1. finance
2. accounting and auditing

Risk Perceptions, Directional Goals and the Link between Risk and Value
W. Brooke Elliott
University of Illinois at Urbana-Champaign
Kristina M. Rennekamp
Cornell University
Brian J. White*
The University of Texas at Austin
April 2015
* Corresponding author’s contact information:
Department of Accounting
The University of Texas at Austin
McCombs School of Business
Department of Accounting
2110 Speedway, B6400
Austin, TX 78712-1281
Phone: (512) 471-5619
E-mail: [email protected]
We appreciate helpful feedback from Tim Bauer, Tim Brown, Shuping Chen, Willie Choi, Paul Demeré, Peter
Demerjian, Cassandra Estep, Harry Evans, Steph Grant, Frank Hodge, Jane Jollineau, Lisa Koonce, Russ Lundholm,
Dawn Matsumoto, Adam Presslee, Nick Seybert, Jane Thayer, Michael Williamson and seminar participants at the
University of British Columbia, University of Oregon and University of Washington (UBCOW) Conference, the
University of Illinois at Urbana-Champaign, the University of Pittsburgh and the University of Texas at Austin.
Risk Perceptions, Directional Goals and the Link between Risk and Value
ABSTRACT
A fundamental premise in accounting and finance research is that risk affects firm value, and a
key purpose of financial disclosures is to communicate risk to market participants. In this paper,
we test how investors perceive risk in response to financial disclosures and how these risk
perceptions affect their judgments of firm value. We also test directional goals for positive firm
performance as a potential boundary condition on investors’ incorporation of risk perceptions
into their judgments of firm value. Consistent with the adage that “losses loom larger than
gains,” we find that prospective investors (those without directional goals) focus on downside
risk. Further, prospective investors’ risk perceptions significantly influence their valuation
judgments. In contrast, long investors perceive risk as more symmetric, and largely disregard risk
in forming their valuation judgments. Taken together, these results suggest an unintended
consequence of communicating risk in financial reports, in that not all investors interpret risk in a
similar way, and some disregard risk in judging value. Finally, our results have implications for
others who assess risk – including preparers, auditors and analysts – given that each of these
groups may have directional goals for firm performance.
Keywords: financial disclosures, risk perceptions, directional goals, valuation
Data availability: Contact the authors.
I. Introduction
A longstanding and fundamental premise in accounting and finance research is that risk
affects firm value: given a level of expected return, increased risk reduces value. Because of the
link between risk and value, a key purpose of financial disclosures is to communicate risk to
market participants. In this paper, we test two important links in the assumed risk-value relation,
plus a boundary condition for this relation. First, we test how investors perceive risk in response
to financial disclosures that convey some uncertainty. Second, we test how risk perceptions are
incorporated into investors’ judgments of firm value. In addition, we test directional goals for
positive firm performance as a potential boundary condition for these links.
Testing the effect of disclosures on risk perceptions, and the link between risk perceptions
and value, is important for several reasons. First, the psychology literature on risk perceptions
indicates that people’s risk perceptions do not always match the way in which risk is defined in
formal models (e.g., Slovic 1987; Koonce, McAnally and Mercer 2005). Thus, the links between
disclosures and risk perceptions, and between risk perceptions and value, are not a foregone
conclusion. Second, standard setters and regulators are clearly interested in conveying
information about risk to investors, since many mandatory disclosures are intended to
communicate risk information (Linsmeier and Pearson 1997; SEC 1997; ASC 715, 820 and 860
[FASB 2014]). Thus, they are likely interested in how investors evaluate such disclosures,
particularly if all users do not evaluate risk in the same way. Third, it is important to test how
directional goals moderate risk perceptions and the link between risk and value, because many
financial statement users hold long or, more rarely, short positions in the firms they analyze, and
thus have a directional goal for positive or negative firm performance. While prior research in
accounting has shown earnings forecasts and bid prices in asset markets move in line with
1 investors’ directional goals (e.g., Hales 2007; Seybert and Bloomfield 2009; Han and Tan 2010),
we investigate how directional goals not only affect a different type of measure – risk
perceptions – but also the influence of risk perceptions in assessing firm value. That is, we
propose that differences in risk perceptions and the extent to which they are considered in
subsequent judgments may be important underlying factors that help to explain the effects of
motivated reasoning documented by prior research.
Drawing on theory and previous research on risk perceptions and directional goals, we
develop two hypotheses. The first hypothesis focuses on perceptions of risk and how directional
goals moderate these perceptions. Building on prior research that suggests individuals focus on
negative aspects of risk, we predict that prospective investors (i.e., those without directional
goals) will perceive the potential for loss as greater than the potential for gain. In contrast,
because of their directional goals for positive firm performance, long investors will assess the
potential for future loss (gain) as smaller (greater) than prospective investors; that is, their risk
perceptions will be more symmetric. The second hypothesis focuses on how investors
incorporate these risk perceptions in their valuation judgments. We predict that long investors
will be less likely than prospective investors to incorporate their perceptions of risk into their
estimates of firm value. That is, if motivated reasoning allows investors with directional goals to
interpret risk more favorably, it may also allow these same investors to disregard risk when
making related valuation judgments. This hypothesis challenges the common assumption that
investors link risk and value.
To test our hypotheses, we conduct an experiment in the context of fair value estimates. We
first instantiate a directional goal for positive firm performance by assigning one group of
participants to a long position in the stock of a real estate firm, while the other group of
2 participants is assigned to consider a prospective investment in the firm’s stock (and thus do not
have a directional goal). We also vary the observability of the inputs to a fair value estimate (i.e.,
Level 2 and Level 3 in the fair value hierarchy in ASC 820 [FASB 2014]). Level 3 estimates are
the most powerful setting in which to test our predictions because the high level of uncertainty in
Level 3 estimates allows for the most flexibility in interpreting risk. However, it is important to
examine whether our predictions also hold with Level 2 estimates. Although Level 2 estimates
include less uncertainty than Level 3 estimates, they represent the majority of fair value
estimates (Laux and Leuz 2010) and allow us to test whether directional goals can affect risk
perceptions and valuation judgments even when there is relatively less flexibility for investors to
exploit in order to reach their desired conclusions. Following these manipulations, participants
evaluate the risk and valuation effects of an accounting estimate related to the impaired value of
land the firm is holding for development.
Results of the experiment support our predictions. First, whereas prospective investors assess
the probability and likely amount of a future economic loss as much higher than a future
economic gain, long investors assess these probabilities and amounts as being more symmetric.
That is, long investors judge the likelihood of a gain to be insignificantly different from the
likelihood of a loss. This result is remarkable given that previous studies across multiple domains
suggest people tend to focus on downside risk (Vlek and Stallen 1981; Fischoff, Slovic and
Lichtenstein 1982; Loewenstein, Weber, Hsee and Welch 2001). Our results thus support the
adage that “losses loom larger than gains” (Kahneman and Tversky 1981, 456) for prospective
investors’ risk perceptions, but directional goals appear to substantially reduce long investors’
emphasis on the potential for loss. Further, we find that these results hold for both Level 2 and
Level 3 estimates, suggesting that investors perceive sufficient subjectivity in Level 2 estimates
3 that they can reach their desired conclusions with respect to risk.
Second, in judging the effect of risk on firm value, we find that long investors’ risk
perceptions (i.e., the potential for loss and gain) are not significantly associated with their
valuation judgments; by contrast, the potential for loss and gain are both significant determinants
of value for prospective investors. Further, risk is generally less important in explaining the
valuation effects of accounting estimates for long compared to prospective investors (as
measured by adjusted R2 values from regressions of risk variables on valuation judgments).
