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Research on the impact of green bond issuance on the stock price of

listed companies Bin Xi and Huimin Jing

Henan University of Technology, Zhengzhou, China

Abstract

Purpose –Considering that listed companies are themain body of natural resource consumption and pollutant emission, this study aims to explore the stock price effect and source channels of green bond issuance of listed companies. This is extremely necessary to promote listed companies to actively fulfill their environmental responsibilities so as to achieve sustainable economic and social development. Design/methodology/approach – In this paper, the companies that issued green bonds in Shanghai and Shenzhen stockmarkets in China from2016 to 2018 are used as samples. First of all, the authors adopt the event studymethod andmatch the twomodels to prove that there is a stock price effect in green bond issuance. Then, the authors introduce the general regressionmodel to analyze the sources of the stock price effect of green bond issuance in detail through three channels: “financing cost,” “investor attention” and “fundamental.” Findings – In the above three channels, the “investor attention” channel can well explain the stock price effect of green bond issuance. Meanwhile, the authors also find that the stock price effect of the subsequent issuance of green bonds ismore significant than that of the first time, non-financial companies aremore pronounced than financial companies, public issuance are more obvious than private issuance, state-owned companies are more notable than non-state-owned companies, small-scale companies are more evident than large-scale companies and companies with high equity concentration are clearer than those with low equity concentration. Originality/value – Taking China as the research object for the first time, this paper comprehensively employs the capital asset pricing model and Fama–French five-factor model to discuss the stock price effect of green bond issuance of listed companies. Secondly, this paper also studies whether the way of green bond issuance, the type and size of the company, as well as the degree of ownership concentration will have different effects on the stock prices of listed companies. The research results provide new ideas and methods for the stock price effect of green bond issuance.

Keywords Green bond issuance, Stock price effect, Investor attention

Paper type Research paper

1. Introduction Global climate deterioration is increasingly becoming an important factor threatening the normal life for the whole of humanity, and it has become the consensus of each country to use green finance to promote environmental protection (Jiang and Zhang, 2017). Because of the large demand for green projects funds and the inability of green credit to meet, the issuance of green bonds, as a new way of green financing, is being widely used (MacAskill et al., 2020). Based on the evolutionary perspective of green bond issuance, in 2007, Europe issued the first “Climate Awareness Bond” specifically to meet the financing needs of green projects (Jakubik and Uguz, 2020); in 2008, theWorld Bank and the Bank of Sweden issued the first bond named

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Funding: This work was financially supported by the Social Science Foundation of Henan Province (No.2019GGJS090).

Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Availability of data and materials: The datasets used and/or analyzed during the current study are

available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests. Author contributions: Bin Xi identified the title and research methods and revised the subsequent

articles. Huimin Jing is responsible for finding data and writing the first drafts.

The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/0368-492X.htm

Received 24 December 2020 Revised 6 April 2021 Accepted 10 May 2021

Kybernetes Vol. 51 No. 4, 2022 pp. 1478-1497 © Emerald Publishing Limited 0368-492X DOI 10.1108/K-12-2020-0900

“Green Bond.” Subsequently, the issuance of green bonds began to receive the attention and recognition of various stakeholders and became prevalent all over the world (Agliardi and Chechulin, 2020). Green bonds are fixed-income bonds issued by financing entities dedicated to the development of green projects (Gianfrate and Peri, 2019). Its purpose is to support the sustainable development of society and respond to the call for the construction of national ecological civilization. In short, green bonds are a means of using private funds and capital markets to finance environmentally sustainable projects (Baulkaran, 2019).

With the new normal of China’s economy entering a new stage, the important position of green growth in the sustainable development of society has become increasingly prominent (Kesidou and Demirel, 2012). The green transformation has obvious positive externalities, which is in line with the trend of ecological civilization, and should become the conscious behavior of enterprises. However, whether the green transformation of enterprises can produce direct investment return is still controversial (Zhou and Cui, 2019). The high cost input and the uncertainty of expected income have become the biggest resistance to the green behavior of enterprises. Different fromEurope and theUSA, China’s financial system is characterized by an underdeveloped bond market and a huge gap in green investment (Sheng et al., 2021). But, the high savings rate of Chinese residents can effectively satisfy the large demand of retail investors for green bond products. Therefore, the preference of investors for green bonds and the characteristics of issuers can fully arouse the interest of researchers and policy makers.

Compared with the environmental benefits, the management and shareholders of the company are evidently more concerned about the return on direct investment brought by the issuance of green bonds (Wang et al., 2019). Accordingly, to determine whether green bond issuance can cause excess return on the stock price of listed companies while achieving environmental benefits, this paper analyzes the stock price effect of green bond issuance of Chinese listed companies based on the event study method. However, investors paid limited attention to the announcements (Ben-Rephael et al., 2017). Themarket should only react to the initial issuance of green bonds, after which it ought to no longer benefit from the “green” label effect. In the light of relevant research, China’s green bond market is a “top-down” issuance model (Huang and Le, 2018). In other words, unlike the green bond issuance pattern abroad, the government agencies, rather than the market, have played a dominant role in China’s green bond issuance process. According to this, we discuss in detail the specific characteristics of the stock price effect of green bond issuance in China’s green bond market.

The main contributions of this study can be summarized as follows:

(1) On the basis of the event studymethod and considering the robustness of the research results, it takes a comprehensive view of the capital asset pricing model (CAPM) and the Fama–French five-factor model to discuss the excess abnormal return on the stock prices of listed companies caused by the issuance of green bonds.

