It’s getting hotter: Climate impact and the quality of
climate-related risk disclosures of listed companies
Master Thesis, MSc Accountancy
University of Groningen, Faculty of Economics and Business
Ruben Nijboer Studentnumber: S2663368 Friesestraatweg 205-5 9743AD, Groningen Tel: +31629396429 E-mail: R.J.Nijboer@student.rug.nl Supervisor: M. Looijenga MSc EMA RA
Co-assessor: Prof. Dr. D.A. de Waard Word count: 8324
ABSTRACT: Global climate change is changing the world we are living in. Rising global
temperatures are causing an increase in climate-related risks such as hurricanes and floods. There is a growing interest in these risks among stakeholders of organizations and an increasing demand of (voluntary) information disclosure about climate-related risks. In this research we studied to what extend the quality of an organization’s climate-related risk disclosure is influenced by an organization’s risk exposure to climate-related risks and by how environmentally polluting an organization is. 131 annual reports of organizations in the Fortune Global 500 have been examined. A scorecard based on the recommendations of the Task Force on Climate-related Financial Disclosures (TCFD) was developed in order to assess the quality of the climate-related risk disclosures in annual reports. The results show that organizations which are highly exposed to climate-related risks and organizations which are environmentally polluting have an increased climate-related risk disclosure quality. These results could be used by organizations to further increase their climate-related risk disclosure quality, helping academics with a better understanding of determinants of climate-risk disclosure quality, and aid stakeholders in their decision making.
Keywords: risk disclosure quality, voluntary disclosure, risk exposure, environmental
Table of Contents 1. INTRODUCTION 3 2. THEORETICAL BACKGROUND 6 2.1AGENCY THEORY 6 2.2LEGITIMACY THEORY 6 2.3SIGNALLING THEORY 7 2.4VOLUNTARY DISCLOSURE 8 2.5RISK DISCLOSURE 8
2.6CLIMATE RISK DISCLOSURE 9
2.7QUALITY OF RISK DISCLOSURE 10
2.8SYMBOLIC AND SUBSTANTIVE RISK MANAGEMENT 10
2.9HYPOTHESIS DEVELOPMENT 11
3.0 METHODOLOGY 13
3.1SAMPLE SELECTION AND DATA COLLECTION 13
3.2DEPENDENT VARIABLE 14 3.3INDEPENDENT VARIABLES 15 3.4CONTROL VARIABLES 16 3.5EMPIRICAL MODEL 18 4. RESULTS 19 4.1DESCRIPTIVE ANALYSIS 19 4.2CORRELATION MATRIX 20 4.3STATISTICAL ANALYSIS 21 4.4ROBUSTNESS CHECK 22
5. DISCUSSION AND CONCLUSION 24
1. INTRODUCTION
It is widely known that global climate change is representing a direct threat to the world, humanity and the economy (IPCC, 2014,2018). Nearly 200 countries agreed upon signing the ‘Paris Agreement’ in 2015 to hold the global temperature rise at a maximum of 2°C (UNFCCC, 2015). The increase in global temperature brings forth increasing heat stress, storms and extreme precipitation, inland and coastal flooding’s, landslides, air pollution, drought, water scarcity, sea level rise and storm surges as a result of climate change and could harm assets, economies, ecosystems and/or human lives, especially in urban areas (IPCC, 2014, 2018). At the World Economic Forum of 2019, the management of companies showed more interest in these in climate related risks. KPMG found out in their survey about corporate social responsibility, published in 2017, that most of the companies see climate related risks as one of the most material risks, however only 28% of the 4900 analyzed financial reports acknowledge the financial risk of climate change. Climate change can have a negative effect on the profitability of a firm (Dafermos et al., 2018) and negatively impact portfolios performance and the value of investments (Battiston et al. 2017). For example, rising temperatures decrease the thermal efficiency of Fossil, nuclear, biomass and solar power generation technologies (Arent et al., 2015). Zhao et al. (2016) estimated that high temperature subsidies for working on extreme hot days in China will increase to 250 billion yuan in 2030 if the global temperature rises with 1,5°C. Lobell et al. (2011) state that an increase in global temperature will result in reduced crop production. The estimated loss of global financial assets due to climate change is expected to be about 24.2 trillion USD worldwide when we do not meet 2°C maximum increase in global temperature (Dietz et al., 2016).
Stakeholders are interested in these risks (VEB, 2020; Blackrock, 2020; Warren, 2020) and could ask questions about how these risks are being addressed or if there any possible business opportunities arising from climate change. For instance, the disclosure of GHG-emission (greenhouse gas) information by a company makes it possible for stakeholders to assess whether opportunities and risks regarding GHG-emission are taken into account, and identifying the strategies that are adopted to cope with these opportunities and risks (Bebbington & Larrinaga-Gonzalez, 2008). This explains the success of initiatives such as the Carbon Disclosure Project which collects carbon data from the world’s largest listed firms through a questionnaire and has more than 1000 respondents each year (Depoers et al., 2016).
If information is not disclosed properly it will impact the ability of an investor to assess information about risks associated with a public company (Abraham and Shives, 2014). Solomon et al. (2011) found that investors use risk management disclosures for their portfolio investment decisions to assess information about whether there are any risks or opportunities for the company regarding climate change. Bonnel and Swann (2015) found that there is a growing awareness of finance institutions regarding integrating climate risks into their risk assessment of investment portfolios.
