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The World Capital Markets’ Perception of Sustainabilityand the Impact of the Financial Crisis
Kerstin Lopatta • Thomas Kaspereit
Received: 21 June 2012 / Accepted: 10 May 2013 / Published online: 13 June 2013
Springer Science+Business Media Dordrecht 2013
Abstract Using a unique dataset provided by the inter-
national rating agency GES, we investigate the effects of corporate sustainability and industry-related exposure to
environmental and social risks on the market value of
MSCI World firms. The results show a negative relation-
ship in the earlier years of our sample period. However, the
analysis reveals that the capital market perception of sus-
tainability has changed owing to the financial crisis.
Looking at the height of the crisis in September 2008, the
month in which Lehman Brothers shocked the world’s
capital markets by filing for Chapter 11 bankruptcy pro-
tection, we find that the previously negative perception of
corporate sustainability across its various dimensions was
positively affected and offset. In addition, as a moderated
regression analysis shows, the crisis led to a positive per-
ception of corporate sustainability in industries that are
exposed to higher environmental and social risks. Our
study has the practical implication that executives, in par-
ticular in industries with high environmental and social
risks, should increase their commitment to corporate sus-
tainability due to the changes in the institutional setting
triggered by the financial crisis.
Keywords Corporate sustainability Environmental risks Financial crisis Global Engagement Services (GES) Instrument variable regression Moderated regressionanalysis Social risks
Introduction
The current financial crisis not only shocked the capital
markets but also led to a change in the society’s perception of
profit maximization and its inherent risks. In October 2011,
members of the Occupy Wall Street movement claimed that
they had greater fear of the public risks of global climate
change and social inequality than of their personal risk of
being arrested and charged. The protesters directly connected
theserisks to thegreed of firms andcapitalmarkets, an attitude
that was shared even by a broad spectrum of political orga-
nizations (Wall Street Journal, 17 October, 2011). Thus, the
financial crisis seems to have strengthened public concerns
about the traditional neo-liberal shareholder value paradigm
that currently rules the major capital markets and which
dominated the corporate world before the concept of sus-
tainability appeared on the stage in the late 1990s. Underthese
circumstances, it is worth questioning how the world’s capital
markets perceive commitment to corporate sustainability and
what impact the financial crisis had on this perception.
This paper contributes to at least two strands of the liter-
ature. First, we expand the empirical literature on the con-
nection between corporate sustainability, sustainability at
the industry level and shareholder value creation. Our study
is the first to use a large sample of MSCI World firms with
sustainability ratings by Global Engagement Services
(GES), an established international rating agency special-
izing in socially responsible investments. Other studies on
the value relevance of corporate sustainability focus on local
markets (e.g. Hassel et al. 2005; Semenova and Hassel 2008;
Semenova et al. 2009; Guenster et al. 2011), whereas this
study addresses all of the world’s developed stock markets.
In addition, the sample has a panel data structure, which
covers the period December 2003–June 2011, which allows
us to control for individual heterogeneity. Applying a
K. Lopatta T. Kaspereit (&)Accounting and Corporate Governance, University of
Oldenburg, Ammerländer Heerstr. 114–118,
26111 Oldenburg, Germany
e-mail: [email protected]
K. Lopatta
e-mail: [email protected]
1 3
J Bus Ethics (2014) 122:475–500
DOI 10.1007/s10551-013-1760-9
8/18/2019 WORLD CAPITAL MARKET'S PERCEPTION
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generalized method of moments (GMM) approach and using
instrumental variables partially mitigate the endogeneity
problem. Thus, we provide reliable results that help to
understand the drivers of corporate sustainable development
and answer the question whether implementing sustainabil-
ity into corporate strategies is compatible with a broader
concept of shareholder value orientation.
Second, we contribute to the sparse theoretical andempirical literature on the momentum change in the capital
market’s perception of corporate sustainability that was
induced by the global financial crisis starting in 2007.
There is empirical evidence that during economic crises,
firms are forced to engage in cost-cutting activities and
consequently cut their spending on sustainability projects
(Karaibrahimoglu 2010). This tendency may be aggravated
by consumers’ focus on the cheapest price rather than
quality or additional product features such as ethical pro-
duction (Manubens, 2009). However, the crisis and the
concept of sustainability call for similar needs, for instance,
innovation to ensure long-term entrepreneurial survival, aninternal organizational culture and employee motivation,
all of which help firms to navigate rough economic waters
(Fernández-Feijóo Souto 2009). From this perspective,
corporate sustainability can serve as an effective tool to
manage economic crises and make firms less vulnerable to
their vicious effects. Furthermore, we argue that main-
taining or even improving the level of corporate sustain-
ability is a signal to the capital markets that a firm still has
enough financial strength to pursue a long-term business
strategy and is not forced to restrict its resources to vitally
important short-run functions. Our empirical findings sup-
port this argument since they detect a positive momentum
shift in perception of corporate sustainability during the
financial crisis, in particular for firms that operate in
industries with high environmental and social risks.
The paper is structured as follows. In the next section, we
develop our research hypotheses, which are based on the
theoretical literature describing the potential relationship
between corporate sustainability, shareholder value and the
financial crisis. Section ‘‘Results of Prior Empirical
Research’’ reviews the existing empirical evidence, before
the ‘‘Data and Methodology’’ section introduces the data and
methodology of our analysis. The results are presented in the
‘‘Results’’ section. Section ‘‘Conclusion’’ summarizes our
findings and provides an outlook on further research.
Theoretical Background and Hypotheses Development
Corporate Sustainability and Firm Value
The business ethics literature so far has provided several
approaches towards deriving a theoretical foundation for a
link between corporate sustainability and the market value
of a firm. These approaches can be assigned to three major
theories, namely, the resource-based view, legitimacy
theory and stakeholder theory.
The resource-based view sees expenditures for envi-
ronmentally friendly and socially desirable business prac-
tices as investments that lead to a better reputation and in
turn to higher long-run profits. In this theoretical frame-work, corporate sustainability contributes to the creation of
the essential resource reputation and can be regarded as a
management practice or even a total quality management
system that reduces manufacturing costs, produces com-
petitive advantages by enhancing production efficiency,
and lowers compliance and liability costs (Klassen and
McLaughlin 1993; Hart 1995; McWilliams and Siegel
2011; Hart and Dowell 2011). Whilst on the cost side,
corporate sustainability has the potential to reduce expen-
ditures resulting from material waste, recruitment and
inefficient processes (Klassen and McLaughlin 1996; Lo
and Sheu 2007), there is empirical evidence that certaincustomer groups tend to favour ‘green’ products from firms
that respect environmental and social standards (Tanner
and Wolfing Kast 2003; Gilg et al. 2005; Trudel and Cotte
2009). Nonetheless, most recent research finds that con-
sumers’ perception of sustainability differs depending on
product attributes. The positive effect of product sustain-
ability on consumer preferences is reduced when strength-
related attributes are valued, sometimes even resulting in
preferences for less sustainable product alternatives (Luchs
et al. 2010). Thus, the net effect of sustainability is case
sensitive and no general prediction is possible.
From a legitimacy theory perspective, corporate sus-
tainability can be seen as a management practice that
ensures going concern by preserving a firm’s organiza-
tional legitimacy. It delays the expected end of the time
series of future cash flows to infinity and in this way
increases firm value. Suchman (1995) defines legitimacy as
‘‘a generalized perception or assumption that the actions of
an entity are desirable, proper, or appropriate within some
socially constructed system of norms, values, beliefs, and
definitions’’. If the behaviour of a firm is at odds with these
norms, values, beliefs and definitions, there is a danger that
customers or suppliers will refuse to do business with that
firm. Then, the firm lacks legitimacy, which implies a
decline in profit or even corporate failure (Hybels 1995).