(2) Based on the three channels of “financing cost,” “investor attention” and “fundamental,” this paper explores exhaustively the specific influence mechanism of the stock price effect of green bond issuance of listed companies, which greatly improves the explanation of the research results.

(3) This paper also studies whether the ways of issuing green bonds (public and private), the types of companies (state-owned and non-state-owned), the size of companies and the degree of equity concentration will have differentiated effects on the stock prices of listed companies.

The rest of this article will be structured as follows: Section 2 will review the relevant literature and put forward the research hypothesis. In Section 3, the data sources, related models and statistical descriptions will be shown thoroughly. The penultimate Section 4

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formulates the specific empirical results and makes further discussion. Finally, Section 5 concludes the paper.

2. Literature review and hypotheses development As the main body of natural resource consumption and pollutant discharge, the company is an important subject and key actor of green governance (Li et al., 2019). At the same time, as a rational person, company management and investors will weigh private wealth and social interests carefully (Martin andMoser, 2016). Consequently, our work is closely related to four aspects of research: (1) the stock price effect of green bond issuance of listed companies, (2) the “financing cost” channel of the stock price effect of green bond issuance, (3) the “investor attention” channel of the stock price effect of green bond issuance, (4) the “fundamental” channel of the stock price effect of green bond issuance.

In 2016, China issued the first “labeled” green bond. Since then, the domestic green bond market has developed rapidly (Huang and Le, 2018). Due to the short development time of China’s green bond market, there are few studies on the stock price effect of green bond issuance. Drawing on relevant foreign research experience, Flammer (2020) investigated the reaction of the stock market to the green bond issuance of listed companies, and the results showed that the stock prices of companies had significant cumulative excess returns. Alonso- Conde and Rojo-Su�arez (2020) thought that when companies raise money by issuing green bonds rather than bank loans, shareholders’ internal rate of return is higher. Simultaneously, Tolliver et al. (2019) studied the synergistic movement between the green bond market and the financial market. They found that the synergistic movement of the green bond market was clear with the corporate bond and national debt market, but weak with the stock and commodity market. This means that investors in the stock and energy markets will be better able to optimize their portfolios by holding green bonds than by holding other types of bonds (Nanayakkara and Colombage, 2019). Besides, Jakubik and Uguz (2020) claimed that as investors becomemore aware of environmental protection, they will be more inclined to build portfolios in line with global environmental goals. Obviously, the issuance of green bonds is a sign that the company is practicing the concept of sustainable social development. On the basis of this, the paper puts forward H1.

H1. The issuance of green bonds will boost the share prices of listed companies.

In recent years, some scholars have indicated that green bond issuance in most countries is usually oversubscribed as demand for green bonds grows (Wisniewski and Zielinski, 2019). That means the issuance of green bonds could not only attract investors but also potentially help lower the cost of financing for companies (Zerbib, 2019; Agliardi and Agliardi, 2019). Green bonds are typically bought by large institutions such as pension funds, with only a small proportion traded in the secondary market (Baulkaran, 2019). The Endelman (2018) survey found that nearly 90% of institutional investors around the world paidmore attention to the performance of corporate social responsibility in their investment decisions over the past year. And, companies with good corporate social responsibility could generally issue green bonds at a lower cost (Ge and Liu, 2015; Oikonomou et al., 2014; Ng and Rezaee, 2015). Meanwhile, the research results of Bauer and Hann (2010) also displayed that environmental problems are mostly related to higher debt financing costs, while positive environmental practices are associated with lower debt costs. Additionally, Gianfrate and Peri (2019) stated that even if green certification requires additional costs, green bonds have potential benefits for issuers because they can reduce companies’ financing costs. Base on this, we propose H2:

H2. Green bond issuance attracts investors with green mandates and socially responsible investment funds, which helps drive up bond prices and reduce companies’ financing costs.

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When a company announces the issuance of green bonds, it gets more media exposure than a regular bond (Jin and Han, 2016). According to the signaling theory, the issuance of bonds with a “green” label by a listed company is a good semaphore that the company is committed to green projects and to improving environmental performance (Lyon and Montgomery, 2015). Chen (2018) pointed out that after the announcement of green bonds issuedby listed companies, the overall positive cumulative abnormal returns shows the support and recognition of the market and investors. Banga (2018) declared that the global green bondmarket has become an effective way to finance a low-carbon economy. Global green bond issuance has increased fivefold from 2016 to 2019, and the target of US$1tn is expected to be reached by 2030 (Fatin, 2019). The explosive growth of green bond issuance displays the obvious environmental preference of bond issuers and investors (MacAskill et al., 2020).At the same time,Gilchrist et al. (2021) stated that listed companies gain green reputation through various mechanisms to attract investors who insist on green investment. The reason is that the green reputation of the issuer or the third-party evaluation certification is very important to reduce information asymmetry, lower the suspicion of “greenwashing” and provide convenient financing conditions (Bachelet et al., 2019). Therefore, H3 is proposed in this paper:

H3. The issuance of green bonds will attract the attention of investors and improve the popularity of listed companies so as to expand the investor base.

