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Accounting, Organizations and Society 27 (2002) 775–810
www.elsevier.com/locate/aos
Experimental research in ﬁnancial accounting
Robert Libby *, Robert Bloomﬁeld, Mark W. Nelson
Johnson Graduate School of Management, 383 Sage Hall,
Cornell University, Ithaca NY 14853 6201, USA
Abstract
This paper uses recent experimental studies of ﬁnancial accounting to illustrate our view of how such experiments
can be conducted successfully. Rather than provide an exhaustive review of the literature, we focus on how particular
examples illustrate successful use of experiments to determine how, when and (ultimately) why important features of
ﬁnancial accounting settings inﬂuence behavior. We ﬁrst describe how changes in views of market eﬃciency, reliance
on the experimentalist’s comparative advantage, new theories, and a focus on key institutional features have allowed
researchers to overcome the criticisms of earlier ﬁnancial accounting experiments. We then describe how speciﬁc
streams of experimental ﬁnancial accounting research have addressed questions about ﬁnancial communication
between managers, auditors, information intermediaries, and investors, and indicate how future research can extend
those streams. We focus particularly on (1) how managers and auditors report information; (2) how users of ﬁnancial
information interpret those reports; (3) how individual decisions aﬀect market behavior; and (4) how strategic interactions between information reporters and users can aﬀect market outcomes. Our examples include and integrate
experiments that fall into both the ‘‘behavioral’’ and ‘‘experimental economics’’ literatures in accounting. Finally, we
discuss how experiments can be designed to be both eﬀective and eﬃcient. # 2002 Elsevier Science Ltd. All rights
reserved.
1. Introduction
Financial accounting research is a broad ﬁeld
that examines ﬁnancial communication between
managers, auditors, information intermediaries,
and investors, as well as the eﬀects of regulatory
regimes on that process. Much of this literature
focuses on managers’ and auditors’ reporting decisions and their relationships to analysts’ forecasts
and value estimates, investors’ trading decisions,
and resulting market prices. This clear focus on
judgment and decision making led to the large
* Corresponding author. Tel.: +1-607-255-3348; fax: +1607-254-4590.
E-mail address: rl54@cornell.edu (R. Libby).
number of experimental ﬁnancial accounting
studies published in major accounting journals in
the 1960s and 1970s.
Serious criticisms of this early research (e.g.
Gonedes & Dopuch, 1974) turned experimentalists’
focus away from ﬁnancial accounting issues in the
1980s and early 1990s. As discussed by Maines
(1995) and Berg, Dickhaut, and McCabe (1995),
major elements of these criticisms were: (1) the
irrelevance of individual behavior in market settings, in which competitive forces will eliminate
individual ‘‘errors’’; (2) poor matching of research
methods to research questions; (3) the lack of
psychological or economic theory to predict eﬀects
and specify the mechanisms through which they
occur; and (4) failure to capture relevant aspects
0361-3682/02/$ – see front matter # 2002 Elsevier Science Ltd. All rights reserved.
PII: S0361-3682(01)00011-3
776
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
of the decisions of interest, in particular, decision
maker attributes and institutional features.
Beginning in the mid-1990s, there was a resurgence of experimental research addressing an even
broader spectrum of ﬁnancial accounting issues.
This paper presents our view of how this new literature has addressed prior criticisms, and how it
can continue to shed light on ﬁnancial accounting
questions. We argue that signiﬁcant evidence of
capital market ineﬃciency has renewed interest in
how individuals make key accounting-related
decisions and how these decisions aﬀect market
prices. Recent studies take advantage of the
experimentalist’s comparative advantage at disentangling variables that are confounded in natural
settings and measuring intervening processes to
draw strong causal inferences. Theories combining
psychology and economics have allowed experimentalists to specify more clearly the mechanisms
aﬀecting individual and market behavior. Finally,
most of the new studies focus on issues of clear
relevance to ﬁnancial accounting, particularly the
eﬀects of decision-maker knowledge and motivation, the complex information environment, regulation, and strategic interaction.
This paper is aimed primarily at those who plan
to conduct ﬁnancial accounting experiments, and
secondarily at other ﬁnancial accountants who are
interested in what can be learned from experimental studies. Our primary goal is to use recent
experimental studies of ﬁnancial accounting to
illustrate our view of how such experiments can be
conducted successfully. The core of our view is
that successful ﬁnancial accounting experiments use
the comparative advantages of the experimental
approach to determine how, when and (ultimately)
why important features of ﬁnancial accounting settings inﬂuence behavior. By elaborating on this
view, we hope to increase the impact of future
experiments and help the new literature avoid the
mistakes and fate of the earlier literature. We do
not provide an exhaustive review of the literature,
nor do we provide detailed critiques of particular
studies. Instead, we focus on how particular examples illustrate successful use of experiments to
address important ﬁnancial accounting issues. Our
examples include and integrate experiments that
fall into both the ‘‘behavioral’’ and ‘‘experimental
economics’’ literatures in accounting.1 Although
these literatures evolved from diﬀerent traditions,
we see them as essentially similar — both use
experiments to shed light on ﬁnancial accounting
issues, and therefore, both present similar opportunities and challenges to researchers. Naturally,
our review is also deeply aﬀected by our own biases and the ﬁnancial accounting issues that we
have been addressing in our own recent research.
In Section 2, we describe in more detail how
changes in views of market eﬃciency, reliance on
the experimentalist’s comparative advantage, new
theories, and a focus on key institutional features
have allowed recent experiments in ﬁnancial
accounting to overcome the criticisms of the earlier literature. In Section 3, we describe how speciﬁc streams of experimental ﬁnancial accounting
research have addressed questions about ﬁnancial
communication between managers, auditors,
information intermediaries, and investors, and
indicate how future research can extend those
streams. We focus particularly on (1) how managers and auditors report information; (2) how
users of ﬁnancial information interpret those
reports; (3) how individual decisions aﬀect market
behavior; and (4) how strategic interactions
between information reporters and users can aﬀect
market outcomes. While we address studies of
auditors in their ﬁnancial reporting role, to limit
the scope of the review, we do not address issues
related to the demand for and conduct of auditing.
We also do not address studies of creditors’ decisions, which have received little attention in recent
ﬁnancial accounting experiments.
In Section 4, we discuss how experiments can be
designed to be both eﬀective and eﬃcient. We use
the ‘‘predictive validity framework’’ (Libby, 1981;
Runkel & McGrath, 1972) to structure our discussion of maximizing eﬀectiveness through careful
hypothesis development and research design. Our
discussion of eﬃciency focuses on the consumption
of scarce resources, such as subjects and compensation to those subjects. We conclude in Section 5
with a brief summary of our main points.
1
See Haynes and Kachelmeier (1998) and Moser (1998) for
recent discussions of the integration of the behavioral and economic approaches to experimentation.
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
2. Factors aﬀecting the supply and demand for
experimental ﬁnancial accounting research
In this section, we examine four interdependent
factors that have mitigated concerns raised about
the earlier experimental literature and promoted
recent progress in experimental ﬁnancial accounting
research: changing views of market eﬃciency,
recognition of the strengths and weaknesses of
experimental methods in addressing ﬁnancial
accounting questions, the availability of new theoretical bases for the research, and a more detailed
view of the institutional features of ﬁnancial
accounting settings. We discuss each of these factors
in turn.
2.1. Changing views of market eﬃciency
Much of the ﬁnancial accounting research in the
1960s implicitly assumed that some investors’ failure to adjust fully for the eﬀects of accounting
method choices would aﬀect allocation of resources in the economy and disadvantage these less
sophisticated investors in their exchanges with
more sophisticated investors (see Maines, 1995 for
a review). A series of papers in ﬁnance (particularly
Fama, 1970) persuaded many accounting researchers that if just a small fraction of investors are
sophisticated enough to respond appropriately to
accounting information, they will compete among
themselves to set security prices equal to their
expected values. As a result, the market becomes a
‘‘fair game’’ in which even unsophisticated investors are protected by the informational eﬃciency
of prices.2 This research led Gonedes and Dopuch
(1974), among others, to argue that experimental
research on individual behavior could have only
limited importance for ﬁnancial accounting.
In the late 1980s and 1990s, however, numerous
studies reported market ineﬃciencies.3 One line of
research provides direct support for the assumptions
underlying early ﬁnancial accounting research:
accounting policies aﬀect pricing, even when they
2
Watts and Zimmerman (1986) also provided particularly
inﬂuential arguments.
3
See Fama (1998), Kothari (2000), and Thaler (1999) for
more comprehensive reviews of this literature.
777
have no true economic eﬀects (e.g. Andrade, 1999;
Hand, 1990; Sloan, 1996; Vincent, 1997). Another
line of research indicates more generally that fundamental analysis of public ﬁnancial statement
information can lead to higher stock returns (e.g.
Frankel & Lee, 1998; Lee, Myers, & Swaminathan, 1999; Ou & Penman, 1989). A third line of
research suggests that even sell-side analysts —
generally recognized as among the most sophisticated users of ﬁnancial statements — are predictably biased (DeBondt & Thaler, 1990; Dechow
& Sloan, 1997; La Porta, 1996).
The best-known lines of eﬃciency research focus
on momentum in earnings and prices. A voluminous literature on post-earnings-announcement
drift shows that markets underreact to large earnings surprises (Ball & Bartov, 1996; Bernard &
Thomas, 1989, 1990; Bhushan, 1994; Brown & Han,
2000; Foster, Olsen, & Shevlin, 1984). Another literature, primarily published in ﬁnance journals,
shows that after adjusting for risk, stock returns
are positively autocorrelated over periods of several months (e.g. Chan, Jegadeesh, & Lakonishok,
1996), but negatively autocorrelated over periods
of several years (DeBondt & Thaler, 1985, 1987).
The literature on market ineﬃciency is controversial, and many of the papers alleging ineﬃciency have been criticized on methodological
grounds (Ball, 1992; Fama, 1998; Kothari, 2000).