The growing pressure of regulating climate change has led to changes in the sustainability risk management practices and reporting (Christofi et al., 2012), like the establishment of the TCFD recommendations. The 2015 United Nations Climate Change Conference in Paris brought forth the discussion on how to address climate risks and also climate-related financial disclosure. The Task Force on climate-related financial disclosures (TCFD) was established in 2015 by the Financial Stability Board (FSB) to support the goals of the Paris climate agreement with the goal to highlight the need for more transparency in climate-related financial disclosure and created tools for assessing the risks and opportunities of climate change (TCFD, 2017). In June 2017 the TCFD recommended companies to disclose the risk management process of climate-related risks and the impact of climate change on their business in their annual reports. The TCFD divides climate-related risks into two sorts of risks. Physical risks resulting from climate change can be event driven (acute) or longer-term shifts (chronic) in climate patterns. Physical risks may have financial implications for organizations, such as direct damage to assets and indirect impacts from supply chain disruption. Organizations’ financial performance may also be affected by changes in water availability, sourcing, and quality; food security; and extreme temperature changes affecting organizations’ premises, operations, supply chain, transport needs, and employee safety. Transitional risks to a lower-carbon economy may entail extensive policy, legal, technology, and market changes to address mitigation and adaptation requirements related to climate change. Depending on the nature, speed, and focus of these changes, transition risks may pose varying levels of financial and reputational risk to organizations.
Companies are recommended to disclose information about how they identify, asses and manages climate-related risks by the TCFD. “Given the right information, investors are expected to deliver the best climate solutions’’ (Carney and Bloomberg, 2016). A recent status report of the TCFD (TCFD, 2019) showed an increased amount of climate-related risk
disclosures, however still not sufficiently detailed for investors In line with the status report of the TCFD, Eccles & Krzus (2019) found that oil & gas companies discussed climate-related risks and are disclosing climate-related risk information accordingly to the TCFD recommendations, but lack detail. relevant to research what influences and causes the difference in disclosure quality of the climate-related risk disclosures and for this research if the type of industry an organization is operating in and climate-related risk exposure has effect on climate-related risk disclosure quality. The research question becomes: To what extend is the quality of climate-related risk disclosure influenced by an organizations industry type its exposure to s.
Environmental disclosure has been widely studied (Alsaifi et al., 2020; Fondevila et al., 2019; Yao et al., 2019; Li et al., 2018; Cho et al. 2012; Clarkson et al., 2008; Milne and Patten, 2002; Wilmshurst and Frost, 2000). However, previous studies that have been studying climate-related risk disclosure are still scarce (Leopizzi et al., 2020; Dumay and Hossain, 2019; Kouloukoui et al., 2019; Kouloukoui et al., 2018; Kouloukoui et al., 2017; Messervy and Mchale, 2016). These previous studies about climate-related risks are primarily focusing on the quantity and transparency of information that is disclosed by companies, but do not study the quality of these disclosures. This introduces the existing research gap of not knowing how good the disclosure quality of climate-related risks is. Conducting research will contribute to future academic research about disclosure quality of climate-related risks and helps reducing th research gap. It is important for our society and the world to know that these climate-related risks are properly being addressed in annual reports and therefore that companies are aware that they are at risk. The outcome of this research will also contribute to the decision making of stakeholders based on the climate-related information of companies by potentially influencing the decision making if a poor or good climate-related risks disclosure quality is determined.
2. THEORETICAL BACKGROUND
In this section three theory’s, namely the agency theory, the legitimacy theory and the signalling theory) will be explained in order to get a better understanding why it is important to disclose information about climate-related risks. Further, an explanation of disclosure, risk disclosure, climate risk disclosure, disclosure quality and symbolic / substantive management will be given. Finally, the hypotheses will be developed.
2.1 Agency Theory
The agency theory is one of the most often used theories to explain the outcomes of voluntary disclosure studies (Abraham and Shrives, 2014; Abraham and Cox, 2007). The agency theory addresses the information asymmetry between the agent the and the principal and the separation of ownership and control between them (Jensen and Meckling, 1976). In practice, the agent can be seen as the management of an organization and the principle is the owner of an organization. The management of an organization and the owners of an organization both have their own interests and are therefore seeking to maximize their own individual utility (An et al., 2011) and information asymmetry between them will occur (Fama and Jensen, 1983).
An increase in information asymmetry leads to higher agency costs but can be solved if private information is fully disclosed by managers and this is shared with investors (Healy and Palepu, 2001). Therefore, disclosing climate-related risk information can lead to less information asymmetry. Decreasing information asymmetry makes it easier for investors to assess the past, current and prospect performance (Hooghiemstra et al., 2015) and, in terms of climate-related risk disclosure, assessing whether these risks are properly addressed by the management. To increase investors trust, information asymmetry needs to be reduced (Scott, 2009).
2.2 Legitimacy Theory
The legitimacy theory suggests that an organization has a contract with the society in which they are operating in (Shocker and Sethi 1973; Gray et al., 1995; O’Donovan, 2002, Deegan, 2006). Organizations behavior is affected by the external social pressure of this society (Tilling 2004), which is congruent with the public opinion, value system and beliefs (Lindblom, 1994; Stanny and Ely, 2008). Society will accept continuation of an organizations operations as long it is in line with society’s beliefs (Deegan, 2006). According to Sinclair and Bolt (2013) legitimate can be seen as acting in line with the society’s beliefs. This is further defined by Suchman (1995): “The generalized perception or assumption that the actions of an entity are
desirable, proper or appropriate’’. To operate in line with these social beliefs an organization will operate and take actions ensuring that it is perceived as legitimized (Prado-Román et al., 2018). When an organization is not handling according to the social beliefs a legitimacy gap will develop (Andreaus et al., 2014). It is important to keep this gap as small as possible in order to create long term value and acceptance by society (Tilling, 2004). An organizations growth and survival are dependent on its ability to operate in a way that is socially desirable (Shocker and Sethi, 1973) and to operate in a way the total of the benefits is higher than the costs for society (Mousa and Hassan, 2015).
The theory of legitimacy has been used in various studies who try to explain the voluntary disclosure of environmental information according to Pellegrino and Lodhia (2012). They studied, based on the theory of legitimacy, why mining companies in Australia are disclosing environmental information and are ‘securing’ their social contract. Disclosing environmental information might be a motivation and a way for organizations to secure their legitimate status within society (Deegan et al, 2002). When looking at risk disclosure, legitimacy is increased when more risks are disclosed, (Oliveira, Rodriques and Craig, 2011). This is achieved through an enhancement of stakeholders’ ability to match their expectations with the outcomes. The management of stakeholder’s social beliefs influences the image of an organization and stakeholders’ perception of management’s ability to cope with risks (Iatridis, 2008). Achieving legitimacy becomes a resource that can be created, manipulated and influenced by applying different disclosure strategies (Woodward et al., 2001). Therefore, disclosure of climate-related risk information will enhance legitimacy through an increase in transparency of the risks related to an organization’s operations and actions.
