file138805

Master thesis
Valuating Enterprise Risk Management:
Does Enterprise Risk Management create value?
Author : Abdelilah Nahari
ANR : s935089
Study Program : Master of Science (MSc) in Finance
Institute : Tilburg University, School of Economics and Management, Department of Finance
Thesis committee members
Supervisor : Dr. M.R.R. van Bremen
Chairman : Dr. J.C. Rodriguez

Abdelilah Nahari 2 Master Thesis Finance
Preface
First I would like to take this opportunity to express my gratitude to my supervisor Dr. Michel
van Bremen for his excellent guidance, academic feedback and support during the writing of
this thesis. Special thanks go out to the Tilburg University and in particular the School of
Economics and Management who have provided me with a high quality education and great
support throughout my Bachelor and Master of Science.
The work put in my Master of Science in Finance culminates in this thesis on Enterprise Risk
Management. I believe that in these times of interconnectedness and fast pace a good
enterprise-wide risk management framework is necessary to control risks that can have
devastating impact. With this thesis I attempted to capture the value relevance of enterprise-
wide risk management and its ability to help firms to achieve their goals.
Finally I would like to thank my parents, friends, family and colleagues who have provided
me with their great support and encouraged me to write this thesis.
Tilburg, 15 December 2015
Abdelilah Nahari

Abstract
Driven by scandals, the sub-prime crisis and the fall-down of several large firms such as
Lehman Brothers and Enron, risk management and in particular Enterprise Risk Management
(ERM) has gained much field. ERM is said to manage firm-wide risk in a holistic way and
thereby enhancing firm value. While much is known about the determinants for
implementation of ERM, only a limited amount of studies have investigated its value creating
ability. These previous studies present mixed findings and mainly focus on financial firms.
Furthermore most studies fall short by focusing on certain industries and geographical regions
only, by the lack of a good benchmark for the determination of ERM implementation or by
measuring performance instead of firm value. This study attempts to answer the question
whether the implementation of ERM leads to additional firm value for non-financial US and
EMEA firms, as compared with firms engaging in what is referred to as traditional risk
management (TRM). Recently, in addition to the ERM benchmark for financial firms,
Standard & Poors introduced a new benchmark to measure the degree of ERM
implementation for non-financial firms called the Management & Governance rating. With
this benchmark and by using Tobin’s Q as measurement for firm value this study conducts a
multiple linear regression analysis on 129 US and 85 EMEA firms. This study presents two
key findings. First for US non-financial firms ERM is found to be positively associated with
firm value, suggesting that ERM creates additional value on top of TRM. This is contrary to
the findings of McShane et al. (2011) for financial firms, but in line with other previous
studies on financial firms. However for EMEA non-financial firms the findings are negative
and mostly significant, suggesting that shareholders in the EMEA countries perceive ERM as
a value destroying mechanism. This result reveals that there might be geographical
differences in the perception of value creating ability of ERM. Further research with larger
sample sizes should be performed in order to further investigate these findings for EMEA
firms.
Keywords: Enterprise Risk Management, ERM, TRM, Tobin’s Q, Value Creation, Finance

Table of Contents
Preface........................................................................................................................................ 2
Abstract ...................................................................................................................................... 3
Table of Contents ....................................................................................................................... 4
Part 1: Introduction..................................................................................................................... 5
Part 2: Literature Review ........................................................................................................... 8
From insurance to Enterprise Risk Management................................................................................ 8
Value relevance of risk management ................................................................................................ 13
Additional value created by Enterprise Risk Management............................................................... 14
Current state of literature .................................................................................................................. 17
Benchmark for ERM......................................................................................................................... 18
Part 3: Research Design ........................................................................................................... 20
Main research question ..................................................................................................................... 20
Hypothesis development................................................................................................................... 20
Part 4: Methodology................................................................................................................. 24
Method .............................................................................................................................................. 24
Variable motivation........................................................................................................................... 25
Model building.................................................................................................................................. 29
Sample and data selection................................................................................................................. 29
Part 5: Data Analysis................................................................................................................ 31
Descriptive statistics ......................................................................................................................... 31
Testing the model.............................................................................................................................. 33
Part 6: Empirical Results.......................................................................................................... 37
Regression analysis........................................................................................................................... 37
Results: US firms .............................................................................................................................. 38
Results: EMEA firms........................................................................................................................ 39
Part 7: Discussion and conclusion............................................................................................ 41
Discussion......................................................................................................................................... 41
Conclusion ........................................................................................................................................ 45
Limitations and Recommendations................................................................................................... 46
Part 8: References..................................................................................................................... 48
Part 9: Appendices ................................................................................................................... 51
List of Tables
Table 1 Essential differences between TRM and ERM ....................................................................... 12
Table 2 Variable definitions and expected signs.................................................................................. 29
Table 3 Descriptive Statistics Categorized by ERM rating.................................................................. 31
Table 4 Descriptive Statistics Categorized by Region and ERM rating............................................... 32
Table 5 Pearson Correlations total sample........................................................................................... 33
Table 6 Pearson Correlations for US firms .......................................................................................... 34
Table 7 Pearson Correlation for EMEA firms...................................................................................... 35
Table 8 Result of Regressions of ERM on Firm Value (Tobin’s Q) for total sample.......................... 37
Table 9 Result of Regressions of ERM on Firm Value (Tobin’s Q) for US Firms.............................. 38
Table 10 Result of Regressions of ERM on Firm Value (Tobin’s Q) for EMEA Firms...................... 39
List of Figures
Figure 1 Normality of error distribution histograms ............................................................................. 35

Part 1: Introduction
In the light of severe scandals over the last decades enterprise-wide risk management is
becoming a more widely known and used mechanism in modern risk management within
firms. Conventional risk measurement and control have shown to fall short managing
enterprise wide risks, such as with the fall down of Enron in 2001 and the Worldcom scandal
the year after, which led to the Sorbannes-Oxley act. While this act was generally to be
considered as the most severe measure since 1930, this regulating measure as well as other
measures was not able to control firm risks to prevent severe losses. In fact over the last
century there were several scandals and downfalls whereby risk-taking has played a major
role, such as the bankruptcy of Lehmann Brothers in 2008 and the UBS and Libor scandals. In
the official bankruptcy report of Lehmann Brothers, the main cause of the fall-down was the
excessive risk taking by the firm. More precisely, as McConnell (2012) explains, the lack of
properly managing and governing its strategic risk led to the total destruction of the entire
firm.
The financial crisis and the several other scandals that followed illustrate that something
needs to change in terms of risk management, in particular that risk management only as a
risk minimizing and reporting tool is not sufficient. Therefore, and for many other factors,
there is a need for better risk management methods that focus on enterprise wide risk
management. By coordinated enterprise wide risk management and the inclusion of strategic
risk in addition to traditional risks, Enterprise Risk Management seems to be the right
response to the need for better risk management. The challenge now is to how to convince
shareholders and senior management at firms to implement such an Enterprise Risk
Management framework. One of the ways to do that is to show that the implementation of
Enterprise Risk Management is a value maximizing tool, rather than an expensive and
complex tool. This study aims to assess whether ERM indeed created firm value.
First the value relevance of Traditional Risk Management (TRM) has already been generally
accepted and supported by empirical evidence. TRM is believed to provide a firm financial
flexibility by coping with the underinvestment problem, reducing cost of financial distress and
reducing expected taxes (Froot et al., 1993; Meulbroek, 2002; Smith and Stulz, 1985;
Weiying and Baofeng, 2008).

While the value relevance of traditional risk management on firm value is clear, there are
some shortfalls to the silo-based risk management approach. ERM theory takes risk
management one step further and suggests that by the central coordination and integration of
risk management in the firm’s strategy, further firm value can be created on top of the value
created by TRM. Furthermore as opposed to traditional risk management which is dominated
by the variance-minimizing thought (Stulz, 1996), the goal of Enterprise Risk Management
(ERM) is to coordinate risks as a whole in order to achieve the firm’s objective, which is
primarily thought to be the creation of shareholder value (COSO, 2004).
Theory suggests that ERM can create additional value compared with TRM in several ways.
By making use of natural hedges and only hedging away the residual risk, ERM can save on
the cost of risk management as it reduces the inefficiencies of the traditional practice of
managing each risk separately (Meulbroek, 2002; McShane et al., 2011). Secondly, and
probably most important, ERM can create additional value by providing base for a better
resource allocation throughout the firm, improving capital efficiency and return on capital
(Nocco and Stulz, 2006). Furthermore ERM improves transparency on a firm’s risk-profile,
reducing cost of external capital (Meulbroek, 2002). Finally by implementing ERM in the
firm strategy, it changes risk management from a defensive to an offensive way of managing
risk. In this way it enables management to anticipate emerging and strategic opportunities,
improving operational and strategic decision making and eventually leading to a higher
shareholder value. The question however is whether this additional firm value theory suggests
to create is recognized by a significantly higher firm value for firms adopting ERM as
opposed to firms using only TRM tools.
Only a small number of studies have focused on measuring the value creating ability of ERM
and the outcome of the studies are mixed. McShane et al. (2011) find a positive relationship
between firm value and the implementation of TRM but fail to find extra value created by
ERM. Pagach and Warr (2010) find that ERM is associated with a reduction in earnings
volatility, but cannot entirely relate this to an addition of value except for non-financial firms.
Liebenberg and Hoyt (2011) and Tahir and Razali (2011) do find positive a relationship
between firms adopting ERM and firm value, but fall short by focusing on certain industries
and geographical regions only.

