MANAGEMENT’S PREFERENCE: CAN AUDITORS STOP IT FROM BIASING ACCOUNTING ESTIMATES?

Brian C. Fitzgerald*

Christopher J. Wolfe**

Kecia W. Smith**

*Department of Accounting D’Amore-McKim School of Business Northeastern University Boston, MA 02115

**Department of Accounting Mays Business School Texas A&M University College Station, TX 77840

September 2015 Contact Author: Christopher Wolfe, cwolfe@mays.tamu.edu, 979-845-0964 Support for the research project described in this article was provided by the Center for Audit Quality. However, the views expressed in this article and its content are those of the authors alone and not those of the Center for Audit Quality. We thank the participating firms for providing auditors for our studies.

Management’s Preference: Can Auditors Stop It from Biasing Accounting Estimates?

Abstract. We examine how auditors can mitigate the biasing influence of management’s

preference when auditing accounting estimates. Across two different experiments using senior

auditors, we find that developing an independent estimate or reviewing relevant estimate

evidence before receiving management’s preference mitigates the influence of management’s

preference. However, in both experiments, we also find that independently evaluating

management’s preference, before reviewing estimate evidence, does not consistently mitigate the

preference’s biasing influence. Though we find that approximately 90 percent of the auditors

who evaluate management’s preference consider it unreasonable, about half go on to accept the

preference’s implementation in the client-preferred estimate. In a final study, we examine this

dissonance. We find that auditors low in the personality trait of conscientiousness, or high in the

trait of openness, are susceptible to the dissonance of evaluating management’s preference as

unreasonable and then accepting its implementation. Likewise, we find that auditors with a weak

sense of auditor-client independence are susceptible to such dissonance, as well as auditors

making a weak effort to eliminate management’s preference from their judgment. Our findings

advance our understanding of factors that influence auditor independence, and are important to

practice in terms of both auditor hiring and training.

Keywords: Accounting estimates, Auditor independence, Assimilation, Contrast, Individual

differences JEL Descriptors: M4, M40, M41, M42

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I. INTRODUCTION

Independence is fundamental to auditing. It requires that auditors suppress management’s

bias and evaluate the client’s financial reporting objectively. Despite professional standards

requiring independence, auditors are frequently biased by management’s preference (see Church,

Jenkins, McCracken, Roush and Stanley 2015). The influence of management’s preference is

particularly relevant to the audit of accounting estimates. Professional guidance notes that

management bias can mislead auditors in testing these accounts (ISA 540 2008). Griffith,

Hammersley, and Kadous (2015) report that auditors tend to over-rely on management’s estimate

preferences. Finally, Public Company Accounting Oversight Board (PCAOB) inspections find

that accounting estimates are a significant source of audit deficiencies, suggesting that

management’s unreasonable estimate preferences often survive the audit process (PCAOB 2008;

Church and Shefchik 2012). We study the influence of management’s preferences on the audit of

accounting estimates, investigating how auditors can correct for their biasing influence.

Psychology research finds that the influence of irrelevant information depends on how that

information is used. If irrelevant information is used to understand evidential matter, judgments

based on that evidential matter are biased by the irrelevant information (Bless and Schwarz 210).

However, when irrelevant information is cognitively separated from evidential matter, the

irrelevant information becomes a comparison standard, resulting in judgments that are contrasted

away from the irrelevant information (Martin and Seta 1983; Wilcox, Roggeveen, and Grewal

2011). Across three studies, we examine how auditors can cognitively separate the irrelevant

information in management’s preference from relevant audit evidence, which theoretically

should eliminate the biasing influence of management’s preference.

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Our methods for separating management’s preference from audit evidence involve making

management’s preference distinct (Helson 1964; Herr 1986; Zhu and Myers-Levy 2009). When

management’s preference becomes distinct, we expect that auditors cognitively categorize it

separately from audit evidence. We examine three methods of making management’s preference

distinct: (1) creation of an independent estimate; (2) independently evaluating management’s

preference; and (3) the timing of management’s preference.

Professional guidance indicates that auditors can overcome management’s bias when

auditing accounting estimates by developing an independent expectation of the client’s estimate

(ISA 540 2008). Auditors should use judgment standards of conservatism and/or reasonableness

when developing an independent estimate. Therefore, an independent estimate should make

management’s preference for an aggressive estimate distinct, by holding it to a well-formed

independent estimate. However, it is unclear whether developing an independent estimate, after

having received management’s preference, will bias the independent estimate and ultimately bias

the auditor’s assessment of management’s estimate (Griffith et al. 2015). We expect that

developing an independent estimate reduces the biasing influence of management’s preference,

contingent on whether the independent estimate is itself unbiased.

The second method we analyze for making management’s preference distinct involves

independently evaluating management’s preference. Empirics from the psychology literature

indicate that independently evaluating irrelevant information, before evaluating relevant

evidence, makes people question whether the irrelevant information is representative of the item

being judged (Martin and Seta 1983; Weary, Tobin, and Reich 2001; Bless and Schwartz 2010).

We expect that independently evaluating management’s preference, before evaluating audit

evidence, will make auditors compare management’s preference to conservatism and/or

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reasonableness judgment standards. If management’s preference violates these standards, it

becomes distinct, leading auditors to contrast their judgment away from the biasing influence of

management’s preference.

The third method we analyze for making management’s preference distinct involves timing.

Wilks (2002) and Ricchiute (2004) find that auditors receiving preferences from supervisors and

attorneys before evidence evaluation are more biased by the preferences than are auditors

receiving preferences after evidence evaluation. Testing the influence of management’s

preference on auditor judgment, Jenkins and Haynes (2003) observe results similar to Wilks

(2002) and Ricchiute (2004), when the audit task involves the decision to disclose. However,

Jenkins and Haynes (2003) observe no preference timing effect when the audit task involves

measurement. Our study’s task setting involves measurement, assessing an accounting estimate,

and we expect that preference timing changes the influence of management’s preference.

Auditors receiving management’s preference before evaluating audit evidence are expected

to use the preference to understand the evidence. As such, no cognitive separation occurs

between management’s preference and audit evidence, leading auditors to assimilate the

preference into their judgment. Conversely, auditors receiving management’s preference after

evaluating audit evidence have reviewed the evidence and categorized it as evidential matter. As

such, when auditors receive management’s preference after evaluating audit evidence, a natural

separation occurs between the evidence and management’s preference. With such separation,

management’s preference becomes distinct, leading auditors to contrast their judgment away

from the biasing influence of management’s preference.

