Tel. : 32 - (0)9 – 264.34.61
Fax. : 32 - (0)9 – 264.35.92
A Critical Note on Empirical Comprehensive Income Research
Philippe Van Cauwenberge 1
Ignace De Beelde 1
1 Department of Accountancy and Finance, Ghent University. Kuiperskaai 55E, 9000 Ghent, Belgium.
This paper presents a critical analysis of empirical comprehensive income research, the majority of
which consists of value relevance studies. The first part of the analysis focuses on the functional form
of the value relevance regressions. The paper distinguishes between the informational and the
measurement approach to value relevance research and systematically traces the origin of the
specifications under both approaches. The informational approach is characterized by diversity in
functional form specifications, which can be traced to differences in expectations models for earnings
or price/earnings ratios. In the light of this diversity, it is remarkable to observe that most of the
authors provide little or no argumentation for the choice of their particular functional specification.
While the authors under the measurement approach try to legitimize their regression specifications by
referring to the work of Ohlson, in fact, one of the contributions of the residual income model is that it
demonstrates the restrictive nature of these specifications. The second part of the paper performs a
detailed investigation of the empirical findings. This analysis reveals several peculiarities that defy
economic intuition. These peculiarities are nontrivial since they, together with the low explanatory
power of the regressions, affect the credibility of the main research findings. The conclusion of the
paper is that there is danger in taking the empirical findings of this research domain at face value and
that the potential for informing standards setters is limited.
Keywords: Comprehensive Income; Dirty Surplus; Value Relevance; Residual Income Valuation
JEL Descriptors: M41
Ackowlegdements: This paper has benefited from the comments and suggestions of Walter Aerts
(University of Antwerp), Ann Tarca (University of Western Australia) and Guy Weyns (Morgan
Stanley and Co, London)
This paper presents a critical analysis of empirical comprehensive income research. The purpose
thereby is to assess the credibility of the research findings. Broadly defined, empirical comprehensive
income research considers statistical relations between market data and different income measures,
with the intention of providing information that is relevant to standard setters’ deliberations of their
performance-reporting projects. Section 2 starts out by briefly discussing the rational behind the
performance-reporting projects of FASB and IASB.
It should be noted from the outset that there is no intention of providing an exhaustive literature
review or a summarization of research findings. Such an overview can be found for instance in
(Thinggaard et al., 2006).1 Rather, the intention is to scrutinize the underlying methodological aspects
and to highlight some peculiar empirical findings. The majority of empirical comprehensive income
studies consists of value relevance research. Hence, a significant part of the analysis focuses on the
functional form specification of the value relevance regressions that are estimated therein. Section 3
provides an introduction to value relevance research and explains the distinction between the
informational and the measurement approach.
The original starting point for this analysis was the observation that, although comprehensive
income value relevance studies are, more or less, all intended to inform standard setters on the same
issue, they employ a wide variety of functional forms. In contrast to this diversity, most researchers
seem to take their functional form specification for granted, providing little or no argumentation for
their particular choice. Given that the functional specification obviously influences the statistical
findings, has implications for the inferences that can be drawn from it (Beaver, 2002), and potentially
has an impact on the credibility of the research, the variety of functional specifications might not be an
innocuous issue and seemed worthy of consideration.
Section 4 analyzes comprehensive income value relevance studies that are conducted under the so-
called informational approach. It is shown that the diversity in functional specifications therein can be
traced to differences in expectations models for earnings or price/earnings ratios. Since empirical
dominance among these different expectations models is not established, the choice of a functional
specification under the informational value relevance approach is arbitrary.
Section 5 considers value relevance tests under the so-called measurement approach, i.e. value
relevance test that are derived from a valuation model. The particular valuation model that is referred
to is the residual income valuation model (RIM). After closer inspection, it turns out that the
restrictions needed to attain congruence between RIM and the value relevance regressions are very
demanding. In fact, rather than legitimizing these particular value relevance tests, RIM actually reveals
their limiting character.
Section 6 considers in detail the nature of the empirical findings. A first general observation is that
the explanatory power of the regressions is exceedingly low, suggesting danger of model
misspecification and bias in coefficient estimation. Furthermore, a deliberately chosen selection of
findings shows several outcomes that defy economic reasoning. Generally, the researchers themselves
do not mention these - somewhat embarrassing - findings. They are also not discussed in the overview
paper of (Thinggaard et al., 2006), which takes the research findings at face value. However, these
counterintuitive findings are nontrivial since they affect the credibility of the main empirical findings
Section 7 presents an alternative approach to value relevance research (Isidro et al., 2006), which
is more in the spirit of RIM and is less restrictive than the aforementioned value relevance studies.
To our knowledge, this is the first paper that brings to the surface and makes an inventory of the
variety of functional form specifications in comprehensive income value relevance research and
systematically traces the origin of these functional forms. Through this analysis, it becomes clear that
the value relevance regressions are both arbitrary and underspecified. Another contribution is the
detailed analysis of the empirical results, which reveals several peculiarities that defy economic
intuition. Together with the low explanatory power of the regressions, these findings impact
negatively on the overall credibility of the main conclusions.
An old and unresolved issue in accounting is whether income should be determined according to the
principle of clean surplus accounting (Brief and Peasnell, 1996). Clean surplus income includes all
value changes in equity, except those resulting from transactions with the owners. Standard setters
have departed from clean surplus accounting on many occasions, allowing certain value changes to
bypass the income statement and be booked directly into equity. Typical examples of these so-called
dirty surplus flows are unrealised gains and losses on available-for-sale securities, additional minimum
pension liability adjustments, currency translations, gains and losses of cash flow hedges and asset
An important concept related to dirty surplus accounting is recycling or reclassification. Under
recycling, dirty surplus flows are booked into income against equity when, at a later date, certain
criteria regarding realisation and uncertainty are met (G4+1, 1999).
The practice of dirty surplus accounting has grown over the years and has been applied in an ad
hoc manner, mostly as a political way out of controversial accounting issues (Barker, 2004).
International evidence indicates that dirty surplus flows are potentially material, often not centred
on zero and subject to substantial cross-country variation (Isidro et al., 2004).
In response to this state of affairs, concerns arose about the increasing lack of transparency of dirty
surplus flows. Smith and Reither (1996) report that companies tend to obscure dirty surplus flows by
combining them with each other or with other categories of equity, resulting in significant search cost
and inefficiencies. Especially from the users’ side grew the demand for a statement of comprehensive
income, which would transparently present all income flows in one statement (AIMR, 1993).
In the US, the FASB responded to these concerns by issuing SFAS No. 130 in 1997, requiring
companies to report comprehensive income in a primary financial statement. However, SFAS 130, in
contrast to the exposure draft that preceded it, allows for the presentation of comprehensive income in
either a performance or a non-performance statement. The significance of this admission is reflected
by the number of companies that took advantage of it. In a survey of US companies, Mazza and Porco
(2004) find that 83 percent report comprehensive income in a statement of stockholders equity.
A particular problem of not presenting comprehensive income in a performance statement arises in
the context of earnings management. Lee et al. (2007) find that insurers who manage earnings through
selective realisation of gains and losses are more likely to report comprehensive income in the
statement of changes in equity. The underlying mechanism that allows companies to manage net
income through such gains trading is recycling. Thereby, previously unrealised gains and losses
appear in net income when they are realised. However, due to double-entry accounting, recycling of
income needs to be matched by a balancing cross-entry in equity. Of crucial importance for the
possibility of gains trading is the display of this cross-entry. When presentation of other
comprehensive income is required, one possibility is that this cross-entry is not only conducted in
equity, but also shown in other comprehensive income. In fact, other comprehensive income is nothing
more than a visually explicit elaboration on the dirty surplus changes in equity (i.e. changes in equity
not arising from retained earnings). In that sense, the inclusion of these so-called reclassification
adjustments in other comprehensive income is self-evident. These adjustments avoid that, over time,
other comprehensive income is double counted in comprehensive income. However, when other
comprehensive income is not included in the performance statement, the recycling entry that appears
in the performance statement is not matched in the same statement by the accompanying cross-entry of
opposite sign. Experimental research (Hirst and Hopkins, 1998) has shown that professional analysts
are less able to detect earnings management when other comprehensive income – and the cross-entry
therein, is not included in a performance statement, but rather in the statement of changes in equity.
