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Iordanis M. Eleftheriadis Assistant Professor University of Macedonia Department of Business Administration 156 N. Egnatia Str. 540 06, Thessaloniki Greece Phone: 00302310891591 E-mail: [email protected]

Evgenia G. Anagnostopoulou Ph.D. Candidate University of Macedonia Department of Business Administration 156 N. Egnatia Str. 540 06, Thessaloniki Greece Phone: +00302310891590 E-mail: [email protected]

Ioannis E. Diavastis Ph.D. Candidate University of Macedonia Department of Business Administration 156 N. Egnatia Str. 540 06, Thessaloniki Greece Phone: +00302310891590 E-mail: [email protected]

Arabatzis C. Konstantinos Ph.D. Candidate University of Macedonia Department of Business Administration 156 N. Egnatia Str. 540 06, Thessaloniki Greece Phone: +00302310891590 E-mail: [email protected]

Relationship between Financial Performance and Corporate Disclosures regarding Climate Change Practices Abstract Concerns about risks, both physical and economic, induced by anthropogenic climate have given rise to the adoption of climate change mitigation policies at national and international level. Climate change policies aim to put a price on carbon emissions, for example through the establishment of carbon markets where CO2 emissions are traded, thus affecting the profitability of firms. As a result there has been an increasing demand for information disclosure, regarding corporate climate change practices of firms, from various stakeholders and institutional investors. This paper contributes to the international research that examines the relationship between environmental information disclosures and firm specific factors that are most likely to have a positive effect on increased disclosure of information. In doing so we have conducted an empirical analysis of the relationship between corporate climate change disclosure practices of Greek firms who are listed in the Athens Stock Exchange Market and firm-specific factors such as financial performance, firm size and activity sector. Our results indicate that there is a positive significant relationship between financial performance, firm size and increased corporate disclosures regarding climate change practices. In other words, large firms and firms that achieve better financial results have the tendency to disclosure more information about their climate change practices than smaller firms or firms with poorer financial performance. Keywords: Climate Change Corporate Disclosures, Financial Performance, Size, Climate Change Business Risks.

1. Introduction

The Global community has acknowledged climate change as a major source of physical, social and economic risk. As a result there has been an increase in the adoption of climate change mitigation policies at national and international level, most notably being the Kyoto Protocol which has set mandatory GHGs reduction targets for industrialized countries. Governments on their part have been implementing and setting into effect climate change policies and regulation that aim to put a price on Greenhouse Gases (GHGs) emissions, for example through the establishment of carbon markets where GHGs emission allowances are traded. All this GHGS - reduction related regulation has increased the regulatory risks companies have to deal with and has created both financial and accounting implications that will eventually affect their profitability. GHGs-intensive business sectors will face the direct regulation risk through increased cost related to their obligation to have GHGs emission allowances matching to their amount emissions while non-intensive business will most likely face the indirect effects of climate regulation through, for example, increased energy prices that will affect their production costs. Building on the above, it is obvious that developing climate change corporate strategies is nowadays of outmost importance to the majority of firms, if they want to avoid additional sources of business risk.

Institutional investors, on their part, have also began to look into firms’ climate change governance practices in an attempt to map the climate change risk related exposure of companies they wish to invest into. However, as it is widely acknowledged, in order to make good investment decisions, complete and accurate information about a firm’s exposure to business risks is required. Inadequate disclosure of climate change related risks will most likely reduce the investor’s ability to accurately measure and manage the exposure of his portfolio thereby leading to false estimates of firms’ performance. As a result there has been an increasing demand for information disclosure, regarding corporate climate change practices of firms such as accounting and reporting for GHGs emissions, investing in low carbon technologies, setting GHGs-reduction targets and calculating potential liabilities stemming from climate regulation.

This paper contributes to the discussion on the need of further enhancing disclosure of the climate change-related by outlining firm specific financial factors that are most likely to have a positive effect on increased disclosure of information regarding corporate climate change governance practices. International academic research has also studied the relationship between firm-specific factors and environmental disclosures. In their research they have used various financial indicators as independent variables to measure firm factors such as size, financial performance, leverage and several environmental disclosure indexes in order to measure the quantity and quality of corporate environmental disclosures. Our research offers an insight to the relationship between carbon disclosure practices of Greek firms who are listed in the Athens Exchange Stock Market and firm-specific factors such as size and financial performance. We claim that there is a positive significant relationship between size, financial performance and corporate climate change disclosure practices. In other words, large firms and firms that achieve better financial results have the tendency to disclosure more information about their climate change practices than smaller firms or firms with poorer financial performance.

The paper’s structure is the following: at the first part we are going to briefly discuss the basic politics of climate change as well as the mitigation policies that have been adopted and regulations that are current in place. The reason we go through this stage is because we believe that the increase during the last ten years in corporate environmental disclosures, including climate change corporate practices, has been the result of the creation of an international climate change regime involving climate change mitigation policies and regulation at national and international level. Therefore we consider it important to spend some time on climate change policy and regulation. Next, we examine the effects of regulation on business activities and we analyze why there is a need for information disclosure regarding corporate climate change practices. In the third part of, we conduct a literature review on previous studies that have examined the relationship of financial performance, size and environmental disclosures while presenting and analyzing our variables and our research methodology. Finally, at the last part we present the results of our empirical analysis and provide a discussion of our findings.