We test our expectations with two experiments and a field study. Participants are senior

auditors from all the Big Four public accounting firms: 57 auditors populate the first experiment,

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112 auditors populate the second experiment, and 94 auditors populate the field study. All

studies use the same case. In the case, an auditor evaluates an estimate (loss accrual) for costs

that the client will incur due to an explosion at the client’s facility just prior to year-end.

Management’s preference is provided by the client’s CFO, who meets with the auditor and

indicates that management intends to record an accrual that will only cover highly-certain claims.

Further, she expresses concern that a large accrual could attract media attention and generate

unwarranted lawsuits from parties inconvenienced by the blast. Management records an estimate

that fully implements their preference. Audit evidence related to the potential claims for the

explosion indicate that management’s estimate is at the aggressively-low end of the range of

potential estimates. Management’s preference for an aggressively-low estimate constitutes a

biasing influence if it is assimilated into the auditor’s assessment of the recorded estimated.

Experiment one tests the effect of an independent estimate and the effect of independently

evaluating management’s preference. This experiment uses a 1x4 experimental design. In

treatment one (the control), participants receive management’s preference before evaluating

estimate evidence. The remaining treatments are identical to the control treatment with the

following exceptions: treatment two participants develop an independent estimate; treatment

three participants independently evaluate management’s preference without a mindset

instruction; and treatment four participants independently evaluate management’s preference and

are instructed to use a skeptical mindset.

We find that 69 percent of the auditors who develop an independent estimate indicate that the

company’s liability surpasses the client’s preferred estimate by an amount greater than

performance materiality (tolerable error). As expected, these auditors are less likely to accept

management’s aggressive estimate than are auditors in the control treatment. However, counter

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to expectations, auditors who independently evaluate management’s preference assess

management’s aggressive estimate no differently than do auditors in the control treatment,

regardless of the skepticism prompt.

Experiment two tests the effect of preference timing and replicates experiment one’s test of

independently evaluating management’s preference. This experiment also uses a 1x4

experimental design. Again, treatment one participants receive management’s preference before

evaluating estimate evidence (the control). The remaining treatments are identical to the control

treatment with the following exceptions: treatment two participants independently evaluate

management’s preference using a skeptical mindset before evaluating estimate evidence

(replication); treatment three participants receive management’s preference after evaluating

estimate evidence; and treatment four participants receive management’s preference after

evaluating estimate evidence and independently evaluate management’s preference. We find that

auditors receiving management’s preference after evaluating estimate evidence, regardless of

whether they evaluate management’s preference, are significantly less likely to accept

management’s aggressive estimate than are auditors in the control treatment. However, identical

to experiment one, we again observe no difference between auditors who independently evaluate

management’s preference and auditors in the control treatment.

Our third study is a field study designed to analyze why independently evaluating

management’s preference failed to reduce the biasing influence of management’s preference.

Across the first two experiments, we find that about 90 percent of the auditors evaluating

management’s preference indicate that the preference lacks conservatism and reasonableness.

Yet, of this group, about one-half are accepting of an estimate that fully implements

management’s preference. We investigate this result by focusing on the characteristics of

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auditors who recognize management’s preference as unreasonable yet still accept the client’s

preferred estimate.

In this study, all participants first evaluate management’s preference with a skeptical mindset

instruction then evaluate estimate evidence, a task identical to the treatment replicated in the first

two experiments. We find that personality traits influence professional judgment. Auditors low in

conscientiousness and/or high in openness demonstrate the dissonance of accepting

management’s estimate, despite evaluating the related preference as unreasonable. We also find

that auditors who weakly attempt to eliminate management’s preference from their judgment

demonstrate such dissonance. Finally, we find that auditors with a weak sense of auditor-client

independence also demonstrate such dissonance. In summary, we find that ex ante recognition of

an unreasonable management preference is necessary, but not sufficient, to mitigate the

preference’s biasing influence. Sufficiency appears dependent on specific auditor characteristics.

Our results indicate that auditors can act to reduce the biasing influence of management’s

preference. Professional guidance suggests that developing an independent estimate will de-bias

the effect of management’s preference. We provide evidence that, in general, it does. We extend

the literature on the timing of management’s preference, finding that evaluating estimate

evidence before receiving management’s preference mitigates the preference’s biasing influence.

New to both the accounting and psychology literatures, we find that evaluating management’s

preference as unreasonable, before assessing the estimate, fails to mitigate the preference’s

biasing influence about 50 percent of the time. Further, in a follow-up study, we identify the

characteristics of auditors susceptible to such dissonance. Our findings should be of interest to

audit firms in terms of both hiring and training, and to audit regulators in understanding the

recurrence of estimate-related audit deficiencies (PCAOB 2013).

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II. BACKGROUND AND THEORY

Audit research finds that explicit client preferences often bias auditor judgments

(Hackenbrack and Nelson 1996; Salterio and Koonce 1997; Gramling 1999; Nelson, Elliot, and

Tarpley 2002; Jenkins and Haynes 2003). Though auditors are incentivized to avoid biased

judgment, due to litigation, reputation loss, and PCAOB sanctions, management’s preference

still biases auditors when they evaluate accounts characterized by imprecision (Gibbins, Salterio,

and Webb 2001; Nelson et al. 2002). Kennedy (1995) contends that auditors are influenced by

management’s preferences, because they are unable to ignore them. We address this contention.

We argue that management’s preference is irrelevant information, because auditor judgment

should be based on relevant audit evidence. Bless and Schwarz (2010) theorize and find that the

effect of irrelevant information on a judgment depends on how people use the irrelevant

information. If irrelevant information is cognitively integrated with other evidence, the irrelevant

information is used to form an understanding of the matter and assimilated into the target

judgment. Conversely, if irrelevant information is cognitively separated from relevant evidence,

the irrelevant information becomes a comparison standard and the target judgment is contrasted

away from the irrelevant information. Theory indicates that the effect of irrelevant information

differs dependent on its use in the judgment process.

