2015-27
An empirical examination of how the corporate governance andstrategy affect GHG emissions efficiency
Bowen Zhou
Michiyuki Yagi Katsuhiko Kokubu

An empirical examination of how the corporate governance and strategy affect
GHG emissions efficiency
Bowen Zhou *, Michiyuki Yagi*, Katsuhiko Kokubu*
周博文・八木迪幸・國部克彦

Abstract
This study aims to empirically examine how environmental efficiency related to GHG emissions
is affected by corporate governance and activities. This study uses data from CDP (former Carbon
Disclosure Project) where the observations are 686 firms worldwide in 2013. As proxy for theenvironmental efficiency, this study adopts GHG emissions per employee. As independent
variables, this study uses dummy variables made from CDP questionnaire. Regarding thecorporate governance, this study finds that the amount of greenhouse gas emissions per employee
is low (i.e., efficient) when direct responsibility for climate change is taken by individual/sub-setof the board and other and senior manager/officer. However, when companies engage directly or
through trade associations on climate change, the companies are considered to be less efficientthan other companies. On the other hand, regarding corporate activities, this study finds thatenvironmentally inefficient companies (i.e., more greenhouse gas emissions per employee) arelikely to participate in emissions trading schemes, take a verification/assurance status that applies
to firm’s Scope 3 emissions at the first year, and engage with customers.

Key words: climate change, corporate governance, corporate activity, CDP, environmental
efficiency
JEL classification: G30, Q54, Q56*

Graduate School of Business Administration, Kobe University
Address: 2-1, Rokkodai-cho, Nada-ku, Kobe-city, 657-8501, Japan
Email: zhoubowen007@yahoo.co.jp
1

1. INTRODUCTION
It has been widely recognized that a reduction in greenhouse gas (GHG) emissions isimportant in order to protect our environment. While some international agreements regarding
GHG emissions have already been signed by countries all over the world, companies are currently
required to decrease GHG emissions through their own inventive approaches. Specifically, toreduce GHG emissions, some kind of leadership such as governance and strategy are important,because GHG emissions often require company-wide consensus rather than a bottom-up approach.
This study aims to empirically examine how environmental efficiency related to GHG emissions
is affected by corporate governance and activities. Analyzing the corporate determinants of GHG
emissions will be informative for companies to improve environmental efficiency. Also, thisanalysis is helpful for policymakers or investors to form expectations about the effect of corporate
behaviors on corporate environmental performance.
This study uses data from CDP (former Carbon Disclosure Project), which gatheredobservations of 686 firms worldwide in 2013. As proxy for the environmental efficiency, thisstudy adopts GHG emissions per employee. As independent variables, this study uses dummy
variables made from the CDP questionnaire. The regression result shows that the amount of GHG
emissions per employee is low when direct responsibility for climate change is taken by anindividual/sub-set of the board and other and the senior manager/officer. Also, the result showsthat the GHG amount is high when the company engages in activities through direct engagement
and trade associations, when companies participate in any emissions trading schemes, when
Scope-3 (i.e., GHG emissions of supply chain) emissions verification is incomplete and it is firstyear it has taken place, and when engagement is taken with corporate customers.
This paper is structured as follows. Section 2 presents some extant literature on corporate
governance and environmental performance and explains CDP. Section 3 discusses themethodology focusing on a regression model and data. Specifically, in the regression model, thisstudy uses the GHG emissions per employee as a dependent variable and the dummy variablesfrom CDP questionnaire as the independent variables. Section 4 shows the results of the regression
model. Section 5 concludes with a short summary of the result and a business implication for2

