corporate incentives to disclose carbon information: evidence from the cdp global 500 report

Corporate Incentives to Disclose CarbonInformation: Evidence from the CDP Global500 Report

Le LuoUniversity of Western Sydney, School of Business, Locked Bag 1797, Penrith South DC,NSW, 2751, Australiae-mail: [email protected]

Yi-Chen LanUniversity of Western Sydney, School of Business, Locked Bag 1797, Penrith South DC,NSW, 2751, Australiae-mail: [email protected]

Qingliang TangUniversity of Western Sydney, School of Business, Locked Bag 1797, Penrith South DC,NSW, 2751, Australiae-mail: [email protected]

Abstract

We investigate how the Global 500 companies respond to the challenge of climatechange with regard to their carbon disclosure strategies. This paper is motivated by agrowing body of research that examines the role of large companies in carbon disclo-sure responsibility and practices. We consider the impact of social, financial market,economic, regulatory, and institutional factors on the motivation to voluntarily partici-pate in the 2009 Carbon Disclosure Project. We find that economic pressure is signifi-cantly associated with the decision. That is, companies facing direct economicconsequence are more likely to disclose. Companies in greenhouse gas (GHG) intensivesectors show the same tendency. In addition, big companies have a higher propensityfor disclosing, suggesting that social pressure plays an important role. We also providepossible explanations as to why a large proportion of our sample firms refuse to dis-close. Furthermore, our results suggest that the proxies for information needs of inves-tors are not associated with a higher propensity to disclose the amount of theiremission footprints. In sum, it appears that the major driving force for climate changedisclosure comes from the general public and government rather than from the othermajor stakeholders such as shareholders and debtholders. Our results are robust aftercontrolling for other influences.

We thank Bobby Banerjee, Terry Sloan, Gabriel Donleavy, Phil Ross, Anne Abraham, and par-ticipants of the World Accounting Frontiers Series 2nd International Conference in the Univer-sity of Western Sydney for their useful comments. We also thank Garry Tibbits and CharlieKoh for their editorial assistance. Particularly, insightful suggestions from Richard Levich (theEditor) and the anonymous reviewers are highly appreciated. Qingliang Tang and Yi-Chen Langratefully acknowledge the financial support for the study from School of Business, Universityof Western Sydney.

Journal of International Financial Management & Accounting 23:2 2012

© 2012 Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.

1. Introduction

There is growing scientific evidence that carbon emission is the major

cause for global warming, which is a serious threat to the quality of

human lives. Despite this, carbon emission is still largely unregulated

and carbon disclosure is not mandatory in most of the countries in the

world. However, many companies have decided to voluntarily take a

proactive emission reduction and disclosure approach. This motivates

us to investigate why these companies incorporate carbon disclosure as

part of their business operations and strategy, while other companies

do not.

It is imperative to identify and understand the managers’ incentives,

as corporate participation is one of the key driving forces to create a

low-carbon economy and society. We attempt to capture the major

factors that motivate large companies (such as the Global 500) to par-

ticipate in the Carbon Disclosure Project (CDP). The CDP is a non-

governmental and not-for-profit organization, which aims at providing

a channel for companies to measure and disclose greenhouse gas

(GHG) emissions and climate change strategies. Companies that have

been invited to participate in the survey can elect to answer a well-

designed questionnaire and to then allow their responses to be made

publicly available, or they can decline the offer.

On the basis of earlier literature that offers various theories to

explain the motivation of management to voluntarily make environ-

mental disclosures, we hypothesize the propensity to disclose carbon

information is associated with social, financial market, economic, regu-

latory, and institutional pressures, which in turn are translated into

disclosure incentives and policies. First, social pressure refers to the

pressure from public opinion. Legitimacy theory argues companies

conduct extensive disclosure in response to social pressure in an

attempt to legitimize their long-term operation and execute their

“social contract” voluntarily (Solomon and Lewis, 2002; Mobus, 2005;

Cho and Patten, 2007). Second, financial market pressure comes from

shareholders and debtholders to whom management is directly

accountable. A failure to disclose relevant information could result in

wider information asymmetry between its management and capital

providers; thereby, increasing the company’s cost of capital (Cormier

et al., 2005). Third, economic pressure relates to imposed or possible

carbon charges, carbon fees, carbon tax, and emission permits costs

which incentivize management to cut emissions and improve energy

94 Le Luo, Yi-Chen Lan and Qingliang Tang

© 2012 Blackwell Publishing Ltd

efficiency and then disclose the good news to stakeholders. Fourth,

existing or proposed changes in legislation regarding carbon abatement

would create legal/regulatory pressure for carbon disclosure. This dis-

closure would help firms mitigate or avoid compliance obligation or

regulatory risks (Solomon and Lewis, 2002), especially for firms within

environmentally sensitive sectors (Bewley and Li, 2000; Clarkson et al.,

2008). It can also be argued that firms in a country with a tradition

for high degree of corporate transparency are more likely to disclose

carbon information. In summary, an understanding of how firms

interpret and respond to the pressures imposed by governments, com-

munities, and other external groups is essential to establishing a regu-

latory and cultural framework for a low-carbon environment.

We use size to proxy for social pressure, as large companies are sub-

ject to more public and media scrutiny. We employ the presence or

absence of an emission trading scheme to proxy for economic pressure

and use financing activities and leverage to represent financial market

pressure from shareholders and debtholders. At the country level, the

nature of the legal system and the level of the enforcement of law are

used to proxy for regulatory and institutional influences. Our sample

includes 291 firms from the Global 500 in nine sectors (excluding firms

in the financial sector) with different institutional backgrounds and

divergent carbon regulatory exposure in different countries. We predict

that the firms in the Global 500 have strong economic incentives and

are under significant social, regulatory and institutional pressure to dis-

close carbon emissions and abatement activities. We expect market

participants to care about carbon information so as to exert their influ-

ence on the managerial disclosure strategy. We also include eight sec-

tor dummy variables to control for related, but omitted influences.

The key findings are summarized below.

1 The evidence is consistent with the notion that firms that take part

in climate change activities and disclosure do so in response to social

pressure. The tendency of Global 500 firms to disclose strengthens

as firm size increases.

2 Economic pressure is significantly related to carbon disclosure. In

other words, the disclosure tendency is attenuated with a decrease in

economic pressure.

3 Regulatory/institutional pressure is also positively associated with

disclosure/non-disclosure decisions.

Corporate Incentives to Disclose Carbon Information 95


4 There is insufficient evidence found for the proposition that financial

market stakeholders play an important role in the disclosure deci-

sion.

The last finding was unexpected. To the extent our measures of

financial market pressure reliably reflect the investment decision-mak-

ing processes of the shareholders and debtholders, our evidence sug-

gests that the decisions to disclose or not disclose are not strongly

influenced by the traditional measures of pressures exerted by the capi-

tal markets. This could either indicate that the decision is more com-

plex than outlined or that the relationship is non-linear. For example,

the traditional measures of pressures reflect the strength of the demand

for information, but they do not consider what countervailing pres-

sures may be operating that discourages management from disclosing.

