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Value Relevance of Environmental, Social and Governance Disclosure
Zuraida Zuraida
Victoria University of Wellington and Syiah Kuala University
&
Noor Houqe and Tony van Zijl
School of Accounting and Commercial Law
Victoria Business School
Victoria University of Wellington
Date: 20/02/2014
Value Relevance of Environmental, Social and Governance Disclosure
ABSTRACT
This paper investigates the extent to which Environmental, Social and Governance disclosure (ESG)
by companies around the world impacts on market value. Using a large sample of non-financial
companies listed in 41 countries during the period 2008 2012, we test for value relevance by
employing the modified Ohlson (1995) model. We find support for the value relevance of disclosure
of ESG and its individual components. These findings support the view of disclosure theory where
companies disclosing more information such as ESG factors are valued higher. We also find that the
benefits received by companies disclosing ESG are stronger in Common Law countries. The results
are robust to several alternative tests.
Keywords: Value relevance, non-financial information, ESG.
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1. INTRODUCTION
In recent years there has been increasing focus in capital markets on Environmental, Social and
Governance disclosure (ESG) in assessment of corporate opportunities and risks. It has been argued
that financial information has limited usefulness to investors as it provides only historical-oriented
information, which is considered insufficient to assess the company's ability to generate future profits.
This study is therefore motivated to explore the extent to which Non-financial information, such as
that provided by ESG disclosure, can usefully supplement traditional sources of information.
The role of ESG information in business has undergone many changes in the course of history. Eccles
and Viviers (2011), for example, report that ESG factors have been discussed in the academic
literature for more than 35 years. However, it is apparent that the role of ESG has changed over time.
In past decades, some economists claimed that businesses have no social responsibilities and therefore
should not expend company resources engaging in socially responsible activities (Friedman, 2007).
More recently the pendulum has swung in the opposite position, actively encouraged by public
expectations and regulatory pressure, to the point at which sustainability issues have assumed a
central role in the management of business (Panwar, Rinne, Hansen, & Juslin, 2006). The area of
concern has also enlarged somewhat. To remain acceptable to wider society today, it appears that
companies must satisfy an array of interests. This means that, in carrying out their activities, firms
must desist from activities such as damaging the environment, harming the health of consumers, or
violating the rights of employees, and they should have concern for sustainability and their overall
contribution to social welfare.
Despite this ideal view of the business-society relationship, the extent to which markets actually
favourably recognise companies that operate in this manner remains an open question. Research to
date on the actual relevance of ESG information to the markets is still in the early stage of
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investigation as research on the effects of ESG disclosure on the market value of companies has
largely been limited to developed countries and regions such as the European Union (
). Comparative international studies have also been confined to specific
industries, such as the financial sector (Cheung & Mak, 2010), or addressed only specific ESG
components such as corporate governance (Ammann, Oesch, & Schmid, 2011). Consequently, the
effects of ESG disclosure on the market value of companies requires further research.
This study addresses the gap by examining the value relevance of ESG factors relative to the future
financial performance of companies (CSR Europe, 2003; Maier, 2007). Specifically, the present study
addresses this matter by assessing the effects of disclosure of ESG and its individual components on
the stock price of companies.
Using a large sample of non-financial companies listed in 41 countries during the period 2008 2012,
we investigate the value relevance of ESG disclosure worldwide. Bloomberg disclosure scores are
used as a proxy for ESG disclosure and a modified Ohlson (1995) model is employed to measure
value relevance. We find strong evidence that ESG and its individual components have positive and
significant associations with market value. The results are robust to several alternative tests. These
findings support the view of disclosure theory that companies disclosing ESG are valued higher
(Healy & Palepu, 2001; Verrecchia, 2001). We also find that the impact is stronger in Common Law
countries.
This paper contributes to our understanding of the benefits of ESG disclosure in three areas. First we
extend previous studies in terms of country coverage. Previous studies such as Balatbat, Siew, &
Carmichael (2012) have focused on single countries, while previous international studies such as
) have only focused on the European region. Second, to the best
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of our knowledge, our study is the first to investigate the issues using the ESG disclosure scores
provided by Bloomberg. This is important as the Bloomberg data is comprehensive and standardised
as it is collected using a consistent methodology across national boundaries. Third, we control for
common and code law institutional factors, which reduces the potential for misspecification errors.
The rest of this paper is organized as follows. Section two presents the theoretical framework
concerning the value relevance of the disclosure of ESG and its individual components. Section three
describes the models, the data and the variables employed. Section four presents the empirical results
and the analysis of the results with several robustness checks. Section five concludes and outlines the
contributions, and limitations of the study.
2. THEORETICAL FRAMEWORK
This section reviews the existing literature and develops the hypotheses for the study. Four types of
disclosure affecting market values are of particular interest, namely environmental factors, social
factors, governance factors and the aggregate of these factors (ESG). Each of these sets of factors will
be considered in turn; but first, it is necessary to examine briefly what indicators are considered as
ESG factors.
The term ESG was first used by the United Nations Principles of Responsible Investment and has
since became popular among investment communities associated with socially responsible
investment (Eccles & Viviers, 2011; ). Other terms have enjoyed
(Eccles & Viviers, 2011) but many researchers have increasingly use ESG because it
refers to a broader set of corporate activities (Boston College Centre for Corporate Citizenship, 2009;
Derwall, 2007).