firms’ owners, managers, and policymakers.
2. BACKGROUNDS
2.1 Corporate governance and environmental performance
While more and more companies are facing pressure to reduce their GHG emissions in orderto mitigate climate change risks, there are already several reasons to prove that corporate
governance plays a key role in environmental performance. Weinhofer and Hoffmann (2010) build
a generic corporate CO2 strategy framework to examine and classify whether and how companies
operate with environmental business operations. They use data of 91 companies from CDP
questionnaires, which include the following information: their electricity production, CO2
emissions data, and regional affiliation from companies’ answers. Focusing on combinations ofdifferent corporate CO2 strategy types, the authors find that most firms operate from theviewpoint of long-term emissions management. Their research also shows that the corporate CO2
strategies are significantly different among countries.
Walls et al. (2012) argue that there is a link between the corporate governance/strategy andthe company’s owners, managers, boards of directors, and environmental performance. The
sample of their study consisted of Standard & Poor’s (S&P) 313 firms in 29 industries in the
primary and manufacturing area between 1997 and 2005. The authors find that shareholders’concentration and activism can affect environmental performance and that board constructs are
relevant for environmental performance. Their study also shows that firms with higher managerial
incentives generally do less well in environmental performance.
Kock et al. (2012) try to build on a stakeholder–agency theoretical perspective to explore theimpact of corporate governance mechanisms on firms’ environmental performance. Focusing
especially on a discussion of whether firms in polluting industries have a better environmental
performance, the authors aim to analyze the effect of corporate governance on environmental
performance with demands for better environmental performance from stakeholders. The authorsuse data of 377 US public companies with 657 firm-year observations from 1998 to 2000,
obtained from Investor Responsibility Research Center (IRRC). The authors find that, when thecorporate exposure is high in the market or in the legal and regulatory system, the firm’s
environmental performance level will be higher. The authors also show that, when stakeholders
3are tough on the corporate board, the firm’s environmental performance level will be higher andthat the equity-based managerial incentives also affect the level of firms’ environmental
performance.

2.2 Corporate governance and corporate social responsibility
As reviewed above, the corporate governance is considered to have an effect on corporate
environmental performance. Also, the literature discusses the relationship between corporate
governance and corporate social responsibility (CSR). Ntim et al. (2013) investigate why
corporate governance mechanisms drive CSR and how a firm’s governance mechanisms drive its
CSR practices based on the neo-institutional theory. The authors also examine why and how the
CSR and corporate financial performance are associated with corporate governance. Data of theirstudy consist of 291 non-financial firms listed on the Johannesburg Stock Exchange (600
firm-year observations) between 2002 and 2009 in five main industries: basic materials, consumer
goods, consumer services, industrials, and technology/telecoms, obtained from annual andsustainability reports by the Perfect Information Database and DataStream. The authors find that
positive association also exists between the following three relations: government ownership andCSR practices, institutional ownership and CSR practices, and board size and CSR practices. On
the other hand, a negative relationship is found between block ownership and CSR practices. The
researchers also found that, when a company has higher (lower) corporate governance quality, therelationship between CSR and financial performance will become more (less) intense.
Although the literature discussed that CSR is beneficial for corporate performance, thefollowing question arises: Is CSR the activity specific to the largest companies? That is, when thecompany’s size becomes larger, should the company relate to the interests of more stakeholders,which are the main target of CSR, as discussed in Jamali et al. (2008). The authors discuss therelationship between corporate governance and CSR in depth and investigate the managerial
explanation and practical application of the relationship, using in-depth interviews with the top
managers of eight corporations operating in Lebanon as a way of qualitative interpretive researchmethodology. From the interview, the authors notice that the majority of managers agree that4

corporate governance is a necessary pillar for sustainable CSR and that companies in developing
countries are starting to become interested in CSR.
As reviewed above, the environmental performance and corporate governance are often
closely related to each other, and CSR activities have become popular in developing countries.
This study aims to further examine what types of corporate governance and activities are related toenvironmental efficiency, using the dataset from CDP, as explained in the below section.

