Gadjah Mada International Journal of Business
Vol. 27, No. 3 (September-December 2025): 351-372

The Impact of Green Bonds on Firm Value
and the Role of ESG:
Revisiting the Stakeholder Value Maximization Theory
Asad Arsya Brilliant Fania*, Ruslan Prijadia
a
Universitas Indonesia, Indonesia

Abstract: This study evaluates managers’ motivations in decision-making and whether
they aim to maximize value or meet environmental and social pressures at the expense
of value. The authors utilize green bonds as a treatment and measure changes in firm
value data using Tobin’s Q, controlling for times and individual fixed effects and several
company characteristics. This research documents the positive impact of issuing green
bonds on a firm's value using the difference-in-differences (DD) method. Our findings
are confirmed over the aggregate sample and most of the industry subsample, whereas we
observed negative associations between green bonds and firm value only in the industrial
subsample (comprising industrial and commercial services, industrial goods, and transportation). These findings align with the hypothesis of the stakeholder value maximizing
theory. So, we suggest that, based on the data we analyzed about green bond issuances,
companies choose to issue green bonds to increase their overall value.
Keywords: green bonds, corporate finance, firm value, stakeholder value maximization
JEL Classification: G320

*Corresponding author’s e-mail: asadarsyaui@gmail.com
ISSN: PRINT 1411-1128 | ONLINE 2338-7238
https://journal.ugm.ac.id/gamaijb

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Introduction

The conventional discussion in the financial field concerns whether a corporation is obligated only to maximize its shareholder value. The shareholder theory has been widely
referenced since Nobel Prize winner Milton Friedman (1970) proposed it in an article
entitled "The social responsibility of business is to increase its profit." Corporate managers,
acting as agents, are only responsible to a company’s owners or its shareholders, who are
considered the principals. In the early 2000s, Jensen (2010) introduced the stakeholder
theory, which he referred to as "enlightened value maximization," thereby contributing to
the ongoing discussion. This theory states that, while environmental, social, and governance (ESG) factors are important, they can undermine value by obscuring the strategic
corporate goal; however, they still have legitimate uses within a corporation.
Thus, investors and the government are increasingly demanding that firms engage in ESG-related activities. In recent years, the climate change problem has become
increasingly prominent, making environmental issues one of the most pressing challenges
in human history. There have been many attempts by researchers, practitioners, and regulators to address the issues, resulting in relevant guidance, ratings, and regulations. In
recent years more than ever, there has been significant pressure on the firms to incorporate environmental policies in their long-term strategies to increase firm value; that is to
say, paying attention to stakeholder concerns is necessary if the company does not want to
harm its value.
A green bond is one of the green finance instruments designed to address environmental, social, and climate conservation issues. The business world has established
numerous ideas to promote the cultivation of environmental and social concerns. The
evidence regarding the impact of green bonds—as a sustainable finance instrument—on
firm value remains mixed (Flammer, 2021; Khurram et al., 2023; Larcker & Watts, 2020;
Wang et al., 2020; R. Zhang et al., 2021; Zheng et al., 2023). There is still limited literature that mainly focuses on the empirical study of green bonds and their relation to the
intrinsic value of the firm. This study tests the impact of green bonds on the firm value.
Surprisingly, to the best of the authors' knowledge, the association between green bonds
and firm value using Tobin’s Q measure has only been examined by Khurram et al. (2023)
and Jiang et al. (2022), and both use data for China. Our study thus expands the dataset to
regions and industries all over the world and, following Deng et al. (2013), examines the
relationship from the perspective of the stakeholder theory.
From the standpoint of firm value maximization, the questions this research poses
are as follows: Do green bonds affect firm value, and if so, how does that change over time?
Do green bonds have an impact on the environmental, social, and governance performance of a firm?
This study employs a difference-in-differences (DD) method to assess the impact
of green bond issuance on firm value, measured using Tobin’s Q. The dataset consists
of 99 green bond issuers and 524 non-issuers across six industries from 2013 to 2023,
sourced from Refinitiv’s Green Bond Guide. Control variables include ROA, ROE, firm
size, leverage, long-term debt, and ESG scores to account for firm characteristics. The
model incorporates firm and time fixed effects to mitigate selection bias and isolate the
causal relationship between green bond issuance and firm value. Two robustness tests are
conducted with (1) separating the sample into high- and low-ESG-combined-score firms
and (2) testing the industry subsample.
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The results reveal that green bond issuance increases firm value by 0.07 (7%) in
Tobin’s Q, supporting the stakeholder value maximization theory. The effect is more pronounced in high-ESG firms and sectors like technology (0.242) and energy (0.214), while
the industrial sector shows a slight decline (-0.066). A dynamic analysis indicates that the
positive effect emerges immediately after issuance but fluctuates over time. These results
highlight the financial and strategic advantages of green bonds in aligning corporate value
creation with sustainability goals.
The findings and discussion of this study contribute to at least two research streams.
The first contribution is to the literature on corporate finance, where the value maximization theory is applied to the decision-making process of financial managers (Deng et al.,
2013; Humphrey et al., 2012; Zerbib, 2019). The second contribution is to the literature on
the association between green bond issuance and firm value (Flammer, 2021; Jiang et al.,
2022; Khurram et al., 2023; Tang & Zhang, 2020; Wang et al., 2020; Yeow & Ng, 2021; R.
Zhang et al., 2021). This study tests the relationship between the issuance of green bonds
as a decision regarding firm financing and the value of the firm, from the perspective of
maximizing stakeholder value. The question arises as to whether firms prioritize the interests of their shareholders by maximizing value or the interests of their stakeholders by
improving the firm’s ESG scores at the expense of value. This research also explores results
regarding the association between green bond issuance and firm value in different industries.
The remainder of this study is structured into four sections. Section 2 discusses the
theories and previous research concerning green bonds, firm value, and stakeholder value
maximization. Section 3 introduces the data and variables used in the study and identifies
the model and method of empirical strategy in evaluating the impact of green bond issuance on the firm's value and ESG scores. Section 4 presents the results and discusses their
implications. Section 5 summarizes the discussion.