A number of factors can determine how irrelevant information is used in the judgment

process (Bless and Schwarz 2010). One such factor is the distinctiveness of the irrelevant

information (Helson 1964; Herr 1986; Wilcox et al. 2011). When irrelevant information is

indistinct, meaning that no boundaries separate the irrelevant information from relevant

evidence, a significant literature indicates that the irrelevant information is assimilated into the

judgment (DeCoster and Clay 2004). However, when boundaries around irrelevant information

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are made distinct, people recognize the irrelevant information and determine whether it is

representative of relevant evidence. As such, when irrelevant information is both distinct and at

odds with representativeness, judgments are contrasted away from the biasing influence of the

irrelevant information (Bless and Schwartz 2010; Wilcox et al. 2011).

We study management’s preference for an aggressive accounting estimate when the estimate

is characterized by uncertainty. In this setting, an estimate is particularly susceptible to the

biasing influence of management’s preference (PCAOB 2008, 2010; Christensen, Glover, and

Wood 2012; Griffith et al. 2015; Wolfe, Christensen, Fitzgerald, Newton, Vandervelde 2015).

Within this context, we analyze techniques that an auditor can use to make the information in

management’s preference distinct, thereby mitigating the preference’s biasing influence.

Developing Independent Expectations

ISA 540 (2008) indicates that auditors can overcome management’s bias in the audit of

accounting estimates by developing an independent expectation of the client’s estimate. This

professional guidance assumes that auditors can develop a truly independent estimate in the

presence of a management bias (Griffith et al. 2015). While Wolfe et al. (2015) find that auditors

developing independent estimates are biased by information in management’s estimation

process, they do not specifically examine the biasing influence of a stated management

preference. Ex ante, it is unclear whether developing an independent estimate, after having

received management’s preference, will bias the auditor’s independent estimate and ultimately

bias the auditor’s assessment of management’s estimate.

If auditors are independent when developing their expectations, we expect that auditors

evaluate estimate evidence using standards of conservatism and reasonableness. The resulting

independent estimate would stand in contrast to management’s preference for an aggressive

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estimate, making the preference distinct and recognizable as an unwanted influence. Conversely,

if auditors assimilate management’s preference for an aggressive estimate into the development

of their independent estimate, we expect that auditors develop a biased independent estimate.

When this occurs, management’s preference does not become distinct and auditor judgment is

biased by the preference. In summary, we expect that an auditor’s independent estimate can

make management’s preference distinct, mitigating the biasing influence of the preference when

the auditor’s estimation process is itself unbiased. Accordingly, we hypothesize:

H1: When auditors’ independent estimates are unbiased by management’s preference, auditors who develop an independent estimate, after receiving management’s preference for an aggressive estimate, assess an aggressive estimate as less reasonable than do auditors who do not develop an independent estimate.

Independently Evaluating Management’s Preference

Empirics from the psychology literature indicate that independently evaluating irrelevant

information, before making the actual judgment, results in people contrasting their judgment

away from the irrelevant information (Martin and Seta 1983; Weary et al. 2001). In the

accounting literature, recent research by Elliot, Jackson, Peecher, and White (2014) produce

similar findings. Specifically, they study the effect of corporate social responsibility reports on

firm valuation. Their results indicate that students who independently evaluate a firm’s corporate

social responsibility report before doing firm valuation are less influenced by corporate social

responsibility when valuing the firm.

Elliot et al. (2014) attribute their findings to students recognizing their affective response to

corporate social responsibility information and correcting for it. The psychology literature

indicates a more complex relation between affect and independently evaluating irrelevant

information. Schwartz and Clore (2007) suggest that affect is triggered and becomes a basis for

judgment only when the distinctiveness of irrelevant information is highly assessable in one’s

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cognition. In support, Weary et al. (2001) find that an affective response derived from

independently evaluating irrelevant information is not required for the evaluation to de-bias.

Given the robustness of this technique, we expect that, when auditors evaluate management’s

preference for an aggressive estimate before evaluating estimate evidence, they analyze the

preference in its own right, recognizing the preference’s aggressiveness. This recognition should

make management’s preference distinct from estimate evidence, creating a comparison standard

and causing auditors to contrast their judgment away from management’s preference.

Accordingly, we hypothesize:

H2: Auditors who evaluate management’s preference for an aggressive estimate, prior to evaluating management’s aggressive estimate and the related estimate evidence, assess the estimate as less reasonable than do auditors who do not evaluate management’s preference.

The Timing of Management’s Preference

A significant literature has studied how the timing of irrelevant information affects the

biasing influence of irrelevant information. Within accounting, Wilks (2002) finds that auditors

who receive a partner’s view, before the evaluating audit evidence, make judgments more

consistent with the partner’s view then do auditors who receive the partner’s view after

evaluating the audit evidence. Ricchiute (2004) finds similar results studying accounting expert

witnesses and verdict preference hints. Jenkins and Haynes (2003) find that auditors receiving

management’s preference about a contingent liability disclosure, before evaluating evidence

about the contingent liability, make judgments more consistent with management’s disclosure

preference than do auditors who receive management’s disclosure preference after reviewing

evidence about the contingent liability. However, Jenkins and Haynes (2003) do not observe any

effect for the timing of management’s preference if the preference and related judgment involve

receivable collectability.

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Jenkins and Haynes (2003) argue that their receivable collectability case has audit evidence

that is too strongly opposed to management’s preference, but they conclude that further research

is needed to better understand management preference timing effects in measurement tasks. We

extend the literature on the timing of management’s preferences with our study of another

measurement task, assessing the reasonableness of an accounting estimate. Similar to the

contention of Jenkins and Haynes (2003), we expect that uncertainty in the audit evidence is a

necessary condition for management’s preference to influence auditor judgment, and uncertainty

commonly defines accounting estimates. When auditors receive management’s preference for an

aggressive estimate before evaluating estimate evidence, we expect that they use the preference

to evaluate and understand estimate evidence, resulting in the assimilation of management’s

preference. Conversely, when auditors first evaluate estimate evidence, they categorize estimate

evidence with the estimate judgment. As such, when auditors subsequently receive

management’s preference, it stands alone, becoming distinct and creating a comparison standard

that causes auditors to contrast their judgment away from management’s preference.

Accordingly, we hypothesize:

H3: Auditors who evaluate estimate evidence before receiving management’s preference for an aggressive estimate, assess management’s aggressive estimate as less reasonable then do auditors who receive management’s preference and then evaluate estimate evidence.