Another major problem with previous studies is the lack of a good proxy in order to determine
the implementation of ERM. In the absence hereof most studies search for keywords as
CRO/ERM (Beasley et al., 2008; Liebenberg and Hoyt, 2011). McShane et al. (2011) had the
novelty to use the newly issued ERM ratings published by Standard & Poors (S&P), at that
time only available for financial firms (McShane et al., 2011). However S&P have recently
announced that for non-financial firms a new rating benchmark similar to the ERM rating, the
Management & Governance rating, shall be part of their ratings (S&P, 2012). The newly
issued Management & Governance rating enables the assessment of the implementation of
ERM for non-financial firms as it assesses the ability of senior management to manage firm
wide risk. And more importantly it links risk management to the management and governance
of a firm, which is of major importance for proper risk management as shown in the Lehman
example. This study would be the first to use the Management & Governance rating as a
proxy for determining the implementation of ERM.
The purpose of this study is to investigate whether the additional value ERM is considered to
create on top of TRM, actually leads to a higher firm value. Since the widely used Tobin’s Q
captures the future expectations of the shareholders in terms of firm value (Chappell and
Cheng, 1982) in this study this ratio is used as a benchmark to assess for recognition of value
created by ERM. Other than previous studies that mostly focused on financial firms, the focus
of this study is on non-financial United States (US) and European, Middle Eastern and
African (EMEA) firms. This allows extending the previous findings for financial firms, to
non-financial firms and to capture geographical differences.
The first part of this study contains a literature review with an introduction to the concept of
risk management and its development over time from insurance to ERM. Then the theory on
the value creating ability of traditional risk management, and specifically the additional value
creation mechanism of ERM, are discussed. The second part contains the research design and
methodology for this study. The third part of this study embodies the multiple regression data
analysis for determining whether the additional value created by ERM is recognized by
shareholders in terms of a higher firm’s value (Tobin’s Q). Finally in the last part the findings
are presented and are linked to previous findings, after which the conclusions and
recommendations from the study are drawn.

Part 2: Literature Review
From insurance to Enterprise Risk Management
This part discusses the development of risk management from insurance and hedging, which
other studies refer to as traditional risk management, to an enterprise wide risk management
framework. Second the value relevance of risk management and in particular the additional
value created by Enterprise Risk Management is discussed.
Traditional Risk Management
The first strand of risk management originates from the ability of firms to protect themselves
from basic risks such as natural disasters, accidents and errors, which are called the insurable
or “non-financial” risks (Culp, 2002). By buying insurance, firms could transfer these risks to
the insurer thereby mitigating the risks on these types. As firms’ interest in risk management
increased, due to value relevance which will be discussed later on, firms started to look into
alternative ways to manage risk. Financial risks such as credit risk, currency risk and
commodity prices were now being taken into account as well. At that same time investment
banks began developing financial risk instruments such as derivatives, hedges, futures and
options (Dickinson, 2001), leading to a more sophisticated way to manage risk or what is now
generally referred to as Traditional Risk Management (McShane et al. 2011; Liebenberg and
Hoyt, 2003; Dickinson, 2001; Gatzert and Martin, 2015).
Traditional Risk Management (TRM) is characterized by the categorization or so called “silo-
based” approach of managing risks (Dickinson, 2001), whereby each individual risk is
managed separately in a disaggregated method. In this so called “silo-based” approach each
firm risk, such as credit risk, currency risk, financial and market risk, is measured and
managed on a separate basis without taking into account any interrelationships of the separate
risks. Usually TRM is something that is decentralized and embedded into separate lower-level
departments such as treasury departments (Nocco and Stulz, 2006). These lower-level
departments are responsible for the day-to-day management of the risks as they are identified,
by buying insurance and hedging instruments in order to mitigate those risks. Which
immediately uncovers one of the problems with TRM, which is that risk is reported
afterwards, making this type of risk management retroactive. More recently other risks, such
as reputational and operational risk, were added to the cart and are mostly under the

management and responsibility of specialized departments as well, such as corporate
governance or corporate communication departments.
The traditional view on risk management is that the objective of TRM is to minimize variance
and therefore protecting the firm against adverse scenarios (Stulz, 1996 and Gatzert and
Martin, 2015). This variance-minimizing view focuses on the identification of risk as it
presents and the remediating action, such as hedging the risk to minimize its impact. As
shown before, most of times in retroactive management, when a risk is identified it is already
too late such as with the Lehman fall-down. Furthermore TRM is by its nature a tactical form
of managing risk, since it has a limited and narrow focus (Meulbroek, 2002). When assessing
and managing risk TRM does not take into account any correlations or interdependencies the
risk might have with other risks in the firm, but rather tries to manage the risk on itself. For
example, a department has entered into a contract to buy oil in USD and needs to pay the
supplier upon delivery in 6 months. If the department only has a Euro account, the traditional
view would be to hedge the currency risk by entering into a FX contract that will provide the
department with the USD amount at the time it is needed. What the traditional view does not
take into account is that there could be another department within the firm that at that same
time is long in USD and would like to have Euro’s. So basically the cost of hedging might
have been unnecessary in that case. More severe, TRM does not actively involve the
management of risk at senior management level, but rather it only focuses on identifying,
reporting and retroactive actions by senior management leaving no space for management to
make risk-return adjustments on time.
As a consequence over the last decades the traditional view of managing risk in a
decentralized way has shifted towards a more integrated approach. Several studies have urged
the need of a better and more holistic way of managing risk (Stulz, 1996, Froot and Stein,
1998 and Meulberg, 2002). In these studies the shortfalls of TRM are set out, which include
the lack of oversight, the inefficiency of managing risks on a separate base and the objective
to minimize risk rather than to optimize risk. Furthermore several cases in which hedging
decisions were made in lower tier departments caused devastating results for the firm as a
whole, such as with the Enron scandal, the fall-down of Lehman and more recently the
hedging activities by the Dutch housing corporation Vestia in 2011. These scandals have

pointed out that there is a need for a more resilient way to manage firm-wide risk. These
shortfalls eventually led to the concept of Enterprise Risk Management.
Enterprise Risk Management
Backed by the shortcomings of TRM and other internal and external factors, ERM has gained
field in corporate risk management over the last decades. Internal factors such as firm size,
volatility of earnings and stock prices are found to be positively related to the implementation
of ERM (Pagach and Warr, 2011). The main internal factors move firms to implement
comprehensive risk management frameworks in order to mitigate the risks of unexpectedly
large losses and to create value for shareholders, such as through the reduction of
inefficiencies from traditional risk management, the stabilization of earnings and more
importantly the improvement of the firm wide risk-return tradeoff (Meulbroek, 2002;
Miccolis and Shah, 2000; Cumming and Hirtle, 2001). The more a firm grows the more
traditional risk management, whereby risks are typically managed in separate silo’s (Kleffner
et al., 2003), is not sufficient to meet the need to keep oversight of all the risks a firm faces.
By making use of ERM, management throughout the firm can easier make risk-return trade-
offs, which helps in making decisions as well as to identify issues before they become real
problems and improve capital efficiency. This is in line with the shifting view on risk
management as a risk reducing mechanism to a shareholder value creation view, which will
be commented on in the next section.
Secondly external factors such as globalization, industry and region specific factors have also
led to a growing need for an enterprise wide risk management (Liebenberg and Hoyt, 2003).
Due to globalization firms now are more exposed to different kind of risks that are often
interdependent with each other, for example currency and other regional risks and therefore
have to adapt and take into consideration their total risk exposure. Last but certainly not least,
as mentioned earlier the several scandals and crises have led to increasing regulatory
requirements in terms of risk management. Requirements for internal controls enhancing risk
control and corporate governance have been imposed by regulators such as the New York
Stock Exchange, London Stock Exchange and the Committee of Sponsoring Organizations of
the Treadway Commission (COSO) (Miccolis and Shah, 2000; COSO, 2004). For example
the Sorbannes-Oxley Act, that was enacted as a reaction to the Enron and Worldcom scandals,

directed risk management to be a top-down assessment requiring management to take explicit
responsibility for the entire firm’s risk management. These kind of regulatory factors are in
particular imposed to specific industries, such as the financial services industry after the 2008
subprime crisis and the energy industry as a result of the Enron scandal.
In 2004 the well-respected Committee of Sponsoring Organizations of the Treadway
Commission (COSO) issued a publication in which they set out a framework for ERM
integration. In their publication the COSO identifies that the primary element of ERM is that a
firm exists to provide shareholder value, and that in order to maximize shareholder value
management needs to “manage the risk to be within its risk appetite” (COSO, 2004).
Although in the literature there is some indefiniteness on what ERM exactly entails, following
a literature review on ERM, Bromily et al. (2015) conclude that the consensus is that the core
elements of ERM consist of a) management of risks as portfolio instead of in tranches b) the
inclusion of strategic risk in addition to traditional risk and c) to use risk to create competitive
advantage instead of looking at risk as a problem. These core elements of ERM are in line
with the COSO (2004) and S&P’s (2012) view of ERM, which includes strategic and
operational alignment (management), and to enhance the reliability of reporting and comply
with applicable laws and regulations (governance).
In line with this concluded consensus, in their framework the COSO provides a broad
definition covering these aspects of ERM:
“Enterprise risk management is a process, effected by an entity’s board of directors,
management and other personnel, applied in strategy setting and across the enterprise,
designed to identify potential events that may affect the entity, and manage risk to be within
its risk appetite, to provide reasonable assurance regarding the achievement of entity
objectives.” (COSO, 2004)
The fundamental way in which ERM differs from TRM is that it has a holistic view on
managing risk, rather than a silo-based view. By managing firm risks in an integrated way,
ERM enables the assessment of the interaction of each risk with other risks (Froot and Stein,
1998) which can be an important value adding mechanism as is shown in the next section.