Literature Review

Corporate Green Bonds and Firm Value

Prior research concerning green bonds seems to agree that they can be defined as a debt
instrument that is used to finance environmentally friendly and climate change-related
activities (Flammer, 2021; Horsch & Richter, 2017; Khurram et al., 2023; Larcker & Watts,
2020; R. Zhang et al., 2021; Zheng et al., 2023). In a more practical way, Tang and Zhang
(2020) explain that a green bond is a fixed-income security issued by capital-raising entities (corporations, financial institutions, government agencies, municipal, national, or
international organizations, or other entities) to fund their environmentally friendly projects such as renewable energy, sustainable water management, pollution prevention, climate change adaptation, and CO2 emission reduction.
The interesting puzzle surrounding green bonds is the question of what might
drive the company to issue them. Compared to the conventional bond, a green bond has
more constraints related to the use of the proceeds of these funds, which restrict companies' investment policies. Although it is voluntary, for an instrument to qualify as a
green bond (such as being included as a CBI or Climate Bond Initiative-aligned bond),
companies have to go through third-party verification, which incurs more administrative
and compliance costs. The disclosure requirements for green bonds are more complicated
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than for conventional ones. Additionally, if the company fails to fulfill the requirements, it
can be exposed to greenwashing and reputational issues. The more reasonable strategy for
firms is to just issue conventional bonds and invest the proceeds into green projects if it is
evident that they are more financially viable than other projects (Flammer, 2021).
The question being asked in this research to address the puzzle is whether the firms
issue green bonds to increase the value or only to improve their reputation by increasing
their ESG scores by showing commitment to the issue without increasing the value. According to previous research, there are different angles to assess as to whether green bonds
affect firm value, namely in terms of (1) the cost efficiency of its operating process, (2)
the market reaction to green bond issuance, and (3) the pricing premium of green bonds.
First, green bonds can be issued for energy management projects that are directed toward
energy efficiency. Energy management projects can reduce operational costs, have a lowrisk ratio, and improve productivity. A green bond is one kind of debt financing available
to firms; for instance, in the energy sector, this type of financial arrangement mitigates
the constraints on a facility’s funding, allowing it to reap the benefits from energy savings
(Woodroof, 2009).
Second, green bonds can influence firm value through market reaction from the
issuer’s signal of environmental and social commitment to the investor. In this stream,
Flammer (2021) has documented a positive cumulative abnormal return (CAR) from
stocks between the 5-10 event window of green bond issuance. He finds a positive investor
reaction of 0.49% to the event, and he states that, consistent with the pecking order theory, the stock market generally shows no significant reaction to bond issues. Instead, the
reaction is likely explained by the signaling theory. This indicates that investors appreciate
green bonds as a means to increase shareholder value (Baulkaran, 2019; Ekawati, 2025;
Tang & Zhang, 2020). From an issuer perspective, a recently published article examines
the green bond issuance on corporate value using the Tobin’s Q and finds that a company
issuing green bonds has a Tobin’s Q ratio that is 0.215 higher than a company that does not
issue green bonds, considering firms characteristics, control variables of ROA, net asset
per share growth rate, and leverage (Khurram et al., 2023). Sustainable financing assists in
enhancing long-term firm value (Wang et al., 2020).
Third, from an investor perspective, Larcker and Watts (2020) examine whether
firms are willing to trade off wealth for societal benefit from the yield difference between
green bonds and comparable conventional bonds. If the yield difference exists, then there
is a premium (also called greenium) for green bonds, which means investors are willing
to trade off wealth for societal benefit, and the opposite applies if there is no difference.
By exploiting municipal green bonds and comparable conventional bond databases in the
US, they find that the greenium is essentially zero. In his study, Zerbib (2019), on the other hand, concludes that the greenium exists in the low difference of yield spread between
the green and conventional bond, and this low rate of greenium does not have substantial
influence on firm value.
Overall, according to previous studies of green bonds at the instrument level (investor perspective) in the US, it seems they have no substantial greenium in the market
(Flammer, 2021; Larcker & Watts, 2020; Zerbib, 2019). At the issuer level (firm perspective), Flamer, who also uses US data, suggests that the material effect of green bonds is
explained through signaling theory, which applies in the market and is observed from the
positive cumulative return of the green bond issuer stock price.
However, in China, both at the issuer and instrument levels, studies on green
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bonds suggest that they have a significant economic impact, both in terms of the greenium
and firm value. This effect might be partly explained by regulations, policy incentives, and
even tax benefits implemented to promote sustainable finance, including green bonds. As
the world's leading greenhouse gas emitter, China faces pressure and has committed to
reducing its carbon footprint with a net-zero target. Therefore, the evidence of whether
green bonds affect firm value at the issuer level remains puzzling.

Stakeholder Value Maximization: The Case of Green Bond

There are at least two general reasons for adopting green bond issuance events to study
the stakeholder value maximization theory in this research. First, issuing green bonds is
a critical financing decision for managers. Like conventional bonds, this instrument will
directly affect the firm's financial structure, especially for a firm that operates with high
leverage (Modigliani & Miller, 1958). In this regard, the financing cost and its risks must
be measured precisely to provide a promising positive net present value and increase firm
value. Wang et al. (2020) have documented a lower yield of 34 basis points for green bonds
in China, denoting lower financing costs for the issuer of green bonds compared to when
they issue conventional bonds. Hence, the decision to issue green bonds is not a trivial one
for finance managers.
Second, the issuance of green bonds requires several stakeholders to acknowledge
some technical knowledge of energy efficiency financing (Woodroof, 2009). Unlike conventional bonds, which usually primarily involve only bondholders, green bonds often
involve more diverse stakeholders, for instance, environmentally friendly investors and
third-party certifiers, including firms’ employees and suppliers; furthermore, for reasons
of compliance, they involve government and regulations. For example, compliance and
internal control for green bonds are costly from the issuer’s perspective. Although the process is voluntary, bonds must be included in the Climate Bond Initiative (CBI) green bond
database and labeled "CBI-aligned" to enhance investor confidence. The EU green bond
standards also require independent third-party reviews, making stakeholder approvals
essential for the finance manager to issue green bonds.
Regarding those reasons for compliance, according to previous research (Deng et
al., 2013; Wang et al., 2020), there are two opposing perspectives regarding the rationale of
green bond issuance by firms: stakeholder value maximization versus stakeholder interest
at the expense of the shareholders (depicted in the conceptual framework diagram below).
The stakeholder value maximization perspective delineates that maximizing the value for
shareholders is congruent with the goals of another stakeholder. Serving broad parties
that are related to and affected by the firms is beneficial for the firm’s long-term sustainability. Therefore, it will likely preserve the firm’s operations and protect its reputation,
thus positively affecting shareholders’ wealth (Jensen, 2010). This perspective is supported
by empirical evidence supporting the signaling theory gathered by Flammer (2021). Employing an event study method, Flammer documents that investors react positively to the
issuance of green bonds. He finds a positive cumulative abnormal stock return of 0.49% in
between 5-10 event windows of green bond issuance. He further explains that this positive
reaction is likely not attributed to the bond issuance itself but rather to the signals of the
firm’s commitment to the environment (Flammer, 2021).
In contrast, the stakeholder interest at the expense of the shareholders perspective
argues that stakeholders such as managers could pursue their interests at the expense of
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the shareholders. Managers might do this for several reasons, such as securing a position
or exercising short-term gain. This perspective implies that managers have environmental
or social responsibility when spending shareholders’ money. In line with the shareholder
theory, as argued by Friedman (1970), “the social responsibility of business is to increase
its profits.” Firms are only obligated to use their resources for profit maximization and act
as agents responsible only to their shareholders as long as they do not commit fraud. This
notion raises an empirical question: Are environmental and social responsibility doing
harm or good to the firm? Although the measure of good can be debatable, we measure it
in this study by the firm's value. Additionally, if environmental and social responsibility
do harm to the firm value, an alternative view to the stakeholder interest at the expense of
the shareholders perspective is that these shareholders are willing to accept lower profit
to incentivize their values, such as commitment to the environmental and social issues
(Starks, 2023).