Overall, the attitude of the general public and government appears to

be the decisive determinant of corporate climate change disclosure

behavior.

To shed new light on these issues, we conducted our research using

a different approach from previous studies and make the following

contributions.

1 We focus on a new research area of carbon emission disclosure. In

contrast, most previous studies cover other hazardous environmen-

tal materials, such as waste, SO2, and other toxic chemicals that

directly cause air or water pollution. Carbon dioxide (CO2) or

GHG emissions would lead to temperature and sea level rise and

increase the occurrence of storms, floods, droughts, and extreme

weather. Hence, these emissions are regarded as the most serious

environmental threats in that they cause much broader and far-

reaching devastating effects on the environment than non-carbon

chemicals.

2 Although most prior studies choose a national setting, our research

is conducted in the context of the world’s largest multinational firms

fighting the challenge of global warming. The international setting

enables us to test country-level influences, such as the adoption of

emission trading schemes, ratification of the Kyoto Protocol, strin-

gency of national environmental regulation, and the different

impacts of commonlaw and code law system on corporate carbon

disclosure.

3 The database we used is different from that of prior research. Previ-

ous studies often use environmental data from annual reports, sus-



tainability reports or from company websites, which is not only vol-

untary but also purely discretionary. That is, management can exer-

cise absolute discretion not only to disclose whatever they wish to

disclose but also to omit information which the firm does not want

to release. The CDP data we adopted is purely voluntary, but not

100 per cent discretionary. In other words, all the participating com-

panies must answer the same questions and many of them are non-

discretionary. Although detailed analysis of the contents of the CDP

report is beyond the scope of this study, we point out the importance

of the difference between voluntary and discretionary disclosure in

annual report and the voluntary but non-discretionary disclosure in

the CDP. Once a firm decides to participate in the CDP, it cannot

manipulate the style and contents of the presentation. The firm may

skip a particular question in the CDP report, but it cannot discre-

tionally delete the question. The missing answer (or omission) itself

is a message that may signal the high sensitivity, the non-availability

of the data, or an unwillingness to disclose the underlying items.

Therefore, non-discretionary disclosure (though voluntary) makes

it more difficult to “green-wash” (i.e., manipulate) environment

information.

4 Another problem of the prior research is the use of multiple data

sources; environmental data of different companies being collected

from difference sources. For instance, the data of an item for com-

pany A may be obtained from the annual report, while the same

item for company B may be from a sustainability report or its

website. This makes it extremely hard for data collection, analysis,

interpretation, and generalization of the results. Despite there being

no internationally accepted carbon reporting standards, the CDP

reports provides globally consistent and comparable data which

allows more meaningful analysis and interpretation, thus increasing

the power of our study.

5 Our sample comprises only the Global 500 firms. We justify the

selection by referring to their unique influence and the leading role

they play in world economy and business. They are also expected to

play an equally significant role in international efforts to meet the

challenges of climate change. Our results shed new light on their

incentives for carbon disclosure, which would be useful for regula-

tors, managers, and other stakeholders for taking further actions to

respond to such challenges.



The remainder of this article is organized as follows. Section 2

details the literature of the related fields. Hypotheses are developed in

Section 3. Section 4 discusses research design, and Section 5 presents

the main results. Section 6 sets out the conclusion and provides future

research directions.

2. Literature Review

The extant studies in environmental accounting research report find-

ings on the relationship between environmental disclosure and environ-

mental performance (e.g., Hughes et al., 2001; Patten, 2002b; Clarkson

et al., 2008, 2011), the association between environmental disclosure

and firm value (e.g., Murray et al., 2006; Plumlee et al., 2008, 2010),

the association between environmental performance and firm value

(e.g., Barth and McNichols, 1994; King and Lenox, 2001; Hassel et al.,

2005), and the determinants affecting management’s decisions to dis-

close environmental information (Barth et al., 1997; Cormier et al.,

2005; Brammer and Pavelin, 2006).

Early environmental accounting studies focus mostly on air or

water pollution and typically measure environmental performance

based on the pollution discharge data (i.e., toxic releases) and use a

content analysis index to proxy for the extensiveness of disclosure

(Clarkson et al., 2008). The attention of environmental studies has

recently shifted to climate change. Kolk et al. (2008) examine corpo-

rate responses to climate change in relation to the development of

carbon reporting mechanisms with a reference to the Carbon Disclo-

sure Project. Their analysis shows carbon disclosure has achieved

some progress in terms of the growing number of disclosing firms,

but much less with regard to the cognitive and value dimensions.

Other authors find that the GHG emission disclosure decision is sig-

nificantly associated with factors such as size, previous disclosure of

carbon emissions, and foreign sales (Stanny and Ely, 2008; Stanny,

2010). Their evidence is consistent with the notion that the cost of

not disclosing increases with the level of scrutiny. Peters and Romi

(2009) investigate the country-level variables and find that environ-

mental regulatory stringency, environmental responsiveness of private

sectors, and the market structure of each country determine the

extent of corporate disclosure. In addition, results from Reid and

Toffel (2009) show that the shareholder resolutions and regulatory

threats are positively associated with a firm’s propensity to fully or



partially participate in the CDP. However, this result seems incon-

clusive as Stanny (2010) finds that when the regression model

includes a variable of previous disclosure, the regulatory threat fac-

tors become insignificant. In sum, it appears the study of carbon

disclosure is at a preliminary stage and our project is an extension

of the literature.

3. Hypotheses Development

Our design simultaneously considers the influence of social, financial

market, economic, and regulatory/institutional pressure exerted from

various stakeholders (Pinkse and Kolk, 2009). We then derive

managerial incentives to incorporate stakeholder’s growing demand for

carbon information into their disclosure policies, strategies, and actions.

3.1. Social Pressure

Social pressure in our context refers to the pressure posed by the

public.1 Legitimacy theory posits that organizations exist within the

bounds of social values (Deegan and Rankin, 1997) and there is

implicit “social contract” between the organization and the society

(Solomon and Lewis, 2002). Climate change concerns lead to a

social expectation for carbon reduction and disclosure. If a company

ignores its social responsibility and is “silent” about carbon perfor-

mance and policies, it will give the impression to the public that

management is unaware of, or does not care about climate change,

and lacks strategies to minimize carbon risks and emissions. Social

groups may penalize non-disclosing companies by depriving them of

their right to continue operations through suspending support and

allocation of resources. This expectation/pressure provides managers

with the incentive to disclose, thereby legitimizing their long-term

operational sustainability (Mobus, 2005; Cho and Patten, 2007).

We employ firm size to proxy for political visibility and social pres-

sure because larger firms are subject to greater scrutiny and media cov-

erage and higher public expectations (Bewley and Li, 2000; Vanstraelen

et al., 2003). In addition, previous studies present evidence of a posi-

tive relationship between size and the level of environmental disclosure

(Al-Tuwaijri et al., 2004; Magness, 2006; Aerts et al., 2008). Hence, we

propose the first hypothesis:



H1: Size is positively associated with a firm’s propensity to disclose carbon

information.