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In its widest sense, ESG is a generic term for a subset of non-financial indicators used by capital
markets to evaluate corporate sustainability. In effect, ESG provides the additional information
employed by investors to better assess the risks and opportunities relating to corporate social
responsibility and behaviour impacting on performance (Bassen & Kovács, 2008). In essence, ESG
is part of those responsible corporate practices that aim to deliver higher risk-adjusted financial
returns (Eccles & Viviers, 2011).
The importance of ESG for capital markets is gaining recognition. Major international bodies1 have
recently been involved in a global dialog resulting in five stock exchanges and a large number of
global investors declaring support for ESG practices (White, 2012). Capital market recognition of
ESG has also motivated several information services (Such as Bloomberg, Thomson Reuters/Asset4,
EIRIS and others) to provide ESG ratings.
ESG is composed of three factors which are combinations of non-financial indicators that are used to
and governance. Sustainable development is expected to balance the three elements so as to ensure
that meeting the needs of the present is not accompanied by sacrificing the ability of future
generations to meet their needs.
Embracing ESG policies entails both costs and benefits for the companies affected. In terms of
complying with the ESG agenda, companies are restricted with regard to certain activities. They are
discouraged, for instance, from doing business with companies that abuse workers or employ children.
1The international bodies include: Global Compact; the United Nations Conference on Trade and Development (UNCTAD); United Nation Principles for Responsible Investment (UN-PRI); and the UN Environment Program Finance Initiative UNEP FI).
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Companies may incur additional costs to maintain green operations or to invest in energy-efficient
machinery. On the other hand, companies may also benefit from compliance by creating a good
reputation and brand loyalties that help ensure long-term survival. On balance, it is increasingly
thought that favourable ESG factors contribute to financial performance, and for this reason ESG
factors are being progressively integrated into the process of investment analysis and decision-making
(UNEP, 2007).
Environmental factors are perhaps the most researched of the three elements of ESG and the most
consistent in respect of the results obtained. This is not surprising, for the steady deterioration of some
environmental factors has put increasing pressure on companies by regulation, peers, and society as
a whole to adopt sustainable operations. However, while the majority of studies on the effects of
environmental factors on market value of companies have reported a positive relationship, it is
important to recognise that some studies have reported the relationship to be either neutral or negative.
Hassel, Nilsson, & Nyquist (2005) classify this type of research into two schools. First the competitive
advantage school, which argues that an environmental effort improves
because of the increased competitive advantage. Second, the cost-concerned school, which argues
closure of environmental information lowers the market value because of
increased costs depressing profit.
The first of these schools is generally founded on the perceived downstream effects of the good
reputation created by transparency and responsiveness to public demands. Environmental disclosure
is considered to increase transparency which in turn creates a positive profile for the company
(Azzone, Manzini, & Noci, 1998)
competitiveness due to the stimulus it provides for product innovation (Brännlund & Lundgren, 2009;
Porter & Linde, 1995). Environmental disclosure also encourages the recognition of company assets
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and liabilities (Barth & McNichols, 1994); and finally, improved environmental performance (as
revealed by environmental disclosure) leads to the perception that the company is complying with
environmental regulation and anticipating future obligations (Porter & Linde, 1995). Thus
environmental factors are value relevant for investors.
The second of the schools noted above, concerning the possibility of a negative relationship between
environmental efforts and market value, appears to have rather less support in the literature. Brammer,
Brooks & Pavelin (2012) have suggested environmental efforts increase costs and are therefore
destructive to shareholder value which echoes the conclusions of the earlier study by Hughes (2000)
who found a negative relationship between firm value and SO2 emissions.
Some doubt however, has arisen concerning the exact nature of the differences between the two
schools of thought. It has been argued, for instance, that the divergence of results arises not so much
from empirical differences as from differences in the methodology used. For instance, UNEP (2007)
dimension and the length of the period over which the study was conducted. More specifically, UNEP
ed with those from the similar but somewhat
longer study of Derwall, Geunster, Bauer, & Koedijk (2005) which indicated environmentally
efficient companies had superior shareholder returns. Furthermore, it has also been suggested by
Cheung & Mak (2010) that the period over which the study has been conducted may affect the results.
Finally it is apparent that some empirical measures are subject to significant measurement error (Boyd,
Gove, & Hitt, 1999). Examples include NFI measures of customer satisfaction, brand and human
capital measures that rely on informal survey data, subjective conceptual frameworks, and other
imprecise measures such as number of employees (Wyatt, 2008). The inconclusive findings may also
have been the result of different disclosure instruments measuring different types of disclosure.
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Overall then, and despite the existence of empirical findings to the contrary, it would appear that the
literature supports the existence of a positive relationship between environmental disclosure and the
market value of firms. The first hypothesis therefore is:
H1: Environmental disclosure is positively associated with company market value.
Stakeholder theory supports a positive relationship between social and financial performance
(Orlitzky, Schmidt, & Rynes, 2003). Companies that have sustainable relationships with a number of
stakeholders, such as employees, customers, suppliers, and investors will increase their
competitiveness. For example, motivated employees can create value by improving productivity, and
adopting a customer oriented approach. Hillman and Keim (2001) state that good relationships with
key stakeholders raise intangible value, which contributes to market returns.