For this and other reasons, FASB is currently reconsidering SFAS No. 130.
The IASB is currently also engaged in an investigation of the presentation of comprehensive
income (Barker, 2004). IAS 1, Presentation of Financial Statements, permits but does not require a
single comprehensive income statement. Since 2004, the IASB and the FASB joined forces in a
performance-reporting project (IASB, 2004).
Currently, some of the more pertinent issues are whether a single or a double performance
statement of comprehensive income should be required, whether earnings per share (EPS) should be
displayed for comprehensive income and whether recycling should be required, allowed or prohibited
2 (IASPlus, 2007). In other words, the debate is not so much about an exclusive choice between net
and comprehensive income, but rather about the relative prominence of display that should be
allocated to net income versus comprehensive income (Van Cauwenberge and De Beelde, 2007).3
When comprehensive income is presented as the most prominent income number, the risk is that users
might not be able to unscramble the different analytical properties of its components (Tarca, 2006).
When other comprehensive income is relegated to less prominent financial statements, its visibility is
reduced, which increases the chance that it might be overlooked (Robinson, 1991).
Obviously, an important consideration for standard setters’ deliberations is the actual relevance of
comprehensive income and other comprehensive income for valuation purposes, as is evidenced by
stock market data. Accordingly, it is no surprise that a considerable number of empirical research
papers has appeared that explicitly try to answer this question. This field of research is referred to in
this paper as empirical comprehensive income research. Since the majority of empirical
comprehensive income papers are value relevance studies, the next section presents a brief
introduction to value relevance research.
3. The nature and specifications of value relevance tests
Value relevance studies examine associations between security price-based dependent variables and a
set of accounting variables (Barth et al., 2001; Holthausen and Watts, 2001; Kothari, 2001). These
associations are investigated by applying linear regression techniques. An accounting number is
termed “value relevant” if its estimated regression coefficient reveals a statistically significant
association with the dependent variable.
Value relevance tests are either relative or incremental. In the context of comprehensive income
research, “relative” association studies compare the association between stock market prices (or
returns) and alternative bottom-line measures - mostly net income versus one or more measures of
comprehensive income. The income number yielding the most significant earnings response
coefficient (ERC) or the highest R² is considered to be the most value-relevant. In other words, relative
association tests aim to rank different income measures in terms of value relevance. On the other hand,
“incremental” value relevance studies examine whether, in addition to net income, one or more
components of OCI are useful in increasing the explained portion of the dependent variable.
Incremental value relevance is judged by whether the earnings response coefficients of these OCI
components are significantly different from zero or whether the adjusted R² increases after inclusion of
the OCI component. Several comprehensive income value relevance studies perform both relative and
incremental association tests.
An issue of obvious importance concerns the extent to which value relevance research has the
potential to allow for standard-setting inferences, an issue which already raised considerable
controversy (Barth et al., 2001; Holthausen and Watts, 2001). Implicitly, all value relevance papers
presume that value relevance implies superiority in some normative sense (Lee, 1999). Also in the
context of comprehensive income research, value relevance studies typically start out by pointing to
the comprehensive income reporting projects of the IASB and the FASB as the motivation for their
research, thereby suggesting that the empirical findings of the performed association tests are relevant
to standard setters’ deliberations.
To scrutinize the question of potential policy relevance, it is necessary to be more specific about
the meaning of the term value relevance. In other words, one needs to consider the underlying rational
behind the investigation of these associations. An important distinction in that regard is between the
measurement and the informational perspective (Barth, 2000; Barth et al., 2001; Holthausen and
Watts, 2001; Beaver, 2002; Walker, 1997)
Under the “measurement” perspective, the specification of a value relevance regression equation is
derived from a valuation model. A valuation model expresses firm value as a function of accounting
variables – mostly income, book value or a combination of both. At the same time, the underlying
valuation model also delivers predictions for the values of the estimated regression coefficients.
Association studies based on the measurement approach potentially allow for inferences with regard to
“relevance” and “reliability” of accounting numbers, properties that the standard setters have adopted
as their goals (Barth, 2000). In other words, under the presumption that the valuation model is
descriptive, failure to find the predicted coefficients may indicate that the inputs to the valuation
model, i.e. the accounting data, are irrelevant, unreliable or both. Therefore, in principle, standard
setters can use the findings of association studies under the measurement approach to judge the
effectiveness of their recognition and measurement policies.
An important assumption of the measurement approach is that accounting variables directly feed
into a firm valuation function. In other words, it needs to be assumed that a valuation function in terms
of accounting variables can be specified. Since the end of the 1960s, this approach has been subject to
severe criticism (Beaver et al., 1968). The most important source of objection was that, due to
uncertainty and the existence of imperfect and incomplete markets for a company’s assets and
liabilities, it is impossible to entertain the assumption that accounting variables bear any simple, direct
relationship to valuation (Beaver, 1998). The informational perspective, which grew out of this belief,
relies on less ambitious assumptions and considers only whether accounting data are useful to
investors (Lev 1989). Accordingly, with regard to the potential of informing standard setters, its
findings pertain only to the more abstract purpose of usefulness of accounting data.4 The only
assumption, that is entertained by the informational association studies, is that, if accounting variables
are useful to investors, then they should show up as price revisions (Ball and Brown, 1968).5
Accordingly, no predictions with respect to the sign and size of the coefficients are made. Usefulness
is assumed when the estimate of a coefficient of an accounting variable statistically differs from zero.
The distinction between the measurement approach and the informational approach also has
implications for whether the estimated relation between market and accounting data is specified in
levels or in flows. The informational approach states that a signal is informative only if the signal can
alter beliefs conditional upon the other information available (Beaver, 1998). In other words,
accounting information can only be relevant if it comes as a surprise. The determination of the surprise
component requires the formulation of an expectations model. With respect to income, a standard
approach has been to assume a naive random walk model, i.e.
Bernard, 1989; Kothari and Zimmerman, 1995; Lev and Ohlson, 1982). The surprise component is
then the change in earnings or .
According to the same reasoning, the corresponding dependent variable is the change in price (or
return) and not the price itself since the latter reflects both expected and unexpected information.
Accordingly, the econometric specification that corresponds naturally to the informational approach is
a flow equation. On the other hand, the measurement approach features a levels specification as a
logical starting point. The reason is that the valuation models, which underlie the estimated
regressions, are defined in levels (Barth, 2000).
Whether a value relevance test is performed in levels or in differences also determines the type of
inferences that are allowed for. The levels specification under the measurement approach addresses the
question of how well accounting variables reflect or summarize the economic condition of the firm, as
reflected by its stock price, irrespective of whether this information is timely or not. The informational
perspective explicitly addresses the question of timeliness: Accounting data can only be relevant in an
informational sense if they are not pre-empted by other information that is relevant for forming
However, when an association is uncovered under the informational approach, due to the lack of
the relation with a valuation model, the underlying economic rational for this association cannot
immediately be inferred from the value relevance study itself and remains an open question. The result
is merely an association, without direct implications or reference potential for standard setters
(Holthausen and Watts, 2001). In contrast, when an association is found under the measurement
approach, there is a valid presumption to conclude that the related accounting variable is both reliable
and relevant and that the valuation model has descriptive power.
It is possible that accounting data are relevant in a measurement sense, but not in an informational
sense. The reason is that they are not timely. A potential critique is that timeliness is not an overriding
issue for accounting standards setters. According to Ohlson and Penman (1992), the construct of
unexpected earnings, which researchers employ to explain returns, is irrelevant to the practicing
accountant who implements accounting principles. An important function of accounting data could be
to provide a legally liable and publicly available confirmation of company events (Beaver, 2002;
Watts and Zimmerman, 2001). This said, in practice, most value relevance studies that follow a
measurement approach are also estimated in first difference form. Typical reasons to depart from a
levels specification are concerns of heteroscedasticity and correlated omitted variables such as scale
(Barth, 2000). Note that, also in this case, the use of returns as a dependent variable requires the
formulation of an expectations model for the right-hand-side variables. However, under the
measurement approach, this issue is typically ignored.