2.3 Signalling Theory
The goal of the signalling theory is, just like the other theory’s, to explain the actions why an organization wants to reduce information asymmetry between their stakeholders and themselves. Information asymmetry leads to sub optimal stock prices because investors are not willing to pay the optimum price (An et al., 2011). The signalling theory suggest that managers tend to disclose more good news and conceal the bad news (Verrecchia, 1983), and try to improve their reputation by voluntary disclosing information (Abraham and Shrives, 2014), signalling investors they are capable of managing problems and risks. Organizations that are facing many risks tend to disclose more information than organizations who face less risks (Elshandidy et al., 2013). A higher quality disclosure improves the signal stakeholders receive about how the management is effectively managing the risks (de Villiers and van Staden, 2011)
and therefore lowers the cost of capital (De Klerk et al., 2015). It is a way of signalling that the risks are properly managed to the stakeholders and reduces information asymmetry. Therefore, in line with the signalling theory, significant climate-related risks must be reported with high quality to lower the chance on adverse selection and information asymmetry between an organization and its shareholders resulting in an increased cost of capital.
2.4 Voluntary Disclosure
To meet the stakeholder’s demands of information, organizations disclose information voluntary (Dumay and Hossain., 2019). Not disclosing information about climate-related risks brings forth information asymmetry and decisions made by stakeholders based on incomplete information, also known as the agent-principal problem (Jensen and Meckling, 1976). Communication of voluntary information between the organization and the stakeholders can be seen as a way of legitimizing what an organization is doing and as an explanation why companies are disclosing climate-related risks. Communication that is taking place between business and society can be seen as fundamental because of the emphasis on dialogue and relationship management, and if this fails legitimacy may be threatened (Kouloukoui et al., 2019). Thus, for this research about disclosure the agency theory and legitimacy theory will be used for explaining the outcomes and results. The adoption of multiple theories mitigates the limitations that each theory brings forth and enhances the possibility of explaining outcomes of this research. For instance, Ntim et al. (2013) used the adoption of multiple theory’s for explaining the outcomes of strategic risks disclosure quality.
2.5 Risk Disclosure
A risk can be defined as “the modern approach to foresee and control the future consequences of human action, the various unintended consequences of radicalized modernization’’ (p. 3 Beck, 1999). In the finance area a risk is often defined as a collection of effects which can be evaluated, and probabilities can be assigned to (Watson et al., 2002).
The annual report is an important channel for an organization to disclose information to the public (Ronen and Yaari, 2001; Barakat and Hussainey, 2013). Disclosing information about a risk normally happens by describing the risk in an organization’s annual report. Dobler (2008) defines risk reporting as risk-disclosures which have impact on future cash flows of an organization. Risk disclosure has been defined in several previous studies. One definition of risk disclosure has been defined by Miihkinen (2012): “All information that firms provide in
the risk reviews they present in their annual reports’’. Beretta and Bozzolan (2004, p. 269) further define what kind of information is affected by a risk and what is seen as risk disclosure: “the communication of information concerning firms’ strategies, characteristics, operations, and other external factors that have the potential to affect expected results”. Linsley and Shrives (2006) define risk disclosure as any exposure, danger, harm, hazard, opportunity, prospect or threat that might have impact on an organization in the future. Studies on risk disclosure often recognize that a risk is very complex and is influenced by multiple factors (Linsley and Shrives, 2006).
The more risk an organization is facing, the more risk disclosure to the public is possible (Miihkinen, 2012). Larger firms tend to disclose more information about risks than smaller firms (Linsey and Shrives, 2006). Abraham and Cox (2007) found that listed firms in the UK tend to disclosure more information than non-listed firms. Larger firms also tend to produce higher quality risk disclosures, because larger firms can pay more attention on improving the risk disclosure quality and have more financial resources (Hassan, 2014).
The disclosure of risks in an annual report has several benefits. Disclosure of risk related information lowers the information asymmetry problem (Healy & Palepu, 2001), lowers the risk premium (Easley & O ‘Hara, 2004), lowers the cost of capital (Botosan and Plumlee, 2002) and increases investors’ confidence about the firms future performance (Nier and Baumann, 2004). Disclosed risk related information can also be used by investors as an external monitoring tool to assess managements performance and decreasing opportunistic behavior of the management (Li et al., 2008). Solomon et al. (2000) found that risk management practices increases shareholders’ wealth by minimizing financial failure and maximizing profitability. Risk management is a systematical approach by the management of identifying, analyzing and managing risks (Emanuals and De Munnik, 2006).
2.6 Climate Risk Disclosure
Sustainability disclosure is a way for companies to disclose of information about sustainability risks on the short, medium and long term (Herbohn et al. 2014). Disclosing information about climate-related risks can be seen as a way of achieving an sustainable image and reducing external pressure from stakeholders (Deegan & Gordon, 1996; Deegan et al., 2002), maintaining the approval of crucial stakeholders (Unerman et al., 2008), and managing political and media visibility (Thorne et al., 2014). In 2007 Pinkse and Kolk found that companies were already exploring the risks as a result of global climate change. Modernization, increasing climate change risks such as environmental disasters (Giddens, 1991), “brings forth threats to
life of plants, animals and human beings” (Beck, 1992, p. 13). 80% of the 20 most significant loss-events over the last 35 year were caused by extreme weather events (Kunreuther and Michel-Kerjan, 2007), which is an example of a physical risk. Products and services that are carbon intensive will in the near future become inferior to more sustainable substitutes (Kolk and Levy, 2001) and investors might shift their investments and capital from carbon intensive assets to more sustainable alternatives (Lee and Ellis, 2013), both being examples of transition risks. In the long run, these climate-related events need to be interpreted better in terms of duration and frequency (Thistlewaite and Wood, 2018). The external impacts of climate change cause a shift in the “broader space that an organization is positioned in” (Spicer, 2006, p. 1473).