But the overall impact of the relationship with the stakeholders on stock returns varies. On the one
hand, good relationships with employees increase productivity and job satisfaction. In addition, good
relationships with the community strengthen a
other hand, research findings suggest that increased public relation results in poor investment returns
(Brammer, Brooks, & Pavelin, 2006). This is partly because the impact of social performance is
highly dependent on the type of business enterprise (Brammer et al., 2006).
Edmans (2011) suggests that although there is a positive association between employee satisfaction
and stock returns in the long run, the stock market still does not fully value intangibles and
consequently only selected ESG factors improve stock returns . However, Bauer, Otten, and Rad
(2006) find that although there is no significant difference between the risk adjusted returns of ethical
and conventional funds, there are differences across periods of time. Between 1992 and 1996, the
conventional funds appear to outperform ethical funds, but during the period from 1997 to 2003, the
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two investment approaches show similar performance. The authors concluded that a learning period
was required before the market was able to truly appreciate ethical screening. This could be another
explanation for the medium to long-term impact of ESG factors on firm performance, and thus market
price of firms, reported in other studies (Balatbat et al., 2012; CSR Europe, 2003; Maier, 2007).
In summary, research evidence from previous studies on the effect of social disclosure and financial
performance has been mixed. However, increasing awareness among capital market investors of the
importance of social factors as an indication of potential future risk and return has prompted greater
attention to these factors when making investment decisions. This study predicts, therefore, that
market participants reactions to current and future social performance will be reflected in changes to
the stock price. Thus the following hypothesis is proposed.
H2: Social disclosure is positively associated with company market value.
Corporate governance has received much attention due to major financial scandals such as Enron and
Lehman Brothers and has led to demands in many countries for reform of corporate governance
systems. In relation to the demands for improved corporate governance, much research has been
conducted to evaluate corporate governance in many organizations. Consistent with stakeholder
theory, the literature linking governance measures to firm value suggests that good corporate
governance is associated with higher market value (Bebchuk & Cohen, 2005; Brown & Caylor, 2006;
Cremers & Nair, 2005; Gompers, Ishii, & Metrick, 2003).
A positive association can also be supported by basic reasoning. For example, Gompers, et al. (2003)
reported that companies with stronger shareholder rights (as a form of good corporate governance)
had higher value, due to higher profits and sales growth, but lower capital expenditures. Similarly,
Maher and Andersson (2000) stated that good governance reduces agency conflicts between
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managers and shareholders. Quality management creates productivity enhances the creativity of the
company, and produces innovative products. Good governance also creates efficiency because it can
suppress waste in the production process and reduce potential conflicts with other stakeholders, thus
avoiding the cost of conflict. All of this ultimately reduces operational costs, thus increasing profits,
and enhancing shareholder value.
Researchers have found that both internal and external governance has a positive relat ionship with
the value of the company (Bebchuk & Cohen, 2005; Brown & Caylor, 2006). However, Cremers &
Nair, (2005) and Brown and Caylor (2006) have reported that not all measures of good governance
are associated with firm value. This applies especially to factors that have not received extensive
determines whether investors consider these factors as a basis for stock valuation.
Corporate governance is a broad and diverse concept. It encapsulates all the mechanisms that
determine the procedure for determining the direction of the firm (Schmidt, 2003). A broad definition
also indicates a lack of clarity of the concept (Webb, Pollard, & Ridley, 2006). Because of the abstract
nature, corporate governance is also not easily measured, or compared between companies. It is tied
to specific organizational contexts as it also involves discretion in selecting policies deemed most
appropriate for specific circumstances. Therefore, despite the consensus among financial
communities of the strong benefits of good corporate governance, the findings of previous studies
have been inconsistent. Some studies suggests a weak to neutral relationship between governance
attributes and firm market value (Bauer, Guenster, & Otten, 2004).
However, the findings of a weak relationship may also be attributed to small sample size; the
measurement metrics used, or possibly the relatively minor importance of the corporate governance
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factor studied compared to other factors in the industry. As suggested by Brown and Caylor (2009),
effective corporate governance measures require broad measures including both internal and external
governance mechanisms to enhance the robustness of findings.
Taken together, the strong support for the positive association between good governance and market
value and the limitations of previous studies, in both the measurement model and the choice of
variables, this study predicts a positive relationship between governance and market value. This leads
to the next hypothesis:
H3: Governance disclosure is positively associated with company market value.
Stakeholder theory suggests that stakeholder expectations play an important part in setting financial
goals. Consequently, the financial goals of a company reflect the combined expectations of all its
stakeholders. Stakeholder expectations may differ from one to another, creating the potential for
conflicts of interest. Maintaining a good balance, therefore, between stakeholder interests is essential
to achieving company financial goals (Balatbat et al., 2012; Donaldson & Preston, 1995). Companies
with ESG policies may be more likely to have superior management and more capable of running a
successful business (Alexander & Buchholz, 1978).
ESG disclosure increases company transparency giving the company a positive profile (Azzone et al.,
1998). The resulting environmental and social engagement increases profits by reducing the cost of
conflict with the community, improving relationships with regulators, increasing employee
productivity and increasing efficiency due to reductions in the amount of waste (Heal, 2005). There
is also evidence that good corporate governance (as manifested by ESG disclosure) reduces conflict
of interest between managers and shareholders, and results in improvements to the quality of
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management, efficiency, and productivity, and ultimately, the value of the company (Maher &
Andersson, 2000).