3.2. Financial Market Pressure

Subsequently, we consider the impact of management accountability to

shareholders and debtholders. Shareholders demand climate change

information to assess the actual value of the firm to facilitate their

investment decisions. On the one hand, the literature suggests disclo-

sure may narrow information asymmetry and decrease financing costs

such as the cost of capital and increase stock liquidity (Healy and

Palepu, 2001), and thus, failure to provide credible information would

be penalized by the market. On the other hand, unless the company

operates in a complete and perfect market, the manager would disclose

only part of their private information due to proprietary costs and

uncertainty (Dye, 1985). Therefore, the decision to disclose is based on

the assessment of the disclosing benefits net of the associated costs

(Cormier and Magnan, 1999). And the net benefits are expected to

increase with the amount of capital raising. This assertion is supported

by empirical evidence (e.g., Frankel et al., 1995; Lang and Lundholm,

2000; Francis and Khurana, 2005) that finds firms that access external

financing are more likely to make voluntary disclosures. In our con-

text, we argue that capital raising firms tend to provide information

pertaining to carbon risks and carbon management activities. This dis-

cussion leads to our second hypothesis:

H2: Firms that raise more capital in the financial markets have a higher

propensity to disclose carbon information.

Our second proxy for market pressure is leverage. Debtholders are

concerned about carbon-related liabilities so that they need the infor-

mation to negotiate debt contracts and reduce the uncertainty and risk.

Such information is used to inspect carbon emissions and monitor the

management for opportunistic behavior so as to mitigate their con-

cerns and ensure compliance with the debt contract. Thus, the higher

the leverage, the more pressure management would bear to disclose

carbon information. On the other hand, it can be argued that manage-

ment in a highly leveraged firm tends to withhold some sensitive infor-

mation, if the disclosure would increase transparency such that the

firm’s financial risks would be higher than anticipated, thereby



undermining the firm’s negotiating position (Verrecchia, 1983). As

these two theories predict opposite signs in the relationship, we test the

non-directional hypothesis:

H3: Leverage is not related to firms’ propensity to disclose carbon informa-

tion.

3.3. Economic Pressure

Next, we consider the effect of economic pressure on carbon disclosure

strategy. In our context, financial pressure is linked to external financing

activities, whereas economic pressure refers to the impact of carbon mit-

igation and disclosure on internal operating costs and profitability.

Carbon emission had been free for a long time, but there is a grow-

ing economic consequence of emission. For example, the European

Union (EU) has adopted an emission trading scheme where a firm that

emits carbon above its allocated cap has to buy an emission permit in

the carbon market. In addition, governments around the world have

imposed various carbon charges, fees, or taxes, which significantly

increase operating costs (Matsumura et al., 2010; Chapple et al.,

2012). And these costs will be internalized by firms and considered in

operating decisions. Under such economic pressure, concern for dimin-

ishing profitability is an internal drive toward carbon reduction, as

well as producing and divulging carbon information to highlight the

success of carbon mitigation. Firms are incentivized to undertake pro-

jects to minimize energy expense and carbon exposure. These firms

also tend to proactively disseminate such “good news” to signal their

“green” type of business, thus improving the firm’s image. We use the

presence of an emission trading scheme to proxy for economic consid-

eration by management due to its direct effect on financial perfor-

mance. Hence, we propose the fourth hypothesis below:

H4: Companies in countries that adopted an emission trading scheme are

more likely to disclose carbon information.

3.4. Regulatory/Institutional Pressure

Prior literature argues that managers would use a voluntary disclosure

framework to prepare for possible future legislation to avoid regula-

tory risks and the negative impact on their operations (Solomon and

Lewis, 2002; Peters and Romi, 2009). We introduce a number of vari-



ables to proxy for regulatory/institutional pressures. The first measure

is a dummy variable to represent whether a country has ratified the

Kyoto Protocol that binds the country to cut emissions and disclose.

Next, we consider the effect of stringency of environmental regulation

on carbon disclosure. Firms in a more stringent environmental regula-

tory regime will have more commitment and pressure to reduce carbon

emissions (Reid and Toffel, 2009), and this pressure may in turn trig-

ger more innovation (Porter and Linde, 1995). In a carbon-constrained

economy, carbon information is more relevant for users to evaluate

climate change opportunities, carbon liabilities, and risks. So we expect

that there is a positive association between the degree of regulatory

stringency and the propensity for disclosure.

We next consider the institutional impact on the firm’s decision.

Institutional theory posits that companies’ social behavior is, to

some extent, determined by the institutions which are “symbolic,

rule-based, and regulative processes” (Cormier et al., 2005). Compa-

nies in certain countries with their unique institutional background

may have different strategic decisions toward their operation and

disclosure issues to conform to the institutional framework within

their existing social-culture system (DiMaggio and Powell, 1983).

Therefore, carbon disclosure can reflect different concerns and views

within the specific historical/institutional environment of the society

in which it operates (Solomon and Lewis, 2002). More specifically,

La Porta et al. (1998) showed that commonlaw countries generally

have the strongest legal protection of small investors. In these coun-

tries, firms have a long tradition of transparent financial reporting

systems. We adopt this argument to carbon disclosure and predict

that companies in common-law countries tend to disclose carbon

information to protect minority investors’ interests. Thus, we form

the following hypotheses:

H5: The firms within the countries that have ratified the Kyoto Protocol

are more likely to disclose carbon information.

H6: The country’s level of stringency of environmental regulatory system is

positively related to the firm’s propensity to disclose carbon informa-

tion.

H7: Firms in common-law countries are more likely to disclose carbon

information.



4. Research Design

4.1. Sample

Our initial sample consists of the Global 500 companies that could be

manually retrieved from the CDP 2009 report (CDP Global 500

Report, 2009). Then, we identified and removed all the financial firms.

We also deleted the observations that have missing values in relation

to the relevant financial data collected from DataStream. The final

sample includes 291 firms operating in the sectors per the Global

Industry Classification Standard (GICS) of Consumer Discretionary,

Consumer Staples, Energy, Health Care, Industrials, Information

Technology, Materials, Telecommunications, and Utilities. Financial

data with the exception of the indicator variables is winsorized at 0.01

level to reduce the impact of extreme observations. The results

reported in Section 5 are based on the winsorized financial data.

4.2. Carbon Disclosure Project (CDP)

Our data are mainly sourced from the CDP report.2 The CDP 2009

questionnaire covers five sections: Risks and Opportunities, Emissions

Accounting, Verification and Trading, Carbon Reduction Performance,

and Climate Change Governance (CDP Questionnaire, 2009). This

information can help users gain insight into the detailed process and the

overall strategy on addressing and managing climate change. Moreover,

the CDP data are designed and reported in a standard format that facili-

tates comparison across companies and industries. By 2009, more than

3,700 of the largest corporations had responded to this survey and made

the results available to a wide range of audiences including policymakers,

advisers, investors, corporations, academics and the public.