Diagram 1. Conceptual framework of Green bond on Firm value relationship diagram
The main discourse between the stakeholder theory and the shareholder theory in
terms of value maximization centers on the fundamental purpose of the corporation. As
explained above, shareholder theory suggests that corporations only serve their principals,
that is to say, their shareholders; therefore, by maximizing shareholder value, they have
fulfilled their social responsibility. The shareholder theory argues that, as businesses, firms
should only be concerned with profitability as a measure of value. Environmental and social responsibilities such as eliminating poverty or reducing pollution harm the business
and are the responsibility of individuals or the government, not of businesses. This theory
can provide a precise measure of performance that is comparable between companies and
distinguishes between good and bad companies (Jensen, 2010). This theory also assigns
clear roles to corporations, individuals, and the government in a free society.
However, the shareholder theory perspective in maximizing value may only be
complete by considering another stakeholder. Considering environmental and social responsibility as part of the stakeholder may not maximize value, yet it is not possible to
maximize value when stakeholders are ignored. As a means to maximize value, finance
managers should satisfy and obtain support from all corporate stakeholders, customers,
employees, managers, suppliers, local communities, and government. That said, businesses cannot be accountable to all stakeholders simultaneously because it would mean that
they are accountable to none of them. Jensen (2010) argues that maximizing shareholder
value should still be an anchor while the business is responsible to stakeholders. This value
acts as a comparable measure to separate between the better and the worse.
A recent article analyzes the effect of green bond issuance on corporate value using Tobin’s Q and finds that companies issuing green bonds have a Tobin’s Q ratio that
is 0.215 higher than those that do not. This comparison considers control variables such
as return on assets (ROA), net asset per share growth rate, and leverage (Khurram et al.,
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2023), which may cause Tobins’s Q values to vary across firms. Flammer (2021) uses an
event study methodology that tests the fluctuating and short-term stock price of a firm in
a specific event window. Therefore, by expanding the data using universe of green bond
issuance, we aim to provide a more comprehensive understanding of the association between green bonds and the value of the firm, as measured by Tobin’s Q, which also reflects
the growth and long-term expectations in terms of firm value.
From a risk-related perspective, Zhang et al. (2021) explore green bond issuance
in the Chinese bond market to understand its influence on the cost of capital in terms of
yield spread. They describe three ways in which firms can minimize the cost of capital by
issuing green bonds: (1) it reduces information asymmetry, (2) it improves the liquidity
of their security, and (3) it lowers perceived risk. Using the difference-in-differences (DD)
method, Zhang et al. (2021) can calculate that the corresponding 24.9 basis points of yield
for firms issuing green bonds is lower than the control firms that do not issue green bonds,
suggesting evidence of the green premium of the green bonds.
Focusing on the same market, J. Wang et al. (2020) have found that the yield spread
of Chinese firms that issue green bonds is considerably lower than companies that do not
issue green bonds of 34 bps (basis points). This 34 bps is not trivial since considering their
yield spread means a dataset that is 213 (15.3% of the average) and a total face value of
the bonds of USD 29.6 (USD 100.6 million savings per year) of the company with green
debt. The yield spread difference confirms a green bond premium, meaning investors are
willing to trade higher prices for environmentally friendly projects.
From the stakeholder theory point of view, shareholders are the leftover residual
owners of the firm’s assets. They come after employees, suppliers, creditors, and the government (Jensen, 2010; Ross et al., 2019). The goal of financial managers is to maximize
the current value per share only and this means that shareholders will gain more if everyone else is also gaining (Ross et al., 2019).
Based on the confounding result of return and the risk-related effect of green bond
issuance on the firm value, this study aims to draw a causal relationship between green
bond issuance and a firm’s value measured by Tobin’s Q. We take this measure as it reflects growth value of the firm and is the most widely used proxy for establishing a firm’s
value. Previous research rigorous methodology motivates this research to use the difference-in-differences (DD) method in estimating the best-educated guess about the true
cause of the impact of green bond issuance on the firm value (Flammer, 2021; Khurram et
al., 2023; Tang & Zhang, 2020; Wang et al., 2020; R. Zhang et al., 2021; Zheng et al., 2023).
If the result is positive, it will reveal that signals perceived by investors are not only that the
firm commits to the environment, but also that both investor and issuer being perceived
as having a commitment to green practices can actually increase the value of the firm. If
the result is negative, then a green bond might reasonably decrease firm value. However,
if the result is not significantly different from zero, then green bonds do not really have
a material impact on firm value. Therefore, this test might complete the signaling theory
hypothesis of Flammer’s (2021) research. More importantly, it can be asserted that the
issuance of green bonds, as an expression of a firm's commitment to environmental sustainability, bears a causal relationship with the firm's intrinsic value.
H1: Firms that issue green bonds have higher firm value compared to firms that
do not issue green bonds. Green bonds can increase firm value.
H2: Firms that issue green bonds have lower firm value compared to firms that do
not issue green bonds. Green bonds can decrease firm value.
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H3: Firms that issue green bonds have the same value compared to firms that do
not issue green bonds. Green bonds are not significantly material to firm
value.