Green bonds are considered to be a sustainable and stable option in providing long-term funding for social projects (Park et al., 2020). The introduction of the “green” label can create a favorable environment for long-term investors, under which green bond issuers will be required to have stricter information disclosure and transparency (Jakubik and Uguz, 2020). Flammer (2018) believed that the issuance of green bonds can improve the company’s long- term value and operating performance. Simultaneously, Kang and Stulz (1996) also believed that green bond issuance contains more information about value investment opportunities, thereby reducing information asymmetry and producing a positive announcement effect. In particular, the green bond issuer clearly states the use of its income in the prospectus and shows its ongoing or future environmental income projects. But, Schoenmaker (2017) held that the positive externalities of corporate green behavior will appear in the medium term, while sustainable investment will only pay off in the long run. Additionally, Capelle- Balancard et al. (2019) indicated that good corporate social responsibility suggests its long- term commitment to sustainable development and can withstand negative shocks. Thus, the management and investors of the company should resolutely overcome the short-sighted behavior and continue to accelerate the sustainable development of corporate finance. On the basis of this, the paper puts forward H4:

H4. The issuance of green bonds presages good investment opportunities and represents the company’s commitment to sustainable development, which helps to improve the long-term returns of listed companies and investors.

3. Data and methodology 3.1 Samples and data This study selects the companies that issued green bonds in China’s A-share Shanghai and Shenzhen stock exchanges from 2016 to 2018 as the research objects. Among them, green bonds consist of asset-backed securities and private green bonds. Since private green bonds are not publicly issued, they aremostly held by institutional investors. Considering the availability of information, we assume that all private green bonds are preserved by institutional investors. The empirical analysis includes the event study method and the general regression model. Specifically, the announcement information of green bond issuance in the event study method

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comes from the official websites of listed companies and financial websites (whichever is the earlier), while the rest of the data come from China Stock Market Accounting Research (CSMAR) database, Wind database and annual reports of listed companies.

3.2 Event study methodology We use the event study method to investigate the impact of green bond issuance on the stock prices of listed companies. The event study method needs to determine the estimation window, event date and event window. As shown in Figure 1, the estimation window is from 300 to 50 trading days before the event date, with the purpose of estimating the normal return rate of the listed company’s stock price. Event date (t5 0) is the date on which investors first get green bonds issued by listed companies (whichever is the earlier). The event window aims to analyze whether green bonds can bring excess and abnormal returns to listed companies after issuance. By using the existing relevant literature for reference, we select three event windows, which are [�1, 1], [�1, 5] and [�1, 7] (Tang and Zhang, 2018). As there are few research studies on the stock price effect of green bond issuance in Chinese market, and taking the robustness of the estimated results into consideration, we comprehensively adopt the CAPM and Fama–French five-factor model to investigate the excess abnormal return brought by green bond issuance to listed companies.

3.2.1 Capital asset pricing model. First of all, the CAPM is used to estimate abnormal returns. The model is set as follows:

Rit � Rft ¼ αi þ βiðRmt � RftÞ þ εit (1)

Where Rit is the rate of return of the company i in period t; Rft is the risk-free interest rate in period t; βi is estimated from the estimation window of 300 to 50 trading days prior to the event date; Rmt is the market-weighted index return in period t, i.e. the market rate of return; and εit is a random interference.

In the light of the CAPM, the abnormal rate of return of company i on day t in the window period can be expressed as:

ARit ¼ Rit � bRit (2)

The cumulative abnormal return of company ion day t in thewindowperiod can be expressed as:

CARit ¼ X i¼1

ARit (3)

3.2.2 Fama–French five-factor model. Compared with the Fama–French three-factor model, the five-factor model proposed by Fama and French not only covers themarket capitalization effect and value effect, which cannot be explained by the CAPM, but also consists of the factors of corporate profit and investment. The specific model is set as follows:

Estimation window Event window

–300 –50

–1

–10 –5 0 5 10

1 t

Note(s): The companies that have been suspended for more than 10 trading days

are excluded

Figure 1. The timewindow of the event study method

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Rit � Rft ¼ αi þ βiðRmt � RftÞ þ siSMBt þ hiHMLt þ riRMWt þ ciCMAt þ εit (4)

where SMTt is the difference in the rate of return between a portfolio of companies with a lower market capitalization and a portfolio of companies with a higher market capitalization in period t;HMLt is the difference in the rate of return between a portfolio of value companies with higher book value and a portfolio of growth companies with lower book value in period t; RMWt is the difference between the rate of return of a portfolio of companies with strong profitability and that of companies with poor profitability in period t; CMAt is the difference in the rate of return between a portfolio of companies with a lower level of investment and a portfolio of companies with a higher level of investment in period t. While, the detail description of other variables can be found in the above corresponding part.

3.3 “Financing cost” channel The basic index to measure the pricing yield of green bonds is the spread of green bonds when they are issued, which is calculated from the difference between the coupon rate and the benchmark interest rate of the central bank (Wang and Zhu, 2011). In this section, green bonds and all ordinary bonds issued by non-financial companies in China’sA-share Shanghai and Shenzhen stock exchanges from 2016 to 2018 are selected as research samples to compare the two types of bonds issued by the same company. Meanwhile, we match similar companies according to size, Tobin Q value and stock liquidity, and examine the validity of H2 by comparing the green bonds of a company with the ordinary bonds of the matching company. The specific regression model is set up as follows:

YieldSpreadit ¼ β0 þ β1 3Greenit þ β2 3Volatilityit þ β3 3Maturityit þ β4 3 Issuesizeit

þ X

βn 3Controlsit þ FE þ εit

(5)

where Yieldspreadit is the spread of the t-th bond issued by company i; Greenit is a green virtual variable, if the t-th bond issued by company i is a green bond, Green is marked as 1, otherwise it is 0; Volatilityit is the stock volatility of the listed company that year when company i issued the t-th bond, calculated by dividing the difference between the highest and lowest stock prices by the average price; Maturityit is the bond maturity of the t-th bond issued by company i; Issuesizeit is green bond issuance scale of the t-th bond issued by company i; Controlsit is a control variable. FE is the fixed effect of the year; εit is a random interference.