2. Global Climate Change and Mitigation Policies

Climate Change has been widely acknowledged as one of the major sources of risk by the global community. The risks climate change poses are not confined strictly to environment and direct physical impacts of global temperature rise but they also involve social, economic and financial impacts. The term anthropogenic climate change, from now on referred to as simply climate change, is being used to describe the changes in global meteorological patterns due to the rise of global temperature. This global temperature rise however is not being treated as a natural phenomenon but rather it is being attributed to human activities, which during the last one hundred years has resulted in the rise of the amount of Greenhouse Gases (GHGs) 1 and especially Carbon Dioxide (CO2) at concentration levels that are beyond normal. According to the current flow of CO2 emissions it has been estimated that there is a chance of 77% to 99% of the temperature rising more than 2°C (Stern 2006). Such an increase in global temperature is most likely to cause rapid changes to current climatic models affecting directly economic sectors such as tourism, transport, agriculture, healthcare, insurance and real estate.

This common worldwide acceptance that the rise of GHGs concentration is a result of industrial activities, has triggered the adoption of measures and policies both at national and international level, that have as a purpose the reduction of GHGs emissions. The first agreement on climate change, the creation of the United Nations Framework Convention on Climate Change (UNFCCC), took place in the 1992 Rio Earth Summit (the United Nations Conference on Environment and Development). The aim of this agreement was the stabilization of GHG concentrations in the atmosphere at a level that would not pose a threat to the climatic models. However the main driver in the development and adoption climate change mitigation policies that eventually prompted several changes in the corporate strategies of companies, regarding management of their GHG emissions, was without any doubt the creation of the Kyoto Protocol in 1997 (Kolk & Pinkse 2008; Haque & Deegan 2010).

1

The industry sector itself has recognized six GHGs as a result of their daily operations: carbon dioxide (CO2) which stands for about 76,7% of total GHGs, methane (CH4), nitrous oxide (NO2), hydroflourocarbons (HCFs), perflourocarbons (PFCs) and sulfur hexafluoride (SF6 ) (Hoffman 2006). In addition, between 1970 and 2004 the larger part of GHGs came from energy production, transport and industry and at a second level from cities, deforestation and agricultural production (IPCC 2007 ).

The Kyoto Protocol went into effect in 2005 and it forms a legally binding agreement that sets emissions reduction targets for industrialised countries (called Annex I countries) by a specific percentage that has been agreed on by the signatory parties. In achieving their emission reduction targets, countries that have ratified the protocol are allowed to use 3 flexible mechanisms: The Clean Development Mechnanism (CDM), Joint Implementation (JI) and Emissions Trading. The emissions trading mechanism allows the buying and selling of emissions credits among Annex I countries in order to meet their emission reduction commitments. Under the CDM procedure Annex I countries may invest in projects that contribute to emissions reductions in developing countries and receive credit units that they may later use to achieve their emission targets or trade in the Emissions Trading Mechanism. Joint Implementation is the same as CDM only it states that Annex I countries must invest in those countries with economies in transition such as the ex Soviet bloc (Chasek et al. 2006).

The need to reach Kyoto targets gave rise to the adoption of national and international climate change mitigation policies. These include putting a price on carbon emissions, through carbon taxes, the establishment of carbon trading programs, setting mandatory process and product standards for industry or provide incentives to invest in low-carbon technologies (Bebbington and Larrinaga – Gonzalez 2008). Based on its binding commitments to reduce its GHG emissions, the European Union launched its own mandatory emissions trading scheme, the European Union Emissions Trading System (EU ETS). The EU ETS, which was set in effect for the first time in 2005, constitutes EU’s main mechanism in achieving its own personal target of a 20% reduction in its emissions by 2020 and forms the largest emissions trading system worldwide, covering 11000 installations (Perdan and Azaparic 2011). Additionally, several other mandatory GHGs trading schemes have already been set into operation such as the Regional Greenhouse Gas Initiative in the USA, New Zealand Emissions Trading Scheme, Tokyo metropolitan trading scheme and the New South Wales Greenhouse Gas Abatement scheme in Australia (Pedan and Azapgic 2011).

According to the EU ETS scheme, each country is required to set a limit, a “cap”, in the number of emission credits ( European Union Allowances) and then distribute them, using an allocation method (free allocation, auctioning etc), to installations participating in the emissions trading system. Installations may meet their cap either by reducing their emissions and selling the surplus, or by increasing or letting their emissions remain higher than the cap and buying allowances from other companies that participate in the EU emissions market in order to meet the cap. The scheme covers electricity generation, power stations, refineries and offshore installations, iron and steel, cement and lime, paper, food and drink, glass, ceramics, engineering and vehicles. The EU ETS has been split in three compliance periods: Phase 1 which ran from 2005 to 2007, formed the initial learning phase of the scheme and did not have any penalties for non-compliance, Phase 2 which is currently in place involves initial free allocation of emission credits for most industry sectors and a penalty of €100 for each tonne of emissions that does not have allowances, Phase 3 which will run from 2013 to 2020 will also involve auctioning of the initial emission allowances (Lovell et al.2010).

Building on the above, it is obvious that climate change regulation is gradually becoming more strict thereby putting more pressure to firms to implement and apply climate change corporate mitigation strategies. As we will discuss below, not all firms are directly affected by climate change regulation, GHGs intensive sectors, such those participating in the EU ETS are particularly vulnerable. However since there is a tendency for suppliers to pass costs of regulation to consumers (Lass and Wellington 2007; Wellington and Sauer 2005) we can assume that the majority of firms will somehow, directly or indirectly, be affected by climate change regulation.