Methods
Data

To compile the sample dataset of this research, we extracted green bond issuance data
from Refinitiv’s green bond guide. These data contain a universe of green bond issuance
at the instrument level; the data include the column for the date issued and maturity date,
which we will use to create a dummy for the treatment group and for post-treatment in
our firm characteristic dataset. The firm characteristics dataset was also acquired from
Refinitiv’s database; we used six industries over a period from 2013 to 2023 (year to date
in December 2023) according to The Refinitiv Business Classification (TRBC) specifically.
For the industry, country, and year, firm characteristics are collected for each firm’s value, and growth measure (Tobin’s Q), firm profitability (ROA and ROE), firm size (total
assets), firm structure (total long-term debt), and firm environmental, social, and governance performance measured by E, S, and G scores. From the above dataset, we obtained a
sample dataset of six industries of firms that issue green bonds (99 firms) and do not issue
green bonds (524 firms) with each firm’s characteristics, indexed by firm, year, industry,
and country, resulting in a total of 6,853 observations with 372 treated group and 6,481 in
the control group.

Definition of Variables

We use Tobin’s Q to measure firm value at each financial year-end during the sample period. Tobin’s Q, a widely used measure in studies, is the ratio of a company's market value to
its replacement cost. In this study, Tobin’s Q is calculated by dividing market capitalization
by total assets (Hao et al., 2022). The detailed description of all the variable measurements
we used in this research is obtained from the Refinitiv database and is disclosed in the
appendix.

Research Model

The difference-in-differences (DD) method is the most widely used in the exploration of
causal inferences (Autor, 2003; Goodman-Bacon, 2021). The DD method provides robust
estimations of causal effect since it compares the average value of the outcome variable
while being conditional on a vector of control variables with time and individual fixed
effect. In this research, since firms voluntarily issued green bonds in the different time
periods from 2013 to 2023, these bonds become a treatment effect, and therefore we exploit the variation across groups of firms that receive treatment at different time periods.
Another form of employing the DD method is the two-way fixed effect. This research’s
specifications use a vector of dummies for individuals and time (staggered or roll-out program) to elicit the treatment effect on the outcome variable. This mechanism allows us to
identify the effect of green bond issuance on the firm value measured by Tobin’s Q using
a staggered DD model. By exploiting the fact that the green bonds are issued in different
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firms and years, we assess their causal impact by contrasting Tobin’s Q in green bond issuer firms and non-issuer firms. The underlying idea is that there are no other changes in the
units that can affect the outcome of interest after controlling for all the correlated variables
except for the program by introducing time and individual fixed effects. In other words,
the DD estimation method overcome the selection bias and time trends that might affect
the outcomes of interest (Karimah & Yudhistira, 2020).
For this staggered DD method, we assign the variable of interest 1 if the company
issues a green bond for the treated group and 0 otherwise for the control group. We then
assign 1 for the year of issuance and the preceding year, and zero otherwise. Hence the
combined dummy of treatment and post (or, more generally, two-way fixed effect) creates
the beta of the variable of interest. This beta is the difference of green bond issuance on
the firm value between the green bond issuer and non-issuer or the impact of green bond
issuance on firm value.
We motivate the effect of green bond issuance on the firm value based on an assumption that the firm that is the first-time issuer of a green bond is comparable to the
firm that has issued a green bond in the following period and to the firm that did not issue
a green bond over the fixed effects and time-varying control variables. For a firm that did
not issue a green bond, the fixed effect and time-varying control alone should explain the
change in the value of the firm.
Firms that issue green bonds are not issuing them in the same year; we use the
staggered DD method to account for this policy difference. To elicit the causal effect of the
green bond issuance on the firm value and address time-varying differences (as long as
it has a parallel trend between the treatment and control group), we adopt prior research
estimates (Flammer, 2021; Karimah & Yudhistira, 2020; Khurram et al., 2023). With some
modifications, our baseline estimate is as follows:
Qit= β0 + β1GBit + θXit + βi + βt + εit
(3.1)
Where Qit is Tobin’s Q as a direct measure of firm value i in year t. GBit is the green
bond issuance as a variable of interest and equal to 1 for the firm i that issues bonds in time
t. β1 captures the difference in Tobin’s Q between the treatment and control group of firms
after issuing green bonds. If issuing green bonds is beneficial to the firm value measured
by Tobin’s Q, we expect that β1 is positive and statistically different from 0. Since Tobin’s
Q measure is expressed as a ratio, the effect of green bond issuance on firm value is interpreted as how much in ratio the firm value in terms of Tobin’s Q increases or decreases.
Xit represents the vector of time-variant control variables that might affect the outcome of estimation. It comprises company characteristics control variables taken from
previous research (Flammer, 2021; Khurram et al., 2023): return on assets (ROA), return
on equity (ROE), leverage, long-term debt, size of the firm, and environment, social, and
government score. ROA and ROE are included to control that the treated firm may be
more profitable and therefore easier to issue debt. ROA and ROE may also have an influence on firm value; higher ROA and ROE mean the company is profitable, which is
reflected in Tobin’s Q. While size, leverage, and long-term debt control for firms with more
access to the capital market, while leverage and long-term debt as firm capital structure
may also have an impact on the firm value (Ross et al, 2019, pp. 10-12). For size, the bigger
the size of a company, the bigger its chance to invest in green buildings. Environmental,
social, and governance scores ensure that treated and controlled firms have similar envi359

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ronmental performance prior to the green bond issuance. The method of using confounding control variables to decrease bias is also conducted by Khurram et al. (2023).
Certain industries, such as real estate, follow a cyclical trend and are highly influenced by regional characteristics (e.g., regulation, geographical conditions). Some of the
industries have faced strong pressure to improve their environmental and social performance in the last decade. We include individual fixed effect βi which is a vector of dummy
variables for each individual that control for mean differences in Tobin’s Q values across
firms, and yearly time fixed effect βt which is a vector of dummy variables for each year
that control for changes in Tobin’s Q values common to all firms. εit is an error term (Autor, 2003).