2.7 Quality of Risk Disclosure
Providing climate-related risk information that can be placed in a context instead of just information is a challenge organizations face, because of the demand for useful information (Themistokles et al., 2008). In a study of Lajili and Zéghal in 2005 they showed that disclosures in general lack clarity, uniformity and quantification, decreasing the readability and usefulness for stakeholders. This is in line with what Ntim et al. (2013) and Oliveira et al., (2011) found about the low quality of risk disclosures being mostly qualitative, generic and historical. Linsley and Lawrence (2007) analyzed the writing style used in disclosures of U.K. companies and found that those lacked readability. Having high quality risk disclosures is important, e.g. it lowers stock volatility (Baumann and Nier (2004). Having higher quality disclosures makes it possible for stakeholders to compare organizations with each other and determine the difference in performance (Chauvey et al. (2015).
2.8 Symbolic and Substantive Risk Management
However, although an annual report might contain much information about climate-related risks, it not necessarily informs stakeholders about an organization’s actual activities. Organizational legitimacy is often acquired through symbolic disclosure of information (Dowling and Pfeffer, 1975: Neu et al., 1998). Symbolic sustainability disclosure leads to misinformation of stakeholders about the actual image of an organization (Cho et al., 2012) and portraying it as committed (Hopwood, 2009). Boiral examined in 2013 to what extend environmental reports were used to hide real sustainability problems and risks by focusing on the quality of the disclosures looking at the standards of the GRI. However symbolic ticking of the GRI boxes seems to be increasing the volume of the disclosed information and the symbolic
performance (Cooper and Annisette, 2012), but this symbolic ticking does not necessarily increase the quality of disclosures. This is in line with the study of Cho et al. (2010) who found that environmental disclosure in annual reports, even in a highly legislated environment, is subjective to impression management techniques. Berrone et al. (2011) studied two general ways of achieving organizational legitimacy. The symbolic disclosure management technique is one of the two general ways of achieving organizational legitimacy. The other way of achieving organizational legitimacy is by substantive management actions, such as actually implementing policies and changes in core practices resulting in organizational legitimacy and does translate into actual performance.
2.9 Hypothesis development
In environmental research, industry type is one of the most common used variables to explain the level of environmental disclosure (Hassan and Ibrahim, 2012; Reverte, 2009; Bowen, 2000; Adams et al., 1998; Morris, 1997; Gray et al., 1995). The level of disclosure may differ across industries due to unique characteristics of an industry (Wallace et al., 1994). In line with the expectation of Wallace et al. (1994), Hackston and Milne (1996) found that industry has influence of the disclosure level.
Some organizations are more exposed to climate-related risks than others, due to the nature of their operations and the associated risks (physical or transition) with these operations (SASB, 2016; SASB, 2017; TCFD, 2017). The difference in risk exposure is a threat for investors aggregated value, return on investment and the organizational performance (Labatt and White, 2007). A study of Roberts (1992) showed that companies with a high regulatory risk are more likely to disclose information about corporate social responsibility. More recently, Abraham and Cox (2007) found a positive relationship between risk levels and amount of risk disclosure. Elshandidy et al. (2013) studied the effect of high-risk organizations on their voluntary disclosure and found that high-risk organizations are more likely to disclose voluntary risk information. In line with the signalling theory, management’s ability to measure, identify and manage the climate-related risks by disclosing more information about these risks signals investors of their capabilities and reduces uncertainty among investors. Therefore, the hypothesis is stated as follows:
H1: An industry type with a higher climate-related risk exposure positively influences the quality of the climate-related risk disclosure of an organization
Organizations operating in different industries have a different environmental impact (Halme and Huse, 1996). If an industry has a high environmental impact, it tends to cause more environmental issues (Bowen, 2000). In other words, if an industry is contributing to the increase in climate change, there is increase in climate-related risk which is self-induced. Organizations from different industries also differ in the level and amount of disclosed information about their environmental activities (Valentine, 2010; Martin and Hadley, 2008; Stray and Ballentine, 2000). Industries that have a negative impact on the environment disclose more information than other industries (Reverte, 2009). Poor environmental performance is associated with an increase in voluntary disclosing information in annual reports to decrease the amount of information asymmetry between stakeholders and an organization (De Villiers and van Staden, 2011). This is in line with the research of Dierkes and Preston (1977) who found that when organizations are acting in a potentially polluting activities, they tend to disclose more environmental information. This is because highly polluting companies are more exposed to political and social influences (Newson and Deegan, 2002). The difference in polluting potential associated with an industry has impact on the control and expectation by stakeholders (Gonzalez-Benito and Gonzalez- Benito, 2006). A legitimacy gap might develop and organizations might feel the need to disclose more information regarding climate-related risks. These arguments might indicate a positive influence of industry type and the amount this type pollutes on the quality of climate-related risk disclosure. Therefore, the hypotheses are stated as follows:
H2: A polluting industry type positively influences the quality of the climate-related risk disclosure of an organization.
To classify an organization’s environmental performance type, organizations will be categorized by industry type as polluting or non-polluting industry. To classify an organization’s risk exposure type, organizations will be categorized by their exposure to climate-related risks in ‘highly exposed’ and ‘less or not exposed’. Categorization of organizations will be described more detailed in the methodology section.
3.0 METHODOLOGY
In this section the data and methods that are used in this research are described. First, the sample selection and the process of data collection will be described. Second, the dependent, independent and control variables will be described. Finally, the regression model will be described.
3.1 Sample selection and data collection
The Fortune Global 500 index is a selection of the 500 largest organizations in the world and is updated annually. The organizations are ranked by the amount of revenue generated in a year and consist of organizations from different industries. This research will use data which is collected from audited annual reports from the 2018 of organizations who were then listed in the Fortune Global 500 Index. The year 2018 is chosen because this is the most recent year in which the TCFD recommendations announced in June 2017 (TCFD, 2017) could have affected the quality of climate-related risk reporting in annual reports.