With its broad enterprise wide scope, ERM differs from traditional risk management by
coordination of risks as a whole in order to achieve entity objectives (COSO, 2004) as
opposed to assessing risks on their own basis as with the traditional variance-minimizing view
(Stulz, 1996). This difference in the objective of risk management might be the most
important between ERM and TRM in terms of adding value. While traditional risk
management views risk as something that must be mitigated and taken care of in order to
minimize the down-side of risk, ERM views risk as a tool to optimize risk in order to serve
the firm’s overall goal, which is to create shareholder value. In order to achieve this objective
ERM dictates that risk management should be incorporated in the firm’s strategy, enabling a
top-down risk management direction by senior management instead of decentralization of
risk. As previously discussed, this should prevent cases such as the fall-down of Lehman and
the Vestia case. Along the same line, another difference with traditional risk management is
the offensive rather than defensive view of ERM as value adding mechanism (Gatzert and
Martin, 2015). ERM tends to proactively identify and assess risks before they affect the firm.
Finally since risk management is embedded in lower-level departments with TRM it is hard
for senior-management and outsiders to assess if a firm is managing its risks in the right way.
With ERM’s coordinated view the firm’s risks are clearly stated and directly linked to the
firm’s strategic objective, which enables both senior-management to keep oversight and steer
if needed. As the firm could then be more open with regards to its risk-profile this provides
outsiders, such as providers of external debt, with the ability to better make an assessment of
the firm’s risk profile. The differences between TRM and ERM are summarized in Table 1.
Table 1
Essential differences between TRM and ERM
This table contains the essential differences between Traditional Risk Management (TRM) and Enterprise Risk Management
(ERM) as found in the literature and presented in part 2 of this study.
Traditional Risk Management Enterprise Risk Management
Objective to protect downside risks Objective to create shareholder value
Silo-based view Portfolio view
Focus on variance-minimization Focus on optimization of risk
Reactive approach Proactive approach
Decentralized Top-down management tool
Opaque Transparent
Tactical Strategic

Value relevance of risk management
Now that the differences in the conceptual frameworks of TRM and ERM have been
discussed, this section discusses the value relevance of risk management in general and then
turns to the way in which ERM is believed to create additional value on top of TRM.
Under perfect market conditions the Modigliani and Miller proposition (1958) states that
capital allocation would be a waste of value. Moreover, since investors should be able to
diversify risk by their optimal portfolio (Markowitz, 1952), risk management would be
irrelevant and any effort inserted in it would be a waste. The problem however is that this
perfect market does not exist in the real world as there are market imperfections such as
transaction cost, bankruptcy cost, taxes, agency cost and cost of external capital. The
existence of these real world cost have driven academic research to argue that risk
management can actually create value, amongst others by reducing the probability that such
cost would be imposed.
Mayers and Smith (1982) showed that corporate insurance contracts could be used to manage
these real world cost. In their paper they emphasize that corporate insurance can mitigate a
firm’s risk by lowering expected cost of bankruptcy, expected tax liabilities and reduce
regulatory cost. Further studies have broadened this view and proposed that risk management
can have value increasing advantages, mainly driven by the same defensive view that a
reduction of expected cost can increase firm value. While new risk management instruments
such as hedging took over from corporate insurance, traditional risk management became a
way for firms to reduce risks once they were identified.
Later on Froot et al. (1993) published a paper partially turning the view of value creation by
cost reduction. In their paper they state that the main way in which traditional risk
management is believed to create value is that it provides financial flexibility, which in turn
enables a firm to cope with the underinvestment problem (Froot et al., 1993). Risk
management does this by improving a firm’s ability to take advantage of attractive investment
opportunities as they are identified by reducing the firm’s cash flow volatility. As illustrated
by Nocco and Stulz (2006), if a firm experiences a temporary shortfall in cash flow it could
lead to the passing up of positive net present value investments that require immediate

funding. In this way the cost of the shortfall in cash flow not only leads to a temporary loss,
more severely the passing up of positive present value investments leads to a permanent
reduction of firm value. To illustrate, when a firm does not have sufficient internal funds at
the time a NPV investment is identified, it is bound to either let the opportunity pass or by
requesting additional external funding. This funding would be more expensive than internal
funding as in case of external funding the cost of capital would be increased leading to a less
NPV of the investment. In addition external financing would also lead to more leverage which
would further increase the cost of capital. The firm could also turn to funding by its
shareholders, however requesting for additional funding often comes with higher cost than
when funds are internally funded leading to higher discount rates which in turn could lead to
either the investment having a negative NPV or the shareholders to find the project not
profitable enough. This underinvestment problem is the believed to be the most important
reason for a firm to perform risk management. Traditional risk management is believed to
cope with this underinvestment problem by lowering cash flow volatility and thereby
providing internal funding possibilities and reducing cost of capital (Froot et al., 1993;
Meulbroek, 2002; Weiying and Baofeng, 2008). In this way traditional risk management
should be able to enhance the firm’s ability to carry out its business plan by investing in NPV
projects. Besides this main advantage, there are several other ways in which traditional risk
management can create firm value. Traditional risk management is believed to reduce
expected tax liabilities by smoothening the firm’s earnings (Smith and Stulz, 1985). The
rationale behind this is that in case of volatile yearly earnings the firm’s tax liabilities are
expected to be higher. The expectation for higher taxes is related to the inability to fully carry
forward the firm’s losses to be set of in future years’ profits, as well as the progressive tax
rates which result in a higher effective tax liability than when the earnings would be
smoothened throughout the years. Moreover traditional risk management is value creating by
reducing the probability of financial distress and the cost related to such a distress.
Additional value created by Enterprise Risk Management
While the value relevance of traditional risk management on firm value is clear, there are
some shortfalls to the silo-based risk management approach of TRM. Theory suggests that
ERM can further create firm value on top of TRM, as Nocco and Stulz (2006) conclude:
“Companies that succeed in creating an effective ERM have a long-run competitive

advantage over those that manage and monitor risks individually”. This value creation is
believed to happen in the following ways.
The main way in which ERM differs from TRM and is able to create value is that it is guided
by the comparative advantage in risk-bearing (Stulz, 1996 and Nocco and Stulz, 2006). The
rationale behind this is that a firm should be reducing risks where it does not have a
comparative advantage, and should take more business and strategic risks where it expects to
have a comparative advantage over other firms. To illustrate, if a firm trades in oil its core risk
is the trading in oil. The firm should expect a positive NPV from its oil trading activities
because it believes it has a comparative advantage over other firms through e.g. experience
and knowledge, otherwise it would not be a good idea for the firm to engage in oil trading.
The trading of oil therefore is the firm’s core strategic and business risk. The other risks, for
example the risk that the USD decreases (currency risk) or that the risk that the firm fails on
interest payments, are so called non-core risks. It is likely that the firm does not have specific
information by which it has a comparative advantage in bearing these risks, and therefore
ERM suggests that the firm should transfer these risks. In this way the firm should be able to
lay-off its exposure to non-core risks, while enhancing the ability to take more strategic and
business risk where it has a comparative advantage. By taking more strategic and business
risk the firm can optimize its risk management which enables the firm to better pursue its
main objective, namely to create shareholder value.
Secondly Nocco and Stulz (2006) explain in their paper that ERM can create shareholder
value by embedding ERM in firm strategy. In this way they argue ERM enables firms to
better allocate its capital through improved selection investments on a better risk-return rate
than under the TRM approach, eventually increasing shareholder value. The implementation
of ERM is said to improve the assessment and management of the firm-wide risk and return
tradeoff. By assessing each investment that can possibly have a material impact on the firm’s
risk, managers throughout are better able to assess whether the investment is sufficiently
profitable to provide an adequate return as compared to the investment’s risk. This risk-return
tradeoff is important as each decision that might increase the total risk of a firm could lead to
higher cost of capital and the passing up of otherwise positive NPV investments. By
implementing a more apprehensive understanding of the firm wide risk-return rates, the

investment decisions and capital allocation in different levels of the firm can be improved.
Nocco and Stulz (2006) emphasize that the role of the CRO herein is crucial. The CRO
however cannot review each investment decision throughout the firm, as that would cause
hick-ups in the operating process. Therefore they claim that the CRO’s role should be that of
making available the right information regarding the analysis for the risk-return tradeoff and
by setting (lower-) management performance measures to evaluate management. In this way
they suggest that by forcing each manager throughout the firm to take into account the firm-
wide risk implications of his/her investment decision, this would lead to a better risk-return
tradeoff. Eventually this affects the firm’s enterprise wide performance, leading to an
improvement of capital efficiency and return on capital, which in turn increases shareholder
value (Liebenberg and Hoyt, 2011; Nocco and Stulz, 1996; Meulbroek, 2002). Empirical
evidence for this increase in return on capital, or otherwise stated as return on assets (RoA),
was found by Grace et al. (2015).
Another way of the abilities of ERM to contribute to a further increase in shareholder value is
by reducing the inefficiencies of managing risks in separate silo’s as is the case with TRM. By
the portfolio view of ERM interdependencies and correlations between risks can be identified.
By making use of natural hedges and hedging the residual risk of the portfolio, it is a far more
efficient way to manage risk. In addition by applying the concept of portfolio theory in this
way ERM can create shareholder value, as the risk of the combined portfolio should be less
than the sum of the individual risks and hence expenditures on risk management can be
minimized.
Finally ERM can even help a firm get to better access the external capital markets at lower
rates due to its transparency on its risk-profile. While in TRM a firm’s risk is opaque, ERM
enables opaque firms to be more transparent in terms of their riskiness (Liebenberg and Hoyt,
2011). Usually outside investors such as external capital providers can only estimate a firm’s
systemic risk by a firm’s past equity return volatility, and not on any other information.
Therefore outside investors often calculate risk premiums for this opaqueness. With a better
ability to determine a firm’s risk profile and to disclose these to external capital providers, it is
likely that outside investors would lower the risk premium in return and therewith reducing
the costs of external capital to the firm (Meulbroek, 2002). Rating agencies such as S&P have