Results

Baseline Result: The Impact of Green Bonds on Firm Value

Here we report our baseline model estimation results. Table 1 presents the results of the
multiple tests for hypothesis 1. In every column, the dependent variable is Tobin’s Q in tt-1
indexed by firm and year. The first model in column (1) is the result of the effect of the
green bond on the Tobin’s Q value without including individual fixed effect, time fixed
effect, and covariates of the control variable. The coefficient is 0.08 positive and significant
at a 5% probability value. The results seem to suggest that the difference between treatment and control firms in our data sample is 0.08 compared to the firms that did not issue
green bonds. However, this estimate does not include the time-variant effect, idiosyncratic
individual effect, and any other relevant control variables that might affect the Tobin’s Q
value of the firm. Hence, our estimation model in column (1) is likely to be overestimated.
In column (2), given that green bond issuance also depends on unobservable variation across firms (idiosyncratic effect) and years (time effect), we introduce year and firm
fixed effect. Thus, we can see from the results that the coefficient drops to 0.071 and is significantly positive with a 5% probability value. Additionally, in column (3), we include the
following control variable covariates: environment, social and governance score, a log of
the total assets, leverage, ROA, ROE, and a log of the long-term debt to the equation since
those variables might affect both Tobin’s Q and the green bond issuance of the firm. The
results show that the coefficient changes slightly to 0.069, while the coefficient significance
remains. In column 4, however, we use the same specification as in column 3 but cluster
the standard error in the country of headquarters and find that the coefficient remains the
same, while the standard error seems to be higher. Thus, we prefer the model specification
in column 3, which suggests that the firms that issue green bonds systematically have a
Tobin’s Q value that is 0.07 higher than the firms that did not issue green bonds.
The overall result of this model seems in line with previous research that had found
a positive effect of green bonds on firm value. According to our findings, the coefficient
of green bond issuance is lower than that of Khurram (2023), who uses data from China;
he finds that green bonds can, on average, increase the Tobin’s Q level in China by 0.19
(Flammer, 2021; Khurram et al., 2023; Wang et al., 2020). The effect of Tobin’s Q being
0.07 higher for green bond issuers seems to be quite small considering that Tobin’s Q is the
replacement cost of firms’ market value. This result can be partly explained by the small
portion of green bonds over the duration of the total long-term debt of the firm. Therefore, in this regard, Flammer (2021) argues that the improved firm performance is unlike360

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ly to be the direct effect of green projects funded by green bonds because its proportion is
small compared to the total size of the firms.
Jiang et al. (2022), who also use data from China, find—in their baseline estimation of the effect of green bond issuance on firm value—that the difference in effect between the green bond issuers and non-green bond issuers in firm value is significant at
0.2 points in the Tobin’s Q level. In line with this previous research result, our findings are
much lower at 0.07. Our lower coefficient result seems more reasonable since we use much
broader data on green bond issuers as well as various significant control firms. Flammer
(2021) mentions that the green bond market is still in the early development phase. The
market of corporate green bonds represents only a tiny share of the overall corporate bond
market (USD 95.7 billion over USD 102.8 trillion in 2018). With this in mind, our results
need not be generalized to future years. Rather, it is safe to consider for the time being that
green projects that are to be funded by green bonds are adequately profitable to sustain
competitive returns with conventional bonds.
Prior research has documented that the effect of green bonds on firm value might
be explained by country-specific policies and incentives (C. Zhang & Zhou, 2023). For
instance, China is one of the top emitters in the world and has a tight policy regarding
environmental and social issues (Shen et al., 2017). Meanwhile, the US and Europe have
more advanced green bond markets relative to other regions like Asia. The effect is not
homogeneous across industries. High-emitter industries such as energy, industrials, and
basic materials are likely to be severely affected by the pressure. Technology, on the other
hand, might be the industry that can reap the benefit because most of its assets are intangible, and they can easily disclose that they are responsible (Hoepner et al., 2010). In that
matter, although indirectly, we are able to capture country-specific and industry effects
with the set of dummy variables for each individual firm and time. This is evident in column (4) of our model specification after including country-clustered standard error; after
testing the model using a dummy variable for each country (not reported in the table), the
coefficient remains as in column (3).
This result has to be interpreted with caution, as our model might still suffer from
the limited number of observations. This is especially so in the generalization of the result
for all industries. It is worth mentioning that our model does not incorporate macro variables such as interest rate and gross domestic product. However, our model of time-fixed
effect should partly reflect the influence of omitted variables or unobserved heterogeneity
that are constant or fixed over time in the model1.
Table 1 also provides the coefficient for the control variables used in the estimation
of equation (3.1). Based on column 3 (our preferred specification), the sign of these covariates is as expected and is statistically different from zero except for the E, S, and G scores.
The E, S, and G coefficients are close to zero and insignificant to Tobin’s Q. The result of
another control variable of firm characteristics is consistent with the previous research.
Leverage and long-term debt both have negative associations with Tobin’s Q. The log of the
long-term debt variable in this model’s estimation is a control variable, holding this value
constant; the green bond as a portion of a firm’s total debt is associated with a marginal
increase of 0.07 in the Tobin’s Q value. This result of control variables is consistent with
prior research that used data from China, which found that ROE and leverage have a significant effect on the firm value (Khurram et al., 2023). Although, in terms of magnitude
(every one unit increase in return on assets increases firm value by 2.3, and every one unit
decrease in leverage by 1.1), in prior research, it is bigger, consistent with the bigger magWe tried the estimation by including industry and country dummies alongside time and firm fixed
effect and found that the results for both industry and country dummies needed to be omitted because of
collinearity.
1

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nitude of the green bond effect on the firm value in that research. This difference might be
due to the different data used in the sample; while prior research used data from China,
this research has used global data.
Table 1. Impact of Green Bonds on Tobin’s Q Values, Baseline Estimate
VARIABLES
Green bond

(1)
Tobin’s Q
0.084**
(0.034)

(2)
Tobin’s Q
0.071**
(0.036)

(3)
Tobin’s Q
0.069**
(0.033)
-0.001
(0.001)
-0.000
(0.001)
-0.000
(0.000)
0.114***
(0.028)
0.022***
(0.002)
0.002*
(0.001)
-0.000**
(0.000)
-0.058***
(0.010)

(4)
Tobin’s Q
0.069
(0.066)
-0.001
(0.001)
-0.000
(0.001)
-0.000
(0.001)
0.114***
(0.037)
0.022***
(0.006)
0.002
(0.004)
-0.000
(0.000)
-0.058***
(0.018)

6,230

6,230
0.037
623

6,188
0.141
623

6,188
0.141
623

Environmental score
Social score
Governance score
Ln total asset
ROA
ROE
Leverage
Ln long-term debt

Observations
R-squared
Number of firms

623

Notes: This table reports estimates of the difference in difference specification in equation (3.1). The dependent
variable is lag 1 of Tobin’s Q as a measure of firm value (Usman et al., 2020). Standard errors of means are in
parentheses. Covariates include E, S, and G scores; a log of total assets; return on assets; return on equity; leverage; and a log of long-term debt. These estimations use firm-level panel data from the period 2013 to 2023. Since
we use the lag 1 dependent variable and the difference-in-differences method 2013 and 2014 (for the dummy
base) are omitted. The data are retrieved from Refinitiv. *** p<0.01, ** p<0.05, and * p<0.1 indicate statistical
significance at 10%, 5%. and 1%. respectively.