4.3. Theoretical Model

Our theoretical model is premised on the discretion of management in

response to climate change as a function of social, financial market,

economic, and regulatory/institutional pressures. The model’s theoreti-

cal construct is thus described in the following form:

Prðdisclosure ¼ 1Þ ¼ fðsocial pressure; financial market pressure;

economic pressure; regulatory=institutional pressureÞ ð1Þ



where Pr (disclosure = 1) operationalizes the propensity of the firm to

publicly disclose carbon information.

4.4. Empirical Model

A logistic model is used to examine the determinants of public disclo-

sure of carbon information.

PrðDis2009 ¼ 1Þ ¼ b0 þ b1Sizeþ b2Finþ b3Levþ b4ETS

þ b5Protocolþ b6WGI1 þ b7WGI2

þ b8Commonlawþ b9TobinQ

þ b10Betaþ b11ROAþ b12Capint

þ b13Newþ b14Capsendþ b15�22Sectors

ð2Þ

.Dependent Variable. Dis2009 is an indicator variable which is equal to

one if the company answered the CDP questionnaire and the answers

are publicly available, and zero otherwise.3

.Independent Variables. Our independent variables include a set of prox-

ies for social, financial market, economic, and legal/institutional pres-

sures as well as control variables.4

.Social pressure measure. Size is the natural logarithm of market capital-

ization at the end of fiscal year 2008.

.Financial market pressure measures.

Fin is the amount of financing in the fiscal year 2009 which is cal-

culated as sales of common stock and preferred shares minus

the purchase of common stock and preferred shares plus long-

term debt issuance minus the long-term debt reduction, and

then scaled by total assets at the beginning of the fiscal year

2008.

Lev is defined as total debt divided by total assets at the end of fiscal

year 2008.



.Economic pressure measure. ETS is an indicator variable that equals

one if the firm is within a country that has an established emissions

trading scheme, and zero otherwise.

.Regulatory/institutional pressure measures.

Protocol is an indicator variable that equals one if the firm is within a

country that has ratified or accepted the Kyoto Protocol, and

zero otherwise.

WGI1 and WGI2 are two proxies for stringency of a country’s environ-

mental regulatory system obtained from factor analysis of six

dimensions of world governance indicators (WGI).5

The WGI comprises six indexes of regulatory governance at the

country level: Voice and Accountability Index (VAI), Political

Stability and Absence of Violence Index (PVI), Government

Effectiveness Index (GEI), Regulatory Quality Index (RQI), Rule

of Law Index (RLI), and Control of Corruption index (CCI).

Using a correlation matrix, we find that the six indexes are

highly correlated. To avoid the multicollinearity problem, we

conduct a factor analysis to form only two factors (labeled as

WGI1 and WGI2) that capture the unobservable nature of the

country-level environmental regulatory stringency (Al-Tuwaijri

et al., 2004; Bushman et al., 2004).

Commonlaw is an indicator variable that equals one if the firm is

within a common-law country, and zero otherwise (La

Porta et al., 1998).

We predict the sign of coefficient for each of the above independent

variables (except Lev) to be positive (See Section 3 for the explana-

tions).

.Control variables. We identify from prior studies and include in our

regression model the following factors that are supposedly related to

voluntary disclosure:

TobinQ measures intangibles such as unrecognized goodwill which

proxies for the firm’s investment environment and future

growth opportunities. We use TobinQ to control for the

impact of growth on carbon disclosure (Clarkson et al., 2008).

TobinQ is measured as the total market value of the company

based on the year end price and the number of shares out-



standing, plus preferred shares, book value of long-term debt,

and current liabilities, divided by book value of total assets at

the end of the fiscal year 2008.

Beta is the proxy to control for the firm’s systematic risk or

stock price volatility (Stanny and Ely, 2008). Beta is based on

between 23 and 35 consecutive month end price per cent changes

and their relativity to a local market index.

ROA is the proxy for firm’s profitability, calculated as net income

divided by total assets at end of fiscal year 2008. Profitable firms

could more easily afford the expenditures needed to reduce car-

bon emission and report carbon information (Bewley and Li,

2000).

Capint is the proxy for capital intensity, calculated by property, plant,

and equipment divided by total assets at the end of fiscal year

2008(Aerts et al., 2008).

New is the measure for updated technology, calculated as new

properties, plant, and equipment divided by total properties,

plant, and equipment at the end of fiscal year 2008. Firms

with newer assets are likely to have adopted energy efficient

technologies to improve carbon performance so that they have

more incentives to disclose the “good news” (Clarkson et al.,

2008).

Capspend is calculated using capital spending divided by total sales

at the end of fiscal year 2008, which is the proxy for the

level of investment in clean technologies (Clarkson et al.,

2008).

Sector Dummies: Many studies such as Clarkson et al. (2008) suggest

that firms in the same industry are facing similar

regulatory and institutional pressure. Particularly

companies in GHG intensive sectors6 are more

likely to utilize voluntary disclosure as a method to

mitigate the negative impact of GHG legislation on

their businesses. Thus, we control for sector influ-

ences using sector dummies.

The directions of the relationships between the dependent vari-

able and each of the control variables (except for the sector dummies)

have been predicted to be positive based on the previous research.



5. Empirical Results

5.1. Descriptive Analyses

Table 1 presents the descriptive statistics for dependent and indepen-

dent variables. The mean of Dis2009 is 0.75, indicating 75 per cent

Table 1. Descriptive Statistics

Variables N MeanStandarddeviation P25 Median P75 Min Max

Dis2009 291 0.75 0.43 0 1 1 0 1Size 291 10.19 0.73 9.63 10.02 10.59 9.01 12.15Fin 291 0.02 0.08 �0.02 0 0.04 �0.15 0.46Lev 291 0.24 0.16 0.13 0.24 0.34 0 0.66ETS 291 0.25 0.44 0 0 1 0 1Protocol 291 0.54 0.5 0 1 1 0 1WGI1 291 0 1 �0.28 0.28 0.28 �7.86 1.26WGI2 291 0 0.97 �0.48 �0.48 0.64 �3.84 2.91Commonlaw 291 0.62 0.49 0 1 1 0 1TobinQ 291 1.66 1.1 1 1.33 1.98 0.59 7.62Beta 291 0.83 0.42 0.52 0.8 1.09 �0.03 2.48ROA 291 0.08 0.06 0.04 0.07 0.12 �0.09 0.3Capint 291 0.35 0.24 0.15 0.3 0.54 0.01 0.91New 291 0.52 0.15 0.41 0.51 0.63 0.25 0.97Capspend 291 0.11 0.13 0.04 0.06 0.14 0 0.91

