Description
The concept of relevance is studied in many different fields, including cognitive sciences, logic, and library and information science. Most fundamentally, however, it is studied in epistemology. Different theories of knowledge have different implications for what is considered relevant and these fundamental views have implications for all other fields as well.
How Increased Value-Relevance?
ABSTRACT
This paper examines the value-relevance of Scandinavian earnings information and book values over the past
decade in order to shed some light on whether the extensive global adoption of IFRS/IAS has
contributed to an increased accounting quality in terms of economic decision-usefulness to equity
investors. We address this research question using a sample of 4.310 firm-year observations for 431 exchange-
listed companies at NASDAQ OMX Nordic and Oslo Stock Exchange between 2001 and 2010. The degree of
value-relevance in our firm-sample is operationalized through two price regressions and one return regression
and empirically tested via the statistical association between capitalized values of equity or annual changes in
capitalized values of equity and the study's three explanatory accounting variables: (i) book values, (ii) accrual-
based earnings and (iii) cash-flow-based earnings. Taken as a whole, our results show significant empirical
signs of an increased value-relevance in both Scandinavian earnings information and book values, allowing us
to draw significant as well as contributing conclusions on the information content of financial statement
information disclosed in the
Scandinavian region. We believe our study adds empirical substance to practical debates over the
function of financial reporting as well as resourceful material to both Scandinavian investors and to the
ongoing international discussion on the harmonization of financial reporting standards.
Keywords • Accruals, Book Values, Cash Flows, Earnings, FASB, IASB, IFRS, Value-Relevance
I. INTRODUCTION
THE OBJECTIVE OF THIS STUDY is to examine the value-relevance of earnings information and book values
over the past decade in order to shed some light on whether the extensive global adoption of
International Financial Reporting Standards and its predecessor set of standards, International Accounting
Standards, henceforth IFRS
1
and IAS
2
respectively, has contributed to an increased accounting quality in
terms of economic decision-usefulness to equity investors. Our inquiry is motivated by the recent practical
concern of an eroded economic relevance of publicly reported accounting information. Particular concern
among practitioners such as corporate accountants,
auditors and financial analysts (e.g., Jenkins, 1994 and Elliott, 1995) and academics (e.g., Francis and
* We gratefully acknowledge both comments and guidance from our tutor Katarzyna Cieslak at Uppsala University. We are
also grateful for valuable insights by our discussants at the SUMA program. The paper has also benefitted from resourceful
material by Thomas Plenborg at Copenhagen Business School and from the comments of Andreas Widegren at Uppsala
University.
Correspondence to † [email protected] and/or to‡ [email protected]
1 The European parliament and the council of the European Union made it via regulation number 1606/2002 mandatory for all
publicly traded companies within the European Union and the European Economic Area to prepare their consolidated
financial statements in accordance with International Financial Reporting Standards no later than 1 January 2005.
2 The main difference between IAS's and IFRS's is that the former were issued by the International Accounting Standards
Comittee, IASC, between 1973 and 2001, while the latter were issued by the International Accounting Standards Board,
IASB, from 2001 and onwards. Both types are included in the regulatory accounting framework that surrounds IFRS-
reporting.
2 BOGSTRAND AND LARSSON
Schipper, 1999 and Lev and Zarowin, 1999) has been directed towards the declined decision- usefulness
of earnings information, especially towards bottom line amounts based on accruals and
cash flows.
3
We address this research question on the basis of Scandinavian data using a sample of 4.310 firm- year
observations for 431 exchange-listed companies at NASDAQ OMX Nordic
4
and Oslo Stock Exchange
between 2001 and 2010. The choice of the Scandinavian region, where we, in addition to
the three genuine Scandinavian countries - Denmark, Norway and Sweden - also include Finland, is
motivated for several reasons. The main rationale stems from the fact that the Scandinavian region, due to
its investor-oriented accounting philosophy, strong legal enforcement and relatively stable external
surroundings, today and in turbulent times such as these, represents an established and secure
and thus attractive investment environment appealing to investors from all over the globe.
5
The attraction of the Scandinavian market is particularly evident when looking at the increasing
rate of publicly listed companies owned by foreign investors. Denmark, Finland, Norway and Sweden
have all seen the proportion of foreign non-Scandinavian ownership increase from a level of around 1.00-
5.00 percent to a level of around 20.00-40.00 percent since the early 1990s (Statistics Denmark, 2012;
Statistics Finland, 2012; Statistics Norway, 2012 and Statistics Sweden, 2012). Sweden, as an example, saw
the proportion of non-Scandinavian ownership increase from a level of 1.70 percent
6
to a level of 23.10
percent
7
between 1990 and 2010. This number corresponds to an average yearly
increase in non-Scandinavian ownership of about 13.90 percent
8
over the past two decades. Similar
increases have occurred also in Denmark, Finland and Norway, leading to an increased need among
investors also outside the Scandinavian region to obtain knowledge about the informational content in
Scandinavian earnings information and book values.
The degree of value-relevance in our firm sample is operationalized through two price regressions and
one return regression and empirically tested via the statistical association between capitalized
values of equity or annual changes in capitalized values of equity
9
and the study's three independent
explanatory accounting variables: (i) book values, (ii) an accrual component of earnings, and (iii) a cash-
flow component of earnings. To maintain comparability across tables and graphs and thus the possibility to
triangulate our results, all tests are based on the same broad set of exchange-listed firms. And, in order to
mitigate the possibility of incorrect inferences associated with scale-related effects such as size differences
across firms and extreme values in the firm sample, panel data regressions are
conducted in all the three regression models.
The results from our empirical tests show that both Scandinavian earnings information, accrual- based
as well as cash-flow-based, and book values are positively associated, albeit, to varying degrees, with
capitalized equity values as well as with annual changes in capitalized equity values.
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 3
These results are broadly consistent with previous value-relevance related research, originating from the
seminal discoveries of Ball and Brown (1968) and Beaver (1968). The results are also, at least to some
extent, in line with our predictions of the modern utilitarian role of publicly reported accounting
information in the Scandinavian region. However, unlike previous value-relevance related research,
particularly empirical research carried out on accounting data between the early 1990s and the beginning
of the twenty first century, our results show a relatively strong explanatory power,
regardless of the regression used. These results in combination with the statistical strength allow us to
draw both significant and contributing conclusions with regards to publicly reported accounting
information, disclosed in Scandinavian financial statements.
We believe that the results in this study are particularly pertinent to accounting standard-setting bodies
such as the International Accounting Standards Board and the Financial Accounting Standards Board,
henceforth IASB and FASB respectively, since it, to some extent, penetrates the relatively
unresolved question of whether or not the current IFRS-based regulatory framework has been fruitful
in terms of an increased economic decision-usefulness of Scandinavian financial statement information.
Our conclusions also provide equity investors with both resourceful material and valuable insights on the
relevance and the reliability of Scandinavian accounting numbers. We also believe that our study might be
useful in regions other than the Scandinavian, especially in countries where directives from the European
Union are compulsory to follow and where the accounting
philosophy is the same. The study might also be of value to regions outside the European Union with
an investment environment similar to the Scandinavian and where IFRS-reporting recently have been or
will be adopted.
Outline
The remainder of the paper is organized as follows. Section II presents the background of the
study where we highlight the primary objective of general purpose financial reporting and discuss its
utilitarian role in capital markets. In Section III we review and discuss previous research, which, in turn,
constitutes the underpinning theoretical ground for our empirical study. First, we present
different types of value-relevance related studies, which, in particular, include various ways to
operationalize and interpret value-relevance. Thereafter, we draw attention to the most significant empirical
findings since the seminal discoveries of Ball and Brown (1968) and Beaver (1968). Ultimately, we sum
up by formalizing our predictions for this study. In Section IV we present our methodological approach.
Section V presents data and descriptive statistics and in Section VI we interpret, discuss and analyze our
empirical results. Section VII finally summarizes the study and we
reveal our conclusions and provide some suggestions for further research.
II. BACKGROUND
Economic decision-usefulness is typically viewed as one of the most important attributes of publicly
reported accounting information, particularly among users such as equity investors, lenders and other
capital providers (Francis, LaFond, Olsson and Schipper, 2004). The attribute of economic decision-
usefulness is therefore - by accounting standard-setting organizations such as the IASB and the FASB
- also recognized as a fundamentally significant qualitative characteristic in the pursuit of high account ing
quality
10
in corporate reports and financial statements. The importance of economic
4 BOGSTRAND AND LARSSON
decision-usefulness is especially evident when looking at the primary objective of general purpose
financial reporting as stated in the conceptual framework:
11
The objective of general purpose financial reporting is to provide financial information about the reporting entity
that is useful to existing and potential investors, lenders and other creditors in making decisions about providing
resources to the entity. Those decisions involve buying, selling or holding equity and debt
instruments, and providing or settling loans and other forms of credit. IASB, 2010 and FASB, 2010.
If publicly reported accounting information is to be considered as useful for economic-decision
making, it must be both relevant and faithfully represent what it purports to represent in the financial
reports (IASB, 2010 and FASB, 2010). The conceptual framework for financial reporting define relevant
accounting information as information capable of making a difference in the decisions made by users
12
and
faithful accounting information as information that is complete, neutral and free from error, typically
referred to as reliable accounting information in value-relevance related research; see, e.g., Barth, Beaver
and Landsman (2001) and Holthausen and Watts (2001).
This means, in a more general sense, that publicly reported accounting information, disclosed in
annual as well as in quarterly corporate reports and financial statements, is set out to serve the public
interest by functioning as a corporate blueprint of the financial health so that its users can assess aspects
associated with corporate growth, profitability and risk
13
in order to make smart and informative
economic decisions. Accordingly, financial reporting does not only constitute an important source of
information when assessing the performance of firms, but also a valuable and
critical cornerstone set out the meet the society's need for an effective as well as an efficient capital
resource allocation. In the following subsection, we therefore reflect upon the critical role of financial
reporting in capital markets.
The Role of Financial Reporting in Capital Markets
A critical challenge for any economy is to assign available financial resources in an economically
efficient manner (Healy and Palepu, 2001). Much of this challenge stems from difficulties in overcoming
the problem with the information asymmetry that exist between companies and potential capital investors
and with the incentive issue that arise between the producer of accounting
information and the user of accounting information once an investment has been placed; see,
Akerlof (1970) and Jensen and Meckling (1976). Frequently discussed along these two dilemmas is the
lemon problem, which, potentially, can break down the very functioning of the capital market. It
works like this:
Consider a situation where half the business ideas are "good" business ideas and where the other half of the business
ideas is "bad" business ideas. If investors cannot distinguish between the two types of business
ideas, entrepreneurs with "bad" ideas will try to claim that their ideas are as valuable as the "good" ideas.
Realizing this possibility, investors value both good and bad ideas at an average level. Unfortunately, this penalizes
good ideas, and entrepreneurs with good ideas find the terms on which they can get financing to be unattractive. As
these entrepreneurs leave the capital market, the proportion of bad ideas in the market
increases. Over time, bad ideas "crowd out" good ideas, and investors lose confidence in this market. Palepu,
Healy and Peek, 2010.
Economies that overcome these problems well can exploit new business ideas to spur innovation
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 5
and create jobs and wealth at a rapid pace; meanwhile, economies that manage this process poorly dissipate
their wealth and fail to support business opportunities (Healy and Palepu, 2001). In overcoming the lemon
dilemma and prevent such a capital market breakdown, intermediaries, financial
14
intermediaries as well as
information
15
intermediaries, are of great value to capital markets since they help investors and other
stakeholders to distinguish between good and bad investment opportunities (Palepu, Healy and Peek,
2010).
Accordingly, financial reporting and other corporate disclosures clearly have high importance for
the functioning of capital markets since it to a great extent is the information that investors and other
stakeholders adopt and concurrently react upon, and therefore also an important source of information to
scrutinize and conduct empirical research on. In the following section, we therefore present the primary
purpose of value-relevance related research along some of the most seminal empirical findings related to
the objective of this study.
III. PREVIOUS RESEARCH
The primary purpose with empirical tests of value-relevance is to examine whether publicly reported
accounting information, disclosed in annual as well as in quarterly corporate reports and financial
statements, fulfill its utilitarian role of being useful for economic decision-making (Barth et al., 2001 and
Holthausen and Watts, 2001). That is, to investigate whether users such as equity investors,
lenders and other capital providers appreciate the information and perceive it as relevant once it has
been publicly available in the marketplace.
A significant portion of the value-relevance related research is therefore, either explicitly or implicitly,
motivated from an accounting standard-setting point of view, especially vis-à-vis the accounting criteria of
relevance and reliability as specified in the conceptual framework for financial reporting (Holthausen and
Watts, 2001; Kothari, 2001 and Francis et al., 2004).
Important to note is that there is no such thing as a standardized one-way-solution on how to
assess how well a particular accounting amount reflects information used by investors. However, in
general, it is measured as the ability of earnings information and book values to explain market values of
equity and/or changes in market values of equity (Barth et al., 2001; Holthausen and Watts, 2001 and
Beaver, 2002). A typical value-relevance study therefore examines the relationship between an equity-
dependent variable such as security prices and/or security returns
16
with a set of explanatory
accounting variables, typically book values in combination with at least one bottom line amount of
earnings information based on either accruals or cash flows or both.
In the extant accounting literature, an accounting amount is defined as value-relevant, i.e., able to change investors'
assessment of the probability distribution of an entity's future earnings capacity, if it has a significant predicted
association with an equity-dependent variable such as share prices and/or security returns. Barth et al. (2001).
Accordingly, publicly reported accounting information can be viewed as value-relevant if it reflect
a significant portion of the capitalized equity value or if the information is significantly associated
6 BOGSTRAND AND LARSSON
with changes in the capitalized equity value.
17
However, significant results of value-relevance, i.e., data
indicating that an accounting amount is relevant and reliable, at least to some degree, are difficult to assign
to one or the other attribute (Barth et al., 2001). This, since neither relevance nor reliability is of
dichotomous nature nor does the conceptual framework specify the extent to which relevance or reliability
is sufficient enough to meet IASB's and FASB's criteria of decision-useful information; see, e.g., IASB
(2010) and FASB (2010). As a result, regardless of the empirical test used, value-
relevance related research is carried out as joint tests of relevance and reliability and therefore, by
researchers, typically seen as a direct operationalization of the decision-usefulness objective as specified
in the conceptual framework.
Worth emphasizing is that value-relevance related research to a great extent is premised on the notion
of some sort of capital market equilibrium since it assume that a substantial degree of the information
content in earnings information and book values is strongly reflected in equity-dependent
variables such as security prices, stock returns and/or trading volumes (Barth et al., 2001; Holthausen
and Watts, 2001 and Kothari, 2001). Much of the value-relevance related research is therefore based on the
underlying assumption of the existence of efficient capital markets
18
and/or on the descriptive validity of an
equilibrium model such as the capital asset pricing model, hereafter CAPM
19
for convenience, or any
extension of the model (Lev and Ohlson, 1982; Kothari and Zimmerman, 1995; Barth et al., 2001;
Holthausen and Watts, 2001 and Kothari, 2001). In the following subsections, we
will present some of the most seminal and important empirical findings that relates to the objective of
this paper.
Early Empirical Findings based on Association Studies
20
Ball and Brown's pioneering study from 1968 was the first paper to formalize the positive
relationship between security returns and earnings information. That is, they established the fact that
movements in common stock partly can be explained by the information content in earnings numbers such
as by accrual-based net income and cash-flows, as approximated by operating income. The
17 Another approach to operationalize value-relevance is to examine whether there is any abnormal security price volatility
and/or abnormal trading volume around the announcement period. This approach originates from Beaver (1968) and Fama,
Fischer, Jensen and Roll (1969).
18 The theory of efficient capital markets is concerned with whether security prices at any point in time fully reflect all
available information and reaches market equilibrium. The assumption of some sort of market equilibrium is, in turn,
typically referred to as the efficient market hypothesis, henceforth EMH, which, originally, was developed by Fama in 1965. It is
common to distinguish among three versions of the EMH, viz., the weak form, the semi-strong form and the strong
form. These versions differ by their notions of what is meant by the term all available information. Specifically, the weak
form asserts that security prices reflect all information that can be derived by examining market-trading data such as the
history of past prices, trading volume and/or short interest, while the semi-strong form asserts that stock prices reflect all
publicly available information regarding the prospects of an entity, which, in addition to past prices and other technical
figures, includes fundamental information such as an entity's product line, quality of management, earnings forecasts and
balance sheet composition. The strong and final form of the EMH asserts that stock prices reflect all information that is
relevant to the firm, including monopolistic information available only to company insiders. These three versions are
discussed in great detail in Fama's seminal paper from 1970.
19 The capital asset pricing model, CAPM, or any extension of the model, e.g., the zero-beta model, is a set of predictions with
regards to equilibrium expected returns on risky assets, which, to a great extent, rests on the foundation of Harry
Markowitz's (1952) modern portfolio theory. The model itself was independently developed by Sharpe (1964),
Lintner (1965) and Mossin (1966) and can in general terms be described as a simplified version of investors and their
behavior in the marketplace. Specifically, the model assumes that all investors are price-takers, in that they act as though
security prices are unaffected by their own trades, and that they are rational and risk-averse and aim to maximize economic
utilities. The model also assumes that all investors can lend and borrow unlimited amounts under the risk-free rate of
interest, and that they analyze securities in the same way and that all investors share the same economic view the world.
Obviously, the model ignore many real world complexities and is therefore constantly subject to criticism; see, e.g.,
Grossman and Stiglitz (1980), Kandel and Stambaugh (1995), Fama and French (1992), Roll (1977) and Roll and
Ross (1994).
20 An association study conducts empirical tests on the relationship between publicly reported accounting information,
typically earnings information and/or book values, and security prices and/or returns over relatively long observation
windows such as one or several years (Kothari, 2001).
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 7
positive relationship between security returns and earnings information has also been confirmed in a
number of other different economic settings (see, e.g., Beaver and Dukes, 1972; Beaver, Lambert and
Morse, 1980; Lipe, 1986; Rayburn, 1986; Bowen, Burgstahler and Daley, 1987; Collins and
Kothari, 1989; Livnat and Zarowin, 1990; Dechow, 1994; Ali and Pope, 1995 and Basu, 1997).
Ball and Brown (1968) also highlight the fact that more prompt media like interim reports and quarterly
earnings tend to supersede the information in annual reports and that most of the information
contained in annual earnings and book values therefore is anticipated by the market before it is
released. In other words, when annual earnings information and balance sheet information is announced
the information might already be obsolete. Kothari (2001) share the same view as Ball and Brown (1968)
and argues that investors and stakeholders in today's capital markets are utilizing quarterly reports and other
more timely information, leading to a scenario where annual reports as a consequence are rendered less
useful.
Early Empirical Findings based on Event Studies
21
Ball and Brown (1968) and Beaver (1968) both provide compelling evidence indicating that
earnings announcements seem to capture the performance of firms. The key argument in the two
pioneering event studies is that there is a substantial empirical association between earnings
announcements and security prices. Ball and Brown (1968) find that the market positively (negatively)
adopts information with regards to unexpected increased (decreased) earnings, which, leads to an increase
(decrease) in security prices. Beaver (1968) examines movements of security prices and trading volume at
the time of the earnings announcements. First, and foremost, his
argument is that company information is more available, scrutinized and adopted surrounding
earnings announcements vis-à-vis periods with no earnings announcements. The findings in Beaver's
(1968) study are bracketing the findings in Ball and Brown's (1968) study, forwarding the fact that earnings
information positively adheres to the market price of securities. Specifically, in periods where earnings
announcements are made, the flow of information increases, and the stock prices are to a great extent
reflecting the content and quality of this information.
Accordingly, early event studies find that the flow of information is higher in periods with
earnings announcement in contrast to periods with no earnings announcements and that information
released by publicly listed companies significantly affects security prices. More recent event studies
support the seminal finding of a significant association between earnings announcements and security
prices; see, e.g., Landsman and Maydew (2002) and Landsman, Maydew and Thornock (2012).
Decline in Value-Relevance of Publicly Reported Accounting Information
It is apparent from early value-relevance related findings that earnings information as well as book
values are positively associated with contemporaneous security returns and reflected in capitalized
equity values over time. However, since the early 1990s, concerns have been expressed by academics
(e.g., Francis and Schipper, 1999 and Lev and Zarowin, 1999) as well as by accounting practitioners in the
financial press (e.g., Rimerman, 1990; Sever and Boisclair, 1990; Elliot, 1994a; Elliot, 1994b, Jenkins,
1994 and Elliott, 1995) that publicly reported accounting information, disclosed in corporate reports and
financial statements, has lost a significant portion of its relative economic decision- usefulness to other
sources of information available in the market place. In particular, it is claimed
that publicly reported accounting information, particularly book values and earnings information
8 BOGSTRAND AND LARSSON
based on accruals and cash-flows, today is less relevant in assessing the fundamental value of high-
technology, service-oriented firms, which, by nature are knowledge-intensive:
Early in the century, financial statements represented a large part of the information available to an enterprise's
debt and equity investors. As accounting principles improved, the value of financial statements
also improved. But, facilitated by information technology, other sources of relevant information are increasingly
available; for example, investors can get up-to-the-minute data about companies through public
and proprietary databases without waiting for quarterly or annual reports. Moreover, information technology
has created new ways for businesses to become more competitive; for example, continuous quality improvement,
cycle-time reduction and enhanced vendor and customer relations - effects of which are not
reflected in financial statements. Thus, financial statements describe modern companies less well than they
described industrial-era companies. Elliott, 1994b.
Hence, the traditional association between publicly reported accounting information and
capitalized values of equity have been called into question. Consistent with these claims Brown, Lo and
Lys (1999 and 2002), Francis and Schipper (1999), Lev and Zarowin (1999) and Core, Guay and Van
Buskirk (2003) find evidence for a decline in the value-relevance of both earnings information
and book values. Value-relevance is in these studies mainly tested for through price-level/return
regressions, where the adjusted explanatory power of the coefficient of determination (R
2
) typically is used
as the yardstick of value-relevance. A higher adjusted R
2
is generally taken as evidence of higher value-
relevance, which, under normal circumstances, means that the accounting amount with the highest
adjusted R
2
is interpreted as most relevant and reliable to its users. Worth emphasizing is that there also are
findings with somewhat contrary indications. For example, Collins, Maydew and
Weiss (1997) find no evidence of a decline in the value-relevance of earnings information and book
values. In fact, they find evidence for a slight increase in value-relevance, particularly among book values
and other balance sheet information.
IFRS Adoption
A growing body of the most recent value-relevance related research examines the implications of
the increasingly widespread adoption of IFRS-reporting among stock exchanges and accounting standard-
setting bodies all over the globe. Heretofore, the research provides somewhat mixed empirical signals on
whether financial statements prepared in accordance with IFRS/IAS exhibit
higher accounting quality than financial statements prepared in accordance with other sets of generally
accepted accounting principles (Ball, 2006 and Leuz and Wysocki, 2008). Worth repeating is that the
European Union did not mandate the use of IFRS-reporting for publicly listed companies until January
2005. As a result, much of the overall impact of IFRS-reporting is therefore yet still to be determined.
Mixed Evidence on Voluntary IFRS Adoption
Barth, Landsman and Lang (2008) analyze changes in the properties of reported earnings around
voluntary adoption of IFRS-reporting and find empirical evidence that publicly reported accounting
information prepared in accordance with IFRS/IAS generally exhibit less earnings management, more
timely loss recognition and higher value-relevance than publicly reported accounting information prepared
in accordance with other generally accepted accounting principles. This allows them to conclude that
financial statements prepared in accordance with IFRS/IAS generally are associated with higher accounting
quality compared to financial statements prepared in accordance with other domestic accounting standards.