Leverage—calculated as net debt over shareholder equity—and long-term debt
indicate a negative trend in terms of Tobin’s Q values. This result is consistent with the
findings of Khurram et al. (2023), who also document the negative relation between leverage and the value of the firm as measured by Tobin’s Q. A higher leverage ratio means
that there is more debt than equity in a firm’s capital structure. Thus, increasing this ratio
would burden firms in fulfilling their obligation and drive market value down. Overall, the
result in this estimation result supports hypothesis 1 that managers issue green bonds with
the purpose of stakeholder value maximization.
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Parallel Trend Assumption Test and the Dynamic Effect of Green Bonds
on Firm Value

Complementing the above results—regarding the discrete impact of green bonds
on firm value—in the context of answering the first research question, we provide the
answer to the second research question with the dynamic effect of the green bond on firm
value. For instance, one might ask how quickly the impact of green bonds can be perceived
and whether the impact grows or diminishes after the issuance of those green bonds. Our
previous specifications do not explain this dynamic impact of the green bond issuance on
firm value. To elicit the dynamic impact in our sample study, we applied the specifications
suggested by Autor (2003) by modifying equation (1) and introducing variables: 10 years
before the first issuance of the green bonds and 10 years after. This effect is the average
treatment on the treated firms (isuuing bonds) distributed across time used in the sample
study; specifically, the model is as follows:
(4.3)
Where β-τ and β+τ represent the anticipatory effects and post-treatment, respectively. Notice that we replace β1 from the baseline estimate to β-τ and β+τ to elicit the dynamic
effect and average of the green bonds’ effect on the firm value each year. If green bond
issuance drives an increase in the Tobin’s Q value of the firm, we expect the coefficient
of anticipatory effects to be close to zero. At the same time, the post-treatment effects
provide the dynamic impacts of the Tobin’s Q value of the firms. Figure 4.1 suggests that
the Tobin’s Q value is already impacted in the issuance year of the green bonds and 1 year
preceding the issuance. The coefficient is positive and statistically significant immediately
when the green bonds are issued and one year after that, yet the effect in the subsequent
year is diminishing and statistically insignificant. However, the effect seems to be negative
in the fourth year after the issuance, although it is statistically close to zero. Figure 4.1
depicts the green bond effect starting to bounce back after year 5 and it is likely to need
5 years to provide robust positive effects on the Tobin’s Q value. The effect appears to be
positive although still insignificant in years 5 and 6, while 7 years forward from the first
green bond issuance, the coefficient is positive and significantly different from zero. Year
7 seems like a jump effect since after year 7 (8 to 10) the coefficient is still positive but
returns to the level similar to year 6. From Figure 2, we obtain suggestive evidence of the
absence of anticipatory responses to the green bond issuance: The coefficients for the lead
term are statistically insignificant and are close to zero, showing little evidence of an anticipatory response in firms about to issue green bonds. Thus, Figure 2 also suggests that the
parallel trend assumption of our DD model is likely to hold; this means that there is the
same (parallel) trend of the average Tobin’s Q level before the issuance of green bonds for
firms that are both green bond issuers and non-green bond issuers.

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Figure 1. Time passage relative to the year of green bond issuance effect on firm value,
the dots indicate the coefficient and the line between dots is the confidence interval
This result is in line with Jiang et al. (2022) who find the dynamic effect of green
bonds on the firm value weakens gradually and is unsustainable. A possible reason for this
effect is that the green bonds issued by issuer firms have various maturity periods. In his
sample, most of the green bonds have a 3- to 5-year maturity period, and they find that in
year 3 the effect is declining. In our sample study, many of the green bonds mature in years
5, 10, and 8, respectively, while the least amount of green bonds are those that mature in
year 8. The maturity periods and graphic seem to have a common pattern; the effect of the
green bonds on the Tobin’s Q value is more pronounced in the year after the firm repays
the principal to the bondholders due to the freed-up space in the firm’s balance sheets.
Subsequently, in the year of the repayment when the bond matures, the Tobin’s Q value
seems to decline due to the repayment burden. This result, indicating a heterogeneous
average effect each year, is also evident from the previous research on parallel trend tests
and dynamic effects (Khurram et al., 2023; Larcker & Watts, 2020).

Robustness Test
High (Low) ESG Combined Score Subsample

To distinguish between the two competing views, stakeholder value maximization and
shareholder expense, we employ a firm-level measure of aggregate ESG performance. We
obtain data on firms’ ESG performance from Refinitiv’s ESG combined score database.
This database contains extensive information about firms' ESG combined scores and is
widely used for evaluating ESG activity. These scores measure the ESG performance of the
firm adjusted due to adverse news or media coverage of greenwashing practices; therefore,
if there is news reporting about greenwashing, the score is reduced.
Using the same model specification as in the baseline model, as per the high (low)
subsample depicted in Table 2, the results are consistent with the stakeholder value maximization hypothesis. In the high ESG combined score subsample, the association between
green bonds and firm value is positive. In contrast, in the low ESG combined score sub364

Fani & Prijadi

sample, there is a negative correlation between green bonds and firm value. Our result in
the baseline estimation of all samples seems to be driven largely by the high ESG combined score firms. This can be seen because the number of treatment groups (green bond
issuers) is higher in the high ESG combined score subsample (218) than in the low one.
Table 2. High ESG Combined Score Subsample
(1)
Tobin’s Q

(2)
Tobin’s Q

(3)
Tobin’s Q

(4)
Tobin’s Q

0.054

0.089

(0.055)

(0.058)

0.083
(0.055)

0.083
(0.124)

Time fixed effect
Individual effect
Control variables

No

Yes

Yes
Yes
Yes

Yes
Yes
Yes

Observations
R-squared
Number of firms

5,664

5,622
0.151
596

5,622
0.151
596

-0.009
(0.053)