3. Global Climate Change and Business

As climate change is affecting both directly and indirectly the business environment, some firms will face more risks than others depending both on the nature of their business and on the strategies they adopt regarding climate change (Porter and Reinhardt 2007; Schwartz 2007). Climate change and GHG reduction policies create systemic risks across the global economy, by affecting energy and food prices, national income and health expenditures. On the other hand it poses direct and indirect risks at sector and company specific level (Hoffman 2006; Wellington and Sauer 2006; ACCA 2009; Ceres 2010). Most of these risks have been pointed out and even been partly estimated by the insurance industry, which has become increasingly concerned about climate risks and how they affect both firms’ physical assets, potential regulatory costs and even litigation costs regarding corporate environmental liabilities (ACCA 2009).

Specific economic sectors, such as the agricultural sector, fishing, forestry, insurance, real estate and tourism are particularly exposed the direct physical impacts of climate change due to their dependency to the natural environment (Lash and Wellington 2007, Wellington and Sauer 2005 ; ACCA 2009) therefore facing increased physical risk. On the other hand, GHG – intensive or energy intensive business sectors such as energy –production, aluminum, cement and pulp industries are more exposed to risks associated with current or impending regulation regarding CO2 emissions (Busch and Hoffman 2007; ABI 2005). As a result, some companies will most likely face increased operational costs as we move towards a carbon constrained economy (Busch and Hoffman 2007). These costs will most certainly affect their profitability and create significant competitive risks not only for GHG intensive industries such energy production but also for the majority of industrial manufacturing sectors, as there is the tendency for energy suppliers to pass the increased costs of regulation to their consumers (Lash and Wellington 2007;Wellignton and Sauer 2005). With the dramatic increase in climate change impacts, there is a pressing need for business to develop appropriate climate change mitigation strategies for the risks posed by the projected climate change policies.

Since now we have only referred to climate change regulation only as a source of business risk. Nevertheless, climate change regulation could under certain circumstance help companies gain a competitive advantage and increase their profitability. This claim is based on the fact that competiveness is not related only to the cost of raw materials or to the ability for mass productions of goods, but also to the ability of firms to be innovative and improve their production processes (Porter & van der Linde 1995; Williams et al. 2002). Therefore, according to Porter and van der Linde 1995,

well designed environmental regulation can stimulate the development of innovative technologies and production process, which on their turn could make up for the costs imposed on firms due to regulation and even offer a competitive advantage. For example, investing in carbon reduction projects could generate a positive return on investment by offering tax credits for energy reduction or the development of carbon capturing and storing technology could leave firms with a surplus of emissions credits to be traded in carbon markets thus offering a new source of revenue (Ernst & Young 2010). However empirical studies have shown that firms are not always able to counterbalance the costs of environmental regulations, the probability to do so increases when the production process is relatively flexible, when the company belongs to a high competitive sector and when the regulation is adaptable, that it when there are pollution permits trading systems (Ambec & Lanoie 2007).

On the financial front there is evidence that institutional investors view climate change as a major source of risk (Solomon et al. 2011) and have also began to pay more attention to corporate climate change practices of firms, demanding more information disclosure from companies regarding their corporate climate change mitigation policies. If a company is not seen as adequately addressing and managing physical or regulatory risks posed by climate change investors might be reluctant to invest in the company until it has developed a specific corporate climate change strategy (ACCA 2009). Specifically, what investors are particularly interested in when assessing the climate risk profile of a company is information regarding GHG emissions, exposure to carbon regulations such as taxes or mandatory product and process standards or corporate strategies regarding renewable energy investments (Solomon et al. 2011; Delloite 2010). Mainstream institutional investors, for example, like Goldman Sachs, Bank of America, JP Morgan and Citigroup have already adopted sustainability criteria such valuating GHG - intensity of projects and promoting low - carbon technologies such as renewable energy (Hoffman 2006; ACCA 2009).

As a result, during the last years, there is an increasing demand on firms disclosing information regarding corporate climate change-governance practices. This demand has also given rise to the creation of voluntary climate change information disclosure schemes such as the Carbon Disclosure Project (CDP) and the GHG Protocol Initiative (Andrew and Cortese 2011). Both of these schemes were the result of the collaboration between government agencies, NGOs and institutional investors in their try to create a reporting benchmark regarding climate change governance practices of firms. Using different methodologies, data regarding GHG emissions and corporate climate change practices are assembled and being codified into annual reports which are later made available to policymakers, investors, corporations, academics and the public. These data are later used from various stakeholders in order to assess the climate change vulnerability of the companies participating in the voluntary information disclosure schemes.

The reason why various stakeholders and institutional investors in particular, insist on companies disclosing information, especially those belonging to GHG – intensive sectors, is the fact that inadequate disclosure of climate change related risks will reduce the investor’s ability to accurately measure and manage the exposure of his portfolio to the reverse effects of climate change (Venugopal et al. 2009) therefore causing him to falsely estimate firms’ performance and future cash flows. On the other hand, scientific research on credit risk management has shown that by incorporating

sustainability criteria in financial assessment of projects, for example, banks can not only lower the chances of having to deal with credit default cases but have also more chances of gaining an advantage against their competitors by improving their credit risk management assessment procedures (Weber et al. 2010; Weber et al. 2008; Nitsche and Hope 1996; Thompson, 1998).