III. METHODS

This research contains three studies: two experiments and a field study. The studies use

senior auditors from all the Big 4 public accounting firms. We surveyed audit partners from

several different firms who indicated that senior auditors would likely be the first to analyze an

estimate similar to the one evaluated in our studies, and that they consider this initial assessment

critical to the audit. These observations are consistent with research indicating that seniors are

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heavily involved in the audit of accounting estimates and that senior assessments influence the

judgments of managers and partners (Ricchiute 1999; Griffith et al. 2015).

Audit Case

Each of the three studies uses the same case-based task.1 In the case, an auditor evaluates an

estimate (loss accrual) for costs that the client will incur due to an explosion at the client’s

facility just prior to year-end. The explosion damaged client property, interrupted the client’s

business, and created health issues for the client’s employees. The property, continuing

operations, and employees of the neighboring businesses were affected in a similar manner.

Management’s preference is communicated to the case’s auditor when the CFO meets with

the auditor. The CFO prefers an accrual covering only high-certainty claims, including medical

costs for injured employees and damage to buildings and inventory. She expresses concern that a

large accrual would attract media attention and generate unwarranted lawsuits from parties

inconvenienced by the blast. Management’s preference to only accrue for highly-certain claims

constitutes a biasing influence.

Auditors are informed that the client has recorded an estimate accruing only for highly-

certain claims, fully implementing management’s preference. Auditors also receive a memo from

management identifying all potential claims and the expected liability range for each claim.

Claims in the memo are determined by outside attorneys and other experts. The materials note

that the auditor in the case tests management’s list of potential claims, concluding that the

claims’ listing is complete and that the claims’ liability ranges appear reasonable. The client’s

total estimated liability ranges from a low estimate of $0.785M to a high estimate of $2.775M.

Management’s preferred estimate is at the aggressively-low end of the liability range, $1.25M.

1 Our case is adapted from an experimental case used in Wolfe et al. (2015).

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Planning materiality is set at $400K and performance materiality (tolerable error) is set at

$275K. The key dependent variable in each of the three studies asks auditors to indicate the

likelihood that the case’s auditor will assess management’s $1.25M estimate as reasonable,

measured with scale anchors of ‘Not Likely’ (0) and ‘Very Likely’ (10).

Participants

Table 1 presents the participant profile. Across the three studies we collect 263 usable

responses. The auditors in our studies had an average 36.69 months (3 years) of experience. They

assessed their familiarity with accounting estimates high at an average of 7.13 on a scale

anchored on “not familiar” (0) and “very familiar” (10). On average, they audited accounting

estimates five or six times (5.65) and served four audit clients (4.06) per year. Finally, they

assessed their understanding of the case materials high at an average of 7.37 on a scale anchored

on “not well” (0) and “very well” (10). These demographics and self-assessments do not vary

across treatments in either experiment (all p-values > 0.10). While auditor demographics and

self-assessments differ between studies, replicated elements across the three studies indicate

consistent judgment by the auditors in our studies.

***** Insert Table 1 *****

IV. RESULTS

Study One

This study is an experiment populated by 57 Big 4 senior auditors.2 We use a 1x4

experimental design. The first treatment group (the control) reviews management’s preference

for an aggressive estimate and then reviews management’s aggressive estimate along with the

related audit evidence. The second treatment is identical to the control except that this treatment

2 In study one, 63 auditors participate, but we drop 6 auditors due to incomplete responses, leaving a final sample of 57 auditors.

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develops an independent estimate. For participants in this treatment, we require that they

estimate the liability for each potential claim related to the explosion and sum them to form their

independent estimate (Appendix B). The third and fourth treatments are identical to the control

except that each of these treatment groups evaluates management’s preference before reviewing

estimate evidence. These auditors are prompted to provide a short written evaluation of

management’s preference as follows:

Review [the CFO’s] statements and evaluate whether [the CFO] exhibits conservatism and/or reasonableness with regard to her position on the explosion’s liability. Review [the CFO’s] statements with a skeptical mindset and evaluate whether [the CFO’] fails to demonstrate conservatism and/or reasonableness with regard to her position on the explosion’s liability.

The first prompt, for the third treatment, is mindset neutral. The second prompt, for the fourth

treatment, indicates the need for a skeptical mindset. We analyze two different mindset

instructions to inform whether presumptive doubt is required when evaluating management’s

preference (Nelson 2009).

Hypotheses Tests

Hypothesis H1 states that auditors who develop unbiased independent estimates, after

receiving management’s preference for an aggressive estimate, assess an aggressive estimate as

less reasonable than do auditors who do not develop an independent estimate. Our findings

support H1. We find that 11 of 16 auditors develop estimates that differ from management’s

estimate by an amount greater than performance materiality, indicating that their estimates are

unbiased by management’s preference to accrue only for highly-certain claims. Auditors in the

control treatment assess management’s estimate as more reasonable than do the 11 auditors

developing unbiased independent estimates (4.071 vs. 1.546, t = 3.278, one-tailed p = 0.003,

Table 2). Our results indicate that most auditors’ independent estimates are indeed independent.

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Further, developing an independent estimate appears to make auditors evaluate estimate evidence

against their own standards of conservatism and reasonableness. Thus, management’s preference

becomes distinct and auditors contrast their judgment away from the preference’s biasing

influence.3

***** Insert Table 2 *****

We observe no difference between the control and auditors developing unbiased independent

estimates in their certainty of estimate reasonableness, perceived effort eliminating

management’s preference from their analysis, or in their assessed importance of claims. These

findings suggest that auditors do not recognize their inability to act independently of

management’s preference. Finally, we observe that auditors developing unbiased independent

estimates are less happy/pleased with management’s preference than are auditors in the control

treatment (1.955 vs. 3.786, t = 3.065, two-tailed p = 0.006, Table 1). As shown in Figure 1,

happy/pleased partially mediates the effect of developing an unbiased estimate on the assessment

of management’s estimate. This finding indicates that developing an unbiased independent

estimate makes the unreasonableness of management’s preference both distinct and cognitively

accessible, producing an affective response that influences auditor assessment.