These results suggest that the fundamental link between risk perceptions and firm value
essentially breaks down for long investors.1
An additional out-of-sample survey provides convergent evidence that long investors are
biased when they fail to incorporate their risk assessments into their valuation judgments. In this
survey, we present unbiased investors (i.e., those with no directional goals) with the assessments
of potential for gain and loss made by long investors in our primary experiment. We find that
these assessments of the potential for gain and loss are significant determinants of unbiased
investors’ valuation judgments (whereas they did not affect long investors’ valuation judgments
in our experiment). Finally, additional analyses confirm that our results are robust to alternative
measures of risk perceptions suggested by prior research.
Our study has implications for both theory and practice. We extend prior research on
directional goals by showing that these goals affect both investors’ risk perceptions and the way
in which risk perceptions are incorporated into valuation judgments. Moreover, our results
identify directional goals as a boundary condition on the idea that “losses loom larger than gains”
in judging risk, thus extending research on the conditions under which people are more sensitive
1
As discussed in more detail in Section IV, we confirm that (1) our manipulations affect risk perceptions but not
participants’ risk preferences, and (2) results are robust to controlling for participants’ underlying risk preferences.
4 to losses than gains (e.g., Novemsky and Kahneman 2005; Ariely, Huber and Wertenbroch 2005)
Further, our results suggest that previously documented effects of directional goals (for example,
on investors’ earnings forecasts and bids in asset markets) may be explained in part by
directional goals causing differences in perceptions of risk and the extent to which these
perceptions affect subsequent judgments.
Our study also has implications for other users of accounting estimates – including preparers,
auditors, and analysts – each of whom may have directional goals (Hackenbrack and Nelson
1996; Lin and McNichols 1998; Michaely and Womack 1999; Kadous, Kennedy and Peecher
2003). As one example, prior to the financial crisis of 2008, ratings agencies were paid by the
firms issuing the instruments they were rating, so their analysts’ interpretation of risk may have
been influenced by a goal to generate more ratings business (e.g., Silver 2012, 29-30; Jollineau,
Tanlu and Winn 2014). Given the catastrophic losses that subsequently occurred, analysts appear
to have underestimated downside risk, which may have contributed to the broader crisis.
For accounting practitioners and regulators, our results are directly informative about the
effect of financial statement estimates on users’ judgments. Given the risk inherent in relying on
accounting estimates, it is important to understand how financial statement users interpret risk
and incorporate risk perceptions into subsequent judgments. Our results are informative on this
issue because we document effects of accounting estimates that are likely unanticipated by
regulators relying on standard economic theory, which assumes that risk information will be
incorporated into valuation judgments. Of course, our results do not suggest that regulators
should abandon the use of estimates, but that the effects we document should be weighed against
the potential benefits of mandating the extensive incorporation of estimates in financial
disclosures.
5 The remainder of the paper is organized as follows. We provide background and develop
hypotheses in Section 2. We discuss the experimental method we employ in Section 3, and
discuss results of the experiment in Section 4. We summarize and conclude in Section 5.
II. Previous Literature, Theory, and Hypotheses
Risk perceptions and financial disclosures
Investors face a variety of risks when deciding whether, and how much, to invest in a given
firm (e.g., market risk, liquidity risk, business risk, exchange rate risk, etc.). Since many of these
sources of risk are directly or indirectly discussed in firms’ financial reports, investors also face
the risk associated with interpreting the information provided in these disclosures. That is,
investors face risk both with respect to the underlying assets and liabilities themselves in a firm,
but also in interpreting related disclosures that can never fully convey all relevant information.
The standard assumption in accounting research is based on economic theory, and suggests
that investors will use financial disclosures to form expectations about risk associated with the
future potential for gain or loss. Further, the expectation is that investors will incorporate these
risk assessments into decisions about how much capital to provide to the firm (see Beyer et al.
2010). This expectation is consistent with formal valuation models in accounting and finance, to
which risk, defined as variance, is a key input (e.g., Merton 1973; Jorgensen and Kirschenheiter
2003).
While formal models define risk as variance, research across a variety of domains suggests
that individual perceptions of risk are largely focused on the potential for negative outcomes,
with much less emphasis on the potential for positive outcomes (Vlek and Stallen 1981, Fischoff,
Slovic and Lichtenstein 1982; Loewenstein, Weber, Hsee and Welch 2001).2 Relatedly, people
2
Slovic (1987) summarizes previous work on risk perceptions and identifies two dimensions (“dread” and the
“unknown”) to explain how people perceive risk. In an accounting context, Koonce et al. (2005) show that these
6 tend to be loss averse, in that they prefer avoiding potential losses to pursuing potential gains,
even when such choices are riskless (e.g., Kahneman and Tversky 1981, Tversky and Kahneman
1991). Taken together, previous research finds substantial evidence that people tend to focus the
potential for loss over the potential for gain in assessing risk, and tend to be more sensitive to
losses than to gains.
The effect of directional goals on beliefs and behavior
The theory of motivated reasoning predicts that goals and motivation influence the process
by which people form judgments, with the result that judgments tend to be biased in favor of
people’s preferred conclusions, at least within reason (Kunda 1990, Ditto and Lopez 1992,
Boiney et al. 1997). The theory divides judgments into two types: those in which an individual
has a goal to arrive at the most accurate conclusion (an “accuracy goal”), and those in which the
individual has a goal to arrive at a conclusion consistent with a particular preference or goal (a
“directional goal”). For our purposes in this study, a key distinction is that long investors have a
directional goal for positive firm performance, while prospective investors do not have
directional goals (although they may have an accuracy goal in that they would like to make an
accurate assessment of a firm’s investment potential).
The type of goal associated with a particular judgment influences how information is
processed (Kunda 1990). Accuracy goals typically lead people to adopt strategies considered
most appropriate to arrive at an accurate judgment, for example attending to more, and more
relevant, information, and by expending more effort processing the information considered.
Directional goals, in contrast, typically lead people to non-consciously adopt strategies that
dimensions have additional explanatory power over more traditional risk measures for explaining the risk associated
with financial instruments. We measure these dimensions in our study and use them as alternative measures of risk
perception as robustness tests in our analyses.
7 support their desired conclusions. Thus, directional goals lead people to selectively search their
memory for supportive knowledge and beliefs.
Supporting this theory, a number of accounting studies have demonstrated that the beliefs
and behavior of auditors and investors are biased by directional goals. For example,
Hackenbrack and Nelson (1996) find that auditors’ preference for accepting client-preferred
accounting treatments leads them to interpret accounting standards in ways that allow them to
accept such treatments. Building on this result, Kadous, Kennedy and Peecher (2003) find that
adding an accuracy goal, in the form of a quality assessment, to a directional preference for
accepting a client-preferred treatment, amplifies the effect of the directional preference. Among
investors, Hales (2007) finds that long investors forecast higher earnings than short investors,
even when firm fundamentals are held constant. Han and Tan (2010) show that these effects are
especially apparent when management earnings guidance is presented in range form and conveys
positive news. Thayer (2011) finds that directional goals influence the information sought out by
investors, with some investors choosing to access preference-consistent information even when it
is of low credibility. Seybert and Bloomfield (2009) show that traders in asset markets make bids
biased by their preferences about future outcomes, and that these bids provoke even more
optimistic beliefs among other traders. Finally, Fanning, Agoglia and Piercey (2014) provide
evidence that investors’ risk perceptions are influenced by the quantity of risk disclosures, and
that this relation varies with directional goals.
To summarize, motivated reasoning predicts that people process and interpret information in
ways that allow them to support directional goals while maintaining an “illusion of objectivity”
by selectively engaging and/or combining memories and beliefs to justify their preferred
conclusion (Kunda 1990, 482-3). When faced with an accounting estimate, the reliance on which
8 entails risk, financial statement users may justify their preferred conclusion (e.g., that the firm
will perform well in the future) by interpreting risk in a way that bolsters the evidence for that
conclusion. As such, financial statement users with directional goals are likely to interpret the
risk associated with accounting estimates in ways that allow them to support their preference for
positive firm performance.