Furthermore, in the real world, there are a variety of internal and external influences that determine
the orientation of different managerial approaches. Deegan, et al., (2002), suggest that each
organization is part of the social system that affects or is affected by the environment. Therefore, the
question of whether all firms will be affected equally by good behaviours in meeting stakeholder
expectations is yet to be answered, especially for companies operating under different institutional
influences such as in a global market. Mahmoudian, Nazari, and Herremans (2012) show that not all
organizations are affected by organizational pressure in the same way. For example, larger
organizations tend to receive higher institutional pressure from the diverse stakeholders, leading to
better compliance with expectations. This is explained by institutional theory that proposes that there
are certain organizational aspects governed by other institutions, which means those aspects are
beyond the control of the members of the organization.
In addition, the two investor perception surveys on ESG reviewed above, have reported that 80 to 90%
of investors believe ESG indicators have a financial impact on the value of the company in the
medium to long term (CSR Europe, 2003; Maier, 2007). Such findings suggest the financial
community favours companies with ESG policies. Similar sentiments are exposed in the United
Nations Principles of Responsible Investment (U
and corporate governance (ESG) issues can affect the performance of investment portfolios (to
(In Balatbat et
al., 2012, p. 2). This illustrates the tendency of the mainstream financial community to include ESG
factors when evaluating the market value of the company.
So the final hypothesis, therefore, is:
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H4: ESG disclosure is positively associated with company market value.
3. RESEARCH DESIGN
3.1. Sample and data
The sample for this study comprises non-financial companies listed on worldwide stock exchanges
during the five-year period 2008-2012. This particular period has been chosen because
comprehensive Bloomberg ESG Disclosure Scores have only been available from 2008 - prior to that,
data was limited in terms of both country and sector coverage.
Samples companies for this study are selected according to the availability of
Disclosure scores. Bloomberg provides disclosure scores for voluntary environmental, social, and
governance (ESG) disclosure ranges from 0.1, to 100, and are tailored according to country, industry,
sector and other criteria; making it possible to compare scores for companies selected according to
different types of criteria. The selection of the companies for this study began by screening the
countries. Only countries with at least five companies consistently disclosing ESG over the study
were included in the sample. Financial companies were excluded from the sample because of their
different nature and regulatory requirements with regard to ESG issues (Goodwin & Ahmed, 2006;
Guenster, 2012; Xiao-Hong & Yu-Hong, 2008). The final sample of company year observations
meeting the criteria for selection covered 41 countries.
This study employs a modified Ohlson (1995) price model that expresses the market value of equity
as a function of book value of equity, accounting earnings and other information. Hence we use price
per share at the end of financial period as the dependent variable of this study. We use Earnings per
share (EPS) as the measure of accounting earnings. The other information is the Bloomberg
Environmental, Social and Governance scores.
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All the financial and the non-financial data were collected from the Bloomberg database. The
Bloomberg ESG disclosure scores reflect the relevant disclosure data available in the public domain.
Several other sources of such data are available and some have been used in previous studies including:
Thomson Reuters (Ioannou & Serafeim, 2010b), Domini Social Index (Evans & Peiris, 2010),
Corporate Monitor (CAER or EIRIS) (Balatbat et al., 2012). A number of studies have already
employed the Bloomberg ESG Disclosure Scores for different research problems (Cheung & Mak,
2010; Eccles et al., 2011; ; Mahmoudian et al., 2012; Wimmer,
2012). To date however, no other international study has investigated value relevance using the
Bloomberg ESG Disclosure scores.
Bloomberg provides a much richer dataset than the sets used in earlier studies. It comprises 247 non-
financial metrics that break down into five groups: Carbon Disclosure Project (CDP), Environmental
metrics, Social metrics, Governance metrics and ESG Disclosure metrics. The last four metrics
measure the degree of transparency of the overall ESG metrics and its components (Eccles et al.,
2011). Bloomberg screening of the ESG Disclosure Score is based on the GRI framework. This is
reflected in the survey result of Levy, Duca, & Alma (2012) showing that 70% of GRI compliant
companies have a Bloomberg ESG Disclosure Score of over 50 and the fact that 79% of the
companies that scored below 50 are not GRI compliant. Except Portugal, all other sample countries
in this study are GRI framework adopters and all of the sample countries except the US have signed
the Kyoto Protocol agreement.
We also use two other firm level variables in addition to the main variables included in the Ohlson
(1995) model. This is to control for variables that have been identified in previous value relevance
studies as impacting on company value. These variables
represents a market based measure of profitability. Profitability has been identified as a driver of price
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and therefore it is included in our model. Applied beta represents relevant risk factors that adversely
impact price. Companies that successfully utilise a degree of leverage may also have higher potential
growth, which is preferred by some investors. Thus companies with high risk may also signal
potential growth. Accordingly, we include applied beta as a control variable in our models.
A number of other cross-country value relevance studies have suggested that country differences have
persisted even after accounting harmonization (Joos & Lang, 1994), due to, for example, their capital
market size (Veith & Werner, 20102) or legal origins (Devalle, Onali, & Magarini, 2010; Hung, 2000;
Veith & Werner, 2010). Wanderley et al. (2008), in fact, found that country of origin had a stronger
influence than industry sector. The above studies suggest that value relevance is influenced by
institutional factors such as political, cultural, legislation and socioeconomic factors. Therefore this
study, include the common law and code law distinction to represent the legal institutional factors
that are used to classify countries (La Porta et. al., 1998). We code countries adopting common law
as 1 and otherwise 0. We also include year and industry dummies in our model to control for year
and industry effects.