Notes: Dis2009 is an indicator variable that equals one if the firm answered the CDP2009questionnaire and made the response public, and zero otherwise. Size is the natural logarithmof market capitalization at the end of fiscal year 2008. Fin is the sale of common stock andpreferred shares minus the purchase of common stock and preferred shares plus long-termdebt issuances minus the long-term debt reductions, and then scaled by the size of total assetsat the beginning of the fiscal year 2008. Lev is total debt divided by the total assets at theend of fiscal year 2008. ETS is an indicator variable that equals one if the holding companyis in a country that have an established emissions trading scheme and zero otherwise. Proto-col is an indicator variable that equals one if the company is in a country that has ratified oraccepted the Kyoto Protocol and zero otherwise. Commonlaw is an indicator variable thatequals one if the firm within the common-law countries and zero otherwise; this variable isused to proxy for legal protection of investors (La Porta et al., 1998). WGI1 and WGI2 arescores for two factors derived from the factor analysis for six dimensions of the world gover-nance indicators (CCI, GEI, PVI, RLI, RQI, and VAI). The WGI data can be access athttp://info.worldbank.org/governance/wgi/index.asp and the general description of the WGImethodology can be referred to Kaufmann et al. (2010). TobinQ is the total market value ofthe company based on year end price and number of shares outstanding, plus preferredstock, book value of long-term debt, and current liabilities, divided by book value of totalassets. Beta is a measure of the firms’ systematic risk, based on between 23 and 35 consecu-tive month end price per cent changes and their relativity to a local market index (retrievedfrom DataStream). ROA is net income divided by total assets at the end of fiscal year 2008.Capint is property, plant, and equipment divided by total assets at the end of fiscal year2008. New is net properties, plant, and equipment divided by total properties, plant, andequipment at the end of fiscal year 2008. Capspend is capital spending divided by total salesrevenues at the end of fiscal year 2008.



Table

2.DistributionofFirms(N

=291)

Panel

A.Distributionoffirm

sbysectors

Sector

Key

industries

within

thesector

Dis2009=

0Dis2009=

1

Total

firm

sNumber

offirm

sPercentage

(%)

Number

offirm

sPercentage

(%)

Consumer

discretionary

Media,Automobiles,SpecialtyRetail,

Hotels,Restaurants

andLeisure

13

40.63

19

59.38

32

Consumer

staples

FoodandStaplesRetailing,Beverage,

FoodProducts,Tobacco

10

25

30

75

40

Energy

Oil,GasandConsumable

Fuel,

EnergyEquipmentandService

720

28

80

35

Healthcare

HealthCare

ProvidersandServices,

HealthCare

Equipmentand

Supplies,Pharm

aceuticals

826.67

22

73.33

30

Industrials

IndustrialConglomerates,Roadand

Rail,Aerospace

andDefense,

ElectricalEquipment

15

36.59

26

63.41

41

Inform

ationtechnology

ITService,

Communications

Equipment,Sem

iconductors

and

Sem

iconductorEquipment

618.18

27

81.82

33

Materials

MetalsandMining,Chem

icals,

ConstructionMaterials

518.52

22

81.48

27

Telecommunications

Diversified

Telecommunication

Service,

WirelessTelecommunication

Services

521.74

18

78.26

23

Utilities

ElectricUtilities,Multi-Utilities,Gas

Utilities

413.33

26

86.67

30

Total

73

25.09

218

74.91

291



Table

2.(C

ontinued)

Panel

B.Distributionoffirm

sbycountries(N

=291)

Country

Dis2009=

0Dis2009=

1

Total

Number

offirm

sPercentage(%)

Number

offirm

sPercentage(%)

Australia

120

480

5Belgium

00

1100

1Brazil

00

3100

3Canada

213.33

13

86.67

15

Denmark

00

1100

1Finland

00

1100

1France

17.69

12

92.31

13

Germany

214.29

12

85.71

14

Ireland

00

1100

1Italy

133.33

266.67

3Japan

18

36.73

31

63.27

49

Korea(South)

00

3100

3Mexico

266.67

133.33

3Netherlands

133.33

266.67

3Norw

ay

00

1100

1Singapore

150

150

2South

Africa

00

2100

2Spain

240

360

5Sweden

00

3100

3Switzerland

112.5

787.5

8Thailand

1100

00

1United

States

39

29.1

95

70.9

134

United

Kingdom

15

19

95

20

Total

73

25.09

218

74.91

291

Notes:

Sectors

inourstudyfollow

theGlobalIndustry

ClassificationStandard

(GIC

S).Thefinancialsectoris

notincluded

inoursample,so

there

are

ninesectors

reported

inthetable.Thepercentageiscalculatedusingthenumber

offirm

sdivided

bythetotalfirm

sin

thesector.



(218 out of 291 firms) of the sample firms fully or partially participated

in the CDP 2009 program and made their responses public. Thus,

there are 73 (25 per cent) non-disclosing firms in the Global 500 com-

panies, which seem significantly high and unexpected. We discuss this

result further in section 6. The mean of ETS (Protocol) is 0.25 (0.54),

showing a quarter of (approximately 50 per cent of) the sample firms

are within the countries having implemented the emission trading

scheme (ratified the Kyoto Protocol).

Table 2 Panel A shows that the sample firms are evenly distributed

in each sector and that a majority of firms within every sector partici-

pated in the CDP. Utilities, Information Technology, and Materials

are three sectors that have the highest participation rates.

Table 2 Panel B reports the distribution of the firms by country.

Of the 291 firms, US firms make up the largest group and account

for more than 40 per cent in the sample. The second-largest group

is from Japan (16.84 per cent), followed by United Kingdom (6.87

per cent) and Canada (5.15 per cent). It is noteworthy that some

countries such as Belgium and Brazil have less than five observa-

tions.

Table 3 provides both Spearman and Pearson pair-wise correlation

coefficients in the upper and lower triangle, respectively. Size is posi-

tively associated with the Dis2009 (Spearman coefficient 0.26 and

Pearson coefficient 0.24; both of which are significant at .01 level)

suggesting that the larger firms tend to answer the CDP question-

naire due to social pressure and public monitoring. In addition, the

result for the ETS is significantly and positively associated with

Dis2009, which shows that firms operating with an emission trading

scheme are more likely to disclose carbon-related information as

these firms are exposed to more carbon risks and costs arising from

ETS. The Spearman correlation coefficient on WGI1 (representing

regulatory pressure) and the Pearson correlation coefficient on WGI2show that they are also significantly associated with the decision to

provide carbon disclosure. But almost all of the financial market-

related variables such as Fin, Lev, Beta, and ROA are not signifi-

cantly correlated with Dis2009 (except for the Spearman correlation

coefficient for Fin). This suggests these variables may not capture the

level of financial market pressure or that the information needs of

market participants are not perceived important by management in

the disclosure decision.