therefore already extended their analysis to include measures on ERM implementation as a
part of their credit rating. The lower cost of capital should reduce the discount rate at which a
firm is valued, increasing the firm value and hence increasing shareholder value.
Current state of literature
Most of the studies imply and conclude that, in theory, ERM should be value creating.
Therefore ERM has earned itself much interest from academic researchers. Lately ERM has
been topic of interest in many studies and in particular studies concerning the implementation
of ERM (Beasley, Clune and Hermanson, 2005) and to a lesser extent on the value creation
part of ERM.
The majority of earlier studies found a somewhat mixed relationship between firms adopting
ERM and firm value (Gatzert and Martin, 2015). While some study results suggest that ERM
creates shareholder value, the studies fall short in the generalization of these findings due to
the focus on certain industries only. Liebenberg and Hoyt (2011) and McShane et al. (2011)
for example focus only on the impact of ERM on firm value for insurance firms. In their study
Liebenberg and Hoyt (2011) focused on 117 US insurers and found a significant positive
relation between firm value (Tobin’s Q) and ERM. According to their results the value
creation of ERM amounted to nearly 20%.
However McShane et al. (2011) focus on 82 publically traded insurers and only found a
significant positive relationship between an insurer’s ERM rating and firm value (Tobin’s Q)
up to a certain level of implementation. In their believe the significant positive relationship is
present in the first three notches of the ERM rating, which they define as the implementation
of traditional risk management, but flattens out for the last two notches which in their believe
capture the implementation of ERM. Their result is interesting since this implies that for their
sample there is no empirical evidence that ERM can create value on top of TRM. Or at least,
that the possible additional value creation is not recognized by shareholders in their firm
value. Since both studies focus on the insurance industry only, it does not necessarily mean
that their conclusions on value creation of ERM hold in other industries as well.

Gordon et al. (2009) performed a more diversified study on a sample of 112 US firms. Their
study is limited in the way that they focus on firm performance rather than firm value and
therefore use the one-year excess stock market returns as a measurement tool. As they
recognize themselves this is one of the limitations of their study and their suggestion is that
Tobin’s Q might be a better measurement tool. Nevertheless they found a significant positive
relationship for the impact of ERM on firm performance, in line with other studies focusing
on firm performance (Grace et al, 2015; Pagach and Warr, 2010). Beasley et al. (2008)
furthermore investigated the impact of ERM on shareholder value, but estimating the value
created with an equity market reaction. They find no significant equity market reaction,
except for non-financial firms. Finally Tahir and Razali (2011) present mixed findings. Their
conclusion is that there is a positive but not significant relationship between ERM and firm
value (Tobin’s Q) for Malaysian firms. Noteworthy is however that while the correlation
matrix shows a positive relationship, their regression coefficient for ERM is negative,
suggesting that their conclusion might not be fully supported by their results.
Benchmark for ERM
As mentioned in the introduction another major problem with previous studies is the lack of a
good proxy to determine the implementation of ERM in firms. As Gatzert and Martin (2015)
point out in their literature study, the main challenge is the poor availability of data regarding
the degree of implementation of ERM. Therefore most studies were bound to come up with
their own ERM benchmark, and then perform a search for keywords through financial
statements. The majority of the studies use the appointment of a CRO as a proxy (Beasley et
al., 2008; Liebenberg and Hoyt, 2011) while others create their own ERM index (Gordon,
Loeb and Tseng, 2009). The use of a CRO appointment as a proxy for example does not cover
the degree of implementation of ERM. More severely the appointment of a CRO is a
quantitative measure rather than a qualitative, as it could be that an appointment of a CRO is
more of a change of title than the start of the actual implementation of ERM (Beasley et al.,
2008). McShane et al. (2011) had the novelty to use the newly issued ERM ratings published
by Standard and Poors (S&P), at that time only available for financial firms (McShane et al.,
2011).

Standard & Poor’s Management & Governance rating
The lack of a good and universal proxy for ERM implementation is therefore one of the major
challenges. For a long time there was no good proxy available for non-financial that
represents the ERM implementation as set forth in COSO (2004). However as discussed
previously, rating agencies are showing an increasing interest in firm’s ERM implementation
and are embedding ERM as a factor in their credit ratings. In the light of this S&P have
recently announced that their efforts in embedding ERM in their credit ratings have finally
ended up in a new rating benchmark for non-financial firms, the Management & Governance
rating. This rating which is comparable to the ERM rating they issued for financial firms shall
be part of their credit ratings going forward (S&P, 2012). The criteria of the Management &
Governance rating are highly in line with the criteria for ERM implementation as defined by
COSO (2014). These include the most important factors such as the firm-wide management of
risk as a whole, the alignment of risk management with the firm’s strategy and the
management’s ability to use ERM to achieve firm objectives. The Management &
Governance rating improves the assessment of the value recognition of ERM for non-
financial firms as it provides an easier and unambiguous way to determine whether a firm
implemented ERM. The Management & Governance score shall be further introduced in
detail in part 4 of this study.
Summarizing it can be said that the main problem with the current literature is the lack of
generalized results for ERM’s impact on firm value on top of TRM, and the lack of a good
proxy to assess the implementation of ERM. Gatzert and Martin (2015) add that future
research should also aim for larger and international data samples in order to control for
geographical differences. Taking into account the little research done of ERM on firm value
on non-financial firms and the lack of a good proxy in previous studies, the main purpose of
this study is to assess the relationship between the additional value created by ERM for non-
financial firms and the shareholders’ recognition of this value for US and EMEA firms. The
widely used Tobin’s Q (Tobin and Brainard, 1968) will be used as a proxy to estimate the
value-effect of ERM. To the best of knowledge this would be the first study to use the
Management & Governance rating as a proxy for determining the implementation of ERM.
The next part sets out the research design by which this study investigates whether the
additional value ERM is believed to create is embedded in firm value.

Part 3: Research Design
Main research question
As previously stated the main purpose of this study is to assess whether ERM is able to create
additional firm value on top of the value created by TRM. Therefore the main research
question for the purpose of this study is formulated as follows:
“Does Enterprise Risk Management create shareholder value?”
More specifically the study looks to answer whether shareholders recognize the theory that
ERM can create additional value and therefore value firms that engage in ERM higher, as
opposed to firms not engaging in ERM. As previous literature focused on financial firms only,
this study investigates the value creation for non-financial firms. Firm value is measured
using Tobin’s Q since it captures the shareholders’ expectations of the profitability of the
firm, and will be discussed in more detail in part 4 of this study. The intention is to measure
whether ERM is perceived by shareholders as a value adding tool, which might motivate
firms not yet using ERM to implement it.
Hypothesis development
As set out in part 2 of this study, based on the theoretical framework and findings in previous
literature (Meulbroek, 2002; Nocco and Stulz, 2006) it is assumed that ERM creates
additional value on top of TRM, and that therefore firm value should increase as a result of
implementation of ERM. Accordingly in order to answer the main research question of this
study, the main hypothesis is formulated as follows:
H1: There is a positive and significant relationship between the implementation of ERM and
firm value for non-financial US and EMEA firms, as compared to firms using TRM.
Before the relationship between value creation by ERM and its recognition by shareholders
can be measured and in order to answer the main question of this study, the research question
is broken-down into more feasible sub-questions.

1.1 What is the difference between Traditional Risk Management and Enterprise Risk
Management?
Before being able to assess whether ERM creates firm value on top of TRM it is essential to
make a clear distinction between the two. Therefore the first sub-question relates to defining
the concept of ERM. In this part of the study the increasing interest in ERM and in particular
the differences with traditional risk management and the characteristics of ERM are
discussed. Defining ERM is mainly of importance in order to be able to distinguish between
firms that implemented ERM and firms that are assumed to engage in what is defined as
TRM.
1.2 How does Enterprise Risk Management create additional shareholder value?
Next in answering the main question is the theory on how ERM is suggested to create
additional firm value on top of the value created by TRM. The results from previous literature
together with the findings of this study will be used to answer this sub-question. Hereby the
theory in previous literature is discussed as well as empirical evidence that such a relationship
between ERM and firm value exists. This section will be useful in answering the question
whether ERM creates additional value as compared to TRM. The measurability of value
drivers however is somehow complex. Theory suggests that the main value drivers for ERM
are the ability to gain or maintain a comparative advantage and the ability to improve the
capital allocation. Increases in comparative advantages are however not easily measurable,
although there are methods to measure comparative advantages it would take an extensive
research to determine whether or not comparative advantage is improved. The latter is better
measurable, since theory implies that the better capital allocation together with the improved
risk-return tradeoff should lead to an increase in return on capital for the firm, eventually
leading to a higher firm value. Therefore it is hypothesized that firms that implemented ERM
will have a higher return on capital. The second hypothesis therefore is:
H2: Firms engaging in ERM have a higher return on capital as compared to firms engaging
in TRM.