3.2. Model Specification
The objective of this study is to investigate the value relevance of ESG disclosure. Two tests are
commonly used in value relevance research which is based on return or price models (Barth, 2000;
Barth, Beaver, & Landsman, 2001; Ota, 2003). This study uses price models, where stock prices are
2 Thirteen firms listed in Canada, Denmark, France, Germany, Ireland, Japan, the Netherlands, Norway, Singapore, Sweden, Switzerland, the United Kingdom and the United States. These countries represent a fair balance of large and small as well as of common and code law countries.
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regressed on book value per share and earnings per share. There has been some debate as to which is
the better model (as outlined in Kothari & Zimmerman, 1995), but several points support the decision
to use the price model in this study. First, the model has been widely adopted by researchers in the
prior value relevance studies (e.g. Amir & Lev, 1996; Bao & Chow, 1999; Hirschey, Richardson, &
Scholz, 2001; Hughes, 2000; Lo & Lys, 2000; Sami & Zhou, 2004). Second, previous studied that
have investigated value relevance using both models, obtained similar results (Bao & Chow, 1999;
Sami & Zhou, 2004). Third, unlike the return model, there is empirical evidence to suggest that the
estimated slope coefficient of the variable tested in the price model is unbiased, which means that
value relevance only persists if there is new information to affect stock returns (Chen, Chen, & Su,
2001; Kothari & Zimmerman, 1995).
Four models are used in this study. The first three models are used to investigate the relationship of
the individual components of environmental, social and governance factors to market value. In the
fourth model, the variable of interest is the aggregate ESG measure. The individual models are listed
below:
Pxit 0 + 1Envit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed .. 1)
Pxit 0 + 1Socit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit = 0 + 1Govit + 2BVit + 3 EPSit + 4Tobins_Qit + 5Betait + 6Commom_Lawit + Year fixed
.. .. (3) Pxit = 0 + 1ESGit + 2BVit + 3 EPSit + 4Tobins_Qit + 5Betait + 6Commom_Lawit + Year fixed
4)
Where, Pxit = Price of a share of firm i, at date t
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Envit = Environment disclosure of firm i at date t Socit = Social disclosure of firm i at date t Govit = Governance disclosure of firm i at date t ESGit = ESG disclosure score of firm i at date t BVit = Book value per share of firm i at time date t EPSit = Earnings per share of firm i at date t Tobins_Qit = i at date t Betait = Bloomberg applied of firm i at date t Commom_Lawit = a dummy variable takes the value 1 for common law country and 0
otherwise Detailed definitions of all of the variables are presented in Table 1.
(Insert Table 1 here)
4. RESULTS
4.1. Descriptive statistics
Table 2 provide descriptive statistics of the main variable in this study. The table shows that
Environmental scores ranges from .78 to 85.27 with mean value is 22.31; Social scores ranges from
3.13 to 94.74 with mean value is 22.57; Governance scores ranges from 3.57 to 85.71 with mean
value is 45.95; while the aggregate ESG scores ranges from 3.31 to 79.34 with mean value is 20.72.
The data indicates that on average the disclosure level of ESG and its individual components is quite
low within our sample companies.
(Insert Table 2 here)
Table 3 presents the Pearson correlations matrix. The table shows that among the ESG variables, the
governance factor has the strongest positive correlation with price (r=0.2926, p<0.001), followed by
the environment factor (r=0.22.58, p<0.001), ESG factor (r=0.2790, p<0.001) and finally by the
weakest variable, social factor (r=0.2125, p<0.001).
(Insert Table 3 here)
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4.2.Main Results
Table 4 shows the results of the basic regressions. The coefficients of ESG and its component are
positive and significant (t-stat of Env = 14.77, p<0.001; t-stat of Soc = 5.04, p<0.001; t-stat of Gov =
19.36, p<0.001; t-stat of ESG = 18.29, p<0.001) and the regressions all have a high adjusted R2. Of
the test variables the governance component has the strongest t values (19.36) and social (5.04) has
the lowest. Similarly, in all regressions the book value and earnings variables have the expected sign
and are significant. The significant positive coefficient on applied beta and common law supports the
expectation that ESG disclosures are more relevant if a company has a higher business risk and if the
company environment characterised by the common law variable. The results thus
strongly support all of hypotheses 1 to 4.
(Insert Table 4 here)
Table 5 to 8 reports the results of the various robustness tests. Table 5 shows the results with the year
2008 excluded from the data set. Table 6 excludes both the years 2008 and 2009 (the GFC years).
Table 7 excludes the 2012 year. Table 8 reports the results of excluding observations from countries
with less than 5 observations in any year (resulting in the exclusion of 12 countries, mainly from
Eastern Europe and East Asia). For the key variables, ESG and its components and book value and
earnings, the results remained qualitatively similar to the full sample results.
(Insert Table 5, 6, 7 & 8)
5. CONCLUSION AND FUTURE RESEARCH
In this study, we use the modified Ohlson (1995) model to investigate the relationship between ESG
disclosure and market value. We source our ESG and financial data from the Bloomberg database
and the legal data from the World Bank. We find that both ESG and the individual components have
19
a positive significant relationship with market value. Our results are robust and consistent across a
number of alternative tests.