2.3 CDP
This sub-section introduces the CDP and some research performed using data from the CDP.
The CDP is a private voluntary initiative designed to promote the improved management ofcarbon by pressuring firms to report their carbon emissions and describe their carbon strategies(Matisoff, 2012). CDP is a non-profit organization that began in 2000 and is headquartered in
London, United Kingdom. CDP is the world’s largest institutional investor collaboration, and themembers signed a single global request for corporate disclosures of information on GHG
emissions (Solomon et al., 2011). The CDP collaborates with 225 institutional investors withassets under management of more than 31 trillion dollars, and it surveys companies through anannual questionnaire on the business implications of climate change (Trucost, 2007). Throughpublishing reports and making disclosures available to the public, CDP tries to compel firms todisclose by increasing the benefits and reducing the costs of disclosing (Stanny, 2013). CDP canbe seen as a “secondary stakeholder” that has facilitated collaborative engagement by institutional
investors to increase corporate accountability in relation to climate change (Arenas et al., 2009).
CDP data has been used in several studies with different purposes. Stanny (2013) examines
voluntary disclosures of GHG emissions based on the data of S&P 500 firms from the CDP,
aiming at understanding general voluntary disclosures and particular emission disclosures.
Matisoff (2012) uses data from CDP and Chicago Climate Exchange to examine GHG reductionin the United States’ power plants, focusing on voluntary environmental policy. Cotter et al. (2011)
assume a stakeholder engagement perspective to investigate the collective influence ofinstitutional investors. The authors find that, in large companies, the influence of institutional5

investors is associated positively with climate change disclosure. Rankin et al. (2011) explain
voluntary corporate GHG reporting in the market governance system of climate change public
policy. The authors find that, when the firm has a higher level of corporate governance quality andreport publicly, the firm will have a larger environmental management system. Weinhofer et al.
(2010) present a framework that focuses on one combination among CO2 compensation, CO2
reduction, and carbon independence.
We also note that the CDP data has some limitations. Firstly, answering the CDPquestionnaire is not associated with a decrease of carbon dioxide emissions or electricity
generation (Matisoff, 2012). These data relate to the current status toward the climate change issue.
Secondly, most of the companies in the CDP’s questionnaires are already considered to have highenvironmental consciousness. Therefore, analysis using CDP questionnaire may result in testing
the responsiveness of already responsive companies to institutional investor pressures (Cotter,2011).

3. METHODOLOGY
3.1 Model 1: Corporate governanceThis study aims to examine what types of corporate governance and activities are related toenvironmental efficiency using a dataset from the CDP. Firstly, following the discussion in theliterature, this study hypothesizes that the environmental efficiency is a function of corporate
governance. Specifically, this study employs the corporate governance model. As proxy forenvironmental efficiency, this study uses GHG emission (Scope 1+2; direct and indirect emissions)divided by the full-time employees in the logarithm form (ln(GHG/Emp)) from CDP. On the other
hand, as the independent variables proxy for corporate governance, this study uses 6
questionnaires (Questions 1 to 6) related to the corporate governance section from CDP. The
corporate governance model is expressed as follows:ln (𝐺𝐻𝐺/𝐸𝑚𝑝) = 𝛽 +∑k 𝛽𝑘1𝐷𝑘1 + ∑k𝛽𝑘2𝐷𝑘2 + ∑k𝛽𝑘3𝐷𝑘3 +∑k𝛽𝑘4𝐷𝑘4 + 𝛽5𝐷56

(1)

+ 𝛽6𝐷6 + 𝛽𝑖 + 𝛽𝑡+𝑒
where 𝐷kj denotes a dummy variable of k-th answer in question j from CDP as explained in the

below sub-section. When 𝛽kj is positively (negatively) significant, the corresponding corporate

governance is considered to have a negative (positive) impact on environmental efficiency. 𝛽𝑖 and𝛽𝑡 denote industry and year effects, respectively, and e denotes an error term.