In addition theory suggests that ERM could lead to lower cost of external debt. However since
most of the data on cost of debt is not available for our dataset, the study does not take into
account this value-driver and leaves it for future research.
1.3 How is the implementation of Enterprise Risk Management determined?
Subsequently the next question is how to determine the degree of implementation of ERM in
a firm. As discussed in the introduction, this has proven to be one of the most challenging
parts in previous studies. The importance of a clear benchmark that qualitatively measures the
implementation of ERM is essential, as only then one is able to distinguish between ERM and
non-ERM using firms. Therefore the introduction of the Management & Governance score as
a benchmark for implementation of ERM will be discussed in detail in part 4 of this study.
1.4 How is the value created by Enterprise Risk Management measured?
The essential piece to answer the main question is to determine how the recognition of the
value created by ERM is measured. This study tries to explain whether the implicated value
creation by ERM is actually recognized by shareholders by means of a change in firm value.
As will be shown in part 4 Tobin’s Q is found to be the most appropriate measurement tool
for this. Therefore the main focus lies on the influence of ERM as an independent variable on
Tobin’s Q. Other independent variables that are known to influence firm value are taken into
account in order to control for changes in Tobin’s Q not related to ERM. After having defined
the determinants of firm value next is the empirical part of this study.
1.5 Does a relationship exist between Enterprise Risk Management and Firm Value?
To come to a verdict whether there is a relationship between the value ERM is thought to
create and the actual value created in terms of firm value, the relationship is put to the test in a
multiple regression data analysis. The focus will be on the relationship between the main
research variable ERM and Tobin’s Q ratio, as compared to firms assumed to be engaged in
TRM. In particular the amount of variance in Tobin’s Q that is captured by ERM, after
controlling for other variables, will be assessed in this section. Based on previous literature in
general ERM is predicted to have a positive impact on firm value.

1.6 What is the impact of region on the relationship between ERM and firm value?
However, as previously indicated another aim of this study is to determine whether there are
regional differences in the recognition of the value created by ERM. Previous studies have
revealed that in the US it seems that ERM is found positively associated with firm value for
financial firms, results from other regions such as Malaysia however do not show a significant
relationship. Therefore this study would like to capture if there is a difference between US
and EMEA firms, leading to the following hypotheses.
H3: Geographic differences between US and EMEA firms alter the effect of ERM
implementation on firm value.
1.7 How do these findings fit into previous findings of Enterprise Risk Management’s value
creation?
Finally the results and findings of the data analysis are reviewed against the findings in other
researches on value creation of ERM and how our findings fit in it. This might give insight
into the recognition of the value of ERM by shareholders. Which in turn lead to the question
about what can be done with this information, which will be part of the discussion at the end
of this study.

Part 4: Methodology
The second part of this study contains the empirical research to test the hypotheses mentioned
before and to formulate an answer to the main research question. The method, variables and
sample data used to test the hypotheses are set forth in this part.
For the purpose of this study the only interest is in the value recognition of shareholders, as in
order for ERM to effectively create value for its shareholders, this has to be reflected or better
said recognized by the shareholders in the firm’s value. Therefore the widely used Tobin’s Q
is introduced as a proxy to determine the firm value (Smithson & Simkins, 2005; McShane et
al., 2011). The next section describes the method, sample construction and explains some
assumptions for the cross sectional data analysis.
Method
In order to be able to investigate whether a relationship exists between the implementation of
ERM and firm value first a cross sectional data analysis will be performed. There are several
reasons for using a cross sectional data analysis. First, in this way the effect of ERM on firm
value can be analyzed in a clear way while controlling for other variables that are known to
effect firm value. Secondly the data on ERM implementation, the Management & Governance
score, is published at a given point in time. Finally there is no time lag effect of ERM
implementation since firm value is measured by Tobin’s Q, which already includes the
expected future firm value. The advantage of using a cross-sectional data analysis is that it is a
quick and effective method and is useful to provide answers to our hypotheses.
As there are several variables known to have an effect on firm value, multiple linear
regression analysis will be used for determining whether the value created by ERM is
recognized by shareholders in terms of a higher firm value. An advantage of multiple linear
regressions is that the regression makes it easy to compare the relative importance of a
variable to the other variables. As previous studies mostly use multiple linear regressions as
well, it enables comparing the findings of this study with their findings. As multiple linear
regressions are known to be sensitive to (multi)collinearity, an extra check on this will be
performed to make sure this does not affect the outcome of the regression coefficient. Next
the dependent and independent variables for the regression will be discussed.

Variable motivation
Dependent variable: Firm Value
Starting with the dependent variable, in line with previous studies on firm value the dependent
variable in our regression is the widely used Tobin’s Q. Tobin’s Q is particularly useful since
it captures investor’s future expectations on firm value at a certain point in time, overcoming
the time lag between the implementation of ERM and its effect in terms of creation
shareholder value (Hoyt and Liebenberg, 2008). In addition other than with other measures,
there is no requirement to adjust or normalize Tobin’s Q (Lang and Stulz, 1994). Tobin’s Q is
defined as the market value of equity plus the book value of liabilities divided by the book
value of assets (Cummins, Lewis, and Wei, 2006; Kubota, Saito and Takehara, 2013).
The data used will be on the market value of equity, which is defined as the shareprice * the
shares outstanding (Rappaport, 1986). Tobin’s Q measures the firm’s market value against its
book value, so an increase in Tobin’s Q implies that a higher value of the firm is expected.
This is relevant for our study as the valuation of the equity market value of the firm captures
the value shareholders are willing to pay. Corporate Valuation techniques are not taken into
account because they also incorporate the valuation of the firm by outsiders, other than direct
shareholders.
Independent variable of interest
Secondly in order to capture the implementation of ERM in firms the dummy variable ERM is
the main independent variable in our regression. As earlier mentioned, S&P had implemented
a benchmark proxy for ERM measurement for insurance firms with their ERM rating
announcement in 2008, which was the base for McShane et al. (2011). Unfortunately at that
time S&P’s ERM rating was limited to insurance firms only, and so McShane et al.’s study
was limited to this sector as well. In their study they acknowledge that in case such a proxy
existed for non-insurance firms as well, the impact of ERM on firm value could be
generalized. This is also set forth in a comparative assessment study by Gatzert and Martin
(2015) where it was recommended that further research using larger and international data
samples would be necessary, in particular to reveal geographical and industrial differences.

S&P have recently announced that for non-financial firms a new rating benchmark, the
Management & Governance rating, similar to the ERM rating that was already available for
insurance firms shall be part of their ratings (S&P, 2012). The criteria of the Management &
Governance rating are highly in line with the criteria for ERM implementation as defined by
COSO (2014). Same as with the COSO ERM framework S&P distinguishes between
Management & Governance objectives for ERM. The Management & Governance rating
assesses the ability of management to effectively implement and manage risk throughout the
firm. These include the firm-wide management of risk as a whole, the alignment of risk
management with the firm’s strategy and the management’s ability to use ERM to achieve
firm objectives. The top-down view of risk management is important as mentioned
previously. S&P shares this view and summarizes this as follows:
“Their strategic competence, operational effectiveness, and ability to manage risks shape an
enterprise's competitiveness in the marketplace and credit profile. If an enterprise has the
ability to manage important strategic and operating risks, then its management plays a
positive role in determining its operational success.” (S&P, 2012)
The Management & Governance rating (S&P, 2012) measures the strategic positioning,
organizational effectiveness as well as the comprehensiveness of enterprise wide risk
management in a firm. In addition the rating takes into account governance sub-factors such
as reporting and compliance, which are used to alter the Management and Governance rating
for governance shortfalls. The main reason why this benchmark is better than other
benchmarks used in previous studies is because it is a qualitative rather than quantitative
measurement tool. Other studies have mostly used the appointment of a CRO as the
assumption that ERM is in place. In fact such a benchmark neither reveals whether ERM is
actually in place nor the degree of implementation of ERM.
For the purpose of determining whether a firm implemented ERM, the S&P’s Management &
Governance rating will be used as a dummy variable. On 13 May 2013 S&P announced that it
had completed the Management & Governance rating for all US and EMEA non-financial
firms, however only the highest and lowest ratings for publically rated firms were published

in this announcement. Although this is a limitation to this study, the impact of the
unavailability of more detailed ratings should be rather small. Using the highest and lowest
scores will still enable to distinguish between firms that implemented ERM and firms that did
not, which are assumed to engage in TRM. This assumption is backed by the fact that
publically listed firms will have engagement in TRM as they are required to do so by stock
exchange requirements for listing and by internal control requirements such as the Sorbannes-
Oxley Act. The only limitation is that the study cannot fully capture the exact relationship
between the level of implementation and the effect on firm value. As a consequence the
Management & Governance rating’s highest score it will be assumed that ERM is well
implemented, and the dummy variable ERM is valued one. For the lowest score firms will
assumed to be engaged in TRM, leading to the dummy variable ERM to be valued zero.
Control variables
In order to control for differences in Tobin’s Q other than due to ERM, the independent
variables known to significantly impact Tobin’s Q will be part of the regression. Based on
earlier research (Stevens, 1986, Allen and Rai, 1996, Hoyt and Liebenberg, 2011, Lang and
Stulz, 1994 and McShane et al, 2011) firm Size, Leverage, Profitability and Dividend Payout
are the most commonly used control variables in Tobin’s Q equations.
Size: While size is often used in Tobin’s Q equations the empirical results regarding the effect
of the variable on Tobin’s Q are not conclusive. In some of the literature size is found to be
positively related to Tobin’s Q mainly because of economies of scale that go with larger firms
(McShane et al, 2011). However there are other studies whereby size is negatively related to
Tobin’s Q, as it is assumed that larger firms will face more agency problems (Lang and Stulz,
1994). This study follows the results presented by McShane et al. (2011) and argues that size
is predicted to be positively related to Tobin’s Q. This study follows previous studies and
defines size as the natural log of a firm’s total assets.
Leverage: As discussed before, in a perfect world with perfect markets the capital structure of
a firm would not be relevant to firm value. However since no perfect markets exist in the real
world the capital structure of a firm might indeed alter its firm value. As leverage makes a
firm more risky, the discount rate at which a firm is valued by shareholders will likely go up,