***** Insert Figure 1 *****

Hypothesis H2 states that auditors who evaluate management’s preference for an aggressive

estimate, prior to evaluating management’s aggressive estimate and the related estimate

evidence, assess the estimate as less reasonable than do auditors who do not evaluate

3 Five of the 16 auditors developed estimates lower than management’s estimate. These auditors assess estimate reasonableness similar to auditors in the control (4.071 vs 4.400, t = 0.289, two-tailed p = 0.778, untabulated) and dissimilar to auditors with estimates greater than management’s estimate (4.400 vs. 1.545, t = 3.150, two-tailed p = 0.028, untabulated). Regardless, when we analyze all auditors who develop an independent estimate, we continue to find a difference between the control and independent estimate treatment (4.071 vs. 2.438, t = 1.899, one-tailed p = 0.036, Table 2).

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management’s preference. Our findings do not support H2. Auditors in the control treatment

assess management’s estimate no differently than do auditors evaluating management’s

preference, regardless of whether the evaluation prompted a neutral mindset (4.071 vs. 5.583, t =

1.184, one-tailed p = 0.125, Table 2) or a skeptical mindset (4.071 vs. 4.867, t = 0.715, one-tailed

p = 0.241, Table 2). We also do not observe differences between the control and the preference

evaluation treatment groups in their certainty of estimate reasonableness, perceived effort

eliminating management’s preference from their analysis, the assessed importance of claims, or

in affect directed at the client preference.4

In summary, we find that independent estimate development usually mitigate the effect of

management’s preference for an aggressive estimate, but independently evaluating

management’s preference after receiving it does not. Given that our finding for preference

evaluation is at odds with both theory and empirics, we analyze the written preference

evaluations. Of the 27 auditors providing preference evaluations, 23 (85.2 percent) recognize that

management’s preference for an aggressive estimate lacks conservative and reasonableness.

Further, we find that auditor preference evaluations are strong, as this example demonstrates:

…[The CFO] fails to demonstrate conservatism and reasonableness. No concern or projection for long term impact or consideration of immediate lawsuit. No indication of including third party legal or environmental experts.5

As such, we replicate the independent preference evaluation manipulation in our second study to

determine if our findings are sample specific.

4 We observe a marginally significant difference between the control and the neutral preference evaluation treatment on happy/pleased (3.786 vs. 2.417, t = 1.802, two-tailed p = 0.077, Table 2). However, we observe no effect of happy/pleased on the assessment of management’s estimate (t = 1.270, two-tailed p = 0.212, untabulated). 5 Comments by the auditors are very similar. Further, the auditor making this comment strongly supported the client’s estimate that wholly implemented management’s preference.

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Study Two

This study is also an experiment, and it is populated by 112 Big 4 senior auditors.6 We again

use a 1x4 experimental design. Identical to our first study, the first treatment group (the control)

reviews management’s preference for an aggressive estimate and then reviews management’s

aggressive estimate along with the related audit evidence. Also identical to our first study, the

second treatment differs from the control by requiring an evaluation of management’s preference

using a skeptical mindset, before reviewing the related audit evidence. The third and fourth

treatments differ from the control in the ordering of management’s preference and the review of

management’s estimate and related audit evidence. In the third treatment, auditors review

management’s estimate and the related audit evidence before receiving management’s preference

for an aggressive estimate. The fourth treatment is identical to the third except that auditors in

this treatment group also evaluate management’s preference using a skeptical mindset.

Hypotheses Tests

We retest H2, which states that auditors who evaluate management’s preference for an

aggressive estimate, prior to evaluating management’s aggressive estimate and the related

estimate evidence, assess the estimate as less reasonable than do auditors who do not evaluate

management’s preference. Again, our findings do not support H2. Auditors in the control

treatment group assess management’s estimate no differently than do auditors independently

evaluating management’s preference (5.138 vs. 5.133, t = 0.006, one-tailed p = 0.498, Table 3).

Also similar to our first study, we do not observe differences between the control and the

preference evaluation treatment group in other measures related to assessing the estimate. This

finding suggests that our results are not sample specific.

6 In study two, 115 auditors participate, but we drop 3 auditors due to incomplete responses, leaving a final sample of 112 auditors.

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***** Insert Table 3 *****

Hypothesis H3 states that auditors who evaluate estimate evidence before receiving

management’s preference for an aggressive estimate, assess management’s aggressive estimate

as less reasonable then do auditors who receive management’s preference and then evaluate

estimate evidence. Our findings support H3. Auditors in the control treatment group assess

management’s estimate as more reasonable than do auditors who receive management’s estimate

and the related audit evidence before receiving management’s preference, regardless of whether

they do not evaluate management’s preference (5.138 vs. 3.667, t = 2.184, one-tailed p = 0.017,

Table 3) or evaluate it (5.138 vs. 3.826, t = 1.821, one-tailed p = 0.038, Table 3). Unlike Jenkins

and Haynes (2003), we find that the timing of management’s preference can mitigate a

preference’s biasing influence on a measurement task.

We observe no difference between the control and the timing difference treatments in their

certainty of estimate reasonableness, perceived effort eliminating management’s preference from

their analysis, or in the assessed importance of claims. Again, our findings suggest that auditors

do not recognize their inability to act independently. Finally, we find that auditors who evaluate

estimate evidence before receiving management’s preference and then evaluate the preference,

are less happy/pleased with management’s preference than are auditors in the control treatment

group (1.891 vs. 3.793, t = 3.553, two-tailed p = 0.001, Table 3). As shown in Figure 1,

happy/pleased fully mediates the timing difference effect on the assessment of management’s

estimate, but only when a timing difference is combined with preference evaluation. This finding

indicates that evaluating the preference made its unreasonableness cognitively accessible to the

auditor, eliciting an affective response (Schwartz and Clore 2007).7

7 Angry/disappointed with management’s preference is higher for auditors evaluating estimate evidence before receiving management’s preference when the preference is not evaluated (4.433 vs. 3.207, t = 1.956, two-tailed p =