For this research this index is partially used because some criteria are applied to the index: 1. For this research it is not feasible to hand collect data from 500 organizations due to
time constraints, therefore a selection will be made of the 150 organizations.
2. Audited annual reports are acquired by downloading it from an organization’s website or, if not available, from a reliable alternative source. Companies which do not have annual reports available, in English, will be excluded from the sample.
The method of content analysis (Weber, 1990) was applied to extract the data from audited annual reports. The extracted data can be used for measuring the disclosure quality of climate-related risks and to distinguish in which industry an organization is operating in. An annual report is the primary source for organizations to disclose information about risks (Abraham and Cox, 2007). During the research collection there was a specific focus on data in the risk paragraph of annual reports, because this is the most common and plausible place where climate-related risk disclosures can be found.
The data was collected by two research practitioners who were familiar with the research objective and carefully studied the climate-related risk paragraph in annual reports. To extract the right data needed for measuring the quality of climate-related risk disclosures a self-constructed scorecard was used based on the TCFD recommendations. In case of doubt
regarding the classification of content, this was carefully discussed between the two researchers. Persistent uncertainty regarding the classification of content was mitigated by a consult of climate disclosure expert. A sub sample of annual reports from Fortune Global 500 organizations was pre-tested in order to increase the validity of the self-constructed scorecard. There is a risk of biased results when data is individually collected through content analysis. To mitigate this risk the two researcher practitioners regularly checked and discussed each other’s work ensuring a homogeneous judgement and inter-rater reliability. The impact of choosing the first 150 organizations of the Fortune Global 500 instead of choosing a sample with random organizations in the Fortune Global 500 is negligible and a variety of industries types was checked in advance before the collection of data from the sample.
The development and use of this scorecard will be further explained in section 3.2.
3.2 Dependent variable
No previous study was found measuring the climate-related risk disclosure quality (CRDQ) in annual reports. As mentioned earlier, most previous studies assess the quantity of climate-related risks and do not assess the quality. The most common way to measure disclosure is by the use of a disclosure index or by the use of content analysis. However, these often measure the quantity of information disclosed and does not asses the quality of information disclosed (Beretta & Bozzolan, 2004). In order to measure the dependent variable CRDQ a scorecard was self-by two researchers, which is known to increase the usefulness of the extracted information (Scaltrito, 2015). The scorecard was based on the TCFD recommendations which were introduced in June 2017. These recommendations which can be found in appendix A and form the foundation of the developed scorecard criteria. The TCFD recommendations regarding ‘Risk Management’ and ‘Metrics and Targets’ were found most useful for the development of our scorecard.
Using the content analysis method on annual reports of organizations, these annual reports were awarded points when they disclosed information that was part of our scorecard criteria. A score of 1 was awarded when the matter was discussed in the risk management paragraph, and 0 otherwise. Making use of a 0- or 1-point award system instead of a multiple score scale increases the objectivity and thus the reliability of the results and is better known as the unweighted method (Kavitha & Nandagopal, 2011). For some criteria an ordinal point award system of 0- (Non-disclosure), 1- (partial disclosure) or 2-points (full disclosure) was used. Enumerating each criteria, the annual reports of organizations obtain a different total amount of awarded points reflecting the CRDQ. Thus, organizations can on score differently on their
CRDQ, making it possible to test what influences this dependent variable. The maximum total score is 12 points, 6 points for the “Risk Management Process” (RMP) and 6 point for “Metrics & Targets” (MT) The scorecard used for measuring CRDQ and a detailed explanation of RMP and MT can be found in appendix B.
3.3 Independent variables
3.3.1 Risk Exposure Type
Industry type is used in several previous environmental studies explaining the level of disclosure. The Sustainability Accounting Standards Board (SASB) recently made a Sustainability Industry Classification Standard (SICS) which classifies an organization into a certain type of industry. The SASB additionally conducted research on which industries are most likely to be exposed to climate-related risks with a financially material impact (SASB, 2016). The identified industries correspond with the 4 groups of industries identified by the TCFD as most exposed to climate-related risks: Energy, Transportation, Materials and building, and agriculture/food/forest products. For organizations in these industries it is relevant to disclose extra information about the climate-related risks they are exposed to. Therefore, we divide organizations two groups: Organizations highly exposed to climate-related risks and organizations that are less or not exposed to climate-related risks. To classify an organizations risk exposure type (REXP) to an SICS industry classification, the International Securities Identification Number (ISIN) of an organization is used to look up and identify the classification using the SICS Look-up tool on the SASB website. A specification of which industry belongs to what group can be found in Appendix C.
3.3.2 Pollution Type
Industry types that are environmental sensitive are chemicals, metal, oil and gas, chemicals and power, and utilities (Prasad et al., 2017; Clarkson et al., 2013; Clarkson et al., 2008; Patten, 2002). emission will be used as a proxy for environmental performance. The GHG-emission by these industry types is expected to be higher than other industries. Recently, the SASB has identified 23 of 79 industries of which GHG-emissions are likely to be material for financial performance, because they are expected to have a higher GHG-emission than other industries (SASB, 2018). The environmentally sensitive industries determined in previous research all fall within those 23 industries. Therefore, in this research we will categorize environmental sensitive industries in the sample, which are 23 industries, as polluting industries. All other 56 industries within the sample will be categorized as non-polluting industries. To classify an organizations pollution type (POLT) to a SICS industry classification, the International Securities Identification Number (ISIN) of an organization is used to look up and identify the classification using the SICS Look-up tool on the SASB on the SASB website. A specification of which industry belongs to what pollution type can be found in Appendix C.
3.4 Control Variables
In this research control variables ‘Firm size’ (SIZE), ‘Profitability’ (PROF), ‘Leverage’ (LEV) and ‘Law type’ (LAW) are used to control for effects other than POLT and REXP on climate-related risk disclosure quality.