simply as shareholders would like to get a premium over the higher risk they bear. This study
therefore argues that leverage would have a negative effect on firm value in line with the
findings of previous studies (McShane et al., 2011; Liebenberg and Hoyt, 2011). Leverage is
defined as the total liabilities divided by the market value of equity.
Profitability: As generally adopted and presented by previous studies, profitable firms are
likely to have higher firm value (Allayannis and Weston, 2001). Therefore this study predicts
that profitability as a control variable is positively associated with Tobin’s Q, in line with
other studies. Profitability is defined as the return on assets (RoA).
Dividend: This study also follows Liebenberg and Hoyt (2011) in controlling for dividend
payout policy’s effect on firm value. As they discussed in their paper according to dividend
payout can have both a positive and a negative effect on firm value. While they argue that
dividend payout policy might have a negative impact on firm value, as supported by literature
(Stevens, 1986; Lang and Stulz, 1996), their finding as not in line with literature as they find
dividend payout to be positively correlated to Tobin’s Q. This study however follow the
literature by predicting that dividend payout negatively affects Tobin’s Q. Dividend payout is
defined by a dummy variable that is 1 when dividend was paid out, and 0 otherwise.
The number of variables has been kept small in order to avoid the problem of capitalizing on
chance. The predicted signs for each of the variables are given in Table 2. As the study takes
into account US and EMEA firms a dummy variable is added to control for possible
geographical differences. Finally a dummy variable for the Financial Year is added in order to
check for time-series differences.

Model building
All these data are analyzed using the data analysis package of SPSS to regress the
independent variables against the dependent variable Tobin’s Q, as follows:
Tobin’s Q (firm value) = β1 ERM Dummy + β2 Size +β3 Leverage+ β4 Profitability + β5
Dividend + ε
Table 2
Variable definitions and expected signs
This table presents the variables used in the model to predict firm value (Tobin’s Q). The predicted signs of the main variable
of interest ERM and the control variables are included, based on previous literature as discussed in the variable motivation.
The definition of the variables and the source from where the variables have been extracted is shown below.
Variable Expected
sign
Definition Source
Firm Value (Tobin’s Q) Share price * no. of shares outstanding (PRCCD * CSHOC + LT) / AT
(COMPUSTAT)
ERM + “Strong” M&G = 1, “Weak” M&G = 0 Management & Governance scores
S&P (2013)
Size - Ln of total assets at T Ln of AT (COMPUSTAT)
Leverage - Total Liabilities / Market Value of
Equity at T
LT / (PRCCD * CSHOC)
(COMPUSTAT)
Profitability + Return on Assets at T NI / AT (COMPUSTAT)
Dividends - Dividend paid in FY at T = 1, otherwise
0
DIV (COMPUSTAT)
Year dummy In order to control for changes in
financial years a year dummy is added
FYEAR (COMPUSTAT)
Geographic region
dummy
In order to control for geographic
differences a region dummy is added.
FIC (COMPUSTAT)
Sample and data selection
For the first theoretical part literature available from the Tilburg University literature library
will be used, in particular the papers by Gatzert et al. (2015) and Nocco et al. (2006) give an
introduction into the main concepts of value creation through ERM. Furthermore for the
definition and core elements of ERM the COSO Enterprise Risk Management Framework
(COSO, 2004) will be used.

For the empirical part of the study the data from S&P regarding the Management &
Governance score for firms will be gathered using S&P’s ratings reports which are publically
available. As mentioned the sample is limited to the publically rated firms in the US and
EMEA and only for the highest and lowest notch. Furthermore firms for which data on
control variables were not available have been dropped.
In addition in order to calculate Tobin’s Q the firms have to be publically listed. The main
data sample is for the year 2013, the same year at which the Management & Governance
score became available. Therefore the final sample size is 214 firms, consisting of 129 US
firms and is 85 EMEA firms. The data for the control variables was gathered using the
CompuStat database, as specified in Table 2.

Part 5: Data Analysis
Table 3
Descriptive Statistics Categorized by ERM rating
Table 3 summarizes the descriptive statistics for the sample used in the study’s model. The
below reports the mean values for the variables used, categorized by the firms ERM rating.
The descriptive statistics show that for the total sample Firm Value is higher for the ERM
firms compared to the TRM firms. Furthermore the ERM firms are larger in terms of size, less
leveraged more profitable and have a higher dividend payout ratio. The variable definitions
are provided in Table 2
ERM
Number
of firms
Firm Value
(Tobin's Q) Size Leverage Profitability Dividends
0 27 1.7132 9.0729 3.2680 -0.0004 0.3704
1 187 2.0304 10.1675 0.7153 0.0722 0.8182
Total 214 1.9904 10.0294 1.0374 0.0631 0.7617
Descriptive statistics
Table 3 shows the descriptive statistics for the sample including the mean values for each of
the variables categorized by their ERM rating. The mean values for Firm Value (Tobin’s Q)
are in line with our expectations, namely that there is a positive relationship between a higher
ERM rating and Firm Value. Noteworthy are the high number of firms having a “strong”
ERM rating, this can be explained due to the fact that there are more “strong” ERM firms
presented in the S&P reports than there are with a “weak” ERM rating. Secondly the firms
with a “weak” ERM rating are more often not listed and hence are excluded for the sample.
Furthermore the descriptive statistics show that firms with a “strong” ERM rating are found to
be larger firms in terms of size, are less leveraged, more profitable and are more likely to pay
dividend.
Geographical differences
Since the focus of the study includes covering for geographical differences, the descriptive
statistics categorized by region are presented in Table 4. The table shows differences in firm
value in relation to ERM rating for US and EMEA firms, supporting the hypothesis H3. For
US firms the Firm Value (Tobin’s Q) for firms with a “strong” ERM rating is higher than for
firms with a “weak” ERM rating, while for EMEA firms the result are the other way around.
These preliminary results suggest that there is a geographical difference between US and
EMEA firms for the value creation of ERM. Therefore the sample is divided into two one US
and one EMEA firms sample.

Table 4
Descriptive Statistics Categorized by Region and ERM rating
This table provides the mean values for the variables used, categorized by Region and
ERM rating. The table reveals that for the US sample ERM firms have a higher firm value
while for the EMEA sample the opposite is found. Region 1=US Firms 2=EMEA Firms.
The variable definitions are provided in Table 2.
Region ERM
Firm Value
(Tobin's Q) Size Leverage Profitability Dividends
1 0 1.3486 8.3580 3.2595 -0.0188 0.5294
1 2.1839 10.2311 0.5282 0.0783 0.9196
Total 2.0738 9.9843 0.8881 0.0655 0.8682
2 0 2.3330 10.2881 3.2825 0.0308 0.1000
1 1.8012 10.0726 0.9948 0.0632 0.6667
Total 1.8638 10.0979 1.2639 0.0594 0.6000
For the US firms the descriptive statistics are in line with our expectations. The Firm Value
for the “strong ERM” firms is almost twice the Firm Value for “weak ERM” firms,
suggesting a strong relationship positive relationship between ERM rating and Firm Value.
These results are not in line with McShane et al. (2011), who only find a significant positive
relationship between the two for TRM and not for ERM. From the descriptive statistics for the
EMEA firms ERM rating seems negatively related to Firm Value. The result implies that
there is a substantial difference between US and EMEA firms in terms of the ERM and Firm
Value relationship, which will be further investigate in part 6.
In line with what ERM theory suggests and hypothesis H2, the return on capital for both
samples is higher for firms using ERM. As discussed in part 2, one of the main ways in which
ERM is implied to add additional shareholder value is through improving the risk-return
tradeoff. The findings from the descriptive statistics could be seen in the light of this. What is
surprising however is that firms engaging in ERM seem to be less leveraged as compared to
firms that are assumed to engage in TRM. One would expect that riskier firms would be more
tend to engage in ERM, since they are riskier in terms of financial obligations. A possible
explanation is that as Liebenberg and Hoyt (2011) set out, that companies with lower financial
leverage might decide to implement ERM in order to take more risk in the future. Finally firm
size seems to be ambiguous, while for US firms size is found to be higher for firms engaging

in ERM the results for EMEA firms imply that there is no substantial difference in size as a
determinant for ERM and TRM. In order to cover for the implied geographical differences
besides an overall sample regression, two separate regressions will be performed categorizing
the sample into US and EMEA firms.
Table 5
Pearson Correlations total sample
The Pearson correlations for the total sample of 214 non-financial firms are provided below. The variable
definitions are provided in Table 2. ***, ** and * denote statistical significance at the 1%, 5% and 10% levels
respectively.
Firm Value
(Tobin's Q) ERM Size Leverage Profitability Dividends
Firm Value (Tobin's Q)
ERM
Sig. (1-tailed)
Size
Sig. (1-tailed)
Leverage
Sig. (1-tailed)
Profitability
Sig. (1-tailed)
Dividends
Sig. (1-tailed)
1.000
0.093* 1.000
0.088
-0.083 0.266*** 1.000
0.113 0.000
-0.265*** -0.345*** 0.039 1.000
0.000 0.000 0.285
0.589*** 0.414*** 0.134** -0.447*** 1.000
0.000 0.000 0.025 0.000
-0.026 0.349*** 0.123** -0.219*** 0.270*** 1.000
0.353 0.000 0.036 0.001 0.000
Testing the model
In order for the results of the multiple linear regressions to be legitimate, in this section it is
described how the assumptions of the multiple linear regression are tested.
Multicollinearity
First the sample is tested for multicollinearity, a problem often related to multiple linear
regression models, by means of the Pearson correlations and the Variance Inflation Factor
(VIF). The Pearson correlation coefficients for the sample of 214 firms are shown in Table 5.
As expected and in line with the above, ERM’s correlation with Firm Value is significant
(p<0.10) although the correlation coefficient is low. The low correlation coefficient can be
explained by the suspected geographical difference as discussed above. Furthermore the only
correlation with Firm Value above 0.5 is Profitability (p<0.01). The correlation coefficients
between the independent variables are all below 0.5.