Additionally, accounting firms have also stressed the importance of climate change related corporate disclosures and place special attention on both the physical and financial accounting of GHGs. Accountants were initially involved with climate change reporting issues due to the creation on the EU ETS (Lovell and MacKenzie 2011) and the financial implications of the treatment of emission allowances in financial reports. Indeed, during the last years carbon markets have began to have material impacts on the balance sheets with carbon allowances being treated as assets or potential liabilities and affecting financial cash flows (Ascuii and Lovell 2011; Lovell et al. 2010; KPMG 2008). These impacts are also expected to rise during the third phase of the EU ETS in which the majority of allowances are expected to be auctioned rather than being given away for free, thereby further affecting the financial results of firms.

As carbon regulation evolves and becomes more and more specialized in addressing carbon reduction issues, stakeholders will demand that companies provide even more information on their climate change governance practices. In our study we will to further add to the discussion on the need of enhancing climate change disclosure practices of firms by exploring firm-specific factors that contribute to increased information disclosure regarding corporate climate change practices. International academic research (Freedman and Jaggi 2005; Liu and Anbumzhi 2009; Zeng et al. 2010; Moneva and Cuellar 2009; Brammer and Pavelin 2006; Clarkson et al.2008; Cong and Freedman 2011; Cormier et al. 2005; Prado-lorengo 2009; Gallego Alvarez 2010; Galani et al. 2011; Zhang et al. 2008) has examined several factors such as size, financial performance, leverage, market to book etc as having an effect on increased information disclosure. We will expand the current bibliography by offering an insight to the relationship between financial performance, size, sector activity and information disclosure, regarding the corporate climate change practices of Greek listed firms.

4. Factors Influencing Corporate Climate Change Disclosures

Firm-specific factors such as return on assets and size may have significant influence on managerial decisions to disclose carbon-related information (Freedman and Jaggi 2005). In this section we analyze the factors that can contribute to increased disclosure of information regarding climate change practices of firms. We examine two firm-specific factors size and financial performance and one explanatory factor, industry sector.

Size

Size has been used several times as an independent or control variable in previous research on environmental disclosures (Freedman and Jaggi 2005; Liu and Anbumzhi 2009; Zeng et al. 2010; Moneva and Cuellar 2009; Brammer and Pavelin 2006; Clarkson et al.2008; Cong and Freedman 2011; Cormier et al. 2005; Prado-lorengo 2009; Gallego Alvarez 2010; Galani et al. 2011; Zhang et al. 2008). The majority of research results show that there is a positive significant association between size and disclosures regarding the environmental practices of firms (Freedman and Jaggi 2005; Liu and Anbumzhi 2009; Zeng et al. 2010; Brammer and Pavelin 2006; Clarkson et al.2008; Cong and Freedman 2011; Cormier et al. 2005; Prado-lorengo 2009;Gallego Alvarez 2010;Galani et al. 2011; Zhang et al. 2008; King and Lenox 2001). However, Patten (2000) has shown that there is no significant relationship between firm size and environmental disclosures.

The reason why the relationship between size and disclosures has been proven almost always positively significant is based on the fact that larger corporations receive increasing attention both from stakeholders and the government agencies (Gray et al. 2001; Liu and Anbumzhi 2009; GallegoAlvarez 2010). This claim is also supported by stakeholder and legitimacy theory which several authors (Liu and Anbumozhi 2009; Freedman and Jaggi 2005; Clarkson 1995;Ullmann 1985) have used as a basis to develop claims that larger firms are more exposed to public pressure regarding their environmental practices and therefore they pay more attention in disclosing information. Furthermore, Freedman and Jaggi (2005) and Liu and Anbumzhi (2009) claim that the relationship between firm size and increased environmental disclosures can also be attributed to the fact, that larger firms can more easily afford expenditures regarding the adoption of cleaner technologies.

Most of the studies mentioned above have used total revenue (Prado-lorengo 2009; Galani et al. 2011), natural logarithm of revenue (Cong and Freedman 2011; Gallego Alvarez 2010) and the natural logarithm of firm assets (Freedman and Jaggi 2005; Liu and Anbumzhi 2009; Brammer and Pavelin 2006; Clarkson et al.2008; King and Lenox 2001; Cormier et al. 2005; Zhang et al. 2008) as financial measure to represent firm size. In this study we also will use the natural log of total firm assets obtained from online published financials reports for the years 2008-2010. The following hypothesis is established:

H1: There is a significant positive relationship between climate change disclosure index and firm size measured in log of total firm assets. Alternatively, larger firms will disclose more information on their climate change corporate practices than smaller firms.

Financial performance

The financial performance of a firm has also been examined in the majority of the literature that we have referred to at the previous chapter regarding the relationship between firm size and environmental disclosures. Several financial indicators have been used in order to measure the financial performance of a firm. Freedman and Jaggi (2005), Brammer and Pavelin (2006), GallegoAlvarez (2010) and Bewli and Li (2000) have used return on assets (ROA) as a financial indicator. Liu and Anbumzhi (2009) and Zhang et al. (2008) have used Return on Equity (ROE) as a financial performance indicator in analyzing environmental disclosure practices of 175 large Chinese listed companies and the Chinese chemical industry respectively. Galani et al. (2011) and Richardson and Welker (2001) have also used ROE as a financial performance indicators while Prado-Lorengo (2001) has used both ROA and ROE. King and Lenox (2001) used Tobin’s q, which represents the firm’s market valuation over the replacement value of its assets. They calculated this variable by dividing the sum of firm equity values, book value of long-term debt and net current liabilities by the book value of total assets. Clarkson et al. (2008) and Nakao et al. (2007) used both ROA and Tobin’s q as measures for financial performance in examining the disclosure practices of US high polluting industries and Japanese listed firms respectively.