-0.009
(0.043)

Yes
Yes
Yes

Yes
Yes
Yes

5,615
0.150
597

5,615
0.150
597

VARIABLES

Panel A upper, ESG
combined score

Green bond

Yes
No
5,664
0.034
596

596

-0.012

-0.014

(0.055)

(0.057)

Time fixed effect
Individual effect
Control variables

No

Yes

No

Yes

No

No

Observations
R-squared
Number of firms

5,657

5,657

Panel B under, ESG
combined score
Green bond

0.033
597

597

Notes: We form the high (low) ESG combined score subsample by sorting the data by ESG combined score from
largest to smallest. The value of the ESG combined score is 0 -100. After sorting, we divide the sample into half,
forming the upper and lower of ESG combined scores. This is an unbalanced panel data since we split the high
and low for each year and each firm. The table reports estimates of the difference in difference specification in
equation (3.1). The dependent variable is lag 1 of Tobin’s Q as a measure of firm value. Standard errors of means
are in parentheses. Covariates include E, S, and G scores; a log of total assets; return on assets;return on equity;
leverage; and a log of long-term debt. These estimations use firm-level panel data from the period 2013 to 2023.
The data is retrieved from Refinitiv. *** p<0.01, ** p<0.05, and * p<0.1 indicate statistical significance at 10%,
5%, and 1%, respectively.

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The results support the stakeholder value maximization perspective and are consistent with prior research that has studied the stakeholder value maximization theory by
dividing the high (low) subsample and using a merger case study (Deng et al., 2013). It
is also in line with prior research, which has shown that, compared to the low ESG score
firms, the higher ESG score firms have a lower cost of debt (Apergis et al., 2022). The
higher ESG score firms tend to have better transparency, which would allow stakeholders
to share the benefits in terms of value and goals (Wandebori, 2018). Additionally, lower
ESG management firms may have difficulties in obtaining funding either from banks or
investors. In financing firms with lower ESG practices, banks are becoming increasingly
cautious of the associated reputational and credit risks as well as the risk of finding the
firms liable to environmental obligations (Kroszner & Strahan, 2001).

The Effect in Different Industries: Green Bonds’ Impact on Firm Value

The results displayed in Table 3 signal that the effect of green bond issuance on firm value is heterogeneous across industries. A significant effect is observed in the technology
industry, resulting in a 0.242 increase in the Tobin’s Q value for green bond issuers. We
only observed a negative coefficient in the industrial sector of -0.06. The strongest positive
effect is in the energy and technology industry, with a positive 0.2 value of Tobin’s Q. Energy is the sector where public and government attention has been the highest in recent
years following the pressure to incorporate ESG, especially in terms of the environment,
into their financing decisions. Technology is under high pressure in terms of social issues.
Thus, all the results showing green bonds' positive impact on the firm value in our sample,
as presented in Table 1, seem to be driven by these two industries.
Table 3. Effect of Green Bonds on Tobin’s Q Values in Different Industries
VARIABLES
Green bond
Environmental score
Social score
Government score
Log total asset
ROA
ROE
Leverage

366

0.214

(2)
Technology
0.242**

(0.132)

(0.101)

(0.056)

(0.062)

(0.064)

(0.042)

-0.003

-0.004**

0.001

0.000

0.001

0.000

(0.002)

(0.002)

(0.001)

(0.001)

(0.001)

(0.001)

-0.000

0.002

0.001

-0.001

-0.003**

-0.001

(0.003)

(0.002)

(0.001)

(0.001)

(0.001)

(0.001)

-0.003

0.001

0.001

0.000

-0.000

0.001

(0.002)

(0.001)

(0.001)

(0.001)

(0.001)

(0.001)

0.030

0.288***

-0.052

-0.168***

0.187***

0.364***

(0.109)

(0.077)

(0.067)

(0.062)

(0.050)

(0.047)

0.035***

0.014***

0.021***

0.054***

0.022***

0.039***

(0.008)

(0.005)

(0.007)

(0.006)

(0.005)

(0.007)

-0.014***

0.007

0.005

-0.002

0.002

-0.003

(0.003)

(0.005)

(0.003)

(0.002)

(0.002)

(0.003)

-0.001*

-0.000

-0.001

0.000

0.000

-0.001*

(0.001)

(0.001)

(0.000)

(0.000)

(0.000)

(0.000)

(1)
Energy

0.054

(4)
(5)
Industri- Basic maals
terials
-0.066
0.071

(6)
Real
estate
0.004

(3)
Utilities

Fani & Prijadi

Log long-term debt

0.048

-0.042*

-0.163***

-0.045**

-0.088***

-0.247***

(0.055)

(0.022)

(0.043)

(0.023)

(0.014)

(0.033)

Observations

627

1,249

489

1,646

1,487

690

R-squared

0.094

0.178

0.195

0.223

0.211

0.323

Number of firms

63

127

49

165

150

69

Notes: This table reports estimates of the difference in difference specification in equation (3.1) in column (3).
In each column, the dependent variable is lag 1 of Tobin’s Q as a measure of firm value. We include a two-way
fixed effect, a first-time fixed effect a vector of dummy variables representing year and individual fixed effect,
and a vector of dummy variables representing each firm. Standard errors of means are in parentheses. Covariates include E, S, and G scores; a log of total assets, return on assets; return on equity; leverage; and a log of
long-term debt. These estimations use firm-level panel data from the period 2013 to 2023., Since we use the lag 1
dependent variable and the difference-in-difference method, 2013 and 2014 (for the dummy base) are omitted.
The data are retrieved from Refinitiv. *** p<0.01, ** p<0.05, and * p<0.1 indicate statistical significance at 10%,
5%, and 1%, respectively.

As a robustness check, the results in Table 3, which use the industry subsample,
indicate the same overall findings as in Table 1, which shows the results of the baseline
estimates using all samples. Aside from the coefficients of the green bonds as explained
above, this can also be seen from the firm characteristics control variables and time trends.
The firm characteristics control variables exhibit a similar pattern in most industries. The
log of total assets, the return on assets, and the log of long-term debt have a significant impact on the firm value. As for the time trends, the results are significant in the years 2018
to 2023, although not uniformly in all industries, and they are also similar to the results in
Table 1, which presents all samples in which significant time trends were observed in the
years 2018, 2020, 2022, and 2023.