One example of the economic consequences of violating
customers’ norms was the Shell boycott after the company
announced plans to dump its oil storage buoy Brent Spar in
the Atlantic Ocean in 1995. Even though none of its cus-
tomers were directly affected in the economic sense, many
refused to buy gasoline from Shell gas stations, which
caused revenues and the share price to decline considerably
(Sandhu 2010). There are similar case studies for firms that
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employ workers in developing countries under question-
able conditions, e.g. Coca-Cola and Nike (Baron 2001;
Martin 2002; Lawrence 2010).
Stakeholder theory and related empirical work suggest
that firms that follow the principles of sustainability have
lower cost of capital due to lower stakeholder risks and a
broader investor base (Heinkel et al. 2001; Sharfman and
Fernando 2008; Bartkoski et al. 2010; Dhaliwal et al.2011; El Ghoul et al. 2011; Goss and Roberts 2011).
Godfrey (2005) developed a comprehensive framework
describing how corporate sustainability in the form of
philanthropy can create shareholder value by generating
positive moral capital amongst communities and stake-
holders. This moral capital can serve as insurance-like
protection for a firm’s relationship-based intangible assets
and in turn may reduce its exposure to stakeholder risks. A
reduction in risk implies lower cost of capital and, all other
factors being equal, higher firm value.
However, besides the benefits of corporate sustainability
described by these theories, when assessing the overalleffects of corporate sustainability on firm value, the
potential benefits have to be balanced against the costs,
which can be broken down into additional capital cost,
material and services, and labour (McWilliams and Siegel
2001). For instance, modern plants, equipment and end-of-
pipe facilities have to be financed, purchased and amor-
tized. To enhance the ecological efficiency of the produc-
tion process, additional research and development have to
be undertaken and money spent on in-house or external
training. Although widely ignored in the literature, the
costs that are most capable of substantially reducing future
cash flows are the opportunity costs that arise due to sus-
tainability-induced constraints on management decisions.
Firms that strive to maintain a sustainable image have to
abandon profitable but unethical business strategies such as
wage dumping, child labour and the use of environmentally
hazardous production materials. Since it remains an
empirical question whether the cost of sustainability
exceeds the benefit or vice versa, our first hypothesis is two
sided.
Hypothesis 1 The level of corporate sustainability affects
the market value of a firm.
If there is no evidence for Hypothesis 1, this can be
explained by microeconomic considerations. In Lundgrens’
(2011) model, firms invest in corporate sustainability until
their related marginal benefits equal the marginal costs.
Different observed levels of corporate sustainability are the
result of different benefit and cost structures rather than of
the varying abilities of management to follow the generally
value-enhancing business strategy of corporate sustain-
ability. As a consequence, the chosen level of corporate
sustainability is always individually optimal and not
relevant to cross-sectional and intertemporal variance in
firm valuation. Recent empirical findings by Chiu and
Sharfman (2011) support this strategic instrumentalization
of corporate sustainability.
Industry Sustainability and Firm Value
The theoretical analysis of the impact of industry envi-
ronmental and social risks on firm value differs from the
corporate level in that industry sustainability is not at the
discretion of management. These risks can change over
time and are driven by macroeconomic factors and trends.
Assuming risk-averse investors and an at least partial
inability to diversify these risks, less exposed industries are
anticipated to have higher firm values. The opposite would
imply the presence of risk-seeking investors or a broader
investor base in more exposed industries. Whilst the exis-
tence of risk-seeking investors would violate theoretical
consensus and be in opposition to broad empirical evi-
dence, the assumption of a broader investor base in riskier
industries can be reasonably justified by the observation
that sustainable investments only account for approxi-
mately 10 % of total assets under management (Derwall
et al. 2011). In addition, a large number of stock market
participants are still focused on dividend stocks with low
economic risk but high environmental and social risks,
such as energy, materials and utilities. Since we do not
know which theoretical argument best reflects reality, we
choose a two-sided hypothesis to account for the effect of
industry environmental and social exposure on firm value.
Hypothesis 2 The level of industry sustainability affectsthe market value of a firm.
Momentum Shifts in the Perception of Corporate
Sustainability During the Financial Crisis
Before the financial collapse in September 2008, capital
market deregulation was the ruling principle in politics.
The financial crisis and its major negative impact on the
real economy caused a turnaround in societal and political
attitudes. At this point, the belief in the corporate world’s
power to self-regulate vanished. More state and supra-
national regulation has become a serious threat, in partic-
ular for the financial sector (Emeseh et al. 2010). Whilst
regulation is not an issue for the non-financial sectors,
debates about greed and the rationale of profit maximiza-
tion are. As Kemper and Martin (2010) noted, the rules and
the values of firms to society changed overnight. Now, they
are employers first and producers of valuable goods sec-
ond. Argandoña (2009) interprets the crisis as an ethical
problem and proposes that genuine, ethical standards-based
corporate sustainability could have protected firms against
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the negative impact of the financial crisis. This suggestion
is reasonable since there is evidence in the marketing lit-
erature that the crisis has influenced consumers such that
they now attach higher importance to environmental and
social issues. Gerzema and D’Antonio (2011) report that
77 % of Americans agreed with the statement ‘‘Since the
recession, I realize that how many possessions I have does
not have much to do with how happy I am’’, 72 % agreedthat ‘‘I make it a point now to buy brands from companies
whose values are similar to my own’’, and two-thirds of all
respondents agreed that ‘‘I make it a point to avoid buying
brands whose values contradict my own’’. Kotler (2011),
although provides no empirical evidence, also asserts a
similar shift in the business-to-business market. These
momentum shifts in consumers’ and contractors’ attitudes
towards corporate sustainability can potentially affect the
cash flow distribution of firms and therefore their market
values, provided these effects are recognized by the capital
markets.
These developments are also covered by a currentlyemerging stream of research that links corporate sustain-
ability with institutional theory. Campbell (2007) analyses
which institutions determine whether a firm acts in a
socially responsible manner. He concludes that firms are
more likely to be socially responsible if they are finan-
cially healthy, operate in a business environment with
moderate competition, or see themselves confronted with
state regulation or social movements that encourage or
even enforce this kind of conduct. We have good reason
to assume that these institutional settings changed dra-
matically during the financial crisis. State regulation has
increased or is more likely to be increased in the near
future, whilst the Occupy Wall Street movement is a clear
indicator for an increase in societal demand for socially
and environmentally responsible business practices. As
Brammer et al. (2012, p. 6) aptly state, whilst before the
crisis a firm was considered a ‘political creation for which
the state granted limited liability in order to facilitate the
accumulation of capital, the post-2008 era of financial
crisis has taught an important lesson: the limited liability
of the privately owned corporation has re-emerged as the
collective liability of society’.
Although the financial crisis has changed the institu-tional setting towards a higher demand for corporate sus-
tainability, at the same time the financial constraints and
increasing competition have prevented many firms from
meeting this demand. In fact, during times of economic
crises, firms tend to restrict themselves to short-term vital
activities and to reduce their spending on sustainability
projects, which are long term by definition (Waddock and
Graves, 1997; Karaibrahimoglu 2010). The degree of
restriction is anticipated to increase in step with the firm-
specific impact of the crisis. The less the firm is affected,
the less non-vital activities are expected to be scaled back.