Table 6
Pearson Correlations for US firms
The Pearson correlations for the US firm sample consisting of 129 non-financial firms are provided below.
The variable definitions are provided in Table 2. ***, ** and * denote statistical significance at the 1%, 5%
and 10% levels respectively.
Firm Value
Firm Value (Tobin's Q) 1.000
ERM 0.288*** 1.000
Sig. (1-tailed) 0.000
Size -0.105 0.482*** 1.000
Sig. (1-tailed) 0.117 0.000
Leverage -0.268*** -0.447*** -0.169** 1.000
Sig. (1-tailed) 0.001 0.000 0.028
Profitability 0.632*** 0.558*** 0.161** -0.590*** 1.000
Sig. (1-tailed) 0.000 0.000 0.034 0.000
Dividends -0.133* 0.390*** 0.191** -0.395*** 0.362*** 1.000
Sig. (1-tailed) 0.067 0.000 0.015 0.000 0.000
After splitting the sample for US and EMEA firms the Pearson correlation coefficients for
each sample are shown in Tables 6 and 7. For the US firms there is a positive and significant
(p<0.01) correlation between the independent variables ERM and the independent variable
Firm Value, in line with the expectations and findings of previous studies for financial firms
(Beasley et al, 2008; Hoyt and Liebenberg, 2011). Again the only correlation above 0.5 is
Profitability, which seems to have multicollinearity with ERM (positive) and Leverage
(negative). This suggested multicollinearity will be tested again with the VIF statistic. For the
EMEA firms as implicated the Pearson correlation coefficient shows a negative relationship
between ERM and Firm value, although not quite reaching significance (p=0.12). Profitability
still shows a positively and significant collinearity to the dependent variable Firm Value
(p<0.01). For the EMEA firms sample no multicollinearity seems to be present within the
independent variables.

Table 7
Pearson Correlation for EMEA firms
The Pearson correlations for the EMEA firm sample consisting of 85 non-financial firms are provided below.
The variable definitions are provided in Table 2. ***, ** and * denote statistical significance at the 1%, 5%
and 10% levels respectively.
Firm Value
Firm Value (Tobin's Q) 1.000
ERM -0.130 1.000
Sig. (1-tailed) 0.118
Size -0.054 -0.048 1.000
Sig. (1-tailed) 0.311 0.330
Leverage -0.254*** -0.251*** 0.237** 1.000
Sig. (1-tailed) 0.009 0.010 0.014
Profitability 0.553*** 0.182** 0.101 -0.303*** 1.000
Sig. (1-tailed) 0.000 0.048 0.179 0.002
Dividends 0.002 0.373*** 0.099 -0.068 0.175* 1.000
Sig. (1-tailed) 0.492 0.000 0.184 0.267 0.055
The Variance Inflation Factors statistics for the samples are shown in Tables 8, 9 and 10.
With the Variance Inflation Factors for all samples being below 2.0, multicollinearity is not
likely to be an issue.
Selecting only cases for which Region = 1 Selecting only cases for which Region = 2
Figure 1 Normality of error distribution histograms

Testing the assumptions
The other main assumptions of the multiple linear regression is that the results from the model
are linear and that there is no heteroscedasticity. Based on the analysis of the residuals versus
the standardized predicted values both of these assumptions seem to be satisfied. Secondly
since the Durbin-Watson test statistics for both samples is close to 2, meaning that there is no
assumed correlation in the residuals and therefore the residuals are independent.
Finally it is tested whether the errors are normally distributed. Below the histograms for the
errors are displayed in Figure 1. Both figures show that the distribution of the errors is fairly
normally distributed. In the case of the EMEA data sample there are 2 outliers present on the
right side of the histogram. The model was tested again by removing these outliers, which led
to a better fit but did not alter the results of the model. Therefore it is assumed that these
outliers do not materially alter the predictions of the model and that the errors are normally
distributed.

Part 6: Empirical Results
Table 8
Result of Regressions of ERM on Firm Value (Tobin’s Q) for total sample
The below table shows multiple linear regression results for the total sample. The variables are
defined in Table 2. For Model 1 the only independent variable is ERM. The dependent variable firm
value (Tobin's Q) is found to be positively affected by ERM when only ERM is included. In Model 2
the control variables are added. When the control variables are included ERM is found to be
negatively related to firm value. The Model Summaries are as follows: Model 1: Adjusted R Square:
0.004, F=1.848 (p=0.18); Model 2: Adjusted R Square: 0.400, F=29.397 (p<0.01). ***, ** and *
denote statistical significance at the 1%, 5% and 10% levels respectively.
Model
Unstandardized Coefficients
Standardized
Coefficients
Sig.
Collinearity
Statistics
B Std. Error Beta VIF
1 (Constant) 1.713 0.218 0.000
ERM 0.317 0.233 0.093 0.175 1.000
2 (Constant) 2.858 0.451 0.000
ERM -0.374* 0.216 -0.110* 0.086 1.428
Size -0.103** 0.046 -0.124** 0.027 1.109
Leverage -0.013 0.028 -0.029 0.641 1.343
Profitability 13.270*** 1.226 0.682*** 0.000 1.410
Dividends -0.432*** 0.153 -0.163*** 0.005 1.171
Regression analysis
Next the study moves to the multiple linear regression analysis whereby the dependent
variable Firm Value (Tobin’s Q) is regressed against the independent variable of interest
ERM and other control variables. The multiple linear regression analysis was performed for
the total sample and two subsamples (US and EMEA firms), the results are presented in
Tables 8, 9 and 10 respectively. In each regression two models are presented, one model only
regressing ERM against the dependent variable Firm Value (Model 1) and the other including
the control variables (Model 2).
The results for the total sample show a positive (non-significant) relationship for ERM at
Model 1, while the relationship is opposite when the control variables are included. As
mentioned earlier this contrary result seems to be related to the geographical difference.
Therefore two separate samples dividing the total sample to US firms (N=129) and EMEA
firms (N=85).

Table 9
Result of Regressions of ERM on Firm Value (Tobin’s Q) for US Firms
The below table shows multiple linear regression results for the total US firms sample. The variables
are defined in Table 2. For Model 1 the only independent variable is ERM. The dependent variable
firm value (Tobin's Q) is found to be positively affected by ERM when only ERM is included. In
Model 2 the control variables are added. When the control variables are included ERM is still found
to be positively related to firm value. The Model Summaries are as follows: Model 1: Adjusted R
Square: 0.075, F=11.447 (p<0.01); Model 2: Adjusted R Square: 0.568, F=34.674 (p<0.01). ***, **
and * denote statistical significance at the 1%, 5% and 10% levels respectively.
Model
Standardized
Coefficients
Sig.
Collinearity
Statistics
1 (Constant) 1.349 0.230 0.000
ERM 0.835*** 0.247 0.288*** 0.001 1.000
2 (Constant) 3.458 0.471 0.000
ERM 0.423* 0.238 0.146* 0.078 1.987
Size -0.159*** 0.050 -0.212*** 0.002 1.333
Leverage 0.024 0.036 0.051 0.497 1.654
Profitability 12.711*** 1.333 0.761*** 0.000 1.887
Dividends -1.175*** 0.191 -0.404*** 0.000 1.280
Results: US firms
The results for the US firms sample are shown in Table 9. The model’s F-value is 11.447 and
34.674 for Model 1 and Model 2 respectively, and is significant in both cases. The model’s
adjusted R2
is 0.075 and 0.568 for Model 1 and 2 respectively. The variable of interest ERM
is positive and significantly related to Firm Value, with a significance of p<0.01 when ERM
is the only independent variable and a significance of p<0.10 when the control variables are
added. These findings are highly in line with the theoretical framework that ERM is able to
create additional value in comparison to TRM and seem to support our main hypothesis H1.
The findings seem to be in accordance with previous studies on US firms (Beasley et al, 2008;
Liebenberg and Hoyt, 2011), as opposed to the results found by McShane et al. (2011).
For the control variables only Profitability is found to be positively and significantly (p<0.01)
related to Firm Value, while Size and Dividend is found to be negatively and significantly
related to Firm Value (p<0.01). These results in line for with what McShane et al. (2011) find
for Profitability and Size, while the negative relationship of Dividend is not in agreement with