3.4.1 Firm size
Previous literature has shown that firm size has a positive influence on risk disclosure (Khlif & Hussainey, 2016; Abraham and Cox, 2007; Linsey and Shrives, 2006). Larger organizations have more complex and varied operations which leads to an increase of the information asymmetry problem (Deumes and Knechel, 2008) and therefore disclose more information about risks to reduce this problem. Costs for disclosing information about risks is lower for larger organizations, relative to smaller organizations (Elshandidy et al., 2013). Firm size (FSIZE) is measured by the natural logarithm of the total assets (Archambault and Archambault, 2003).
3.4.2 Profitability
In line with the signalling theory, organizations with a high profitability and good performance have greater incentives to signal investors about their risk management by disclosing more information (Khlif & Hussainey, 2016). Previous research has shown that profitability has a positive effect on risk disclosure (Miihkinen, 2012). Profitability (PROF) will be measured by return on equity, which can be calculated dividing profit by total equity at the end of the year.
3.4.3 Leverage
Being an agency problem, previous research has shown that highly leveraged organizations have higher incentives to disclose more information about their risks (Khlif & Hussainey, 2016; Taylor et al., 2010). A higher leverage results in more agency costs (Elzahar and Hussainey, 2012), because of more restrictive covenants in debt contracts which increases agency costs (Khlif and Hussainey, 2016). Disclosing information about the management of climate-related risks can mitigate creditors concerns of an organizations future ability to pay off debts (Rajab and Handley-Schachler, 2009). Leverage (LEV) will be calculated by dividing an organizations total debt by total equity at the end of the year.
3.4.4 Law
In 1999, Ahmed and Courtis found inconclusive results of determinants of risk disclosure and thought a legal system might influence the results. In general, there are 2 different kinds of legal systems: civil law and common law. While the civil law system is known for its secrecy and control, common law is known for its professionalism and transparency, both impacting the transparency of risk disclosures (Stulz and Williamson, 2003) because secrecy causes a negative effect on the level of risk-related disclosure (Hooi, 2007). Recently, Khlif and Hussainey (2016) studied the effect of different law systems on the level of risk disclosure and concluded that law type has a moderating effect on the risk-related disclosure. Ruland et al. (2007) states that in general the level of risk disclosure is larger in common law countries. Elshandidy et al. (2015) found that a common law type has a positive effect on the level of risk disclosure. The variable law type (LAW) will have a value of 0 if the organization is operating from a civil law country and a value of 1 when it is operating from a common law country.
3.5 Empirical model
The ordinary least square method will be used for testing the hypotheses. Climate-related risk disclosure quality (CRDQ) is the dependent variable in the empirical model. The independent variables will be ‘Risk exposure’ (REXP) for testing H1 and ‘Pollution type’ (POLT) for testing H2. IBM SPSS statistics 25 will be used to for executing our statistical analysis. The empirical model is shown below:
CRDQ = ß0 + ß1 REXP + ß2 POLT + ß3 FSIZE + ß4 PROF + ß5 LEV + ß6 LAW + ε
Table 1
Summary of variables
Variable Description
Dependent variable
CRDQ The quality of the climate-related risk disclosure of an organization, which is measured by a self-constructed scorecard consisting of 2 different categories (Risk Management Process / Metrics & Targets).
Independent variables
REXP Climate-related risk exposure type of an organization POLT Environmental pollution type of an organization
Control variables
FSIZE The size of a firm, which is measured by the natural logarithm of the total assets at the end of the year
PROF Profit divided by total equity at the end of the year
LEV Total debt divided by the total assets at the end of the year LAW Common or civil law in the organization’s country of origin
4. RESULTS 4.1 Descriptive Analysis
The descriptive statistics about the dependent variable, independent variables and control variables are included in Table 2 and 3. The original sample consisted of 150 organizations, however due to unavailable annual reports of certain organizations the final sample consisted of 131 organizations, which is an acceptable sample size. The average of the Climate Risk Disclosure Quality (CRDQ) is 31,11% with a standard deviation of 29,63%. The average Risk Management Process score was 2,01 of the 6 points available. The average Metrics & Targets score was 1,71 of 6 points available. 20 organizations scored the minimum CRDQ score of 0. The maximum CRDQ score of 12 points was achieved by 2 organizations. 55 organizations were found to be operating in an industry which is highly exposed to climate-related risks, 44 organizations were found to be operating in a polluting industry, 81 organizations are operating from a civil law country. Furthermore, the average firm size (FSIZE) is 25,95, the average profitability 3,83%, the average leverage 72,38% and in total 50 organizations originating from a country with a common law.
Table 2
Descriptive Statistics
Variables N Minimum Maximum Mean Std. Deviation
CRDQ 131 0% 100% 31.11% 29,63% REXP 131 0,00 1,00 0,34 0,47 POLT 131 0,00 1,00 0,42 0,50 FSIZE (ln) 131 20.39 29.02 25,95 1,37 PROF 131 -14,66% 25,27% 3,83% 4,34% LEV 131 23,70% 334,36% 72,38% 29,34% LAW 131 0,00 1,00 0,41 0,49 Table 3 Sample composition
Highly exposed Less or not exposed N
REXP 55 76 131
Polluting industry Non-polluting industry N
POLT 44 87 131
Civil Law Common Law N
4.2 Correlation Matrix
In table 4 the correlations between the dependent, independent and control variables are shown. According to if values in the matrix are higher than 0,0 or lower than -0,0 multicollinearity becomes a problem. All values are lower than 0,0 or higher than -0,0 indicating that multicollinearity is not a problem. The VIF value can also be used as an indicator for multicollinearity. All VIF values were there s no reason to suspect any multicollinearity all VIF values are lower than 5.
In total there are 8 significant relationships between the variables of which the relationship between CRDQ and REXP, CRDQ and LAW, POLT and REXP, FSIZE and POLT, LEV and PROF are strongly significant with a p-value <0,01. The strongest relationship in the matrix is between LEV and PROF (ß = -0,525; p <0,01).