Support for this line of reasoning is illustrated in Fig. 1,which shows the development of mean GES sustainability
ratings. The shaded area marks the time span between the
first major write-down of subprime loans by HSBC in
February 2007 and Lehman Brothers’ Chapter 11 filing,
during which a decline in average corporate sustainability
and a rise in average environmental risks across industries
were observed. Since Jensen and Meckling (1976) devel-
oped their theory of the firm, it has been widely accepted
that market valuation depends on asymmetric information
between the management and owners. During the financial
crisis, this asymmetry mainly referred to a given firm’s
exposure to it. Thus, firms that did not reduce their cor-
porate sustainability activities signalled that they did not
suffer as much. Seen in aggregate, these and the above-
mentioned potential effects lead to Hypothesis 3.
Fig. 1 Average GES ratings
during the financial crisis
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Hypothesis 3 The financial crisis affected the capital
market perception of sustainability positively.
Hypothesis 3 can also be based on the idea that man-
agers balance the expected benefits of corporate sustain-
ability against its expected costs (McWilliams and Siegel
2001; Lundgren 2011). The financial crisis was an external
shock for the above-mentioned institutions, which has inturn increased the expected benefits of corporate sustain-
ability. However, firms have not been able to adjust their
levels of corporate sustainability to the new optimum level
immediately since this is a complex and time-consuming
task. Therefore, firms the management of which was more
optimistic with respect to the benefits of corporate sus-
tainability before the crisis are now expected to have a
comparative advantage over firms which were more
reluctant to implement corporate sustainability strategies.
This idea applies to sustainability at the industry level as
well. Here, the ability to adjust is even more constrained.
To implement higher standards of business ethics, socialengagement or environmental protection can take several
years or even decades, if it is possible at all.
Interactions Between Corporate Sustainability
and Sustainability at the Industry Level
Recent empirical literature concentrates on the value rele-
vance of corporate sustainability in industries that are
strongly exposed to environmental and social risk, such as
the electric utility industry in Hughes (2000) and the
chemical industry in Griffin and Mahon (1997). The
rationale behind this is the potentially greater importanceand visibility of sustainability issues in these industries
compared to less exposed sectors. In the case of water
pollution, non-sustainable behaviour on the part of an
insurance company has a far weaker negative impact on
biodiversity than if it comes from a global leading chem-
icals manufacturer. This argument is in line with the
empirical results of Brammer et al. (2006), who find that
environmental performance has a positive reputational
effect only in the chemicals, consumer products and
transportation sectors. Thus, it can be hypothesized that
sustainability at the corporate level is more important the
greater the environmental and social risks at the industrylevel. However, Semenova (2011) argues that firms in more
exposed industries face more restrictive regulatory
requirements and have fewer opportunities to gain com-
petitive advantages through sustainability activities. As a
consequence, their corporate sustainability efforts are per-
ceived as costly activities without corresponding benefits.
As in the case of the capital market’s general perception of
sustainability, both arguments appear reasonable, and
therefore Hypothesis 4 is two sided.
Hypothesis 4 The capital market’s perception of corpo-
rate sustainability depends on industries’ exposure to
environmental and social risks.
Results of Prior Empirical Research
Prior research on local markets has found evidence that
corporate sustainability affects firm value, but in diverg-
ing directions. Using KLD social issue ratings for the
period 1991–2003, Bird et al. (2007) show that the market
value of S&P 500 firms is negatively affected if they fail
to meet regulatory and community standards with respect
to the environmental dimension, but that it is positively
affected if the firm abstains from proactive engagement in
employee relations. For the UK stock market, Brammer
et al. (2006) arrive at contradictory results. For the period
July 2002–December 2005, their analysis of portfolio
returns for FTSE All-Share listed firms reveals a negativerelationship between environmental and community indi-
cators and stock returns. Furthermore, they measure a
weakly positive relationship for the employment indicator.
Very closely related to our analysis is the empirical study
by Hassel et al. (2005) who investigate the effect of
environmental performance on the market value of
Swedish firms for the period June 1998–September 2000.
Their results indicate a negative relationship between
environmental performance and market value. They
interpret this as evidence that investors perceive envi-
ronmental responsibility activities as profit-decreasing
measures. In a follow-up study to Hassel et al. (2005),Semenova et al. (2009) use the GES rating as a proxy for
environmental and social performance and find a positive
relationship with shareholder value between 2005 and
2008. Using the same dataset, Semenova (2011) finds
evidence of the positive effect of corporate sustainability
and of an interaction with environmental risks at the
industry level. Another study by Semenova and Hassel
(2008), which also uses the GES rating for U.S. compa-
nies from 2003 to 2006, measures a positive impact on
firm value for lower industry-specific environmental risk
as well as for higher environmental preparedness and
performance. Bagaeva (2010) applies the research designby Hassel et al. (2005) to Russian listed firms for the
period 2005–2007. She finds that environmental perfor-
mance has incremental value relevance and that investors
value lower environmental impacts positively. These
results are in line with the results of Guenster et al.
(2011), who find a positive effect of eco-efficiency in
U.S. companies between 1996 and 2004, together with a
time lag in this perception and an upwards trend over
time.
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Data and Methodology
Sustainability, Financial and Market Data
Our sample consists of all firms in the GES database from
December 2003 to June 2011 the financial and market data
of which are available in Thomson Financial Datastream/
Worldscope. Besides its reliability, the most importantadvantage of the GES database over its direct opponent
KLD is that it covers the whole MSCI World universe
instead of only U.S. firms. It therefore includes firms from
26 different countries and various industries. For this study,
Datastream/Worldscope is preferable to the commonly
used alternative Compustat because a merged sample from
Compustat North America, Compustat Global, and Com-
pustat Banks yielded a significantly lower coverage of the
firms rated by GES. Table 1 lists the firms and industries in
the sample.
The GES rating assesses both environmental and social
risks at the industry level and the corresponding opportuni-
ties at the firm level. Industries are demarcated using the 6- or
8-digit MSCI Global Industry Classification Standards
(GICS) classification, and all ratings are measured on a
7-level scale ranging across C (high risk/low opportunities),
over C?, B-, B , B?, A-, to A (lowrisk/high opportunities).
The industry-specific environmental rating ( IENV ) i s aweighted average of the direct risks of the industry and the
indirect risks that result from dependencies on other indus-
tries. The social rating at the industry level ( ISOC ) averages
employee, community and supplier concerns.
At the firm level, GES breaks down the environmental
dimension into two subdimensions, environmental perfor-
mance (FEPF ) and environmental preparedness (FEPR).
Environmental preparedness captures the relevant efforts
by management such as environmental certification, envi-
ronmental policy and programmes, implementation of an
Table 1 Country and industrycomposition of sample
observations
Countries Industries
Country Frequency Percent 4-Digit GICS Frequency Percent
United States 7,675 41.10 Capital goods 1,818 9.73
Japan 3,257 17.44 Materials 1,651 8.84
Great Britain 1,293 6.92 Banks 1,430 7.66
Canada 826 4.42 Energy 1,142 6.11
France 823 4.41 Utilities 1,019 5.46
Australia 729 3 .90 Insurance 856 4.58
Germany 632 3.38 Diversified financials 839 4.49
Sweden 409 2.19 Real estate 836 4.48
Italy 388 2.08 Food, beverage & tobacco 801 4.29
Hong Kong 387 2.07 Retailing 724 3.88
Switzerland 358 1.92 Technology hardware & equipment 719 3.85
Spain 317 1.70 Health care equipment & services 702 3.76
Shanghai 254 1.36 Transportation 669 3.58
The
Netherlands
223 1.19 Consumer durables & apparel 669 3.58
Finland 188 1.01 Software & services 656 3.51
Belgium 168 0.90 Media 644 3.45
Norway 132 0.71 Pharmaceuticals, biotech & life sciences 639 3.42
Denmark 129 0.69 Telecommunication services 547 2.93
Greece 117 0.63 Automobiles & components 423 2.26
Austria 97 0.52 Consumer services 422 2.26Portugal 87 0.47 Commercial & professional services 411 2.20
Ireland 71 0.38 Food & staples retailing 405 2.17
New Zealand 57 0 .31 Semiconductors & semiconductor
equipment
397 2.13
Israel 38 0.20 Household & personal products 196 1.05
Luxembourg 15 0.08 Unknown 61 0.33
Cyprus 3 0.02
Unknown 3 0.02
Total 18,676 100.00 Total 18,676 100.00
480 K. Lopatta, T. Kaspereit
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environmental management system, screening of suppliers
and environmental reporting. These efforts can, but do not
necessarily, result in better environmental performance.