We extend the literature in this area in two ways. First, while prior research has focused on
how investors use motivated reasoning to arrive at desired conclusions related to firm value (for
example, in their earnings forecasts and market bid prices), we are one of the first studies to
examine how motivated reasoning might influence risk perceptions, which standard economic
theory indicates should influence conclusions about firm value.3 Thus, our study seeks to shed
light on the process underlying previous results. Second, we explicitly test how a directional goal
affects the link between risk perceptions and value, and whether a directional goal leads to biased
judgments.
Hypotheses
Our hypotheses focus on the risk associated with an accounting estimate. As noted,
motivated reasoning requires a certain degree of flexibility or ambiguity for individuals with
directional goals to gather evidence in support of their preferred conclusions while maintaining
an illusion of objectivity (Kunda 1990, Kadous et al. 2003). Thus, it is important that flexibility
exists that financial statement users with directional goals can exploit to reach their desired
conclusion. The uncertainty associated with accounting estimates provides that flexibility.
When faced with an accounting estimate, there are at least two opportunities for investors to
3
One exception is Fanning et al. (2014) which provides evidence that overall risk perceptions are influenced by the
quantity of risk disclosures, and that this relation varies with directional goals. In contrast, we hold disclosure
quantity constant and test the effect of directional goals on the gain and loss components of risk, and on how these
components of risk influence perceptions of firm value.
9 engage in motivated reasoning. The first is in assessing the risk associated with the estimate.
Based on previous research showing that people focus on the potential for loss over the potential
for gain in assessing risk, we expect prospective investors (those without directional goals) to
assess the potential for loss to be greater than the potential for gain. However, we expect
investors with directional goals to exploit the flexibility in accounting estimates to support their
preferred conclusions. We therefore predict that long investors will interpret the risk associated
with accounting estimates more favorably than prospective investors, such that they judge
downside risk less negatively and the upside more favorably.
Hypothesis 1: Prospective investors will judge the potential for loss associated with an
accounting estimate to be greater than the potential for gain, but this difference will be
smaller for long investors.
While assessing the risk of an accounting estimate provides one opportunity for investors to
support their preferred conclusions via motivated reasoning, assessing the effect of the estimate
on firm value provides another. Although much of the research on motivated reasoning focuses
on how directional goals bias individuals’ processing of information, there is also evidence to
suggest that directional goals will affect whether certain information is considered at all. In
arriving at their desired conclusions, individuals often fail to search for, or tend to dismiss,
evidence that does not support their preferred conclusion (Ditto and Lopez 1992). Related
research in the literature on message persuasiveness suggests that, even when facing information
that is relatively difficult to refute, individuals with a goal to reach a desired conclusion appear to
be able to isolate negative information and minimize its impact on subsequent judgments
(Ahluwalia 2000). Thus, in our setting, even though investors provide risk and valuation
judgments in tandem, we predict that long investors are more likely to minimize the relation
between risk information and related valuation judgments. In other words, we predict that long
10 investors will be less likely than prospective investors to incorporate their risk judgments into
their estimates of firm value.4
Hypothesis 2: Perceptions of risk are more likely to affect the valuation judgments of
prospective investors than long investors.
III. Method
Design overview and participants
To test our predictions, we conducted an experiment with a 2 × 2 between-subjects design
with investor type (prospective vs. long) and fair value input level (Level 2 vs. Level 3) as
manipulated independent factors. The investor type manipulation allows us to compare the risk
perceptions of investors with directional goals for positive firm performance (long investors) to
those without directional goals (prospective investors). The fair value input manipulation plays
two roles in our design. From a theory perspective, it allows us to test whether investors’
propensity to engage in motivated reasoning is moderated by level of uncertainty. From a
practical perspective, it allows us to test whether the effects of directional goals generalize to
multiple types of estimates.
Experimental materials were randomly distributed to 198 masters of accounting students at a
large public university. Sixty-one students completed and returned the materials. They
participated in this and another experiment in return for a cash payment (calculated as described
below) and a chance to win one of five $100 participation prizes in a random draw. The
experimental conditions in this experiment were counterbalanced with conditions in the other
experiment, and we detect no carryover effects in our analyses. At the time of the experiment,
4
Alternatively, it is possible that long investors would use motivated reasoning to incorporate the potential for gains
into their valuation judgments while ignoring the potential for losses. However, motivated reasoning theory suggests
this is unlikely due to reasonableness constraints. If long investors recognize that risk assessments should influence
valuation judgments (i.e., by incorporating gains), it is likely to be psychologically unjustifiable to simultaneously
ignore losses. Because of this, we instead predict that long investors will instead prefer to limit the influence of both
gain and loss risk assessments on their valuation judgments.
11 participants had completed an average of 14 accounting courses and three finance courses. All
participants had some full-time work experience in accounting or finance, averaging eight
months at the time of the experiment. Forty-eight percent (29 of 61) had previously invested in
debt or equity securities and ninety-seven percent (59 of 61) planned to do so in the future,
suggesting that these participants were reasonable proxies for investors.
Case materials and procedures
The experiment consisted of three parts, divided into numbered envelopes to ensure that
participants worked through materials in order. Figure 1 describes the tasks participants
completed in each of these three parts.
<INSERT FIGURE 1 HERE>
Part one & investor type manipulation
In the first envelope, participants received information about two hypothetical real estate
firms, Lanark Residential and Moray Residential. We manipulated investor type at two levels—
long and prospective—using an approach adapted from previous research on directional goals
(e.g., Hales 2007). First, long investors chose to take a long position in one of the two firms.
Prior to making this choice, long investors were informed that their task was to select the firm
that they believed would be the better performer as the firm that they would invest in, and that
their compensation would depend on whether the firm they chose was actually the better
performer of the two firms. Specifically, they would be paid $15 if the firm they chose to invest
in was the better performer and $5 otherwise. In contrast, prospective investors were informed
that their task was to evaluate the companies as a potential investment and that they would be
paid $10 for providing their judgments on one of the firms to be chosen at random (Han & Tan
2010, Fanning et al. 2014).
12 Next, all participants viewed summary information for each firm, including three financial
statement ratios and four qualitative statements about the firms’ operations (see Figure 2).
Importantly, this information holds constant the underlying economics of the two firms by
deriving all six ratios (three for each firm) from the same underlying financial statements.
Consistent with the two firms having the same underlying economics, the choice of firm did not
affect the information provided about the accounting estimate in the second part of the
experiment; that is, the information in part two was identical regardless of which firm was
selected. After responding to a comprehension check question to ensure they understood how
their compensation would be determined, participants moved on to part two.
<INSERT FIGURE 2 HERE>
Part two & fair value input level manipulation
In part two, long investors were provided with two sealed envelopes (one for each firm), but
opened only the one corresponding to the firm they chose in part one.5 Prospective investors
opened the envelope provided to them, which contained materials for one of the two firms
chosen at random.
These envelopes contained summary information from the firm’s financial statements,
including two line items from the firm’s most recent quarterly financial statements related to land
held for development. The first line item came from the income statement and listed a loss of
$21.152 million on land held for development. The second line item came from the balance sheet
and listed land held for development at a net carrying value of $267.095 million. To ensure
participants recognized that these values were material for the firm, they were also told that the
impairment loss was equal to approximately 30% of the firm’s net income in the previous year,
5
One of the experimenters confirmed that the seal on the other envelope had not been broken prior to authorizing
each participant’s payment.
13 and that the impaired value of the land represented approximately 20% of the firm’s total assets.
Participants then viewed a note containing further information about the land’s fair value.