This conclusion is supported by empirical evidence from a cross-
sample comparison between German-based, US-based and IFRS-based generally accepted accounting
principles in a study carried out by Bartov, Goldberg and Kim (2005). The view of higher accounting
quality in conjunction with voluntary adoption of IFRS-reporting is also the general opinion of
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 9
Soderstrom and Sun (2007) and Leuz and Wysocki (2008) in their reviews of empirical studies examining
the implications of voluntary IFRS adoption. However, contrary to this view, Hung and Subramanyam
(2007) find no evidence for a higher value-relevance associated with voluntary IFRS- reporting and thereby
no evidence for a higher accounting quality among financial statements prepared in accordance with
IFRS/IAS. Eccer and Healy (2003) find similar results in their cross- sample comparison between
accounting amounts based on IFRS/IAS standards and accounting
amounts based on Chinese standards.
Overall, the empirical evidence on voluntary IFRS disclosure is somewhat mixed. Possible
explanations for this diversity might be due to sample selection biases and/or methodological issues such as
omitted variables, lack of robustness and/or problems with deflation among the firm sample; see, e.g.,
Brown et al. (1999 and 2002) and Barth and Clinch (2009). Another possible explanation for the mixed
results stem from the many institutional factors that surround each and every industry,
country and region. In the following subsection, we therefore discuss some empirical evidence upon
the importance of institutional factors.
The Importance of Institutional Factors
Looking at previous research with regards to the IFRS debate, there are, as mentioned above,
somewhat mixed empirical evidence, particularly with respect to voluntary IFRS-reporting. This is, as
noted above, assumingly, associated with either econometrical issues or with the quality of the legal
environment and institutional factors that surrounds each and every industry, country and region.
Specifically, institutional factors such as regulatory accounting frameworks and investor protection
are immensely important factors for how companies and investors act with regards to financial
reporting (Soderstrom and Sun, 2007 and Leuz and Wysocki, 2008). The strength of domestic regulatory
bodies is closely connected to the interplay between companies and investors, and will, concurrently,
affects what kind of information, and in what way, companies display (in) their financial reports (Ball,
Kothari and Robin, 2000 and Leuz, Nanda and Wysocki, 2003). The key argument is that it might be
common in some industries, countries, and/or regions to mislead investors and other
stakeholders by acting on personal incentives rather than adhering to regulations, which, thus, reduce
the overall accounting quality by ignoring the relevance and the reliability of the financial reports.
The issues mentioned in the above are part of what the IASB and the FASB constantly are trying to
improve upon. Institutional factors that are of particular concern in previous research and associated with
stronger (weaker) reporting quality and thus stronger (weaker) accounting quality are strong (weak)
investor protection (see, e.g., La Porta et al., 2002); strong (weak) legal enforcement (see, e.g.,
Leuz and Wysocki, 2008) and a strong (weak) tax enforcement system (see, e.g., Guenther and
Young, 2000 and Haw, Hu, Hwang and Wu, 2004). The content of previous research, with regards to
institutional factors, is that a poor institutional quality will excavate the effectiveness of accounting
standards, which, as noted above, potentially might disassemble the main objective of accounting standards
and thus lead to a decreased accounting quality among financial reports. Accordingly, it is of vital
importance to be aware of the external surroundings when conducting value-relevance related
research.
Lack of Evidence on Mandatory IFRS Adoption
The European Union mandated, as mentioned in the introduction, the adoption and
implementation of IFRS/IAS in January 2005. Much of the overall impact with respect to the mandatory
adoption of IFRS-reporting is therefore yet still to be determined, particularly pertaining the accounting
quality in terms of economic decision-usefulness among equity investors. However, recently, Landsman,
Maydew and Thornock (2012) found that, in countries with mandatory IFRS-
MATRIX I
Value-Relevance Related Studies Examining Earnings Information and Book Values of Equity
AUTHORS AND YEAR TYPE OF STUDY DATA METHODOLOGY FINDINGS AND CONTRIBUTION
Ball and Brown, 1968 BB conduct a combined association The final firm sample includes 261 The degree of information content is The first paper to formalize the
and event study that examines the publicly listed companies. The data is operationalized via a return regression relationship between security returns
relative as well as the incremental obtained from Compustat, CRSP and that regresses change in firm-specific and earnings information. The paper
informational content of earnings The Wall Street Journal between 1957 earnings with change in market- also highlights evidence for the post-
information. and 1965. specific earnings. A simple time- earnings-announcement drift, the
series model, building on the relative importance of earnings
somewhat naïve assumption of a information and on the incremental
random walk, is used as a check of the value of different earnings
statistical efficiency of the first model. information.
Beaver, 1968 B conducts an event study that The final firm sample includes 143 The degree of information content in The first paper to find significantly
examines the information content of NYSE listed companies. The data is annual earnings announcements is strong empirical evidence for value-
annual earnings announcements. obtained from Compustat and The operationalized via both abnormal relevance in earnings information in
Wall Street Journal between 1961 and trading volume and abnormal security the week of the announcement.
1965. price volatility.
Collins, Maydew and Weiss, 1997 CMW conduct an inter-temporal The final firm sample includes The degree of value-relevance in CMW find no empirical evidence for a
association study that examines 115.154 firm-year observations for earnings information and book values decline in the value-relevance of
systematic changes in the value- NYSE, AMEXandNASDAQlisted is operationalized via the valuation earnings information and books
relevance of earnings information and companies. The data is obtained from framework provided by Ohlson values. Contrary, they find evidence book
values over time. Compustat and CRSP between 1953 (1995), which expresses price as a for a slight increase in the value-
and 1993. linear function of earnings information relevance of earnings information and
and book values. book values - over the sample period:
1953-1993.
Brown, Lo and Lys, 1999 BLL conduct an inter-temporal The final firm sample includes The degree of value-relevance in BLL find significant empirical
association study that examines 112.134 firm-year observations for earnings information and book values evidence for a decline in the value-
systematic changes in the value- publicly listed companies. The data is is operationalized via both price relevance of both earnings information
relevance of earnings information and obtained from Compustat and CRSP regressions and return regressions. and book values - over the sample book
values over time. between 1958 and 1996. period: 1958-1996.
Francis and Shipper, 1999 FS conduct an inter-temporal The final firm sample includes The degree of value-relevance in FS find significant empirical evidence
association study that examines
systematic changes in the value-
relevance of earnings information and
book values over time.
between 393 and 1.419 firms per year
for NYSE listed companies and
between 1.124 and 2.866 firms per year
for NASDAQ listed companies. The data
is obtained from Compustat
earnings information and book values
is operationalized via (i) price
regressions and return regressions, and
(ii) the total return that could be earned
from foreknowledge of
for a decline in the value-relevance of
earnings information, and an increase
in the value-relevance of balance sheet
and book value information over the
sample period, i.e., between 1952 and
and CRSP between 1952 and 1994 for publicly reported accounting 1994.
NYSE listed companies and between information.
1974 and 1994 for NASDAQ listed companies.
!!
10
!
MATRIX I (CONTINUED)
Value-Relevance Related Studies Examining Earnings Information and Book Values of Equity
AUTHORS AND YEAR TYPE OF STUDY DATA METHODOLOGY FINDINGS AND CONTRIBUTION
Lev and Zarowin, 1999 LZ conduct an inter-temporal The final firm sample includes The degree of value-relevance in LZ find significant empirical evidence
association study that examines between 3.700 and 6.800 firms per earnings information and book values of a decline in the value-relevance of
systematic changes in the value- year for publicly listed companies. is operationalized via both price both earnings information and book
relevance of earnings information and The data is obtained from Compustat regressions and return regressions. values - over the sample period: 1963-
book values over time. between 1977 and 1996 and from 1996.
CRSP between 1963 and 1995.
Landsman and Maydew, 2002 LM conduct an inter-temporal event The final firm sample includes 92.613 The degree of information content in LM find no empirical evidence of a
study that examines systematic firm-quarter observations for publicly quarterly earnings announcements is decline in the information content of
changes in the information content of listed companies. The data is obtained operationalized via both abnormal quarterly earnings announcements -
quarterly earnings announcements. from Compustat between 1972 and trading volume and abnormal security over the sample period: 1972-1998.
1998. price volatility.
Core, Guay and Van Buskirk, 2003 CGB conduct an inter-temporal The final firm sample includes The degree of value-relevance in CGB find empirical evidence of a
association study that examines 109.559 firm-year observations for earnings information and book values slight decrease in the value-relevance
systematic changes in the value- NASDAQ listed companies. The data is operationalized via price of earnings information and book
relevance of earnings information and is obtained from Compustat and CRSP regressions. values - over the sample period: 1975-
book values over time. between 1975 and 1999. 1999.
Bartov, Goldberg and Kim, 2005 BGK conduct a combined inter- The final firm sample includes 915 The degree of value-relevance in BGK find significant empirical
temporal and cross-sectional firm-year observations for Frankfurt, earnings information and book values evidence for a higher degree of value-
association study that examines NYSE, AMEX, NASDAQ and LSE is operationalized via a time-series relevance among accounting amounts
systematic changes in the value- listed companies. The data is obtained return regression and between three prepared in accordance with IFRS
relevance of earnings information and from The Global Vantage Database sets of generally accepted accounting reporting than accounting amounts book
values over time and between between 1998 and 2000. principles using a cross-sectional prepared in accordance with other three
different sets of generally return regression. accounting standards - over the
accepted accounting principles. sample period: 1998-2000.
Barth, Landsman and Lang, 2008 BLL conduct an inter-temporal The final firm sample includes 1.896 The degree of value-relevance in BLL find significant empirical
association study that examines firm-year observations for publicly earnings information and book values evidence for a higher degree of value-
systematic changes in the value- listed companies from 21 different is operationalized via both price relevance among accounting amounts
relevance of earnings information and countries. The data is obtained from regressions and return regressions. prepared in accordance with IFRS book
values over time, particular focus DataStream and WorldScope between reporting than accounting amounts revolves around accounting amounts 1990 and
2003. prepared in accordance with other prepared in accordance with IFRS accounting standards - over the
reporting. sample period: 1990-2003.
Landsman, Maydew and Thornock, 2012 LMT conduct a combined inter- The final firm sample includes 20.517 The degree of information content in LMT find significant empirical
temporal and cross-sectional event earnings announcements from 16 annual earnings announcements is evidence for a greater increase in both
study that examines systematic countries that mandated adoption of operationalized via both abnormal abnormal trading volume and
changes in the information content of IFRS/IAS and 11 countries that trading volume and abnormal security abnormal security price volatility in
earnings announcements, particular retained domestic accounting price volatility. firms that prepare their financial
focus revolves around accounting
amounts prepared in accordance with
IFRS reporting.
standards. The data is obtained from
I/B/E/S, DataStream and WorldScope
between 2002 and 2007.
!
11
statements in accordance with IFRS
reporting than in firms that follow other
accounting standards - over the sample
period: 2002-2007.
12 BOGSTRAND AND LARSSON
reporting the usefulness and utilization of information surrounding earnings announcements is greaterthan
in countries that have retained domestic accounting standards.
These findings, thus, indicate that IFRS-reporting positively affects the value-relevance of accounting
information, but the area is still an unexplored territory, especially with regards to value- relevance and the
effects of IFRS-reporting. The majority of previous research on mandatory IFRS- reporting cogitates how
IFRS/IAS has affected companies' cost of capital as well as the market
liquidity of its securities (see, e.g., Daske, Hail, Leuz and Verdi, 2008). The quality of accounting
measures and amounts is still somewhat imprecise, which connects to the fact that data regarding pre- and
post-IFRS adoption to a great extent still is unavailable. The main rationale for the lack of evidence on
mandatory IFRS-reporting is therefore, that there, until recently, has been non-existent analyzable data.
Empirical Summary and Predictions
Both earnings information and book values are, as appears from the preceding subsections and
Matrix 1 above, positively associated with contemporaneous security returns and reflected in
capitalized equity values over time. This is evident in both event- and association studies and applies
regardless of the specific parameters used. That is, irrespective of which expectation model, earnings
definition, return and price specification, statistical model and set of generally accepted accounting
principles the study is conducted on. It is also apparent that the relationship during the beginning of the
early 1990s until the beginning of the twenty first century has become weaker, which, in turn, indicates that
publicly reported accounting information, disclosed in financial statements, has lost a
significant portion of its relevance to equity investors. This could, in a worst-case scenario, lead to a
so-called lemon market, see, e.g., Akerlof, 1970, that potentially might frustrate the function and thus the
very objective of capital markets; see also, e.g., Jensen and Meckling (1976) and Healy and Palepu (2001).
Against the background of the mixed empirical evidence vis-à-vis voluntary IFRS adoption and the lack of
evidence vis-à-vis mandatory IFRS adoption, it is also clear that much of the implications of IFRS-
reporting are still yet to be determined, particularly with respect to the overall
reporting quality and whether or not the principle-based regulatory framework of accounting
standards has been fruitful in terms of an increased economic decision-usefulness to its users.
From the preceding subsections, Matrix I, and the above empirical summary, it is feasible to depict
some predictions with regards to this study. First of all, we believe that the Scandinavian region, in which
we include Denmark, Finland, Norway and Sweden, due to its investor oriented accounting philosophy,
strong legal enforcement and relatively stable external surroundings - institutional factors
of importance when implementing regulatory frameworks - has experienced an increase in the value-
relevance over the past decade. Worth to emphasize is that the relatively short time period equity investors
and financial intermediaries have had to adjust to the new set of accounting standards might have led to a
slight decrease in the post-adoption period. Our notion is that this will be revealed in an increase in the
explanatory power (adjusted R
2
) over the full sample period between 2001 and 2010 and in a slight
decrease in adjusted R
2
between the pre-IFRS period and the post-IFRS period.
IV. METHODOLOGY
In previous research, several models are being utilized to provide empirical results on the value- relevance
of accounting measures (see, e.g., Dechow, 1994; Kothari and Zimmerman, 1995 and Barth, Beaver, Hand
and Landsman, 2005). There are, as mentioned in the preceding section, two approaches that elevate with
regards to the value-relevance discussion. The two approaches are referred to as
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 13
price-level regressions
22
and return regressions, and yield different answers to the same inquiry; namely,
the value-relevance of accounting amounts. This study is constructed upon similar models and sample
variables initiated in previous studies, and will, concurrently, adopt the methods utilized in previous
research. Thus, the methodology applied in this study, is also advocated in a great amount of previous
research (e.g., Kothari and Zimmerman, 1995; Barth et al., 2005 and Hellström, 2006).
As previously described, the intention of this study is to assess how and to what extent book
values and earnings, divided into accruals and cash-flows, henceforth BV, ACC and CF, are
connected to the year-end market capitalization as well as the change in year-to-year market
capitalizations, hereafter MC, for the sample period 2001-2010 and the two sub-periods, i.e., the period
before, 2001-2004, and after, 2005-2010, the mandatory introduction of IFRS-reporting. To obtain this
information, the study performs several regressions, specifically a price regression, a lagged price
regression and a return regression (see, e.g., Kothari and Zimmerman, 1995 or
Hellström, 2006). The above-mentioned regression models are widely used to assess value-relevance,
but they differ, as hinted in the preceding paragraph, distinctively in what they actually answer (Barth et al.,
2001). Barth et al. (2001) state that level regressions examine if accounting measures are reflected in price
levels, whilst return regressions examine if accounting measures are reflected in the change in price levels
over a specific period of time; see also, footnote 14.
This study, following the arguments from previous research, defines the different year-end
accounting variables as the level variables, and the year-to-year change in the different accounting
variables as the return variables. Following the considerations of Barth et al. (2001) it is clear that two level
regressions and one return regression will produce suitable results that relates to the objective of this study.
In the following subsections, the regression models adopted in this study as well as particular issues
connected to this area are described and discussed. Following the regression models, we dive into the
different alternatives available when performing panel data analysis and we further
develop the environment attached to the regression models. Hereunder, we also describe the tests and
the necessary econometric adjustments connected to the tests.
Cross-Sectional Time-Series Analysis
Price regressions and return regressions in their simplest forms are some of the most adopted and
established models in value-relevance related research (see, e.g., Kothari and Zimmerman, 1995 or Barth et
al., 2005). The Ohlson-framework (1995) or any extension of the framework is a well-known example of a
valuation model that commonly is connected to value-relevance regression models. The
Ohlson-model is based upon the dividend discount model and is defined as:
#
P
t
=
- R
!¬
E
t
(d
t
+
¬
) (Ohlson-Model)
¬=1
The price and return regressions that we have used in this paper can be traced back to several
articles in previous research. To establish the regression models in this study, equivalent
methodologies as e.g., Collins et al. (1997), Burgstahler and Dichev (1997) and Hellström (2006) is
operationalized. The price and lagged price regression determines how much of the MC-variable that is
explained by respectively BV and earnings, divided into CF and ACC, and the return regression determines
the relationship between the change in MC and the change in BV, ACC and CF. Effectively, we are using
a panel regression to express the relationship between the dependent
variable, MC, and the independent variables, BV and earnings, defined as ACC and CF.
Panel regressions are equivalent to cross-sectional time-series analysis, which are regressions that adjust
for company and time specific errors (Gujarati, 2004). In order to streamline the lagged price
14 BOGSTRAND AND LARSSON
and return regressions we have operated with a one-year lag and return window, i.e., from fiscal year to
fiscal year. This means that the relationship between the dependent variables and the explanatory variables
in the lagged price and return regression is affected by every announcement the company makes throughout
a full year respectively.
In panel data there are essentially two main alternatives related to how the regression is carried out,
either fixed effects or random effects (Gujarati, 2004). The fixed effect model assumes, in short,
that the variables are correlated and applies corrections to the regression accordingly. Moreover, the
fixed effect panel regression takes into account the individuality of the sample variables similar to
introducing dummy variables to the regression. The equation for a cross-sectional time-series
regression with fixed effects can be expressed in the following way:
Y
it
= !
1i
+ !
2
X
2it
+ !
3
X
3it
+ ¬
it
(Fixed Effects)
The random effect regression is theoretically the opposite of the fixed effect regression; in terms of
it assuming that the variables are uncorrelated and appropriately can apply random effects when
performing the regression. Moreover, the random effect regression disregards the need for generating
dummy variables and instead uses a disturbance term (u) in correspondence with the error term. The
equation for a cross-sectional time-series regression with random effects can be expressed in the
following way:
Y
it
= !
1i
+ !
2
X
2it
+ !
3
X
3it
+ ¬
it
+ u
i
(Random Effects)
The following four subsections will, in detail, explain the price regression, the lagged price
regression and the return regression. Alongside, we also present adjustments that enable more
statistically accurate results. Please note that we, to some extent, simplify the illustration of both the
price regression and the return regression in the equations below, but the underlying equation utilized by
the statistical software, STATA, is the comprehensive regressions for both random effects and fixed effects.
Price Regression : Model 1
The price regression utilized in this paper is based on what is proposed by Burgstahler and
Dichev (1997) and Hellström (2006). Several other researchers have utilized similar regressions; see, e.g.,
Collins et al. (1997), Francis and Schipper (1999) and Lev and Zarowin (1999). The basic
regression is concurrently a function of MC as the dependent variable and BV, ACC and CF as the
three independent variables. One issue, proposed by certain researchers, is to express the regression without
scaling the numbers; see, e.g., Easton and Sommers (2003) and Barth and Clinch (2009). Scaling, or
deflating, means that you divide the variables by a common denominator in order to increase
comparability and remove company specific issues. We have, however, decided not to scale, or deflate, our
variables but instead recognize the arguments of Gujarati (2004), i.e., that panel data
takes into consideration the individual panels, i.e., firm and year specification. Therefore, we argue,
that by running panel data regressions, the issues with scale effects will not be that significant. Or, phrased
differently, by deflating the accounting numbers the transformation might bias the results rather than
improve them. To some extent, we have already explained the different variables that we have chosen to
investigate in this paper. However, in order to further clarify, the different variables in
the two price regressions are listed below:
MC
it
= Market Capitalization of Firm i in Fiscal Year t (MC)
BV
it
= Total Shareholder Equity of Firm i in Fiscal Year t (BV)
ACC
it
= Earnings
it
- CF
it
of Firm i in Fiscal Year t (ACC)
CF
it
= Cash-Flow from Operations of Firm i in Fiscal Year t (CF)
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 15
The sample consists of data between 2001 and 2010, which will be analyzed for the full time period, as
well as for the pre- and post-IFRS periods. The different equations that are implemented in
Model 1 and the unlagged price regressions are:
MC
it
= !
0
+ !
1
BV
it
+ !
2
ACC
it
+ !
3
CF
it
+ ¬
it
MC
it
= !
0
+ !
1
BV
it
+ ¬
it
MC
it
= !
0
+ !
1
ACC
it
+ ¬
it
MC
it
= !
0
+ !
1
CF
it
+ ¬
it
Lagged Price Regression : Model 2
(1A)
(1B)
(1C)
(1D)
Following the price regression we also introduce a lagged price regression model. The reason
behind this is that we also want to test a one-year lag effect on the variables. More precisely, we lag the
independent variables, BV, ACC and CF, on the opening dependent variable, MC.
23
This will result in a
more accurate perspective of the relationship between MC and BV, ACC and CF because the market has
received a full year to react, and adopt to the dependent variable, the information
content of the independent variables. Accordingly, the different regressions that are implemented in
Model 2 and the lagged price regressions are:
MC
it
= !
0
+ !
1
BV
it-1
+ !
2
ACC
it-1
+ !
3
CF
it-1
+ ¬
it
MC
it
= !
0
+ !
1
BV
it-1
+ ¬
it
MC
it
= !
0
+ !
1
ACC
it-1
+ ¬
it
MC
it
= !
0
+ !
1
CF
it-1
+ ¬
it
Return Regression : Model 3
(2A)
(2B)
(2C)
(2D)
Similar to the above-mentioned regressions the return regression is based on MC, BV, ACC and
CF. We anchor our return regression in several prior researchers' methodology; see, e.g., Easton and Harris
(1991), Kothari and Zimmerman (1995) and Hellström (2006). Hellström's (2006) methodology
originates from Easton and Harris' model that regresses the return variable against both price level and price
change. Our model is solely considering the return variable and change in BV, ACC and CF. One reason
for this is that we already have performed level models in the price
regression and the lagged price regression, and therefore want to execute a clean return regression to
facilitate comparison between diverse models. According to e.g., Brown, Lo and Lys (1999) and
Hellström (2006) a return regression is preferably deflated by price at the beginning of the year. Thus, our
return regression model is deflated by the opening price at period t. Before we move on, we believe it is
imperative to define all the distinctive variables that will be employed in the return
regression constituting Model 3:
MC_R = (MC
it
- MC
it-1
) / MC
it-1
(MC_R)
BV_R = (BV
it
- BV
it-1
) / MC
it-1
(BV_R)
ACC_R = (ACC
it
- ACC
it-1
) / MC
it-1
(ACC_R)
CF_R = (CF
it
- CF
it-1
) / MC
it-1
(CF_R)
Following the same thoughts as presented above we adopt return equations comparable to previous
research (see, e.g., Kothari and Zimmerman (1995) or Hellström (2006). The assumption in this study is
that the return variables are as normally distributed as possible and therefore will yield unbiased
16 BOGSTRAND AND LARSSON
statistical results. Listed below are the equations implemented in Model 3 and the return regression
approach:
MC_R
it
= !