3.2 Model 2: Corporate activity
Secondly, this study examines whether environmental efficiency is affected by the corporate
activities with other organizations, hypothesizing that the environmental efficiency is a function of
corporate activities. This study refers to the model as the corporate activity model. As theindependent variables proxy for corporate activities, this study uses 4 questionnaires (Questions 7
to 10) related to performance section from CDP. The corporate activity model is expressed asfollows:ln (𝐺𝐻𝐺/𝐸𝑚𝑝) = 𝛽 +∑k 𝛽𝑘7𝐷𝑘7 + 𝛽8 𝐷8 + ∑k𝛽𝑘9𝐷𝑘9 +∑k𝛽𝑘10𝐷𝑘10 + 𝛽𝑖 + 𝛽𝑡+𝑒(2)where 𝐷kj denotes a dummy variable of k-th answer in question j from CDP. When 𝛽kj is positively(negatively) significant, the corresponding corporate activity is considered to be correlated
negatively (positively) with the environmental efficiency.

3.3 Data
Data of this study in both corporate governance and activity models are firm-level dataobtained from a questionnaire survey of CDP Supply Chain 2013 Information Request by CDP in
2013, based on three parts: management, risk and opportunities, and emissions. Table 1 shows thedescriptive statistics of this study. The number of observations is 648, which includes 64 countries
and 56 industry groups. The dependent variable is scope 1 and 2 emissions for the reporting year
in metric tons of CO2 per full-time equivalent employee in the log-form (i.e., ln(GHG/Emp)).
7

The independent variables are based on questionnaires and all dummy variables that take 0 or
1. The corporate governance model uses 6 questionnaires of the CDP Supply Chain 2013
Information Request (original questionnaires are as follows: Governance: Q1.1; Strategy: Q2.1,
Q2.2; Targets and initiatives targets: Q3.1, Q3.2, Q3.3). Question 1 asks what department has thegreatest direct responsibility for climate change (1: Individual/Sub-set of the Board; 2: OtherManager/Officer; 3: Senior Manager/Officer; “No”: baseline). Question 2 asks, “Please select theoption that best describes your risk management procedures with regard to climate change risks
and opportunities”: (1: a specific risk management process; 2: Integrated into multi-disciplinary
risk management processes; 3 Describe the process and outcomes; “No”: baseline). Question 3
asks who engages in GHG emissions reduction (1: Direct engagement/other; 2: Funding researchorganizations; 3: Trade associations/other; 4: other; ‘No’: baseline). Question 4 asks, “Did you
have an emissions reduction target that was active (ongoing or reached completion) in thereporting year?”: (1: Absolute and intensity targets; 2: Absolute target; 3: Intensity target; “No”:
baseline). Question 5 asks, “Does the use of your goods and/or services directly enable GHG
emissions to be avoided by a third party?” Question 6 asks. “Did you have emissions reduction
initiatives that were active within the reporting year (this can include those in the planning andimplementation phases)?”On the other hand, corporate activity model uses 4 questionnaires from the CDP Supply
Chain 2013 Information Request (original questionnaires are as follows: emissions trading: Q13.1,
Q13.2; Scope 3 emissions: Q14.2, Q14.4). Question 7 asks, “Do you participate in any emissions
trading schemes?” (1: Yes, we participate in emissions trading schemes; 2: No, but we anticipate
doing so in the next 2 years). Question 8 asks, “Has your company originated any project-basedcarbon credits or purchased any within the reporting period?”: (1: Yes, we have originatedproject-based carbon credits or purchased some within the reporting period; 2: No). Question 9
prompts, “Please indicate the verification/assurance status that applies to your Scope-3 emissions”:(1: More than 0% but less than or equal to 20%; 2: More than 20% but less than or equal to 40%;
3: More than 40% but less than or equal to 60%; ‘No’: baseline). Question 10 asks, “Do you
engage with any of the elements of your value chain on GHG emissions and climate change
strategies?”: (1: Our suppliers; 2: Our customers; 3: Other partners in the value chain; “No”:
8baseline).