Therefore, environmental performance is measured directly
using a battery of 21 indicators such as investment in
renewable energies, product recycling, decrease in green-
house gas emissions and water use. The firm-specific social
ratings are broken down into employee (FEMP), commu-nity (FCOM ) and supplier (FSUP) subratings. There are
between three and six direct indicators for each subcate-
gory that are derived from the United Nations’ Universal
Declaration of Human Rights, the United Nations’ Con-
vention on the Rights of the Child and the International
Labor Organization’s Core Labor Convention. In this way,
the GES ratings provide reliable proxies for a reasonable
selection of corporate sustainability issues. Although the
equal weightings of indicators are arbitrary and the
assignments of scores are, at least to some extent, subject to
personal judgement, the rating process is highly transparent
and reproducible. To make use of the GES ratings, thealphabetical scores are uniformly transformed to an integer
scale ranging from 1 (Score C) to 7 (Score A?) and are
interpreted as a metric variable. The database contains
ratings for the constituents of the MSCI World in 16
semiannual intervals during the period from the end of
2003–mid-year 2011, which results in an initial sample of
21,723 observations, of which 18,676 are covered by Da-
tastream/Worldscope. Table 2 contains an overview of the
GES variables used in this study.
The quarterly accounting and market data for each
semiannual observation of the GES ratings encompass
market capitalization ( MV ), book value of equity ( BV ), net
income ( NI ), the logarithm of total assets (lnTA), leverage
( LEV ) defined as total debt divided by total assets, one-year
sales growth (SG), country and currency codes, and
accounting standards in use. Additionally, some derivative
variables are constructed. The loss variable LO takes the
value of net income if net income is negative and zero
otherwise. BVI, BVL, NII, NIL, LOI and LOL are the
interactions between book value of equity, net income and
loss with two dummy variables that indicate whether the
accounting information is generated by IAS/IFRS (suffix I ) or local standards (suffix L ) instead of U.S.-GAAP.
However, the model contains no intercept terms for the
different accounting standards since they are collinear with
firm fixed effects. All accounting variables are translated
into U.S. dollar amounts at the daily exchange rate and
divided by total assets to mitigate the problem of different
scales (Barth and Clinch 2009). Table 3 summarizes the
descriptions of the descaled accounting and market data
variables.
The correlation matrix in panel B of Table 4 reveals a
strong correlation between all sustainability proxies. Firms
with a high degree of corporate sustainability in onedimension tend to have a high degree of corporate sus-
tainability in the other dimensions. However, the relation-
ship is negative for sustainability proxies at both the firm
and industry level. The higher the corporate sustainability
score, the higher the environmental and social risks for a
given industry. This supports the idea that corporate sus-
tainability acts as an opponent to serious industry envi-
ronmental and social risks and is therefore more important
in exposed industries.
Reference Model and Removing Statistical Outliers
The empirical analysis begins with setting up a reference
valuation model that explains the market value of a firm in
Table 2 Overview of GES rating variables
Variable Dimension Description
IENV Industry environmental
risk
Describes the environmental risks inherent in a specific industry at a specific point in time. Industries are
defined by their 6- or 8-digit GICS codes
FEPF Firm environmental
performance
A measure of 21 indicators that measure current success in environmental issues
FEPR Firm environmental
preparedness
Captures the efforts of the management in environmental sustainability, for instance, environmental
certification, environmental policy and programmes ISOC Industry social risk Describes the social risks inherent in a specific industry at a specific point in time. Industries are defined by
their 6- or 8-digit GICS codes
FEMP Firm employee rating Firm rating for the compliance with general human rights issues, such as exclusion of child labour and
discrimination
FCOM Firm community rating Captures the engagement of a firm in the community. Indicators are, for instance, policies for local
community involvement, a document policy towards prevention of corruption and a policy to identify the
social impacts of the firm’s investments
FSUP Firm supplier rating Captures the efforts of a firm in screening its entire supply chain for compliance with human rights.
Indicators are the existence of a corresponding management system and a supplier policy that covers the
core value of the International Labor Organization
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terms of its book value of equity, net income, the loss
variable, their interactions with the accounting standards’
dummy variables, sales growth, leverage and the natural
logarithm of total assets as a proxy for size. In this way, the
model can be regarded as an extended version of theempirical analogues of the Ohlson (1995) model, which is
commonly used in association studies to measure the
incremental value relevance of accounting and other
information (Barth et al. 2001; Hassel et al. 2005).
MV it ¼b0 þ b1 BV it þ b2 NI it þ b3 LOit þ b4 BVI it
þ b5 BVL it þ b6 NII it þ b7 NIL it þ b8 LOI it
þ b9 LOL it þ b10SGit þ b11 LEV it þ b12lnTAit þ d t
þ gi þ it
(Reference model)
In the reference model, the indexes i are for the individualcross-sectional unit and t for the time period. d t captures
the time effects, which are macroeconomic variables that
have the same effects on all firms, but differ from period to
period. The loss variable LO captures the capital market’s
special perception of losses. The expected sign of its
coefficient is negative, whilst its absolute value is expected
to be smaller than that of the coefficient of net income. It
hence partly offsets the net income coefficient. The eco-
nomic rationale behind this is the assumption that capital
market participants perceive losses as temporary and lim-
ited liability prevents negative market values (Hayn 1995;
Basu, 1997). Since quarterly data are released with a fairly
short delay, and capital markets are assumed to have the
ability to accurately anticipate accounting information, notime lag is included. Nevertheless, all results that are
reported later in this paper have been checked for sensi-
tivity to a time lag of three month and are found to be
robust to this modification.