3.4 “Investor attention” channel Institutional investors include banks, insurance companies, mutual funds, pension funds, investment companies and private trust institutions. Although institutional investors have great advantages in capital, information and fund management, they do not have experience in selling specific products. Therefore, most institutional investors participate in corporate governance through shareholders’meeting, board of directors and board of supervisors. The “investor attention” channel suggests that the green bond issuance of listed companies will increase themedia exposure to the company, thus sending a positive signal to themarket that these companies have green investment opportunities at this time, which in turn attracts the attention of institutional investors and expands the investor base (Dyck et al., 2018; Dimson et al., 2015). As shown in Figure 2, the stock trading volume before and after the month in which green bonds are issued is significantly higher than that in the months in which green bonds are not issued.

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The empirical test of institutional investors’ shareholding in “investor attention” channel includes a green dummy variable, a post-dummy variable and their interaction term. The purpose is to analyze the difference between the shareholding ratio of institutional investors after the issuance of green bonds and that of institutional investors after the issuance of ordinary bonds. The specific regression model is set up as follows:

Instit ¼ β0 þ β1 3Greenit 3Postit þ β2 3Greenit þ β3 3Postit þ X

βn 3Controlsit

þ FE þ εit (6)

where Instit is the institutional ownership of the company i in year t, which is the total ownership of the institution as a percentage of the total market capitalization; Greenit is a green virtual variable, if company i issued green bonds in year t, Green is marked as 1, otherwise it is 0; Postit is a post-dummy variable, if company i issued green bonds before the year t, Post is marked as 1, otherwise it is 0;Greenit 3 Postit is an interaction term of the green virtual variable and the post-dummy variable; Controlsit is a control variable. FE is the fixed effect of the year. εit is a random interference.

3.5 “Fundamental” channel “Fundamental” channel holds that green bond issuance can bring long-term benefits to listed companies and resist negative shocks, which means that green bond issuance is a valuable investment opportunity for corporate management and investors. However, unlike the “financing cost” channel, “investor attention” channel and the “fundamental” channel cannot be directly distinguished. Thence, referring to the practice of Tang and Zhang (2018), we introduce stock liquidity test to distinguish between “investor attention” channel and “fundamental” channel. In particular, we adopt the average annual turnover rate of stocks (based on freely circulated equity) as an indicator of liquidity, and we also take the Amihud index as an alternative indicator of the average annual turnover rate of stocks (Deng et al., 2016). The specific method for calculating the Amihud index is as follows:

Illiquidityit ¼ 1

Daysit

XDaysd i¼1

jReturnitdj Volumeitd

(7)

4

5

6

7

8

M o n th

ly a

v er

ag e

v o lu

m e(

b il

li o n )

–6 –5 –4 –3 –2 –1 0 1 2 3 4 5 6 7 8 9 10 11 12

Green Bond Event Month

Figure 2. Monthly average trading volume of stocks before and after the issuance of green bonds

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where Returnitd is the rate of return of stock i on day d of year t; Volumeitd is the trading volume of stock i on day d of year t; Daysit is the number of trading days of stock i in year t; the Illiquidityit indicator intuitively reflects the price shock dimension of liquidity. In general, the higher the Amihud index, the greater the impact of unit transaction value on stock returns, and the lower the liquidity of the stock. On the contrary, the lower the Amihud index, the better the liquidity of the stock.

To prove the robustness of the regression results, sample matching is needed to eliminate the problem that the liquidity of all companies has improved in the year of green bond issuance. Although there is still no evidence to show that the stock liquidity of listed companies will increase after the issuance of ordinary bonds, there may be some missing variables that will lead to the improvement of stock liquidity of all listed companies in the year of green bond issuance. To address this problem, the same matching method is used for filtering in this section. Moreover, this section also takes matching and further analysis with companies whose green bond issuers are not listed on the same exchange. The empirical model of “fundamental” channel performs panel regression and control on company characteristics, liquidity characteristics and annual fixed effects. The specific regression model is set up as follows:

Liquidityit ¼ β0 þ β1 3Greenit 3Postit þ β2 3Greenit þ β3 3Postit þ X

βn 3Controlsit

þ FE þ εit

(8)

where Liquidityit is the liquidity of stock i in year t; FE is the fixed effect of the year. While,the detail description of other variables can be found in the above corresponding part.

3.6 Descriptive statistics The types of green bonds and annual green bond issuance are shown in Table 1. Specifically, the statistical date of China’s green bonds is up to March 16, 2020. Table 1 displays that since China issued its first “labeled” green bond in 2016, a total of 713 green bonds have been issued in China, which has generally maintained an upward trend. In particular, the issuance of asset-backed securities ranked first, followed by corporate bonds.