Nevertheless, many researchers now doubt whether markets satisfy the requirements of the semistrong form of the eﬃcient markets hypothesis
(that markets respond eﬃciently to all publicly
available information), or even the weak form
(that markets respond eﬃciently to information
contained in past market prices). Even some of the
most skeptical seem to be convinced that postearnings-announcement drift is not simply an
artifact of research design (Ball, 1992). Recent
research on eﬃciency has also led theorists to
examine how the assumptions underlying the eﬃcient markets hypothesis might be relaxed to
account for archival results. (We discuss these
models more in Section 2.3). As a result, experimental researchers can more easily argue that
individual behavior can be an important element
in determining market behavior, even in the presence of competitive forces.
778
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
2.3. Theoretical advances in psychology, ﬁnance,
and economics
experiments in ﬁnancial accounting can rely on
well-developed psychological theories of judgment
and decision making4 that were in their infancy
when the studies reviewed by Gonedes and Dopuch
(1974) were conducted. Recent research can also
rely on economic models that describe more carefully when and how equilibrium outcomes arise.
The major idea underlying much research on
judgment and decision making is that decision
makers are boundedly rational (Simon, 1957).
Decision makers often have limited information
on which to base their judgments and decisions,
limited ability to retain and retrieve that information from memory, limited ability to process and
use that information, and limited insight into their
own decision processes and future preferences.
Studies over the last 25 years have focused on how
various attributes of human cognition determine
exactly what humans do well and what they do
poorly. A number of their ﬁndings have inﬂuenced
recent thinking in ﬁnancial accounting and the
study of ﬁnancial markets.
Many decision-making studies emphasize the
role of heuristics (Tversky & Kahneman, 1974).
Heuristics are simpliﬁed decision rules developed
to deal with complex situations. These heuristics
are eﬃcient and often work well. But in some circumstances they may lead to systematic biases
such as over- and under-conﬁdence in judgment
(Griﬃn & Tversky, 1992) and misperceptions of
the covariation between signals and events (Lipe,
1991), which can systematically aﬀect the manner
in which individuals react to ﬁnancial accounting
information and the manner in which that information is impounded in prices. Learning to overcome biases is diﬃcult because of the uncertainty
and poor feedback inherent in complex environments. Often what we learn from experience is not
valid (Einhorn, 1980).
The importance of (imperfect) storage and
retrieval of information from memory has also
been recognized in recent ﬁnancial accounting
experiments. Some of these studies rely on models
Earlier experimental research was criticized for
the lack of psychological or economic theory that
speciﬁed the mechanisms through which eﬀects of
accounting disclosures would occur. Recent
4
Syntheses of the key constructs or ideas that drive psychological theories of judgment and decision making have been
provided by Carroll and Johnson (1990), Hogarth (1993),
Bazerman (1998), and others.
2.2. The comparative advantage of ﬁnancial
accounting experiments
Earlier ﬁnancial accounting experiments typically
sought to determine whether speciﬁc accounting
policy choices would aﬀect investors’ decisions.
Answers to such research questions call for estimates of the magnitude of an eﬀect (or error) by
representative actors in representative circumstances, a task ill suited to experiments. Such a
task is more appropriate for archival-empirical
research, which examines large representative
samples of naturally occurring phenomena.
More recent experimental research strives to use
experimentalists’ comparative advantage to focus
on disentangling the eﬀects of variables that are
confounded in natural settings and determining
under what circumstances and through which
processes speciﬁc phenomena arise. Experiments
are well suited to this task because they construct
their own research setting. In a constructed
research setting, one can manipulate the independent variables, control for other potentially inﬂuential variables by holding them constant or
through randomisation, and measure the intervening processes (such as information search or
the path players take to equilibrium outcomes in
strategic settings) and mental states (such as
knowledge, beliefs, or conﬁdence) that aﬀect ﬁnal
outcomes. This allows an experimentalist to disentangle the eﬀects of variables that are confounded in the environment to draw strong causal
inferences, and to test the eﬀects of conditions that
do not yet exist or do not exist in suﬃcient quantity in the natural environment (Libby & Luft,
1993). Experiments testing how and why (rather
than whether or not) ﬁnancial accounting phenomena occur can be based on theories of psychological, economic or institutional processes.
We discuss these theories next.
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
of memory organization (e.g. Smith & Medin,
1981) that indicate how knowledgeable decision
makers eﬃciently organize and retrieve data.
Other studies recognize that memory for events is
inﬂuenced by factors that are normatively relevant, such as their frequency of occurrence, and
factors that are normatively irrelevant, such as
primacy, recency, and contrast eﬀects (e.g.
Hogarth & Einhorn, 1992). Still others recognize
that the limited capacity of working memory
aﬀects our ability to consider multiple factors in
making a judgment or choice. Consequently, even
normatively relevant factors that decision makers
are aware of often have limited inﬂuence on their
judgments and decisions.
Recent research in accounting and ﬁnance also
relies on psychological models of risk (e.g. Kahneman & Tversky, 1979) and ambiguity (e.g. Einhorn
& Hogarth, 1986) that characterize individuals’
responses to risk and reward in ways that deviate
from standard expected utility theory.5 This more
recent psychology literature provides greater ability to predict under what circumstances behavior
will be more or less likely to diﬀer from the predictions of standard economic theory (e.g. in
earnings predictions versus trading behavior, in
diﬀerent information environments). A large literature on social psychology could also be used to
understand interaction between participants in
ﬁnancial accounting settings. For example, research
related to accountability (e.g. Tetlock, 1992),
motivated reasoning (e.g. Kunda, 1990) and group
decision processes (e.g. Yetton & Bottger, 1982)
has signiﬁcantly inﬂuenced auditing studies.
Other ﬁnancial accounting studies use advances
in ﬁnancial economics to test the assertion that
biased traders will be driven out of the market
through systematic trading losses. Some of these
models focus on how biases might inﬂuence market outcomes. For example, Barberis, Shleifer, and
Vishny (1998) use psychological models of how
people perceive random-walk sequences in a
model with a representative investor. Daniel,
Hirshleifer, and Subrahmanyam (1998), Gervais
and Odean (1997) and Odean (1998) incorporate
5
See Hodder, Koonce, and McAnally (2001) for further
discussion of risk in ﬁnancial accounting settings.
779
overconﬁdence into trading models. Other models
focus on forces that keep unbiased traders from
exploiting price errors. For example, De Long,
Shleifer, Summers, and Waldmann (1991) show
that traders who respond irrationally to irrelevant
information (‘‘sentiment’’) create enough noise in
prices to keep rational traders from exploiting the
resulting price errors. Fischer and Verrecchia
(1999) and Kyle and Wang (1997) show that
overconﬁdence, although irrational, can actually
give traders higher payoﬀs than their rational
compatriots. These results make it diﬃcult to
argue that some form of natural selection will
eliminate irrational traders in dynamic equilibria,
and provide accounting researchers with speciﬁc
models of how and when individual biases might
inﬂuence market prices.
Experiments focusing on game theoretic models
of ﬁnancial accounting settings can now rely on
new economic models that move beyond the traditional equilibrium view. Rather than simply
identifying an equilibrium and assuming that it
will occur, many economists have examined in
detail what assumptions about rationality must be
satisﬁed for equilibria to have predictive power
(Bernheim, 1984; Pearce, 1984; Tan & Werlang,
1988). Other models have examined the process by
which equilibria are achieved, using either psychological theories based on behaviorism (Herrnstein & Vaughn, 1980) or evolutionary theories of
natural selection (Maynard Smith, 1982). In a similar vein, Gode and Sunder (1993, 1997) used such
ideas to show that ‘‘zero-intelligence’’ traders, who
do nothing more than avoid obviously horrible
strategies, can achieve eﬃcient security allocations
in some markets. By focusing on processes by
which equilibria are achieved, these studies provide
indications of when equilibria will and will not
predict behavior in ﬁnancial accounting settings.
2.4. Key institutional features of ﬁnancial
accounting settings
Most early experimental studies in ﬁnancial
accounting took relatively narrow views of ﬁnancial accounting institutions. They typically focused
on the set of rules governing how accounting information could be reported in ﬁnancial statements,
780
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
implicitly assuming that reporting choices (and
interpretations of those choices) were made neutrally, rather than being inﬂuenced by the incentives of a strategic manager or auditor. Early
studies also implicitly assumed that responses to
ﬁnancial accounting information would be independent of the expertise or incentives of the user,
and that interactions among users and reporters
would not alter outcomes.
Consistent with the advice of Libby and Luft
(1993), recent experimental research in ﬁnancial
accounting has considered institutional features
more broadly, and has also focused on the interaction between individual and environmental
characteristics. Two key individual characteristics
are the knowledge and motivation of information
reporters and users. These determine the parties’
goals, and how they use ﬁnancial accounting to
achieve those goals. Key environmental characteristics include the complex regulations governing reporting, the existence of ﬁnancial markets,
and the strategic interactions between reporters
and users, as well as between diﬀerent sets of
users. Regulations determine the set of choices
open to managers and auditors, and may also
determine the results of those actions (e.g. lawsuit
outcomes). Financial markets aﬀect how individual decisions result in aggregate market outcomes, such as stock prices, liquidity and trading
volume, and may also determine wealth transfers
among diﬀerent sets of investors. Strategic interactions capture the intertwining of the incentives
and actions of the many parties to ﬁnancial
accounting decisions. Financial accounting settings include managers, auditors, investors and
information intermediaries (analysts and the
press) who may all interact strategically. Managers and auditors negotiate to determine the
contents of the ﬁnancial statement and audit
report. Investors draw inferences about managers’
and analysts’ information and incentives from
observing reports. Managers may choose reports
in an attempt to ‘‘fool’’ investors, but the investors
may be able to anticipate these attempts.6
6
Financial accounting information is also used for contracting and stewardship purposes, but that has not been the
focus of signiﬁcant experimental research.
Focusing explicitly on individual and environmental characteristics allows experimental
researchers to shed light on how and when
experimental results will generalize to target settings, and also indicate how variations in these
institutions will alter behavior. In this way, an
institutional focus helps researchers to exploit the
comparative advantage of experimentation. In the
next section, we describe how speciﬁc streams of
experimental ﬁnancial accounting research have
done so, and indicate how future research could
extend those streams.