4. RESULT
4.1 Corporate governance model
The corporate governance model regression results are shown in Table 2. We find that somecoefficients of Questions 1 (direct responsibility for climate change) and 3 (engage in activities on
climate change) are statistically significantly different from zero. In Question 1, all three answers
are statistically significantly negative, indicating that direct responsibility for climate change isimportant to reduce GHG emissions. The largest effect (i.e., the lowest coefficient) on GHG
emissions reduction occurs when another manager or officer takes direct responsibility for climatechange. Both two options of Question 2 are not significant. Regarding Question 3, answer 1(direct engagement) and answer 3 (trade association) are statistically significantly positive,
indicating that companies implementing engagement with these two options are lessenvironmentally efficient. Questions 4, 5, and 6 are not significant.

4.2 Corporate activity model
The corporate activity model regression results are shown in Table 3. Some coefficients ofQuestions 7, 9, and 10 are statistically significantly different from zero. Only Question 8 is not
significant. In Question 7, answer 1 (yes, we participate in emissions trading schemes) is
statistically significantly positive, indicating that companies implementing emissions trading
schemes are inefficient in terms of GHG emissions. In Question 9, answer 2 (incomplete
third-party verification or assurance: first year it has taken place) is statistically significant,indicating that companies which take the verification/assurance status of scope 3 emissions for the
first time are inefficient in terms of GHG emissions. Regarding Question 10, answer 2 (engage
with firm’s customers) is statistically significantly positive, indicating that companies engaging
with customers are environmentally inefficient. Question 8 (company originated any project-basedcarbon credits) is not significant with climate.

95. CONCLUSIONSThe purpose of this study is to examine the effects of corporate governance and activities onenvironmental performance. In the corporate governance model, this study finds that the amountof GHG emissions per employee is low (i.e., efficient) when direct responsibility for climatechange is taken by an individual/sub-set of the board and the other and senior manager/officer.
Secondly, when companies engage directly or through trade associations on climate change, thecompanies are considered to be less efficient than other companies. This suggests that these two
engagements will be indications of inefficient companies. On the other hand, in the corporate
activity model, this study finds that environmentally inefficient companies (i.e., more GHG
emissions per employee) are likely to participate in emissions trading schemes, to take averification/assurance status that applies to the firm’s Scope-3 emissions at the first year, and toengage with customers.
Managers have increasingly begun to recognize the importance of corporate environmental
performance. The findings of this study show that boards should make the responsibilities ofvarious managers clear on environmental performance. This suggests that, to be moreenvironmentally efficient, strong leadership is necessary. Also, this study suggests thatenvironmentally inefficient companies are likely to engage directly or through trade associations
on climate change or participate in emissions trading schemes. Therefore, these activities are
informative signs for policymakers and investors to distinguish between efficient and inefficientcompanies.
Note that this research has several limitations. Our sample included companies from 64
countries, including developed countries and developing countries. Dividing samples into thesegroups may yield a different result. Secondly, the sample of CDP may include only
environmentally efficient firms, and therefore, sample selection bias may occur. Finally, we findthat environmentally inefficient companies are likely to engage with customers. Hence, therelationship between consumer concerns and corporate environmental performance could be
investigated in future research.
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ACKNOWLEDGMENT
This study was carried out as part of the SESAMI project in Kobe University and was
supported by research grant from the Research Institute of Advanced Management. We would liketo thank Masaki Yasuda, Ryuji Shimono, and all concerned members of Panasonic Corporation for
arranging and coordinating our research survey.

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Table 1. Descriptive statistics
Variable

obs

Mean

S.D.

Min

Max

686

2.80872.7240−11.7566

16.7013

1 (Individual/Sub-set of the Board)686

0.67060.47040

1

2 (Other Manager/Officer)

686

0.29150.16840

1

3(Senior Manager/Officer)

686

0.26970.44410

1

1(A specific risk management process)686

0.07300.26010

12(Integrated risk management processes)

686

0.74200.43790

11(Direct engagement)

686

0.3936

0.48900

12(Funding research organizations)686

0.19100.3933013(Trade associations)

686

0.53640.4990014(Other/ Direct engagement)

686

0.26380.4410011(Absolute and intensity targets)

686

0.16330.3700012(Absolute target)