Table 2 reports statistics on green bonds and key variables of non-financial companies. The sample covers all green bond issuers from January 1, 2016 to March 16, 2020. As can be seen from Table 2, among all the green bonds issued, the average coupon rate is 5.00%, the averagematurity of bonds is 5.01 years and the average amount of bonds issued isU1.314bn. At the same time, sub-samples of non-financial companies in Panel A are used for follow-up

Year Corporate

debt Financial debt

Local government

bonds

Asset- backed securities

Private placement

International development

agency bonds

The others Total

2016 23 21 0 28 1 1 7 81 2017 53 42 0 54 9 0 9 167 2018 48 28 0 25 9 0 6 116 2019 72 25 5 144 39 0 22 307 2020 13 2 0 7 14 0 6 42 Total 209 118 5 258 72 1 50 713

Note(s): Other bonds mainly include green debt financing instruments and medium-term notes

Table 1. Statistics on the types

and issuance of green bonds

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basic regression analysis. The sub-sample of non-financial companies excludes the green bonds issued by all financial institutions and unlisted companies. Among all green bonds issued by non-financial companies, the average coupon is 5.18%, the average maturity of bonds is 4.74 years, and the average amount of bonds issued is U795m.

4. Results and discussion 4.1 The stock price effect of green bond issuance The results of the event studymethod are displayed inTable 3. Among them, PanelA is divided into initial issue and subsequent issue, and Panel B is classified into non-financial companies and financial companies, to compare the stock price effect of green bonds issued by different types of companies. Themodels used in the stock price effect of green bond issuance are CAPM and Fama–French five-factor model. In view of the availability of data, we only make use of green bonds issued by Chinese A-share companies in Shanghai and Shenzhen, with a sample size of 127. Panel A points out that the stock price effect of the initial issue of green bonds is not pronounced in the three window periods of [�1, 1], [�1, 5] and [�1, 7], but is notable in the subsequent issuance. Panel B indicates that the stock price effect of green bonds issued by non- financial companies is more obvious than that of financial companies in the [�1, 5] and [�1, 7] window periods. The above results verify H1. Put differently, the issuance of green bonds can promote the stock prices of listed companies to rise.

4.2 The source channel of the stock price effect of green bond issuance 4.2.1 “Financing cost” channel. Table 4 presents the results of the yield spread analysis of green bond issuance. The results indicate that the green virtual variable in Column (1) is

Panel A characteristics of green bonds Variable Mean Standard deviation Min P25 Median P75 Max N

CouponðpercentÞ 5.00 1.26 0.50 4.00 4.80 5.80 8.50 682 MaturityðyearÞ 5.01 3.18 0.03 3.00 5.00 6.09 20.00 706 AmountðmillionÞ 1314 2922 1 171 600 1300 30,000 711

Characteristics of green bonds issued by non-financial companies CouponðpercentÞ 5.18 0.91 3.30 4.74 4.99 5.50 7.50 34 MaturityðyearÞ 4.74 0.93 3.00 5.00 5.00 5.00 7.00 34 AmountðmillionÞ 795 557 100 500 675 1000 2400 34

Panel B company characteristics Variable Mean Standard deviation Min P25 Median P75 Max

Asset 5.57 1.24 1.13 4.88 5.57 6.23 7.69 Leverage 0.58 0.15 0.06 0.51 0.61 0.68 0.83 Cash 0.23 0.11 0.02 0.14 0.21 0.31 0.61 Profitability 0.11 0.11 �0.29 0.04 0.09 0.17 0.53 Tobinq 1.09 1.59 0.07 0.40 0.71 1.31 11.39 Dividend 0.01 0.01 0.00 0.00 0.01 0.02 0.06 Tangibility 0.28 0.19 0.00 0.11 0.26 0.41 0.67

Note(s): The company size (Asset) is the natural logarithm of the company’s total assets; leverage ratio (Leverage) is the asset–liability ratio of a company; cash ratio (Cash) is the ratio of the sum of monetary funds and short-term loans to total assets; net profit margin (Profitability) is the ratio of net profit to total operating income; TobinQ value (Tobinq) is the ratio of the company’smarket capitalization to the replacement cost of the company’s total assets; the dividend yield (Dividend) is the ratio of the total annual dividend to the market value; the proportion of fixed assets (Tangibility) is the ratio of fixed assets to total assets

Table 2. Summary statistics of main variables

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P an el A fi rs t- ti m e v s su b se q u en t is su es

F ir st -t im

e S u b se q u en t

(1 )

(2 )

(3 )

(1 )

(2 )

(3 )

E v en t w in d ow

[� 1, 1]

[� 1, 5]

[� 1, 7]

[� 1, 1]

[� 1, 5]

[� 1, 7]

C A P M _ C A R ð%

Þ 0. 21 7 (0 .7 4)

0. 37 2 (0 .6 9)

0. 42 8 (0 .7 2)

0. 66 6* * (2 .0 4)

0. 72 7*

(1 .7 3)

0. 71 6*

(1 .6 9)

F F 5 C A R ð%

Þ 0. 69 7 (2 .3 6)

0. 73 2 (1 .4 2)

0. 79 8 (1 .3 9)

0. 53 8 (1 .6 7)

0. 78 2*

(1 .7 6)

0. 79 7*

(1 .7 4)

N 86

86 86

41 41

41

P an el B N on -f in an ci al v s F in an ci al co m p an ie s

N on -f in an ci al

F in an ci al

(1 )

(2 )

(3 )

(1 )

(2 )

(3 )

E v en t w in d ow

[� 1, 1]

[� 1, 5]

[� 1, 7]

[� 1, 1]

[� 1, 5]

[� 1, 7]

C A P M _ C A R ð%

Þ 0. 43 1 (1 .1 4)