4. Comprehensive income value relevance under the informational approach
Table 1 presents an overview of the different functional form specifications that appear in
comprehensive income value relevance research, together with a categorization of these specifications
as either derived from a valuation model or not. With the exception of (Brimble and Hodgson, 2005)
and (Cahan et al., 2000), all studies follow an informational perspective. In other words, they do not
provide a link to a valuation model.
As mentioned before, value relevance studies under the informational perspective are inferior, in
terms of standard setting inferencing potential, vis-à-vis valuation theory-based association studies.
Another consequence of the absence of an underlying valuation model is that the informational
perspective lacks the necessary rigor to discriminate among different functional specifications (Ohlson
and Skroff, 1992). A priori, one functional specification is as good as another and dominance can only
be settled by goodness-of-fit considerations. This ad hoc character is reflected by the diversity of
econometric specifications that characterizes the informational approach. This section intends to
investigate this diversity.
As explained in section 3, according to the basic random walk expectations model, the
specification that accords naturally to the informational perspective is a first difference relation
between returns and changes in income.
When relative informational value-relevance is investigated, the estimated value relevance
equation has the following form:
In the context of comprehensive income research, income is measured either as net income (NI) or
as comprehensive income (CI). When incremental value-relevance is investigated, the corresponding
is the vector of changes of other comprehensive income (OCI) components and
the associated vector of coefficients. When the incremental value relevance of aggregate OCI is
reduce to a scalar.
Returns are measured either as raw (R) or as abnormal returns (AR). Abnormal returns are
calculated as the out-of-sample forecast errors of an estimated market return model (i.e.
it Mt it
, where is the return of the reference market).
It is standard procedure in value relevance studies that income, or the change therein, is
normalized by beginning of period stock price (Christie, 1987; Ohlson, 1991).
Equations (1) and (2) are typically considered as the straightforward articulations of the research
question under the informational approach (Easton and Harris, 1991; Ohslon, 1991; Ohlson and Skroff
,1992). Note however that, although the use of the linear form for these equations is standard practice,
the restriction of linearity on the relation between unexpected earnings and returns is not implied as
such by the informational approach. Consider for instance (Ball and Brown, 1968), which is
uncontroversially regarded as the seminal paper for the informational approach to accounting research
(Beaver, 1998). Ball and Brown only partition a sample of firms according to whether they have a
negative or a positive earnings surprise and investigate whether this partition has discriminatory power
with respect to unexpected stock returns. No linearity is assumed. However, over time, correlation has
become a standard measure in empirical information content studies (Lev, 1989). Correlation confines
the discovery of co-movement between two variables to the linear form.
After consideration of part A of table 1, it is clear that none of the estimated functional forms
exactly corresponds to the basic format of equations (1) and (2). Nonetheless, it can be shown that the
right-hand sides of these equations, in some way or another, all proxy for unexpected earnings and that
they are variations to the basic formulations in (1) and (2). More in particular, the difference in
specifications is due to alternative expectations models for earnings or price/earnings ratios.
A first class of functional specifications is the one used by (Chambers et al., 2006) – henceforth
CLSS, (Dhaliwal et al., 1999) – henceforth DST, and O’Hanlon and Pope (1999) – henceforth OP (see
table 1). In each of these studies, returns are regressed over levels of income, to wit net income or
comprehensive income. Note that first differencing of a balance sheet valuation model (i.e.
, where MVE
u BVE MVE
it = market value of equity, BVEit = book value of equity and uit =
error term) also leads to this specification. However, none of these papers provide a link to a valuation
model. In fact, the motivation of the functional form generally receives scarce attention. With regard
to DST for example, it is only in a footnote that there is an (implicit) indication that the authors follow
an informational perspective: DST state that the use of income proxies for unexpected income (p. 50).
However, no further explanation is provided, apart from a reference to work of Easton and Harris
(1991) and Ohlson and Skroff (1992). DST also provide no link between the functional form
specification and the research question. Actually, the fact that DST essentially trace the relation
between returns and unexpected income is at odds with the central motivation of their paper, which is
described as ‘to investigate whether comprehensive income or net income better summarizes firm
performance as reflected in stock returns’ (p. 46). However, as mentioned in section 3, an association
study under the informational approach, which investigates the surprise component of earnings, is ill
suited to address this question.
CLSS provide even less explanation and defend their particular functional specification only by
the desire to be consistent with DST. Accordingly, CLSS also follow an informational perspective. It
is remarkable that CLSS invoke the work of Ohlson –more in particular Ohlson (1999), to explain
their empirical findings. So, while CLSS are clearly conscious of the work in Ohlson, they are silent
about the implications that this work has for the specification of value relevance regressions (see
To see how the specification in DST-CLSS-OP accords with equation (1), the latter is rewritten as:
it it itit itit
P INCP INCreturn
The only difference between (1) and (3) is that the normalisation by previous period price is
written explicitly in equation (3) instead of implicitly as in equation (1). The advantage is that the
formulation in equation (3) facilitates an alternative interpretation, which is that
P INCP INC
represents scaled unexpected earnings, with
serving as a
measure of expected
In an equilibrium model under certainty, the expected ratio for income to price is always equal to a
constant, more specifically, the risk free rate of return r (Ohlson, 1991). In other words,
. Accordingly then, the effect of adjusting
for its expected value –
the constant, is irrelevant in a regression context because the regression intercept picks up the constant.
In other words, when investigating the relation between returns and unexpected income, one might just
as well regress returns on income, which provides a rational for the specification of DST-CLSS-OP.
Notice that (Ohlson, 1991) is actually an attempt to reintroduce the measurement perspective into
the informational approach. More in particular, the equality between the price/earnings ratio and 1/r
applies only when accounting income equals economic income in a Hicksian sense.
Another specification is the one by (Cheng et al., 1993) – henceforth CCG. CCG regress both raw
and abnormal returns on income and the change in income. Notice that this specification corresponds
to the first difference form of a valuation model expressed in book value and income (i.e.
u INCk BVEk MVE
, were k indicates the level of rents and θ is related to
the discount rate). However, the use of abnormal returns as the dependent variable in CCG precludes
this possibility. CCG cite the conflict in the accounting profession between all-inclusive
comprehensive income and net income as the motivation for their work (p. 195), but do not explain
how this functional specification fits in addressing this policy issue. To justify their specification,
CCG only refer to work of Easton and Harris (1991), without any further explanation.
Returning to the specification of DST-CLSS-OP, the property of a constant ratio between expected
earnings and prices (Ohlson, 1991) was derived under specific conditions and is probably too stylized
a description of reality. A less extreme assumption is that earnings/price ratios are mean reverting.
Beaver and Morse (1978) have presented evidence supporting this assumption. The implication of this
mean-reverting behaviour is that
is a suboptimal indicator of expected
it itP INC
. As a
practical remedy towards this problem, the change in is often included as an additional
variable to the level of . Easton and Harris (1991) have provided evidence indicating that the
inclusion of both levels and changes in income increases the explained portion of returns. This
inclusion is however not supported by any formal modelling, but rather, is defended by goodness-of-fit
considerations. The above reasoning explains the specification of CCG as a variant of equations (1)
Finally, another functional form under the informational approach is the one by (Biddle and Choi,
2006) – henceforth BC, (Kubota et al., 2006) – henceforth KST and (Kanagaretnam et al., 2007) –
henceforth KMS. As a motivation, BC merely provide a reference to (Biddle et al., 1995). Instead of
considering the time series properties of the price/earnings ratio, (Biddle et al., 1995) models the time
series properties of earnings themselves. In particular, they propose an AR(1) pattern as a proxy for
the earnings expectations process. Furthermore, their approach to modelling the expectations process
is less restrictive in the sense that they leave the determination of the persistence parameter to be
settled by the data. In other words, the markets expectations parameter is estimated jointly with the
earnings response coefficient. The link to the specification of BC-KST-KMS can be seen as follows.