3. Key ﬁnancial accounting questions and
experimental evidence
The goals of the literature that we review are
similar to those of the broader ﬁnancial accounting literature: to increase our understanding of the
ﬁnancial reporting process and its eﬀects. While all
of the studies that we examine share the same
general goal, they focus on diﬀerent elements of
the interactions of boundedly rational managers,
auditors, information intermediaries, and investors. These diﬀerences in emphasis led us to divide
the studies into four related categories described
by the following questions.
1. How do managers’ and auditors’ incentives
and ﬁnancial accounting regulations determine how they report events?
2. How do knowledge of accounting regulations, managers’ incentives, and the information content of accounting reports aﬀect
users’ (investors and information intermediaries) interpretations of accounting
reports?
3. How do individual responses to information
aﬀect market-level phenomena?
4. How do strategic interactions between
reporters and users of information aﬀect
reporting and market outcomes?
We focus primarily on papers published since
the publication of Maines’s (1995) review of this
literature.
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
3.1. How do managers’ and auditors’ incentives
and ﬁnancial accounting regulations determine how
they report events?
Reporting performance is fundamental to ﬁnancial accounting. Discretion provided by ﬁnancial
accounting regulations, coupled with the inherent
subjectivity of much accounting measurement,
allows managers some ﬂexibility to opportunistically report or manage earnings. Consequently,
much archival and experimental research has
focused on this area.
Archival studies typically examine opportunistic
reporting by identifying whether earnings or
accruals diﬀer from expectation in a manner favored
by managers’ incentives (see Healy & Wahlen,
1999 for a review). While these studies have
demonstrated numerous instances of apparent
earnings management, their conclusions are sometimes criticized because of methodological diﬃculties, including poor incentive proxies, misstated
discretionary accruals models, or potential omitted variables such as operating choices that have
non-earnings-management rationales but that
aﬀect discretionary accruals (Bernard & Skinner,
1996; Dechow, Sloan, & Sweeney, 1995). Also,
archival studies of earnings management focus on
post-audit ﬁnancial statements that are a joint
product of the negotiations between managers and
auditors, which makes it diﬃcult to distinguish the
separate contributions of managers and auditors
to earnings management or to determine how
managers’ and auditors’ separate incentives inﬂuence their reporting and attesting behavior (Nelson, Elliott, & Tarpley, 2000).
Experimental studies avoid these problems by
manipulating incentives and assessing treatment
eﬀects rather than attempting to measure unexpected accruals, and by holding constant task
characteristics that create potential omitted variables problems. Experiments can examine managers’ and auditors’ judgments separately, but can
also examine auditor–client interactions. These
characteristics of experimental work have led to a
growing experimental literature that complements
the archival work in this area.
The largest group of experimental earningsmanagement studies focuses on auditors’ incentives
781
and the circumstances under which they allow
managers to take aggressive accounting positions.
Consistent with the general auditing literature (e.g.
Kinney & Martin, 1994), results indicate that auditors reduce the aggressiveness of ﬁnancial reports.
For example, Hirst (1994) provides evidence that
auditors consider management competence and
objectivity when evaluating management-provided
evidence. Phillips (1999) demonstrates that, after
auditors receive evidence of aggressive reporting in
high-risk accounts, they are more likely to attend
to it elsewhere, even in accounts they typically
consider to be of low risk. Kinney and Nelson
(1996) demonstrate a circumstance in which
auditors make audit-reporting judgments that
are as conservative as thought appropriate by
even those investors who are evaluating the
audit report in the presence of negative outcome
information.
However, other studies indicate that auditors
are more likely to allow their clients to take
aggressive accounting positions when the relevant
evidence or precedents oﬀer more room for interpretation. For example, Nelson and Kinney (1997)
provide evidence that auditors are more (less)
conservative than users required when the relevant
evidence was precise (ambiguous). Similarly, Salterio and Koonce (1997) provide evidence that
auditors’ treatment of clients’ capitalization versus
deferral decisions depends on whether the relevant
precedents unanimously favor one alternative.
When the precedents favor one alternative, auditors follow the precedents, but when the precedents are mixed, auditors tend to follow their
client’s preference. Mayhew, Schatzberg, and Sevcik (2000) provide consistent evidence in experimental markets. When participants in the role of
auditor were sure of the appropriate disclosure,
they made that disclosure, but as their uncertainty
about appropriate disclosure increased, they tended to misreport in favor of their client.
Other studies have focused on the role of speciﬁc incentives in auditors’ reporting decisions.
For example, Hackenbrack and Nelson (1996)
provide evidence that auditors are more likely to
allow their clients to take aggressive accounting
positions if the auditors’ litigation risk is reduced,
and that auditors justify the aggressive position
782
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
with aggressive interpretations of the relevant
ﬁnancial accounting regulations. Hackenbrack
and Nelson hold constant the underlying audit
evidence while varying auditors’ incentives and
whether those incentives favored accrual or footnote disclosure of a contingency, allowing them to
infer with high conﬁdence that incentives were
driving the eﬀects they observed. Using the same
case materials, Kennedy, Kleinmuntz, and Peecher
(1997) provide evidence that, even when litigation
risk is relatively high, auditors may tend to take
aggressive reporting positions when they can diffuse personal responsibility by consulting other
experts within the ﬁrm. Wilks (2001) provides evidence that auditors’ interpretations of evidence
and decisions are aﬀected by the views of more
senior auditors. Beeler and Hunton (2001) provide
evidence that incentives from lowballing or management-advisory services aﬀect audit partners’
going concern judgments. Bazerman, Morgan,
and Loewenstein (1997) suggest that auditors
cannot be independent because of the unconscious
eﬀect of such incentives, or even because of a sense
of auditor–client aﬃliation that occurs through
multiple interactions. However, Dopuch and King
(1996) provide evidence that competitive pressures
can reduce the eﬀect of incentives like lowballing,
and King (2001) provides evidence that, holding
constant economic incentives, professional–group
aﬃliation can oﬀset the inﬂuence of auditor–client aﬃliation, demonstrating that oﬀsetting
aﬃliations can have oﬀsetting eﬀects on auditors’
independence.
A smaller group of studies examines how managers’ incentives aﬀect the aggressiveness of their
reporting decisions. These studies take two
approaches. One approach is to elicit managers’
judgments directly. For example, Cloyd, Pratt,
and Stock (1996) gather data from corporate
ﬁnancial executives at both public and private
manufacturing ﬁrms. They provide evidence
that, when a manager has selected an aggressive
tax treatment, the manager tends to choose a
ﬁnancial accounting method that conforms to
the tax choice in hopes of better defending the
appropriateness of the tax choice if it is later
questioned by the IRS. Managers of public ﬁrms
were less likely to choose conformity than were
managers of private ﬁrms, presumably because
managers of public ﬁrms face more disincentives
for making income-decreasing ﬁnancial accounting
disclosures.
The second approach is to elicit the joint product of the manager–auditor negotiation indirectly
from auditors. Three diﬀerent studies use diﬀerent
versions of this approach. Libby and Kinney
(2000) manipulate factors that aﬀect managers’
incentives and ask auditors to determine how the
audited ﬁnancial statements would appear. They
provide evidence that correction of quantitatively
immaterial errors is much less likely if the correction would cause the ﬁrm to miss analysts’ EPS
forecasts (i.e. is qualitatively material), and that
the recently promulgated SAS 89 has little eﬀect
on this behavior. Gibbins, Salterio, and Webb
(2000) develop a model of auditor–client negotiation and support their model by surveying auditors concerning their experiences negotiating
contentious accounting issues with their clients.
Nelson, Elliott, and Tarpley (2000) survey auditors concerning their experiences with clients’
attempts to manage earnings, and provide evidence
concerning managers’ incentives for attempting
earnings management, the ﬁnancial accounting
areas in which managers attempt earnings management, and the circumstances under which
auditors pass or thwart managers’ attempts.
Overall, these studies provide direct evidence
that managers and auditors use the ﬂexibility
inherent in accounting rules to make disclosures
that are favored by their incentives. Holding constant amount of ﬂexibility, changes in incentives
move disclosure in the direction favored by those
incentives. Holding incentives constant, increasing
ﬂexibility increases the degree to which incentives
aﬀect decisions.
Certainly one direction for future research is to
continue examining how managers’ and auditors’
incentives aﬀect their decisions. In addition, the
literature could work more to identify the processes through which these eﬀects occur. To what
extent are these eﬀects intentional and strategic
versus the unintended results of cognitive limitations? Wilks (2001) provides evidence that incentives aﬀect decisions more when the incentives are
made apparent to subjects prior to evaluating
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
evidence, suggesting that incentive eﬀects inﬂuence
the evaluation process as well as the decisions that
result from that process. Beeler and Hunton
(2001) provide evidence that incentives aﬀect both
the favorability and weighting of evidence, and
that auditors believe that incentives aﬀect other
auditors’ judgments, but not their own. A fruitful
direction for future research is to further understand how and when such incentive eﬀects occur.
Another useful direction is to examine how
changes in regulations or other interventions
might aﬀect the aggressiveness of ﬁnancial reporting. For example, Libby and Kinney (2000), Hirst
and Hopkins (1998), and Maines and McDaniel
(2000) provide evidence of recent regulatory
changes that do not appear to prevent managers
from making aggressive reporting decisions. Cuccia, Hackenbrack, and Nelson (1995) provide
evidence in a tax context that increasing the precision of a standard does not prevent aggressive
reporting when the underlying evidence also provides latitude for interpretation. When coupled
with evidence of the eﬀect of incentives on reporting judgments, ﬁndings indicating the ineﬀectiveness of some regulatory interventions suggest that
regulators might reduce aggressiveness more
eﬀectively by addressing incentives directly via
changes in penalties. Alternatively, other approaches like improvements in audit-evidence sequencing (Phillips, 1999) or within-ﬁrm consultation
(Kennedy et al., 1998) might also aﬀect the
aggressiveness of ﬁnancial reports, by aﬀecting the
extent to which auditors discourage aggressive
reporting.