0
+ !
1
BV_R
it
+ !
2
ACC_R
it
+ !
3
CF_R
it
+ ¬
it
+ u
i
MC_R
it
= !
0
+ !
1
BV_R
it
+ ¬
it
+ u
i
MC_R
it
= !
0
+ !
1
ACC_R
it
+ ¬
it
+ u
i
MC_R
it
= !
0
+ !
1
CF_R
it
+ ¬
it
+ u
i
Tests and Final Econometric Adjustments
(3A)
(3B)
(3C)
(3D)
Preliminary testing consists of determining whether to use a fixed effect or a random effect
regression model. Which model to utilize is established by running both regressions, saving their estimates,
and subsequently run a Hausman test; see, StataCorp (2011). The Hausman test assumes the null hypothesis
that you can use the random effect regression model. To interpret the Hausman test, in short, you reject the
hypothesis to use the random effect model if the probability of the test is lower than five percent. Therefore,
if the probability of the test is higher than five percent, you can use
random effects and if it is lower than five percent you should use fixed effects. Regarding our price
and lagged price data the probability of the Hausman test is 0.26 percent or lower and we will accordingly
use the panel data fixed effect model. For the return regression model we accept the Hausman-test with
11.87 percent and will therefore use the panel data random effect model.
After determining that the fixed effect model is preferred in the price and lagged price regressions, it is
also necessary to control for heteroskedasticity and auto/serial-correlation. In STATA this is
accomplished by running a Wald-test, testing for groupwise heteroskedasticity, and a Wooldridge-test,
testing for autocorrelation; see, StataCorp (2011). The Wald-test assumes the null-hypothesis that there are
no groupwise heteroskedasticity, however, in our case we reject this hypothesis and accept that there is
heteroskedasticity present in our data. The Wooldridge-test assumes that there are no autocorrelation in the
data, however, also apparent after testing is that our data contain autocorrelation. Considering the
random effects approach in the return regression, the assumption is
that there are no, or low, heteroskedasticity and autocorrelation. This is, first and foremost, because
the very basis of the random effects regression assumes that the error term of the coefficients are random
rather than fixed (Gujarati, 2004).
Autocorrelation means that the error terms in the model are correlated, which is especially common in
regression analysis containing dummy variables, which, in turn, is similar to a fixed effect model; see, e.g.,
Gujarati (2004). In panel data it is also very common to be affected by
heteroskedasticity and therefore we are not surprised that the general response, from testing, is that
both autocorrelation and heteroskedasticity is present in our study.
The first step to deal with autocorrelation and heteroskedasticity is to introduce robust standard errors to
the fixed effect regression model. This means that the regression models will be less sensitive to outliers
and therefore might deliver an improved statistical result. The second step to deal with both autocorrelation
and heteroskedasticity is to cluster the panel variable, i.e., the firm variable,
which also will help deliver stronger econometrical results. The following section will elaborate on
the data and descriptive statistics of this paper, followed by the empirical results and our analyzes vis- à-vis
the objective of this paper.
V. DATA AND DESCRIPTIVE STATISTICS
Prominent approaches with regards to value-relevance research and the components of earnings are based
on reported accounting numbers from the financial statements; see, e.g., Healy (1985) and
Dechow, Sloan and Sweeney (1995). The foundation of the components in our regression models is
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 17
based on financial data derived from each respective company. There are several different approaches in
previous research that all disassembles and define earnings into an accrual component and a cash flow
component. The most eligible methods, with respect to this study, are perhaps Sloan (1996) and Barth et al.
(2005). Sloan (1996) defines accruals by combining a subset of accounting measures and then subtracts
this component from earnings in order to receive a cash flow component. By restructuring the definiti on
of accruals, this study determines accruals as net income before
extraordinary items subtracted by cash flow from operations. A similar approach is used and
recommended by Barth et al. (2005).
The accounting and firm specific measures collected in this study are net income before
extraordinary items, cash flow from operations, market capitalization, and the total value of shareholders'
equity. Additional clarifications involving how the accounting measures will be implemented and/or
adjusted is further explained for each regression model as described in the
methodological part in Section IV. However, to eliminate any misinterpretations the accounting
measures in this paper are the following:
Market Capitalization
The Total Value of Shareholders' Equity
Net Income Before Extraordinary Items
Cash Flow from Operations
An Accrual Component (EARN - CF)
Sample Selection and Choice Criteria
(MC)
(BV)
(EARN)
(CF)
(ACC)
In order to enable the supplement of the continuous growing research concerning the value-
relevance of accruals and cash flows, we intend to perform this study on the Scandinavian region, in which
we include Denmark, Finland, Norway and Sweden; see, Table 1. Simply determining which areas and
exchanges to study is, nevertheless, insufficient since all the securities listed on the
exchanges may not meet the criteria required to conduct the methodology presented in this paper. It is
important to make sure that every firm included in the sample satisfies the demands necessitated by the
regression models. Albeit, there are several reasons for why this study decided to enhance the empirical
evidence surrounding the Scandinavian stock exchanges. Firstly, all the four countries are closely
connected both from an economic as well as a geographical perspective. Secondly, similarities are also
evident when scrutinizing the listed securities from an industry specific perspective, i.e., the
Scandinavian countries are also comparable when looking at the variety of businesses apparent on the
stock exchanges. Thirdly, as in detail described in the introduction, the foreign non-Scandinavian
ownership, and thus interests, in the Scandinavian stock exchanges is noticeably high. This means that the
comparability and importance of the countries in the sample are high, and concurrently also interesting to
study.
The criteria in this study are conservative, and consist of two stages. First, the study necessitates
data for a considerable time period, and the selected sample has been set to ten years. This yields ten
years of data, which is sufficient in order to complete both the two price regressions and the return
regression. In other words, any company that does not have data for at least ten years will be excluded from
the sample. Second, to perform the methodology presented in this paper, all the accounting measures as
defined above are required to be available for each company. Accordingly, if either MC, BV, EARN, or CF
is unavailable, the company will be excluded from the sample. The outcome of
these criteria is that we have an available sample of 4.310 firm-year observations, consisting of 431
exchange-listed firms with ten years of data spanning between 2001 and 2010, which, depending on the
model specifications, will deliver nine or ten years of analyzable regression variables.
18 BOGSTRAND AND LARSSON
To collect comparable data in this study we have used DataStream, Worldscope, henceforth DS.
This choice affects the study both positively and negatively. The positive effect of using DS, as the only source of data, is that the entire sample is available in one database.
Furthermore, if some parts of the data have been altered, all the measures are assumingly changed in the same manner. For example, EARN may not equal what is found in
the financial reports of the companies, but all the EARN found in DS are assumed to be comparable. The negative aspect of only using this database is
that the sample size might be limited due to DS license agreements. However, since the positive
aspects unquestionably outweigh the negative aspects, we have chosen to utilize DS Worldscope as the exclusive source of data.
The data collection process has resulted in the collection of accounting measures for ten consecutive years for 431 Scandinavian publicly listed companies.
Originally, the sample was intended to consist of all companies on each respective stock exchange. However, after running the
sample through the above-mentioned criteria, the final sample consists of 85 firms listed on NASDAQ
OMX Copenhagen, 96 firms listed on NASDAQ OMX Helsinki, 75 firms listed on Oslo Stock Exchange and 175 firms listed on NASDAQ OMX Stockholm. In total, we
are, as mentioned above, consequently carrying out our research on a sample of 431 Scandinavian exchange-listed firms; see also, Table 1 and Table 2.
Table 2 presents the descriptive statistics for the full sample and the different regressions that have
been performed in this study. As is portrayed in Table 2 the availability of descriptive statistics for a
panel data sample is limited. Nevertheless, Table 2 also highlights the fact that all of the regressions are significantly dispersed and that there are no explanatory variables
that have distinctive outliers compared to each other. To further clarify, the descriptive statistics in Table 2 are expressed with within-values
24
for each panel, which is why
we also recognize the descriptive statistics for each stock exchange in Table 1 via Panel A, B and C.
Table 1, Panel A concerns the price regression and consecutively encloses the variables utilized by
the price regression. Although the variables in the three regressions all are based on the same accounting measures, they are implemented differently in each regression
respectively. By further examining Panel A below, it is evident that the range of values is significant. Table 1, Panel B concerns the lagged price regression, and
successively presents the variables adopted in the lagged price regression model. Accordingly, it is evident that the sample in the lagged price regression is
somewhat smaller. However, the reason behind the smaller sample is that the independent variables,
BV, ACC and CF, are lagged with one year. This is apparent when comparing N/n in Panel A, B and C. Furthermore, also for the lagged price regression the dispersion of
variable values is significant, meaning that the values are spread out and thus not grouped in clusters close to each other.
Table 1, Panel C apprehends the return regression in this study, and displays the variables relevant for the return regression model. Similar to the lagged price data, the
sample size is also for the return
regression smaller than the price regression data. This is because the return variable is calculated by
dividing by opening market price and the model therefore has to be shortened with one year. However, the sample used to obtain the return values is still the full ten-year
period between 2001 and 2010. By looking at the min and max values in Panel C, which probably best explain the distribution of the variables, it is acknowledged that the
variables are significantly dispersed. However, they are more closely structured than in Panel A and B.
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 19
TABLE 1
Descriptive Statistics per Stock Exchange
COPENHAGEN HELSINKI OSLO STOCKHOLM
1, 2
MC BV ACC CF MC BV ACC CF MC BV ACC CF MC BV ACC CF
PANEL A
N/N 850/85 850/85 850/85 850/85 960/96 960/96 960/96 960/96 750/75 750/75 750/75 750/75 1750/175 1750/175 1750/175 1750/175
Q1 176.1 147.1 -169.9 7.9 37.3 23.8 -36.8 2.4 407.3 242.2 -288.2 15.5 210.4 103.5 -132.3 -1.3
MEAN 6223.4 2253.0 -330.8 623.6 1498.1 665.3 -66.1 148.1 10743.6 5721.3 -990.9 1781.1 11738.9 5550.1 -396.6 1034.0
Q3 3056.4 1911.0 -8.1 350.2 578.4 348.6 -1.4 72.1 4506.4 2470.1 -7.7 594.8 4014.9 1681.1 -3.8 308.5
STD. DEV. 21182.2 5898.1 1137.2 1926.4 7634.4 1930.7 248.7 567.8 44022.9 20037.8 5079.7 8556.7 38828.8 17602.5 2979.6 3694.4
MIN 1.0 -96.4 -12604.0 -514.3 1.4 -15.0 -3396.0 -1289.0 5.8 -859.1 -63073.0 -4395.7 3.4 -484.0 -40322.0 -34677.0
MEDIAN 706.9 482.7 -46.5 70.0 130.8 62.8 -6.5 13.3 1216.1 767.1 -69.5 130.3 735.7 407.4 -23.6 51.8
MAX 359657.9 64248.0 3938.0 21346.0 137163.3 15148.0 2003.0 7289.0 538510.4 219542.0 12237.0 106338.0 450795.9 169947.0 43190.0 32496.0
PANEL B
N/N 765/85 765/85 765/85 765/85 864/96 864/96 864/96 864/96 675/75 675/75 675/75 675/75 1575/175 1575/175 1575/175 1575/175
Q1 176.1 148.1 -165.0 8.0 37.8 23.7 -36.8 2.5 416.9 230.4 -270.3 15.5 216.8 100.9 -130.9 -1.6
MEAN 6398.7 2139.8 -327.7 604.5 1440.1 656.6 -69.9 152.0 11248.0 5476.0 -941.3 1720.1 11949.7 5348.9 -406.7 982.6
Q3 3192.0 1844.5 -8.1 -350.2 606.8 344.2 -1.4 71.7 4850.5 2346.0 -6.3 550.1 4320.3 1616.8 -3.8 295.1
STD. DEV. 21708.2 2139.8 -327.7 604.5 6558.0 1915.5 257.6 588.5 45879.4 18967.0 4814.2 8152.8 38692.7 17042.6 2956.8 3604.6
MIN 1.0 -96.4 -12604.0 -514.3 1.4 -13.9 -3396.0 -1289.0 5.8 -859.1 -63073.0 -4395.7 3.4 -108.6 -40322.0 -34677.0
MEDIAN 750.4 469.0 -46.0 70.4 137.9 61.5 -6.5 13.3 1285.8 738.9 -65.2 127.2 749.5 393.0 -23.2 46.6
MAX 359657.9 55521.0 3938.0 21346.0 101994.6 15148.0 2003.0 7289.0 538510.4 214079.0 12237.0 106338.0 439116.4 159167.0 43190.0 32496.0
PANEL C
N/N 765/85 765/85 765/85 765/85 864/96 864/96 864/96 864/96 675/75 675/75 675/75 675/75 1575/175 1575/175 1575/175 1575/175
Q1 -0.18 -0.04 -0.05 -0.03 -0.23 -0.06 -0.04 -0.03 -0.20 -0.02 -0.03 -0.02 -0.20 -0.04 -0.04 -0.03
MEAN 0.34 0.13 0.01 0.03 0.35 0.10 0.05 0.05 0.31 0.06 0.01 0.03 0.33 0.05 0.02 0.02
Q3 0.46 0.09 0.04 0.06 0.46 0.10 0.04 0.06 0.48 0.10 0.02 0.05 0.51 0.10 0.03 0.06
STD. DEV. 2.91 2.66 0.26 0.28 1.44 0.83 0.83 0.43 1.19 0.47 0.32 0.22 1.67 0.38 0.52 0.51
MIN -0.85 -6.86 -2.85 -1.44 -0.96 -2.66 -6.22 -4.24 -0.93 -2.54 -2.23 -1.14 -0.97 -3.88 -7.06 -11.74
MEDIAN 0.11 0.02 0.00 0.01 0.11 0.03 0.00 0.01 0.13 0.03 0.00 0.01 0.13 0.03 0.00 0.01
MAX 77.86 72.48 1.67 4.38 18.58 13.27 19.63 6.05 18.98 6.21 3.74 2.45 50.55 4.07 11.23 7.19
1 Panel definitions of Table 1: Panel A = Unlagged price regression; Panel B = Lagged price regression; and, Panel C = Return regression.
2 Variable definitions of Table 1: MC = Market capitalization sorted by stock exchange; BV = Book value sorted by stock exchange; ACC = Accruals sorted by stock exchange; and, CF = Cash flows sorted
by stock exchange.
20 BOGSTRAND AND LARSSON
TABLE 2
Descriptive Statistics for the Firm Sample
VARIABLES
1. 2
N/N STD. DEV. MIN MAX
Panel B
MC
it
4310/431 12778.7 -180159.4 234640.6
BV
it
4310/431 5037.1 -79619.1 93733.9
ACC
it
4310/431 1930.5 -50602.0 32910.0
CF
it
4310/431 2054.7 -46186.5 44765.2
Panel B
MC
it
3879/431 12452.2 -196838.6 214953.0
BV
it
3879/431 4760.6 -69779.7 98110.3
ACC
it
3879/431 1928.4 -48627.6 34884.4
CF
it
3879/431 2023.4 -44961.9 48730.0
Panel C
MC
it
3879/431 1 .8 -9 .0 69.4
BV
it
3879/431 1 .2 -8 .6 64.7
ACC
it
3879/431 0 .5 -7 .9 17.5
CF
it
3879/431 0 .4 -10.8 8 .1
1 Panel definitions for Table 2: Panel A = Price regression; Panel B = Lagged price regression; and, Panel C = Return
regression.
2 Variable definitions for Table 2: MC
it
= Market capitalization of firm i in fiscal year t. BV
it
= Book value of equity of firm i in
fiscal year t. ACC
it
= Accruals of firm i in fiscal year t. CF
it
= Cash flows of firm i in fiscal year t.
VI. EMPIRICAL RESULTS
This section will present the results from the three regression models that this study has implemented and
conducted on Scandinavian data. Important to remember is that this study identifies earnings as one accrual
component and one cash flow component. To reduce the possibility of confusion, the
tables enclosed below will only include information that is considered relevant in terms of the analysis
of the objective of this study. The adjusted explanatory power of the different regression models is
defined by R
2
in each respective model. Table 3, 4 and 5 also include the coefficients (!) for each
explanatory variable. It is particularly important to keep in mind that for the two level regressions the
coefficients can be arbitrary due to scale-related effects
25
, while, for the return regression, which deflates
the variables with the opening market capitalization, awareness regarding the explanatory
variable coefficients can be beneficial to recognize. Nevertheless, the pivotal subject in this study is
value-relevance and therefore the explanatory power (R
2
) of each respective regression model is of focal
interest. Also, worth noting is that all the R
2
values are significant at a 1 percent level. The T- value is also
deliberately excluded from the tables since it is significantly high for all the regression models.
Similar to e.g., Kothari and Zimmerman (1995) this study also found that the return regression was
less affected by heteroskedasticity and autocorrelation than the two level regressions, i.e., the price
regression and the lagged price regressions. Therefore, as previously mentioned, the price and lagged price
results found in Table 3 and Table 4 are predicted by using a fixed effect panel data regression, while the
return regression results found in Table 5 is predicted using a random effect panel data regression. The
following section will analyze the results within each regression model for the full
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 21
sample period, as well as the pre- and post-IFRS sub-periods. Conclusively, a discussion connecting the
research question to the results from each regression model is presented.
TABLE 3
Price Regression : Model 1
1A: BV
it
+ ACC
it
+ CF
it
1B: BV
it
1C: ACC
it
1D: CF
it
PRICE
1
!
1
!
2
!
3
R
2
!
1
R
2
!
1
R
2
!
1
R
2
2001-2010 0.460 0.911 3.144 34.98% 1.246 24.14% -1.063 2.58% 3.478 31.27%
*** *** *** *** *** ***
PRE-IFRS 0.625 3.048 1.321 11.38% 0.844 3.32% 1.748 4.15% 0.380 0.48%
*** *** *** *** *** **
POST-IFRS -0.463 1.023 4.430 23.32% 0.679 4.64% -0.501 0.13% 3.162 18.70%
*** *** *** *** *** ***
*** Significant at 1 percent level ** Significant at 5 percent level * Significant at 10 percent level
1 Price Regression: MC
it
= !
0
+ !
1
BV
it
+ !
2
ACC
it
+ !
3
CF
it
+ ¬
it
Variable definitions for Table 3: MC
it
= Market capitalization of firm i in fiscal year t. BV
it
= Book value of equity of firm i in
fiscal year t. ACC
it
= Accruals of firm i in fiscal year t. CF
it
= Cash flows of firm i in fiscal year t. ! = Coefficient of the
explanatory variables. R
2
= Adjusted R
2
within the panel regression.
Price Regression : Model 1
The price regression considers the relationship between the company specific year-end market
capitalization, book value of equity and the study's two earnings measures using a fixed effect panel data
regression. Table 3 presents the results after running regression 1A, 1B, 1C, and 1D, as described
in the methodological part in Section IV. When examining the price regression results, it is apparent
that the explanatory power of the four price regressions has very high significance for all the time periods.
Below we discuss the results, and reflect upon substantial issues, pertaining to the price regression models.
For the full sample period Model 1 indicate that the combined explanatory variables, 1A, explain 34.98
percent of the variance in the market capitalization. Apparent from regression 1B and 1D is that
both book values and cash flows have much higher explanatory power than accruals. Since both book
values and cash flows have high-adjusted R
2
values (24.14 percent and 31.27 percent) it is presumable that
they contain overlapping incremental information with regards to the combined explanatory power. A
possible explanation for these values could be the fact that one of the main valuation models utilized by
investors today is the discounted cash flow model, henceforth DCF-model. A high application of DCF-
models could also help explaining the low explanatory power of the accrual
component (2.58 percent) highlighted under regression 1C.
The pre-IFRS period compared to the post-IFRS period indicates lower value-relevance, i.e., lower
explanatory power, for the explanatory variables in regression 1A (respectively 11.38 percent and 23.32
percent). Another interesting finding in Model 1 concerns the pre- and post-IFRS results and the fact that in
the pre-IFRS period regression 1C shows stronger explanatory power of accruals (4.15 percent) than cash
flows in regression 1D (0.48 percent). This means that for the pre-IFRS period
accruals have more value-relevance than cash flows. Thus, accruals, for the pre-IFRS period, are the
most important explanatory variable
26
. The post-IFRS period indicates that book values have slightly
increased in terms of value-relevance. More interesting, though, is the difference that is apparent
22 BOGSTRAND AND LARSSON
when looking at the explanatory power of regression 1C and 1D (0.13 percent and 18.70 percent
respectively). This means that for the post-IFRS period cash flows have ascended with almost 97.5 percent
and accruals have descended with almost 97 percent in the post-IFRS period compared to the pre-IFRS
period.
Albeit, since Model 1 employs the year-end market capitalization it is understandable that the accruals
measure has lower explanatory power than book values and cash flows. One issue that is
apparent when considering Model 1 is, in fact, that it looks at the relationship between the market
capitalization at the end of period t and the book value and earnings at the end of period t. The model is,
nevertheless, interesting, in terms of explanatory power of recent book value and earnings measures
concerning the market capitalization at the same date, since a number of valuation models consists of
predicting future equity and cash flows based on the present value today. Hence, the increased use of cash
flow as a predictor in equity investments can probably be one reason for the
sudden change of value-relevance from the pre-IFRS period to the post-IFRS period. Nevertheless,
logical assumptions would suggest that the explanatory variables should be better reflected in the market
capitalization for the lagged price regression than in the price regression.
TABLE 4
Lagged Price Regression : Model 2
2A: BV
it-1
+ ACC
it-1
+ CF
it-1
2B: BV
it-1
2C: ACC
it-1
2D: CF
it-1
LAGGED PRICE
1
!
1
!
2
!
3
R
2
!
1
R2 !
1
R
2
!
1
R
2
2001-2010 0.225 0.387 3.100 29.05% 1.062 16.48% -1.316 4.15% 3.273 28.28%
*** *** *** *** *** ***
PRE-IFRS -0.120 -1.349 4.040 68.80% 0.209 0.29% -4.663 47.83% 4.896 66.80%
*** *** *** * *** ***
POST-IFRS 0.765 0.591 3.467 2.08% 1.114 0.40% -0.582 0.02% 3.831 2.70%
*** *** *** *** *** ***
*** Significant at 1 percent level ** Significant at 5 percent level * Significant at 10 percent level
1 Lagged Price Regression: MC
it
= !
0
+ !
1
BV
it-1
+ !
2
ACC
it-1
+ !