Table

3.CorrelationCoeffi

cients

Matrix

ofthevariables(N

=291)

Variables

Dis-

2009

Size

Fin

Lev

ETS

Protocol

WGI 1

WGI 2

Common-

law

TobinQ

Beta

ROA

Capint

New

Cap-

spend

Dis2009

1.00

0.26***

0.12**

0.03

0.17***

0.09

0.12**

0.05

0�0

.07

0.01

0.04

0.05

�0.06

0.09

Size

0.24***

1.00

�0.09

�0.07

0.14**

0.06

0.04

�0.06

�0.03

0.22***

�0.02

0.23***

�0.16***

�0.09

�0.11*

Fin

�0.02

�0.08

1.00

0.05

0.09

0.15***

0.10*

0.12**

�0.03

�0.20***

0.11*

�0.08

0.29***

0.12**

0.27***

Lev

0.01

�0.07

0.02

1.00

0.11*

0.13**

�0.05

�0.07

�0.06

�0.31***

�0.17***

�0.40***

0.32***

0.05

0.34***

ETS

0.17***

0.13**

0.07

0.11*

1.00

0.54***

0.17***

0.07

�0.40***

�0.10*

�0.06

�0.16***

�0.10*

�0.07

�0.01

Protocol

0.09

0.02

0.13**

0.13**

0.54***

1.00

�0.23***

0.48***

�0.73***

�0.18***

�0.06

�0.22***

0.10*

�0.22***

0.17***

WGI 1

0.01

0.08

0.04

�0.05

0.13**

�0.26***

1.00

�0.08

0.66***

0.21***

0.01

0.25***

0.04

0.01

0.35***

WGI 2

0.12**

00.14**

�0.07

0.19***

0.46***

01.00

�0.52***

�0.13**

0.01

�0.10*

00.08

�0.28***

Common-

law

00

�0.01

�0.07

�0.40***

�0.73***

1.00

�0.08

1.00

0.24***

0.07

0.30***

0.07

0.44***

�0.03

TobinQ

�0.09

0.12**

�0.15**

�0.30***

�0.10

�0.12**

0.11*

�0.05

0.16***

1.00

�0.24***

0.70***

�0.27***

0�0

.34***

Beta

0.02

�0.06

0.12**

�0.15***

�0.05

�0.08

0.09

�0.02

0.09

�0.15***

1.00

�0.01

�0.07

0.11*

0.03

ROA

�0.01

0.21***

�0.07

�0.35***

�0.14**

�0.18***

0.13**

�0.04

0.24***

0.60***

�0.01

1.00

�0.08

0.08

�0.16***

Capint

0.04

�0.17***

0.20***

0.28***

�0.14**

0.07

�0.05

�0.02

0.11*

�0.24***

�0.06

�0.07

1.00

0.37***

0.72***

New

�0.04

�0.10*

0.13**

0.02

�0.08

�0.20***

0.15**

�0.23***

0.43***

0.07

0.11*

0.05

0.42***

1.00

0.29***

Capspend

0�0

.18***

0.22***

0.13**

�0.10*

0.03

00.06

0.13**

�0.16***

0.08

�0.09

0.63***

0.35***

1.00

Notes:

*,**,***Correlationis

significantat0.1,0.05,and0.01levels,

respectively(two-tailed).

Pearson(Spearm

an)correlationcoeffi

cients

are

inthelower

(upper)triangle.Financialdata

hereare

inUSmilliondollars.

Dis2009isanindicatorvariable

thatequalsoneifthefirm

answ

ered

theCDP2009questionnaireandmadetheresponse

public,

andzero

otherwise.

Sizeisthe

naturallogarithm

ofmarket

capitalizationattheendoffiscalyear2008.Fin

isthesale

ofcommonstock

andpreferred

sharesminusthepurchase

ofcommon

stock

andpreferred

sharespluslong-term

debtissuancesminusthelong-term

debtreductions,andthen

scaledbythesize

oftotalassetsatthebeginningofthe

fiscalyear2008.Lev

istotaldebtdivided

bythetotalassetsattheendoffiscalyear2008.ETSisanindicatorvariablethatequalsoneiftheholdingcompanyis

inacountrythathaveanestablished

emissionstradingschem

eandzero

otherwise.Protocolisanindicatorvariablethatequalsoneifthecompanyisin

acoun-

trythathasratified

oracceptedtheKyoto

Protocolandzero

otherwise.

Commonlawisanindicatorvariable


within

thecommon-law

countriesandzero

otherwise,

andthisvariable

isusedto

proxyforlegalprotectionofinvestors

(LaPortaet

al.,1998).WGI 1

andWGI 2

are

scoresfortw

ofac-

tors

derived

from

thefactoranalysisforsixdim

ensionsoftheworldgovernance

indicators

(CCI,GEI,PVI,RLI,RQI,andVAI).TheWGIdata

canbeaccess

athttp://info.worldbank.org/governance/w

gi/index.asp

andthegeneraldescriptionoftheWGImethodologycanbereferred

toKaufm

annet

al.(2010).TobinQ

isthetotalmarket

valueofthecompanybasedonyearendprice

andnumber

ofsharesoutstanding,pluspreferred

stock,bookvalueoflong-term

debt,and

currentliabilities,divided

bybookvalueoftotalassets.Betaisameasure

ofthefirm

s’system

aticrisk,basedonbetween23and35consecutivemonth

endprice

per

centchanges

andtheirrelativityto

alocalmarket

index

(retrieved

from

DataStream).ROA

isnet

incomedivided

bytotalassetsatendoffiscalyear2008.

Capintisproperty,plant,andequipmentdivided

bytotalassetsattheendoffiscalyear2008.New

isnet

properties,plant,andequipmentdivided

bytotalprop-

erties,plant,andequipmentattheendoffiscalyear2008.Capspendiscapitalspendingdivided

bytotalsalesrevenues

attheendoffiscalyear2008.



5.2. Multivariate Analyses

We use five logistic models (equations) to test the incremental effect of

these pressures on carbon disclosure. The results are presented in

Table 4.

In model 1 (Column 3 of Table 4), we only incorporate Size and

control variables into the equation. The estimated coefficient of Size is

significantly positive (1.032, p < .01) indicating that larger firms are

more likely to use voluntary disclosure to legitimize their long-term

operation in response to the social scrutiny and media coverage. This

finding supports our first hypothesis. The pseudo-R2, analogous to the

R-square in OLS regression, is 0.0767.

In model 2 (Column 4 of Table 4), the financial market pressure

indicators (Fin and Lev) together with Size are included. Both the coef-

ficient estimates for the market pressure are insignificant (Fin:

b = �0.645, z = �0.357; Lev: b = �0.459, z = �0.454), and the

pseudo-R2 is 0.0777. The results reject H2 and fail to reject H3 and

indicate the financial market pressure (as measured by our surrogate)

does not affect the carbon disclosure decision. Therefore, the inclusion

of the financial market factors provides little incremental explanatory

power in the study.

In the fifth column of the Table 4 (model 3), the equation comprises

the social and market pressure indicators as well as economic pressure

proxy, ETS. The significant positive coefficient of ETS (1.064, p < .01)

provides support for H4 and suggests the firms’ propensity to disclose

increases with economic pressure (such as those imposed by a carbon-

trading scheme). Statistically, ETS adds incremental explanatory power

in the test model as the pseudo-R2 increases from 0.0777 to 0.102.