1. 00 6 (1 .5 5)

1. 18 5*

(1 .6 8)

0. 27 4 (1 .6 0)

�0 .1 71

(� 0. 56 )

�0 .3 21

(� 0. 95 )

F F 5 C A R ð%

Þ 0. 61 0 (1 .6 4)

1. 38 3* * (2 .1 9)

1. 62 2* * (2 .3 6)

0. 69 1* **

(3 .5 5)

�0 .0 58

(� 0. 23 )

�0 .2 47

(� 0. 79 )

N 71

71 71

56 56

56

N o te (s ): T h e t v al u e is in

p ar en th es es .* ** ,* * an d * re p re se n t si g n if ic an ce

le v el s of

1, 5 an d 10 % ,r es p ec ti v el y

Table 3. Stock price effect of green bond issuance

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evidently positive, while those in Columns (2) and (3) are not significant. It can be seen that compared with ordinary bond issuance, green bond issuance does not show a negative premium. Namely, unlike the green bond market in Europe and the USA, China’s green bond issuance cannot reduce the financing costs of listed companies, which may be stem from the immature development of China’s green bondmarket. Therefore, the “financing cost” channel does not seem to be the driving force of the stock price effect of green bond issuance of listed companies, and H2 is not valid.

4.2.2 “Investor attention” channel. Table 5 reports the impact of green bond issuance of listed companies on institutional ownership. The results express that the interaction terms between green virtual variables and post-virtual variables in Columns (2) and (3) are distinctly positive, which indicates that the shareholding ratio of institutional owners after green bond issuance is remarkably higher than that of ordinary bond issuance. Obviously, the green bond issuance of listed companies is a good investment opportunity for institutional investors. Thus, it can be seen that the “investor attention” channel is the source channel of the stock price effect of green bond issuance of listed companies, and H3 is established.

4.2.3 “Fundamental” channel. Table 6 shows the impact of green bond issuance of listed companies on their stock liquidity. The regression results display that both theAmihud index and the average annual turnover rate of stocks are significant, which implies that green bond issuance of listed companies can notably improve the liquidity of listed companies than ordinary bond issuance. On the other side, institutional investors and retail investors are not keen to hold shares of listed companies that issue green bonds for a long time. In summary, the “fundamental” channel does not appear to be the driver of the share price effect of green bond issuance by listed companies. Therefore, H4 is not true, and H3 is tested again.

Yield spread (1) (2) (3)

Green 0.574** (2.44) 0.333 (1.23) 0.026 (0.17) Volatility 0.509 (0.73) 0.342 (0.53) 0.339 (1.12) Maturity �0.240** (�2.38) �0.183 (�1.57) �0.061 (�1.07) Issuesize �0.000 (�0.04) �0.011 (�0.90) �0.022 (�1.69) Cons 0.734 (1.48) 2.868* (1.95) 2.738** (2.30) Controls No Yes Yes Year No No Yes Adj−R2 0.118 0.238 0.581 N 67 67 67

Note(s): The t-value is in parentheses. ***, ** and * represent significance levels of 1, 5 and 10%, respectively

Institutional ownership (1) (2) (3)

Green3Post 0.145 (1.37) 0.212** (2.31) 0.203** (2.19) Green �0.104 (�1.26) �0.101 (�1.47) �0.094 (�1.34) Post 0.010 (0.26) 0.002 (0.06) 0.0344 (0.52) Cons 0.504*** (12.33) 0.780*** (10.00) 0.787*** (9.95) Controls No Yes Yes Year No No Yes Adj−R2 0.002 0.311 0.300 N 89 83 83

Note(s): The t-value is in parentheses. ***, ** and * represent significance levels of 1, 5 and 10%, respectively

Table 4. Spreads of green bonds

Table 5. Impact of green bond issuance on institutional ownership

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4.3 Statistical analysis of the financing cost advantage of green bonds This section further discusses the financing cost advantages of green bond issuance of listed companies. Owing to the large number of green bonds issued every year, we take the green bonds issued in China in the first half of 2018 as an example. We compared the difference in interest rates between green bonds and comparable bonds in the first half of 2018. Comparable bonds of the same kind refer to bonds of the same type, maturity and grade as those of the month in which green bonds are issued. Specifically, in the first half of 2018, China issued a total of 41 “labeled” green bonds, of which 33 had comparable bonds of the same kind. The statistical results present that a total of 25 of the 33 green bonds have the advantage of financing cost, accounting for 75.76%.

Table 7 further statistics the proportion of financing advantages of all kinds of green bonds on the basis of the above research. We have made an in-depth discussion from three aspects: the enterprise category, the main body level and the bond type of the issuer. According to the data in Table 7, in terms of the enterprise categories of green bond issuers, local state-owned enterprises and central enterprises have obvious advantages in financing costs. Regarding the subject level of the green bond issuer, the issuer whose credit rating is AAA has obvious advantage in financing cost. Meanwhile, with regard to bond types of green bonds, the financing cost advantage of green corporate bonds is obvious, followed by green financial bonds and medium-term bills. Thus, in contrast to the empirical results, the statistics clear that green bonds may have the advantage of issuing cost to a great extent.

