the number of reports varied greatly from enterprise to enterprise. It can be seen that, with the growth in government regulation and corporate environmental awareness, the sample enterprises have reduced the number of environmental accidents and ramped up environmental investment.

As shown in Table 5, the coefficient of POS number was estimated by model (4) as 0.251, which is significant at the 5% level. Obviously, the Adj_EDI increases with the number of POS. After all, government subsidies and social images greatly motivate the enterprises to protect the environment.

The coefficients of POS number estimated by models (5) and (6) were also positive, but only significant at the 10% level. The results show that positive reports have basically the same promoting effect on EDIF and NEDIF.

The coefficients of NEU number were of low significance in all three models. This means neutral reports have an insignificant impact on corporate environmental disclosure.

The coefficients of NEG number were estimated as -0.415, -0.0218 and -0.0288 by models (4)-(6), respectively, which were significant at the levels of 1%, 5% and 10%, respectively. Therefore, the number of negative reports has a significantly negative correlation with corporate environmental disclosure. In other words, negative reports will suppress the enterprises. To evade environmental risks, the enterprises will be cautious and conservative about environmental disclosure.

Moreover, the coefficients of government subsidies estimated by the three models were positive, and significant at the levels of 1%, 5% and 10%, respectively. Hence, government subsidies have significantly positive effects on Adj_EDI and EDIF, but have little impact on NEDIF.

Table 4. Descriptive statistics on main variables

Table 5. Results of multiple regressions

Note: The bracketed numbers are standard errors; *, ** and *** are p<0.1, p<0.05, and p<0.01, respectively.