The note disclosed the reason for the impairment, the designation of the fair value as either
Level 2 or Level 3 within the fair value hierarchy, and a description of the valuation technique
used in accordance with fair value disclosure requirements in ASC 820 (FASB 2014). In Level 2
conditions, the fair value of the land parcels was estimated based on recent sales of several
comparable parcels. In Level 3 conditions, the fair value of the land parcels was generated using
an expected present value technique. All disclosures were adapted from actual disclosures and
examples provided in accounting standards. The appendix contains further details of the fair
value disclosure manipulation for Moray; all information was identical for Lanark except the
name of the firm. After reviewing this information, participants responded to dependent
measures.
Part three and payment
In part three, participants responded to several post-task questions and received a payment
summary page. The payment summary page informed long investors whether their chosen firm
performed better; the better-performing firm was randomized to avoid participants learning
which firm was the better performer from their peers. Prospective investors were reminded that
they would be paid a fixed amount. All participants were provided instructions on how to collect
their payment. Specifically, they brought the payment summary page and completed materials to
the office of one of the experimenters to receive payment and register for the prize drawing. Dependent measures
In part two of the experiment, participants responded to questions designed to measure the
risk and valuation effects of the impaired land. We use four questions to capture perceptions
14 associated with the risk of gain and/or loss: (1) the probability of a further economic loss to the
company from the land, (2) the amount of a further economic loss to the company from the land,
(3) the probability of a further economic gain to the company from the land, (4) the amount of a
further economic gain to the company from the land. A fifth question asked about the probability
of the status quo (i.e., neither an economic loss nor an economic gain from the land).
In addition, because prior research has also identified additional, “behavioral”, dimensions of
risk, called “dread” and the “unknown” (Slovic 1987; Koonce et al. 2005), we asked a further
seven questions related to these behavioral risk dimensions as a robustness check on the more
traditional measures of risk as the potential for loss and gain. We conduct supplemental analyses
using these behavioral risk measures discussed in Section IV. Finally, two questions asked about
the overall level of risk associated with the land held for development and about how the land
affected the value of the company.
IV. Results
Manipulation checks
To assess the effectiveness of the investor type manipulation, we asked participants how their
pay would be determined. The two possible responses were: “I will be paid $15 if the firm I
chose is the better performer, or $5 otherwise” and “I will be paid a fixed amount of $10”.6
Eighty-seven percent of participants correctly indicated their condition and responses are
significantly associated with experimental condition (χ2 = 33.87, p < 0.01), indicating a
successful manipulation of investor type. To verify the effectiveness of the fair value input level
manipulation, we asked participants what level of the fair value hierarchy the value of the land
held for development was considered to be: “Level 2” or “Level 3”. Ninety-seven percent of
6
For all results, long investors’ responses do not differ depending on which of the two hypothetical firms they
chose.
15 participants correctly indicated their condition and these responses are also significantly
associated with condition (χ2 = 53.21, p < 0.01), indicating a successful manipulation of fair
value input level.7
Tests of H1
H1 predicts that prospective investors will perceive greater potential for loss than potential
for gain, and that this difference will be smaller for long investors. To test this, we measured
both the probability and the likely amount of a future gain or loss on the land held for
development. To create a single measure of potential for loss or gain, we multiply the probability
of a loss or gain (as a percentage) by the amount of a gain or loss. Table 1, Panel A presents cell
sizes, means, and standard deviations for both the individual and combined measures.8 Since
results are inferentially identical whether we use the individual measures or the combined
measure, we focus on the combined measure for the sake of brevity. Figure 3 also depicts the
pattern of cell means for the combined potential for loss or gain measure by experimental
condition.
<INSERT TABLE 1 & FIGURE 3 HERE>
Table 1, Panel B presents an analysis of variance (ANOVA) model of the potential for loss or
gain. The significant within-subjects effect of the gain/loss variable indicates a significant onaverage difference between the potential for gain and the potential for loss (F = 20.77, p < 0.01).
Of interest in testing H1, however, is the gain/loss × investor type interaction (F = 11.08, p <
0.01). This indicates that the two-way interactions depicted in Panels A and B of Figure 3 are
significant, in support of H1. We do not observe a significant interaction of gain/loss with fair
7
Excluding the manipulation failures yields inferentially identical results.
An additional risk question asked about the probability of the status quo (i.e., neither a loss nor a gain related to the
land held for development). We detect no main or interactive effects of our manipulated variables on this measure
(all p-values > 0.29).
8
16 value level, or a significant three-way interaction. This indicates that neither the relative potential
for gain versus loss nor the significant two-way interaction of gain/loss with investor type differ
significantly between Level 2 and Level 3 fair value conditions.
Planned contrasts in Table 1, Panel C provide additional support for H1. Specifically,
prospective investors assess the potential for a future loss on the land as greater than the potential
for a future gain (t = 5.17, p < 0.01, one-tailed). By contrast, long investors view the potential for
loss as not significantly different from the potential for gain (t = 1.13, p = 0.27, two-tailed). In
other words, while prospective investors’ perceptions are heavily weighted toward downside
risk, long investors’ perceptions of upside and downside risk are statistically symmetric. For
completeness, we also confirm that long investors’ assessments of the potential for loss are lower
than those of prospective investors (t = 2.30, p = 0.01, one-tailed), whereas long investors’
assessment of the potential for gain are higher than those of prospective investors (t = 2.49, p <
0.01, one-tailed).9
Taken together, these results provide strong support for H1. Specifically, prospective
investors judge the potential for loss to be significantly greater than the potential for gain, long
investors view the upside and downside potential as more symmetric.
Tests of H2
Table 2, Panel A presents cell sizes, means, and standard deviations by experimental
condition for participants’ valuation judgments (i.e., the effect of the land held for development
on firm value). Before testing the effect of investors’ risk perceptions on their valuation
9
We confirm that our manipulations affect risk perceptions but not participants’ risk preferences. Specifically, we
measure risk preferences by eliciting participants’ level of agreement with the statement, “I believe protecting the
principal of my investment is more important than the potential for achieving high returns.” Participants responded
on a 101-point scale (0 = “Strongly Disagree”, 100 = “Strongly Agree”). Results of an ANOVA with risk
preferences as the dependent variable indicate no significant main or interactive effects of investor type or fair value
level (all p-values > 0.10). Further, including risk preferences as a covariate in our test of H1 does not affect our
inferences. Specifically, the gain/loss × investor type interaction remains highly significant (F = 10.34, p < 0.01).
17 judgments predicted in H2, we first consider the effect of our manipulated variables, investor
type and fair value input level, on valuation judgments. The ANOVA presented in Panel B of
Table 2 indicates a main effect of both of these variables on valuation judgments. First,
consistent with motivated reasoning theory, the main effect of investor type indicates that the
land has a significantly more negative effect on the valuation judgments of prospective investors
than long investors (F = 5.30, p = 0.03). Second, the main effect of fair value input level
indicates that the Level 2 estimate has a significantly less negative effect than the Level 3
estimate on investors’ valuation judgments (F = 4.73, p = 0.03). These two main effects are also
apparent in the pattern of cell means depicted in Figure 4. The interaction of investor type and
fair value level is not significant (F = 0.03, p = 0.86)
<INSERT TABLE 2 & FIGURE 4 HERE>
We next turn to formal tests of H2. H2 predicts that perceptions of risk are more likely to
affect the valuation judgments of prospective investors than long investors. Panel C of Table 2
presents regressions of valuation judgments on participants’ perceptions of the potential for gain
and loss. In support of H2, we observe that the coefficient on potential for loss is negative and
significant (t = -2.55, p < 0.01, one-tailed) for prospective investors, but does not differ
significantly from zero for long investors (t = 1.19, p > 0.10). Similarly, the potential for gain
significantly affects prospective investors’ valuation judgments (t = 3.66, p < 0.01), but does not
significantly affect long investors’ valuation judgments (t =1.18, p > 0.10). These results support
H2, indicating that long investors appear to ignore risk (both upside and downside) in assessing
the effect of a fair value estimate on firm value.