Prior empirical research has examined the relationship between firms’ financial performance and their environmental disclosure practices. Most studies show a positive relationship between financial performance and environmental disclosures (Freedman and Jaggi 2005; Liu and Anbumzhi 2009; Nakao et al. 2007; Richardson and Welker 2001; Brammer and Pavelin 2006; Clarkson et al.2008; Gallego Alvarez 2010; Galani et al. 2011; Zhang et al. 2008) which can be interpreted under the assumption that low financial performance of firms will put economic priorities first rather than environmental. However, the inverse relationship between financial performance and volume of information issued has also been detected by Freedman and Jaggi (1982) and Prado-Lorengo (2009). These results suggest that companies which perform more poorly have an incentive to reveal a higher volume of environmental information in order to make themselves more attractive to various stakeholders (Prado-Lorengo 2009). However the majority of the above studies have also shown that the relationship between environmental disclosures and financial performance, at conventional levels of significance, is deemed insignificant suggesting that corporate disclosure practices are not strongly affected by financial performance (Bewli and Li 2000).

Freedman and Jaggi (2005), Liu and Anbumzhi (2009), Richardson and Welker (2001), Brammer and Pavelin (2006), Clarkson et al. (2008), Gallego-Alvarez (2010), Galani et al. (2011), and Lenox (2001) and Bewli and Li (2000) have shown that financial performance is not significantly related to the environmental disclosure activities. On the other hand Prado-Lorengo (2001) has found a significant and negative relationship between disclosures and financial performance, Nakao et al. (2007) have shown that a firm’s financial performance has a positive significant impact on its environmental performance and vice versa and stress that this relationship appears to be a recent phenomenon (Nakao et al. 2007) while Zhang et al. (2008) have also found a positive significant impact between ROE and environmental disclosures. In this study we will use the return on total firm assets (ROA) obtained from online published financials reports for the years 2008-2010. The following hypothesis is established:

H2: There is a significant positive relationship between climate change disclosure index and financial performance measured using the return on total firm assets (ROA) financial indicator. Alternatively, firms with good financial performance will disclose more information on their climate change corporate practices than firms with a poor financial performance.

Industry Sector

Business sectors in which the firms operate have been used as either a control or an independent variables in several studies (Freedman and Jaggi 2005; Gallego-Alvarez 2010; Brammer and Pavelin 2006; Clarkson et al. 2008; Richardson and Welker 2001; Cormier et al.2005; Prado-Lorengo 2009). In this study will also use Industry Sector as a control variable. For our research we have identified the following industries: Oil and Gas, Chemicals, Metals, Mining, Building Materials, Industrial Goods Production and Energy Production.

5. Research Method

Sample Selection

The aim of this research is to investigate the relationship between firm-specific financial factors and corporate disclosure practices of firms regarding their climate change strategies. In order to test our two hypotheses we have selected, as the target population, Greek companies listed in the Athens Stock Exchange Market. The activity sectors selected to undertake this research are Oil and Gas, Chemicals, Metals, Mining, Building Materials, Industrial Goods and Energy Production. Our intention was to extend and generalize the results obtained in previous research regarding the relationship of financial factors and climate change related corporate disclosures and to shade some light to the environmental disclosure practices of Greek firms, a field which is still new to empirical research ( Galani et al. 2011).

Therefore a sample of 45 firms was chosen and data was selected for the years 2008, 2009 and 2010 based on the information disclosed in financial, annual and environmental reports of our sample firms. After we selected the sample, we carried on a content analysis of firms’ corporate climate change practices based on a disclosure index developed by Haque and Deegan (2010) in their assessment of the climate change corporate disclosure practices of 5 large Australian firms.

Disclosure Index and Content analysis

In order to examine the corporate climate change related governance practices and disclosures of Australian firms Haque and Deegan (2010) developed a climate change disclosure index based on reports by the Coalition for Environmental Responsible Economies (CERES), the Business for Social Responsibility (BSR), the AMP Henderson Global Investors, the Carbon Disclosure Project (CDP), the Global Reporting Initiative (GRI) and the Association of Chartered Certified Accountants (ACCA). Building on these reports they developed a list of climate change – related governance disclosure items (see Appendix I) and then used this list to conduct content analysis in order to assess the climate change practices of 5 major Australian companies in GHG – intensive industries from 1992 to 2007. We decided to use this tool developed by Haque and Deegan (2010) instead of more well known assessment indexes such as the GRI or the CDP first because it was build based not only on the above reports but also on information derived from the sustainability reports of their sample companies, thereby making it a more practical guide, second because it incorporates disclosure items that were found in at least two of the above reports, therefore making it a more complete guide, and third because it is specifically oriented to disclosure items regarding only climate change practices and not environmental practices in general. Content analysis has been employed to analyse the climate change disclosure practices of Greek firms. Content analysis involves codifying qualitative information into content categories that have been carefully and explicitly defined (Guthrie and Abeysekera 2006; Montabon et al. 2007). This method was used by many authors in studying environmental disclosures (Freedman and Jaggi 2005; Brammer and Pavelin 2006; Clarkson et al.2008; Cong and Freedman 2011; Richardson and Welker 2001; Prado-lorengo 2009;Gallego Alvarez 2010;Galani et al. 2011;Haque and Deegan 2010). In applying this methodology to analyze the volume of information disclosed in annual and environmental reports of Greek firms regarding their climate change corporate practices we use the value of either 1, if the data are reported and 0 if they are not.