Finally, future research could focus more on the
interaction among participants in the ﬁnancial
reporting process. Researchers are only beginning
to consider the process by which auditors negotiate with their clients to produce the joint product
that investors consume. Also, the increasing role
of audit committees in this process remains largely uninvestigated. Addressing these issues via
experiments (e.g. Libby & Kinney, 2000), surveys
(e.g. Gibbins et al., 2000; Nelson, Elliot, & Tarpley, 2000), and laboratory markets (e.g. Mayhew
et al., 2000) appear to be useful directions for
future research. These issues are discussed more in
Section 3.4.
783
3.2. How do information users interpret reports,
given their knowledge of the regulations governing
those reports, and their knowledge of the reporters’
incentives?
Three streams of literature address distinct
facets of this question:
1. How do accounting methods and disclosure
alternatives aﬀect earnings predictions and
value estimates of investors and information
intermediaries?
2. How do investors and analysts use the timeseries properties of earnings to predict future
earnings?
3. What determines analysts’ forecasting and
valuation performance?
We discuss each in turn.
3.2.1. How do accounting methods and disclosure
alternatives aﬀect earnings predictions and value
estimates of investors and information intermediaries?
The earliest experimental research in ﬁnancial
accounting tended to be motivated by the need for
evidence to address speciﬁc accounting policy
debates. These studies focused on whether investors and others adjusted appropriately for the
eﬀects of accounting methods and disclosure
alternatives (e.g. Dyckman, 1964; Jensen, 1966).
Looking back on the earlier literature, it is readily
apparent that the answer to this question is
‘‘sometimes.’’ Some participants in nearly every
study of this type demonstrate some degree of
functional ﬁxation; they do not fully adjust for
diﬀerences in the eﬀects of accounting alternatives
on the bottom line (Maines, 1995, p. 90, 91). As a
consequence, ﬁrms that are in identical economic
circumstances except for their choice of accounting
alternatives are sometimes judged to be diﬀerent.
These speciﬁc policy-oriented studies did little to
tell us how the extent of functional ﬁxation will
vary across types of decision makers or economic
circumstances, or what psychological processes
underlie insuﬃcient adjustments to accounting
policies. Consistent with this concern, much
recent research has heeded the advice of Maines
(1994) to focus on the dimensions of disclosure,
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environmental factors, and processes that determine the degree to which appropriate adjustments
are made. In response to a recent call for more
speciﬁc policy-oriented experiments (Beresford,
1994), Maines (1994) noted that ‘‘Psychological and
sociological research may be most productively used
to guide behavioral accounting research on general issues that underlie many diﬀerent accounting
standards, rather than focusing on issues relevant
to only one standard.’’ Understanding the eﬀects
of these general factors will dramatically broaden
the relevance of this research.
Three groups of studies demonstrate progressive
reﬁnement in the manner in which this research
question has been addressed. The ﬁrst group
focuses on the mechanisms through which placement and classiﬁcation of accounting disclosures
aﬀect the use and interpretation of the disclosures.
The second group explicitly or implicitly recognizes that managers issuing accounting reports
have their own strategic interests and will report
opportunistically, and examines how users
respond to voluntary disclosures by managers.
The third recognizes that analysts respond to their
own strategic interests and examines how users
respond to potential relationship induced bias in
analysts’ reports. We discuss each in turn.
3.2.2. General issues underlying functional ﬁxation
The development of category structures in
memory plays a major role in allowing expert
decision makers to respond eﬀectively and eﬃciently in complex decision environments. In these
structures, attributes are associated with categories as opposed to individual instances of the
category. An individual instance or event is then
interpreted based in part on its category membership. This allows for eﬃcient and often eﬀective
processing of attributes of the environment, but
sometimes produces errors when the particular
instance does not match the typical category
attributes well. A number of recent papers have
recognized that classiﬁcation issues like the
assignment of a ﬁnancial disclosure to a particular
ﬁnancial statement, to a speciﬁc subsection within
a statement, or to the notes, will aﬀect decision
makers’ categorization of that disclosure and
interpretation of its relevance and meaning.
Existing studies have examined three dimensions
of classiﬁcation. Hopkins (1996) examined the
eﬀects of classiﬁcation of items on the right side of
the balance sheet as debt, equity, or mezzanine
ﬁnancing on judgments of the stock price eﬀects of
new ﬁnancing. He found that experienced buy-side
analysts who had knowledge of the diﬀerential
stock price eﬀect of debt and equity issuances
found in ﬁnancial economics research responded
to the issuance of hybrid securities based on their
categorization. When the securities were classiﬁed
as mezzanine, for which the analysts had no welldeﬁned category, they responded based on the
attributes of the individual security. Similarly,
Hopkins, Houston, and Peters (2000) examined
issues related to categorization of costs as operating expenses, one-time charges, or note disclosure.
Experienced buy-side analysts treated the accounting acquisition premium in a merger in part based
on its classiﬁcation. One-time charges and note
disclosures were treated as less relevant to stock
valuation than operating expenses. Finally, Hirst
and Hopkins (1998) and Maines and McDaniel
(2000) examined whether placement of elements of
comprehensive income on the income statement
versus the statement of stockholders’ equity aﬀected the ability to detect earnings management and
changes in earnings volatility. Information placed
on the income statement (the primary performance statement) was much more likely to be
treated as relevant to future performance estimates by the experienced analysts in Hirst and
Hopkins (1998) as well as by the evening MBA
students in Maines and McDaniel (2000).
Maines and McDaniel (2000) also present the
beginnings of a theory of format eﬀects. Their
theory lists ﬁve factors that aﬀect the degree to
which investors will rely on a particular disclosure
in assessments of corporate performance: placement, labeling as income, linkage (to net income),
isolation, and degree of aggregation. Such a theory holds the promise of allowing predictions of
eﬀects beyond the scope of individual studies, as
Maines (1994) recommends. Future research can
reﬁne and test the model in other circumstances.
Other studies identify the stage in the decision
process where any failure to adjust for accounting
or disclosure diﬀerences occurs. Following prior
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
credit analysis and auditing research (e.g. AbdelKhalik & El-Sheshi, 1980; Bonner, 1990), Lipe
(1998) uses a series of debrieﬁng questions to
separate the eﬀects of measurement from weighting. She examines whether investors can accurately
assess the variance and covariance of returns in
making risk assessments and whether they use
those assessments in their investment decisions.7
Maines and McDaniel (2000) use a combination
of debrieﬁng questions and regression analysis to
determine whether diﬀerences in accessing the
information cues, interpreting or measuring the
cues, or weighting the cues caused their results.
They suggest that participants in all disclosure
conditions accessed and interpreted the cues in the
same manner, but weighted them more heavily in
the income statement presentation condition.
Another set of studies uses improved theories of
functional ﬁxation to deﬁne ‘‘superior’’ disclosure
methods. Early studies only determined if diﬀerent
judgments or decisions are made and ignore the
issue of determining the superior disclosure
method. Many of the newer studies specify subtasks necessary for successful ﬁnal judgments or
decisions, such as detection of earnings management (Hirst & Hopkins, 1998), assessment of
variability in underlying ‘‘core’’ earnings (Maines
& McDaniel, 2000), or covariance assessment (Lipe,
1998). Alternatively, Maines, Mautz, Wright, Graham, Rosman, and Yardley (2000) approach the
question of assessing which disclosure method is
superior in a way similar to the training and decision aids literature in auditing. They suggest that
high quality reporting methods (1) allow novice
decision makers to perform like expert decision
makers and (2) allow the same decisions to be
made as completely disaggregated disclosures.
They apply their approach in a study of joint-venture ﬁnancial reporting standards. The approach is
consistent with the SEC and FASB’s concern for
7
She also examines how they react when market and
accounting measures conﬂict. Her study is unique at this point
in jointly examining the role of accounting and non-accounting
information. It also suggests the possibility that the weight
placed on normatively relevant information may change with
the inclusion of less-relevant information and presents a
potential explanation for the lack of diversiﬁcation of individual portfolios.
785
the naive investor, as well as eﬃciency concerns
and Hand’s (1990) suggestion of investor sophistication eﬀects as a partial explanation for market
ineﬃciencies. This study, Maines, McDaniel, and
Harris’s (1997) study of segment standards, and a
number of the above-mentioned are motivated in
part by a particular policy issue of current interest.
Again, we believe that their impact is determined
by their ability to relate the particular policy issue
of interest to more general phenomena that inform
a wider array of policy questions.
3.2.3. Responses to voluntary disclosures
The studies discussed above implicitly assume
that disclosures are generated by a neutral process.
However, managers issuing accounting reports
generally have their own strategic interests and
will report opportunistically. A number of studies
address how this strategic element aﬀects users’
decisions.
The ﬁrst two studies examine the eﬀects of the
form of disclosures. Kennedy, Mitchell, and Sefcik
(1998) examine how investors interpret the diﬀerent allowable forms of contingent environmental
liability disclosure: minimum, best estimate, maximum, or range of the distribution. Experienced
ﬁnancial executive, manager, banker, and MBA
student participants’ assessments of the distribution of possible losses implied by each disclosure
did not match the commonly accepted meaning of
the terms. For example, when the ‘‘best estimate’’
was disclosed by management, the participants
interpreted it as the minimum, and when a range
was disclosed, the participants’ estimates of the
expected value were well above the midpoint of
the range. The participants clearly believed that
managers bias their disclosures downward.8 It also
indicates that accounting information has diﬀerent
eﬀects on diﬀerent judgments, in this case, management credibility and ﬁrm value.
Hirst, Koonce, and Miller (1999) examine
investors’ interpretation of point versus range
forecasts and historic forecast accuracy on earnings
8
Participants also believed that managers that decided to
disclose the minimum were the least credible, yet they valued
their ﬁrms the most highly. This suggests that the accounting
standard provides managers with a perverse incentive to provide the least informative disclosure.