what Hoyt and Liebenberg (2011) find for Dividends. Beasley et al (2008) and Tahir and
Razali (2011) find an opposite relationship of Size on Firm Value, however with a different
measurement method for Firm Value (Excess Return) or a different region (Malaysia). The
findings have been tested for robustness by omitting Profitability, which was found to show
some collinearity with ERM, and by omitting the non-significant variables. In all cases ERM
was still significant (p<0.01 and p<0.10 respectively).
Table 10
Result of Regressions of ERM on Firm Value (Tobin’s Q) for EMEA Firms
The below table shows multiple linear regression results for the total EMEA firms sample. The
variables are defined in Table 2. For Model 1 the only independent variable is ERM. The dependent
variable firm value (Tobin's Q) is found to be negatively affected by ERM when only ERM is
included, but this finding is insignificant. In Model 2 the control variables are added. When the
control variables are included ERM is still found to be significantly negatively related to firm value.
The Model Summaries are as follows: Model 1: Adjusted R Square: 0.005, F=1.425 (p=0.24); Model
2: Adjusted R Square: 0.352, F=10.112 (p<0.01). ***, ** and * denote statistical significance at the
1%, 5% and 10% levels respectively.
Model
Standardized
Coefficients
Sig.
Collinearity
Statistics
1 (Constant) 2.333 0.419 0.000
ERM -0.532 0.446 -0.130 0.236 1.000
2 (Constant) 3.018 0.905 0.001
ERM -1.114*** 0.401 -0.272*** 0.007 1.242
Size -0.088 0.085 -0.096 0.302 1.110
Leverage -0.057 0.044 -0.126 0.203 1.247
Profitability 13.245*** 2.193 0.574*** 0.000 1.170
Dividends 0.011 0.259 0.004 0.966 1.194
Results: EMEA firms
The results for the EMEA firms sample are shown in Table 10. The model’s F-value is 1.425
and not significant when including only ERM as a predictor of Firm Value (Model 1). When
controlling for other variables, the F-value is 10.112 and significant (p<0.01) while the
adjusted R2
is 0.352.
As implied by the descriptive statistics and the Pearson correlation coefficients, surprisingly
the findings suggest that the variable of interest ERM is negatively related to Firm Value.
This finding is only significant (p<0.01) when the control variables are included. The negative

finding for ERM has been tested by including time variance (2011-2014) and this resulted an
even higher significance (p<0.01) of the negative relationship.
After checking for robustness Size is also found to be negatively and significantly (p<0.10)
related to Firm Value same as for the US firms sample. For robustness testing purposes the
findings have been tested for yearly changes and by omitting the non-significant variables,
after which ERM was found to be still significant (p<0.01). The results for the EMEA firms
are not in line with what theory suggests and therefore do not support the main hypothesis H1.
What is noteworthy is that while the Return on Assets is higher for ERM firms, which is
equally the case in the US firms sample, the firm value is lower than compared with TRM
firms. Further analysis to this finding and the possible explanations will be discussed in part
7.
For the control variables only Profitability is found to be significant with a positive relation to
Firm Value, conforming to the findings with for the US firms found previously. The other
variables are not found to be significant for this dataset.

Part 7: Discussion and conclusion
In part 6 the results of the cross sectional data analysis have been presented. In this part these
results and findings of this study will be discussed, as well as how these findings can answer
the research question and hypotheses. Subsequently the academic and economic implications
of the findings are discussed, after which the conclusion is presented. Lastly the limitations
and recommendations for further research are discussed.
Discussion
The objective of this study is to answer the question whether ERM creates additional
shareholder value. In the literature review the theoretical basis was discussed of why and how
ERM can create value in addition of TRM. It was shown that ERM should create additional
value by improving the risk-return tradeoff and therefore the capital allocation, by reducing
inefficiencies of TRM and by reducing the cost of external capital. This study attempts to
provide empirical evidence for the theory that ERM is able to create additional value, by
means of the multiple regression data analysis. In the previous part the empirical evidence
was presented. The results from the empirical evidence of this study provide us with two new
key findings.
First for US non-financial firms ERM is found to create additional value on top of TRM.
From the empirical results it is evident that ERM is found to be significantly and positively
associated with firm value. These findings are at odds with what McShane et al. (2011) found
for financial firms, as they only found that TRM creates value but that ERM does not create
additional firm value. The different finding in this study could be explained by the fact that
McShane et al.’s study (2011) focused on insurance firms only, and not on non-financial
firms. What this implies is that firm specific elements, such as the firm’s industry, might
determine whether ERM is perceived to add value. As McShane et al. (2011) explain in their
findings section, two circumstances that might have altered their findings as presented in their
results. First the timing of their study was right in the middle of one of the largest financial
crises all times, this could have biased the results as the largest firms are often more involved
in ERM, as there is empirical evidence that size is one of the determinants of ERM
implementation. These largest financial firms, such as the largest insurance firms were
disproportionally hard hit by the financial crises. Therefore McShane et al. (2011) ask their

selves whether the results would have been the same under normal circumstances. Secondly
financial firms, such as the insurance firms studied by them, are generally assumed to be
pioneers in risk management as it is their core business. Therefore it might be that the extra
mile for these firms to engage in ERM is not perceived as something new that might increase
their value by shareholders of these types of firms.
On the other hand the finding in the empirical evidence supports the suggestion of Beasley et
al. (2008) who found that for some non-financial firms with firm specific elements, a positive
equity market reaction was measurable. Combined with the findings from the descriptive
statistics the higher firm value for firms engaging in ERM might be explained by the return
enhancing capability of ERM which leads to a higher profitability, but further research needs
to be done to come to such a conclusion.
The second key finding of this study is that for EMEA non-financial firms an opposite
relationship is found. For this EMEA sample the results suggest that ERM does not create
additional value, instead the results merely suggest that ERM is perceived as value destroying.
This finding is contrary to theory and earlier studies that almost all found a positive
relationship between ERM and firm value. As this study is the first to be studying EMEA
firms, the results could be due to geographical differences, as previous studies were mostly
performed for US firms only. Nevertheless when further analyzing the results, as shown in the
descriptive statistics, same as with the US firms ERM seems to enhance profitability for
EMEA firms as well. Therefore the main way in which ERM is suggested to create additional
value, by means of enhancing return on capital due to a better capital allocation, is practically
the same for both US and EMEA samples. Remarkably the descriptive statistics for both
samples show that firms engaging in ERM have a higher return on assets (RoA) than firms
that are assumed to engage in TRM.
There are two explanations that might be able to answer why there is such a negative
relationship. First it could be that shareholders for EMEA firms do not value firms engaging
in ERM higher as opposed to firms engaging in TRM. As a result while in the US market
might perceive ERM as value enhancing, EMEA shareholders do not share this view leading
to geographical differences in perceived value creation. As a matter of fact the results suggest
that the adoption of ERM can have a value destroying effect on firm value for EMEA firms.

Another explanation could be that the data sample is biased due to the limited data available.
This could lead that the small sample of TRM firms coincidently has a higher firm value than
the ERM firms. At this point it unclear what causes this relationship and further research
should be done to explain what causes the negative relationship.
There are some other studies that find a similar negative effect of ERM on firm value. In their
study Lin et al. (2012) find negative market reaction to the implementation of ERM in a
specific insurance industry. As a possible explanation they provide that it might be that ERM
is perceived as a costly program of which the potential benefits do not give justification of its
cost. Another academic study found a similar negative relationship between firm value and
implementation of ERM. In the results of the master thesis of Liao (2012) the descriptive
statistics show a similar negative relationship between the implementation of ERM and
Tobin’s Q. Liao (2012) addresses that the negative relationship could be due to the value
destroying effect of the 2008 crises. Notable to say is that another study finds a slight
insignificant negative relationship between ERM and Tobin’s Q as well (Bartelsman, 2012).
This study also finds some evidence that the dividend payout ratio of a firm might be
associated with the implementation of ERM. In the descriptive results it is shown that for both
samples the firms engaging in ERM more often pay out dividend. It is not clear what these
results exactly imply. One explanation could be that ERM enhances the ability of a firm to
pay out dividend by better managing risks and cash flows. On the other hand firms paying out
dividend might implement ERM to improve their ability to manage their cash flows. Further
research is needed to investigate what the exact relationship is between the two.
Together these results from the empirical evidence can be used to provide an answer to the
hypotheses and the main research question of this study. The first hypothesis H1 is partially
accepted as for the US sample the results suggest that ERM does create additional value.
However for EMEA firms this is not the case and it is unclear whether EMEA shareholders
do not believe in the value creating ability or ERM or if ERM just does not create value due to
specific geographical conditions. These findings indirectly support hypothesis H3 which
suggests that there are geographical differences between US and EMEA firms, therefore this
hypothesis is accepted. The third hypothesis H2 suggested that firms engaging in ERM have a
higher return on capital as compared to firms engaging in TRM. As shown in the descriptive

results in part 5 for both samples return on assets is higher for the groups with the highest
ERM rating. Therefore this hypothesis is accepted as well.
Recapitulating, the main research question was whether ERM creates shareholder value.
Although the findings of this study cannot provide a generalized answer on this question, it is
evident that for non-financial US firms ERM does create shareholder value. On the other
hand, for non-financial EMEA firms ERM does not create shareholder value. When looking
further into the results it is notable that firms engaging in ERM do have higher return on
assets (RoA), supporting the theoretical suggestion that ERM is able to improve return on
capital. Therefore it is possible that ERM does create value in both samples, but that EMEA
shareholders just do not immediately perceive this value creation and therefore do not value
ERM firms higher at first, but that eventually ERM is able to enhance a firm’s value. Further
research might provide insight in answering that question.
Academic and economic implications
The findings presented in this study are valuable to academic research on ERM as to the best
of knowledge this is the first study to investigate non-financial EMEA firms and compare the
results with non-financial US firms. In this way the findings of this study reveals that
geographical differences that may alter the relationship between ERM and firm value seem to
be present. Furthermore the study provides an answer to the value creating ability of ERM on
non-financial firms and can complement previous studies that focused on financial firms.
From an economic relevance perspective the results create an incentive for senior
management and shareholders in the US to take into account the implementation of an ERM
framework. The results of this study underwrite the theoretical argument that ERM is able
create additional value by improving return on capital and therefore this might provide insight
for EMEA shareholders to perceive ERM to be value enhancing. Nevertheless further
research should focus on the exact reason why the results for EMEA firms are different.

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