19

Study Three

In the first two experiments, we find that 51 of 57 (90 percent) auditors asked to

independently evaluate management’s preference, before reviewing estimate evidence, evaluate

the preference as lacking conservatism and reasonableness. However, 51.0 percent of the 51

auditors who evaluate management’s preference as unreasonable accept its implementation in the

client’s preferred estimate.8 This finding indicates that explicit recognition of a biasing influence

does not necessarily cause auditors to attempt some form of bias mitigation, suggesting that

certain auditors are more likely to accept management’s estimate. Accordingly, study three

analyzes how auditor characteristics (individual differences) influence the relation between

independently evaluating management’s preference and estimate assessment. Participants in this

study consist of 94 Big 4 senior auditors.9

Study three’s task is identical to the skeptical mindset preference evaluation treatment

replicated across studies one and two. In this task, auditors first receive management’s

preference and evaluate the preference with a skeptical mindset, then receive management’s

estimate and the related estimate evidence. Following the task, we ask participants to complete

the following: a mind map depicting their thought process in assessing estimate reasonableness,

the Identification of Other-in-Self scale (IOS) to assess perceptions about the auditor-client

relationship (IOS – Client) and professional responsibilities (IOS – Profession), and several

individual difference scales including the Wonderlic Personnel Test (WPT), the Cognitive

Reflection Test (CRT), the Rational/Experiential Index (REI), the Need for Cognition scale

(NFC), the Five Factor Model (FFM), the Fear of Negative Evaluation scale (FNE), and the 0.053, Table 3) or evaluated (5.304 vs. 3.207, t = 3.119, two-tailed p = 0.002, Table 3). However, angry/disappointed never acts as a mediator. 8 Accept indicates an assessment of six or above on the 0-10 point assessment scale. 9 In study three, 98 auditors participate but we drop 4 auditors due to incomplete responses, leaving a final sample of 94 auditors.

20

Indecisiveness scale (IND). These scales capture cognitive ability and thinking style (WPT,

CRT, REI, and NFC) and personality traits (FFM, FNE, and IND). A description of each is

provided in Appendix A, and construct validity tests are shown in Appendix C for scales with

multiple measures. Given the absence of empirics or theory that would explain why an auditor

would evaluate a preference as unreasonable and then accept its implementation, we offer a

research question:

R1: Do individual differences explain why auditors evaluate management’s preference for an aggressive estimate as unreasonable but then accept its implementation?

Of the 94 auditors responding to our study, 81 (86.2 percent) independently evaluate

management’s preference as unreasonable, and 51.9 percent of this group accept its

implementation, which is similar to our two previous studies. We drop 11 of the 81 auditors from

our model, shown in Figure 2, due to missing individual difference responses. Four of the 11

failed to complete multiple individual difference measures, six failed to provide their perception

of auditor-client independence (IOS – Client), and one failed to complete elements of the Five

Factor Model (FFM). We performed tests to determine differences between the 13 auditors who

independently evaluate management’s preference as acceptable, the 11 auditors who failed to

complete all individual difference measures, and the 70 auditors who populate or model. We

observe no statistically significant differences for the individual differences measured across

these three groups. Descriptive statistics for the individual differences are shown in Table 4, and

the correlation matrix for the variables in Figure 2 is shown in Appendix D.

***** Insert Figure 2 and Table 4 Here *****

As shown in Figure 2, we find that the personality trait of openness influences the likelihood

of assessing management’s estimate as reasonable. Greater openness indicates imagination and

curiosity, whereas lower scores are associated with individuals who act conventionally and

21

conservatively (Parkinson and Taggar 2006). We find that higher openness, which indicates a

lack of conservatism, leads auditors to accept management’s estimate in the face of concern

about management’s preference. As shown in Figure 2, other influential individual differences

work through auditor certainty of estimate reasonableness. As expected, when auditors become

more certain of estimate reasonableness, they are more likely to assess it as reasonable.

We find that auditors who attempt to eliminate management’s preference from their

judgment become less certain of the reasonableness of management’s estimate (indirect path to

estimate assessment, t = 2.25, two-tailed p = 0.024, untabulated). Similar to findings in our first

two experiments, we find a strong positive relation between happy/pleased with management’s

preference and certainty of estimate reasonableness. This finding is consistent with ‘affect as

information’ (Elliot et al. 2014). More specifically, this finding indicates that auditors who

evaluate management’s preference as unreasonable, and cognitively access the significance of

the preference, develop and use their emotions in assessing management’s aggressive estimate

(Schwartz and Clore 2007).

We find that auditors who do not cognitively access the significance of the unreasonable

management preference lack a strong innate perception of auditor independence and/or are low

on the personality trait of conscientiousness. We find that as perceived closeness of the client-

auditor relationship increases (IOS – Client), auditors become more happy/pleased with

management’s preference. Conscientiousness indicates organized, consistent, striving, and self-

disciplined facets of personality, and higher conscientiousness reduces how happy/pleased

auditors are with management’s preference. Both the perceived closeness of the client-auditor

relationship (t = 1.85, two-tailed p = 0.064, untabulated) and conscientiousness (t = 2.08, two-

22

tailed p = 0.038, untabulated) anchor statistically significant indirect paths to the estimate

reasonableness assessment.

The willingness to evaluate a preference one way, and assess its implementation another does

not appear related to cognitive ability. We observe no modeling significance for any of our

cognitive ability or thinking style measures (WPT, CRT, REI, and NFC). Further, neither fear of

negative evaluation (FNE) nor indecisiveness (IND) is influential. We also observe no modeling

significance for the perceived relationship between auditor and profession (IOS – Profession).

With regard to the mind map, we find that 22 percent of the auditors contemplate bias/materiality

when considering estimate reasonableness, and 78 percent of the auditors contemplate estimate

components when considering estimate reasonableness.10 We find no difference in estimate

reasonableness assessments between auditors who contemplate bias/materiality and those

contemplating estimate components (5.214 vs. 5.140, t = 0.875, two-tailed p = 0.843,

untabulated).

V. DISCUSSION

Our results indicate that auditors can act to reduce the biasing influence of management’s

preference. In an accounting estimate setting, we find that a majority of auditors develop

independent estimates unbiased by management’s preference, and that independent estimate

development mitigates the biasing influence of management’s preference. We also find that

when auditors can avoid the receipt of management’s preference until after the review of audit

evidence, the biasing influence of management’s preference is mitigated. However, counter to

findings in both the psychology and accounting literatures, we find that evaluating

management’s preference as unreasonable, before reviewing audit evidence, does not necessarily

10 A mind map diagrams the thought process using short words and phrases centered on the identified topic (Wheeldon 2010). Of the 70 auditors used to construct the Figure 2 model, 64 performed mind maps. We code their responses based on two themes, bias/materiality and estimate components.