Variables and Analysis Techniques

After conducting content analysis and analyzing the information regarding the disclosure practices of Greek firms we developed a dependency model where we used the disclosure index as the dependent variable, size, measured using the natural log of total assets, and financial performance, measured using return on assets (ROA) as independent variables and activity sector a control variable.

Disclosure Climate Change Index = f(Size, Economic performance, Activity Sector) The above model can be empirically estimated by using the equation: DIi = β0 + β1 SIZE i + β2 FINANCIAL_PERFORMANCEi + Σk βi SECTOR ki + ε

where: k = 1,…7 (number of business sectors included); DIi is the climate change corporate practices disclosure index obtained after analyzing the annual and environmental reports for each firm; SIZE i measured as the natural log of total firm assets; FINANCIAL_PERFORMANCEi of each firm examined using ROA as financial performance measure; Σk βi SECTOR ki as a dummy variable that takes the value 1 if the firm belong to the k sector and 0 if it doesn’t belong to the k sector.

The above model was tested empirically using linear regression analysis and estimated using the ordinary least squares methodology.

6. Results of Empirical Analysis

Descriptive Statistics and Bivariate Results

In table 1 we present the descriptive statistics of the depended and independent variables. The minimum, maximum, mean and standard deviation values are reported. As we can see, the companies issue an average of 1, 98 out of the 12 disclosure items that we have observed in our analysis of the climate change corporate practices of Greek firms. A high variation in the natural logarithm (LNASSETS) of total assets is also depicted, ranging from 16,55 to 23,50, meaning that the size of the sample companies varies in a great extent. Finally financial performance, measured by return on assets (ROA), is on a 13% average.

Table 1.Descriptive Statistics N

Minimum

Maximum

Mean

Std. Deviation

DI

135

,00

12,00

1,9852

3,46622

ROA

135

-,1297

,7733

,013543

,0800703

LNASSETS

135

16,5583

23,5083

19,188448

1,5621630

Table 2. Pearson’s correlation

1.

2.

3.

4.

1. 2.

DI ROA

1 ,211*

1

3.

LNASSETS

,647**

-0,06

1

**

0,057

,267**

1

5.

6.

7.

8.

9.

4.

OILANDGAS

,311

5.

CHEMICALS

-,247**

0,036

-0,167

-0,115

1**

6.

IRONANDSTEEL

0,051

-0,082

0,166

-0,161

-0,259

1

7. 8. 9.

MINING BUILTMAT INDPROD

0,077 0,047 -0,157

0,136 -0,1 0,031

-0,048 -0,103 -,240**

-0,047 -0,124 -0,152

-0,075 -0,2 -0,244

-0,105 -0,28 -0,343

1 -0,081 -,099**

1 -0,264

1

0,084

0,025

,370**

-0,058

-0,093

-0,13

-,038**

-0,1

-0,123

10. ENERGYPROD

*Correlation is significant at 0.10 ; **Correlation is significant at 0.05

10.

1

In Table 2, the bivariate correlations between dependent, independent and control variables in presented. As we can see the variables size, represented by LNASSETS (0,647), financial performance, represented by ROA (0,211) and the activity sectors Oil and Gas and Chemicals (OILANDGAS (0,311) and CHEMICALS(-0,247) respectively) show the highest correlation with the dependent variable DI (Climate Change Disclosure Index ). On the other hand there is no significant correlation between IRONANDSTEEL (0,051), MINING (0,077), Building Materials, BUILTMAT (0,047), Industrial Goods Production companies ,INDPROD (-0,157) and Energy Production companies, ENERGYPROD (0,084).

Regression Analysis

In order to estimate the ordinary least squares regression function, we analyzed several statistical assumptions of the regression analysis used, such as: normality, homoscedasticity, multicollinearity and autocorrelation. Regarding normality, we applied the Kolmogorov–Smirnov test which showed us that the variables do not show a normal distribution. However, according to Gallego Alvarez (2010) and Lumley et al. (2002) the absence of a normal distribution does not reduce the validity of the values of coefficients. In our case, the lack of normal distribution is due to the size of our sample and the existence of extreme values in our data, especially data regarding the disclosure index variable (because firms will disclose either a large amount of information or a very little or not at all).

In order to alleviate heteroscedasticity problems we have used the usual method of transforming variables for example into a logarithm (Katos 2004). This last method has been used in the variable SIZE of our sample where we used natural logarithm of total assets. Regarding autocorrelation in the residuals from the regression, we conducted the Durbin-Watson’s test. The value obtained from Durbin–Watson’s test (2,394) is around the value 2, which according to Katos (2004) reflects the absence of autocorrelation in the residuals. The variance-inflation factors and tolerance factors have been used to analyze the absence or presence of multicollinearity. For there to be no problems of multicollinearity, the values obtained in tolerance have to be high and the values obtained in the variance-inflation factors have to be low. Our model presents tolerances of 0,956 and 0,698 and variance-inflation factors of 1,046 and 1,432 indicating the absence of multicollinearity.