According to the AR(1) process,
where ρ is the persistence parameter. Equation (1) between returns and unexpected income becomes:
is the surprise component in income. Or alternatively,
In conclusion, behind the diversity in functional form specifications that appears in informational
value relevance comprehensive income studies, lies a variety in expectations models regarding
earnings or price-earnings ratios. In the light of this variety, it is remarkable to observe that most
authors seem to take their specification for granted, providing no explanation for their particular
Another problem concerning the formulations of earnings expectations models relates to the
presumed uniformity over different income components. Note that this is even a problematic
assumption for the different components of net income (Sloan, 1996). However, as a rough
approximation, it might be defensible. For instance, prior research (Bernard, 1993) has shown that
most components of net income follow a random walk. However, in the context of comprehensive
income, this assumption becomes more difficult to uphold. Components of other comprehensive
income are typically regarded as more transitory or less persistent than net income (Barker, 2004;
Black, 1993). Clearly, this causes difficulty with regard to the formulation of a uniform expectations
model for comprehensive income. None of the papers that were considered above make mention of
this problem. Nonetheless, each time comprehensive income – or the change therein, is included as an
independent variable in an informational value relevance regression, the underlying assumption is
made that a uniform expectations model for all components of comprehensive income is appropriate.
Barth and Clinch (1998) mention an even more particular problem in the case where other
comprehensive income incorporates fixed asset revaluations (FAR). Most firms opt not to revalue their
assets each year (Cahan et al., 2000). The consequence is that in the revaluation year, ,
while in the next year
and FAR = 0 in all the other years. Obviously, such a time
pattern is difficult to reconcile with any of the expectations models mentioned above.
5. CI value relevance research based on valuation theories
Value relevance regressions according to the measurement perspective are supposedly derived from a
valuation model, which relates company value either to book value, income or a combination of both
(Barth, 2000). Obviously, the latter class of valuation models is the most general as it subsumes the
former two. An important class of valuation models in terms of both book value and income are
residual income valuation models (RIM), which are generally attributed to the work of Feltham and
Ohlson.6 Important papers are (Feltham and Ohlson, 1995) and (Ohlson, 1995). Ohlson argues that the
abandonment of the income measurement theories in the late 1960s was a fundamental error in the
development of accounting research in general and in the value relevance research in particular
(Brimble and Hodgson, 2005) – henceforth BH, and (Cahan et al., 2000) – henceforth CCGU, are,
to the best of our knowledge, the only comprehensive income value relevance studies that follow the
measurement perspective. Both papers explicitly refer to the work of Ohlson (1995) to support their
The basic form of their (relative) value relevance regressions is a relation in first differences:
it it itit
The related levels specification from which it is derived is
itit it it
u INCk BVEk MVE
with k indicating rents and θ related to the discount rate.
However, it not immediately obvious how this specification accords to the formulation of RIM.
Basically, RIM translates the dividend-discounting model (DDM) into a valuation function in terms
book value and future abnormal earnings:
j itj it
Since it is a transformation of DDM, which is generally regarded as noncontroversial, and relies
thereby mainly on the assumption of clean surplus accounting, RIM is generally appreciated for its
versatility (Beaver, 2002; Lo and Lys, 2000).
Although RIM is expressed in terms of accounting variables, a limitation is that it still requires
predictions of future accounting numbers (Dechow et al., 1999). This means that it does not lend itself
to straightforward application in value relevance studies like BH and CCGU, which investigate the
relation between prices (or returns) and historical accounting numbers. To liberate RIM from the
prediction of future accounting numbers, Ohlson (1995) imposes an autoregressive process on
abnormal accounting income. These are the so-called linear information dynamics (LID):
ω is the persistence parameter of abnormal returns for company i and is assumed to be smaller
than one to guarantee stationarity.
ω < 1 accords to the assumption that, due to competition, abnormal
income should erode over time.7 Of particular importance is the inclusion of the other information
term , which makes the autoregressive model on abnormal income less restrictive. The inclusion of
explicitly recognizes that other financial and non-financial information besides income is
potentially relevant to determine income expectations.
i ϕ is the persistence parameter of these other
information shocks and is assumed to be smaller than 1 to assume stationarity. The LID assumption
allows RIM to be rewritten as:
, 2, 1
) 1 (
( ) ()()
While the pattern of mean reverting abnormal returns actually frees RIM from the prediction of
future accounting variables, this is only an assumption, whose validity is an empirical matter.
(Dechow et al., 1999) presents evidence that seems to support this assumption. However, even when
the LID pattern is entertained, the valuation expression, although it is defined in current accounting
variables, does still not resemble the specification of BH and CCGU. Thereto, even further restrictions
are required. First of all, both r and the persistence parameter of abnormal earnings,
ω , need to be
identical over all firms. Secondly, the other information, , needs to be considered as irrelevant for
predicting future income (Lee, 1999). This latter assumption is particularly troublesome since several
studies have shown that the inclusion of other financial and non-financial variables besides income
and book value can be useful in explaining market returns (Amir and Lev, 1996; Lev and Thiagarajan;
1993; Ou and Penman; 1989).
To conclude, to arrive from RID at the functional specifications of BH and CCGU, the amount and
nature of the restrictions is enormous. Both BH and CCGU are silent on these restrictions. So while,
by referring to the work of Ohlson, these papers explicitly try to establish legitimacy for their
functional specifications, in fact, a contribution of RIM is just that it demonstrates the restrictive
nature of these functional specifications. In this sense, it does not seem exaggerated to claim that the
functional specifications under the so-called measurement approach are no less ad hoc than the
specifications that follow the informational perspective. As a matter of fact, both BH and CCGU
perform their regressions in first difference form, which makes them literally indistinguishable, except
for the dependent variable, from the specification under the informational approach of CCG.
6. Some empirical findings
Section 4 showed that, under the informational value relevance approach, to each functional
specification, corresponds a different expectations model for earnings or for the price/earnings ratio.
The validity of these competing expectations models can only be settled empirically. Ex ante, each
earnings expectations model, and hence each functional specification is as good as another. This ad
hoc feature is reflected by the diversity of functional form specifications. Under the measurement
approach, BH and CCGU refer to RIM. However, the discussion in section 5 showed that the link
between RIM and the specifications of BH and CCGU relies on very demanding restrictions.
The conclusion emerges that there exists considerable latitude in the field of comprehensive
income value relevance research concerning the specification of the test equations. Another related
potential problem concerns the exclusive focus on book values and earnings – or, in first difference
form, earnings and changes therein - as independent variables. The omission of other (non-accounting)
information ( ) in the regressions and the focus on a few accounting variables is typical of value
relevance research in general. According to Barth (2000), this can be explained by the aim of
researchers to inform standard setters, who only have control over financial statement variables and
whose projects are typically focussed on one or a few accounting issues at a time. An obvious
drawback to this approach is the danger of model misspecification and omitted variables bias.
According to conventional econometric wisdom, a low R² indicates that a regression is badly specified
(Gujarati, 2003). However, R²’s in the range of 5 to 15% have become quite commonplace in value
relevance tests of earnings (Lev, 1989). Accordingly, they are not likely to arouse suspicion when
results are interpreted. With the intention of further assessing the credibility of value relevance
research in the field of comprehensive income, the next section presents a selection of empirical
Relative Value Relevance Tests
Relative association studies investigate which measure of income, net or comprehensive income, is
most highly associated with stock returns. Depending on the constituency, typical items that account
for the difference between net and comprehensive income are unrealised gains and losses on-available-
for-sale securities, foreign currency translations, minimum required pension liability adjustments,
asset revaluations (UK, Australia, New Zealand, Japan and IFRS GAAP), subsidies and consolidation
adjustments (Isidro et al., 2004).
It is hardly a controversial issue that, in general, these other comprehensive income components
can be considered as being less permanent than net income (Barker, 2004; Skinner, 1999). In fact, one
of the main sources of objection against the incorporation of dirty surplus flows in net income
originates from their transitory nature (Black, 1993; Brief and Peasnell, 1996). Accordingly,
comprehensive income is a measure that lumps together both relatively more permanent and more
transitory income components.
Kothari (2001) demonstrates that such an aggregate income number will be less correlated with
returns than the more permanent subtotal. Empirical research by Collins and Kothari (1989), Easton
and Zmijewski (1988), Kormendi and Lipe (1987) and Lipe (1986) already documented a positive
association between estimates of earnings persistence and earnings response coefficients. In his
overview, Lev (1989) commented on these findings as not particularly revealing. Indeed, the whole
idea of trying to make a link between prices, which are forward looking, and earnings, automatically
brings forward the suggestion that earnings should be persistent. In other words, association studies
automatically focus on the predictive ability of accounting numbers (Walker, 1997). Accordingly, any
empirical finding that confirms that net income is more value relevant than comprehensive income
would be both non-interesting and non-surprising (Skinner, 1999). A finding that comprehensive
income is more value relevant than net income would be puzzling.