Column A of Table 5 shows the regression results for all
the observations with available accounting and market
data. It is noticeable that the absolute value of the loss
variable’s coefficient is larger than its counterpart for net
income. This result is not in line with economic theory
because it implies that higher losses are connected to a
higher market value. Furthermore, the marginal effects of
book value of equity under IAS/IFRS, which is the sum of the coefficients on BV and BVI , and local accounting
standards, which is the sum of the coefficients on BV and
BVL , are negative. Therefore, the estimates of the reference
model lack economic reason. It is known from other
empirical studies (Collins et al. 1997; Hirschey et al. 2001;
Rajgopal et al. 2003) that removing statistical outliers can
solve this problem. After removing outliers in a three-step
procedure, defined as observations with an externally stu-
dentized residual greater than 12 (8 in the second and 4 in
Table 3 Overview of accounting, market and instrumental variables
Variable Mnemonic Description
MV MV Market value, calculated as the product of ordinary shares and share price scaled by total assets (WC02999A)
BV WC03501A Common equity, which, amongst others, includes common stock value, retained earnings, capital surplus, capital
stock premiums and cumulative gain or loss of foreign currency translation. BV is scaled by total assets
(WC02999A)
NI WC01751A Net income available to common, excluding extraordinary items. NI is scaled by total assets (WC02999A) LO – Loss, which takes the value of NI if NI is negative and a value of zero otherwise
BVI – Interaction variable of BV and a dummy that takes the value of 1 if the accounting standards are IAS/IFRS and zero
otherwise
BVL – Interaction variable of BV and a dummy that takes the value of 1 if the accounting standard is local and zero otherwise
NII – Interaction variable of NI and a dummy that takes the value of 1 if the accounting standards are IAS/IFRS and zero
otherwise
NIL – Interaction variable of NI and a dummy that takes the value of 1 if the accounting standard is local and zero otherwise
LOI – Interaction variable of LO and a dummy that takes the value of 1 if the accounting standards are IAS/IFRS and zero
otherwise
LOL – Interaction variable of LO and a dummy that takes the value of 1 if the accounting standard is local and zero otherwise
SG WC08631A Sales growth, calculated as follows: (Current year’s net sales or revenues divided by last year’s total net sales or
revenues - 1)*100
LEV – Leverage, calculated as the relation of total debt (WC03255A) to total assets (WC02999A)
TA WC02999A Represents total assets, i.e. the sum of total current assets, long-term receivables, investment in unconsolidated
subsidiaries, other investments, net property plant and equipment and other assets
EGY ENERDP033 Total direct and indirect energy consumption, scaled by sales (WC01001A)
ACC SOHSDP027 Number of injuries and fatalities reported by employees and contractors whilst working for the company, divided by
the number of employees (WC07011) and sales (WC01001A)
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T a b l e 4
D e s c r i p t i v e s t a t i s t i c s a n d c o r r e l a t i o n m a t r i x f o r m o d e l v a r i a b l e s
I E N V
F E P F
F E P R
I S O C
F E M P
F C O M
F S U P
M V
B V
N I
P a n e l A : D e s c r i p t i v e s t a t i s t i c s
M e a n
3 . 7 6
2 . 6 6
3 . 3 9
3 . 7 7
2 . 8 9
2 . 9 0
1 . 9 7
1 . 0 5
0 . 3 7
0 . 0 2
M e d i a n
4 . 0 0
3 . 0 0
4 . 0 0
4 . 0 0
3 . 0 0
3 . 0 0
1 . 0 0
0 . 6 8
0 . 3 7
0 . 0 1
S D
2 . 1 2
1 . 6 4
1 . 8 9
2 . 2 1
1 . 4 4
1 . 3 4
1 . 3 7
1 . 2 8
0 . 2 3
0 . 0 3
M i n
1 . 0 0
1 . 0 0
1 . 0 0
1 . 0 0
1 . 0 0
1 . 0 0
1 . 0 0
0 . 0 0
-
3 . 5 5
- 0 . 6 0
M a x
7 . 0 0
7 . 0 0
7 . 0 0
7 . 0 0
7 . 0 0
7 . 0 0
7 . 0 0
3 3 . 0 6
1 . 0 3
1 . 0 8
P a n e l B : C o r r e l a t i o n m a t r i x
I E N V
1 . 0 0
F E P F
- 0 . 2 7 * * *
1 . 0 0
F E P R
- 0 . 4 2 * * *
0 . 7 8 * * *
1 . 0 0
I S O C
0 . 6 6 * * *
- 0 . 1 8 * * *
- 0 . 3 0 * * *
1 . 0 0
F E M P
- 0 . 2 2 * * *
0 . 6 5 * * *
0 . 6 2 * * *
- 0 . 1 3
* * *
1 . 0 0
F C O M
- 0 . 1 2 * * *
0 . 4 0 * * *
0 . 4 0 * * *
- 0 . 1 2
* * *
0 . 5 8 * * *
1 . 0 0
F S U P
0 . 1 0 * * *
0 . 4 0 * * *
0 . 3 7 * * *
- 0 . 0 4
* * *
0 . 5 3 * * *
0 . 4 4 * * *
1 . 0 0
M V
0 . 0 4 * * *
- 0 . 1 4 * * *
- 0 . 1 0 * * *
- 0 . 1 1
* * *
- 0 . 1 2 * * *
0 . 0 1
- 0 . 0 1
1 . 0 0
B V
- 0 . 1 8 * * *
- 0 . 0 7 * * *
0 . 0 0
- 0 . 2 7
* * *
- 0 . 1 5 * * *
- 0 . 1 0 * * *
- 0 . 1 1 * * *
0 . 3 6 * * *
1 . 0 0
N I
- 0 . 0 2 * * *
- 0 . 0 3 * * *
0 . 0 0
- 0 . 1 0
* * *
- 0 . 0 1
0 . 0 2 * *
0 . 0 5 * * *
0 . 3 6 * * *
0 . 2 0 * * *
1 . 0 0
L O
0 . 0 1 *
0 . 0 2 * *
0 . 0 1 *
0 . 0 0
0 . 0 1
0 . 0 1
0 . 0 2 * *
0 . 0 1 *
0 . 0 2 * *
0 . 6 7 * * *
B V I
- 0 . 1 4 * * *
0 . 2 0 * * *
0 . 1 9 * * *
- 0 . 0 9
* * *
0 . 2 4 * * *
0 . 0 5 * * *
0 . 1 8 * * *
0 . 0 3 * * *
0 . 2 6 * * *
0 . 1 3 * * *
B V L
- 0 . 1 3 * * *
0 . 0 2 * *
0 . 0 8 * * *
- 0 . 1 0
* * *
- 0 . 2 1 * * *
- 0 . 2 7 * * *
- 0 . 1 8 * * *
0 . 0 1
0 . 3 5 * * *
0 . 0 1 *
N I I
- 0 . 0 3 * * *
0 . 0 8 * * *
0 . 0 8 * * *
- 0 . 0 5
* * *
0 . 1 0 * * *
0 . 0 2 * *
0 . 1 0 * * *
0 . 1 5 * * *
0 . 0 3 * * *
0 . 6 5 * * *
N I L
- 0 . 0 4 * * *
- 0 . 0 3 * * *
0 . 0 2 * *
- 0 . 0 4
* * *
- 0 . 1 1 * * *
- 0 . 0 8 * * *
- 0 . 0 5 * * *
0 . 1 1 * * *
0 . 1 7 * * *
0 . 3 3 * * *
L O I
0 . 0 2 * *
- 0 . 0 2 * *
- 0 . 0 1 *
0 . 0 0
- 0 . 0 2 * *
0 . 0 2 * *
0 . 0 0
0 . 0 0
0 . 0 1 *
0 . 3 6 * * *
L O L
0 . 0 2 * *
- 0 . 0 2 * *
- 0 . 0 2 * * *
0 . 0 1
0 . 0 2 * *
0 . 0 6 * * *
0 . 0 3 * * *
0 . 0 3 * * *
0 . 0 0
0 . 2 5 * * *
S G
0 . 0 0
- 0 . 0 4 * * *
- 0 . 0 4 * * *
- 0 . 0 1
*
- 0 . 0 4 * * *
- 0 . 0 1
- 0 . 0 3 * * *
0 . 0 5 * * *
0 . 0 2 * * *
0 . 0 3 * * *
L E V
- 0 . 0 9 * * *
0 . 0 3 * * *
0 . 0 2 * * *
- 0 . 0 1
0 . 0 7 * * *
0 . 0 8 * * *
- 0 . 0 1
- 0 . 1 7 * * *
-
0 . 5 1 * * *
- 0 . 1 2 * * *
l n T A
0 . 1 5 * * *
0 . 2 7 * * *
0 . 1 7 * * *
0 . 2 7 * * *
0 . 3 1 * * *
0 . 2 4 * * *
0 . 2 7 * * *
- 0 . 4 8 * * *
-
0 . 4 5 * * *
- 0 . 1 9 * * *
L O
B V I
B V L
N I I
N I L
L O I
L O L
S G
L E V
l n T A
P a n e l A : D e s c r i p t i v e s t a t i s t i c s
M e a n
0 . 0 0
0 . 0 9
0 . 1 0
0 . 0 1
0 . 0 0
0 . 0 0
0 . 0 0
8 . 8 6
0 . 2 6
1 6 . 6 8
M e d i a n
0 . 0 0
0 . 0 0
0 . 0 0
0 . 0 0
0 . 0 0
0 . 0 0
0 . 0 0
6 . 2 7
0 . 2 3
1 6 . 4 3
S D
0 . 0 2
0 . 1 9
0 . 2 1
0 . 0 2
0 . 0 1
0 . 0 1
0 . 0 1
6 4 . 4 6
0 . 1 9
1 . 6 5
M i n
- 0 . 6 0
- 3 . 5 5
- 0 . 4 9
- 0 . 4 9
- 0 . 4 7
- 0 . 4 9
- 0 . 4 7
- 3 6 9 1 . 9 3
0 . 0 0
1 2 . 2 2
M a x
0 . 0 0
0 . 9 9
0 . 9 8
1 . 0 8
0 . 2 2
0 . 0 0
0 . 0 0
4 8 0 5 . 4 2
3 . 9 7
2 5 . 3 5
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the third step) or a Cook’s measure of distance greater than
12/ n (8/ n, 4/ n) with n as the number of observations, we
obtain the coefficients in Column B of Table 5. Now, all
coefficients have economically sound estimates.