Panel C of Table 2 also includes adjusted R2 values for the regressions of prospective and
long investors’ risk perceptions on valuation judgments. In least squares regressions like these,
18 R2 captures the strength of the association between the predictor variables (here, investors’ risk
perceptions) and the dependent variable (here, investors’ valuation judgments) (Hays 1994).
Adjusted R2 makes a downward adjustment for the number of predictor variables in the model,
since unadjusted R2 can be artificially inflated by adding additional predictors. The adjusted R2
values for the regression of risk perceptions on valuation judgments are considerably higher for
prospective investors than for long investors. Specifically, the adjusted R2 for prospective
investors is 0.37, compared to only 0.04 for long investors. Thus, consistent with the importance
of risk as an input in formal valuation models, risk is an important determinant of prospective
investors’ valuation judgments. By contrast, risk perceptions explain very little of the variation in
long investors’ valuation judgments.10,11
In the analyses reported above, we estimate separate regressions for long and prospective
investors so that we can assess the explanatory power of risk perceptions on value separately for
each group via R2 and adjusted R2 values. To provide corroborating evidence, we also estimate a
single regression (untabulated) with interaction terms for the incremental effect of the gain and
loss risk dimensions on prospective investors’ valuation judgments. These results are again
consistent with H2. Specifically, the coefficients on potential for loss and potential for gain are
insignificant (loss: t = 1.21, p = 0.23; gain: t = 1.20, p = 0.24; both two-tailed), while the
interaction of prospective investor status and potential for loss is negative and significant (t = 2.37, p = 0.01, one-tailed) and the interaction of prospective investor status and potential for gain
10
A comparison of variances confirms that these differences in adjusted R2 values are not caused by greater
dispersion in long investors’ risk perceptions (Levene’s test, all p-values > 0.10).
11
We confirm that these results are robust to controlling for participants’ underlying risk preferences. Specifically,
including risk preferences as a covariate in the regressions in Panel C of Table 2 does not affect our inferences.
Controlling for risk preferences, prospective investors’ valuation judgments are significantly affected by both
potential for loss and potential for gain (both p-values < 0.01, one tailed), but long investors’ valuation judgments
are not significantly affected by potential for loss or potential for gain (both p-values > 0.10, one-tailed).
19 is positive and marginally significant (t = 1.50, p = 0.07, one-tailed), indicating that risk
significantly affects prospective investors’ valuation judgments, but not those of long investors.
Supplemental Study: Long Investors and the Link between Risk Perceptions and Value
We conduct a supplemental study to provide convergent evidence that long investors are
biased when they neglect to incorporate risk assessments into their valuation judgments. On its
face, it may seem reasonable that a symmetric risk of gain and loss would lead to no change in
valuation judgments. For example, if an investor learns that an asset currently priced at $100 has
a 10% chance of a $50 gain and a 10% chance of a $50 loss, then it may seem reasonable to
conclude that the expected value of the asset has not changed and the asset is still worth $100.
However, it is unreasonable to assume that the aforementioned asset should have the same value
as one currently priced at $100 that has a 50% chance of a $50 loss and a 50% chance of a $50
gain. That is, investors should be willing to pay more for an asset with less variance in the
distribution of future outcomes.
To provide evidence of this particular to our setting, we conduct an out-of-sample survey
using 94 participants from Amazon’s Mechanical Turk (MTurk) platform. We provide all
participants with background information on Lanark Residential, one of the hypothetical firms
from our primary experiment. We include information related to the impairment loss on land
held for development. Participants are randomly assigned to either the condition using Level 2 or
Level 3 inputs. We then present all participants with scenarios showing potential distributions for
gain or loss associated with the land. These scenarios are drawn from actual responses made by
long investors in our primary experiment. For example, if a given participant indicated
probability of a loss (gain) was 44% (47%) with an estimated magnitude on our 101-point scale
(0 = zero gain, 100 = very large gain) of 22 (27), we converted the magnitude to dollar amounts
20 of $8,800,000 ($10,800,000) and told them to imagine that there was a 44% chance that the
company would suffer a loss of $8,800,000, and a 47% chance that the company would
experience a future gain of $10,800,000, on the land held for development.12 In total, participants
assigned to the Level 2 (Level 3) group saw 11 (15) separate scenarios.13
For each scenario, participants then respond to a valuation judgment question that is identical
to the one used in our primary between-subjects experiment. We present all scenarios on the
same page in order to increase the chance that participants attend to and process differences in
the scenarios, and consider how each scenario should affect valuation. Importantly, we do not
give participants in this supplemental study any directional goals. Thus their valuation judgments
in response to the different scenarios serve as a benchmark to determine whether, and how,
unbiased observers perceive that the long investors’ perceptions of the potential for loss and
gains should affect valuation judgments.
As shown in Table 3, we find that both the gain potential and loss potential are significant in
explaining participants’ valuation judgments. Greater loss (gain) potential is significantly
associated with decreased (increased) valuation judgments (p<0.01, two-tailed for both loss and
gain).14 Recall that these same perceptions did not significantly influence long investors’
valuation judgments in our primary experiment. These results therefore further support that long
investors in our primary experiment are biased by their directional goals to ignore the
fundamental relationship between risk perceptions and firm valuation.
12
In all cases we made the conversion by dividing responses on the 101-point scale by 100 and then multiplying by
$40,000,000. For ease of interpretation, Table 3 further scales the calculated gain and loss potentials by dividing
each by $1,000,000.
13
The difference in the number of scenarios presented is driven by two things. First, the actual number of
participants in each cell of our primary experiment differs to due random assignment (12 in Level 2 and 15 in Level
3 for long investors). Second, one of the responses from the Level 2 condition indicated a 70% chance of gain and
70% chance of loss. Because this adds to greater than 100%, we exclude this response from our adapted scenarios. 14
Our inferences are unchanged if we instead use rank regressions for each gain or loss potential. Both gain and loss
are still significant in explaining valuation judgments (p<0.01, one-tailed, untabulated, for both).
21 <INSERT TABLE 3 HERE>
Robustness: Behavioral Risk Measures
As discussed in Section III, we also asked participants seven questions designed to measure
risk perceptions from the behavioral perspective identified in prior literature (Slovic 1987;
Koonce et al. 2005). These questions capture aspects of both “dread” and the “unknown”, and
include: (1) the extent to which the land causes worry, (2) the likelihood that the risks from the
land are likely to be catastrophic, (3) whether participants would invest voluntarily in a firm that
they were aware held the land, (4) management’s ability to control the risk of the land, (5)
whether the risks are new, novel ones or old, familiar ones, (6) the extent to which the risks from
the land are known precisely by investors, and (7) the extent to which the risks from the land are
known precisely by company management.15 Responses to the first four (last three) of these
questions capture the “dread” (“unknown”) dimension of risk. Slovic (1987) finds that the
“dread” dimension is particularly associated with risk judgments, whereas the “unknown”
dimension reflects the extent to which a particular phenomenon provides information about risks
in related areas. Thus we would expect directional goals to primarily affect the “dread”
dimension.
Descriptive statistics for these measures and comparisons between long and prospective
investors’ judgments are shown in Table 4. Of the four measures associated with dread, two
differ significantly between long and prospective investors. Specifically, the potential for the
15
We measured the same decision theory and behavioral risk variables as Koonce et al. (2005) with one exception.
The results reported in Koonce et al (2005) suggest that the effects of the immediacy variable are weak and
inconsistent in a financial statement context. Specifically, immediacy does not significantly affect risk judgments in
either experiment reported in that paper. In addition, although immediacy is classified as an “unknown” risk variable
in Slovic (1987), it loads—albeit weakly—on the factor associated with “dread” in the Koonce et al. (2005) data. As
a result, and because we did not specify a particular timeframe for the investment being considered in our study, we
did not ask a question about immediacy.