Surprisingly, when the evidence of relative comprehensive income value relevance research is
considered, only a few studies are able to confirm this basic prediction. Cheng et al. (1993), using a
1972-1989 sample of US companies, find that comprehensive income is less useful in explaining
abnormal returns than net income. Their results hold both for pooled regressions and – with the
exception of banks, separate industry regressions. Brimble and Hodgson (2005) confirm this finding
using Australian data for the period between 1988 and 1997. Using a 1998-2003 sample of Japanese
companies, (Kubota et al., 2006) find that net income dominates comprehensive income for abnormal
returns. However, they do not find a significant difference for explaining raw returns. Another study
that cannot discriminate between net and comprehensive income is Dhaliwal et al. (1999) – at least not
when financial companies are excluded. DST investigate a 1994-1995 sample of US companies. The
tests of DST fail to discriminate between net and comprehensive income as an explanatory variable,
even after deletion of firm-years with non-material OCI numbers. When financial companies are
included, comprehensive income according to SFAS 130 actually dominates net income. Also for the
US, but for the period 1994-1998, Biddle and Choi (2006) find that comprehensive income defined by
SFAS 130 dominates net income in explaining equity returns. Perhaps not surprisingly, Biddle and
Choi offer no economic rational for their findings.
In conclusion, the question of which income measure has the highest value relevance seems
rhetorical and uninteresting, the dice being loaded in favour of net income. Several comprehensive
income studies do not even perform a relative value relevance test. Surprisingly, the empirical findings
do not speak with one voice. Given that these tests were performed over different periods and
countries, variations in the reporting environment might offer a partial explanation (Thinggaard et al.,
2006). However, given the absence in the literature of an economic rational explaining these results,
whatever the time period or country, alternative explanations should be considered. One such
alternative explanation is the limited explanatory power of the estimated regressions. Consider for
example the finding of (Kubota et al., 2006) that net income dominates comprehensive income with
respect to abnormal returns. The underlying adjusted R²’s of the regressions on which their conclusion
is based are respectively 2,2 and 3 percent. Except for the table where this result is reported, these R²’s
are not mentioned in the paper. However, R²’s of such a size suggest model misspecification and the
need to augment the specification with other variables.
In conclusion, the findings of relative comprehensive income value relevance research are either
non-interesting, confirming basic expectations, or puzzling. In the latter case, the low credibility of the
test results, due to the poor specifications, provides the most plausible explanation.
Incremental Value Relevance Tests
Incremental value relevance tests consider whether, in addition to net income, OCI or its separate
components are useful in explaining returns. Under the measurement approach, valuation theory
indicates that the size of the earnings response coefficient of OCI should equal one if OCI is transitory
(Ohlson, 1999). However, several factors might cause deviations from this prediction. For instance, a
coefficient greater than one might suggest a certain degree of persistence. Alternatively, the earnings
response coefficient of OCI items might deviate from one if these items contain measurement error.
Also the nature of OCI might influence the predicted coefficient. For instance, fixed asset revaluations
are even not considered as income if the concept of physical capital maintenance is entertained. Under
the informational approach, the only hypothesis that is tested is whether the earnings response
coefficients of OCI or its separate components are significantly different from zero.
(Cheng et al., 1993) only investigate the incremental value relevance of OCI as a whole and do not
consider the different components of OCI separately. CCG also do not provide estimates of earnings
response coefficients but only compare differences between adjusted R²’s when OCI is included in the
regression or not. They find little evidence of incremental value relevance of OCI. When regressions
are performed year by year, CCG find that the average adjusted R² does not change when OCI is
included. Performing the regressions industry-wise does show a significant increase in adjusted R²
(from 0,15 to 0,18). However, this result is attributable to one sector only (rubber, metal and
O’Hanlon and Pope (1999) use UK data over the period 1972-1992. They also find no relevance
for OCI or for any of its components. According to the authors, their test results provide particularly
strong evidence, since the relation between returns and earnings is estimated using long-term intervals.
By increasing the return interval, O’Hanlon and Pope claim to reduce the potential downward bias on
earnings response coefficients, which is due to timing differences between the recognition of
economic events by the stock market and by the accounting system (Easton et al., 1992). In other
words, the use of long-term return intervals is more generous towards the possibility of uncovering a
potential relation between returns and earnings. OCI as a whole, as well as its separate components fail
to be incrementally value relevant even when the relation between returns interval is prolonged up to a
period of 20 years.
However, it is far from obvious that the earnings response coefficient of OCI or its items should
increase when the returns interval is prolonged, since OCI items are not typically these income items
where one would expect timing differences between stock market recognition and accounting
recognition to be an issue. In fact, one of the main objections against incorporating OCI items into the
bottom-line income number is exactly that the concern that OCI items are volatile, incorporating value
changes too nervously into the accounting system (Black, 1993). Another source of objection against
the reasoning of O’Hanlon and Pope is the nature of the estimated results themselves.
Table 2 shows the findings when the incremental value relevance as OCI as a whole is estimated.9
The adjusted R² of the regression increases from 0,14 to 0,66 as the return interval is prolonged from 1
up to 20 years. According to the authors, ’the strength of the returns-earnings association increases as
the accumulation interval increases’ (p. 473). However, this is a remarkable conclusion, given that the
coefficient on net income does not increase – in fact, it slightly decreases from 1,98 to 1,87 and its
statistical significance decreases from 17,37 to 11,36. In fact, the whole idea of having a more
generous estimation of earnings response coefficients does not seem to work for net income, which
casts doubt on the argumentation that O’Hanlon and Pope provide to document the power of their test
results with respect to OCI. Rather, the increase in adjusted R² seems more likely to be attributable to
the constant term, which gains in size and significance over longer return intervals, indicating that the
unexplained portion of the regression that is picked up by this constant is increasing when longer
returns are used.
Using a 1992-1997 New Zealand sample, Cahan et al. (2000) find little evidence that OCI items
are value relevant above net income. However, due to the small sample size, the power of their test is
not impressive. When their tests are repeated after winsorization of the top/bottom 1% outliers for
each variable, the regression coefficient on net income is not even significantly different from zero,
which is hardly beneficial for the overall credibility of their findings (O’ Hanlon, 2000).
Biddle and Choi (2006) claim to find incremental value relevance for both gains and losses on
available-for-sale securities (SEC) and foreign currency translations (FCT). The regression on which
their conclusion is based yields an adjusted R² of 3,3 %. Moreover, several subresults of their analysis
are puzzling. Table 3 shows the results of their estimated regression.
Firstly, a somewhat disturbing finding is that the coefficient on net income is relatively small in
comparison to the coefficients of the components of other comprehensive income. From the
coefficients for t and t-1 on net income on the one hand and gains and losses on available-for-sale
securities on the other hand – respectively 0,24 and 0,01 and 1,17 and –0,17, can be derived that the
implicit estimate of the persistence factor for the income series ρ equals -0,04 for net income and
0,17 for available for-sale securities gains and losses.10 In other words, net income is estimated to be
less persistent than gains and losses from available-for-sale securities. Secondly, regarding foreign
currency translations adjustments, the negative coefficient for the current period of –0,52 and the
positive coefficient on the previous period of 4,46 together imply that market reacts negatively to
positive foreign currency translation surprises. In spite of the fact that these counterintuitive subresults
are embarrassing for the credibility of the overall findings, Biddle and Choi do not elaborate on (or
even mention) these subresults.
Kanagaretnam et al. (2007) compare the incremental value relevance of OCI items before and after
the implementation of SFAS 130, the idea being that markets participants better understand the value
implications of OCI items after SFAS 130 came into effect in 1997. For the post-implementation
period (1998-2003), they find that OCI items are incrementally value relevant and more so than in the
pre-implementation period (1994-1997). However, the empirical findings of Kanagaretnam et al.
(2007) also contain some remarkable subresults. For instance, for the pre-implementation period, the
earnings response coefficient for net income is 0,097. While the absolute size of this coefficient is
puzzling, even more suspect is the finding that the coefficient on available for sale securities is
approximately five times as large (0,47). The authors do not discuss these particular outcomes. Again,
it could be argued that they undermine the overall credibility of the findings. The R²’s, which are in
the area of between 0,6 and 3 %, are hardly comforting in this respect.