After correcting for outliers, we end up with a sample of
16,619 observations from 1,993 firms. The entire sample
reduction process from missing accounting or market data
to the removal of outliers is reported in Table 6.
Regression Models
To test for the effects of the various levels and dimensions of
corporate sustainability on firm value, the market value of a
firm’s equity is regressed on its GES ratings and all of the
independent variables in the reference model, which are now
interpreted as control variables and summarized under CTRL .
T a b l e 4
c o n t i n u e d L
O
B V I
B V L
N I I
N I L
L O I
L O L
S G
L E V
l n T A
P a n e l B : C o r r e l a t i o n m a t r i x
L O
1 . 0 0
B V I
- 0 . 0 1
1 . 0 0
B V L
0 . 0 2 * *
- 0 . 2 3 * * *
1 . 0 0
N I I
0 . 2 7 * * *
0 . 3 9 * * *
- 0 . 1 2 * * *
1 . 0 0
N I L
0 . 2 1 * * *
- 0 . 1 1 * * *
0 . 4 8 * * *
- 0 . 0 6 * * *
1 . 0 0
L O I
0 . 5 3 * * *
- 0 . 1 0 * * *
0 . 0 4 * * *
0 . 4 6 *
* *
0 . 0 2 * *
1 . 0 0
L O L
0 . 3 4 * * *
0 . 0 4 * * *
- 0 . 1 2 * * *
0 . 0 2 *
* *
0 . 5 1 * * *
- 0 . 0 1
1 . 0 0
S G
0 . 0 1
0 . 0 0
- 0 . 0 1
0 . 0 1
0 . 0 2 * * *
0 . 0 2 * * *
0 . 0 0
1 . 0 0
L E V
- 0 . 0 6 * * *
- 0 . 1 2 * * *
- 0 . 1 6 * * *
0 . 0 0
- 0 . 0 9 * * *
- 0 . 0 5 * * *
- 0 . 0 2 * * *
0 . 0 1
1 . 0 0
l n T A
0 . 0 6 * * *
- 0 . 1 0 * * *
- 0 . 2 4 * * *
- 0 . 1 1 * * *
- 0 . 1 2 * * *
0 . 0 4 * * *
0 . 0 4 * * *
- 0 . 0 1
0 . 0 8 * * *
1 . 0 0
A l l fi n a n c i a l v a r i a b l e s a r e s c a l e d b y t o t a l a s s e t s
A s t e r i s k s i n d i c a t e s t a t i s t i c a l s i g n i fi c a n c e a t t h e 1 % ( * * * ) , 5 % ( * * ) a n d 1 0 %
( * ) l e v e l s
Table 5 Regression of market value on controls before and after
removing outliers
Variables Column A: before
removing outliers
Column B: after
removing outliers
BV 1.3808*** 0.9431***
(0.1020) (0.0398)
NI 11.0762*** 8.7503***
(0.5773) (0.2633)
LO -11.5836*** -8.6348***
(0.7280) (0.3154)
BVI -1.6401*** -0.0919*
(0.1234) (0.0487)
BVL -1.7591*** -0.2674***(0.1406) (0.0526)
NII -6.8652*** -6.2689***
(0.6821) (0.3336)
NIL -6.7727*** -5.9098***
(0.9242) (0.3874)
LOI 5.9914*** 5.4080***
(0.9939) (0.4556)
LOL 7.3164*** 5.3147***
(1.4505) (0.5493)
SG 0.0093 0.0019
(0.0077) (0.0034)
LEV 0.2713*** -0.2193***
(0.0710) (0.0297)
lnTA -0.4581*** -0.2523***
(0.0085) (0.0034)
Observations 18,676 16,619
Firms 2,266 1,993
Adj. R2 0.2321 0.5135
Standard errors displayed in parentheses. Asterisks indicate statistical
significance at the 1 % (***), 5 % (**) and 10 % (*) levels. Variables
are defined as in Table 3
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Since the correlation matrix in Table 4 and variance
inflation indicators calculated on the basis of a model that
includes all sustainability proxies simultaneously indicate
strong collinearity between the sustainability proxies,
Regression (1) estimates the effects separately for each
corporate sustainability dimension represented by FSUS .
Nevertheless, the corresponding risk rating at the industry
level, represented in the model by ISUS , is always included
because omittance would induce bias as it correlates with
the corporate sustainability proxy.
MV it ¼ b0 þ b1 ISUS it þ b2FSUS it þ b3CTRL it
þ d t þ gi þ it ð1Þ
If, as stated by Hypothesis 3, the financial crisis brought
about a change in the perception of corporate sustainability
or industry environmental and social risks, the regression
coefficient of the sustainability proxies in Model (1) should
have shifted with the onset of the crisis. To capture this
effect, the 16 semiannual cross sections in the sample are
divided into twoparts, oneranging from the endof 2003–mid
2008 and the other ranging from the end of 2008–mid 2011.The first part hence contains all observations before Lehman
Brothers’ Chapter 11 filing, whilst the second contains all
observations after this triggering event at the peak of the
financial crisis. This partitioning enters Model (2) in the form
of a dummy variable CRISIS that takes the value of 1 if the
observation is from the later part and zero otherwise. CRISIS
interacts with the sustainability proxies, and the coefficients
on the interactions measure the crisis-induced shift in the
marginal effect of sustainability on the market value of firms.
MV it ¼ b0 þ b1 ISUS it þ b2CRISIS t ISUS it þ b3FSUS it
þ b4CRISIS t FSUS it þ b5CTRL it þ d t þ gi þ it :
ð2Þ
The coefficients b1 and b3 in Model (2) capture the mar-
ginal effects under the condition that CRISIS is zero. The
estimates for b1 ? b2 and b3 ? b4 measure the marginal
effects when CRISIS is one. Positive estimates for the
coefficients b2 and b4 would indicate a shift to a more
positive perception of sustainability, compared to before
the crisis. Note that no intercept dummy for the crisis is
included since it would be perfectly collinear with the time
dummies d t .