22 land to lead to catastrophe is rated as higher by prospective investors than by long investors (t =
1.69, p = 0.05, one-tailed), and prospective investors indicate that they would be less likely than
long investors to take on the risks associated with the land voluntarily (t = 2.01, p = 0.02, onetailed). These results indicate that prospective investors assess these dimensions of risk more
negatively than long investors, providing additional support for H1. The other two variables
associated with dread—worry and control—do not differ significantly between long and
prospective investors (both p-values > 0.10). We also do not observe significant differences
between prospective and long investors’ judgments for the variables associated with the
unknown (all p-values > 0.10).16
<INSERT TABLE 4 HERE>
Consistent with prior research on risk perceptions (e.g., Slovic 1987, Koonce et al. 2005), we
next conduct a factor analysis on all of the risk perception measures, including both the potential
for gain and loss variables and the seven behavioral variables. This analysis serves two functions.
First, it confirms that our measures capture the dimensions of risk suggested by theory and
previous research (e.g., Slovic 1987, Koonce et al. 2005). Second, reducing the data to fewer
dimensions reduces collinearity and improves interpretability for the regressions we will use to
provide additional evidence for H2 (Dunteman 1989). Results of this factor analysis are shown in
Panel A of Table 5. The analysis reveals five factors: one each for the potential for loss and
potential for gain, as well as one “dread” factor and two “unknown” factors.17 These factors thus
appear consistent with both theory and prior research.
16
We observe no significant effect of fair value input level on the behavioral variables, with one exception. A main
effect of fair value level on worry indicates that Level 3 estimates cause more worry than Level 2 estimates (F =
5.14, p = 0.03). Further, we observe no significant interaction between investor type and fair value input level for
any of the behavioral variables.
17
We follow Koonce et al. (2005) in using principal components extraction with varimax rotation to identify factors
corresponding to risk dimensions. However, our results are robust to various alternative specifications, including
least squares and maximum likelihood extraction methods and oblique (nonorthogonal) rotation.
23 Finally, as in our main test of H2, Panel B of Table 5 presents regressions of valuation
judgments on the five risk factors identified in our factor analysis for prospective and long
investors. In further support of H2, we observe that the coefficient on the potential for loss,
potential for gain, and “dread” risk factors have the expected sign and differ significantly from
zero (all p-values < 0.05, one-tailed) for prospective investors. For long investors, only the factor
associated with potential for gain has a marginally significant effect on valuation judgments (t =
1.65, p = 0.06, one-tailed); none of the other risk factors have a significant effect on long
investors’ valuation judgments. Further, the adjusted R2 is much higher for prospective investors
(0.46) than for long investors (0.04).
<INSERT TABLE 5 HERE>
Combined, these supplemental analyses using measures from the behavioral perspective on
risk indicate that our results are robust to alternative methods of measuring risk perceptions.
They therefore provide additional support for the idea that prospective investors perceive more
downside risk than long investors, and that long investors largely ignore risk in assessing the
effect of a fair value estimate on firm value.
V. Conclusion
This study presents theory and experimental evidence that directional goals affect investors’
risk assessments and their incorporation of risk assessments into valuation judgments. Most
notable are two new insights. First, long investors in our study view risk as symmetric, assessing
the potential for future gain and loss as statistically equivalent. By contrast, and consistent with
previous research on risk perceptions, prospective investors emphasize downside risk, assessing
the potential for loss as higher than the potential for gain. Second, in judging the effect of an
estimate on firm value, long investors in our study disregard risk. That is, despite risk being a
24 key input into formal models of firm value, and despite the fact that we ask participants to make
valuation judgments immediately following their risk judgments, risk perceptions explain very
little of the variation in long investors’ valuation judgments. Further, using an out-of-sample
survey we provide convergent evidence that long investors are biased when they fail to
incorporate risk assessments into their valuation judgments by showing that investors without
directional goals do incorporate these very same risk assessments into their valuation judgments.
These results challenge the link between risk perceptions and firm value that is often assumed in
the accounting literature, in that directional goals can lead to a breakdown in this fundamental
relationship.
Our study of course has certain limitations, which in turn raise interesting questions for
future research. First, we investigate the effect of directional goals for positive firm performance
on investors’ perceptions of risk and their use of risk perceptions in valuation. We focus on
directional goals for positive firm performance because this reflects the preferences of a majority
of investors (e.g., Odean 1999) as well as financial statement preparers, auditors and analysts.
However, certain participants in the financial reporting process have directional goals for
negative firm performance, including recent examples of prominent activist investors taking
short positions in firms (see, e.g., Schmidt et al. 2014 on Bill Ackman’s billion dollar short of
Herbalife). Future research might investigate how such directional goals for negative
performance influence perceptions of risk and the emphasis placed on risk in valuation. Second,
we find that risk perceptions play very little role in determining long investors’ valuation
judgments. However, because we focus on risk perceptions, we do not investigate other inputs to
investors’ valuation judgments. Formal models suggest book value, expected future cash flows
or earnings, and estimates of long-term growth as additional determinants of value. We leave it
25 to future research to determine how directional goals affect the weights placed on these or other
determinants of value.
Despite these limitations, our study contributes to the literatures on risk perceptions and the
effects of directional goals on judgment. Our study also speaks directly to regulators and
standard setters interested in how the increase in the use of estimates and, in turn, the increase in
disclosures on estimate-related risks in financial reports affects users’ judgments. Our results
suggest that one of the costs associated with mandating estimated-related risk disclosures is that
the information may be interpreted differently depending on the investor’s directional goal,
particularly given the inherent subjectivity in estimates that gives investors the flexibility to
reach their desired conclusions. While explicit analysis of the costs and benefits of the
mandatory disclosure regime has been rare historically, political pressure for cost-benefit
analysis is high, and regulators have indicated some willingness to conduct such analyses as part
of their rule-making process in the future (Committee on Oversight and Government Reform
2012, Kraus and Raso 2013).
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29 Appendix
Fair value disclosures
Part 1: Level 2 disclosures
The following information is related to an impairment loss on land held for development by
Moray, announced in the first quarter of 2014. The impairment loss is equal to approximately
30% of net income in the previous year (2013), and the impaired value of the land represents
approximately 20% of Moray’s total assets.
Income Statement
($ in thousands)
Q1 2014
Expenses:
Impairment loss – land held for development (see note 1)
21,152
Balance Sheet
($ in thousands)
Assets:
Land held for development (fair value net of impairment loss; see note 1)
267,095
Note 1
Assets measured at Fair Value on a Nonrecurring Basis
($ in thousands)
Description
Land held for
development
Fair Value at
End of Period
Fair Value Measurements Using
Quoted Prices
Significant
in Active
Other
Significant
Markets for
Observable
Unobservable
Identical Assets
Inputs
Inputs
(Level 1)
(Level 2)
(Level 3)
Total
Gains
(Losses)
$267,095
$267,095
$(21,152)
Impairment Loss
During the period, the Company concluded that market conditions did not support the development and construction
of certain new apartment communities that were previously in planning. Accordingly, two land parcels held for
development with a carrying value of $288,247 were written down to their fair value of $267,095, resulting in an
impairment charge of $21,152, which was included in earnings for the period. Because the valuation of the land
parcels incorporated significant other observable inputs, these values are considered to be Level 2 prices in the fair
value hierarchy.
Valuation Technique
The fair value of the land parcels was estimated based on recent sales of several comparable land parcels. The sales
prices of the comparable parcels were adjusted for differences including size, location, and zoning restrictions.