A particularly interesting paper is Pinto (2005), which demonstrates the vulnerability of test results
to the specification of comprehensive income value relevance regressions. Pinto uses a levels
specification to investigate the incremental value relevance of foreign currency adjustments for US
firms with direct investment located primarily in either Mexico or Germany. Translation adjustments
arise when multinational firms restate their foreign domiciled assets and liabilities, denominated in
local currency units, into home currency units at the balance sheet date.
According to the results in table 4, foreign currency translations ( CTA
11) are value relevant, but
in the opposite direction of what one would expect, i.e. appreciation of a foreign subsidiary’s currency
leads to a lower stock price for the parent company. This result is consistent with (Biddle and Choi,
2006). However, and contrary to the aforementioned studies, Pinto does not ignore this economically
implausible result, but rather explicitly addresses it as an indication of model misspecification12 and
enriches the regression analysis with interaction terms. The latter serve as proxies for theoretical
factors which are relevant to determine the true economic exchange rate exposure to which a company
is exposed through it foreign operations. CAPITALINTENSITY indicates the percentage of non-
monetary assets of a subsidiary. According to the theory of purchasing power parity, local prices and
exchange rates move in opposite directions. In other words, non-monetary assets tend to immunitize
the effect of exchange rate changes.13 COUNTRY is a dummy indicating whether the exchange rate
change occurs in a developed or in an emerging country, the underlying idea being that currencies of
developed countries tend to follow a random walk pattern, while the currencies of emerging countries
tend to be more serially correlated. 1994 is a dummy for the Mexican peso crisis.
The results of this augmented regression analysis (table 5) show that the sign of the coefficient of
foreign currency translation has turned from significantly negative to significantly positive. Granted
that the absolute value of this coefficient is still puzzling, these results clearly demonstrate the
sensitivity to omission of variables. Given that the regressions that were performed in the
aforementioned studies all suffer from exceedingly low R²’s, the danger that they may suffer from the
same problem looms large.
7. An alternative: The Valuation Approach of (Isidro et al., 2006)
An alternative to value relevance research is (Isidro et al., 2006) – henceforth IHY. IHY explore
the association between dirty surplus flows and valuation errors from a standard empirical application
of RIM. The analysis is performed for France, Germany, the U.K. and the U.S. for the period 1994-
2001. IHY calculate the intrinsic value per share VPS using a three-period per-share RIM:
)(*) 1 () 1 (
where bps is book value per share, are expected abnormal earnings per share and g is a constant
growth rate for residual income per share as of t+3. Predictions for and are obtained
from I/B/E/S mean consensus forecasts. The forecasts for are estimated by the country-industry
specific average return on equity over the previous seven years to the date of valuation. Dividends per
share are predicted by using the average country-industry specific dividend payout ratio over the
previous seven years. Given forecasts of eps and dividends per share, forecasts for and
are obtained through the mechanics of the per-share clean surplus relation. The discount rate r reflects
a country-industry specific estimation of a company’s beta. The constant growth rate g is the product
of the estimated return on equity and (1- the estimated dividend ratio). Finally, the valuation error is
measured as the intrinsic value per share VPS less the market price at the valuation date.
Note that, when compared to the aforementioned value relevance studies that claim to be based on
RIM, the valuation approach by IHY is far less limiting. Firstly, since the RIM specification is used in
its original form, there is no need to squeeze RIM into a linear function in terms of book value and
earnings. In addition, since earnings predictions are obtained through I/B/E/S estimates, there is no
need to rely on the linear information dynamics (LID). Another advantage of the use of I/B/E/S
estimates is that the ‘other information’ (V) is no longer ignored, since one can assume that analysts
incorporate all available information in their predictions.
IHY find only limited evidence of a relation between dirty surplus flows and valuation errors and
conclude: ‘Overall, our results do not suggest that dirty surplus accounting flows are a consistent
source of error in applications of accounting-based valuation models’ (p. 303).14 Note that the
contemporaneous effect on book value of dirty surplus flows at time t is included into the valuation
model of IHY through the incorporation of .
15 Therefore, IHY need to rely on the assumption that
current dirty surplus flows predict future dirty surplus flows in order to expect a relation between dirty
surplus and valuation errors. In other words, the lack of association between dirty surplus flows and
valuation errors in IHY only confirms the aforementioned property that dirty surplus flows are
generally transitory in nature.16 Obviously, one might wonder whether a more straightforward
approach might not have been to directly investigate the time series properties of surplus flows
themselves. Nonetheless, the results of IHY are relatively more credible than the results of value
relevance studies, given the less restrictive nature of their research assumptions.
This paper assesses the credibility of comprehensive income value relevance research through an
investigation of the functional form specifications of the value relevance regressions and analysis of
the empirical findings.
The analysis of the functional form specifications revealed that the regressions are ad hoc and
underspecified. A detailed study of the empirical results uncovered several counterintuitive findings,
which affect the overall credibility of the main research results. The central conclusion of our analysis
is that the credibility of comprehensive income value relevance research presents an obstacle for its
potential usefulness of informing standard setters.
Our analysis is fundamentally distinct from the one presented by Holthausen and Watts (2001).
Their issue with value relevance research stems the supposed absence of a relation between the
statistical properties investigated by value relevance research and the objectives of standard setters.
The analysis that was presented here does not even consider this relation.
Our analysis from the current is potentially relevant to appreciate the contribution of a recent
overview paper by (Thinggaard et al., 2006). Thinggaard et al. (2006) explicitly state their objective as
to inform standard setters regarding research that is relevant to the performance-reporting project (p.
35). They also presented their work to the IASB as part of a comment on the exposure draft regarding
the first phase of the performance-reporting project (IASB, 2007). However, Thinggaard et al. present
the overall conclusions of the papers involved at face value, taking the underlying functional form
specifications and the credibility of the findings for granted. Given the problems that were mentioned
in this paper, it becomes doubtful that such a mere summarization of research findings really does a
service to standard setters.
A suggestion that seems to follow naturally from our analysis is that value relevance researchers
investigating comprehensive income should at least be sensitive to the potential of omitted variable
bias and consider augmenting their value relevance regressions with other (non-accounting) variables.
Liu and Thomas (2000), for example, show that the inclusion of other variables besides earnings
increases the R² substantially and reduces the bias in coefficient estimates. On the other hand, the
choice of which other variables to include will probably always be arbitrary and therefore suspect.
The valuation approach, as exemplified by (Isidro et al., 2006), was suggested as an alternative to
value relevance research that merits further consideration for future work.
1 (Chambers et al., 2006), (Isidro et al., 2006), (Kanagaretnam et al., 2007) and (Kubota et al., 2006)
are recent papers that are not covered by (Thinggaard et al., 2006).
2 A special issue in the context of recycling concerns cash flow hedges. A prohibition on recycling
would essentially eliminate cash flow hedge accounting.
3 According to Hodge et al. (2004), given the emergence of search technologies like for instance
XBRL, the definition of income by standard setters will be partially pre-empted by the definition of
“data tags” in these search engines. Up to now, the implications of XBRL have been ignored in the
4 The conceptual frameworks of both IASB and FASB refer to usefulness, relevance and reliability.
However, usefulness is defined at a higher level: Reliability and relevance are operationalisations of
the usefulness criterion (IASB, 1989; FASB, 2000)
5 In micro-economic terms, accounting information is assumed to be useful if it can change the
information set of an expected utility maximizing investor. The ensuing update in the subjective
probability distribution or belief function of an investor might, taking into account transactions costs,
etc., in turn invoke a response. This response is reflected in market data (prices, returns, volatility,
6 (Preinreich, 1936) and (Edwards and Bell, 1961) contain earlier formulations of RIM. The
widespread popularity of RIM is due to the work of Ohlson, mainly because of the inclusion of the
linear information dynamics (LID).
7 In other words, it is thereby also assumed that accounting is unbiased, which means that abnormal
earnings are on average zero. Accounting is biased for instance if it is conservative. Feltham and
Ohlson (1995, 1996) incorporate biased accounting by assuming that current book values help predict
information about future income.