Regarding the explanatory power of our model, the R2 has a value of 0,571 for a confidence level of 99% (p < 0.01), which means that our model has an explanatory power of 57%. The value of adjusted R square can be considered high if we take into consideration similar results of other studies. Specifically, Freedman and Jaggi (2005) obtained a value of 0,15 for the adjusted R2, Bewli and Li (2000) 0.37, Liu and Anbumzhi (2009) 0,034 and Gallego-Alvarez (2010) 0,406. Therefore we can consider our model to have a relatively high explanatory value.

Now we can present the results obtained from the estimation of our proposed model using the ordinary least squares methodology (Table 3.)

Table 3. Linear Regression

Depedent Variable: DI (Disclosure Index) Beta t (Constant) ROA LNASSETS OILANDGAS CHEMICALS IRONANDSTEEL MINING BUILTMAT INDPROD ENERGYPROD

0,251 0,707 -0,079 -0,376 -0,351 -0,048 -0,155 -0,305 -0,323

-7,671 4,190** 10,074** -0,583 -2,060* -1,594 -0,478 -0,808 -1,430 -2,734**

Sig. 0,000 0,000 0,000 0,561 0,042 0,113 0,634 0,420 0,155 0,007

*Significant at 0.05; **Significant at 0.01

The model estimated to determine the relationship between the disclosure of information regarding corporate climate change practices of Greek firms and firm – specific factors such as financial performance, size and activity sector has an explanatory power, 57.1%, for a confidence level of 99%. Both of the independent variables proposed and two control variables were found statistically significant.

More specifically, positive effects, statistically significant for a confidence level of 99%, are detected for both independent variables size, represented by LNASSETS and financial performance, represented by ROA. Regarding control variables, CHEMICALS and ENERGYPROD (Energy Production companies) show a statistical significant effect for a confidence level of 95% and 99% respectively. No significant relationships were found between the depended variable and the control variables representing the activity sectors of Oil and Gas (OILANDGAS), Iron and Steel (IRONANDSTEEL), Mining (MINING), Building Materials Production Companies (BUILTMAT) and Industrial Goods Production Companies (INDPROD). The above results obtained for the model estimated allow us to accept both hypotheses H1 and H2, related to positive, significant relationships between companies with higher size and better financial performance and increased disclosure of information regarding corporate climate change practices.

7. Discussion of Findings

This research contributes to the international research regarding the relationship between environmental disclosures and firm-specific financial factors by analyzing the effects of financial performance and firm size on climate change corporate disclosures of Greek firms listed in the Athens Stock Exchange Market. Furthermore, the effect of activity sectors on corporate climate change disclosures was analyzed. The sectors examined where: Oil and Gas, Chemicals, Metals, Mining, Building Materials, Industrial Goods Production and Energy Production.

The analysis of the dependency model used in our research shows that there is a significant positive relationship between corporate climate change disclosures and firm size. Our results are supported by the majority of literature reviewed above (Freedman and Jaggi 2005; Liu and Anbumzhi 2009; Zeng et al. 2010; Brammer and Pavelin 2006; Clarkson et al.2008; Cong and Freedman 2011;Cormier et al. 2005; Prado-lorengo 2009;Gallego Alvarez 2010;Galani et al. 2011; Zhang et al. 2008; King and Lenox 2001). However, Patten (2000) has shown that there is no significant relationship between firm size and environmental disclosures.

Regarding the relationship between financial performance and environmental disclosures the results of international research are mixed. Our results are consistent with those of Nakao et al. (2007) and Zhang et al. (2008) who have shown a firm’s financial performance has a positive significant impact on its environmental disclosures. However Freedman and Jaggi (2005), Liu and Anbumzhi (2009), Richardson and Welker (2001), Brammer and Pavelin (2006), Clarkson et al. (2008), Gallego-Alvarez (2010), Galani et al. (2011), and Lenox (2001) and Bewli and Li (2000) have shown that financial performance is not significantly related to the environmental disclosure activities.

8. Conclusion

Climate change has been globally acknowledged as a major source of physical, economic and social risk. The mandatory GHGs – reduction targets that have been set for the industrialized countries under the auspices of the Kyoto Protocol have given rise to the adoption of climate change mitigation policies at national and international level. These include putting a price on carbon emissions through setting process and product standards for industry, carbon taxes and the establishment of carbon trading programs such as the EU ETS. As a result companies are expected to face increased costs in their production processes both directly for the GHG-intensive sectors and indirectly by passing carbon – related cost through the supply chain, thereby affecting the profitability of the majority of firms.

These increased risks that companies face have also caught the attention of various stakeholders, such as institutional investors, banks, accounting firms, governmental agencies, NGOs and consumers who have been demanding information on companies’ part, regarding their corporate climate change

practices. The aim of this research was to contribute to the discussion on the need of further enhancing disclosure of the climate change-related practices both in environmental reports and financial statements by outlining firm specific financial factors that are most likely to have a positive effect on increased disclosure of information regarding corporate climate change governance practices.

In order to do so, we conducted content analysis of the information disclosed on the environmental reports of firms who are listed in the Athens Exchange Stock Market using a climate change disclosure index, developed by Haque and Deegan (2010). Then we formed a dependency model where the relationship between the disclosure index (used as the dependent variable) and firm-specific financial factors such as financial performance, represented by return on assets and firm size, represented by the natural logarithm of total assets were examined as having a positive significance on increased information disclosures regarding corporate climate change practices. We also used activity sector as our control variable, the sectors included were Oil and Gas, Chemicals, Metals, Mining, Building Materials Production, Industrial Goods Production and Energy Production. Our results show that there is indeed a positive significant between our dependent variable and firm’s size and financial performance. These results imply first that larger firms will disclose more information on their climate change corporate practices than smaller firms and second that firms with good financial performance will disclose more information on their climate change corporate practices than firms with a poor financial performance.