30 Part 2: Level 3 disclosures
The following information is related to an impairment loss on land held for development by
Moray, announced in the first quarter of 2014. The impairment loss is equal to approximately
30% of net income in the previous year (2013), and the impaired value of the land represents
approximately 20% of Moray’s total assets.
Income Statement
($ in thousands)
Q1 2014
Expenses:
Impairment loss – land held for development (see note 1)
21,152
Balance Sheet
($ in thousands)
Assets:
Land held for development (fair value net of impairment loss; see note 1)
267,095
Note 1
Assets measured at Fair Value on a Nonrecurring Basis
($ in thousands)
Description
Land held for
development
Fair Value at
End of Period
$267,095
Fair Value Measurements Using
Quoted Prices
Significant
in Active
Other
Significant
Markets for
Observable
Unobservable
Identical Assets
Inputs
Inputs
(Level 1)
(Level 2)
(Level 3)
$267,095
Total
Gains
(Losses)
$(21,152)
Impairment Loss
During the period, the Company concluded that market conditions did not support the development and construction
of certain new apartment communities that were previously in planning. Accordingly, two land parcels held for
development with a carrying value of $288,247 were written down to their fair value of $267,095, resulting in an
impairment charge of $21,152, which was included in earnings for the period. Because the valuation of the land
parcels incorporated significant unobservable inputs, these values are considered to be Level 3 prices in the fair
value hierarchy.
Valuation Technique
The internal model used to estimate the fair value of the land parcels employed an expected present value technique.
The model used a set of probability-weighted future cash flows to generate a single stream of expected cash flows.
These expected cash flows were then adjusted using a risk-adjusted discount rate. The discount rate used in
generating the fair value of the impaired land parcels was the Company’s estimated weighted average cost of capital
(WACC) at the balance sheet date. The WACC is a weighted average of the Company’s cost of equity capital,
estimated using the capital asset pricing model (CAPM), and the Company’s after-tax incremental borrowing rate
for long-term debt. This valuation technique is the same as techniques used to measure similar assets in prior
periods.
31 Figure 1
Summary of the three parts of the experiment
Part One
Part Two
• All participants receive
• Long (prospective) investors open
information about two
a sealed envelope related to the
hypothetical real estate firms.
firm they chose (were assigned
to) in Part One.
• Long (prospective) investors learn
they will receive $15 if they
• All participants view summary
choose the better performer of the
performance information from the
two firms, and $5 otherwise (flat
firm’s financial statements
pay of $10).
(identical regardless of which
firm they chose or were assigned
• Long (prospective) investors
to).
choose (are assigned to) one of the
two firms.
• Participants view a footnote
containing additional information
about an impairment related to
the fair value of land held for
development. The land represents
a large portion of the firm’s total
assets (20%) and its impairment
loss represents a large proportion
of the prior year’s net income
(30%) to ensure participants view
the values related to the land as
material.
• In the Level 2 (Level 3) condition
of our experiment, the footnote
discloses that the fair value of the
land is estimated based on recent
sales of comparable parcels (an
expected present value
technique).
• Participants respond to dependent
measures related to risk
perceptions and valuation
judgments.
Part Three
• Participants respond to post-task
questions and receive a page
summarizing their payment.
• Long investors learn whether
their chosen firm performed
better (this was randomized), and
prospective investors are
reminded that they will be paid a
fixed fee.
• All participants are given
instructions on how to collect
their payment.
This figure describes the tasks participants complete in each of the three parts of our experiment. Participants
complete all tasks in a given part before moving on to the next part.
32 Figure 2
Summary firm information provided to all participants
This figure presents the information provided to all participants in part one of the experiment. After reviewing this
information, long investors chose to invest in one of the firms, while prospective investors were randomly assigned
to one of the two firms. To hold underlying economics constant, the three ratios presented for each firm were
derived from the same set of financial statements.
33 Figure 3
Effect of investor type on the potential for future gain or loss
Panel A: Potential for gain/loss (Fair Value Level 2)
35.00
Potential for gain/loss
30.00
25.00
Prospective
20.00
Long
15.00
10.00
5.00
Loss
Gain
Panel B: Potential for gain/loss (Fair Value Level 3)
35.00
30.00
25.00
Prospective
20.00
Long
15.00
10.00
5.00
Loss
Gain
This figure depicts the observed pattern of cell means for assessments of the potential (probability × amount) for a
future gain and loss based on whether (1) the participant is a long or prospective investor, and (2) whether the fair
value estimate is based on Level 2 or Level 3 inputs.
34 Figure 4
Effect of investor type on valuation judgments
Valuation Judgment
10
0
-10
Prospective
-20
Long
-30
-40
Level 2
Level 3
Fair Value Disclosures
This figure depicts the observed pattern of cell means for the effect of impaired land held for development on firm
value based on whether (1) the participant is a long or prospective investor, and (2) whether the fair value estimate is
based on Level 2 or Level 3 inputs.
35 Table 1
Descriptive statistics and tests of H1 – Effect of investor type on potential for future gain or loss
Panel A: Descriptive statistics – Means (std deviations) for judgments of probability and
amount of future loss and gain
Long
Level 2
n = 12
Long
Level 3
n = 16
Prospective
Level 2
n = 16
Prospective
Level 3
n = 17
Loss probability
46.25
(18.81)
45.25
(17.51)
58.31
(13.01)
61.18
(19.42)
Loss amount
41.42
(19.41)
39.44
(18.18)
43.31
(17.72)
47.41
(26.74)
Potential for loss
(probability × amount)
20.28
(14.00)
19.03
(13.67)
26.54
(14.43)
32.62
(23.52)
Gain probability
47.00
(11.18)
41.00
(13.69)
31.63
(17.35)
23.12
(17.76)
Gain amount
42.50
(22.28)
30.25
(22.22)
27.94
(20.59)
19.53
(17.04)
Potential for gain
(probability × amount)
19.34
(9.22)
13.57
(11.58)
11.71
(13.18)
6.43
(11.71)
Panel B: Potential for loss or gain – ANOVA
SS
df
MS
F-stat
p-value
48.37
72.46
114.49
12125.93
1
1
1
57
48.37
72.46
114.49
212.74
0.23
0.34
0.54
0.64
0.56
0.47
4207.93
2243.54
471.92
1
1
1
4207.93
2243.54
471.92
20.77
11.08
2.33
<0.01
<0.01
0.13
87.70
1
87.70
0.43
0.51
11545.79
57
202.56
Prospective investors: Loss (26.54+32.62) > Gain (11.71+6.43)
t-Stat
5.17
p-value
<0.01†
Long investors: Loss (20.28+19.03) < Gain (19.34+13.57)
1.13
0.27
Potential for loss: Long (20.28+19.03) < Prospective (26.54+32.62)
2.30
0.01†
Potential for gain: Long (19.34+13.57) > Prospective (11.71+6.43)
2.49
<0.01†
Between subjects:
Investor type
Fair value level
Investor type × FV level
Error
Within subjects:
Gain/loss
Gain/loss × investor type
Gain/loss × FV level
Gain/loss × investor type × FV
level
Error
Panel C: Planned contrasts
Participants responded to the following questions (scale endpoints in parentheses):
36 Loss probability: What do you think is the probability of a further economic loss to the company from the land
held for development? (0 = zero probability; 100 = absolute certainty)
Loss amount: If there were a further economic loss to the company from the land held for development, how big a
loss would you expect? (0 = zero loss; 100 = very large loss)
Gain probability: What do you think is the probability of a future economic gain to the company from the land
held for development? (0 = zero probability; 100 = absolute certainty)
Gain amount: If there were a future economic gain to the company from the land held for development, how big a
gain would you expect? (0 = zero gain; 100 = very large gain)
The combined measure potential for loss (gain) is calculated as loss (gain) probability (as a percentage) multiplied
by loss (gain) amount. This combined measure is the dependent variable in the analyses in Panels B and C.