8 Also for banks, Barth et al. (1990) demonstrate that earnings before security gains and losses is
associated with a higher multiple than security gains and losses, indicating that the latter are perceived
by the market as being more transitory in nature.
9 The results are more or less the same when the value relevance of OCI items separately is
10 Because of the underlying AR (1) earnings expectations model,
, where ρ is the
persistence parameter of the AR(1) process.
is the per-share change in the cumulative translation adjustment from period t to period t-1
12A similar analysis is presented in (Louis, 2003). According to Louis, ‘sticky wages’ might cause
foreign currency depreciations to actually increase parent company profits. The reason is that foreign
inflation, which according to purchasing power theory, coincides with depreciation, is not fully
matched by wage increases when wages are sticky. Accordingly, labour-intensive firms might benefit
from foreign currency depreciations. When this is not explicitly taken into account in a regression
analysis, the estimated coefficient on foreign currency translation might pick up this effect.
13 Note that this argument relies on historical cost measurement of the assets of the subsidiary.
14 For some components of OCI and for some specific countries, Isidro et al. (2006) do find a relation
between dirty surplus flows and valuation errors, although sometimes, like for instance for goodwill
write-offs, the relation is positive. In other words, dirty surplus goodwill write-offs cause RIM to
undervalue a stock. According to Isidro et al. (2006), an explanation could be that goodwill write-offs
imply growth opportunities. However, this explanation is only satisfactory to the extent that these
growth opportunities are not already included in the I/B/E/S earnings expectations.
15 Note that since dirty surplus flows are included in book value of equity, which is included in RIM,
the study of Isidro et al. is not able to investigate the ‘book value’ relevance of dirty surplus flows.
16 An alternative explanation might be that there are dirty surplus flows are indeed persistent, but that
dividend payments from future dirty surplus flows are expected to arise long after the flow itself, for
example as part of a liquidating dividend. Other potential explanations are related to lack of data
accuracy, the undescriptive nature of RIM and accounting diversity among firms due to the composite
nature of the sample (Tarca, 2006).
AIMR, Association for Investment Management and Research, 1993, Financial Accounting in the
1990s and Beyond; AIMR, Charlottesville, VA.
Amir, E. and Lev, B., 1996, Value-relevance of Nonfinancial Information: The Wireless
Communications Industry, Journal of Accounting and Economics, 22, pp. 3-30.
Ball, R. and P. Brown, 1968, An Empirical Evaluation of Accounting Income Numbers, Journal of
Accounting Research, Autumn, pp. 159-178.
Barker, R., 2004, Reporting Financial Performance, Accounting Horizons, 18 (2), pp. 157-172.
Barth, M.E., 2000, Valuation-based Accounting Research: Implications for Financial Reporting and
Opportunities for Future Research, Accounting and Finance, 40, pp. 7-31.
Barth, M.E. and G. Clinch, 1998, Revalued, Tangible, and Intangible Assets; Associations with Share
Prices and Non-Market Based Value Estimates, Journal of Accounting Research, 36, Supplement, pp.
Barth, M.E. , Beaver, W.H. and W.R. Landsman, 2001, The Relevance of the Value Relevance
Literature for Financial Accounting Standard Setting: Another View, Journal of Accounting and
Economics, 31, pp. 77-104.
Barth, M.E., W.H. Beaver and M. Wolfson, 1990, Components of Earnings and the Structure of Bank
Share Prices, Financial Analysts Journal, 46, pp. 53-60.
Beaver, W.H., 2002, Perspectives on Recent Capital Markets Research, Accounting Review, 77 ( 2),
Beaver, W.H., 1998, Financial Reporting: An Accounting Revolution, Prentice-Hall.
Beaver, W. H. and J. Demski, 1979, The Nature of Income Measurement, Accounting Review, 55, pp.
Beaver, W.H., Kennelly, J.W. and W.M. Voss, 1968, Predictive Ability as a Criterion for the
Evaluation of Accounting Data, Accounting Review, pp.675-683.
Beaver, W. and D. Morse, 1978, What determines Price-Earnings Ratios?, Financial Analysts Journal,
July/August, pp. 65-76.
Bernard, V. 1993, Accounting-based Valuation Methods, Determinants of Market-to-Book Ratios and
Implications for Financial Statements Analysis, Working Paper Michigian Business School,
University of Michigan.
Bernard, V., 1989, Capital Markets Research in Accounting during the 1980s: A Critical Review.
Paper for the University of Illinois Accountancy Ph.D. Program, Golden Jubilee Symposium.
Biddle, G. and J. H. Choi, 2006, Is Comprehensive Income Useful?, Journal of Contemporary
Accounting Research and Economics, 2(1)
Biddle, G.C., Seow, G.S. and A.F. Siegel, 1995, Relative versus Incremental Information Content,
Contemporary Accounting Research, 12 (1), pp. 1-23.
Black, 1993, Choosing Accounting Rules, Accounting Horizons, 7, pp. 1-17.
Brief, R.P. and K.V. Peasnell, eds., 1996, Clean Surplus, A Link between Accounting and Finance,
Garland Publishing Inc.
Brimble, M. and A. Hodgson, 2005, The Value Relevance of Comprehensive Income Components in
an Asset Revaluation Environment, Paper Presented at the EAA Annual Congress Götheborg.
Cahan, S.F., Courtenay, S.M., Gronewoller, P.L and D.R. Upton, 2000, Value Relevance of Mandated
Comprehensive Income Disclosures, Journal of Business Finance and Accounting, 27, 9-10, pp. 1273-
Chambers, D., Linsmeier, T.J., Shakespeare, C. and T. Sougiannis, 2006, An Evaluation of SFAS No.
130 Comprehensive Income Disclosures, working paper
Cheng, C.S.A., Cheung, J.K., and V. Gopalakrishnan, 1993, On the Usefulness of Operating Income,
Net Income and Comprehensive Income in Explaining Security Returns, Accounting and Business
Research, 23, 91, pp. 195-203.
Christie, A., 1987, On Cross-Sectional Analysis in Accounting Research, Journal of Accounting and
Collins, D. and S. Kothari, 1989, An Analysis of Inter-Temporal and Cross-Sectional Determinants of
Earnings Response Coefficients, Journal of Accounting and Economics, 11, pp. 143-181.
Dechow, P.M., Hutton, A.P, and R.G. Sloan, 1999, An Empirical Assessment of the Residual Income
Valuation Model, Journal of Accounting and Economics, 26, pp. 1-34.
Dhaliwal, D., Subramanyam, K.R. and R. Trezevant, 1999, Is Comprehensive Income Superior to Net
Income as a Measure of Firm Performance?, Journal of Accounting and Economics, 26, pp. 43-67.
Easton, P.D. and M. Zmijewski, 1989, Cross-sectional Variation in the Stock Market Response to
Accounting Earnings Announcements, Journal of Accounting and Economics, 11, pp. 117-141.
Easton, P.D., and T.S. Harris, 1991, Earnings as an Explanatory Variable for Returns, Journal of
Accounting Research, 29(1), pp. 19-36.
Easton, P.D., Harris, T. and J. Ohlslon, 1992, Aggregate Accounting Earnings Can Explain Most of
Security Returns, Journal of Accounting and Economics, June, pp. 119-142.
Edwards, E. and P. Bell, 1961, The Theory and Measurement of Business Income, Berkeley:
University of California Press.
Feltham, G.A., and J.A. Ohlson, 1995, Valuation and Clean Surplus Accounting for Operating and
Financial Activities, Contemporary Accounting Research, 11, pp. 689-732.
Feltham, G.A., and J.A. Ohlson, 1996, Uncertainty Resolation and the Theory of Depreciation
Measurement, Journal of Accounting Research, 34 (Autumn), pp. 209-234.
G4+1, 1999, Position Paper: Reporting Financial Performance, www.iasb.org.
Gujarati, D.M., 2003, Basic Econometrics, McGraw-Hill Companies.
Hirst, D.E. and P.E. Hopkins, 1998, Comprehensive Income Reporting and Analysts’ Valuation
Judgements, Journal of Accounting Research, 36, Supplement, pp. 47-74.
Hodge, F., Kennedy, J.J. and L.A. Maines, 2004, Does Search-Facilitating Technology Improve
Transparency ?, Accounting Review, 79, 3, pp. 687-703.