In the sixth column of Table 4 (model 4), contrary to our expecta-

tion (in H5), Protocol is not significantly associated with disclosure

propensity. This result could be affected by the fact that US firms

account for a large part of our sample and that the United States has

not ratified the Kyoto Protocol. The two factors derived from the fac-

tor analysis for the six dimensions of world governance indicators

(WGI1 and WGI2) are significantly associated with the disclosure pro-

pensity, but the coefficients on WGI1 and WGI2 are in opposite direc-

tions. This evidence is not fully consistent with our prediction made in

H6. The coefficient of Commonlaw (2.988, p < .01) is significant with a

predicted positive sign (H7) showing that a stronger legal investor pro-

tection mechanism, together with a long tradition of transparent finan-



Table

4.Factors

InfluencingtheFirms’CarbonInform

ationDisclosure

Decision

Variables

Expected

sign

Dependentvariable:Dis2009

(1)

(2)

(3)

(4)

(5)

Socialpressure

Size

+1.032***(4.180)

1.031***(4.176)

0.972***(3.900)

1.002***(3.904)

1.142***(4.074)

Market

pressure

Fin

+�0

.645(�

0.357)

�0.969(�

0.518)

�1.348(�

0.683)

�2.161(�

1.038)

Lev

�0.459(�

0.454)

�0.769(�

0.742)

�0.804(�

0.750)

�0.408(�

0.347)

Economic

pressure

ETS

+1.064***(2.620)

2.582***(3.466)

2.733***(3.470)

Legal/institutional

pressure

Protocol

+�0

.213(�

0.331)

�0.408(�

0.584)

WGI 1

+�1

.588**(�

2.144)

�1.581**(�

2.119)

WGI 2

+1.005***(2.705)

1.166***(2.894)

Commonlaw

+2.988***(3.020)

2.855***(2.779)

Controlvariable

TobinQ

+�0

.160(�

1.019)

�0.170(�

1.076)

�0.153(�

0.964)

�0.112(�

0.669)

�0.027(�

0.144)

Beta

+0.151(0.427)

0.144(0.403)

0.204(0.559)

0.277(0.709)

1.133**(2.062)

ROA

+�0

.493(�

0.179)

�0.765(�

0.270)

�0.283(�

0.100)

�2.047(�

0.666)

�2.524(�

0.762)

Capint

+1.041(1.220)

1.169(1.318)

1.494*(1.658)

2.065**(2.130)

2.204**(2.013)

New

+�0

.825(�

0.744)

�0.844(�

0.759)

�0.934(�

0.835)

�2.276*(�

1.726)

�2.569*(�

1.724)

Capspend

+�0

.288(�

0.213)

�0.282(�

0.206)

�0.239(�

0.173)

�1.228(�

0.860)

�1.718(�

1.054)

Consumer

staples

1.272**(1.972)

Energy

1.261(1.598)

Healthcare

1.362*(1.951)

Industrials

0.132(0.238)

Inform

ation

technology

1.360*(1.948)

Materials

0.759(1.067)

Telecommunications

0.973(1.174)



Table

4.(C

ontinued)

Variables

Expected

sign

Dependentvariable:Dis2009

(1)

(2)

(3)

(4)

(5)

Utilities

2.417***(2.913)

Constant

�9.005***(�

3.530)�8

.870***(�

3.469)�8

.593***(�

3.344)�1

0.039***(�

3.732)�1

3.133***(�

4.260)

Observations

291

291

291

291

291

Log-likelihood

�151.3

�151.2

�147.2

�138.7

�131.1

Degreeoffreedom

79

10

14

22

Chi-square

25.15***

25.48***

33.36***

50.48***

65.60***

%Correctly

predicted

76.98%

76.98%

74.57%

75.60%

78.01%

PseudoR

20.0767

0.0777

0.102

0.151

0.200

Notes:

Logisticmodel

isusedin

thestudyto

examinethedeterminants

ofpublicdisclosure

ofcarboninform

ation.

*,**,***Significantat0.1,0.05,and0.01levels,

respectively(two-tailed).z-statisticsare

reported

inparentheses.Financialdata

hereare

inUSmil-

liondollars.Dis2009is

anindicatorvariable

thatequals

oneif

thefirm

answ

ered

theCDP2009questionnaireandmadetheresponse

public,

and

zero

otherwise.

Sizeis

thenaturallogarithm

ofmarket

capitalizationattheendoffiscalyear2008.Fin

isthesale

ofcommonstock

andpreferred

sharesminusthepurchase

ofcommon

stock

and

preferred

sharespluslong-term

debtissuancesminusthelong-term

debtreductions,

andthen

scaledbythesize

oftotalassetsatthebeginningofthefiscalyear2008.Lev

istotaldebtdivided

bythetotalassetsattheendoffiscalyear2008.

ETS

isanindicatorvariable

thatequals

oneif

theholdingcompanyis

inacountrythathaveanestablished

emissionstradingschem

eandzero

otherwise.

Protocolisanindicatorvariable

thatequalsoneifthecompanyisin

acountrythathasratified

oracceptedtheKyoto

Protocolandzero

otherwise.

Commonlawisanindicatorvariable


within

thecommon-law

countriesandzero

otherwise,

thisvariable

isused

toproxyforlegalprotectionofinvestors

(LaPortaet

al.,1998).WGI 1

andWGI 2

are

scoresfortw

ofactors

derived

from

thefactoranalysisforsix

dim

ensionsoftheworldgovernance

indicators

(CCI,

GEI,

PVI,

RLI,

RQI,

andVAI).TheWGIdata

canbeaccessedathttp://info.worldbank.org/

governance/w

gi/index.asp

andthegeneraldescriptionoftheWGImethodologycanbereferred

toKaufm

annet

al.(2010).TobinQ

isthetotalmar-

ket

valueofthecompanybasedonyearendprice

andnumber

ofsharesoutstanding,pluspreferred

stock,bookvalueoflong-term

debt,andcur-

rentliabilities,divided

bybookvalueoftotalassets.Betaisameasure

ofthefirm

s’system

aticrisk,basedonbetween23and35consecutivemonth

endprice

per

centchanges

andtheirrelativityto

alocalmarket

index

(retrieved

from

DataStream).ROA

isnet

incomedivided

bytotalassetsat

endoffiscalyear2008.Capintis

property,plant,andequipmentdivided

bytotalassetsattheendoffiscalyear2008.New

isnet

properties,plant,

andequipmentdivided

bytotalproperties,plant,andequipmentattheendoffiscalyear2008.Capspendis

capitalspendingdivided

bytotalsales

revenues

attheendoffiscalyear2008.



cial reporting practice would push firms to make a decision to disclose

carbon information. The test power of model 4 (pseudo-R2 = 0.151) is

higher than that of model 3 suggesting regulatory/instructional pres-

sure have an extra effect on management’s decision beyond social pres-

sure and economic pressure.