3
CF
it-1
+ ¬
it
Variable definitions for Table 4: MC
it
= Market capitalization of firm i in fiscal year t. BV
it-1
= Book value of equity of firm i in
fiscal year t-1. ACC
it-1
= Accruals of firm i in fiscal year t-1. CF
it-1
= Cash flows of firm i in fiscal year t-1. ! = Coefficient of the
explanatory variables. R
2
= Adjusted R
2
within the panel regression.
Lagged Price Regression : Model 2
The lagged price regression considers the relationship between the market capitalization at year t
and the one-year lagged book value of equity and the study's two earnings measures using a fixed effect
panel data regression. This means that book values, accruals and cash flows are measured against the
market capitalization for the subsequent year. This study assumes that this should remedy any issues that
might be present in the price regression with regards to the explanatory variables not yet being mirrored in
the market capitalization. Table 4 presents the results after running regression
2A, 2B, 2C and 2D as presented in the methodological part in Section IV. Moreover, each regression
is performed for the entire sample period, for the pre-IFRS period and for the post-IFRS period. In Model 2
all the regression models are significant at a 1 percent level, which means that we have
strong statistical evidence for the displayed adjusted R
2
values as well as the model's coefficients.
For the full sample period Model 2 indicate that the combined explanatory variables, displayed in 2A,
explains 29.05 percent of the variance in the market capitalization. Furthermore, regressions 2B,
2C and 2D reveal that, similar to Model 1, cash flows have the strongest explanatory power for the
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 23
full sample period with 28.28 percent. Book values are also important in Model 2 with an adjusted R
2
value
of 16.48 percent, while accruals have the lowest explanatory power for the full sample period with 4.15
percent. Nevertheless, accruals have more explanatory power in Model 2 than in Model 1, an increase of
1.57 percent, which means that in Model 2, for the full sample period, a higher amount of the accrual-based
information has been adopted in the market capitalization.
Looking at the pre-IFRS period in Model 2, the results are astoundingly distinctive in comparison
to Model 1. The combined explanation power of the independent variables, 2A, for the pre-IFRS
period is 68.80 percent. Moreover, book values, 2B, have lost almost all their importance with regards to
value-relevance, only 0.29 percent, and the highest explanatory power, in the pre-IFRS period, lies within
accruals and cash flows with 47.83 percent and 66.80 percent respectively. This means, however, that
both regression 2C and 2D contain information that incrementally overlaps, i.e., accruals and cash flows
contain similar information for the pre-IFRS period since they both have
explanatory power close to the combined explanatory power found in regression 2A. The clear
indication of Model 2 is that, for the pre-IFRS period, both accruals and cash flows have high value-
relevance and are better predictors of the market capitalization than the book value found in regression 2B.
One explanation for the strong results is that the economy in the Scandinavian countries was growing and
expanding rapidly, especially within the technology sector, in the years representing the pre-IFRS period.
This is especially evident in the aftermath of the Dot-Com bubble in 2000/2001, as
all the markets show signs of optimism and increased growth between 2001/2002 and 2007/2008
27
.
Thus, the positive upturn in the market is highly dependent on the economic growth in companies on the
market.
The post-IFRS period displays a different result than the pre-IFRS period, with a combined
explanatory power of 2.08 percent, 2A. The difference between the pre-IFRS period and the post- IFRS
period is remarkable with a drop in explanatory power of 66.72 percent, and there has to be
several underlying reasons for the sudden decrease. Model 2B, 2C and 2D explain 0.4 percent, 0.02
percent and 2.70 percent of the variance in the market capitalization respectively. Although these results are
weak, it is evident that cash flows have the strongest explanatory power by far. It is difficult to explain the
reasons behind the sudden decrease in value-relevance; however, one reason can definitely be the financial
turmoil that emerged between 2007 and 2008. Moreover, the results of the post-IFRS period could be
highly affected by the destructive effects of the financial crisis. This
could also help acknowledge the assumption that Model 2 is a better predictor of value-relevance than
Model 1, i.e., during the financial crisis it is likely that the market utilized other factors than book values,
accruals and cash flows since they did not rely on financial information in the same manner as they did
before the financial crisis.
The issue with this explanation is that it is unsupportive of the results in Model 1. However, it could
also be argued that Model 1 looks at the relationship between market capitalization and book
values, accruals and cash flows at the same point in time, while Model 2 looks at how the information
in year 1 is reflected in the price of year 2. More precisely, the argument is that Model 1 displays how much
the explanatory variables actually explain at the same point in time, while Model 2 displays how much the
explanatory variables explain after the market has adopted the information in the market capitalization.
Accepting this argumentation, it is evident that during the post-IFRS period in Model 2, perhaps due to the
financial crisis, the market did not choose to rely on the information in
neither book values, accruals nor cash flows, although, the explanation power of the explanatory
variables actually increased from the pre-IFRS period to the post-IFRS period in Model 1.
24 BOGSTRAND AND LARSSON
TABLE 5
Return Regression : Model 3
3A: BV_R
it
+ ACC_R
it
+ CF_R
it
3B: BV_R
it
3C: ACC_R
it
3D: CF_R
it
RETURN
1
!
1
!
2
!
3
R
2
!
1
R
2
!
1
R
2
!
1
R
2
2001-2010 1.094 0.226 0.248 58.73% 1.117 58.46% 0.482 1.92% 0.553 1.29%
*** *** *** *** *** ***
PRE-IFRS 1.077 0.347 0.346 84.51% 1.106 84.04% 0.750 3.90% 0.978 2.33%
*** *** *** *** *** ***
POST-IFRS 0.976 0.093 0.077 19.96% 0.996 19.97% 0.171 0.79% 0.171 0.35%
*** * * *** ** **
*** Significant at 1 percent level ** Significant at 5 percent level * Significant at 10 percent level
1 Return Regression: MC_R
it
= !
0
+ !
1
BV_R
it-1
+ !
2
ACC_R
it-1
+ !
3
CF_R
it-1
+ ¬
it
Variable definitions for Table 5: MC_R
it
= Change in market capitalization of firm i in fiscal year t divided by MC
t-1
. BV_R
it-
=
Change in book value of equity of firm i in fiscal year t divided by MC
t-1
. ACC_R
it
= Change in accruals of firm i in fiscal year t
divided by MC
t-1
. CF_R
it
= Change in cash flows of firm i in fiscal year t divided by MC
t-1
. ! = Coefficient of the explanatory
variables. R
2
= Adjusted R
2
within the panel regression.
Return Regression : Model 3
The return regression reflects the relationship between the change, or return, in market
capitalization and the change in book value of equity and the change in earnings measures, defined as
accruals and cash flows. Table 5 displays the results after running regression 3A, 3B, 3C and 3D as
presented in the methodological part in Section IV. Similar to Model 1 and Model 2, each regression is run
for the full sample period, for the pre-IFRS period and for the post-IFRS period. Worth specifying is that
all the regressions in Model 3 are significant at a 1 percent level and that some of the coefficients have
weaker significance than in Model 1 and Model 2. This can also be verified by
looking at Table 5 and the strong results of book values, 3A and 3B, compared to accruals and cash
flows, 3A, 3C and 3D.
Issues with heteroskedasticity and autocorrelation, which are present in the level regressions, are not
common in return regression models. This is also the case for our return regression model. However,
Francis and Schipper (1999) point out that return regression models might be less suited for economically
unstable periods. Therefore, to build on the previous arguments regarding both the
upturn during the pre-IFRS period and the recession in the post-IFRS period, the sample period in this
study can be defined as economically unstable. Nevertheless, the intention of this study is not to study the
effects of financially upturns and downturns, but the value-relevance of the above-mentioned explanatory
variables. It is, in any way, important to comment on what, at least in certain ways, that can affect the
results of the different regression models.
For Model 3, the full sample period results found in regression 3A indicate that, combined, the
explanatory variables explain 58.73 percent of the variance in the market capitalization returns. It is
evident, though, that book value returns, 3B, have the outright strongest explanatory power of the three
explanatory variables. According to regression 3B book value returns explain 58.46 percent while accrual
returns and cash flow returns, 3C and 3D, for the full sample period explain 1.92 percent and 1.29 percent
of the variance in market capitalization returns. That the results for regressions 3C and 3D are quite low is
not necessarily negative. It means, however, that for this return
model and the full sample period, book value returns have considerably stronger explanatory power
than accrual returns and cash flow returns.
The pre-IFRS period indicates a stronger explanatory power than for the full sample period when
looking at regression 3A, 84.51 percent. Similar to the full sample period, the book value return found
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 25
in regression 3B is the strongest explanatory variable with 84.04 percent for the pre-IFRS period as well.
Compared to Model 1 and Model 2, the distribution of explanatory power between book value returns,
accrual returns and cash flow returns is fairly constant for all the periods. In the pre-IFRS period accrual
returns, 3C, and cash flow returns, 3D, indicate explanatory power of 3.90 percent and 2.33 percent
respectively. Thus, in the pre-IFRS period accrual returns explain, out of the two
earnings components, more of the variance in market capitalization returns than cash flow returns.
In the post-IFRS period, there are indications in all the regressions, 3A, 3B, 3C and 3D, that the
value-relevance, i.e., that the explanatory power, has plummeted. For the combined regression model, 3A,
this study finds that the explanatory power is 19.96 percent - a significant decline compared to the pre-
IFRS period. The relationship between the models is, however, the same as in the two previous periods.
Book value returns, 3B, explain more than the combined model, 3A, with an explanatory power of 19.97
percent. Accrual returns, 3C, and cash flow returns, 3D, explains 0.79
percent and 0.35 percent of the variance in the market capitalization returns. The weak results of
accrual returns and cash flow returns, in the post-IFRS period, could definitely be connected to the financial
turmoil that erupted between 2007 and 2008. Also important, is the suggestion that return models, by some
extent, are considered to be unsuitable for unstable financial times; see, Francis and Schipper (1999).
This study finds that all the regression models are coinciding on the fact that the financial crisis
and the arduous economic situation on the market have affected the outcome of the regression
analysis. Since Model 3 measures the return, and not the level, it is more comparable to Model 2 than
Model 1. Therefore, the same argumentation is compatible, and valid, for Model 3 as it was for the lagged
price regression in Model 2. Moreover, the return model looks at the change in each variable with a return
window of one year, and thus how the information has been transformed over the course of the return
window. The argument, and possible explanation, is accordingly, even though we find an
increase in value-relevance in Model 1, this increase has not been recognized by the market and
implemented in the market capitalization in Model 3.
Value-Relevance and Proximate Implications
Based on the above results there are, first of all, strong indications that there is a positive
association between market capitalization and book values, accruals and cash flows for the given sample
period between 2001 and 2010. This means that the current accounting standards are producing
accounting numbers that can be utilized to predict and explain the variance in market capitalization,
which, thus, are important regarding the value-relevance discussion. There are,
nevertheless, also several other areas that are important in relation to value-relevance and accounting
information. In the following paragraphs, we will further discuss the above results in connection with other
ramifications existent in the area of financial reporting.
One element that is highly important is, as mentioned above, the quantity of key accounting items that
are utilized by investors, which to a great extent affects the value-relevance of reported accounting
information. The argumentation behind this statement is founded in the efficient market
hypothesis, elevating that all accounting information should be adopted and reflected in the
capitalized market value of equity; see, e.g., Fama (1965 and 1970). Furthermore, if investors, due to for
example economic turbulence, decide to form their investment approaches on other information than what
is enclosed in financial reports, the market capitalization will not likely comprehend the same degree of
accounting information. Therefore, in situations where investors feel that there is information, other than
what is disclosed in the financial reports, that are more beneficial in terms of
investment opportunities, the value-relevance will most likely decline. This can perhaps be what is
reflected in Model 2 and Model 3, compared to Model 1.
26 BOGSTRAND AND LARSSON
If it is the general consent on the market that publicly available accounting information is too
uncertain with regards to the financial situation on the market, the investment community might consider
knowledge, other than financial, when anticipating investment prospects. For example, organic growth
companies, i.e., companies that grow without acquisitions, are good investment opportunities because they
are a safer option, in terms of risk, especially in turbulent times. Another area that is highly important, and
should receive further attention, is the very substance of the income
statement, the cash flow statement and the balance sheet within each company. Thus, if investors
believe new accounting information to be unjustifiable, they might consider investing in companies that
over time have proven that they have a strong economy and the financial ability to overcome obstacles.
The economical strength of each company should definitely be taken into consideration when
discussing the value-relevance of their financial information, and on that note, e.g., the balance sheet
information can have very high impact on each respective company's market capitalization. In other
words, if a company has an exceptionally strong (weak) financial leverage in the balance sheet, it most
likely will affect the market capitalization positively (negatively). Therefore, it is also important to keep in
mind that some companies might have implicating effects in relation to this study, e.g., due their strong
(weak) balance sheet information and how this affects the market.
During the whole sample period, 2001-2010, information technology has been growing and
evolving, leading to a significant increase in the amount of information available to investors and
other stakeholders, as well as an increase in the time it takes for information to become obsolete. In other
words, the developments within information technology can also be argued as an important contributor
when it comes to the value-relevance discussion. Connecting this argument to the findings in this study, the
lower value-relevance found in Model 2 and Model 3 for the post-IFRS period can also be explained by the
evolvement in information technology and the adjacent increased
informational flow. This can even be linked to the previous arguments regarding investors utilizing
other information, i.e., investors that are faced with an expanded area of information and thus either find it
difficult to apprehend the financial information, react to other information available or even combine
financial information with other information available. This can lead to decreased value- relevance of
specific accounting components since market capitalization also contain a wide range of different
information.
Another implication, yet to be mentioned, is that the data for the pre-IFRS period cover fewer
years than the data for the post-IFRS period. The analysis might suffer from biased results due to this,
since, having fewer analyzable years in the pre-IFRS period than the post-IFRS period can affect the
regression results. When analyzing data with fewer observations it is more likely to be more sensitive to
extreme values and thus yield significantly stronger, or weaker, results. Likewise, the data for the post-
IFRS period contain more observations than the pre-IFRS period and it can be assumed that
accounting variables stabilize over time, the post-IFRS results might therefore be lower than the pre-
IFRS results. Nevertheless, both the pre-IFRS period and the post-IFRS period have sufficient
observations to be analyzed, and therefore it is important to also keep in mind that there might be other
reasons, such as those mentioned above, causing the incline in value-relevance from the pre- IFRS period to
the post-IFRS period.
In total, there is significant empirical evidence that book values, accruals and cash flows all have
value-relevance. Book values are in most of the regression models very important when trying to
explain the variation in market capitalization. In Model 2 and Model 3 the results indicate that the value-
relevance of book values, accruals and cash flows have decreased after the implementation of IFRS, while
the results in Model 1 indicate that the value-relevance have increased. This can, however, as discussed in
detail above, have several explanations. Conclusively, it is imperative to keep in mind that the results of
this analysis are valid only for the exact years, sample and
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 27
methodology as presented earlier in the paper. In the following and final section, we will summarize and
draw our conclusions regarding the findings presented above. We will also provide some suggestions for
further research.
VII. SUMMARY AND CONCLUSIONS
This paper examines the value-relevance of Scandinavian earnings information and book values over the
past decade in order to shed some light on whether the extensive global adoption of IFRS-
reporting has contributed to an increased accounting quality in terms of economic decision-usefulness to
equity investors. Our inquiry is motivated by the recent practical and empirically validated concern of an
eroded economic decision-functionality of publicly reported accounting information. Particular concern
among practitioners such as corporate accountants, auditors and financial analysts has been directed
towards the declined decision-usefulness of bottom line amounts based on accruals and cash
flows.
We address this research question using a sample of 4.310 firm-year observations for 431 exchange-
listed companies at NASDAQ OMX Nordic and Oslo Stock Exchange between 2001 and 2010. The degree
of value-relevance in our firm sample is operationalized through two price regressions and one return
regression and empirically tested via the statistical association between capitalized values of equity or
annual changes in capitalized values of equity and the study's three
independent explanatory accounting variables: (i) book values, (ii) accrual-based earnings and (iii)
cash-flow-based earnings. To maintain comparability across tables and graphs and thus the possibility to
triangulate our results, all tests are based on the same broad set of exchange-listed firms. And in order to
mitigate the possibility of incorrect inferences associated with scale-related effects such as size differences
across firms and extreme values in the firm sample, panel data regressions are conducted in all the three
regression models.
The results from our empirical tests show that both Scandinavian earnings information, accrual-
based as well as cash-flow-based, and book values are positively associated, albeit, to varying degrees,
with capitalized market values of equity as well as with annual changes in capitalized market values of
equity. These results are broadly consistent with previous value-relevance related research, originating from
the seminal discoveries of Ball and Brown (1968) and Beaver (1968). The results are also, at least to some
extent, in line with our theoretical predictions of the modern utilitarian role of
publicly reported accounting information. However, unlike previous value-relevance related research,
particularly empirical research carried out on accounting data between the early 1990s and the beginning
of the twenty first century, our results show a relatively strong explanatory power, regardless of the
regression used. This indicates, in comparison to previous periods, that there has been an increased value-
relevance among bottom line amounts based on both accruals and cash flows over the full sample period.
Similar reasoning applies also to Scandinavian book values, albeit, not in
the same extent.
Worth emphasizing is that our tests within the sample period - pre- and post the mandatory adoption of
IFRS-reporting in January 2005 - demonstrate somewhat mixed empirical signals on whether the
explanatory variables adopted in the study exhibit higher or lower value-relevance after the shift from
voluntary to mandatory IFRS disclosure. Findings from the lagged price regression as well as the return
regression show significant signs of a decline in value-relevance subsequent to the
mandatory adoption of IFRS, while the reverse reasoning applies for the results from the unlagged
price regression. Namely that, book values, accrual-based earnings and cash-flow-based earnings, in
connection with the shift from voluntary to mandatory IFRS disclosure, exhibit an increase in value-
relevance. A possible explanation for this discrepancy might, as discussed in Section V, stem from the fact
that the pre-IFRS period is characterized by a strong economic upturn, particularly in the
28 BOGSTRAND AND LARSSON
technology-sector, while the post-IFRS period to a great extent is reflected by a number of destructive
effects caused by the financial turmoil that emerged between 2007 and 2008. Part of the explanation can of
course also be attributed to the fact that the unlagged price regression mirrors the information at the time of
the announcement, while the lagged price regression looks at how the information is reflected in the
subsequent year's price and the return regression as reflected in annual changes between capitalized market
values of equity and the study's three explanatory variables.
Taken as a whole, our results show significant empirical evidence of an increased value-relevance
in Scandinavian earnings information as well as in Scandinavian book values compared to earlier periods as
presented in previous research, and thereby also as evidence of an increased accounting quality in terms of
economic decision-usefulness to equity investors over the past decade. However, we are, at the same time,
due to our mixed empirical findings within the full sample period, unable to conclude whether or not this
increased value-relevance is related to the adoption and implementation
of IFRS-reporting, and therefore also unable to conclude whether or not the harmonized regulatory
framework of accounting standards surrounding the current IFRS-based reporting model is moving
corporate disclosure regulation in a satisfying direction. Nevertheless, as hinted above, we are able to
conclude that publicly reported accounting information, disclosed in the income statement, the cash flow
statement and the balance sheet, not have continued to lose its relevance. On the contrary, it has regained
much of the decision-usefulness that has been lost in the past. However, to fully understand
whether or not this can be related to the adoption and implementation of IFRS-reporting, further
research, which in depth considers the concerns within the full sample period, is necessary to undertake.
Contribution
We believe that the results in this study are pertinent to both Scandinavian investors and to
accounting standard-setting bodies such as the IASB and the FASB since it - to some extent - penetrates
the relatively unresolved question of whether or not the current IFRS-based regulatory framework has been
fruitful in terms of an increased economic decision-usefulness among financial
statement information, which provide equity investors with resourceful material as well as with
valuable insights on the relevance and reliability of Scandinavian accounting numbers.
We also believe that our study might be useful in regions other than the Scandinavian, particularly in
countries where directives from the European Union are compulsory to follow and where the accounting
philosophy is the same. The study might also be of value to regions outside the European Union with an
investment environment similar to the Scandinavian and where IFRS-reporting recently
have been or will be adopted.
The analyses in this paper also raise a number of other interesting questions and unresolved issues
related to financial reporting and the current IFRS-based regulatory framework. In the following and final
subsection, we therefore list some of the more interesting areas where value-relevance research might be
fruitful or where value-relevance research could be improved.
Suggestions for Further Research
Our first research suggestion is detailed studies of the specifics in the regulatory framework of
accounting standards that surround the current IFRS-based financial reporting model. Increased
insights and understanding of how these accounting standards are perceived, interpreted and utilized
by users such as corporate accountants, auditors and financial analysts would certainly contribute to the
overall international debate on harmonized accounting standards and to the issue of whether or not we
should have a global framework for financial reporting. By studying the specifics, we would also be able to
approach an answer of the underlying raison d'être for the increased value-relevance in the
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 29
Scandinavian region. Given the recent global changes from a traditional capital-intensive economy into a
high-tech and service oriented economy with knowledge-intensive companies, we suggest that particular
research interest is directed towards intangible assets and the, since long, controversial subject of goodwill
- typically referred to as the black sheep of the balance sheet. Accounting standards of particular research
interest should therefore include IAS 38, which deals with both intangible assets and internally generate
goodwill. Particular research interest should also include
IFRS 3 where business combinations and thus externally generated goodwill are treated. IAS 36
should also obtain some research interest since it deals with impairments of both intangible assets and
goodwill, internally as well as externally generated.
A second suggestion for further research is to test and compare the value-relevance of annual and
quarterly earnings in order to shed some light on whether the market adopts and reacts to audited- and non-
audited financial information differently. Relative value-relevance comparisons of annual and
quarterly accounting data will to a great extent also reflect and address questions associated with the
modern role of the auditor.
A third research suggestion is to address and discuss the implications of the many underlying
assumptions and econometrical issues that surround value-relevance related research. Tests of market
efficiency could bring us closer to an answer of how rapidly equity investors react upon announcements
of publicly reported accounting information and improvements of equilibrium models
can help us broaden the scope of value-relevance research by eliminating some of the limitations that
is related to the simplifying assumptions of rational market behavior among investors.
A fourth and closely related issue to investigate is how we methodologically can address the fact that
financial information might be relevant - in that it is capable of making a difference in a decision as issued
in the conceptual framework for financial reporting - even though some user choose not to take advantage
of it or are already aware of it from other sources of information.
As a fifth and final recommendation for further research, we suggest studies that advance the
current knowledge on how we could simplify financial reports and statements into a language that is
understandable to even untrained accounting individuals. Research attention should primarily be directed
towards the problem of so-called black-box accounting where complex principle-based accounting
standards enable companies to hide unfavorable information by restating facts and include unnecessary
technical information, which easily can confuse untrained investors and force them into
wrong economic decisions. Contributions in this research area would benefit the society on a both
personal investor level and on a broader macro-economic level since it would increase the possibility for
investors, untrained as well as trained, to avoid investing in unprofitable companies, which, in the long run,
would benefit the society by mitigating the possibility for so-called lemons to exist.
30 BOGSTRAND AND LARSSON
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Statistics, Norway., 2012. "Ownership of Shares
in Companies Listed on The Norwegian Stock
Exchange" ssb.no.