786
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forecasts and conﬁdence in forecasts (which they
relate to trading). If both of these forecast attributes indicate precision of the forecast, they both
should aﬀect forecasts and conﬁdence. However,
only prior accuracy had an eﬀect on earnings
forecasts, while both factors aﬀected conﬁdence
and trading. This again indicates that normatively
relevant attributes of accounting information may
aﬀect some judgments and decisions but not others.
Libby and Tan (1999) and Tan, Libby, and
Hunton (2000) investigate the eﬀects of earnings
warnings or preannouncements on sell-side analysts’ forecasts of future periods’ earnings. Libby
and Tan provide a demonstration of the process
through which the same disclosure can have differential eﬀects on diﬀerent judgments and decisions. They examine why analysts say in the press
that they reward ﬁrms that warn, yet punish them
in their forecasts. They demonstrate that this
inconsistency results from the simultaneous processing of the warning and earnings announcement in answers to press questions versus the
sequential processing of the same signals in the
forecasting setting. Tan, Libby, and Hunton (2000)
demonstrate that ﬁrms that low-ball preannouncements of both positive and negative earnings
surprises will receive higher forecasts for future
period’s earnings, even though the reporting managers themselves are judged as having lower
integrity and competence. Also, analysts are aware
of management’s tendency to low-ball the preannouncements, but do not adjust their estimates
of earnings of ﬁrst time preannouncers in light of
this base rate knowledge. This again indicates that
known attributes of accounting information do
not aﬀect all judgments in the same manner.
3.2.4. Responses to analyst’s forecasts
Hirst, Koonce, and Simko (1995) and Ackert,
Church, and Shehata (1997) investigate the eﬀects
of potential bias in analysts’ reports on investors’
use of those reports. MBA student subjects in
Hirst, Koonce, and Simko (1995) expected analysts whose employers also provide investment
banking services to the company to be more
biased than those that do not. However, this perceived bias only aﬀected their reliance on the report
when the report gave a negative recommendation.
Similarly, the strength of the analysts’ arguments
had an eﬀect only for negative recommendations.
Ackert, Church, and Shehata (1997) extend this
study to a multiperiod setting where subjects have
the option to acquire forecasts from analysts, and
also observe actual earnings. Individuals were
much less willing to acquire analysts’ forecasts
that proved to be biased in the past, even when the
forecast information was useful. Both studies suggest the need to better understand the processes
that determine when reports from analysts and
other information intermediaries will be purchased
and relied upon.
A general picture emerges from the above studies. First, management’s often cited (Beresford,
1994) preoccupation with the bottom line, and more
speciﬁcally with potential penalties for earnings
volatility and eﬀects of cosmetic diﬀerences,
appears at least in part well founded. Second, we
have begun to understand that placement, categorization, and labeling all play a role in the simpliﬁcations that even professional analysts apply when
evaluating accounting information. Future research
on the knowledge structures developed by experts
for diﬀerent types of companies and diﬀerent types
of ﬁnancial judgments and decisions promises to
increase our understanding of these eﬀects.
It is also clear from the above results that the
information that decision makers rely upon in
their judgments is limited, and the information
emphasized clearly changes depending on the
ﬁnancial judgment being made and other elements
of the environment. In fact, awareness of cosmetic
diﬀerences (and ability to ‘‘do the math’’) does not
ensure full consideration of their implications for
valuation. The same is true of knowledge of management’s tendency to opportunistically employ
vague reporting standards or analysts’ tendency to
bias their reports. There appear to be many cases
where the same normatively relevant factors are
ignored in one circumstance, but adequately
weighted in another by the same decision maker.
The fact that results here tie closely to archival
data gathered in prior studies adds to the credibility of the results. Future studies should focus
on systematically determining the circumstances in
which diﬀerent classes of information receive ﬁrstorder consideration.
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
Earlier research on the eﬀect of task complexity
on the use of alternative decision rules in credit
decisions (e.g. Biggs, Bedard, Gaber, & Linsmeier,
1985; Paquette & Kida, 1988; see Payne, Bettman,
& Johnson, 1992 for a review of psychological
studies) will provide some guidance in this area.
However, it appears that the determinants of which
information items receive ﬁrst order consideration
in particular judgment situations involves more
than task complexity. Findings of the importance
of cue-response compatibility (Slovic & Lichtenstein, 1968) and other task determinants of cue
usage in early judgment and decision making
research (e.g. Einhorn & Hogarth, 1981; Slovic &
Lichtenstein, 1971) may provide useful directions
for future research in this area. Furthermore, the
interplay between these factors, investor sophistication and eﬀort, and various market attributes discussed in Section 3.3 appear critical in determining
the importance of cosmetic disclosure diﬀerences.
3.2.5. How do investors and analysts use the timeseries properties of earnings to predict future
earnings?
Post-earnings-announcement drift has become a
very active stream of archival research. Bernard
and Thomas (1990) provide evidence that drift
arises because investors misperceive the time-series
of earnings. Speciﬁcally, quarterly earnings follow a
Brown–Rozeﬀ model, which has two key elements.
One element is the autoregressive component —
changes from one quarter of one year to the same
quarter of the next tend to be positively autocorrelated. The other element is the ‘‘moving
average’’ component — the diﬀerences between
actual and predicted earnings tend to be negatively
correlated from one quarter to the same quarter of
the next year. Research by Bernard and Thomas
(1990) and Ball and Bartov (1996) indicate that
investors underestimate both the autoregressive
and moving-average components of quarterly
earnings; results from Abarbanell and Bernard
(1992) indicate that analysts make a similar mistake.
Recent studies have used the advantages of the
experimental approach to understand the psychological nature of investors’ and analysts’ time-series prediction errors. Calegari and Fargher (1997)
provides a logical starting point — they attempt to
787
replicate drift in the laboratory, using experimental controls to rule out the possibility that
prediction errors are driven by factors other than
judgment errors.9 Just as archival studies focus
only on ﬁrms with extreme earnings surprises,
Calegari and Fargher use time series that exhibit
unusually large earnings changes in the most
recent quarter. Their results are largely consistent
with archival research — both individual traders
and market prices underreact to earnings surprises.
Maines and Hand (1996) extend this ﬁnding in
two ways. First, they present MBA students with
two diﬀerent 40-quarter time-series. One series has
strong autoregressive and moving-average components. Another is simply a seasonal random
walk with no such components. Subjects underreact to both elements when they are present, but
also act as if the autoregressive element is present
when it is not. This suggests that drift may arise in
the target environment simply because it is too
diﬃcult for investors to discern the autoregressive
and moving average terms. Drift may therefore be
less severe for ﬁrms that adhere more closely to a
seasonal random walk. Second, Maines and Hand
directly test Bernard’s (1993) hypothesis that
investors anchor too strongly on earnings from the
same quarter of the previous year, perhaps
because it is stressed in the reporting format used
in the popular press. Maines and Hand test this
supposition by presenting a new set of subjects
with a Brown–Rozeﬀ time-series, and reporting
earnings relative to earnings from four quarters
ago. The results raise doubts about Bernard and
Thomas’s (1990) hypothesis, because these subjects place even more weight on the autoregressive
component of the time series. These results suggest
the need to test for alternative causes.
Bloomﬁeld, Libby, and Nelson (2000a) argue
that drift may arise because people naturally overrely on unreliable information (Bloomﬁeld, Libby,
& Nelson, 2000b; Griﬃn & Tversky, 1992), and
old earnings numbers tend to be unreliable predictors of future earnings, once more current
9
For example, investors and analysts could appear to make
prediction errors in archival studies because they respond to
information other than earnings, because they have incentives
for something other than prediction accuracy, or because they
are attempting to manage risk.
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R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
earnings are known. They test this hypothesis by
manipulating information about old earnings performance, holding recent earnings performance
constant. Student subjects rely much too heavily
on old earnings numbers, and generate errors
consistent with post-earnings-announcement drift,
even when they are presented with a time series
that is much simpler than that used in other
experiments. This suggests that drift may not arise
merely because the time-series properties of earnings are so complex.
Future research in time-series perceptions might
follow several directions. One direction is to integrate the diﬀerent research approaches described
above. The realistic time-series used by Calegari
and Fargher (1997) and Maines and Hand (1996)
allow them to generalize their results readily to
archival settings, but make it diﬃcult for them to
ascertain how aspects of the time-series data
interact with psychological processes to cause
prediction errors. The simpler time-series data
used in Bloomﬁeld, Libby, and Nelson (2000a)
poses precisely the opposite problem. Future
research might attempt to work toward the middle
of these two approaches, either by using timeseries that are progressively simpler than in the
former studies, or progressively more complex
than in the latter study.
Future research might also investigate the model
of Barberis, Shleifer, and Vishny (1998). That
model assumes that earnings follow a random
walk, but that investors believe that earnings
switch between regimes of positive autocorrelation
and regimes of negative autocorrelation. This
misperception results in both underreactions to
recent earnings changes and overreactions to longterm trends. While such misperceptions are broadly
consistent with psychological ﬁndings indicating
representativeness and conservatism biases, no
single study supports its assumptions, and their
predictions are not entirely consistent with archival evidence (e.g. Lee and Swaminathan, 2000).
Finally, future studies might attempt to integrate research on time-series predictions with
other research streams that consider earnings prediction more broadly. For example, how might
knowledge of earnings components (accruals, cash
ﬂows) alter subjects’ time-series predictions?
3.2.6. What personal and process attributes
determine analysts’ forecasting and valuation
performance?
As Maines (1995) notes, a number of studies in
the 1970s and 1980s examined the manner in
which expert and novice analysts process
accounting information (e.g. Mear & Firth, 1987;
Pankoﬀ & Virgil, 1970; Slovic, Fleissner, & Bauman, 1972; Wright, 1977). The studies assessed
various characteristics of information search, cue
weighting, judgment consistency and consensus,
and self-insight into information processing. A
number of the more recent studies in this group
used detailed process tracing techniques in an
attempt to tie individual or process attributes to
judgment accuracy (e.g. Anderson, 1988; Biggs,
1984; Bouwman, 1984). However, most studies
were only able to relate process attributes to
experience because of subject sample constraints
or diﬃculty in measuring judgment performance.