4.4 Further study 4.4.1 The influence of the way of issuing green bond on the stock price of the company. Table 8 reports the comparison of the stock price effect of public issuance of green bonds and private placement of green bonds, to further explore the difference of the stock price effect of green bonds issued under different issuance methods. The findings of Table 8 suggest that the stock price effect of public issuance of green bonds is more obvious than that of private offerings, which reveals that while government agencies play their leading role, the market also plays an important part. Accordingly, the “top-down” green bond issuance mode of China’s green bond market should be gradually liberalized and let the market play a role continuously so as to encourage listed companies to actively fulfill their social responsibilities.

4.4.2 The influence of company types on the stock price effect of green bond issuance.Table 9 analyzes whether the types of companies (state-owned and non-state-owned) have varying degrees of impact on the stock price effect of green bond issuance. It can be seen that the stock price effect of green bond issuance of state-owned companies ismore notable than that of non- state-owned companies in the three window periods of [�1, 1], [�1, 5] and [�1, 7]. Due to the large proportion of shares held by institutional investors in state-owned companies, to a large extent, the result further validates the conclusion of the empirical part. In addition, state-

Amihud Turnover rate (1) (2) (1) (2)

Green3Post �0.401* (�1.84) �0.349* (�1.69) 0.266* (1.69) 0.334** (2.11) Green 0.271** (2.10) 0.248* (1.86) �0.281** (�2.14) �0.296** (�2.29) Post 0.264** (2.48) 0.288** (2.07) �0.258** (�2.02) �0.186 (�1.43) Cons 2.376*** (4.72) 2.373*** (4.67) 0.186 (0.62) 0.362 (1.17) Controls Yes Yes Yes Yes Year No Yes No Yes Adj−R2 0.545 0.545 0.584 0.594 N 177 177 157 157

Note(s): The t-value is in parentheses. ***, ** and * represent significance levels of 1, 5 and 10%, respectively

Table 6. Impact of green bond

issuance on stock liquidity

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owned companies play an important role in China’s national economy in the aspect of volume and scale, so under the mode of green bond issuance led by the government, the stock price effect of green bond issuance of state-owned companies must be more obvious than that of non-state-owned companies.

4.4.3 The influence of company size on the stock price effect of green bond issuance.Table 10 studies whether the company size will have varying degrees of impact on the stock price effect of green bond issuance. In particular, large- and small-scale companies are classified by the three-quarter quartile (U852m) of the company’s annual total assets. The empirical results display that the stock price effect of green bond issuance by small-scale companies is generally larger than that of large-scale companies. Obviously, this is consistent with the advantages of highmarket demand integration, professionalism and high efficiency of small- scale companies. Although large-scale companies have certain cost advantages, they are more prone to bureaucracy, resulting in the failure of the internal competition mechanism.

4.4.4 The influence of ownership concentration on the stock price effect of green bond issuance. Table 11 explores whether equity concentration will have different degrees of impact on the stock price effect of green bond issuance. Among them, companies with high equity concentration and companies with low equity concentration are classified according to the three-quarter quartile (40%) of the shareholding ratio of the largest shareholder, which implies that the largest shareholder of the company with high equity concentration is basically in an absolute holding position. As the controlling shareholder is directly related to the interests of

Category

Local state- owned

enterprises Central

enterprises Public

enterprise Private

enterprise

Sino- foreign joint

venture

The enterprise category of the issuer

Have the advantage of financing cost

18 4 2 – 1

No financing cost advantage

4 1 1 2 –

Proportion of financing cost advantage

81.82% 80.00% 66.67% 0.00% 100.00%

Category AA AAþ AAA – – The subject level of the issuer

Have the advantage of financing cost

4 9 12 – –

No financing cost advantage

2 4 2 – –

Proportion of financing cost advantage

66.67% 69.23% 85.71% – –

Category Corporate bonds

Financial bonds

Enterprise bonds

Medium- term notes

–

Bond type Have the advantage of financing cost

4 6 6 9 –

No financing cost advantage

2 2 1 3 –

Proportion of financing cost advantage

66.67% 75.00% 85.71% 75.00% –

Note(s): The data come from public data collation

Table 7. Statistics on the proportion of financing advantages of various types of green bonds

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P u b lic

P ri v at e

(1 )

(2 )

(3 )

(1 )

(2 )

(3 )

E v en t w in d ow

[� 1, 1]

[� 1, 5]

[� 1, 7]

[� 1, 1]

[� 1, 5]

[� 1, 7]

C A P M _ C A R ð%

Þ 0. 42 2 (1 .4 1)

0. 73 9 (1 .4 0)

0. 97 0*

(1 .7 0)

0. 22 1 (0 .8 4)

�0 .1 03

(� 0. 27 )

�0 .5 31

(� 1. 17 )

F F 5 C A R ð%

Þ 0. 55 8*

(1 .8 7)

0. 91 3*

(1 .7 6)

1. 19 2* * (2 .1 2)

0. 84 9* **

(3 .0 4)

0. 36 0 (1 .1 6)

�0 .1 25

(� 0. 31 )

N 89

89 89

38 38

38

N o te (s ): T h e t- v al u e is in

p ar en th es es .* ** ,* * an d * re p re se n t si g n if ic an ce

le v el s of

1, 5 an d 10 % ,r es p ec ti v el y

Table 8. Comparison between

public and private issuance of green bonds

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S ta te -o w n ed

N on -s ta te -o w n ed

(1 )

(2 )

(3 )

(1 )

(2 )

(3 )

E v en t w in d ow

[� 1, 1]

[� 1, 5]

[� 1, 7]

[� 1, 1]

[� 1, 5]

[� 1, 7]