Statistics, Sweden., 2012. "Ownership of Shares
in Companies Listed on The Swedish Stock
Exchange" scb.se.
doc_293517079.docx
The concept of relevance is studied in many different fields, including cognitive sciences, logic, and library and information science. Most fundamentally, however, it is studied in epistemology. Different theories of knowledge have different implications for what is considered relevant and these fundamental views have implications for all other fields as well.
How Increased Value-Relevance?
ABSTRACT
This paper examines the value-relevance of Scandinavian earnings information and book values over the past
decade in order to shed some light on whether the extensive global adoption of IFRS/IAS has
contributed to an increased accounting quality in terms of economic decision-usefulness to equity
investors. We address this research question using a sample of 4.310 firm-year observations for 431 exchange-
listed companies at NASDAQ OMX Nordic and Oslo Stock Exchange between 2001 and 2010. The degree of
value-relevance in our firm-sample is operationalized through two price regressions and one return regression
and empirically tested via the statistical association between capitalized values of equity or annual changes in
capitalized values of equity and the study's three explanatory accounting variables: (i) book values, (ii) accrual-
based earnings and (iii) cash-flow-based earnings. Taken as a whole, our results show significant empirical
signs of an increased value-relevance in both Scandinavian earnings information and book values, allowing us
to draw significant as well as contributing conclusions on the information content of financial statement
information disclosed in the
Scandinavian region. We believe our study adds empirical substance to practical debates over the
function of financial reporting as well as resourceful material to both Scandinavian investors and to the
ongoing international discussion on the harmonization of financial reporting standards.
Keywords • Accruals, Book Values, Cash Flows, Earnings, FASB, IASB, IFRS, Value-Relevance
I. INTRODUCTION
THE OBJECTIVE OF THIS STUDY is to examine the value-relevance of earnings information and book values
over the past decade in order to shed some light on whether the extensive global adoption of
International Financial Reporting Standards and its predecessor set of standards, International Accounting
Standards, henceforth IFRS
1
and IAS
2
respectively, has contributed to an increased accounting quality in
terms of economic decision-usefulness to equity investors. Our inquiry is motivated by the recent practical
concern of an eroded economic relevance of publicly reported accounting information. Particular concern
among practitioners such as corporate accountants,
auditors and financial analysts (e.g., Jenkins, 1994 and Elliott, 1995) and academics (e.g., Francis and
* We gratefully acknowledge both comments and guidance from our tutor Katarzyna Cieslak at Uppsala University. We are
also grateful for valuable insights by our discussants at the SUMA program. The paper has also benefitted from resourceful
material by Thomas Plenborg at Copenhagen Business School and from the comments of Andreas Widegren at Uppsala
University.
Correspondence to † [email protected] and/or to‡ [email protected]
1 The European parliament and the council of the European Union made it via regulation number 1606/2002 mandatory for all
publicly traded companies within the European Union and the European Economic Area to prepare their consolidated
financial statements in accordance with International Financial Reporting Standards no later than 1 January 2005.
2 The main difference between IAS's and IFRS's is that the former were issued by the International Accounting Standards
Comittee, IASC, between 1973 and 2001, while the latter were issued by the International Accounting Standards Board,
IASB, from 2001 and onwards. Both types are included in the regulatory accounting framework that surrounds IFRS-
reporting.
2 BOGSTRAND AND LARSSON
Schipper, 1999 and Lev and Zarowin, 1999) has been directed towards the declined decision- usefulness
of earnings information, especially towards bottom line amounts based on accruals and
cash flows.
3
We address this research question on the basis of Scandinavian data using a sample of 4.310 firm- year
observations for 431 exchange-listed companies at NASDAQ OMX Nordic
4
and Oslo Stock Exchange
between 2001 and 2010. The choice of the Scandinavian region, where we, in addition to
the three genuine Scandinavian countries - Denmark, Norway and Sweden - also include Finland, is
motivated for several reasons. The main rationale stems from the fact that the Scandinavian region, due to
its investor-oriented accounting philosophy, strong legal enforcement and relatively stable external
surroundings, today and in turbulent times such as these, represents an established and secure
and thus attractive investment environment appealing to investors from all over the globe.
5
The attraction of the Scandinavian market is particularly evident when looking at the increasing
rate of publicly listed companies owned by foreign investors. Denmark, Finland, Norway and Sweden
have all seen the proportion of foreign non-Scandinavian ownership increase from a level of around 1.00-
5.00 percent to a level of around 20.00-40.00 percent since the early 1990s (Statistics Denmark, 2012;
Statistics Finland, 2012; Statistics Norway, 2012 and Statistics Sweden, 2012). Sweden, as an example, saw
the proportion of non-Scandinavian ownership increase from a level of 1.70 percent
6
to a level of 23.10
percent
7
between 1990 and 2010. This number corresponds to an average yearly
increase in non-Scandinavian ownership of about 13.90 percent
8
over the past two decades. Similar
increases have occurred also in Denmark, Finland and Norway, leading to an increased need among
investors also outside the Scandinavian region to obtain knowledge about the informational content in
Scandinavian earnings information and book values.
The degree of value-relevance in our firm sample is operationalized through two price regressions and
one return regression and empirically tested via the statistical association between capitalized
values of equity or annual changes in capitalized values of equity
9
and the study's three independent
explanatory accounting variables: (i) book values, (ii) an accrual component of earnings, and (iii) a cash-
flow component of earnings. To maintain comparability across tables and graphs and thus the possibility to
triangulate our results, all tests are based on the same broad set of exchange-listed firms. And, in order to
mitigate the possibility of incorrect inferences associated with scale-related effects such as size differences
across firms and extreme values in the firm sample, panel data regressions are
conducted in all the three regression models.
The results from our empirical tests show that both Scandinavian earnings information, accrual- based
as well as cash-flow-based, and book values are positively associated, albeit, to varying degrees, with
capitalized equity values as well as with annual changes in capitalized equity values.
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 3
These results are broadly consistent with previous value-relevance related research, originating from the
seminal discoveries of Ball and Brown (1968) and Beaver (1968). The results are also, at least to some
extent, in line with our predictions of the modern utilitarian role of publicly reported accounting
information in the Scandinavian region. However, unlike previous value-relevance related research,
particularly empirical research carried out on accounting data between the early 1990s and the beginning
of the twenty first century, our results show a relatively strong explanatory power,
regardless of the regression used. These results in combination with the statistical strength allow us to
draw both significant and contributing conclusions with regards to publicly reported accounting
information, disclosed in Scandinavian financial statements.
We believe that the results in this study are particularly pertinent to accounting standard-setting bodies
such as the International Accounting Standards Board and the Financial Accounting Standards Board,
henceforth IASB and FASB respectively, since it, to some extent, penetrates the relatively
unresolved question of whether or not the current IFRS-based regulatory framework has been fruitful
in terms of an increased economic decision-usefulness of Scandinavian financial statement information.
Our conclusions also provide equity investors with both resourceful material and valuable insights on the
relevance and the reliability of Scandinavian accounting numbers. We also believe that our study might be
useful in regions other than the Scandinavian, especially in countries where directives from the European
Union are compulsory to follow and where the accounting
philosophy is the same. The study might also be of value to regions outside the European Union with
an investment environment similar to the Scandinavian and where IFRS-reporting recently have been or
will be adopted.
Outline
The remainder of the paper is organized as follows. Section II presents the background of the
study where we highlight the primary objective of general purpose financial reporting and discuss its
utilitarian role in capital markets. In Section III we review and discuss previous research, which, in turn,
constitutes the underpinning theoretical ground for our empirical study. First, we present
different types of value-relevance related studies, which, in particular, include various ways to
operationalize and interpret value-relevance. Thereafter, we draw attention to the most significant empirical
findings since the seminal discoveries of Ball and Brown (1968) and Beaver (1968). Ultimately, we sum
up by formalizing our predictions for this study. In Section IV we present our methodological approach.
Section V presents data and descriptive statistics and in Section VI we interpret, discuss and analyze our
empirical results. Section VII finally summarizes the study and we
reveal our conclusions and provide some suggestions for further research.
II. BACKGROUND
Economic decision-usefulness is typically viewed as one of the most important attributes of publicly
reported accounting information, particularly among users such as equity investors, lenders and other
capital providers (Francis, LaFond, Olsson and Schipper, 2004). The attribute of economic decision-
usefulness is therefore - by accounting standard-setting organizations such as the IASB and the FASB
- also recognized as a fundamentally significant qualitative characteristic in the pursuit of high account ing
quality
10
in corporate reports and financial statements. The importance of economic
4 BOGSTRAND AND LARSSON
decision-usefulness is especially evident when looking at the primary objective of general purpose
financial reporting as stated in the conceptual framework:
11
The objective of general purpose financial reporting is to provide financial information about the reporting entity
that is useful to existing and potential investors, lenders and other creditors in making decisions about providing
resources to the entity. Those decisions involve buying, selling or holding equity and debt
instruments, and providing or settling loans and other forms of credit. IASB, 2010 and FASB, 2010.
If publicly reported accounting information is to be considered as useful for economic-decision
making, it must be both relevant and faithfully represent what it purports to represent in the financial
reports (IASB, 2010 and FASB, 2010). The conceptual framework for financial reporting define relevant
accounting information as information capable of making a difference in the decisions made by users
12
and
faithful accounting information as information that is complete, neutral and free from error, typically
referred to as reliable accounting information in value-relevance related research; see, e.g., Barth, Beaver
and Landsman (2001) and Holthausen and Watts (2001).
This means, in a more general sense, that publicly reported accounting information, disclosed in
annual as well as in quarterly corporate reports and financial statements, is set out to serve the public
interest by functioning as a corporate blueprint of the financial health so that its users can assess aspects
associated with corporate growth, profitability and risk
13
in order to make smart and informative
economic decisions. Accordingly, financial reporting does not only constitute an important source of
information when assessing the performance of firms, but also a valuable and
critical cornerstone set out the meet the society's need for an effective as well as an efficient capital
resource allocation. In the following subsection, we therefore reflect upon the critical role of financial
reporting in capital markets.
The Role of Financial Reporting in Capital Markets
A critical challenge for any economy is to assign available financial resources in an economically
efficient manner (Healy and Palepu, 2001). Much of this challenge stems from difficulties in overcoming
the problem with the information asymmetry that exist between companies and potential capital investors
and with the incentive issue that arise between the producer of accounting
information and the user of accounting information once an investment has been placed; see,
Akerlof (1970) and Jensen and Meckling (1976). Frequently discussed along these two dilemmas is the
lemon problem, which, potentially, can break down the very functioning of the capital market. It
works like this:
Consider a situation where half the business ideas are "good" business ideas and where the other half of the business
ideas is "bad" business ideas. If investors cannot distinguish between the two types of business
ideas, entrepreneurs with "bad" ideas will try to claim that their ideas are as valuable as the "good" ideas.
Realizing this possibility, investors value both good and bad ideas at an average level. Unfortunately, this penalizes
good ideas, and entrepreneurs with good ideas find the terms on which they can get financing to be unattractive. As
these entrepreneurs leave the capital market, the proportion of bad ideas in the market
increases. Over time, bad ideas "crowd out" good ideas, and investors lose confidence in this market. Palepu,
Healy and Peek, 2010.
Economies that overcome these problems well can exploit new business ideas to spur innovation
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 5
and create jobs and wealth at a rapid pace; meanwhile, economies that manage this process poorly dissipate
their wealth and fail to support business opportunities (Healy and Palepu, 2001). In overcoming the lemon
dilemma and prevent such a capital market breakdown, intermediaries, financial
14
intermediaries as well as
information
15
intermediaries, are of great value to capital markets since they help investors and other
stakeholders to distinguish between good and bad investment opportunities (Palepu, Healy and Peek,
2010).
Accordingly, financial reporting and other corporate disclosures clearly have high importance for
the functioning of capital markets since it to a great extent is the information that investors and other
stakeholders adopt and concurrently react upon, and therefore also an important source of information to
scrutinize and conduct empirical research on. In the following section, we therefore present the primary
purpose of value-relevance related research along some of the most seminal empirical findings related to
the objective of this study.
III. PREVIOUS RESEARCH
The primary purpose with empirical tests of value-relevance is to examine whether publicly reported
accounting information, disclosed in annual as well as in quarterly corporate reports and financial
statements, fulfill its utilitarian role of being useful for economic decision-making (Barth et al., 2001 and
Holthausen and Watts, 2001). That is, to investigate whether users such as equity investors,
lenders and other capital providers appreciate the information and perceive it as relevant once it has
been publicly available in the marketplace.
A significant portion of the value-relevance related research is therefore, either explicitly or implicitly,
motivated from an accounting standard-setting point of view, especially vis-à-vis the accounting criteria of
relevance and reliability as specified in the conceptual framework for financial reporting (Holthausen and
Watts, 2001; Kothari, 2001 and Francis et al., 2004).
Important to note is that there is no such thing as a standardized one-way-solution on how to
assess how well a particular accounting amount reflects information used by investors. However, in
general, it is measured as the ability of earnings information and book values to explain market values of
equity and/or changes in market values of equity (Barth et al., 2001; Holthausen and Watts, 2001 and
Beaver, 2002). A typical value-relevance study therefore examines the relationship between an equity-
dependent variable such as security prices and/or security returns
16
with a set of explanatory
accounting variables, typically book values in combination with at least one bottom line amount of
earnings information based on either accruals or cash flows or both.
In the extant accounting literature, an accounting amount is defined as value-relevant, i.e., able to change investors'
assessment of the probability distribution of an entity's future earnings capacity, if it has a significant predicted
association with an equity-dependent variable such as share prices and/or security returns. Barth et al. (2001).
Accordingly, publicly reported accounting information can be viewed as value-relevant if it reflect
a significant portion of the capitalized equity value or if the information is significantly associated
6 BOGSTRAND AND LARSSON
with changes in the capitalized equity value.
17
However, significant results of value-relevance, i.e., data
indicating that an accounting amount is relevant and reliable, at least to some degree, are difficult to assign
to one or the other attribute (Barth et al., 2001). This, since neither relevance nor reliability is of
dichotomous nature nor does the conceptual framework specify the extent to which relevance or reliability
is sufficient enough to meet IASB's and FASB's criteria of decision-useful information; see, e.g., IASB
(2010) and FASB (2010). As a result, regardless of the empirical test used, value-
relevance related research is carried out as joint tests of relevance and reliability and therefore, by
researchers, typically seen as a direct operationalization of the decision-usefulness objective as specified
in the conceptual framework.
Worth emphasizing is that value-relevance related research to a great extent is premised on the notion
of some sort of capital market equilibrium since it assume that a substantial degree of the information
content in earnings information and book values is strongly reflected in equity-dependent
variables such as security prices, stock returns and/or trading volumes (Barth et al., 2001; Holthausen
and Watts, 2001 and Kothari, 2001). Much of the value-relevance related research is therefore based on the
underlying assumption of the existence of efficient capital markets
18
and/or on the descriptive validity of an
equilibrium model such as the capital asset pricing model, hereafter CAPM
19
for convenience, or any
extension of the model (Lev and Ohlson, 1982; Kothari and Zimmerman, 1995; Barth et al., 2001;
Holthausen and Watts, 2001 and Kothari, 2001). In the following subsections, we
will present some of the most seminal and important empirical findings that relates to the objective of
this paper.
Early Empirical Findings based on Association Studies
20
Ball and Brown's pioneering study from 1968 was the first paper to formalize the positive
relationship between security returns and earnings information. That is, they established the fact that
movements in common stock partly can be explained by the information content in earnings numbers such
as by accrual-based net income and cash-flows, as approximated by operating income. The
17 Another approach to operationalize value-relevance is to examine whether there is any abnormal security price volatility
and/or abnormal trading volume around the announcement period. This approach originates from Beaver (1968) and Fama,
Fischer, Jensen and Roll (1969).
18 The theory of efficient capital markets is concerned with whether security prices at any point in time fully reflect all
available information and reaches market equilibrium. The assumption of some sort of market equilibrium is, in turn,
typically referred to as the efficient market hypothesis, henceforth EMH, which, originally, was developed by Fama in 1965. It is
common to distinguish among three versions of the EMH, viz., the weak form, the semi-strong form and the strong
form. These versions differ by their notions of what is meant by the term all available information. Specifically, the weak
form asserts that security prices reflect all information that can be derived by examining market-trading data such as the
history of past prices, trading volume and/or short interest, while the semi-strong form asserts that stock prices reflect all
publicly available information regarding the prospects of an entity, which, in addition to past prices and other technical
figures, includes fundamental information such as an entity's product line, quality of management, earnings forecasts and
balance sheet composition. The strong and final form of the EMH asserts that stock prices reflect all information that is
relevant to the firm, including monopolistic information available only to company insiders. These three versions are
discussed in great detail in Fama's seminal paper from 1970.
19 The capital asset pricing model, CAPM, or any extension of the model, e.g., the zero-beta model, is a set of predictions with
regards to equilibrium expected returns on risky assets, which, to a great extent, rests on the foundation of Harry
Markowitz's (1952) modern portfolio theory. The model itself was independently developed by Sharpe (1964),
Lintner (1965) and Mossin (1966) and can in general terms be described as a simplified version of investors and their
behavior in the marketplace. Specifically, the model assumes that all investors are price-takers, in that they act as though
security prices are unaffected by their own trades, and that they are rational and risk-averse and aim to maximize economic
utilities. The model also assumes that all investors can lend and borrow unlimited amounts under the risk-free rate of
interest, and that they analyze securities in the same way and that all investors share the same economic view the world.
Obviously, the model ignore many real world complexities and is therefore constantly subject to criticism; see, e.g.,
Grossman and Stiglitz (1980), Kandel and Stambaugh (1995), Fama and French (1992), Roll (1977) and Roll and
Ross (1994).
20 An association study conducts empirical tests on the relationship between publicly reported accounting information,
typically earnings information and/or book values, and security prices and/or returns over relatively long observation
windows such as one or several years (Kothari, 2001).
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 7
positive relationship between security returns and earnings information has also been confirmed in a
number of other different economic settings (see, e.g., Beaver and Dukes, 1972; Beaver, Lambert and
Morse, 1980; Lipe, 1986; Rayburn, 1986; Bowen, Burgstahler and Daley, 1987; Collins and
Kothari, 1989; Livnat and Zarowin, 1990; Dechow, 1994; Ali and Pope, 1995 and Basu, 1997).
Ball and Brown (1968) also highlight the fact that more prompt media like interim reports and quarterly
earnings tend to supersede the information in annual reports and that most of the information
contained in annual earnings and book values therefore is anticipated by the market before it is
released. In other words, when annual earnings information and balance sheet information is announced
the information might already be obsolete. Kothari (2001) share the same view as Ball and Brown (1968)
and argues that investors and stakeholders in today's capital markets are utilizing quarterly reports and other
more timely information, leading to a scenario where annual reports as a consequence are rendered less
useful.
Early Empirical Findings based on Event Studies
21
Ball and Brown (1968) and Beaver (1968) both provide compelling evidence indicating that
earnings announcements seem to capture the performance of firms. The key argument in the two
pioneering event studies is that there is a substantial empirical association between earnings
announcements and security prices. Ball and Brown (1968) find that the market positively (negatively)
adopts information with regards to unexpected increased (decreased) earnings, which, leads to an increase
(decrease) in security prices. Beaver (1968) examines movements of security prices and trading volume at
the time of the earnings announcements. First, and foremost, his
argument is that company information is more available, scrutinized and adopted surrounding
earnings announcements vis-à-vis periods with no earnings announcements. The findings in Beaver's
(1968) study are bracketing the findings in Ball and Brown's (1968) study, forwarding the fact that earnings
information positively adheres to the market price of securities. Specifically, in periods where earnings
announcements are made, the flow of information increases, and the stock prices are to a great extent
reflecting the content and quality of this information.
Accordingly, early event studies find that the flow of information is higher in periods with
earnings announcement in contrast to periods with no earnings announcements and that information
released by publicly listed companies significantly affects security prices. More recent event studies
support the seminal finding of a significant association between earnings announcements and security
prices; see, e.g., Landsman and Maydew (2002) and Landsman, Maydew and Thornock (2012).
Decline in Value-Relevance of Publicly Reported Accounting Information
It is apparent from early value-relevance related findings that earnings information as well as book
values are positively associated with contemporaneous security returns and reflected in capitalized
equity values over time. However, since the early 1990s, concerns have been expressed by academics
(e.g., Francis and Schipper, 1999 and Lev and Zarowin, 1999) as well as by accounting practitioners in the
financial press (e.g., Rimerman, 1990; Sever and Boisclair, 1990; Elliot, 1994a; Elliot, 1994b, Jenkins,
1994 and Elliott, 1995) that publicly reported accounting information, disclosed in corporate reports and
financial statements, has lost a significant portion of its relative economic decision- usefulness to other
sources of information available in the market place. In particular, it is claimed
that publicly reported accounting information, particularly book values and earnings information
8 BOGSTRAND AND LARSSON
based on accruals and cash-flows, today is less relevant in assessing the fundamental value of high-
technology, service-oriented firms, which, by nature are knowledge-intensive:
Early in the century, financial statements represented a large part of the information available to an enterprise's
debt and equity investors. As accounting principles improved, the value of financial statements
also improved. But, facilitated by information technology, other sources of relevant information are increasingly
available; for example, investors can get up-to-the-minute data about companies through public
and proprietary databases without waiting for quarterly or annual reports. Moreover, information technology
has created new ways for businesses to become more competitive; for example, continuous quality improvement,
cycle-time reduction and enhanced vendor and customer relations - effects of which are not
reflected in financial statements. Thus, financial statements describe modern companies less well than they
described industrial-era companies. Elliott, 1994b.
Hence, the traditional association between publicly reported accounting information and
capitalized values of equity have been called into question. Consistent with these claims Brown, Lo and
Lys (1999 and 2002), Francis and Schipper (1999), Lev and Zarowin (1999) and Core, Guay and Van
Buskirk (2003) find evidence for a decline in the value-relevance of both earnings information
and book values. Value-relevance is in these studies mainly tested for through price-level/return
regressions, where the adjusted explanatory power of the coefficient of determination (R
2
) typically is used
as the yardstick of value-relevance. A higher adjusted R
2
is generally taken as evidence of higher value-
relevance, which, under normal circumstances, means that the accounting amount with the highest
adjusted R
2
is interpreted as most relevant and reliable to its users. Worth emphasizing is that there also are
findings with somewhat contrary indications. For example, Collins, Maydew and
Weiss (1997) find no evidence of a decline in the value-relevance of earnings information and book
values. In fact, they find evidence for a slight increase in value-relevance, particularly among book values
and other balance sheet information.