Model 5 (the last column of Table 4) is based on model 4, but

includes eight sector dummy variables to control for the systematic sec-

tor differences. Consistent with prior studies (Bewley and Li, 2000;

Patten, 2002a), our results show that some of the coefficients for sector

classification variables are statistically significant, suggesting that dis-

closure propensity does vary with sectors. In a separate test, we run the

same regression using a single dummy variable, Carbon Sensitivity

(instead of eight sector dummies). We code Carbon Sensitivity as one if

a firm operates in the Materials, Energy, or Utilities sector and zero

otherwise and find that the firms in these sectors are more likely to dis-

close probably due to higher exposure to future carbon costs or liabili-

ties. Regarding control variables, only Beta and capital intensity

(Capint) are both significant and with the predicted signs. The evidence

suggests that firms with higher Beta are more likely to disclose as it

may help investors by reducing carbon-related risks and uncertainty. In

addition, the pseudo-R2 of Model 5 increases further to 0.200 which is

consistent with prior voluntary disclosure literature (e.g., Barth et al.,

1997; R2 = 0.059–0.234; Eng and Mak, 2003; R2 = 0.1808–0.2061;Peters and Romi, 2009; R2 = 0.13–0.17; Reid and Toffel, 2009; R2 =0.15–0.16). Table 4 also shows that our models correctly predicted the

outcome of disclosure decision for 75–78 per cent of the firms in our

sample. This appears to be a reasonable and acceptable prediction

accuracy rate. On the whole, we find that the Size, ETS, and Common-

law variables are significantly and positively associated with firms’ pro-

pensity to disclose carbon information, while the coefficients on

financial market pressure proxies remain insignificant. These findings

are consistent across all the five model specifications.

5.3. Robustness Checks

We conduct a number of sensitivity checks to ascertain whether our

tests are valid. First, we examine whether our results are sensitive to

the winsorization operation, which has changed 2 per cent of the origi-

nal observations. Using unwinsorized financial data to run regressions,

the statistic results (which are not tabulated) are qualitatively the same



as those in Table 4. Second, instead of using market capitalization, we

use another measurement for size, the natural logarithm of total asset

at the end of fiscal year 2008 in the regression model. The results (not

reported) are consistent with the findings presented in Table 4. Third,

we use an alternative measure for stringency of environmental regula-

tory system in a country that combines regulatory stringency, struc-

ture, subsidies, and enforcement sub-indexes developed by Esty and

Porter (2005). The results (not tabulated) do not alter our main infer-

ences, although the pseudo-R2 is reduced to 0.16.

6. Discussion and Conclusion

On the basis of a sample of the Global 500 companies, our results sup-

port the notion that firms have provided carbon disclosure information

in response to the climate change challenge and that the carbon disclo-

sure pattern is likely to be explained by social, economic, and legal

influences. Larger firms are aware of their social responsibility and are

willing to disclose carbon information voluntarily even in the absence

of a corresponding requirement in the accounting and reporting stan-

dards.

But our evidence suggests that investors such as shareholders and

debtholders do not exert an observable influence on carbon disclosure

decisions. In other words, the attitudes of the general public and the

government, at present, are the decisive determinants of corporate cli-

mate change disclosure behavior. From the company’s perspective, if

the purpose of disclosure is to impress the public and regulatory

bodies rather than to account to its direct stakeholders such as inves-

tors, the quality of the disclosure may be suspect; as such disclosure

may include cosmetic information.

The Global 500 firms are regarded as corporate models in social

responsibility and their corporate governance and financial reporting

are supposed to be the most transparent systems among the business

community. Nevertheless, a large proportion (about 25 per cent) of

our sample firms had chosen not to disclose carbon information. This

result is surprising given the overwhelming recognition of the serious-

ness of global warming effects on the quality of life and the increasing

public attention to climate change.

What can we learn from this strong message? We offer an explana-

tion for non-disclosing decisions of these firms. We find these firms are

relatively smaller, so they may be lacking in the resources for processing



carbon information. In addition, these firms are more likely to be in the

non-carbon intensive sectors where the GHG information is less rele-

vant and important. Finally, on the one hand, our overall results show

that companies generally appear to be apathetic to the information

needs of the investors. On the other hand, our evidence could also

suggest that the non-disclosure is attributable to the lack of interest on

the part of the investors in carbon footprint information. This would

certainly provide no incentive for the management to disclose.

Given the evidence that the market does not play a major role, the

policy implications of the findings are that the government and rule

makers should take more actions to alleviate investors’ apparent apathy

and encourage firms to make carbon reduction and disclosure as a stra-

tegic priority. These actions include the establishment of regulation as

well as a more effective market mechanism to achieve the objective. An

international standard should be set up to prescribe the measures and

financial effects of emissions and the contents and format of a GHG

statement. This disclosure can be incorporated in the annual report or

sustainability statement. However, given the importance and complex-

ity of this issue, it may be desirable to require a separate carbon report.

One limitation of the study is that the sample firms are the largest

corporations in the world. Hence, caution should be taken to generalize

the findings to other companies. Future research may consider analyz-

ing the contents of the CDP reports and exploring the relationship

between carbon disclosure and carbon performance. Such an examina-

tion can extract more insights about corporate GHG emissions, carbon

management, and carbon mitigation strategies and actions.

Notes

1. The public include taxpayers, ratepayers, other community, and special interestgroups such as consumer and environmental protection societies and regional pressuregroups.2. https://www.cdproject.net/en-US/Pages/HomePage.aspx3. This category includes firms that answer all or part of the CDP questionnaire. Notewe treat the firms that answered the CDP questionnaire, but refused to make it publicas non-disclosing firms. This is different from previous studies that categorize thesefirms as disclosing firms (Stanny and Ely, 2008; Peters and Romi, 2009; Stanny, 2010).4. In our study, we follow Clarkson et al. (2008) to calculate Fin, TobinQ, Lev, Capint,and Capspend. In general, we use financial data at the end of fiscal year 2008 instead of2009 because CDP asks for carbon data for the previous year. For example, the CDP2009 questionnaire asks companies to provide carbon information during fiscal year2008.



5. The Worldwide Governance Indicators (WGI) are composite indicators of sixdimensions of governance, covering 212 countries and territories between 1996 and2009 (no 1997, 1999, 2001 data). They are based on hundreds of individual indicatorsof governance drawn from 33 data sources produced by 31 different organizations (seeKaufmann et al. (2010) for detailed information).6. In this study, we follow the CDP classification to identify Materials, Energy, andUtilities as GHG/carbon intensive sectors (See https://www.cdproject.net/en-US/WhatWeDo/CDPNewsArticlePages/GHG-targets-FTSE100-UK-Climate-Change-Act.aspx).An alternative way to determine carbon intensive sector/firm is using carbon emissionintensity measure, such as tonnes of carbon emission per one million dollar sales. How-ever, these data are not available for Global 500 firms in our sample that do not partic-ipate in the CDP.

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corporate incentives to disclose carbon information: evidence from the cdp global 500 report

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