23

mitigate the preference’s biasing influence. Instead, we find that specific auditor characteristics

determine whether an auditor, who recognizes a unreasonable management preference, rejects

the client’s estimate that implements the preference.

Our results also inform theory. When auditors receive and evaluate management’s preference

after reviewing estimate evidence, it reduces positive affect related to management’s preference,

which then feeds into their assessment of management’s estimate. Conversely, auditors who only

receive management’s preference after reviewing estimate evidence do not experience a

reduction in positive affect, yet still contrast their judgment away management’s preference. Our

findings indicate that preference timing’s ability to mitigate the biasing influence of

management’s preference is not contingent on an affective response. Further, our findings

indicate that an affective response to an unreasonable management preference can influence

auditor judgment, but this occurs only when the unreasonableness of the preference is very clear

to the auditor (i.e. when it is cognitively accessible).

Our results also indicate that recognizing the unreasonableness of a management preference

does not necessarily lead to rejecting an aggressive estimate that implements management’s

preference. This suggests that recognizing preference unreasonableness does not necessarily

equate to recognizing a preference’s potential biasing influence. Our results indicate that auditors

who recognize an unreasonable preference and contrast their judgment away from it are more

conscientious, more conservative, and have a greater sense of independence from client.

Our study is subject to limitations. First, the participants in our study are senior auditors, so

our results are specific to senior auditors. Further, auditor/client interactions are rich, but they are

necessarily restricted in this study due to time limits on access to participants. In addition, our

case materials involve the evaluation of an accrual estimate. Our results may not generalize to

24

the evaluation of other types of estimates, such as assessing the reasonableness of fair value

disclosures. We also note that audits are conducted in a team environment. We do not capture

dynamic team interactions. However, audit seniors’ initial judgments have been shown to

influence reviewing auditors’ judgments (Ricchiute 1999). The audit seniors in our study had

experience auditing accounting estimates. Interviews with practitioners indicate that seniors are

capable of addressing the issues in our case and that their individual judgments are important to

the audit.

In summary, we note that our findings are important to practice. We demonstrate the efficacy

of developing independent estimate expectations and reviewing audit evidence before receiving

management’s preference. We inform firm training and hiring with our study of auditor

characteristics that lead to the dissonance of assessing management’s preference as unreasonable,

but still accepting its implementation. Finally, we provide insight into a problem noted by audit

regulators, deficiency reoccurrence in the audit of accounting estimates (PCAOB 2013). Client-

management is not necessarily trying to bias auditors with their preferences. However,

management’s preferences will in many, if not most, cases benefit management. If auditors are to

provide independent judgments, then they must avoid the biasing influence of management’s

preference. Our findings inform such avoidance.

25

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FIGURE 1 The Mediating Effect of Auditor Affect

Regression beta coefficients reported. *, **, and *** represent significance levels of 0.10, 0.05, and 0.01, respectively. IV = independent variable; DV = dependent variable. IVs are dichotomous variables in which the shown item is set to one for the specified treatment group. IV significance tests are one-tailed, and all others are two-tailed tests. All other variables are defined in Appendix A. a The independent estimate variable only includes auditors who developed independent estimates greater than performance materiality (tolerable error). Including all auditors who developed independent estimates produces results inferentially similar to those reported.

D. 1. 0.763*** 2. 0.799*** 3. 0.543***

C. 1. -1.831*** 2. -0.426 3. -1.902***

Happy/Pleased w/ Client

Preference Mediator

Estimate Reasonableness

DV

1. Independent Estimate a 2. Preference after evidence, do not

evaluate client preference 3. Preference after evidence, evaluate

client preference IV

B. 1. -1.526*, 0.546** 2. -1.145**, 0.766*** 3. -0.358, 0.502**

A. 1. -2.526*** 2. -1.471** 3. -1.321**

Legend: A. DV = f(IV) B. DV = f(IV, Mediator) C. Mediator = f(IV) D. DV = f(Mediator)

30

FIGURE 2 The Effect of Individual Differences on Auditor Assessment of Estimate Reasonableness

Path coefficients (t-statistics) reported. *, **, and *** represent two-tailed significance at 0.10, 0.05, and 0.01, respectively. Refer to Appendix A for variable definitions.

The model is estimated based the sample of auditors who evaluated management’s preference as lacking conservatism and reasonableness. Table 4 provides descriptive statistics for this sample. Parameter estimation is based on covariance matrices. Model fit is assessed with the Tucker-Lewis index (TLI) = 0.947, the comparative fit index (CFI) = 0.922, and the root mean square error of approximation (RMSEA) = 0.061.

We perform several robustness tests on the model presented above. First, we re-estimate the model excluding IOS-Client. Next, we re-estimate the structural model while constraining paths of the measurement model to the values shown above. We also alternate the fixed path across the three measures of each latent factor. Finally, we simulate the number of observations to double or triple the sample size and re-estimate the model using factor scores and measure averages. Results are inferentially identical in all instances.

0.68*** (4.89)

-0.77*** (2.55)

0.33** (2.18)

-0.22** (2.31)

FFM_cons_M3

0.58** (2.29)

0.47*** (3.85)

0.84*** (8.74)

Happy/Pleased w/management’s

preference

Estimate Reasonableness

FFM_cons_M5

FFM_cons_M8

1.00

FFM_open_M2

FFM_open_M3

FFM_open_M7

1.00

Certainty of accrual reasonableness

Attempt to eliminate management’s

preference

0.53*** (3.46) 0.80***

(3.77)

FFM – Conscientiousness

FFM

Openness

0.64*** (4.89) FFM –

Openness

IOS – Client (Perceived Independence)

31

TABLE 1 Participant Profile

Mean Diff. F-stat a Study One Study Two Study Three Total

Number of auditor participants 57 112 94 263

Months of audit experience 47.74 (16.05)

27.57 (7.39)

40.85 (16.77)

36.69 (15.70)

49.86*** b

Familiarity with accounting estimates 7.75 (1.56)

6.75 (1.56)

7.20 (1.60)

7.13 (1.62)

7.82*** c

Number of times auditing accounting estimates7.51

(3.12) 4.43

(2.87) 5.96

(3.14) 5.65

(3.24) 20.23*** d

Number of audit clients per year 3.88 (2.80)

3.80 (1.82)