The interaction effects of sustainability at the firm and at
the industry level are tested by a moderated regression
analysis, which includes interaction terms of the explana-
tory variables.
MV it ¼ b0 þ b1 ISUS it þ b2CRISIS t ISUS it þ b3FSUS it
þ b4CRISIS t FSUS it þ b5 ISUS it FSUS it
þ b6CRISIS t ISUS it FSUS it þ b7CTRL it þ d t þ gi þ it :
ð3Þ
In moderated regression analysis with continuous vari-
ables, as in Model (3), the interpretation of the coefficient
substantially differs from that in purely additive multiple
linear regression models. The coefficient b5 captures the
contingent effects of the research interest variables on each
other’s coefficients before the crisis. The coefficient b6
Table 6 Sample reductionDate GES
Tape
Missing accounting
or market data
Sample before
removing outliers
Statistical
outliers
Sample after
removing outliers
End of Q04/2003 890 233 657 46 611
End of Q02/2004 1,000 297 703 94 609
End of Q04/2004 994 248 746 59 687
End of Q02/2005 1,000 292 708 59 649
End of Q04/2005 1,000 205 795 80 715End of Q02/2006 999 195 804 74 730
End of Q04/2006 1,000 128 872 75 797
End of Q02/2007 1,002 162 840 65 775
End of Q04/2007 1,883 254 1,629 255 1,374
End of Q02/2008 1,941 267 1,674 213 1,461
End of Q04/2008 1,696 150 1,546 172 1,374
End of Q02/2009 1,676 142 1,534 80 1,454
End of Q04/2009 1,659 93 1,566 112 1,454
End of Q02/2010 1,658 103 1,555 113 1,442
End of Q04/2010 1,655 60 1,595 164 1,431
End of Q02/2011 1,679 227 1,452 396 1,056
Total 21,732 3,056 18,676 2,058 16,619
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captures this effect when CRISIS is one (Dawson and
Richter 2006). However, the constitutive elements, which
are the terms without interactions, cannot be directly
interpreted in a meaningful sense. The term b3 FSUS it , for
instance, measures the marginal effect of a one-unit
increase in corporate sustainability on the market value of a
firm conditional on CRISIS and ISUS being zero. Whilst the
interpretation of the first condition is straightforward(‘‘before the crisis’’), the second is not, in particular when
the sample consists of no observations with ISUS being
zero (Brambor et al. 2006). Therefore, to draw inferences
from Model (3), we apply a plotting technique that depicts
the marginal effect of corporate sustainability on the
market value of a firm conditional on the level of industry
sustainability.
Endogeneity and Method of Estimation
The degree to which a firm follows the concept of sus-
tainability is at the discretion of the management, and thenet benefits that arise from a given level of corporate
sustainability may depend on size, which is proxied by
market capitalization. Therefore, the regression models
potentially suffer from endogeneity due to reverse causal-
ity. Other potential sources of endogeneity are measure-
ment errors in the sustainability proxies and omitted
variables. In these cases, the coefficient estimates are
biased and the results of the empirical analysis are unreli-
able (Wooldridge 2010, Chap. 8). To mitigate the problem
of endogeneity, we estimate each model using an instru-
ment variable approach.
Since it is difficult to find valid and relevant instrumentsfor corporate sustainability in a price-level regression, we
do not claim to have found perfect instruments, but rather
the best available instruments. For the environmental
dimensions of corporate sustainability, these are the 6-digit
GICS industry averages of the potentially endogenous
variables calculated without the instrumented observation
and the industry average of energy consumption scaled by
sales. The proxies for corporate sustainability in the social
dimension are instrumented by their industry averages and
the industry average of the total accidents per employees
scaled by sales. Using industry averages as instruments
solves the problem of pure reverse causality that is not the
result of omitted variables because a firm’s market valua-
tion is unlikely to affect the level of corporate sustain-
ability of other firms in the same industry. The calculation
procedure also largely averages out random measurement
errors. However, there can be industry-specific factors that
affect both valuation of the firms and their chosen level of
the corporate sustainability. If these effects are constant
over time, they will be mitigated by fixed effects estima-
tion. If they vary over time, they will prevent the
instruments from overcoming endogeneity. Whether an
instrumental variable approach with semi-endogenous
instruments is preferable to not instrumenting depends on
the unknown correlations between the instruments and the
error term, between the endogenous regressors and the
instruments, and between the endogenous regressors and
the error term (Larcker and Rusticus 2010). Therefore, we
report the results for both the instrumented and non-instrumented models. All the models in this study are
estimated with the two-step GMM estimator that provides
efficient estimates and standard errors that are robust to
arbitrary heteroskedasticity and intra-firm correlation of the
residuals.
Results
Regression Results
Tables 7 and 8 show the regression results for Model (1).At the industry level, in all Specifications (a)–(e), the
perception of sustainability in the environmental and social
dimensions is significantly negative at the 1 % level. This
implies that a broader investor base prefers to invest in
environmentally and socially riskier industries. At the firm
level, there is only weak statistical evidence of a negative
perception of sustainability in the community dimension
when instrument variable estimation is applied (Table 8).
Thus, Model (1) provides no substantial support for
Hypothesis 1, but does provide evidence for Hypothesis 2
in a negative direction.
In Model (2), the impact of the financial crisis on the
perception of sustainability is included in the form of
interaction between a dummy variable CRISIS and the
sustainability proxies from GES. Tables 9 and 10 show
the regression results for the estimation of this model. At the
industry level, Specifications (a) and (b) in both the instru-
mented and non-instrumented regression measure a signif-
icantly positive effect of the crisis on the perception of lower
environmental risks, the latter being equivalent to higher
values of the rating score IENV . At first glance, the results
are inconclusive concerning the effect of the crisis on the
perception of industry-related social risks. In Specification
(c), the impact is significantly positive, whereas in Specifi-
cation (e), it is negative. The divergence of these results can
be attributed to a substantial sample reduction of almost five
thousand observations due to missing values of the variable
FSUP. However, when the analysis is conducted with a
multiply imputed dataset or with ISUS and controls as
explanatory variables alone (not reported), a statistically
significant positive impact of the crisis is measured.
At the firm level, the results reported in Table 9 show a
significantly positive change in the perception of
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environmental performance and corporate sustainability in
the employee dimension. The instrument variable approach
indicates that this effect also exists for the community
dimension, although the level of significance is weak
(Table 10). Thus, we note that the model estimates provide
support for Hypothesis 3. The financial crisis has had a
positive effect on the perception of corporate sustainability
in specific dimensions. Model (2) also provides new
estimates for the perception of corporate sustainability
before the financial crisis. The coefficients of environmental
performance and sustainability in the employee dimension
are negative when CRISIS is zero. This is true for the
community dimension when instrument variable regression
is applied. Hence, when the variable CRISIS is included,
there is empirical evidence for the materiality of some of the
corporate sustainability dimensions in firm valuation.