Conclusion

The primary purpose of firms and their responsibilities to stakeholders remains an ongoing debate. Green bonds are still in the development phase, and they can serve as a
potential financing tool for managers to implement green projects within their firms. The
results of this research seem to suggest that green bonds have the drive to improve intrinsic firm value, represented by a higher Tobin’s Q value. Green bonds can be used to fund
energy management projects, which will cut costs and boost productivity. This positive
effect of green bonds on firm value is heterogeneous across industries and is more prevalent in firms with high ESG performance, supporting the stakeholder value maximization
theory. The results are consistent with the stakeholder theory, which posits that focusing
on shareholder value while considering the other stakeholders can benefit the firm's value
in the long term.
The use of a green bond issuance event to study the financing decisions of managers that favor stakeholder value is the center of this research. In other words, this study
focuses on green bonds as a mechanism to align environmental, social, and governance
(ESG) goals with shareholder interests, particularly in the context of global firms across
multiple industries. The study’s findings show that green bonds positively impact firm value, especially in high-ESG firms, and add to the growing body of literature on sustainable
finance.
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The empirical evidence indicating an 0.069 increase in the Tobin's Q value following green bond issuance has several implications for corporate managers and policymakers. This study proves that aligning financing decisions with environmental preservation
can actually increase firm value. This is related to the empirical findings of research on
the inclination of pro-environmental investors to engage in environmentally responsible investment (Hartzmark & Sussman, 2019); hence, managers can opt to satisfy both
shareholders and stakeholders, particularly environmental activists and altruistic investors, in generating long-term and stable value for the firm (Brodback et al., 2019). Based
on this result, policymakers could support the issuance of green bonds by enhancing ESG
disclosure requirements or incentivizing the issuance through tax benefits. Additionally,
this research highlights societal implications of green bonds. A 7% firm value boost from
green bonds could subsequently drive positive societal change by mobilizing funding for
projects that reduce carbon emissions, promote clean energy, and support climate resilience. These kinds of projects direct capital toward sustainable development, benefiting
communities through improved environmental quality and long-term economic stability.
To reiterate, the goal of this study is to revisit the theory of stakeholder value maximization using the case of green bonds and evaluating the motivation of managers in
issuing green bonds. This study employs the firm's green bond issuance data, Tobin's Q as
a firm value metric, and Refinitiv's ESG combined score to gauge the ESG performance of
firms. The recommendation from this study is for future research to incorporate a measure of policy regarding green bonds in each country. Future research could utilize various
measures of ESG performance from different rating institutions, such as Bloomberg and
Sustainalytics, to achieve a more comprehensive and reliable assessment of ESG performance, given that prior research has examined the weak association between ratings from
different institutions (Cornell & Damodaran, 2020).

Limitation

Data limitation is the issue in this study; there are many missing values in the ESG scores
from Refinitiv’s database. Thus, we have to remove all firms and observations containing
missing values. This leads to a notable decrease in the number of firms and observations.
Our estimation results in the baseline model might still be affected by other factors that
influence the firm's green bond issuance and value. Therefore, the generalization of the
results must be interpreted with caution, as the study’s sample includes only a small portion of green bond issuers. The measure of E, S, and G scores is solely based on Refinitiv’s
database. These ESG scores are taken from public information and companies’ voluntary
disclosures.
This research uses the difference-in-differences method to elicit the effect of green
bond issuance on firm value. We must meet two assumptions to provide robust estimation
results and establish a causal relationship. First, the parallel trend assumption states that
the outcome variable must behave similarly before the treatment is implemented. Second,
the treatment effect has to be constant over time. This research uses green bond issuance
as a treatment effect toward firm value. We assign a value of 1 to firms that issue green
bonds and a value of 0 to those that do not in order to indicate the treatment effect. We assign 1 for the year green bonds are issued by firms and the year preceding the issuance and
assign 0 otherwise in all years for post-treatment. However, firms issue different numbers
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of green bonds at particular times. For example, in 2019, Apple issued one green bond and
then issued another in 2021, while Microsoft issued only one green bond in 2019. For this
case, we would assign 1 to Microsoft from 2019 to 2023 and assign Apple 1 for 2019 to
2023 throughout our sample period. Therefore, the effect of green bonds on firm value in
these settings should be interpreted with that in mind.
This study only provides minimal evidence of the correct direction of causality
between the outcome and the interest variables. Since there are firms that have a high
Tobin’s Q value, this might affect the firm to issue green bonds (with credibility from the
debtor perspective). We address a little of the endogeneity problem or the reverse causality
problem along with the dynamic effect analysis above. Therefore, future research should
focus on addressing the reverse causality problem between green bonds and firm value.

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Appendix

Method
Variable Definitions
Variable name
Tobin’s Q

Variable definition
Company market capitalizations are divided by the total assets
of the firms.
Green bond
Variable takes 1 if the firm i is issuing a green bond in time t,
and 0 otherwise. The data is extracted from Refinitiv’s Green
Bond Data Guide dataset.
Environmental score Taken from the Refinitiv ESG score database. This number
measures the environmental performance of the firm and has
a value of 0-100, 0 being the company has 0 ESG performance
and 100 as the highest score (refinitiv.com/esg).
Social score
Taken from the Refinitiv ESG score database. This number
measures the social performance of the firm and has a value of
0-100, 0 being the company has 0 ESG performance and 100 as
the highest score (refinitiv.com/esg).
Governmental score Taken from the Refinitiv ESG score database. This number
measures the governance performance of the firm and has a
value of 0-100, 0 being the company has 0 ESG performance
and 100 as the highest score (refinitiv.com/esg).
Total asset
The sum of total current assets and total non-current assets is
reported in the fiscal year-end financial or annual report.
Leverage
The ratio (%) of net debt divided by the total value of shareholders’ equity. Shareholder equity includes minority interest,
and net debt includes hybrid debt. Net debt is calculated from
total debt minus cash and short-term investment total.
Return on assets
Is expressed in percentage terms (%). This value is calculated
as the income after taxes for the fiscal period divided by the
average total assets. Average total assets are the average of total
assets at the beginning and the end of the year.
Return on equity
The company's actual value is normalized to reflect the I/B/E/S
default currency and corporate actions (e.g. stock splits). Return on equity is a profitability ratio calculated by dividing a
company's net income by the total equity of common shares.
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Long-term debt

372

Represents total non-current debt or interest-bearing financial
obligations. It includes both convertible and non-convertible
debt. It includes non-current lease obligations, non-current
hybrid financial documents, and long-term FHLB advances.