C A P M _ C A R ð%

Þ 0. 61 2* * (2 .0 9)

0. 05 5 (0 .1 7)

0. 23 8 (0 .6 1)

�0 .0 49

(� 0. 14 )

1. 19 8 (1 .3 8)

0. 98 7 (1 .0 6)

F F 5 C A R ð%

Þ 1. 01 7* **

(3 .4 4)

0. 62 6* * (2 .1 5)

1. 04 5* **

(3 .2 5)

0. 03 3 (0 .1 0)

0. 94 9 (1 .0 8)

0. 39 2 (0 .4 1)

N 79

79 79

48 48

48

N o te (s ): T h e t- v al u e is in

p ar en th es es .* ** ,* * an d * re p re se n t si g n if ic an ce

le v el s of

1, 5 an d 10 % ,r es p ec ti v el y

Table 9. The influence of company types on the stock price effect of green bond issuance

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L ar g e sc al e

S m al l sc al e

(1 )

(2 )

(3 )

(1 )

(2 )

(3 )

E v en t w in d ow

[� 1, 1]

[� 1, 5]

[� 1, 7]

[� 1, 1]

[� 1, 5]

[� 1, 7]

C A P M _ C A R ð%

Þ 0. 06 4 (0 .3 2)

0. 28 1 (0 .8 4)

0. 48 8 (1 .3 6)

0. 46 7 (1 .5 8)

0. 55 9 (1 .0 9)

0. 53 3 (0 .9 5)

F F 5 C A R ð%

Þ �0

.0 72

(� 0. 35 )

�0 .5 75 * (�

1. 92 )

�0 .8 75 **

(� 2. 24 )

0. 89 7* **

(3 .0 9)

1. 21 2* * (2 .4 8)

1. 38 5* * (2 .6 1)

N 33

33 33

94 94

94

N o te (s ): T h e t- v al u e is in

p ar en th es es .* ** ,* * an d * re p re se n t si g n if ic an ce

le v el s of

1, 5 an d 10 % ,r es p ec ti v el y

Table 10. The influence of

company size on the stock price effect of green bond issuance

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H ig h eq u it y co n ce n tr at io n

L ow

eq u it y co n ce n tr at io n

(1 )

(2 )

(3 )

(1 )

(2 )

(3 )

E v en t w in d ow

[� 1, 1]

[� 1, 5]

[� 1, 7]

[� 1, 1]

[� 1, 5]

[� 1, 7]

C A P M _ C A R ð%

Þ 0. 81 5 (1 .5 6)

0. 88 5 (1 .4 7)

1. 60 2* **

(2 .8 4)

0. 24 0 (0 .9 7)

0. 37 9 (0 .8 1)

0. 22 9 (0 .4 4)

F F 5 C A R ð%

Þ 1. 20 3* * (2 .4 2)

1. 35 0* * (2 .1 6)

2. 37 7* **

(4 .0 5)

0. 49 5*

(1 .9 7)

0. 58 5 (1 .3 1)

0. 37 2 (0 .7 5)

N 27

27 27

10 0

10 0

10 0

N o te (s ): T h e t- v al u e is in

p ar en th es es .* ** ,* * an d * re p re se n t si g n if ic an ce

le v el s of

1, 5 an d 10 % ,r es p ec ti v el y

Table 11. The influence of equity concentration on the share price effect of green bond issuance

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the company, the operating efficiency of companies with high ownership concentration will be higher than that of companies with low ownership concentration. At the same time, Table 11 also shows that the stock price effect of green bonds issued by companies with high equity concentration is more obvious than that of companies with low equity concentration.

5. Conclusion Through the event studymethod, this paper studies the impact of green bond issuance on the stock price of listed companies. In the event study method, we specifically adopt two models: the CAPM and the Fama–French five-factor model. The model confirms the stock price effect of green bond issuance of listed companies. Besides, we discover that the subsequent issuance of green bonds ismore significant than the initial issue, and non-financial companies are more obvious than financial companies. Subsequently, we take non-financial companies as samples to explore the specific sources of the stock price effect of green bond issuance through three channels: “financing cost,” “investor attention” and “fundamental.” The findings of the study suggest that the “investor concern” channel well explains the stock price effect of green bond issuance, the “financing cost” channel is still open to discussion and the “fundamental” channel is obviously not the source of green bond stock price effect. On this basis, we further explorewhether the issuingmethods of green bonds (public and private), the types of companies (state-owned and non-state-owned), the size of companies and the degree of ownership concentration will have different effects on the stock prices of listed companies. The research presents that public issuance of green bonds is more notable than private issuance, state-owned companies are more pronounced than non-state-owned companies, small companies are more evident than large companies and companies with high ownership concentration are clearer than companies with low ownership concentration.

Based on the event study method and general regression model, we analyzed the stock price effect of green bond issuance and its source channels, which provides newmethods and ideas for green bond issuance of listed companies, as well as enriches the research of existing literature. However, this paper still needs some improvement. For one thing, the empirical analysis results in the “financing cost” channel are inconsistent with the statistical results in Table 7, which may be owing to the late start of China’s green bond market and insufficient data. For another thing, in view of the fact that the “investor attention” channel is the source of the stock price effect of green bond issuance of listed companies, further consideration of the impact of this channel on corporate performance can considerably enrich the existing research. Therefore, the relevant scholars can take the above two aspects as the main research direction for follow-up research.

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Corresponding author Huimin Jing can be contacted at: [email protected]

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