Holthausen, R.W. and R.L. Watts, 2001, The Relevance of the Value-Relevance Literature for
Financial Accounting Standard Setting, Journal of Accounting and Economics, 31, pp. 3-75.
IASPlus, 2007, IASB Projects, www.iasplus.com.
International Accounting Standards Board (IASB), 2004, International Working Group on
Performance Reporting Announced, www.iasb.org.
International Accounting Standards Board (IASB), 2005, Performance Reporting, Project Update,
International Accounting Standards Board (IASB), 2007, Performance Reporting, www.iasb.org.
Isidro, H., O’Hanlon, J. and S. Young, 2006, Dirty Surplus Accounting Flows and Valuation Errors,
Abacus, Vol. 42, 3-4, pp. 302-344.
Isidro, H., O’Hanlon, J. and S. Young, 2004, Dirty Surplus Accounting Flows: International Evidence,
Accounting and Business Research, 34(4), pp. 383-411.
Kanagaretnam, K., Mathieu, R. and M. Shehata, 2007, Usefulness of Comprehensive Income
Reporting in Canada: Evidence from Adoptation of SFAS 130, Journal of Accountancy and Public
Kormendi, R. and R. Lipe, 1987, Earnings Innovations, Earnings Persistence and Stock Returns,
Journal of Business, 60, pp. 323-345.
Kothari, S.P., 2001, Capital Markets Research in Accounting, Journal of Accounting and Economics,
31, pp. 105-231.
Kubota, K., Kazuyuki, S., and H. Takehara, 2006, Reporting of the Current Earnings plus Other
Comprehensive Income: Information Content Test of Japanese Firms, paper presented at the AAA
2006 Annual Meeting.
Lee, C. M., 1999, Accounting-Based Valuation: Impact on Business Practices and Research,
Accounting Horizons, 13, 4, pp. 413-425.
Lee, Y., Petroni, K. and M. Shen, 2007, Cherry Picking, Financial Reporting Quality and
Comprehensive Income Reporting Choices: The Case of Property-Liability Insurers, Contemporary
Accounting Research, forthcoming.
Lev, B. and J.A. Ohlson, 1982, Market-Based Empirical Research in Accounting: A Review,
Interpretation, and Extension., Journal of Accounting Research, 20, pp. 249-322.
Lev, B. and S.R. Thiagarajan, 1993, Fundamental Information Analysis, Journal of Accounting
Research, 31(2), pp. 190-215.
Lev, B., 1989, On the Usefulness of Earnings and Earnings Reactions: Lessons and Directions from
Two Decades of Empirical Research, Journal of Accounting Research, 27, Supplement, pp. 153-192.
Lipe, R.C., 1986, The Information Contained in the Components of Earnings, Journal of Accounting
Research, 24, Supplement, pp. 37-64
Liu, J. and J. Thomas, 2000, Stock Retuns and Accounting Earnings, Journal of Accounting Research,
38(1), pp. 71-101.
Lo, K. and T. Lys, 2000, The Ohlson Model: Contribution to Valuation Theory, Limitations and
Empirical Applications, Journal of Accounting, Auditing and Finance, 15, 3, pp. 337-367.
Louis, H., 2003, The Value Relevance of the Foreign Translation Adjustments, Accounting Review,
78, 4, pp. 1027-1047.
Mazza, C. and B. Porco, 2004, An Assessment of the Transparancy of Comprehensive Income
Practices of U.S. Companies, working paper.
O’Hanlon, J. and P. Pope, 1999, The Value-Relevance of UK Dirty Surplus Accounting Flows, British
Accounting Review, 31, pp. 459-482
O’Hanlon, J., 2000, Discussion of ‘Value Relevance of Mandated Comprehensive Income
Disclosures, Journal of Business Finance and Accounting, 27(9) and (10), pp. 1303-1309.
Ohlson, J.A., 1995, Earnings, Book Values and Dividends in Security Valuation, Contemporary
Accounting Research, 11, pp. 661-687.
Ohlson, J.A., 1991, The Theory of Value and Earnings, and an Introduction to the Ball-Brown
Analysis, Contemporary Accounting Research, Fall, pp. 1-19.
Ohlson, J. A. and P.K. Skroff, 1992, Changes versus Levels in Earnings as Explanatory Variables for
Returns: Some Theoretical Considerations, Journal of Accounting Research, Vol. 30, No.2, pp. 210-
Ohlson, J.A. and S.H. Penman, 1992, Disaggregated Accounting Data as Explanatory Variables for
Returns, Journal of Accounting, Auditing and Finance, Fall, pp. 553-573.
Ohlson, J.A., 1999, On Transitory Earnings, Review of Accounting Studies, 4, pp. 145-162.
Ou, J.A., and S.H. Penman, 1989, Accounting Measurement, Price-Earnings Ratio and the Information
Content of Security Prices, Journal of Accounting Research, 27, Supplement, pp. 111-144.
Pinto, J. A. , 2005, How Comprehensive is Comprehensive Income? The Value Relevance of Foreign
Currency Translation Adjustments, Journal of International Financial Management and Accounting,
16, 2, pp. 97-122.
Preinreich, G.A.D., 1936, The Fair Value and Yield of Common Stock, Accounting Review, pp. 130-
Robinson, L.E., 1991, The Time Has Come to Report Comprehensive Income, Accounting Horizons,
June, pp. 107-112.
Skinner, D.J., 1999, How Well Does Net Income Measure Firm Performance? A Discussion of Two
Studies, Journal of Accounting and Economics, 26, pp. 105-111.
Sloan, R.G., 1996, Do Stock Prices Fully Reflect Information in Accruals and Cash Flows about
Future Earnings, Accounting Review, 71, 3, pp. 289-315.
Smith, P.A. and C.L. Reither, 1996, Comprehensive Income and the Effect of Reporting It, Financial
Analysts Journal, November/December, pp. 14-19.
Tarca, A., 2006, Discussion of Isidro, O’Hanlon and Young, Abacus, Vol. 42, 3-4, pp. 345-353.
Thinggaard, F., Wagenhofer, A., Eva, L., Gebhardt, G., Hoogendoorn, M., Marton, J., Di Pietra, R.,
Mora, A., and K. Peasnell, 2006, Performance Reporting - The IASB’s Proposed Formats of Financial
Statements in the Exposure Draft of IAS 1, Accounting in Europe, Vol. 3, pp. 35-63.
Van Cauwenberge, P. and De Beelde, I., 2007, On the IASB Comprehensive Income Project: An
Analysis of the Case for Dual Income Display, Abacus, Vol. 43, No. 1, pp. 1-26.
Walker, M., 1997, Clean Surplus Accounting Models and Market-Based Accounting Research: A
Review, Accounting and Business Research, Vol. 27, No. 4, pp. 341-355.
Functional form of estimated equation
Part A: Informational
Chambers et al. (2006)
Dhaliwal et al. (1999)
O’Hanlon and Pope (1999)
TABLE 1. Overview of functional specifications
* R(elative) and I(ncremental)
R = raw return, AR = abnormal return, INC = Income, NI = Net Income, CI = Comprehensive Income and OCI = Other Comprehensive Income
Relative value relevance (R)
Incremental value relevance (I)
Cheng et al. (1993)
Relative value relevance (R)
it it it it
Incremental value relevance (I)
itit ititit it
OCI OCININI AR
Mean reversion of
ii PINC /
Biddle and Choi (2006)
Kubota, Suda, Takehara,
Kanagaretnam et al. (2007)
Relative value relevance (R)
Incremental value relevance (I)
[ ] [
itit it itit it
irrelevance of other
RIM and LID,
[ ] [
] [ ] [
it it itititit
it itit it
Incremental value relevance
Relative value relevance
Brimble and Hodgson
Cahan et al. (2000)
Part B: Measurement
TABLE 2. Source: (O’Hanlon and Pope, 1999)
Interval length (T) N
1 years 3060 -0,01
2 years 1529 -0,10
5 years 610 -0,44
10 years 302 0,23
20 years 147 4,14
TABLE 3. Source: Biddle and Choi (2006)
it ititit it itit it
NI SEC FCT … R²
TABLE 4. Source: Pinto (2005)
40 Download full-text
TABLE 5. Source: Pinto (2005)
itit ititit it it