Table 4
Correlation Matrix
CRDQ REXP POLT FSIZE PROF LEV LAW
CRDQ 1 REXP 0.274** 1 POLT 0.200* 0.443** 1 FSIZE 0,029 -0,178* -0.338** 1 PROF 0,022 -0,012 0,096 -0.254** 1 LEV -0,089 -0,097 -0.188* 0,111 -0.525** 1 LAW -0,291** -0,159 -0,126 0,002 0,124 0,163 1
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
4.3 Statistical Analysis
Table 5 shows the results of the 4 different models used for testing the effect of independent variables REXP and POLT on the dependent variable CRDQ. The regression was performed by using the ordinary least squares (OLS) regression method. Model 1 contains the control variables FSIZE, PROF, LEV and LAW, Model 2 contains the control variables and REXP, Model 3 contains the control variables and POLT, Model 4 contains all variables. At the bottom of Table 5 the R2, adjusted R2, F-value and highest VIF value for each model is shown. The regressions of all models contained all of the 131 observations of the final sample.
Model 1 is the first model that was tested and only contains the control variables. It has an R2 value of 0,090 and an adjusted R2 value of 0,062, which means that 6,2% of the variance in CRDQ is explained by the control variables. LAW (β = -0,181; p <0,01) is the only variable in this model which is significantly influencing the CRDQ. The negative value (β = -0,181) for LAW indicates that organizations with a civil law scored better on the CRDQ. In all other models LAW also has a significant negative influence on CRDQ. In all other models the control variables FSIZE, PROF, LEV are not significantly influencing CRDQ.
Model 2 is the second model that was tested and contains Risk Exposure Type (REXP as independent variable and the control variables. It has an R2 value of 0,149 and an adjusted R2 value of 0,115, which means that 11,5% of the variance in Climate-related Risk Disclosure Quality (CRDQ is explained by the independent variable REXP and the control variables. REXP (β = 0,150; p <0,01) is significantly positively influencing CRDQ. This result is in line with hypothesis 1, the research of Elshandidy et al. (2013), the research of Abraham and Cox (2007) and in line with what was expected according to the signalling theory. Hypothesis 1 is accepted.
Model 3 is the third model that was tested and contains Pollution Type (POLT as independent variable and the control variables. It has an R2 value of 0,124 and an adjusted R2 value of 0,089, which means that 8,9% of the variance in CRDQ is explained by the independent variable POLT and the control variables. POLT (β = 0,125; p <0,05) is significantly positively influencing CRDQ. This result is in line with hypothesis 2, the research of Dierkes and Preston (1977), the research of Reverte (2009) and is in line with what was expected according to the legitimacy theory. Hypothesis 2 is accepted.
Model 4 is the final model which was tested and contains all the independent variables and control variables. It has an R2 value of 0,159 and an adjusted R2 value of 0,118, which means that 11,8% of the variance in CRDQ is explained by the independent variables REXP, POLT and the control variables. REXP (β = 0,125; p <0,05) is significantly positively influencing CRDQ. In comparison with model 2, REXP is less significantly influencing CRDQ in model 4 (p < 0,05) than it does in model 2 (p < 0,01). POLT (β = 0,071; p > 0,05) however is not significantly influencing CRDQ in model 4, while in model 2 (p < 0,05) it does.
When looking at the results of model 4, which is containing both independent variables and control variables, pollution type (POLT) isn’t significant while it was in model 3. Model 3 did not contain risk exposure type (REXP) as a variable. Risk exposure type (REXP) is, in model 4, less significant than it was in model 2. It can be concluded that both variables are jointly explaining the change in CRDQ but do have an overlap in explaining the variance. Despite a strong significant correlation between REXP and POLT, the low VIF values and correlation matrix show no signs of multicollinearity. Future research might provide greater clarity on this topic through theoretical explanations exposing a possible moderating or mediating effect. In this research the focus lies more on the outcomes of the individual models than the integrated model
The R2 and adjusted R2 values in the 4 models are relatively low. A possible reason for this is the fact that the climate-related risk disclosure is on a voluntary basis and not mandatory. Voluntary organizational behavior is harder to predict and therefore a possible explanation for the relatively low R2 values.
4.4 Robustness check
As previously explained in section 3.1, the sample that was examined for this study not only consisted of annual reports but also contained 10-K or 20-F fillings from US listed firms. To verify whether using 10-K and 20-F fillings in our sample had a significant influence on the results 2 extra tests were conducted. To test the effect, the dummy variable SEC report (SEC) (0 if an organization disclosed a 10-K or 20-F report, 1 if an organization disclosed an annual report) was added in model 5 and 6. Model 5 tests hypothesis 1, model 6 tests hypothesis 2. The results show no changes in significance in comparison with model 2 and 3 and therefore there can be concluded that using 10-K and 20-F fillings did not had a significant influence on the outcomes of hypothesis 1 and 2.
Table 5
Ordinary Least Squares (OLS) Regression Results
(1) (2) (3) (4) (5) (6) Dependent Variable CRDQ CRDQ CRDQ CRDQ CRDQ CRDQ Intercept 0,125 -0,262 -0,347 -0,456 -0,178 -0,245 (0,520) (0,512) (0,544) (0,538) (0,513) (0,546) REXP - 0,150** - 0,125* 0,145** - (0,051) (0,055) (0,051) POLT - - 0,125* 0,071 - 0,116* (0,057) (0,061) (0,057) FSIZE 0,010 0,021 0,025 0,027 0,017 0,021 (0,019) (0,019) (0,020) (0,020) (0,019) (0,020) PROF 0.443 0,618 0,536 0,641 0,748 0,664 (0,725) (0,706) (0,715) (0,705) (0,708) (0,717) LEV -0,011 0,016 0,023 0,031 0,031 0,036 (0,105) (0,102) (0,104) (0,103) (0,102) (0,104) LAW -0,181** -0,161** -0,170** -0,158** -0,088 -0,098 (0.054) (0,053) (0,054) (0,053) (0,053) (0,072) SEC -0,112 -0,110 (0,074) (0,075) R-square 0,090 0,149 0,124 0,159 0,165 0,139 Adjusted R-square 0,062 0,115 0,089 0,118 0,124 0,098 F-value 3,131* 4,389** 3,549** 3.895** 4,081** 3,342** Highest VIF 1,559 1,570 1,565 1,572 2,074 2,087 ** = p < 0.01 * = p < 0.05
5. DISCUSSION AND CONCLUSION
This study examined whether climate-related organizational factors such as the exposure to climate-related risks and the amount of environmental pollution of an organization influence the climate-related risk disclosure quality (CRDQ) in the annual report from listed firms worldwide. With the increase in global temperature, organizations and investors start seeing climate-related risks as a material problem. The recently published TCFD recommendations by the Task Force on Climate-related Financial Disclosures show that the current lack in detail of related risk disclosures in annual reports is being challenged. To date, previous climate-related risk disclosure studies are primarily focusing on the quantity and transparency. This study focused on the quality of climate-related risk disclosure and aims at understanding: To what extend is the quality of climate-related risks disclosure influenced by an organizations industry pollution type and its exposure to climate-related risks.