These earlier experiments also did not focus on the
eﬀects of analysts’ incentives, which have received
a great deal of attention in recent archival studies.
Three recent studies have added substantially to
our understanding of the relationship of personal
and process variables to forecast accuracy as well
as the impact of relationship incentives on bias in
forecasts. Hunton and McEwen (1997) emphasize
both process measurement and disentangling
variables that are confounded in natural settings.
They address whether sell-side analysts’ search
strategies and incentives (in the form of their relationship to the company) aﬀected the accuracy
and bias of their earnings forecasts. Information
search strategy was assessed with an eye movement measurement system that eliminates most
concerns about the reactivity and validity of verbal protocols. The authors measured the accuracy
of the forecasts made in the experiment as well as
historical accuracy from company archives, which
assures external validity. Analysts that followed a
more directed (as opposed to sequential) search
strategies were more accurate both in the experimental task and in practice. The analysts in the
underwriting condition gave higher (more biased)
forecasts than those in the following condition,
which were higher than those in the no relationship condition. Careful use of controls eliminates
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
concerns about omitted variables such as information availability, time on task, and some forms of
selection that could have explained similar ﬁndings
in archival studies (see Kothari, 2000 for a review).
Few studies have examined the knowledge and
abilities that lead to successful performance by
analysts. Ghosh and Whitecotton (1997) present
evidence that two standard psychometric measures
of information processing ability (perceptual ability and tolerance for ambiguity) were correlated
with forecast accuracy. But, as in Hunton and
McEwen (1997), experience was unrelated to
accuracy. However, Whitecotton (1996) reports
that experienced analysts outperformed MBA
students, who outperformed undergraduate students, though the experienced analysts were the
most over optimistic.
Like similar work in auditing, these ﬁndings are
potentially relevant to the selection and training of
analysts, as well as the interpretation of their
forecasts and reports. Again, the fact that results
here tie closely to archival data, gathered either in
the same study in the case of Hunton and McEwen’s (1997) accuracy measures, or in prior studies
in the case of their incentives ﬁndings, adds to the
credibility of the results. Recent archival studies
by Mikhail, Walther, and Willis (1997), Clement
(1999), and Jacob, Lys, and Neale (1999) have
documented diﬀerences in the experiences of more
and less accurate analysts that may indicate directions for future research. In the auditing literature,
expertise studies have reﬁned such ﬁndings in studies
that specify the knowledge necessary to complete
various tasks, when it is acquired, and the
mechanisms through which knowledge content and
structure aﬀect performance. These studies can
provide guidance for future ﬁnancial accounting
research in this area. Other recent work has begun
to look at how these individual responses aﬀect
market-level performance and the characteristics
of markets that will aﬀect information dissemination. This research is discussed in the next section.
3.3. How do individual responses to information
aﬀect market-level phenomena?
Early experimental research in ﬁnancial accounting implicitly assumed that individual behavior
789
would aﬀect market-level prices in some straightforward manner (e.g. the price might be simply the
average of all investors’ beliefs), and that some
investors would lose money to more sophisticated
investors by trading unwisely at market prices.
Counter-arguments by proponents of the eﬃcient
markets hypothesis have led many experimental
researchers to make these assumptions explicit and
subject them to testing. We divide this literature
into three lines: those that address diﬀerences
between individual and aggregate behavior, information aggregation, and excess trading volume.
3.3.1. Diﬀerences between individual and
aggregate behavior
A number of papers examine whether or not
individual responses to information extend to the
market level. Two papers examine whether individual responses to risk extend to the market level.
Coller (1996) shows that both individual traders
and market prices respond to uncertainty in public
disclosures in a manner roughly consistent with
Bayesian rationality. Bloomﬁeld and Wilks (2000)
show that, consistent with theoretical and archival
work on disclosure, more accurate disclosures
increase individual and market prices relative to
expected values, and also increase individual and
market liquidity. A larger number of papers show
that biases in individual decisions result in biased
market prices as well. For example, Calegari and
Fargher (1997) show that post-earnings-announcement drift persists in a double auction market, and
Bloomﬁeld, Libby, and Nelson (2000a) show that
over-reliance on previous years’ earnings persists
in a clearinghouse market. Tuttle, Coller, and
Burton (1997) show that recency eﬀects extend to
the market level.
Dietrich, Kachelmeier, Kleinmuntz, and Linsmeier (2000) conduct a study closely related to the
functional ﬁxation (e.g. Hopkins, 1996) and voluntary disclosure (e.g. Kennedy et al., 1998) studies
discussed in Section 3.2.1. They demonstrate that
more explicit disclosure of accounting information
about oil-producing properties leads to more eﬃcient market prices even though the same information can be inferred from the balance sheet and
income statement. Diﬀerent disclosure forms
either mitigate or exacerbate biases in prices. The
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R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
authors test their process explanation by tying
individual participant’s behavior to prices to
ensure that the market price results are the result
of individual information processing biases.
Other research investigates how competitive forces might allow less biased traders to have more
inﬂuence on price, and use that explanation to
guide examination of when this is more likely to
occur. Of particular interest is the ‘‘smart-trader’’
hypothesis, which states that traders who are less
susceptible to the bias trade more actively than
other traders, driving prices to unbiased levels
(Camerer, 1987, 1992). The intuition behind this
hypothesis underlies the strong-form of the eﬃcient markets hypothesis, which states that prices
will fully reﬂect information even if it is held only
by a small number of traders.
Anderson and Sunder (1995) provide evidence
that the smart-trader hypothesis might be more
predictive among professional traders than among
student traders. They compare the extent of baserate neglect in markets involving student subjects
with the bias in markets involving professional
traders. They report that price biases in markets of
professional traders exhibit less base-rate neglect
over time, while price biases in markets of students
do not. This is so even though the professional
traders’ individual value estimates do not appear
to diﬀer from the students’ estimates. This suggests
that the professional traders are able to trade in a
way that reduces bias more (or increases it less).
Bloomﬁeld, Libby, and Nelson (1996) provide
evidence favoring the smart-trader hypothesis in a
market in which security values are determined by
the answer to general business knowledge questions. Traders with more accurate answers do
indeed trade more actively than other traders.
When prices are inﬂuenced by trading volume,
prices become more accurate than the simple
average of all traders’ value estimates. (Prices are
no more accurate than average estimates when
they are not inﬂuenced by trading volume.) This
study might support the smart-trader hypothesis
more strongly than the studies above because
inaccurate traders are not biased, but merely
uninformed. It is possible that uninformed people are more likely to know that their answers
are inaccurate (and therefore trade less aggres-
sively) than biased people, because biases are
unconscious.
Kachelmeier (1996a) uses an analysis of bids
and asks to show the diﬃculty in determining
exactly how markets can debias prices. He induces
a sunk-cost fallacy that signiﬁcantly increases sellers’ asking prices and buyers’ bidding prices.
However, these biases have no eﬀect on transaction prices, because the higher bids and asks cause
more trades to take place at the bids, which keeps
prices low.
Other recent studies show that market structure
can be important in determining when the smarttrader hypothesis is likely to be supported.
Ganguly, Kagel, and Moser (1994) present student
subjects with a problem that leads to base-rate
neglect. They ﬁnd that, because traders are not
allowed to sell shares they do not own (short-selling is prohibited), market prices are set by the
traders with the highest valuation. As a result,
market prices exhibit base-rate neglect most
strongly (weakly) when the biased prices are
higher (lower) than the Bayesian expected values.
Bloomﬁeld and Wilks (2000) ﬁnd strong individual evidence of an ‘‘endowment’’ eﬀect — inconsistent with Bayesian optimization, traders choose
higher ask (selling) prices for riskier securities,
even as they simultaneously enter lower bid (buying) prices. However, higher risk does not cause
the market ask price to rise. This form of irrationality at the individual level is eliminated at the
market level because the market ask is determined
by the lowest individual ask. The market ask,
therefore, reﬂects the selling price of the investor
who succumbs least to the endowment eﬀect. In
this way, the structure of the market combines
with the nature of the bias to mitigate the bias at
the market level.
Future research could examine the foundations
of the smart-trader hypothesis more directly. In
particular, what factors might induce less-biased
traders to exploit biases, or keep them from doing
so? What factors might make more-biased traders
curtail their trading activity? How might changes
in market structure, or the degree of market depth
and liquidity, aﬀect bias mitigation? (Archival
studies routinely show larger biases in less liquid
stocks.) Future research could also examine how
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
the nature of ﬁnancial accounting information will
aﬀect the diﬀerence between individual and
aggregate behavior. To the extent that information induces biases, rather than degrees of
informedness that diﬀer across traders, prices
would seem more likely to represent an average of
all traders’ beliefs.
3.3.2. Information aggregation and underreaction
A diﬀerent stream of research examines the
ability of ﬁnancial markets to aggregate information held by diﬀerent traders. Like studies of the
smart-trader hypothesis, aggregation studies are
motivated by the belief that traders who know a
security value does not reﬂect their own information will trade aggressively to exploit that fact,
thereby revealing their information to the market.
Early studies on information aggregation
showed that markets do often aggregate information. They do so most eﬀectively when security
values are tied to states of nature in very simple
ways (O’Brien & Srivastava, 1991; Plott & Sunder,
1988), and when experienced traders have common knowledge regarding the information environment (Forsythe & Lundholm, 1990).
More recent studies have examined how uncertainty aﬀects information aggregation. In a series
of double-auction markets, Lundholm (1991)
manipulates the ‘‘aggregate uncertainty’’ that
remains after combining investors’ information
about security value. He ﬁnds that markets with
aggregate uncertainty aggregate information much
less eﬃciently than those with aggregate certainty.
Imperfect aggregation can lead markets to underreact to information, because prices will be too
high when the aggregate information indicates a
very low value, and too low when the aggregate
information indicates a very high value. Bloomﬁeld (1996a, 1996b) shows a similar type of
underreaction in a setting which allows aggregate
certainty, but in which the information structure is
suﬃciently complex that information aggregation
is still very diﬃcult.