Table 7 Regression results for Model (1)
Variables Hyp. Exp. (a) (b) Variables Hyp. Exp. (c) (d) (e)
IENV H2 ? -0.0329*** -0.0332*** ISOC H2 ? -0.0302*** -0.0228*** -0.0208***
(0.0044) (0.0044) (0.0048) (0.0052) (0.0057)
FEPF H1 ? -0.0061 FEMP H1 ? -0.0036
(0.0038) (0.0040)
FEPR H1 ? -0.0049 FCOM H1 ? -0.0011
(0.0042) (0.0045)
FSUP H1 ? 0.0018
(0.0055)
BV ? 0.9552*** 0.9566*** BV ? 0.9388*** 0.9451*** 0.9675***
(0.0919) (0.0917) (0.0915) (0.0972) (0.1006)
NI ? 8.7162*** 8.7030*** NI ? 8.6904*** 8.6614*** 8.4205***
(0.7098) (0.7107) (0.6970) (0.6819) (0.6652)
LO - -8.6282*** -8.6188*** LO - -8.5906*** -8.5593*** -8.3554***
(0.7626) (0.7637) (0.7494) (0.7343) (0.7137)
BVI -0.1025 -0.1076 BVI -0.0784 -0.0240 -0.0411
(0.1181) (0.1181) (0.1215) (0.1293) (0.1318)
BVL -0.2752** -0.2750** BVL -0.2512** -0.2986** -0.3351***
(0.1167) (0.1164) (0.1187) (0.1248) (0.1271)
NII -6.2491*** -6.2401*** NII -6.1640*** -5.8863*** -5.2990***
(0.8034) (0.8027) (0.7963) (0.8010) (0.8147)
NIL -5.9537*** -5.9317*** NIL -5.9008*** -5.8013*** -4.9586***
(0.8464) (0.8479) (0.8375) (0.8312) (0.8557)
LOI 5.4559*** 5.4533*** LOI 5.4156*** 4.8546*** 4.2495***
(0.9056) (0.9052) (0.9021) (0.9185) (1.0200)
LOL 5.3637*** 5.3473*** LOL 5.3260*** 5.0148*** 4.0153***
(0.9535) (0.9551) (0.9441) (0.9419) (0.9726)
SG 0.0018 0.0016 SG 0.0020 0.0040 0.0225*
(0.0029) (0.0029) (0.0029) (0.0030) (0.0127) LEV -0.1981*** -0.1968*** LEV -0.1953*** -0.1541*** -0.1619***
(0.0532) (0.0531) (0.0525) (0.0550) (0.0622)
lnTA -0.2522*** -0.2521*** lnTA -0.2523*** -0.2528*** -0.2614***
(0.0057) (0.0057) (0.0057) (0.0059) (0.0064)
Time dummies YES YES Time dummies YES YES YES
Firm dummies YES YES Firm dummies YES YES YES
Observations 16,556 16,556 Observations 16,555 13,890 11,590
Firms 1,968 1,968 Firms 1,968 1,781 1,399
Adj. R2
0.5202 0.5201 Adj. R2
0.5193 0.5334 0.5465
Heteroskedasticity and cluster robust standard errors from GMM estimation are displayed in parentheses. Asterisks indicate statistical signifi-
cance at the 1 % (***), 5 % (**) and 10 % (*) levels. Variables are defined as in Tables 2 and 3
The World Capital Markets’ Perception 487
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The coefficients estimated in Model (2) measure the
perception of sustainability before the crisis and the change
induced by the crisis. To measure the marginal effect of
sustainability on shareholder value after September 2008,
we calculate the sum of the coefficient before the crisis and
the coefficient of the crisis interaction term. The standard
Table 8 Instrument variable regression results for Model (1)
Variables Hyp. Exp. (a) (b) Variables Hyp. Exp. (c) (d) (e)
IENV H2 ? -0.0390*** -0.0376*** ISOC H2 ? -0.0383*** -0.0270*** -0.0295***
(0.0049) (0.0050) (0.0053) (0.0053) (0.0070)
FEPF H1 ? -0.0288 FEMP H1 ? -0.0140
(0.0449) (0.1309)
FEPR H1 ? -0.0068 FCOM H1 ? -0.0694**
(0.0290) (0.0335)
FSUP H1 ? 0.1004
(0.1041)
BV ? 0.9475*** 0.9611*** BV ? 0.8782*** 0.8223*** 0.8505***
(0.1055) (0.1022) (0.1304) (0.1108) (0.1124)
NI ? 8.0837*** 8.1269*** NI ? 7.7301*** 7.8526*** 7.8451***
(0.6807) (0.6891) (0.6466) (0.6467) (0.7046)
LO – -7.9594*** -8.0296*** LO – -7.5834*** -7.7448*** -7.7841***
(0.7446) (0.7447) (0.7051) (0.7099) (0.7727)
BVI -0.1369 -0.1484 BVI -0.0341 0.0226 -0.0186
(0.1243) (0.1277) (0.1641) (0.1458) (0.1403)
BVL -0.2679** -0.2778** BVL -0.1903 -0.1643 -0.1620
(0.1247) (0.1233) (0.1343) (0.1402) (0.1427)
NII -5.5598*** -5.6712*** NII -4.8914*** -5.1992*** -4.5043***
(0.7954) (0.7809) (0.8020) (0.7872) (0.8182)
NIL -5.4538*** -5.4871*** NIL -4.4146*** -4.5160*** -4.6910***
(0.8305) (0.8576) (1.1290) (0.8449) (1.0117)
LOI 4.7348*** 4.8701*** LOI 3.8665*** 4.1693*** 3.0369***
(0.9067) (0.8825) (0.9367) (0.9176) (1.0373)
LOL 4.7313*** 4.8200*** LOL 3.4617*** 3.5938*** 3.7626***
(0.9470) (0.9644) (1.2201) (0.9727) (1.1615)
SG 0.0012 0.0012 SG 0.0002 0.0016 0.0076
(0.0028) (0.0029) (0.0039) (0.0032) (0.0154) LEV -0.2329*** -0.2229*** LEV -0.1966*** -0.1660*** -0.1873**
(0.0604) (0.0563) (0.0578) (0.0619) (0.0728)
lnTA -0.2487*** -0.2493*** lnTA -0.2488*** -0.2508*** -0.2576***
(0.0059) (0.0058) (0.0058) (0.0060) (0.0068)
Time dummies YES YES Time dummies YES YES YES
Firm dummies YES YES Firm dummies YES YES YES
Observations 15,121 15,121 Observations 13,284 11,638 9,742
Firms 1,896 1,896 Firms 1,789 1,640 1,294
Adj. R2
0.5227 0.5257 Adj. R2
0.5256 0.5163 0.5134
Kleibergen–Paap (KP) 17.1523 40.4726 KP 4.5025 53.0325 5.3760
p-value (KP) 0.0002 0.0000 p-value (KP) 0.1050 0.0000 0.0680
Hansen-J 0.0014 0.3533 Hansen-J 0.4660 0.1843 0.1641
p-value (J) 0.9710 0.5538 p-value (J) 0.4950 0.6686 0.6859
Heteroskedasticity and cluster robust standard errors from GMM estimation are displayed in parentheses. Asterisks indicate statistical signifi-
cance at the 1 % (***), 5 % (**) and 10 % (*) levels. Variables are defined as in Tables 2 and 3. The Kleibergen-Paap (KP) Wald F -statistic tests
the relevance of the instruments. Its null hypothesis is that the instruments are uncorrelated with the endogenous regressors (Kleibergen and Paap
2006). Hansen-J is a test of the over-identifying restrictions. Its null hypothesis is that the instruments are exogenous (Hansen 1982)
488 K. Lopatta, T. Kaspereit
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T a b l e 9
R e g r e s s i o n r e s u l t s f o r M o
d e l ( 2 )
V a r i a b l e s
H y p .
E x p .
( a )
( b )
V a r i a b l e s
H y p .
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