†
one-tailed p-value
37 Table 2
Descriptive statistics and tests of H2 – Valuation judgments
Panel A: Descriptive statistics – Means (std deviations) for effect of land held for development
on firm value
Valuation judgment
Long
Level 2
n = 12
Long
Level 3
n = 16
Prospective
Level 2
n = 16
Prospective
Level 3
n = 17
1.08
(23.27)
-13.50
(26.96)
-14.44
(28.64)
-31.59
(31.93)
Panel B: Valuation judgments – ANOVA
SS
df
MS
F-Stat
p-value
Investor type
4228.11
1
4228.11
5.30
0.03
Fair value level
3769.51
1
3769.51
4.73
0.03
24.67
1
24.67
0.03
0.86
45468.97
57
797.70
Investor type × FV level
Error
Panel C: Regression model for incorporation of risk perceptions into valuation judgments
Long Investors
Risk Variable
Prediction
Intercept
Coefficient
-24.33
**
Prospective Investors
t-stat
Prediction
-2.25
Coefficient
-19.26
***
t-stat
-2.20
Potential for loss
–
0.43
1.19
–
-0.57***
-2.55
Potential for gain
+
0.54
1.18
+
1.43***
3.66
Adjusted R2
0.04
0.37
Valuation judgments are responses to the following question (endpoints in parentheses): “Overall, how does the land
held for development affect the value you place on the company?” (-100 = greatly decreases how much I value the
company; 0 = neither increases nor decreases how much I value the company; 100 = greatly increases how much I
value the company)
*,**,***
indicate significance at p < 0.10, 0.05 and 0.01, respectively (one-tailed for directional predictions, two-tailed
otherwise).
38 Table 3
Regression Analysis for Out-of-Sample Valuation Judgments
Panel A: Regression model for incorporation of risk perceptions into valuation judgments
Risk Variable
Prediction
Intercept
Coefficient
4.35
*
t-stat
1.70
Potential for loss
–
-4.78***
-14.14
Potential for gain
+
1.79***
4.20
Adjusted R2
0.14
Valuation judgments are responses to the following question (endpoints in parentheses): “Overall, how does the land
held for development affect the value you place on the company?” (-100 = greatly decreases how much I value the
company; 0 = neither increases nor decreases how much I value the company; 100 = greatly increases how much I
value the company). Participants respond to either 11 (Level 2 condition) or 15 (Level 3 condition) scenarios with
different combinations of potential for gain or loss.
*,**,***
indicate significance at p < 0.10, 0.05 and 0.01, respectively (one-tailed for directional predictions, two-tailed
otherwise).
39 Table 4
Robustness test – Effect of investor type on behavioral risk variables
Panel A: Descriptive statistics – Means (std deviations) for behavioral risk variables
Worry
Catastrophic
Voluntary
Control
Newness
Known by investor
Known by management
Long
Level 2
n = 12
47.50
(20.95)
32.92
(18.08)
52.75
(16.87)
33.75
(23.52)
25.75
(22.05)
36.75
(17.89)
66.42
(19.90)
Long
Level 3
n = 16
62.75
(16.26)
33.00
(19.55)
47.94
(20.89)
35.88
(17.27)
38.56
(28.29)
31.87
(20.61)
67.31
(21.51)
Prospective
Level 2
n = 16
52.63
(18.67)
41.63
(18.78)
41.00
(18.58)
44.13
(21.99)
29.50
(15.33)
31.50
(17.70)
68.19
(12.21)
Prospective
Level 3
n = 17
61.88
(26.12)
41.88
(24.52)
37.12
(27.08)
42.47
(20.97)
37.18
(27.85)
29.88
(18.53)
68.24
(23.37)
Panel B: Contrasts
p-value
Worry: Long (47.50+62.75) < Prospective (52.63+61.88)
t-stat
0.21
Catastrophic: Long (32.92+33.00) < Prospective (41.63+41.88)
1.69
0.05†
Voluntary: Long (52.75+47.94) > Prospective (41.00+37.12)
2.01
0.02†
Control: Long (33.75+35.88) > Prospective (44.13+42.47)
1.57
0.12
Newness: Long (25.75+38.56) ≟ Prospective (29.50+37.18)
0.06
0.95
Known by investor: Long (36.75+31.87) ≟ Prospective (31.50+29.88)
0.70
0.49
Known by management: Long (66.42+67.31) ≟ Prospective (68.19+68.24)
0.26
0.80
0.42†
Participants responded to the following questions (scale endpoints in parentheses):
Worry: Are the risks to the company from the land held for development ones that cause you to worry or do they
cause you no worry? (0 = no worry; 100 = high worry)
Catastrophic: To what extent are the risks to the company from the land held for development likely to be
catastrophic? (0 = not likely to be catastrophic; 100 = very likely to be catastrophic)
Voluntary: Would you voluntarily invest in a company that had this land held for development or would such an
investment only occur if you were unaware of the land held for development (i.e., you would only invest
involuntarily)? (0 = involuntarily, 100 = voluntarily)
Control: How difficult is it for the company’s management to use their skill and diligence to control (limit) the
risks of the land held for development? (0 = very difficult to control; 100 = very easy to control)
Newness: Are the risks to the company from the land held for development new, novel ones or old, familiar ones?
(0 = old; 100 = new)
Known by investor: To what extent are the risks to the company from the land held for development known
precisely by you, as an investor? (0 = not known; 100 = known precisely)
Known by management: To what extent are the risks to the company from the land held for development known
precisely by management? (0 = not known; 100 = known precisely) †one-tailed
40 Table 5
Robustness test – Effect of all risk variables (potential for loss and gain plus behavioral
variables) on valuation judgments
Panel A: Factor analysis
Factor 1
(Dread)
0.117
Factor 2
(Gain)
-0.142
Factor 3
(Loss)
0.872
Factor 4
(Unknown 1)
-0.065
Factor 5
(Unknown 2)
0.001
Loss amount
0.349
0.176
0.766
0.034
0.142
Gain probability
-0.287
0.810
-0.164
0.082
0.048
Gain amount
-0.041
0.851
0.123
0.002
-0.183
Status quo probability
-0.271
-0.213
-0.189
0.451
0.452
Worry
0.787
-0.080
0.178
-0.006
0.088
Catastrophic
0.745
-0.096
0.203
-0.029
0.049
Voluntary
-0.662
0.344
-0.151
-0.042
0.153
Control
-0.542
-0.097
0.311
0.089
-0.495
Newness
0.086
-0.088
0.211
-0.032
0.775
Known by investor
-0.085
0.298
0.043
0.715
0.202
Known by mgmt
0.121
-0.101
-0.027
0.781
-0.241
Loss probability
Panel B: Regression model for incorporation of risk perceptions into valuation judgments
Prospective Investors
Long Investors
Risk Variable
Prediction
Intercept
Coefficient
-12.60
*
t-stat
Prediction
-1.73
Coefficient
-14.02
***
t-stat
-3.11
Loss
–
2.57
0.41
–
-8.12**
-1.85
Gain
+
12.42*
1.65
+
16.54***
4.01
Dread
–
-5.23
-0.91
–
-12.22***
3.84
Unknown 1
?
5.25
1.06
?
3.31
0.75
Unknown 2
?
2.79
0.52
?
-0.10
-0.02
Adjusted R2
0.04
0.46
Valuation judgments are responses to the following question (endpoints in parentheses): “Overall, how does the land
held for development affect the value you place on the company?” (-100 = greatly decreases how much I value the
company; 0 = neither increases nor decreases how much I value the company; 100 = greatly increases how much I
value the company)
*,**,***
indicate significance at p < 0.10, 0.05 and 0.01, respectively (one-tailed for directional predictions, two-tailed
otherwise).
41