Despite the earlier views on ESG factors and the mixed results in the literature, our results suggest
that in recent years, investors have become more appreciative of ESG information. Our results also
suggest that the most significant effect is on common law countries. Thus, countries that have the
strongest institutions tend to benefit the most from regard for ESG factors..
Although our results are strong and consistent, they should be interpreted with some caution. The
variables may be subject to measurement error. For example, many companies are multinational and
therefore their operations do not reflect national boundaries in respect of the legal tradition.
Furthermore, our results are not tested on alternative data provided by other suppliers of ESG ranks.
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25
Table 1: Variable definition
Variable Measure Description of Variable PX Price per share Last price for the security as provided by the exchange.
Env Environmental
disclosure score Proprietary Bloomberg score based on the extent of a company's environmental disclosure as part of Environmental, Social and Governance (ESG) data. The score ranges from 0.1 for companies that discloses minimum amount of ESG data to 100 for those that disclose every data point collected by Bloomberg. Each data point is weighted in terms of importance, with data such as Greenhouse Gas Emissions carrying greater weight than other disclosures.
Soc Social disclosure score
Proprietary Bloomberg score based on the extent of a company's social disclosure as part of Environmental, Social and Governance (ESG) data. The score ranges from 0.1 for companies that discloses minimum amount of social data to 100 for those that disclose every data point collected by Bloomberg. Each data point is weighted in terms of importance, with workforce data carrying greater weight than other disclosures. The score is also tailored to different industry. In this way, each company is only evaluated in terms of the data that is relevant to its industry sector.
Gov Governance disclosure score
Proprietary Bloomberg score based on the extent of a company's governance disclosure as part of Environmental, Social and Governance (ESG) data. The score ranges from 0.1 for companies that disclose minimum amount of governance data to 100 for those that disclose every data point collected by Bloomberg. Each data point is weighted in terms of importance, with board of data carrying greater weight than other disclosures. The score is also tailored to different industry sectors. In this way, each company is only evaluated in terms of the data that is relevant to its industry sector.
ESG Environmental, social and governance disclosure score
Proprietary Bloomberg score based on the extent of a company's Environmental, Social, and Governance (ESG) disclosure. The score ranges from 0.1 for companies that disclose a minimum amount of ESG data to 100 for those that disclose every data point collected by Bloomberg. Each data point is weighted in terms of importance, with data such as Greenhouse Gas Emissions carrying greater weight than other disclosures. The score is also tailored to different industry sectors. In this way, each company is only evaluated in terms of the data that is relevant to its industry sector.
BV Book value per share
Total Common Equity / Number of Shares Outstanding.
26
ESP Earnings per share
Net Income Available to Common Shareholders divided by the Basic Weighted Average Shares outstanding.
Tobins_Q Tobins Q (Market Cap + Liabilities + Preferred Equity + Minority Interest) / Total Assets
Beta Applied Beta Percentage change in the price of an equity given a one percent change in its benchmark index.
Common_Law
Common law dummy
A dummy to represent country clusters using Common law (1) and Code law (0)
27
Tabl
e 2:
Des
crip
tive
stat
istic
s
Vari
able
(s)
PX
Env
Soc
G
ov
ESG
B
V
EP
S T
obin
s_Q
Ap
plie
d Be
ta
Com
mon
_Law
Mea
n 12
.65
22.9
8 26
.25
47.4
4 29
.41
8.02
0.
74
1.39
0.
95
0.39
Med
ian
5.67
17
.83
22.8
1 46
.43
26.8
6 4.
64
0.29
1.
15
0.94
0
SD
16.4
7 15
.99
16.2
4 9.
61
12.1
4 9.
30
1.30
0.
72
0.29
0.
49
Min
imum
0.
02
0.78
3.
51
3.57
3.
31
0.01
-4
.9
0.34
-0
.8
0
Max
imum
10
7.35
85
.27
94.7
4 85
.71
79.3
4 64
.83
8.58
5.
83
2.66
1
Not
e: V
aria
ble
defin
ition
s of a
ll of
the
varia
bles
are
pre
sent
ed in
Tab
le 1
.
28
Tabl
e: 3
Cor
rela
tion
mat
rix
V
aria
ble(
s)
P X
E
nv
So
c
Gov
ESG
BV
E
PS
T
obin
s_Q
Ap
plie
d Be
ta
Com
mon
_Law
P X
1
Env
0.22
58
(0.0
00)
1
Soc
0.21
25
(0.0
00)
0.56
77
(0.0
00)
1
Gov
0.
2926
(0
.000
) 0.
2805
(0
.000
) 0.
4472
(0
.000
) 1
ESG
0.
2790
(0
.000
) 0.
9320
(0
.000
) 0.
7953
(0
.000
) 0.
5208
(0
.000
) 1
BV
0.76
23
(0.0
00)
0.25
66
(0.0
00)
0.41
23
(0.0
00)
0.14
47
(0.0
00)
0.25
66
(0.0
00)
1
EPS
0.78
73
(0.0
00)
0.20
93
(0.0
00)
0.18
32
(0.0
00)
0.24
73
(0.0
00)
0.20
93
(0.0
00)
0.62
39
(0.0
00)
1
Tobi
ns_Q
0.