Our results are consistent with the international research on the relationship between environmental disclosures and firm-specific factors. Furthermore we have offered an insight to the carbon disclosure practices of Greek firms, a field which is relative new to empirical research. This fact is perhaps the biggest limitation of our research as there is lack in the availability of data regarding corporate climate change practices in Greece. In fact, the majority of firms did not have sustainability reports at all before 2008. Future research should focus on examining the relationship between climate change disclosures of Greek firms and more financial factors than those examined in the present study. In addition a larger sample could be used involving firms from other activity sectors as well as firms that are not only listed in the Athens Exchange Stock Market.

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APPENDIX I DISCLOSURE INDEX (Haque and Deegan 2010) General issues

Board oversight

Specific issues 1) Whether the organisation has a board committee with explicit oversight responsibility for environmental affairs. 2) Whether the organisation has a specific board committee for climate change and GHG-related issues. 3) Whether the board conducts periodic reviews of climate change performance. 4) Whether the CEO/chairperson articulates the organisation’s views on the issue of climate change through publicly available documents such as annual reports, sustainability reports and websites.

Senior management engagement and responsibility

5) Whether the organisation has an executive risk management team, dealing specifically with GHG issues. 6) Whether some senior executives have specific responsibility for relationships with government, the media and the community with a specific focus on climate change issues. 7) Whether the organisation has a performance assessment tool to identify current gaps in GHG management. 8) Whether the executive officers’ and/or senior managers’ compensation is linked to attainment of GHG targets. 9) Whether the organisation conducts an annual inventory of total direct/indirect GHG emissions from operations. 10) Whether the organisation calculates GHG emissions savings and offsets from its projects. 11) Whether the organisation has set an emissions baseline year by which to estimate future GHG emissions trends.

Emissions accounting

12) Whether the organisation sets absolute GHG emission reduction targets for facilities and products. 13) Whether the organisation has third-party verification processes for GHG emissions data. 14) Whether the organisation has a specific policy to purchase and/or develop renewable energy sources. 15) Whether the organization has specific requirements for suppliers to reduce greenhouse gas emissions associated with their operations. 16) Whether the organisation has a policy of providing product information, including emissions reduction information to the customers through product labelling.

Research and development

17) Whether the organisation has a specific policy to develop energy efficiency by utilising/acquiring low-emission technologies. 18) Whether the organisation has a policy of investment to accelerate the research and development of low-emissions technologies and support energy efficient projects.

Potential liability reduction

Reporting/ benchmarking

19) Whether the organisation pursues strategies to minimise exposure to potential regulatory risks and/or physical threats to assets relating to climate change. 20) Whether the organisation has specific frameworks to benchmark its GHG emissions against other companies and competitors. 21) Whether the organisation has a policy of compliance with Global Reporting Initiatives (GRI) Guidelines or a comparable Triple Bottom Line format (for example, GHG Protocol) to report its greenhouse gas emissions and trends 22) Whether the organisation has a policy for trading in regional and/or international emission trading schemes.

Carbon pricing and trading 23) Whether the organisation has a policy to assist government and other stakeholders on the design of effective climate change policies such as carbon pricing and/or a national emission trading scheme.

External affairs

24) Whether the organisation has a public policy to support collaborative solutions (for example, work with the government and other organisations in voluntary emission reduction projects) for climate change. 25) Whether the organisation has a policy to promote climate friendly behaviour within the community by raising awareness through environmental sustainability education.

APPENDIX II Model Summaryb Model

R

1

,755a

R Square

Adjusted R Square

,571

Std. Error of the Estimate

,540

DurbinWatson

2,35187

2,394

a. Predictors: (Constant), ENERGYPROD, ROA, OILANDGAS, MINING, CHEMICALS, BUILTMAT, LNASSETS, INDPROD, IRONANDSTEEL b. Dependent Variable: DI ANOVAa Model

1

Sum of Squares

df

Mean Square

Regression

918,561

9

102,062

Residual

691,410

125

5,531

1609,970

134

Total

F

Sig. ,000b

18,452

a. Dependent Variable: DI b. Predictors: (Constant), ENERGYPROD, ROA, OILANDGAS, MINING, CHEMICALS, BUILTMAT, LNASSETS, INDPROD, IRONANDSTEEL

Coefficientsa Model

Unstandardized Coefficients B (Constant)

-25,765

3,359

10,876

2,596

1,568

OILANDGAS

t

Sig.

Beta -7,671

,000

,251

4,190

,000

,156

,707

10,074

,000

-1,088

1,866

-,079

-,583

,561

CHEMICALS

-3,587

1,742

-,376

-2,060

,042

IRONANDSTEE L

-2,738

1,717

-,351

-1,594

,113

-,974

2,039

-,048

-,478

,634

BUILTMAT

-1,403

1,735

-,155

-,808

,420

INDPROD

-2,451

1,714

-,305

-1,430

,155

ENERGYPROD

-5,420

1,983

-,323

-2,734

,007

ROA LNASSETS

1

Std. Error

Standardized Coefficients

MINING