Other papers show that market prices can even
underreact to public information that need not be
aggregated. Gillette, Stevens, Watts and Williams
(1999) construct a market in which security values
are determined by a sequence of random dividends.
791
The authors analyze the market’s reactions as the
dividends are announced publicly one-by-one.
They ﬁnd that the individual traders’ estimates of
value underreact slightly to the dividend announcements, possibly because they erroneously believe
that random events tend to reverse over time (the
‘‘gambler’s fallacy’’). More interesting is the fact
that market prices underreact substantially more
than individual value estimates. The reason for
this sluggishness in market prices is not clear, but
the authors replicate it in both double-auctions
and call markets. Bloomﬁeld, Libby, and Nelson
(2000b) also observe a similar eﬀect in clearinghouse markets. Bloomﬁeld (1996a) shows that
markets react to a public signal when it is subject
to manipulation by a self-interested seller, but not
when the signal is purely random. These results
raise the possibility that post-earnings-announcement drift and underreactions to other information (e.g. fundamental values, analysts’ estimates)
may arise simply due to a generic underreaction of
market prices to information, rather than information-speciﬁc biases.
Several future directions for research in this area
entail making endogenous the distribution of
information among subjects. All of the aggregation studies described above manipulate information distribution by exogenously altering who is
given information and who is not. Future studies
might relax this assumption by recognizing that
collection of information is an intentional action
that is driven in part by the perceived beneﬁt of
becoming informed, as in Tucker (1997). Alternatively, one might recognize that some information may be eﬀectively widely distributed because
it is more easily analyzed. For example, Sloan’s
(1996) archival evidence that prices are too high
(low) when ﬁrms have high (low) accruals might
simply reﬂect an underreaction to ﬁnancial statement information that is not widely known. This
result is consistent with Bloomﬁeld and Libby’s
(1996) ﬁnding that laboratory markets respond
more strongly to information that is more widely
available. However, a more direct test of this
hypothesis would be to give all traders the same
information (e.g. a complete ﬁnancial statement),
and vary the ease with which the information can
be analyzed (as in Dietrich et al., 2000), as well as
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R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
the traders’ knowledge and training that would
help with such analysis.
More generally, researchers might start with the
features we argue are essential for progress in
functional ﬁxation research — explicitly understanding how people process and interpret the
information in ﬁnancial statements, and then considering how diﬀerences in that processing might
alter market behavior.
3.3.3. Trading volume
A third line of research examines the determinants of trading volume in laboratory markets.
Many of these studies are motivated by a generalization of the ‘‘no-trade’’ theorem (Milgrom &
Stokey, 1982), which shows that under fairly general conditions, information releases should not
induce any trading between traders. The intuition
is that if one trader expects to make money trading at a given price, the trader on the other side of
the transaction must expect to lose money (since
trading is a zero-sum game).
Gillette et al. (1999) ﬁnd routine violations of
the no-trade theorem: trading volume is generally
quite high, and is even higher after very high or
low dividend announcements. These results are
consistent with archival evidence on trading
volume (e.g. Bamber, 1987; Bamber, Barron, &
Stober, 1997), which have generated a number of
theoretical models that generate trade through
complex interactions between public and private
information (e.g. Kim & Verrecchia, 1994). However, the simplicity of the market in Gillette et al.
(1999) makes such explanations unlikely.
Excess trading is a puzzle in Gillette et al.
(1999), but it has few welfare implications because
all traders are identical, and therefore wealth
transfers can be ignored (or are at best impossible
to interpret). Bloomﬁeld, Libby, and Nelson
(1999) examine excess trading that has very clear
welfare implications. They create markets in which
less-informed traders hold a subset of the information available to better-informed traders. Lessinformed traders unwisely trade with — and lose
money to — the more-informed traders. However,
additional instructions that clarify to lessinformed investors the extent of their informational disadvantages reduce these wealth transfers
(although it has no apparent eﬀect on price biases). These results have regulatory implications:
less sophisticated individual investors (who have
less information than more sophisticated individuals or institutional investors) can be protected
by regulations that emphasize the extent of their
informational disadvantage.
There appear to be a number of open questions
related to trading volume. Archival papers have
examined volume in response to earnings
announcements, or tie volume to pricing anomalies (Lee & Swaminathan, 2000; Swaminathan &
Lee, 2000). These ﬁndings may be caused by factors indicated in economic models (e.g. Kim &
Verrecchia, 1994) or by psychological factors. The
literature on motivated reasoning seems particularly promising, because it examines how initial
variations in beliefs and preferences can be magniﬁed by ambiguous public disclosures of information (Wilks, 2001).
3.4. How do strategic interactions between
reporters and users of information aﬀect reporting
and market outcomes?
Game theory has been exceptionally useful in
modeling the strategic interactions between sellers
(who can make reports about their value) and
buyers who rely on those reports in making their
trading decisions. These models potentially have
regulatory implications, because they show that
seemingly reasonable regulations may be unnecessary or unwise when one considers the joint
response of buyers and sellers to the regulation.
The models are very diﬃcult to test with archival
methods, because their predictions are derived in
settings that are far simpler than natural markets.
However, a number of experimental researchers
have chosen to examine behavior in settings that
closely resemble those described in the models. In
this section, we brieﬂy review some of these
experiments.
One line of research examines voluntary disclosure models, in which sellers choose between
honestly disclosing the exact value of the security
they are selling, and not disclosing anything at all.
Two papers by King and Wallin ﬁnd strong support for the qualitative predictions of the models
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
of Jung and Kwon (1988), and Wagenhofer
(1990). King and Wallin (1991b) ﬁnd that increasing the probability that the seller is informed leads
sellers to disclose more often, and also leads buyers
to draw more unfavorable inferences when they do
not observe disclosure (making disclosure a wise
strategy for sellers). King and Wallin (1995) show
that disclosure is also limited by introducing a cost
to disclosing favorable information (a competitor
who will take advantage of favorable disclosures
to enter the seller’s product market), because even
high-value ﬁrms might choose not to disclose. In
both cases, however, results deviate substantially
from the point predictions of the models.
Forsythe, Lundholm, and Reitz (1999) show
how disclosure regulations aﬀect the welfare of
buyers and sellers in a simple market with voluntary disclosure. When sellers are not permitted to
disclose their information about value, many surplus-enhancing transactions do not occur, and
both buyers and sellers suﬀer. Allowing sellers to
disclose any value (even a false one) increases
market surplus, but these gains accrue almost
entirely to the sellers. Requiring sellers’ reports to
include the true value shifts part of this surplus
from the sellers to the buyers.
King (1996) examines whether disclosure patterns change when sellers have an opportunity to
develop reputations. He permits sellers to report
any value they wish, but imposes a cost on buyers
when the seller’s report is inaccurate. This setting
includes two equilibria. In an ‘‘inﬂation’’ equilibrium, sellers always report the highest value, and
buyers pay expected value net of the cost of inaccuracy. In a ‘‘reputation’’ equilibrium, the seller
reports honestly, and the buyers believe the reports
until the seller reports dishonestly; at that point,
the players revert to the inﬂation equilibrium.
King ﬁnds that an exogenous cost for inaccuracy
does permit reputation formation, but that the
reputation equilibrium arises only in a few cases.
There are several natural directions for research
in strategic disclosure. There is certainly no shortage of new disclosure models to test. However, it is
probably more important for researchers to begin
to delve into how and why various equilibria do
and do not have predictive power. Some researchers have begun doing so by asking whether
793
‘‘adaptive’’ strategies (doing more of strategies
that performed better in the past) lead to a given
equilibrium. For example, King and Wallin (1995)
ﬁnd little support for an ‘‘adaptively unstable’’
equilibrium that is not the end result of adaptive
behavior. Other researchers focus more directly on
the players’ thought processes. For example,
experiments by Bloomﬁeld and Hales (2000)
examine how sellers’ abilities to form reputations
for honest reporting are inﬂuenced by buyers’ and
sellers’ expectations of one another’s likely behavior and beliefs.
Future research might also begin to integrate
disclosure research with the other literatures
described in this section. For example, Bloomﬁeld
(1996a) integrates the disclosure literature with the
information aggregation literature by showing that
sellers are willing to pay a fee to inﬂate a public
signal, even though the information available to
the market as a whole is unchanged. They are willing to do this because markets tend to react more
strongly to information held by more investors.
Researchers might also integrate economicsbased disclosure research with the psychology-based
literature described in Section 3.1. That research
focuses on how investors could use ﬁnancial
reporting choices to draw inferences about managers’ incentives and information, but ignores the
fact that managers should anticipate investors’
reactions. On the other hand, the psychologybased research presents a more comprehensive
treatment of ﬁnancial accounting institutions, by
allowing managers to choose how to classify and
report accounting information. We believe it
would be worthwhile — though diﬃcult — to
examine fully strategic interactions in more complex
accounting institutions. Researchers in ﬁnancial
accounting might also attempt to integrate game
theory and social psychology, as has been done
successfully in the auditing context by King (2001).
4. Eﬀective and eﬃcient research design:
methodological considerations in experiments
Section 3 presented a number of directions for
future experiments. In this section, we discuss
how these experiments can be designed to be
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R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
both eﬃcient and eﬀective. An experiment is eﬃcient if it achieves a given level of eﬀectiveness as
economically as possible. An experiment is eﬀective if it provides evidence of suﬃcient internal
validity that readers should believe the results of
hypothesis tests, while being of suﬃcient external
validity that it bears on a signiﬁcant part of the
ﬁnancial accounting issue of interest.10 Both
internal and external validity are key to eﬀectiveness. An experiment that lacks internal validity
fails by providing a misleading indication of the
relation between the dependent and independent
variable, while an experiment that lacks external
validity produces results that are (or at least
should be) divorced from the motivation of the
study. We do not provide an exhaustive treatment
of research design (see Kinney, 1986; Runkel &
McGrath, 1972; Trotman, 1996 for more comprehensive discussions). Rather, we focus on issues
that we believe are particularly important or are
often misunderstood. Section 4.1 addresses techniques for maximizing eﬀectiveness through careful hypothesis development and research design.