IFRS Adoption
A growing body of the most recent value-relevance related research examines the implications of
the increasingly widespread adoption of IFRS-reporting among stock exchanges and accounting standard-
setting bodies all over the globe. Heretofore, the research provides somewhat mixed empirical signals on
whether financial statements prepared in accordance with IFRS/IAS exhibit
higher accounting quality than financial statements prepared in accordance with other sets of generally
accepted accounting principles (Ball, 2006 and Leuz and Wysocki, 2008). Worth repeating is that the
European Union did not mandate the use of IFRS-reporting for publicly listed companies until January
2005. As a result, much of the overall impact of IFRS-reporting is therefore yet still to be determined.
Mixed Evidence on Voluntary IFRS Adoption
Barth, Landsman and Lang (2008) analyze changes in the properties of reported earnings around
voluntary adoption of IFRS-reporting and find empirical evidence that publicly reported accounting
information prepared in accordance with IFRS/IAS generally exhibit less earnings management, more
timely loss recognition and higher value-relevance than publicly reported accounting information prepared
in accordance with other generally accepted accounting principles. This allows them to conclude that
financial statements prepared in accordance with IFRS/IAS generally are associated with higher accounting
quality compared to financial statements prepared in accordance with other domestic accounting standards.
This conclusion is supported by empirical evidence from a cross-
sample comparison between German-based, US-based and IFRS-based generally accepted accounting
principles in a study carried out by Bartov, Goldberg and Kim (2005). The view of higher accounting
quality in conjunction with voluntary adoption of IFRS-reporting is also the general opinion of
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 9
Soderstrom and Sun (2007) and Leuz and Wysocki (2008) in their reviews of empirical studies examining
the implications of voluntary IFRS adoption. However, contrary to this view, Hung and Subramanyam
(2007) find no evidence for a higher value-relevance associated with voluntary IFRS- reporting and thereby
no evidence for a higher accounting quality among financial statements prepared in accordance with
IFRS/IAS. Eccer and Healy (2003) find similar results in their cross- sample comparison between
accounting amounts based on IFRS/IAS standards and accounting
amounts based on Chinese standards.
Overall, the empirical evidence on voluntary IFRS disclosure is somewhat mixed. Possible
explanations for this diversity might be due to sample selection biases and/or methodological issues such as
omitted variables, lack of robustness and/or problems with deflation among the firm sample; see, e.g.,
Brown et al. (1999 and 2002) and Barth and Clinch (2009). Another possible explanation for the mixed
results stem from the many institutional factors that surround each and every industry,
country and region. In the following subsection, we therefore discuss some empirical evidence upon
the importance of institutional factors.
The Importance of Institutional Factors
Looking at previous research with regards to the IFRS debate, there are, as mentioned above,
somewhat mixed empirical evidence, particularly with respect to voluntary IFRS-reporting. This is, as
noted above, assumingly, associated with either econometrical issues or with the quality of the legal
environment and institutional factors that surrounds each and every industry, country and region.
Specifically, institutional factors such as regulatory accounting frameworks and investor protection
are immensely important factors for how companies and investors act with regards to financial
reporting (Soderstrom and Sun, 2007 and Leuz and Wysocki, 2008). The strength of domestic regulatory
bodies is closely connected to the interplay between companies and investors, and will, concurrently,
affects what kind of information, and in what way, companies display (in) their financial reports (Ball,
Kothari and Robin, 2000 and Leuz, Nanda and Wysocki, 2003). The key argument is that it might be
common in some industries, countries, and/or regions to mislead investors and other
stakeholders by acting on personal incentives rather than adhering to regulations, which, thus, reduce
the overall accounting quality by ignoring the relevance and the reliability of the financial reports.
The issues mentioned in the above are part of what the IASB and the FASB constantly are trying to
improve upon. Institutional factors that are of particular concern in previous research and associated with
stronger (weaker) reporting quality and thus stronger (weaker) accounting quality are strong (weak)
investor protection (see, e.g., La Porta et al., 2002); strong (weak) legal enforcement (see, e.g.,
Leuz and Wysocki, 2008) and a strong (weak) tax enforcement system (see, e.g., Guenther and
Young, 2000 and Haw, Hu, Hwang and Wu, 2004). The content of previous research, with regards to
institutional factors, is that a poor institutional quality will excavate the effectiveness of accounting
standards, which, as noted above, potentially might disassemble the main objective of accounting standards
and thus lead to a decreased accounting quality among financial reports. Accordingly, it is of vital
importance to be aware of the external surroundings when conducting value-relevance related
research.
Lack of Evidence on Mandatory IFRS Adoption
The European Union mandated, as mentioned in the introduction, the adoption and
implementation of IFRS/IAS in January 2005. Much of the overall impact with respect to the mandatory
adoption of IFRS-reporting is therefore yet still to be determined, particularly pertaining the accounting
quality in terms of economic decision-usefulness among equity investors. However, recently, Landsman,
Maydew and Thornock (2012) found that, in countries with mandatory IFRS-
MATRIX I
Value-Relevance Related Studies Examining Earnings Information and Book Values of Equity
AUTHORS AND YEAR TYPE OF STUDY DATA METHODOLOGY FINDINGS AND CONTRIBUTION
Ball and Brown, 1968 BB conduct a combined association The final firm sample includes 261 The degree of information content is The first paper to formalize the
and event study that examines the publicly listed companies. The data is operationalized via a return regression relationship between security returns
relative as well as the incremental obtained from Compustat, CRSP and that regresses change in firm-specific and earnings information. The paper
informational content of earnings The Wall Street Journal between 1957 earnings with change in market- also highlights evidence for the post-
information. and 1965. specific earnings. A simple time- earnings-announcement drift, the
series model, building on the relative importance of earnings
somewhat naïve assumption of a information and on the incremental
random walk, is used as a check of the value of different earnings
statistical efficiency of the first model. information.
Beaver, 1968 B conducts an event study that The final firm sample includes 143 The degree of information content in The first paper to find significantly
examines the information content of NYSE listed companies. The data is annual earnings announcements is strong empirical evidence for value-
annual earnings announcements. obtained from Compustat and The operationalized via both abnormal relevance in earnings information in
Wall Street Journal between 1961 and trading volume and abnormal security the week of the announcement.
1965. price volatility.
Collins, Maydew and Weiss, 1997 CMW conduct an inter-temporal The final firm sample includes The degree of value-relevance in CMW find no empirical evidence for a
association study that examines 115.154 firm-year observations for earnings information and book values decline in the value-relevance of
systematic changes in the value- NYSE, AMEXandNASDAQlisted is operationalized via the valuation earnings information and books
relevance of earnings information and companies. The data is obtained from framework provided by Ohlson values. Contrary, they find evidence book
values over time. Compustat and CRSP between 1953 (1995), which expresses price as a for a slight increase in the value-
and 1993. linear function of earnings information relevance of earnings information and
and book values. book values - over the sample period:
1953-1993.
Brown, Lo and Lys, 1999 BLL conduct an inter-temporal The final firm sample includes The degree of value-relevance in BLL find significant empirical
association study that examines 112.134 firm-year observations for earnings information and book values evidence for a decline in the value-
systematic changes in the value- publicly listed companies. The data is is operationalized via both price relevance of both earnings information
relevance of earnings information and obtained from Compustat and CRSP regressions and return regressions. and book values - over the sample book
values over time. between 1958 and 1996. period: 1958-1996.
Francis and Shipper, 1999 FS conduct an inter-temporal The final firm sample includes The degree of value-relevance in FS find significant empirical evidence
association study that examines
systematic changes in the value-
relevance of earnings information and
book values over time.
between 393 and 1.419 firms per year
for NYSE listed companies and
between 1.124 and 2.866 firms per year
for NASDAQ listed companies. The data
is obtained from Compustat
earnings information and book values
is operationalized via (i) price
regressions and return regressions, and
(ii) the total return that could be earned
from foreknowledge of
for a decline in the value-relevance of
earnings information, and an increase
in the value-relevance of balance sheet
and book value information over the
sample period, i.e., between 1952 and
and CRSP between 1952 and 1994 for publicly reported accounting 1994.
NYSE listed companies and between information.
1974 and 1994 for NASDAQ listed companies.
!!
10
!
MATRIX I (CONTINUED)
Value-Relevance Related Studies Examining Earnings Information and Book Values of Equity
AUTHORS AND YEAR TYPE OF STUDY DATA METHODOLOGY FINDINGS AND CONTRIBUTION
Lev and Zarowin, 1999 LZ conduct an inter-temporal The final firm sample includes The degree of value-relevance in LZ find significant empirical evidence
association study that examines between 3.700 and 6.800 firms per earnings information and book values of a decline in the value-relevance of
systematic changes in the value- year for publicly listed companies. is operationalized via both price both earnings information and book
relevance of earnings information and The data is obtained from Compustat regressions and return regressions. values - over the sample period: 1963-
book values over time. between 1977 and 1996 and from 1996.
CRSP between 1963 and 1995.
Landsman and Maydew, 2002 LM conduct an inter-temporal event The final firm sample includes 92.613 The degree of information content in LM find no empirical evidence of a
study that examines systematic firm-quarter observations for publicly quarterly earnings announcements is decline in the information content of
changes in the information content of listed companies. The data is obtained operationalized via both abnormal quarterly earnings announcements -
quarterly earnings announcements. from Compustat between 1972 and trading volume and abnormal security over the sample period: 1972-1998.
1998. price volatility.
Core, Guay and Van Buskirk, 2003 CGB conduct an inter-temporal The final firm sample includes The degree of value-relevance in CGB find empirical evidence of a
association study that examines 109.559 firm-year observations for earnings information and book values slight decrease in the value-relevance
systematic changes in the value- NASDAQ listed companies. The data is operationalized via price of earnings information and book
relevance of earnings information and is obtained from Compustat and CRSP regressions. values - over the sample period: 1975-
book values over time. between 1975 and 1999. 1999.
Bartov, Goldberg and Kim, 2005 BGK conduct a combined inter- The final firm sample includes 915 The degree of value-relevance in BGK find significant empirical
temporal and cross-sectional firm-year observations for Frankfurt, earnings information and book values evidence for a higher degree of value-
association study that examines NYSE, AMEX, NASDAQ and LSE is operationalized via a time-series relevance among accounting amounts
systematic changes in the value- listed companies. The data is obtained return regression and between three prepared in accordance with IFRS
relevance of earnings information and from The Global Vantage Database sets of generally accepted accounting reporting than accounting amounts book
values over time and between between 1998 and 2000. principles using a cross-sectional prepared in accordance with other three
different sets of generally return regression. accounting standards - over the
accepted accounting principles. sample period: 1998-2000.
Barth, Landsman and Lang, 2008 BLL conduct an inter-temporal The final firm sample includes 1.896 The degree of value-relevance in BLL find significant empirical
association study that examines firm-year observations for publicly earnings information and book values evidence for a higher degree of value-
systematic changes in the value- listed companies from 21 different is operationalized via both price relevance among accounting amounts
relevance of earnings information and countries. The data is obtained from regressions and return regressions. prepared in accordance with IFRS book
values over time, particular focus DataStream and WorldScope between reporting than accounting amounts revolves around accounting amounts 1990 and
2003. prepared in accordance with other prepared in accordance with IFRS accounting standards - over the
reporting. sample period: 1990-2003.
Landsman, Maydew and Thornock, 2012 LMT conduct a combined inter- The final firm sample includes 20.517 The degree of information content in LMT find significant empirical
temporal and cross-sectional event earnings announcements from 16 annual earnings announcements is evidence for a greater increase in both
study that examines systematic countries that mandated adoption of operationalized via both abnormal abnormal trading volume and
changes in the information content of IFRS/IAS and 11 countries that trading volume and abnormal security abnormal security price volatility in
earnings announcements, particular retained domestic accounting price volatility. firms that prepare their financial
focus revolves around accounting
amounts prepared in accordance with
IFRS reporting.
standards. The data is obtained from
I/B/E/S, DataStream and WorldScope
between 2002 and 2007.
!
11
statements in accordance with IFRS
reporting than in firms that follow other
accounting standards - over the sample
period: 2002-2007.
12 BOGSTRAND AND LARSSON
reporting the usefulness and utilization of information surrounding earnings announcements is greaterthan
in countries that have retained domestic accounting standards.
These findings, thus, indicate that IFRS-reporting positively affects the value-relevance of accounting
information, but the area is still an unexplored territory, especially with regards to value- relevance and the
effects of IFRS-reporting. The majority of previous research on mandatory IFRS- reporting cogitates how
IFRS/IAS has affected companies' cost of capital as well as the market
liquidity of its securities (see, e.g., Daske, Hail, Leuz and Verdi, 2008). The quality of accounting
measures and amounts is still somewhat imprecise, which connects to the fact that data regarding pre- and
post-IFRS adoption to a great extent still is unavailable. The main rationale for the lack of evidence on
mandatory IFRS-reporting is therefore, that there, until recently, has been non-existent analyzable data.
Empirical Summary and Predictions
Both earnings information and book values are, as appears from the preceding subsections and
Matrix 1 above, positively associated with contemporaneous security returns and reflected in
capitalized equity values over time. This is evident in both event- and association studies and applies
regardless of the specific parameters used. That is, irrespective of which expectation model, earnings
definition, return and price specification, statistical model and set of generally accepted accounting
principles the study is conducted on. It is also apparent that the relationship during the beginning of the
early 1990s until the beginning of the twenty first century has become weaker, which, in turn, indicates that
publicly reported accounting information, disclosed in financial statements, has lost a
significant portion of its relevance to equity investors. This could, in a worst-case scenario, lead to a
so-called lemon market, see, e.g., Akerlof, 1970, that potentially might frustrate the function and thus the
very objective of capital markets; see also, e.g., Jensen and Meckling (1976) and Healy and Palepu (2001).
Against the background of the mixed empirical evidence vis-à-vis voluntary IFRS adoption and the lack of
evidence vis-à-vis mandatory IFRS adoption, it is also clear that much of the implications of IFRS-
reporting are still yet to be determined, particularly with respect to the overall
reporting quality and whether or not the principle-based regulatory framework of accounting
standards has been fruitful in terms of an increased economic decision-usefulness to its users.
From the preceding subsections, Matrix I, and the above empirical summary, it is feasible to depict
some predictions with regards to this study. First of all, we believe that the Scandinavian region, in which
we include Denmark, Finland, Norway and Sweden, due to its investor oriented accounting philosophy,
strong legal enforcement and relatively stable external surroundings - institutional factors
of importance when implementing regulatory frameworks - has experienced an increase in the value-
relevance over the past decade. Worth to emphasize is that the relatively short time period equity investors
and financial intermediaries have had to adjust to the new set of accounting standards might have led to a
slight decrease in the post-adoption period. Our notion is that this will be revealed in an increase in the
explanatory power (adjusted R
2
) over the full sample period between 2001 and 2010 and in a slight
decrease in adjusted R
2
between the pre-IFRS period and the post-IFRS period.
IV. METHODOLOGY
In previous research, several models are being utilized to provide empirical results on the value- relevance
of accounting measures (see, e.g., Dechow, 1994; Kothari and Zimmerman, 1995 and Barth, Beaver, Hand
and Landsman, 2005). There are, as mentioned in the preceding section, two approaches that elevate with
regards to the value-relevance discussion. The two approaches are referred to as
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 13
price-level regressions
22
and return regressions, and yield different answers to the same inquiry; namely,
the value-relevance of accounting amounts. This study is constructed upon similar models and sample
variables initiated in previous studies, and will, concurrently, adopt the methods utilized in previous
research. Thus, the methodology applied in this study, is also advocated in a great amount of previous
research (e.g., Kothari and Zimmerman, 1995; Barth et al., 2005 and Hellström, 2006).
As previously described, the intention of this study is to assess how and to what extent book
values and earnings, divided into accruals and cash-flows, henceforth BV, ACC and CF, are
connected to the year-end market capitalization as well as the change in year-to-year market
capitalizations, hereafter MC, for the sample period 2001-2010 and the two sub-periods, i.e., the period
before, 2001-2004, and after, 2005-2010, the mandatory introduction of IFRS-reporting. To obtain this
information, the study performs several regressions, specifically a price regression, a lagged price
regression and a return regression (see, e.g., Kothari and Zimmerman, 1995 or
Hellström, 2006). The above-mentioned regression models are widely used to assess value-relevance,
but they differ, as hinted in the preceding paragraph, distinctively in what they actually answer (Barth et al.,
2001). Barth et al. (2001) state that level regressions examine if accounting measures are reflected in price
levels, whilst return regressions examine if accounting measures are reflected in the change in price levels
over a specific period of time; see also, footnote 14.
This study, following the arguments from previous research, defines the different year-end
accounting variables as the level variables, and the year-to-year change in the different accounting
variables as the return variables. Following the considerations of Barth et al. (2001) it is clear that two level
regressions and one return regression will produce suitable results that relates to the objective of this study.
In the following subsections, the regression models adopted in this study as well as particular issues
connected to this area are described and discussed. Following the regression models, we dive into the
different alternatives available when performing panel data analysis and we further
develop the environment attached to the regression models. Hereunder, we also describe the tests and
the necessary econometric adjustments connected to the tests.
Cross-Sectional Time-Series Analysis
Price regressions and return regressions in their simplest forms are some of the most adopted and
established models in value-relevance related research (see, e.g., Kothari and Zimmerman, 1995 or Barth et
al., 2005). The Ohlson-framework (1995) or any extension of the framework is a well-known example of a
valuation model that commonly is connected to value-relevance regression models. The
Ohlson-model is based upon the dividend discount model and is defined as:
#
P
t
=
- R
!¬
E
t
(d
t
+
¬
) (Ohlson-Model)
¬=1
The price and return regressions that we have used in this paper can be traced back to several
articles in previous research. To establish the regression models in this study, equivalent
methodologies as e.g., Collins et al. (1997), Burgstahler and Dichev (1997) and Hellström (2006) is
operationalized. The price and lagged price regression determines how much of the MC-variable that is
explained by respectively BV and earnings, divided into CF and ACC, and the return regression determines
the relationship between the change in MC and the change in BV, ACC and CF. Effectively, we are using
a panel regression to express the relationship between the dependent
variable, MC, and the independent variables, BV and earnings, defined as ACC and CF.
Panel regressions are equivalent to cross-sectional time-series analysis, which are regressions that adjust
for company and time specific errors (Gujarati, 2004). In order to streamline the lagged price
14 BOGSTRAND AND LARSSON
and return regressions we have operated with a one-year lag and return window, i.e., from fiscal year to
fiscal year. This means that the relationship between the dependent variables and the explanatory variables
in the lagged price and return regression is affected by every announcement the company makes throughout
a full year respectively.
In panel data there are essentially two main alternatives related to how the regression is carried out,
either fixed effects or random effects (Gujarati, 2004). The fixed effect model assumes, in short,
that the variables are correlated and applies corrections to the regression accordingly. Moreover, the
fixed effect panel regression takes into account the individuality of the sample variables similar to
introducing dummy variables to the regression. The equation for a cross-sectional time-series
regression with fixed effects can be expressed in the following way:
Y
it
= !
1i
+ !
2
X
2it
+ !
3
X
3it
+ ¬
it
(Fixed Effects)
The random effect regression is theoretically the opposite of the fixed effect regression; in terms of
it assuming that the variables are uncorrelated and appropriately can apply random effects when
performing the regression. Moreover, the random effect regression disregards the need for generating
dummy variables and instead uses a disturbance term (u) in correspondence with the error term. The
equation for a cross-sectional time-series regression with random effects can be expressed in the
following way:
Y
it
= !
1i
+ !
2
X
2it
+ !
3
X
3it
+ ¬
it
+ u
i
(Random Effects)
The following four subsections will, in detail, explain the price regression, the lagged price
regression and the return regression. Alongside, we also present adjustments that enable more
statistically accurate results. Please note that we, to some extent, simplify the illustration of both the
price regression and the return regression in the equations below, but the underlying equation utilized by
the statistical software, STATA, is the comprehensive regressions for both random effects and fixed effects.
Price Regression : Model 1
The price regression utilized in this paper is based on what is proposed by Burgstahler and
Dichev (1997) and Hellström (2006). Several other researchers have utilized similar regressions; see, e.g.,
Collins et al. (1997), Francis and Schipper (1999) and Lev and Zarowin (1999). The basic
regression is concurrently a function of MC as the dependent variable and BV, ACC and CF as the
three independent variables. One issue, proposed by certain researchers, is to express the regression without
scaling the numbers; see, e.g., Easton and Sommers (2003) and Barth and Clinch (2009). Scaling, or
deflating, means that you divide the variables by a common denominator in order to increase
comparability and remove company specific issues. We have, however, decided not to scale, or deflate, our
variables but instead recognize the arguments of Gujarati (2004), i.e., that panel data
takes into consideration the individual panels, i.e., firm and year specification. Therefore, we argue,
that by running panel data regressions, the issues with scale effects will not be that significant. Or, phrased
differently, by deflating the accounting numbers the transformation might bias the results rather than
improve them. To some extent, we have already explained the different variables that we have chosen to
investigate in this paper. However, in order to further clarify, the different variables in
the two price regressions are listed below:
MC
it
= Market Capitalization of Firm i in Fiscal Year t (MC)
BV
it
= Total Shareholder Equity of Firm i in Fiscal Year t (BV)
ACC
it
= Earnings
it
- CF
it
of Firm i in Fiscal Year t (ACC)
CF
it
= Cash-Flow from Operations of Firm i in Fiscal Year t (CF)
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 15
The sample consists of data between 2001 and 2010, which will be analyzed for the full time period, as
well as for the pre- and post-IFRS periods. The different equations that are implemented in
Model 1 and the unlagged price regressions are:
MC
it
= !
0
+ !
1
BV
it
+ !
2
ACC
it
+ !
3
CF
it
+ ¬
it
MC
it
= !
0
+ !
1
BV
it
+ ¬
it
MC
it
= !
0
+ !
1
ACC
it
+ ¬
it
MC
it
= !
0
+ !
1
CF
it
+ ¬
it
Lagged Price Regression : Model 2
(1A)
(1B)
(1C)
(1D)
Following the price regression we also introduce a lagged price regression model. The reason
behind this is that we also want to test a one-year lag effect on the variables. More precisely, we lag the
independent variables, BV, ACC and CF, on the opening dependent variable, MC.
23
This will result in a
more accurate perspective of the relationship between MC and BV, ACC and CF because the market has
received a full year to react, and adopt to the dependent variable, the information
content of the independent variables. Accordingly, the different regressions that are implemented in
Model 2 and the lagged price regressions are:
MC
it
= !
0
+ !
1
BV
it-1
+ !
2
ACC
it-1
+ !
3
CF
it-1
+ ¬
it
MC
it
= !
0
+ !
1
BV
it-1
+ ¬
it
MC
it
= !
0
+ !
1
ACC
it-1
+ ¬
it
MC
it
= !
0
+ !
1
CF
it-1
+ ¬
it
Return Regression : Model 3
(2A)
(2B)
(2C)
(2D)
Similar to the above-mentioned regressions the return regression is based on MC, BV, ACC and
CF. We anchor our return regression in several prior researchers' methodology; see, e.g., Easton and Harris
(1991), Kothari and Zimmerman (1995) and Hellström (2006). Hellström's (2006) methodology
originates from Easton and Harris' model that regresses the return variable against both price level and price
change. Our model is solely considering the return variable and change in BV, ACC and CF. One reason
for this is that we already have performed level models in the price
regression and the lagged price regression, and therefore want to execute a clean return regression to
facilitate comparison between diverse models. According to e.g., Brown, Lo and Lys (1999) and
Hellström (2006) a return regression is preferably deflated by price at the beginning of the year. Thus, our
return regression model is deflated by the opening price at period t. Before we move on, we believe it is
imperative to define all the distinctive variables that will be employed in the return
regression constituting Model 3:
MC_R = (MC
it
- MC
it-1
) / MC
it-1
(MC_R)
BV_R = (BV
it
- BV
it-1
) / MC
it-1
(BV_R)
ACC_R = (ACC
it
- ACC
it-1
) / MC
it-1
(ACC_R)
CF_R = (CF
it
- CF
it-1
) / MC
it-1
(CF_R)
Following the same thoughts as presented above we adopt return equations comparable to previous
research (see, e.g., Kothari and Zimmerman (1995) or Hellström (2006). The assumption in this study is
that the return variables are as normally distributed as possible and therefore will yield unbiased
16 BOGSTRAND AND LARSSON
statistical results. Listed below are the equations implemented in Model 3 and the return regression
approach:
MC_R
it
= !