686

0.26090.43950

13(Intensity target)

686

0.29740.45740

1

Q5 GHG emissions avoided by goods/service

686

0.63990.48040

1

Q6 Emissions reduction initiatives

686

0.87170.33460

1

1 (Yes, we participate in emissions trading schemes)

648

0.23770.4260012 (No, but we anticipate doing so in the next 2 years)

648

0.0741

0.26210

1

Q8 Company originated any project-based carbon credits

648

0.18210.3862016480.03090.1731016480.03340.1812016480.25150.434201

1 (Engage with firm’s suppliers)648

0.50000.50040

1

2 (Engage with firm’s customers)

648

0.50930.500301

3 (Engage with firm’s other partners)

648

0.1914

0.393701

Dependent variable
ln GHG/Emp(Scope 1 and 2 emissions in metric tons CO2 perunit)
Independent variable
Q1 Direct responsibility for climate change

Q2 The option of risk management procedures

Q3 Engage in activities on climate change

Q4 Have an emissions reduction target

Q7 Participate in any emissions trading schemes

Q9 Scope 3 emissions verification/assurance status
1(Incomplete third party verification or assurance: Last year’s
statement available)
2 (Incomplete third party verification or assurance: First year it
has taken place)
3 (Third party verification or assurance complete)
Q10 Engage on GHG emissions and climate change
strategies

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Table 2. Regression results (Corporate governance model)(1)ln(GHG/Emp)
Coef.
S.E.
Q1 Direct responsibility for climate change
1 (Individual/Sub-set of the Board)−1.1913* (0.6673)
2 (Other Manager/Officer)−1.6561* (0.8455)
3(Senior Manager/Officer)−1.3472** (0.6560)
Q2 The option of risk management procedures
1(A specific risk management process)0.2433(0.4612)2(Integrated into multi-disciplinary risk management processes)
0.2798(0.3225
Q3 Engage in activities on climate change
1(Direct engagement)
0.5452** (0.2445)
2(Funding research organizations)−0.1145(0.3036)3(Trade associations)0.6153** (0.2426)
4(Other)−0.2203(0.2400)
Q4 Have an emissions reduction target in the reporting year
1(Absolute and intensity targets)−0.1120(0.3998)2(Absolute target)
0.2111(0.3270)3(Intensity target)
0.2947(0.3288)
0.0580(0.2490)
Q5 Goods or services directly enable GHG emissions to be avoided−0.1949(0.3643)
Q6 Emissions reduction initiatives within the reporting year
Constant
3.4842(0.6610)
Country dummy
Yes
Industry dummy
Yes
Obs
686
Year
2013
R-squared
0.1952
Note: ***, ** and * stand for statistically significant levels at 1%, 5% and 10%, respectively.

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Table 3. Regression results (Activity model)(1)ln(GHG/Emp)
Coef.
S.E.
Q7 Participate in any emissions trading schemes
1 (Yes, we participate in emissions trading schemes )0.5470** (0.2763)
2 (No, but we anticipate doing so in the next 2 years)−0.2581 (0.4227)
0.1878(0.2989)
Q8 Company originated any project-based carbon credits
Q9 Scope 3 emissions verification/assurance status
1 Incomplete third party verification or assurance:
Last year’s statement available
0.1794(0.6110)
2 Incomplete third party verification or assurance:
First year it has taken place
1.2930** (0.5715)
3 Third party verification or assurance complete−0.1500 (0.2674)
Q10 Engage on GHG emissions and climate change strategies
1(Engage with firm’s suppliers)
0.1637(0.2416)2(Engage with firm’s customers)
0.4450* (0.2219)
3(Engage with firm’s other partners)−0.0448 (0.2772)
Constant
2.4051(0.3103)
Country dummy
Yes
Industry dummy
Yes
Obs
648
Year
2013
R-squared
0.1059Note: ***, ** and * stand for statistically significant levels at 1%, 5% and 10%, respectively.

[2015.11.5 1212]

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