2228
(0
.000
) -0
.021
0 (0
.023
2)
0.10
44
(0.0
00)
0.18
49
(0.0
00)
-0.0
210
(0.0
232)
-0
.173
9 (0
.000
) 0.
1511
(0
.000
) 1
Appl
ied
Beta
-0
.007
2 (0
.438
5)
0.04
61
(0.0
00)
0.00
04
(0.9
621)
0.
1019
(0
.000
) 0.
0461
(0
.000
) 0.
0076
(0
.410
3)
-0.0
335
(0.0
003)
-0
.065
7 (0
.000
) 1
Com
mon
_Law
0.
0622
(0
.000
) -0
.181
1 (0
.000
) -0
.150
0 (0
.000
0)
0.28
03
(0.0
00)
-0.1
811
(0.0
00)
-0.1
445
(0.0
00)
0.08
87
(0.0
00)
0.16
41
(0.0
00)
-0.0
131
(0.1
574)
1
Not
e: V
aria
ble
defin
ition
s of a
ll of
the
varia
bles
are
pre
sent
ed in
Tab
le 1
.
29
Table 4: Regression analysis
Pxit = 0 + 1Envit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year effects + Industry
Pxit = 0 + 1Socit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year effects +Industry
Pxit 0 + 1Govit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year effects + Industry
Pxit 0 + 1ESGit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year effects + Industry
Variable(s) Model 1 Model 2 Model 3 Model 4
Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat.
Env 0.064154 (0.000)
14.77
Soc 0.020625 (0.000)
5.04
Gov 0.116095 (0.000)
19.36
ESG 0.076397 (0.000)
18.29
BV 0.968178 (0.000)
65.95 1.06929 (0.000)
76.60 0.995387 (0.000)
87.81 1.006693 (0.000)
89.65
EPS 4.95323 (0.000)
40.54 4.530087 (0.000)
41.04 4.569497 (0.000)
50.82 4.495366 (0.000)
50.10
Tobins_Q 5.798423 (0.000)
41.46 6.024855 (0.000)
44.94 4.087038 (0.000)
50.49 4.204005 (0.000)
52.40
Beta 0.774178 (0.000)
4.02 1.254225 (0.000)
6.44 1.020449 (0.000)
7.11 1.32178 (0.000)
9.25
Common_Law 2.630045 (0.000)
20.07 3.052548 (0.000)
23.25 2.964053 (0.000)
29.94 3.955117 (0.000)
40.07
Intercept -10.88035 (0.000)
-37.08 -10.10318 (0.000)
-32.65 -12.62397 (0.000)
-43.90 -8.9615 (0.000)
-39.49
Year effects Yes Yes Yes Yes Industry effects Yes Yes Yes Yes Adj.R2 0.8243 0.7922 0.7690 0.7689 N 13,616 16,634 25,126 25,179
Note: Coefficient p-values are two-tail and based on asymptotic Z-statistic robust to heteroskedasticity. For clarity in presentation the coefficients on year and industry dummies have not been reported.
Variable definitions of all of the variables are presented in Table 1.
30
Additional analysis
Table 5: Excluding 2008 financial year
Pxit 0 + 1Envit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit 0 + 1Socit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit 0 + 1Govit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit 0 + 1ESGit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Variable(s) Model 1 Model 2 Model 3 Model 4 Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat.
Env 0.0641604 (0.000)
12.36
Soc 0.0262833 (0.000)
5.93
Gov 0.1260817 (0.000)
18.58
ESG 0.0796129 (0.000)
17.56
BV 0.9768471 (0.000)
55.64 1.044871 (0.000)
68.16 0.9949881 (0.000)
81.14 1.003333 (0.000)
82.02
EPS 5.252191 (0.000)
34.91 4.914148 (0.000)
38.57 4.70241 (0.000)
46.81 4.684208 (0.000)
46.51
Tobins_Q 4.78739 (0.000)
32.29 4.994105 (0.000)
37.23 3.956771 (0.000)
46.97 4.118957 (0.000)
48.91
Beta 1.233446 (0.000)
5.24 1.506854 (0.000)
7.05 1.153972 (0.000)
7.23 1.437636 (0.000)
9.07
Common-Law 2.957052 (0.000)
19.03 3.462071 (0.000)
24.06 3.244348 (0.000)
30.19 4.218815 (0.000)
38.97
Intercept -8.761952 (0.000)
-24.19 -8.865215 (0.000)
-27.15
-12.09338 (0.000)
0.324603 -9.257741 (0.000)
-38.28
Year effects Yes Yes Yes Yes Yes Industry effects
Yes Yes Yes Yes Yes
Adj.R2 0.8138 0.7936 0.7722 0.7720 N 11306 13654 21207 21229
Note: Coefficient p-values are two-tail and based on asymptotic Z-statistic robust to heteroskedasticity. For clarity in presentation the coefficients on year and industry dummies have not been reported.
Variable definitions of all of the variables are presented in Table 1.
31
Table 6 Excluding both 2008 and 2009 financial years
Pxit 0 + 1Envit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit 0 + 1Socit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit 0 + 1Govit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed effe Pxit 0 + 1ESGit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Variable(s) Model 1 Model 2 Model 3 Model 4 Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat.