Section 4.2 addresses when it is (and is not) possible to improve eﬃciency by consuming fewer
resources without sacriﬁcing eﬀectiveness. We
address the number and type of subjects used in
the experiment, the payment of monetary incentives, the use of within-subject designs, and the
decision to use single-person tasks rather than
interactive tasks (such as ﬁnancial markets or
strategic reporting settings).
4.1. Increasing experimental eﬀectiveness
We organize our discussion of experimental
eﬀectiveness around the predictive validity model
(Libby, 1981; Runkel & McGrath, 1972). This
model provides a useful description of the
hypothesis testing process, and focuses our attention on the key determinants of the internal and
external validity of a research design.
10
Internal validity is the degree to which you can be sure
that observed eﬀects are the result of the independent variables.
External validity is the degree to which results can be generalized beyond the speciﬁc tasks, measurement methods, and participants employed in the study.
Fig. 1 illustrates the predictive validity model as
it applies to Hypothesis H1b from Hunton and
McEwen (1997; hereafter, HM). As noted earlier,
based on prior theory and evidence HM hypothesized that sell-side analysts’ relationship-based
incentives would decrease their forecast accuracy.
Analysts’ relationship-based incentives were operationally deﬁned as a three-level independent
variable: an ‘‘underwriting relationship’’ that has a
direct impact on fees, a ‘‘following relationship’’
that creates the need for future access to private
information, or ‘‘no future relationship.’’ HM
expect analysts in the underwriting condition to
provide the most optimistic forecasts, those who
follow the ﬁrm to be next most optimistic, and
analysts who do not follow the ﬁrm to be the least
optimistic. They operationally deﬁne optimism
(the dependent variable) as the analysts’ forecast
minus the actual earnings outcome. HM also controlled for a number of other potentially inﬂuential
variables including subject background, experience, time on task, and information availability.
In Fig. 1, link 1 depicts the relationship in HM’s
underlying theory. No theory can be tested
directly; rather, a theory is tested by assessing the
relationship between the operational deﬁnitions of
key concepts in the theory (i.e. by assessing link 4).
For this test to be valid, the links between the
concepts and the operational deﬁnitions (links 2
and 3) must be valid, and other factors that might
aﬀect the dependent variable (link 5) must be
controlled or have no eﬀect. A study’s internal and
external validity is determined by the validity of
these ﬁve links. We now discuss ways in which
researchers can strengthen each of these links.
4.1.1. Link 1: theory and hypotheses
The ﬁrst determinant of experimental eﬀectiveness is speciﬁcation of a good research question. A
good research question addresses the relation
between two or more concepts, can be stated
clearly and unambiguously as a question, implies
the possibility of empirical testing, and is important to the researcher and others (Kinney, 1986).
Experimental tests of research questions must
rely on some theory depicting forces that inﬂuence
behavior in the experimental setting. Theories may
range from highly speciﬁc numerical models (such
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
795
Fig. 1. Predictive validity framework.
as those derived from economics or artiﬁcialintelligence cognition models) to more general
qualitative predictions based on prior evidence
(such as systematic evidence that people use a
certain heuristic in a given setting). Regardless of
its nature, the theory suggests the expected answer
to the research question, and serves to guide the
many decisions and tradeoﬀs that must be made
during the design and administration of an experiment. Whereas archival researchers analyze data
from secondary sources,11 the experimental setting
is speciﬁcally designed to gather data relevant to
the hypotheses. Consequently, all stages of the
design of experiments are profoundly aﬀected by
the need for a well-formulated research question
and hypotheses. In this section, we emphasize four
issues that are particularly important in developing good research questions and hypotheses in
experimental ﬁnancial accounting research.
First, the hypotheses must have external validity; that is, readers must believe that the theoretical concepts and the relationships between them
capture important aspects of the target environment. Although people often speak of external
validity as an aspect of experimental stimuli, we
consider it an element of theory as well. If the
theory and hypotheses are appropriately capturing
relationships among elements of the target environment, an internally valid experiment will test
that theory in a manner that generalizes to the target environment. External validity is established
11
That is, the data is initially gathered for a diﬀerent purpose.
empirically by extensions of the research that test
additional hypotheses concerning environmental
contingencies that deﬁne the limits of generality of
the initial hypotheses (Trotman, 1996).
For example, HM’s research question of ‘‘Do
sell-side analysts’ relationships with the ﬁrms they
cover decrease their forecast accuracy?’’ relates an
antecedent (analysts’ relationships) and consequence (forecast accuracy) that clearly maps into ﬁrst
order concerns indicated by theory and prior evidence. If the experiment operationalizes those
concepts well and provides an internally valid test
of their relation, it will provide insight into the
real-world eﬀect of analysts’ incentives on their
judgments. Future research can then test the
extent to which those insights can be generalized.
Second, experimental research questions in
ﬁnancial accounting should focus on how theories
drawn from fundamental disciplines (such as psychology and economics) interact with details of
ﬁnancial accounting institutions (as discussed in
Section 2.4). As Gibbins and Swieringa (1995)
suggest, accounting experiments should be ‘‘both
theory driven and setting sensitive.’’
Tying the accounting institution to theory from
a fundamental discipline allows hypotheses to
have relevance beyond the very speciﬁc practice
context that motivated the experiment (as recommended by Maines, 1994). It also allows experimenters to contribute to both ﬁnancial accounting
and the fundamental discipline. For example,
Nelson and Kinney (1997) apply Einhorn and
Hogarth’s (1986) ambiguity model to predict how
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R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
ambiguity aﬀects ﬁnancial statement auditors’ and
users’ judgments of appropriate contingent-liability disclosure. Their study shows how the diﬀerences between auditors’ and users’ incentives lead
auditors to use the discretion provided by ambiguous evidence to justify lower levels of disclosure
than users desire. This result is of clear interest to
ﬁnancial accounting researchers, and also contributes to psychologists’ understanding of how
incentives interact with ambiguity.12
A more ambitious approach is to use fundamental disciplines to develop and experimentally
test a general theory that is applied to the ﬁnancial
accounting phenomenon of interest. For example,
Maines and McDaniel (2000) identify various
general dimensions of formats that signal information importance or that aﬀect the cognitive cost
of processing information (see also Lipe, 1998).
They apply their theory when testing whether
information-disclosure format aﬀects consideration of the volatility of unrealized gains and losses,
but their theory is much broader than the particular practice context that they examine.
Third, researchers should frame their theories at
the least speciﬁc level that can account for the data
expected to arise from the experiment. Stating the
theory with greater speciﬁcity will simply encourage readers to argue that the results are driven by
a slightly diﬀerent theory (such as a diﬀerent theory of categorization) that yields identical predictions in the experimental setting. Such debates are
rarely productive. If the distinction is likely to be
important in accounting settings, researchers interested in accounting issues should consider what
other experiments might illustrate this importance.
If the distinction is unlikely to have important
ramiﬁcations for accounting settings, experiments
discriminating between such theories are more
appropriately seen as contributions to the fundamental disciplines from which the theory is drawn.
12
Of course, the theory should entail some element of doubt
before testing. Experiments applying psychology to accounting
settings can be uninteresting if readers are certain that the
results obtained in psychology will readily extend to accounting
even without seeing the experimental results. Experiments
applying economics to accounting settings can be uninteresting
if they are little more than complex ways of showing that people prefer more money to less (Kachelmeier, 1996b).
Finally, experimental research questions should
be based on a theory that describes causal relationships between concepts. As discussed above,
the key advantage of the experimental method lies
in its ability to disentangle factors that are confounded in natural settings, and thus provide
indications of how and why phenomena arise. A
causal theory also improves external validity,
because causal forces are more likely to generalize
to diﬀerent settings. This also leads to a preference
for research questions that focus on a directional
prediction of diﬀerences, as opposed to a single
point prediction. As Trotman (1996) indicates,
‘‘the basis of any experimental design is that one
or more independent variables are manipulated
and the eﬀect on the dependent variable(s) is
observed.’’ Since experiments require abstraction
from the real world, any number of diﬀerences
between the experimental and real-world environments could aﬀect the particular levels of observed
measures. Consequently, evidence consistent with
point predictions (e.g. ‘‘the market price will be
$5.00’’) and particular parameter estimates (e.g.
‘‘managers will weight current year’s earnings
twice as heavily as prior year’s earnings’’) are
unlikely to generalize to real-world environments.
Directional eﬀects are more likely to generalize,
because diﬀerences between the experimental setting and the target setting are more likely to alter
the magnitude of an eﬀect than its direction. A
focus on directional eﬀects also makes it much
easier to design an experiment that controls for
competing explanations. We discuss this latter
issue further in Section 4.1.3.
4.1.2. Links 2 and 3: operationalizing dependent
and independent variables
Link 2 relates the antecedent theoretical concept
A to the independent variable(s) operationalized
in the experiment. Link 3 relates the consequential
concept B to the dependent variable operationalized
in the experiment. An internally valid test requires
manipulation of each independent variable in a
way that changes only one theoretical antecedent
at a time. At the same time, they must construct
an operational dependent variable that measures
the conceptual variable, and that variable alone.
This section discusses three particularly diﬃcult
R. Libby et al. / Accounting, Organizations and Society 27 (2002) 775–810
issues in operationalizing variables: (1) choosing
the appropriate realism of the stimuli presented to
participants; (2) choosing the appropriate levels of
independent variables; and (3) using measured
independent variables.
4.1.2.1. Realism of stimuli. A common challenge
in operationalizing independent variables is deciding how realistic the stimuli should be. The
appropriate level of realism in the operationalization of an independent variable is determined by
the role of realism in the theory to be tested.
Experiments testing psychological theories typically present participants with more realistic stimuli than experiments testing economic theory,
because psychology-based experiments are typically focused on how participants make decisions
using cognitive processes and knowledge that
developed in response to their real-world education, training, and experience. Without relatively
realistic stimuli, participants may not rely on the
cognitive processes and knowledge of interest. For
example, HM’s theory relates analysts’ knowledge
of their incentives to…

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