The quality of the disclosures should, according to the signalling theory, increase when an organization is highly susceptible to climate-related risks. According to the legitimacy theory, the quality of the disclosures should also increase when an organization is environmentally polluting. The data used to test the hypotheses was retrieved with the use of a self-constructed scorecard. Annual reports from the financial year 2018 of 131 organizations listed worldwide have been examined and awarded points with a self-constructed scorecard which assesses the quality of the disclosed climate-related risk information.
When looking at the average CRDQ of 31,11%, one can conclude that there is still a lot of work to be done by organizations to increase the quality of their climate-related risk disclosures. Of the 131 organizations, 20 organizations scored the lowest possible score 0. It was noticeable that organizations from China rarely disclosed climate-related risk information, if they disclosed an annual report at all. This might be the case due to the fact that most of the Chinese organizations in the sample of this research are state-owned by the Chinese government, which in general does not leads to disclose information. It is striking that just 2 of the 131 organizations scored the highest possible score of 12. These organizations, Glencore International AG and BASF, both adapted all the TCFD recommendations regarding ‘Risk management’ and ‘Metrics & Targets’ in their annual report. Having the industry classification ‘Metals & Mining’ and ‘Chemicals’ respectively, both industries have a higher climate-risk exposure and are environmentally polluting. The CRDQ score of these organizations is in line with the study of Elshandidy et al. (2013) who found that high-risk organizations voluntary disclose more risk
information and in line with the study of De Villiers and van Staden (2011) who found that organizations with a poor environmental performance disclose more information.
The results of this study show that there is a positive significant relationship between the climate-related risk exposure of an organization and the CRDQ. Hypothesis 1 “An industry type with a higher related risk exposure positively influences the quality of the climate-related risk disclosure of an organization” is accepted. This implies that an organization which is highly exposed to climate-related risks has a higher disclosure quality of climate-related risks in their annual report. The result is in line with the findings of the aforementioned study of Elshandidy et al. (2013), the study of Abraham and Cox (2007) and the signalling theory. Furthermore, the results of this study show that there is a positive significant relationship between the environmental pollution type of an organization and the CRDQ. Hypothesis 2 “A polluting industry type positively influences the quality of the climate-related risk disclosure of an organization” is accepted. This implies that an organization with a poor environmental performance has a higher disclosure quality of climate-related risks in their annual report. The result is in line with the findings of the aforementioned research of Villiers and van Staden (2011), the research of Dierkes and Preston (1977) and the legitimacy theory. Furthermore, the research shows that both independent variables are jointly explaining CRDQ, however there is some overlap in the explanatory power of both and future research could provide more clarity.
An additional conducted analysis of cross-national differences between EU and US listed firms uncovered some interesting CRDQ averages. The EU listed firms average CRDQ is 55,17%. On the contrary, the US listed firms average is 17,38%, which is below the overall average CRDQ of 31,11%. The mandatory 10-K or 20-F fillings which are required by the Securities and Exchange Commission (SEC) and annual reports of US listed firms occasionally disclosed information about climate-related risks. The low average score of US listed firms might be caused by the fact that US listed companies sometimes only disclose a 10-K filling or 20-F filling and do not publish an annual report. These 10-K / 20-F fillings are snapshots of an organization’s risks and performance for stakeholders and often do not contain climate-related risk information. Climate-related risks could be included in an organizations sustainability report but are not sufficiently reflected in an organizations 10-K or 20-F filling, resulting in a low CRDQ score. A different explanation might be the fact that the US is almost on the bottom of Climate Change Performance Index (CCPI, 2018), which is implying that the US does not see climate change and its related risks as a material problem. This index might also explain
the high average CRDQ score of EU listed organizations. EU countries on average score high on CCPI index, which is implying that EU listed organizations see climate change and its risks as a material problem. These findings could be interesting for future climate-related research.
This study has several limitations. For this study a sample of organizations listed in the Fortune Global 500 of 2018 was chosen. The Fortune Global 500 contains the largest listed organizations worldwide and therefore smaller organizations are not included in the sample of this study. It is not known whether the found results also apply to smaller organizations or non-listed firms. Using a self-constructed scorecard has several limitations. First, despite aligning judgement and ensuring inter-rater reliability, rating annual reports is still a subjective action. Second, the reliability of the results from the scorecard are also questionable due to the fact that in this study it was used for the first time. Future research using this specific scorecard will increase its reliability. Organizations could not only disclose climate-related risks in annual reports but also in sustainability reports. Investors could also retrieve information from sustainability reports about climate-related risks relevant for an organization. Future research could include sustainability reports and it would be interesting to see if the results in this study will still hold.
In conclusion, this study uses annual reports from the year 2018 and assesses their climate-related risk disclosure quality. Future research could incorporate other years to uncover the multi-year effect of the recently announced TCFD recommendations from June 2017. It will be interesting to see if the rapidly changing climate will cause a major change in future climate-related risk disclosure practices. The results in this research show that the industry specific amount of exposure to climate-related risks and environmental pollution does have a significant effect on the quality of the climate-related risk disclosures of an organization. The findings in this research could aid stakeholders when making decisions regarding climate-related risks and the mitigation of these risks. In the future not only the climate will change, but also the climate-related risk disclosure will change, and it will be a hot topic.
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