Env .0568872 (0.000)
9.70
Soc .0182626 (0.000)
3.56
Gov .1232448 (0.000)
15.57
ESG 0706343 (0.000)
13.73
BV .9037559 (0.000)
43.56 .9855265 (0.000)
54.53 .9504578 (0.000)
67.80 .959312 (0.000)
68.48
EPS 5.825471 (0.000)
32.35 5.397549 (0.000)
35.61 5.047585 (0.000)
43.61 5.033348 (0.000)
43.32
Tobins_Q 4.690147 (0.000)
27.59 4.916236 (0.000)
32.16 3.968917 (0.000)
42.03 4.095341 (0.000)
43.30
Beta .95677 (0.000)
3.55 1.188506 (0.000)
4.97 .949247 (0.000)
5.37 1.209523 (0.000)
6.89
Common_Law 2.837789 (0.000)
16.02 3.520316 (0.000)
21.38 3.519678 (0.000)
29.10 4.359192 (0.000)
35.54
Intercept -8.218811 (0.000)
-19.80 -8.83722 (0.000)
-24.81 -12.55797 (0.000)
-31.81 -9.163499 (0.000)
33.98
Year effects Yes Yes Yes Yes Industry effects Yes Yes Yes Yes Adj.R2 0.8219 0.8010 0.7766 0.7760 N 8,515 10,385 16,688 16,688
Note: Coefficient p-values are two-tail and based on asymptotic Z-statistic robust to heteroskedasticity. For clarity in presentation the coefficients on year and industry dummies have not been reported.
Variable definitions of all of the variables are presented in Table 1.
32
Table 7 Excluding 2012 financial year
Pxit 0 + 1Envit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit 0 + 1Socit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit 0 + 1Govit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Pxit 0 + 1ESGit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year fixed
Variable(s) Model 1 Model 2 Model 3 Model 4 Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat.
Env 0.0645475 (0.000)
13.35
Soc 0.020599 (0.000)
4.66
Gov 0.1141083 (0.000)
17.57
ESG 0.0768364 (0.000)
16.79
BV 0.9997477 (0.000)
62.49 1.085318 (0.000)
71.55 1.018173 (0.000)
81.45 1.029351 (0.000)
83.32
EPS 4.711283 (0.000)
36.60 4.305068 (0.000)
36.89 4.386276 (0.000)
45.24 4.308179 (0.000)
83.72
Tobins_Q 5.873143 (0.000)
38.34 5.994896 (0.000)
41.40 .3.921908 (0.000)
45.58 4.05199 (0.000)
47.52
Beta 0.7657594 (0.000)
3.61 1.256426 (0.000)
5.80 0.947256 (0.000)
5.90 1.262293 (0.000)
7.89
Common_Law 2.622087 (0.000)
18.04 2.863028 (0.000)
19.70 2.728292 (0.000)
25.03 3.739288 (0.000)
34.43
Intercept -9.44974 (0.000)
-28.53 -9.460804 (0.000)
-28.68 -12.10815 (0.000)
-39.45 -9.731465 (0.000)
-41.12
Year effects Yes Yes Yes Yes Industry effects Yes Yes Yes Yes Adj.R2 0.8218 0.7879 0.7676 0.7681 N 11,429 13,819 20,453 20,493
Note: Coefficient p-values are two-tail and based on asymptotic Z-statistic robust to heteroskedasticity. For clarity in presentation the coefficients on year and industry dummies have not been reported.
Variable definitions of all of the variables are presented in Table 1.
33
Table 8 Excluding countries with small number of observations Pxit 0+ 1Envit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year effects + Industry
Pxit 0+ 1Socit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year effects + Industry
Pxit 0+ 1Govit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year effects + Industry
Pxit 0+ 1ESGit 2BVit 3 EPSit 4Tobins_Qit 5Betait 6Commom_Lawit + Year effects + Industry
Variable(s) Model 1 Model 2 Model 3 Model 4 Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat. Estimates (p value)
t-stat.
Env 0.0675473 (0.000)
15.20
Soc 0.0214598 (0.000)
5.09
Gov 0.12399 (0.000)
20.04
ESG 0.078946 (0.000)
18.49
BV 0.9742199 (0.000)
65.29 1.078589 (0.000)
76.46 1.001975 (0.000)
87.73 1.012835 (0.000)
89.49
EPS 4.87302 (0.000)
39.31 4.449838 (0.000)
39.91 4.494754 (0.000)
49.73 4.430789 (0.000)
49.10
Tobins_Q 5.859427 (0.000)
39.31 6.102443 (0.000)
44.87 4.120378 (0.000)
50.18 4.053075 (0.000)
52.11
Beta 5.859427 (0.000)
41.53 1.327728 (0.000)
6.77 1.038769 (0.000)
7.19 1.357853 (0.000)
9.44
Common_Law 2.769975 (0.000)
20.84 3.134195 (0.000)
23.65 3.033559 (0.000)
30.38 4.053075 (0.000)
40.70
Intercept -10.75274 (0.000)
-34.33 -11.52614 (0.000)
-39.35 -11.977 (0.000)
-40.00 -9.211809 (0.000)
-40.28
Year effects Yes Yes Yes Yes Industry effects Yes Yes Yes Yes Adj.R2 0.8260 0.7933
0.7940 0.7700
N 13,185 16,162 24,530 24,582 Note: Coefficient p-values are two-tail and based on asymptotic Z-statistic robust to heteroskedasticity. For clarity in presentation the coefficients on year and industry dummies have not been reported.
Variable definitions of all of the variables are presented in Table 1.