0
+ !
1
BV_R
it
+ !
2
ACC_R
it
+ !
3
CF_R
it
+ ¬
it
+ u
i
MC_R
it
= !
0
+ !
1
BV_R
it
+ ¬
it
+ u
i
MC_R
it
= !
0
+ !
1
ACC_R
it
+ ¬
it
+ u
i
MC_R
it
= !
0
+ !
1
CF_R
it
+ ¬
it
+ u
i
Tests and Final Econometric Adjustments
(3A)
(3B)
(3C)
(3D)
Preliminary testing consists of determining whether to use a fixed effect or a random effect
regression model. Which model to utilize is established by running both regressions, saving their estimates,
and subsequently run a Hausman test; see, StataCorp (2011). The Hausman test assumes the null hypothesis
that you can use the random effect regression model. To interpret the Hausman test, in short, you reject the
hypothesis to use the random effect model if the probability of the test is lower than five percent. Therefore,
if the probability of the test is higher than five percent, you can use
random effects and if it is lower than five percent you should use fixed effects. Regarding our price
and lagged price data the probability of the Hausman test is 0.26 percent or lower and we will accordingly
use the panel data fixed effect model. For the return regression model we accept the Hausman-test with
11.87 percent and will therefore use the panel data random effect model.
After determining that the fixed effect model is preferred in the price and lagged price regressions, it is
also necessary to control for heteroskedasticity and auto/serial-correlation. In STATA this is
accomplished by running a Wald-test, testing for groupwise heteroskedasticity, and a Wooldridge-test,
testing for autocorrelation; see, StataCorp (2011). The Wald-test assumes the null-hypothesis that there are
no groupwise heteroskedasticity, however, in our case we reject this hypothesis and accept that there is
heteroskedasticity present in our data. The Wooldridge-test assumes that there are no autocorrelation in the
data, however, also apparent after testing is that our data contain autocorrelation. Considering the
random effects approach in the return regression, the assumption is
that there are no, or low, heteroskedasticity and autocorrelation. This is, first and foremost, because
the very basis of the random effects regression assumes that the error term of the coefficients are random
rather than fixed (Gujarati, 2004).
Autocorrelation means that the error terms in the model are correlated, which is especially common in
regression analysis containing dummy variables, which, in turn, is similar to a fixed effect model; see, e.g.,
Gujarati (2004). In panel data it is also very common to be affected by
heteroskedasticity and therefore we are not surprised that the general response, from testing, is that
both autocorrelation and heteroskedasticity is present in our study.
The first step to deal with autocorrelation and heteroskedasticity is to introduce robust standard errors to
the fixed effect regression model. This means that the regression models will be less sensitive to outliers
and therefore might deliver an improved statistical result. The second step to deal with both autocorrelation
and heteroskedasticity is to cluster the panel variable, i.e., the firm variable,
which also will help deliver stronger econometrical results. The following section will elaborate on
the data and descriptive statistics of this paper, followed by the empirical results and our analyzes vis- à-vis
the objective of this paper.
V. DATA AND DESCRIPTIVE STATISTICS
Prominent approaches with regards to value-relevance research and the components of earnings are based
on reported accounting numbers from the financial statements; see, e.g., Healy (1985) and
Dechow, Sloan and Sweeney (1995). The foundation of the components in our regression models is
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 17
based on financial data derived from each respective company. There are several different approaches in
previous research that all disassembles and define earnings into an accrual component and a cash flow
component. The most eligible methods, with respect to this study, are perhaps Sloan (1996) and Barth et al.
(2005). Sloan (1996) defines accruals by combining a subset of accounting measures and then subtracts
this component from earnings in order to receive a cash flow component. By restructuring the definiti on
of accruals, this study determines accruals as net income before
extraordinary items subtracted by cash flow from operations. A similar approach is used and
recommended by Barth et al. (2005).
The accounting and firm specific measures collected in this study are net income before
extraordinary items, cash flow from operations, market capitalization, and the total value of shareholders'
equity. Additional clarifications involving how the accounting measures will be implemented and/or
adjusted is further explained for each regression model as described in the
methodological part in Section IV. However, to eliminate any misinterpretations the accounting
measures in this paper are the following:
Market Capitalization
The Total Value of Shareholders' Equity
Net Income Before Extraordinary Items
Cash Flow from Operations
An Accrual Component (EARN - CF)
Sample Selection and Choice Criteria
(MC)
(BV)
(EARN)
(CF)
(ACC)
In order to enable the supplement of the continuous growing research concerning the value-
relevance of accruals and cash flows, we intend to perform this study on the Scandinavian region, in which
we include Denmark, Finland, Norway and Sweden; see, Table 1. Simply determining which areas and
exchanges to study is, nevertheless, insufficient since all the securities listed on the
exchanges may not meet the criteria required to conduct the methodology presented in this paper. It is
important to make sure that every firm included in the sample satisfies the demands necessitated by the
regression models. Albeit, there are several reasons for why this study decided to enhance the empirical
evidence surrounding the Scandinavian stock exchanges. Firstly, all the four countries are closely
connected both from an economic as well as a geographical perspective. Secondly, similarities are also
evident when scrutinizing the listed securities from an industry specific perspective, i.e., the
Scandinavian countries are also comparable when looking at the variety of businesses apparent on the
stock exchanges. Thirdly, as in detail described in the introduction, the foreign non-Scandinavian
ownership, and thus interests, in the Scandinavian stock exchanges is noticeably high. This means that the
comparability and importance of the countries in the sample are high, and concurrently also interesting to
study.
The criteria in this study are conservative, and consist of two stages. First, the study necessitates
data for a considerable time period, and the selected sample has been set to ten years. This yields ten
years of data, which is sufficient in order to complete both the two price regressions and the return
regression. In other words, any company that does not have data for at least ten years will be excluded from
the sample. Second, to perform the methodology presented in this paper, all the accounting measures as
defined above are required to be available for each company. Accordingly, if either MC, BV, EARN, or CF
is unavailable, the company will be excluded from the sample. The outcome of
these criteria is that we have an available sample of 4.310 firm-year observations, consisting of 431
exchange-listed firms with ten years of data spanning between 2001 and 2010, which, depending on the
model specifications, will deliver nine or ten years of analyzable regression variables.
18 BOGSTRAND AND LARSSON
To collect comparable data in this study we have used DataStream, Worldscope, henceforth DS.
This choice affects the study both positively and negatively. The positive effect of using DS, as the only source of data, is that the entire sample is available in one database.
Furthermore, if some parts of the data have been altered, all the measures are assumingly changed in the same manner. For example, EARN may not equal what is found in
the financial reports of the companies, but all the EARN found in DS are assumed to be comparable. The negative aspect of only using this database is
that the sample size might be limited due to DS license agreements. However, since the positive
aspects unquestionably outweigh the negative aspects, we have chosen to utilize DS Worldscope as the exclusive source of data.
The data collection process has resulted in the collection of accounting measures for ten consecutive years for 431 Scandinavian publicly listed companies.
Originally, the sample was intended to consist of all companies on each respective stock exchange. However, after running the
sample through the above-mentioned criteria, the final sample consists of 85 firms listed on NASDAQ
OMX Copenhagen, 96 firms listed on NASDAQ OMX Helsinki, 75 firms listed on Oslo Stock Exchange and 175 firms listed on NASDAQ OMX Stockholm. In total, we
are, as mentioned above, consequently carrying out our research on a sample of 431 Scandinavian exchange-listed firms; see also, Table 1 and Table 2.
Table 2 presents the descriptive statistics for the full sample and the different regressions that have
been performed in this study. As is portrayed in Table 2 the availability of descriptive statistics for a
panel data sample is limited. Nevertheless, Table 2 also highlights the fact that all of the regressions are significantly dispersed and that there are no explanatory variables
that have distinctive outliers compared to each other. To further clarify, the descriptive statistics in Table 2 are expressed with within-values
24
for each panel, which is why
we also recognize the descriptive statistics for each stock exchange in Table 1 via Panel A, B and C.
Table 1, Panel A concerns the price regression and consecutively encloses the variables utilized by
the price regression. Although the variables in the three regressions all are based on the same accounting measures, they are implemented differently in each regression
respectively. By further examining Panel A below, it is evident that the range of values is significant. Table 1, Panel B concerns the lagged price regression, and
successively presents the variables adopted in the lagged price regression model. Accordingly, it is evident that the sample in the lagged price regression is
somewhat smaller. However, the reason behind the smaller sample is that the independent variables,
BV, ACC and CF, are lagged with one year. This is apparent when comparing N/n in Panel A, B and C. Furthermore, also for the lagged price regression the dispersion of
variable values is significant, meaning that the values are spread out and thus not grouped in clusters close to each other.
Table 1, Panel C apprehends the return regression in this study, and displays the variables relevant for the return regression model. Similar to the lagged price data, the
sample size is also for the return
regression smaller than the price regression data. This is because the return variable is calculated by
dividing by opening market price and the model therefore has to be shortened with one year. However, the sample used to obtain the return values is still the full ten-year
period between 2001 and 2010. By looking at the min and max values in Panel C, which probably best explain the distribution of the variables, it is acknowledged that the
variables are significantly dispersed. However, they are more closely structured than in Panel A and B.
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 19
TABLE 1
Descriptive Statistics per Stock Exchange
COPENHAGEN HELSINKI OSLO STOCKHOLM
1, 2
MC BV ACC CF MC BV ACC CF MC BV ACC CF MC BV ACC CF
PANEL A
N/N 850/85 850/85 850/85 850/85 960/96 960/96 960/96 960/96 750/75 750/75 750/75 750/75 1750/175 1750/175 1750/175 1750/175
Q1 176.1 147.1 -169.9 7.9 37.3 23.8 -36.8 2.4 407.3 242.2 -288.2 15.5 210.4 103.5 -132.3 -1.3
MEAN 6223.4 2253.0 -330.8 623.6 1498.1 665.3 -66.1 148.1 10743.6 5721.3 -990.9 1781.1 11738.9 5550.1 -396.6 1034.0
Q3 3056.4 1911.0 -8.1 350.2 578.4 348.6 -1.4 72.1 4506.4 2470.1 -7.7 594.8 4014.9 1681.1 -3.8 308.5
STD. DEV. 21182.2 5898.1 1137.2 1926.4 7634.4 1930.7 248.7 567.8 44022.9 20037.8 5079.7 8556.7 38828.8 17602.5 2979.6 3694.4
MIN 1.0 -96.4 -12604.0 -514.3 1.4 -15.0 -3396.0 -1289.0 5.8 -859.1 -63073.0 -4395.7 3.4 -484.0 -40322.0 -34677.0
MEDIAN 706.9 482.7 -46.5 70.0 130.8 62.8 -6.5 13.3 1216.1 767.1 -69.5 130.3 735.7 407.4 -23.6 51.8
MAX 359657.9 64248.0 3938.0 21346.0 137163.3 15148.0 2003.0 7289.0 538510.4 219542.0 12237.0 106338.0 450795.9 169947.0 43190.0 32496.0
PANEL B
N/N 765/85 765/85 765/85 765/85 864/96 864/96 864/96 864/96 675/75 675/75 675/75 675/75 1575/175 1575/175 1575/175 1575/175
Q1 176.1 148.1 -165.0 8.0 37.8 23.7 -36.8 2.5 416.9 230.4 -270.3 15.5 216.8 100.9 -130.9 -1.6
MEAN 6398.7 2139.8 -327.7 604.5 1440.1 656.6 -69.9 152.0 11248.0 5476.0 -941.3 1720.1 11949.7 5348.9 -406.7 982.6
Q3 3192.0 1844.5 -8.1 -350.2 606.8 344.2 -1.4 71.7 4850.5 2346.0 -6.3 550.1 4320.3 1616.8 -3.8 295.1
STD. DEV. 21708.2 2139.8 -327.7 604.5 6558.0 1915.5 257.6 588.5 45879.4 18967.0 4814.2 8152.8 38692.7 17042.6 2956.8 3604.6
MIN 1.0 -96.4 -12604.0 -514.3 1.4 -13.9 -3396.0 -1289.0 5.8 -859.1 -63073.0 -4395.7 3.4 -108.6 -40322.0 -34677.0
MEDIAN 750.4 469.0 -46.0 70.4 137.9 61.5 -6.5 13.3 1285.8 738.9 -65.2 127.2 749.5 393.0 -23.2 46.6
MAX 359657.9 55521.0 3938.0 21346.0 101994.6 15148.0 2003.0 7289.0 538510.4 214079.0 12237.0 106338.0 439116.4 159167.0 43190.0 32496.0
PANEL C
N/N 765/85 765/85 765/85 765/85 864/96 864/96 864/96 864/96 675/75 675/75 675/75 675/75 1575/175 1575/175 1575/175 1575/175
Q1 -0.18 -0.04 -0.05 -0.03 -0.23 -0.06 -0.04 -0.03 -0.20 -0.02 -0.03 -0.02 -0.20 -0.04 -0.04 -0.03
MEAN 0.34 0.13 0.01 0.03 0.35 0.10 0.05 0.05 0.31 0.06 0.01 0.03 0.33 0.05 0.02 0.02
Q3 0.46 0.09 0.04 0.06 0.46 0.10 0.04 0.06 0.48 0.10 0.02 0.05 0.51 0.10 0.03 0.06
STD. DEV. 2.91 2.66 0.26 0.28 1.44 0.83 0.83 0.43 1.19 0.47 0.32 0.22 1.67 0.38 0.52 0.51
MIN -0.85 -6.86 -2.85 -1.44 -0.96 -2.66 -6.22 -4.24 -0.93 -2.54 -2.23 -1.14 -0.97 -3.88 -7.06 -11.74
MEDIAN 0.11 0.02 0.00 0.01 0.11 0.03 0.00 0.01 0.13 0.03 0.00 0.01 0.13 0.03 0.00 0.01
MAX 77.86 72.48 1.67 4.38 18.58 13.27 19.63 6.05 18.98 6.21 3.74 2.45 50.55 4.07 11.23 7.19
1 Panel definitions of Table 1: Panel A = Unlagged price regression; Panel B = Lagged price regression; and, Panel C = Return regression.
2 Variable definitions of Table 1: MC = Market capitalization sorted by stock exchange; BV = Book value sorted by stock exchange; ACC = Accruals sorted by stock exchange; and, CF = Cash flows sorted
by stock exchange.
20 BOGSTRAND AND LARSSON
TABLE 2
Descriptive Statistics for the Firm Sample
VARIABLES
1. 2
N/N STD. DEV. MIN MAX
Panel B
MC
it
4310/431 12778.7 -180159.4 234640.6
BV
it
4310/431 5037.1 -79619.1 93733.9
ACC
it
4310/431 1930.5 -50602.0 32910.0
CF
it
4310/431 2054.7 -46186.5 44765.2
Panel B
MC
it
3879/431 12452.2 -196838.6 214953.0
BV
it
3879/431 4760.6 -69779.7 98110.3
ACC
it
3879/431 1928.4 -48627.6 34884.4
CF
it
3879/431 2023.4 -44961.9 48730.0
Panel C
MC
it
3879/431 1 .8 -9 .0 69.4
BV
it
3879/431 1 .2 -8 .6 64.7
ACC
it
3879/431 0 .5 -7 .9 17.5
CF
it
3879/431 0 .4 -10.8 8 .1
1 Panel definitions for Table 2: Panel A = Price regression; Panel B = Lagged price regression; and, Panel C = Return
regression.
2 Variable definitions for Table 2: MC
it
= Market capitalization of firm i in fiscal year t. BV
it
= Book value of equity of firm i in
fiscal year t. ACC
it
= Accruals of firm i in fiscal year t. CF
it
= Cash flows of firm i in fiscal year t.
VI. EMPIRICAL RESULTS
This section will present the results from the three regression models that this study has implemented and
conducted on Scandinavian data. Important to remember is that this study identifies earnings as one accrual
component and one cash flow component. To reduce the possibility of confusion, the
tables enclosed below will only include information that is considered relevant in terms of the analysis
of the objective of this study. The adjusted explanatory power of the different regression models is
defined by R
2
in each respective model. Table 3, 4 and 5 also include the coefficients (!) for each
explanatory variable. It is particularly important to keep in mind that for the two level regressions the
coefficients can be arbitrary due to scale-related effects
25
, while, for the return regression, which deflates
the variables with the opening market capitalization, awareness regarding the explanatory
variable coefficients can be beneficial to recognize. Nevertheless, the pivotal subject in this study is
value-relevance and therefore the explanatory power (R
2
) of each respective regression model is of focal
interest. Also, worth noting is that all the R
2
values are significant at a 1 percent level. The T- value is also
deliberately excluded from the tables since it is significantly high for all the regression models.
Similar to e.g., Kothari and Zimmerman (1995) this study also found that the return regression was
less affected by heteroskedasticity and autocorrelation than the two level regressions, i.e., the price
regression and the lagged price regressions. Therefore, as previously mentioned, the price and lagged price
results found in Table 3 and Table 4 are predicted by using a fixed effect panel data regression, while the
return regression results found in Table 5 is predicted using a random effect panel data regression. The
following section will analyze the results within each regression model for the full
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 21
sample period, as well as the pre- and post-IFRS sub-periods. Conclusively, a discussion connecting the
research question to the results from each regression model is presented.
TABLE 3
Price Regression : Model 1
1A: BV
it
+ ACC
it
+ CF
it
1B: BV
it
1C: ACC
it
1D: CF
it
PRICE
1
!
1
!
2
!
3
R
2
!
1
R
2
!
1
R
2
!
1
R
2
2001-2010 0.460 0.911 3.144 34.98% 1.246 24.14% -1.063 2.58% 3.478 31.27%
*** *** *** *** *** ***
PRE-IFRS 0.625 3.048 1.321 11.38% 0.844 3.32% 1.748 4.15% 0.380 0.48%
*** *** *** *** *** **
POST-IFRS -0.463 1.023 4.430 23.32% 0.679 4.64% -0.501 0.13% 3.162 18.70%
*** *** *** *** *** ***
*** Significant at 1 percent level ** Significant at 5 percent level * Significant at 10 percent level
1 Price Regression: MC
it
= !
0
+ !
1
BV
it
+ !
2
ACC
it
+ !
3
CF
it
+ ¬
it
Variable definitions for Table 3: MC
it
= Market capitalization of firm i in fiscal year t. BV
it
= Book value of equity of firm i in
fiscal year t. ACC
it
= Accruals of firm i in fiscal year t. CF
it
= Cash flows of firm i in fiscal year t. ! = Coefficient of the
explanatory variables. R
2
= Adjusted R
2
within the panel regression.
Price Regression : Model 1
The price regression considers the relationship between the company specific year-end market
capitalization, book value of equity and the study's two earnings measures using a fixed effect panel data
regression. Table 3 presents the results after running regression 1A, 1B, 1C, and 1D, as described
in the methodological part in Section IV. When examining the price regression results, it is apparent
that the explanatory power of the four price regressions has very high significance for all the time periods.
Below we discuss the results, and reflect upon substantial issues, pertaining to the price regression models.
For the full sample period Model 1 indicate that the combined explanatory variables, 1A, explain 34.98
percent of the variance in the market capitalization. Apparent from regression 1B and 1D is that
both book values and cash flows have much higher explanatory power than accruals. Since both book
values and cash flows have high-adjusted R
2
values (24.14 percent and 31.27 percent) it is presumable that
they contain overlapping incremental information with regards to the combined explanatory power. A
possible explanation for these values could be the fact that one of the main valuation models utilized by
investors today is the discounted cash flow model, henceforth DCF-model. A high application of DCF-
models could also help explaining the low explanatory power of the accrual
component (2.58 percent) highlighted under regression 1C.
The pre-IFRS period compared to the post-IFRS period indicates lower value-relevance, i.e., lower
explanatory power, for the explanatory variables in regression 1A (respectively 11.38 percent and 23.32
percent). Another interesting finding in Model 1 concerns the pre- and post-IFRS results and the fact that in
the pre-IFRS period regression 1C shows stronger explanatory power of accruals (4.15 percent) than cash
flows in regression 1D (0.48 percent). This means that for the pre-IFRS period
accruals have more value-relevance than cash flows. Thus, accruals, for the pre-IFRS period, are the
most important explanatory variable
26
. The post-IFRS period indicates that book values have slightly
increased in terms of value-relevance. More interesting, though, is the difference that is apparent
22 BOGSTRAND AND LARSSON
when looking at the explanatory power of regression 1C and 1D (0.13 percent and 18.70 percent
respectively). This means that for the post-IFRS period cash flows have ascended with almost 97.5 percent
and accruals have descended with almost 97 percent in the post-IFRS period compared to the pre-IFRS
period.
Albeit, since Model 1 employs the year-end market capitalization it is understandable that the accruals
measure has lower explanatory power than book values and cash flows. One issue that is
apparent when considering Model 1 is, in fact, that it looks at the relationship between the market
capitalization at the end of period t and the book value and earnings at the end of period t. The model is,
nevertheless, interesting, in terms of explanatory power of recent book value and earnings measures
concerning the market capitalization at the same date, since a number of valuation models consists of
predicting future equity and cash flows based on the present value today. Hence, the increased use of cash
flow as a predictor in equity investments can probably be one reason for the
sudden change of value-relevance from the pre-IFRS period to the post-IFRS period. Nevertheless,
logical assumptions would suggest that the explanatory variables should be better reflected in the market
capitalization for the lagged price regression than in the price regression.
TABLE 4
Lagged Price Regression : Model 2
2A: BV
it-1
+ ACC
it-1
+ CF
it-1
2B: BV
it-1
2C: ACC
it-1
2D: CF
it-1
LAGGED PRICE
1
!
1
!
2
!
3
R
2
!
1
R2 !
1
R
2
!
1
R
2
2001-2010 0.225 0.387 3.100 29.05% 1.062 16.48% -1.316 4.15% 3.273 28.28%
*** *** *** *** *** ***
PRE-IFRS -0.120 -1.349 4.040 68.80% 0.209 0.29% -4.663 47.83% 4.896 66.80%
*** *** *** * *** ***
POST-IFRS 0.765 0.591 3.467 2.08% 1.114 0.40% -0.582 0.02% 3.831 2.70%
*** *** *** *** *** ***
*** Significant at 1 percent level ** Significant at 5 percent level * Significant at 10 percent level
1 Lagged Price Regression: MC
it
= !
0
+ !
1
BV
it-1
+ !
2
ACC
it-1
+ !
3
CF
it-1
+ ¬
it
Variable definitions for Table 4: MC
it
= Market capitalization of firm i in fiscal year t. BV
it-1
= Book value of equity of firm i in
fiscal year t-1. ACC
it-1
= Accruals of firm i in fiscal year t-1. CF
it-1
= Cash flows of firm i in fiscal year t-1. ! = Coefficient of the
explanatory variables. R
2
= Adjusted R
2
within the panel regression.
Lagged Price Regression : Model 2
The lagged price regression considers the relationship between the market capitalization at year t
and the one-year lagged book value of equity and the study's two earnings measures using a fixed effect
panel data regression. This means that book values, accruals and cash flows are measured against the
market capitalization for the subsequent year. This study assumes that this should remedy any issues that
might be present in the price regression with regards to the explanatory variables not yet being mirrored in
the market capitalization. Table 4 presents the results after running regression
2A, 2B, 2C and 2D as presented in the methodological part in Section IV. Moreover, each regression
is performed for the entire sample period, for the pre-IFRS period and for the post-IFRS period. In Model 2
all the regression models are significant at a 1 percent level, which means that we have
strong statistical evidence for the displayed adjusted R
2
values as well as the model's coefficients.
For the full sample period Model 2 indicate that the combined explanatory variables, displayed in 2A,
explains 29.05 percent of the variance in the market capitalization. Furthermore, regressions 2B,
2C and 2D reveal that, similar to Model 1, cash flows have the strongest explanatory power for the
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 23
full sample period with 28.28 percent. Book values are also important in Model 2 with an adjusted R
2
value
of 16.48 percent, while accruals have the lowest explanatory power for the full sample period with 4.15
percent. Nevertheless, accruals have more explanatory power in Model 2 than in Model 1, an increase of
1.57 percent, which means that in Model 2, for the full sample period, a higher amount of the accrual-based
information has been adopted in the market capitalization.
Looking at the pre-IFRS period in Model 2, the results are astoundingly distinctive in comparison
to Model 1. The combined explanation power of the independent variables, 2A, for the pre-IFRS
period is 68.80 percent. Moreover, book values, 2B, have lost almost all their importance with regards to
value-relevance, only 0.29 percent, and the highest explanatory power, in the pre-IFRS period, lies within
accruals and cash flows with 47.83 percent and 66.80 percent respectively. This means, however, that
both regression 2C and 2D contain information that incrementally overlaps, i.e., accruals and cash flows
contain similar information for the pre-IFRS period since they both have
explanatory power close to the combined explanatory power found in regression 2A. The clear
indication of Model 2 is that, for the pre-IFRS period, both accruals and cash flows have high value-
relevance and are better predictors of the market capitalization than the book value found in regression 2B.
One explanation for the strong results is that the economy in the Scandinavian countries was growing and
expanding rapidly, especially within the technology sector, in the years representing the pre-IFRS period.
This is especially evident in the aftermath of the Dot-Com bubble in 2000/2001, as
all the markets show signs of optimism and increased growth between 2001/2002 and 2007/2008
27
.
Thus, the positive upturn in the market is highly dependent on the economic growth in companies on the
market.
The post-IFRS period displays a different result than the pre-IFRS period, with a combined
explanatory power of 2.08 percent, 2A. The difference between the pre-IFRS period and the post- IFRS
period is remarkable with a drop in explanatory power of 66.72 percent, and there has to be
several underlying reasons for the sudden decrease. Model 2B, 2C and 2D explain 0.4 percent, 0.02
percent and 2.70 percent of the variance in the market capitalization respectively. Although these results are
weak, it is evident that cash flows have the strongest explanatory power by far. It is difficult to explain the
reasons behind the sudden decrease in value-relevance; however, one reason can definitely be the financial
turmoil that emerged between 2007 and 2008. Moreover, the results of the post-IFRS period could be
highly affected by the destructive effects of the financial crisis. This
could also help acknowledge the assumption that Model 2 is a better predictor of value-relevance than
Model 1, i.e., during the financial crisis it is likely that the market utilized other factors than book values,
accruals and cash flows since they did not rely on financial information in the same manner as they did
before the financial crisis.
The issue with this explanation is that it is unsupportive of the results in Model 1. However, it could
also be argued that Model 1 looks at the relationship between market capitalization and book
values, accruals and cash flows at the same point in time, while Model 2 looks at how the information
in year 1 is reflected in the price of year 2. More precisely, the argument is that Model 1 displays how much
the explanatory variables actually explain at the same point in time, while Model 2 displays how much the
explanatory variables explain after the market has adopted the information in the market capitalization.
Accepting this argumentation, it is evident that during the post-IFRS period in Model 2, perhaps due to the
financial crisis, the market did not choose to rely on the information in
neither book values, accruals nor cash flows, although, the explanation power of the explanatory
variables actually increased from the pre-IFRS period to the post-IFRS period in Model 1.
24 BOGSTRAND AND LARSSON
TABLE 5
Return Regression : Model 3
3A: BV_R
it
+ ACC_R
it
+ CF_R
it
3B: BV_R
it
3C: ACC_R
it
3D: CF_R
it
RETURN
1
!
1
!
2
!
3
R
2
!
1
R
2
!
1
R
2
!
1
R
2
2001-2010 1.094 0.226 0.248 58.73% 1.117 58.46% 0.482 1.92% 0.553 1.29%
*** *** *** *** *** ***
PRE-IFRS 1.077 0.347 0.346 84.51% 1.106 84.04% 0.750 3.90% 0.978 2.33%
*** *** *** *** *** ***
POST-IFRS 0.976 0.093 0.077 19.96% 0.996 19.97% 0.171 0.79% 0.171 0.35%
*** * * *** ** **
*** Significant at 1 percent level ** Significant at 5 percent level * Significant at 10 percent level
1 Return Regression: MC_R
it
= !
0
+ !
1
BV_R
it-1
+ !
2
ACC_R
it-1
+ !
3
CF_R
it-1
+ ¬
it
Variable definitions for Table 5: MC_R
it
= Change in market capitalization of firm i in fiscal year t divided by MC
t-1
. BV_R
it-
=
Change in book value of equity of firm i in fiscal year t divided by MC
t-1
. ACC_R
it
= Change in accruals of firm i in fiscal year t
divided by MC
t-1
. CF_R
it
= Change in cash flows of firm i in fiscal year t divided by MC
t-1
. ! = Coefficient of the explanatory
variables. R
2
= Adjusted R
2
within the panel regression.
Return Regression : Model 3
The return regression reflects the relationship between the change, or return, in market
capitalization and the change in book value of equity and the change in earnings measures, defined as
accruals and cash flows. Table 5 displays the results after running regression 3A, 3B, 3C and 3D as
presented in the methodological part in Section IV. Similar to Model 1 and Model 2, each regression is run
for the full sample period, for the pre-IFRS period and for the post-IFRS period. Worth specifying is that
all the regressions in Model 3 are significant at a 1 percent level and that some of the coefficients have
weaker significance than in Model 1 and Model 2. This can also be verified by
looking at Table 5 and the strong results of book values, 3A and 3B, compared to accruals and cash
flows, 3A, 3C and 3D.
Issues with heteroskedasticity and autocorrelation, which are present in the level regressions, are not
common in return regression models. This is also the case for our return regression model. However,
Francis and Schipper (1999) point out that return regression models might be less suited for economically
unstable periods. Therefore, to build on the previous arguments regarding both the
upturn during the pre-IFRS period and the recession in the post-IFRS period, the sample period in this
study can be defined as economically unstable. Nevertheless, the intention of this study is not to study the
effects of financially upturns and downturns, but the value-relevance of the above-mentioned explanatory
variables. It is, in any way, important to comment on what, at least in certain ways, that can affect the
results of the different regression models.
For Model 3, the full sample period results found in regression 3A indicate that, combined, the
explanatory variables explain 58.73 percent of the variance in the market capitalization returns. It is
evident, though, that book value returns, 3B, have the outright strongest explanatory power of the three
explanatory variables. According to regression 3B book value returns explain 58.46 percent while accrual
returns and cash flow returns, 3C and 3D, for the full sample period explain 1.92 percent and 1.29 percent
of the variance in market capitalization returns. That the results for regressions 3C and 3D are quite low is
not necessarily negative. It means, however, that for this return
model and the full sample period, book value returns have considerably stronger explanatory power
than accrual returns and cash flow returns.
The pre-IFRS period indicates a stronger explanatory power than for the full sample period when
looking at regression 3A, 84.51 percent. Similar to the full sample period, the book value return found
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 25
in regression 3B is the strongest explanatory variable with 84.04 percent for the pre-IFRS period as well.
Compared to Model 1 and Model 2, the distribution of explanatory power between book value returns,
accrual returns and cash flow returns is fairly constant for all the periods. In the pre-IFRS period accrual
returns, 3C, and cash flow returns, 3D, indicate explanatory power of 3.90 percent and 2.33 percent
respectively. Thus, in the pre-IFRS period accrual returns explain, out of the two
earnings components, more of the variance in market capitalization returns than cash flow returns.
In the post-IFRS period, there are indications in all the regressions, 3A, 3B, 3C and 3D, that the
value-relevance, i.e., that the explanatory power, has plummeted. For the combined regression model, 3A,
this study finds that the explanatory power is 19.96 percent - a significant decline compared to the pre-
IFRS period. The relationship between the models is, however, the same as in the two previous periods.
Book value returns, 3B, explain more than the combined model, 3A, with an explanatory power of 19.97
percent. Accrual returns, 3C, and cash flow returns, 3D, explains 0.79
percent and 0.35 percent of the variance in the market capitalization returns. The weak results of
accrual returns and cash flow returns, in the post-IFRS period, could definitely be connected to the financial
turmoil that erupted between 2007 and 2008. Also important, is the suggestion that return models, by some
extent, are considered to be unsuitable for unstable financial times; see, Francis and Schipper (1999).
This study finds that all the regression models are coinciding on the fact that the financial crisis
and the arduous economic situation on the market have affected the outcome of the regression
analysis. Since Model 3 measures the return, and not the level, it is more comparable to Model 2 than
Model 1. Therefore, the same argumentation is compatible, and valid, for Model 3 as it was for the lagged
price regression in Model 2. Moreover, the return model looks at the change in each variable with a return
window of one year, and thus how the information has been transformed over the course of the return
window. The argument, and possible explanation, is accordingly, even though we find an
increase in value-relevance in Model 1, this increase has not been recognized by the market and
implemented in the market capitalization in Model 3.
Value-Relevance and Proximate Implications
Based on the above results there are, first of all, strong indications that there is a positive
association between market capitalization and book values, accruals and cash flows for the given sample
period between 2001 and 2010. This means that the current accounting standards are producing
accounting numbers that can be utilized to predict and explain the variance in market capitalization,
which, thus, are important regarding the value-relevance discussion. There are,
nevertheless, also several other areas that are important in relation to value-relevance and accounting
information. In the following paragraphs, we will further discuss the above results in connection with other
ramifications existent in the area of financial reporting.
One element that is highly important is, as mentioned above, the quantity of key accounting items that
are utilized by investors, which to a great extent affects the value-relevance of reported accounting
information. The argumentation behind this statement is founded in the efficient market
hypothesis, elevating that all accounting information should be adopted and reflected in the
capitalized market value of equity; see, e.g., Fama (1965 and 1970). Furthermore, if investors, due to for
example economic turbulence, decide to form their investment approaches on other information than what
is enclosed in financial reports, the market capitalization will not likely comprehend the same degree of
accounting information. Therefore, in situations where investors feel that there is information, other than
what is disclosed in the financial reports, that are more beneficial in terms of
investment opportunities, the value-relevance will most likely decline. This can perhaps be what is
reflected in Model 2 and Model 3, compared to Model 1.
26 BOGSTRAND AND LARSSON
If it is the general consent on the market that publicly available accounting information is too
uncertain with regards to the financial situation on the market, the investment community might consider
knowledge, other than financial, when anticipating investment prospects. For example, organic growth
companies, i.e., companies that grow without acquisitions, are good investment opportunities because they
are a safer option, in terms of risk, especially in turbulent times. Another area that is highly important, and
should receive further attention, is the very substance of the income
statement, the cash flow statement and the balance sheet within each company. Thus, if investors
believe new accounting information to be unjustifiable, they might consider investing in companies that
over time have proven that they have a strong economy and the financial ability to overcome obstacles.
The economical strength of each company should definitely be taken into consideration when
discussing the value-relevance of their financial information, and on that note, e.g., the balance sheet
information can have very high impact on each respective company's market capitalization. In other
words, if a company has an exceptionally strong (weak) financial leverage in the balance sheet, it most
likely will affect the market capitalization positively (negatively). Therefore, it is also important to keep in
mind that some companies might have implicating effects in relation to this study, e.g., due their strong
(weak) balance sheet information and how this affects the market.
During the whole sample period, 2001-2010, information technology has been growing and
evolving, leading to a significant increase in the amount of information available to investors and
other stakeholders, as well as an increase in the time it takes for information to become obsolete. In other
words, the developments within information technology can also be argued as an important contributor
when it comes to the value-relevance discussion. Connecting this argument to the findings in this study, the
lower value-relevance found in Model 2 and Model 3 for the post-IFRS period can also be explained by the
evolvement in information technology and the adjacent increased
informational flow. This can even be linked to the previous arguments regarding investors utilizing
other information, i.e., investors that are faced with an expanded area of information and thus either find it
difficult to apprehend the financial information, react to other information available or even combine
financial information with other information available. This can lead to decreased value- relevance of
specific accounting components since market capitalization also contain a wide range of different
information.
Another implication, yet to be mentioned, is that the data for the pre-IFRS period cover fewer
years than the data for the post-IFRS period. The analysis might suffer from biased results due to this,
since, having fewer analyzable years in the pre-IFRS period than the post-IFRS period can affect the
regression results. When analyzing data with fewer observations it is more likely to be more sensitive to
extreme values and thus yield significantly stronger, or weaker, results. Likewise, the data for the post-
IFRS period contain more observations than the pre-IFRS period and it can be assumed that
accounting variables stabilize over time, the post-IFRS results might therefore be lower than the pre-
IFRS results. Nevertheless, both the pre-IFRS period and the post-IFRS period have sufficient
observations to be analyzed, and therefore it is important to also keep in mind that there might be other
reasons, such as those mentioned above, causing the incline in value-relevance from the pre- IFRS period to
the post-IFRS period.
In total, there is significant empirical evidence that book values, accruals and cash flows all have
value-relevance. Book values are in most of the regression models very important when trying to
explain the variation in market capitalization. In Model 2 and Model 3 the results indicate that the value-
relevance of book values, accruals and cash flows have decreased after the implementation of IFRS, while
the results in Model 1 indicate that the value-relevance have increased. This can, however, as discussed in
detail above, have several explanations. Conclusively, it is imperative to keep in mind that the results of
this analysis are valid only for the exact years, sample and
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 27
methodology as presented earlier in the paper. In the following and final section, we will summarize and
draw our conclusions regarding the findings presented above. We will also provide some suggestions for
further research.
VII. SUMMARY AND CONCLUSIONS
This paper examines the value-relevance of Scandinavian earnings information and book values over the
past decade in order to shed some light on whether the extensive global adoption of IFRS-
reporting has contributed to an increased accounting quality in terms of economic decision-usefulness to
equity investors. Our inquiry is motivated by the recent practical and empirically validated concern of an
eroded economic decision-functionality of publicly reported accounting information. Particular concern
among practitioners such as corporate accountants, auditors and financial analysts has been directed
towards the declined decision-usefulness of bottom line amounts based on accruals and cash
flows.
We address this research question using a sample of 4.310 firm-year observations for 431 exchange-
listed companies at NASDAQ OMX Nordic and Oslo Stock Exchange between 2001 and 2010. The degree
of value-relevance in our firm sample is operationalized through two price regressions and one return
regression and empirically tested via the statistical association between capitalized values of equity or
annual changes in capitalized values of equity and the study's three
independent explanatory accounting variables: (i) book values, (ii) accrual-based earnings and (iii)
cash-flow-based earnings. To maintain comparability across tables and graphs and thus the possibility to
triangulate our results, all tests are based on the same broad set of exchange-listed firms. And in order to
mitigate the possibility of incorrect inferences associated with scale-related effects such as size differences
across firms and extreme values in the firm sample, panel data regressions are conducted in all the three
regression models.
The results from our empirical tests show that both Scandinavian earnings information, accrual-
based as well as cash-flow-based, and book values are positively associated, albeit, to varying degrees,
with capitalized market values of equity as well as with annual changes in capitalized market values of
equity. These results are broadly consistent with previous value-relevance related research, originating from
the seminal discoveries of Ball and Brown (1968) and Beaver (1968). The results are also, at least to some
extent, in line with our theoretical predictions of the modern utilitarian role of
publicly reported accounting information. However, unlike previous value-relevance related research,
particularly empirical research carried out on accounting data between the early 1990s and the beginning
of the twenty first century, our results show a relatively strong explanatory power, regardless of the
regression used. This indicates, in comparison to previous periods, that there has been an increased value-
relevance among bottom line amounts based on both accruals and cash flows over the full sample period.
Similar reasoning applies also to Scandinavian book values, albeit, not in
the same extent.
Worth emphasizing is that our tests within the sample period - pre- and post the mandatory adoption of
IFRS-reporting in January 2005 - demonstrate somewhat mixed empirical signals on whether the
explanatory variables adopted in the study exhibit higher or lower value-relevance after the shift from
voluntary to mandatory IFRS disclosure. Findings from the lagged price regression as well as the return
regression show significant signs of a decline in value-relevance subsequent to the
mandatory adoption of IFRS, while the reverse reasoning applies for the results from the unlagged
price regression. Namely that, book values, accrual-based earnings and cash-flow-based earnings, in
connection with the shift from voluntary to mandatory IFRS disclosure, exhibit an increase in value-
relevance. A possible explanation for this discrepancy might, as discussed in Section V, stem from the fact
that the pre-IFRS period is characterized by a strong economic upturn, particularly in the
28 BOGSTRAND AND LARSSON
technology-sector, while the post-IFRS period to a great extent is reflected by a number of destructive
effects caused by the financial turmoil that emerged between 2007 and 2008. Part of the explanation can of
course also be attributed to the fact that the unlagged price regression mirrors the information at the time of
the announcement, while the lagged price regression looks at how the information is reflected in the
subsequent year's price and the return regression as reflected in annual changes between capitalized market
values of equity and the study's three explanatory variables.
Taken as a whole, our results show significant empirical evidence of an increased value-relevance
in Scandinavian earnings information as well as in Scandinavian book values compared to earlier periods as
presented in previous research, and thereby also as evidence of an increased accounting quality in terms of
economic decision-usefulness to equity investors over the past decade. However, we are, at the same time,
due to our mixed empirical findings within the full sample period, unable to conclude whether or not this
increased value-relevance is related to the adoption and implementation
of IFRS-reporting, and therefore also unable to conclude whether or not the harmonized regulatory
framework of accounting standards surrounding the current IFRS-based reporting model is moving
corporate disclosure regulation in a satisfying direction. Nevertheless, as hinted above, we are able to
conclude that publicly reported accounting information, disclosed in the income statement, the cash flow
statement and the balance sheet, not have continued to lose its relevance. On the contrary, it has regained
much of the decision-usefulness that has been lost in the past. However, to fully understand
whether or not this can be related to the adoption and implementation of IFRS-reporting, further
research, which in depth considers the concerns within the full sample period, is necessary to undertake.
Contribution
We believe that the results in this study are pertinent to both Scandinavian investors and to
accounting standard-setting bodies such as the IASB and the FASB since it - to some extent - penetrates
the relatively unresolved question of whether or not the current IFRS-based regulatory framework has been
fruitful in terms of an increased economic decision-usefulness among financial
statement information, which provide equity investors with resourceful material as well as with
valuable insights on the relevance and reliability of Scandinavian accounting numbers.
We also believe that our study might be useful in regions other than the Scandinavian, particularly in
countries where directives from the European Union are compulsory to follow and where the accounting
philosophy is the same. The study might also be of value to regions outside the European Union with an
investment environment similar to the Scandinavian and where IFRS-reporting recently
have been or will be adopted.
The analyses in this paper also raise a number of other interesting questions and unresolved issues
related to financial reporting and the current IFRS-based regulatory framework. In the following and final
subsection, we therefore list some of the more interesting areas where value-relevance research might be
fruitful or where value-relevance research could be improved.
Suggestions for Further Research
Our first research suggestion is detailed studies of the specifics in the regulatory framework of
accounting standards that surround the current IFRS-based financial reporting model. Increased
insights and understanding of how these accounting standards are perceived, interpreted and utilized
by users such as corporate accountants, auditors and financial analysts would certainly contribute to the
overall international debate on harmonized accounting standards and to the issue of whether or not we
should have a global framework for financial reporting. By studying the specifics, we would also be able to
approach an answer of the underlying raison d'être for the increased value-relevance in the
HAVE IFRS CONTRIBUTED TO AN INCREASED VALUE-RELEVANCE? 29
Scandinavian region. Given the recent global changes from a traditional capital-intensive economy into a
high-tech and service oriented economy with knowledge-intensive companies, we suggest that particular
research interest is directed towards intangible assets and the, since long, controversial subject of goodwill
- typically referred to as the black sheep of the balance sheet. Accounting standards of particular research
interest should therefore include IAS 38, which deals with both intangible assets and internally generate
goodwill. Particular research interest should also include
IFRS 3 where business combinations and thus externally generated goodwill are treated. IAS 36
should also obtain some research interest since it deals with impairments of both intangible assets and
goodwill, internally as well as externally generated.
A second suggestion for further research is to test and compare the value-relevance of annual and
quarterly earnings in order to shed some light on whether the market adopts and reacts to audited- and non-
audited financial information differently. Relative value-relevance comparisons of annual and
quarterly accounting data will to a great extent also reflect and address questions associated with the
modern role of the auditor.
A third research suggestion is to address and discuss the implications of the many underlying
assumptions and econometrical issues that surround value-relevance related research. Tests of market
efficiency could bring us closer to an answer of how rapidly equity investors react upon announcements
of publicly reported accounting information and improvements of equilibrium models
can help us broaden the scope of value-relevance research by eliminating some of the limitations that
is related to the simplifying assumptions of rational market behavior among investors.
A fourth and closely related issue to investigate is how we methodologically can address the fact that
financial information might be relevant - in that it is capable of making a difference in a decision as issued
in the conceptual framework for financial reporting - even though some user choose not to take advantage
of it or are already aware of it from other sources of information.
As a fifth and final recommendation for further research, we suggest studies that advance the
current knowledge on how we could simplify financial reports and statements into a language that is
understandable to even untrained accounting individuals. Research attention should primarily be directed
towards the problem of so-called black-box accounting where complex principle-based accounting
standards enable companies to hide unfavorable information by restating facts and include unnecessary
technical information, which easily can confuse untrained investors and force them into
wrong economic decisions. Contributions in this research area would benefit the society on a both
personal investor level and on a broader macro-economic level since it would increase the possibility for
investors, untrained as well as trained, to avoid investing in unprofitable companies, which, in the long run,
would benefit the society by mitigating the possibility for so-called lemons to exist.
30 BOGSTRAND AND LARSSON
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