4.48 (2.08)

4.06 (2.17)

2.77* e

Understanding of estimate case materials 7.67 (2.01)

7.44 (1.80)

7.08 (1.63)

7.37 (1.80)

2.02

Mean (standard deviation) reported. Self-assessments are made on 11-point scales with 10 (0) representing a high (low) level of familiarity and understanding. In studies one and two, self-assessments and demographics do not differ across experimental conditions (p > 0.10).

a Reports F-Statistics from the one-way ANOVA comparing the mean responses across all three studies. *, **, and *** represent two-tailed significance at 0.10, 0.05, and 0.01, respectively. Significant differences across studies investigated using Bonferroni (Games-Howell) post-hoc analysis in the presence of equal (unequal) variance based on Levene’s test.

b The means differ significantly from each other across all three studies based on Games-Howell post-hoc analysis (p < 0.05 in all comparisons).

c The mean of study 1 differs from the mean of study 2 based on a Bonferroni post-hoc analysis (p < 0.01).

d The means differ significantly from each other across all three studies based on Bonferroni post-hoc analysis (p < 0.01 in all comparisons).

e The mean of study 2 differs from the mean of study 3 based on a Games-Howell post-hoc analysis (p < 0.05).

32

TABLE 2 Study One – The Effect of Independent Estimates and Preference Evaluation

Preference Received Before Evidence Review

Independent Estimate

Evaluate Preference Control (Neutral) (Skeptical) Mean Contrasts (t-value) c ANOVA

Variable a 1 2 2b 3 4 1 vs. 2 1 vs. 2 b 1 vs. 3 1 vs. 4 F-Value

Estimate Reasonableness 4.071 2.438 1.546 5.583 4.867 1.899** 3.278*** 1.184 0.715 3.190**

(2.731) (1.825) (0.820) (3.630) (3.284)

Certainty of Reasonableness 3.429 3.688 2.909 4.167 3.933 0.286 0.533 0.759 0.550 0.219

(2.277) (2.056) (1.446) (3.129) (2.463)

Attempt to Eliminate Bias 6.286 7.250 7.091 7.083 6.867 1.002 0.733 0.771 0.594 0.368

(2.431) (2.017) (2.256) (3.315) (2.774)

Happy/Pleased 3.786 2.438 1.955 2.417 2.679 1.907* 3.065*** 1.802* 1.516 1.574

w/ Client Preference (1.939) (1.825) (0.986) (1.607) (2.267)

Angry/Disappointed 3.714 4.313 5.182 5.375 3.964 0.611 1.377 1.577 0.247 0.942

w/ Client Preference (1.590) (2.732) (2.610) (3.016) (3.135)

Average Claim Importance 7.521 7.463 7.527 8.100 8.440 0.101 0.010 0.923 1.551 1.295

(1.495) (1.816) (1.402) (1.778) (1.234)

Evaluate as Unreasonable 10/12 13/15

n 14 16 11 12 15

Mean (standard deviation) reported for the four treatments. *, **, and *** represent significance levels of 0.10, 0.05, and 0.01, respectively. The ‘Estimate Reasonableness’ contrast t-statistic is adjusted for unequal variances. For the remaining variables, Levene’s test indicates equality of variance (p > 0.10). The final column contains the F-statistics for the one-way ANOVA upon which the contrasts are calculated. a ‘Evaluate as Unreasonable’ is the ratio of auditors who evaluate management’s preference as lacking conservatism and reasonableness to the total number of participants in the treatment group. Other variables are defined in Appendix A. b This column includes the subset of auditors developing an independent estimates that exceeded the client’s preferred estimate by an amount greater than performance materiality. c Due to the directional nature of the hypotheses, mean contrasts testing ‘Estimate Reasonableness’ are one-tailed. All other contrasts are two-tailed tests.

33

TABLE 3 Study Two – The Effect of Client Preference Timing and Preference Evaluation

Preference Received Before Evidence Review After Evidence Review

Evaluate Pref. Base Evaluate Pref. Control (Skeptical) Case (Skeptical) Mean Contrasts (t-value) b ANOVA

Variable a 1 2 3 4 1 vs. 2 1 vs. 3 1 vs. 4 F-Value

Estimate Reasonableness 5.138 5.133 3.667 3.826 0.006 2.184** 1.821** 2.577*

(2.722) (2.968) (2.440) (2.462)

Certainty of Reasonableness 4.448 4.367 3.600 3.696 0.139 1.446 1.196 1.088 (2.046) (2.400) (2.159) (2.420)

Attempt to Eliminate Bias 7.172 7.167 7.600 7.348 0.010 0.722 0.276 0.239 (1.853) (2.506) (2.078) (2.656)

Happy/Pleased 3.793 3.167 3.367 1.891 1.255 0.854 3.553*** 4.513***w/ Client Preference (1.948) (2.098) (1.912) (1.609)

Angry/Disappointed 3.207 4.250 4.433 5.304 1.663 1.956* 3.119*** 3.341**

w/ Client Preference (2.520) (2.735) (2.277) (1.923)

Average Claim Importance 7.921 8.013 7.639 8.255 0.220 0.669 0.740 0.659

(1.420) (1.467) (1.777) (1.803)

Evaluate as Unreasonable 28/30 19/23

n 29 30 30 23

Mean (standard deviation) reported for the four treatments. *, **, and *** represent significance levels of 0.10, 0.05, and 0.01, respectively. The ‘Estimate Reasonableness’ contrast t-statistic is adjusted for unequal variances. For the remaining variables, Levene’s test indicates equality of variance (p > 0.10). The final column contains the F-statistics for the one-way ANOVA upon which the contrasts are calculated. a Refer to Table 1 and Appendix A for variable definitions. b Due to the directional nature of the hypotheses, mean contrasts testing ‘Estimate Reasonableness’ are one-tailed. All remaining contrasts are two-tailed tests.

34

TABLE 4 Study Three – Descriptive Statistics for Auditor Individual Differences

Full Sample Recognized Bias Included in Figure 2 Model (n = 94) (n = 81) (n = 70) Mean Std. Dev. Median Mean Std. Dev. Median Mean Std. Dev. Median Estimate Reasonableness 5.240 2.835 6.000 5.090 2.753 6.000 5.200 2.706 6.000 Certainty of Estimate Reasonableness 6.220 2.603 6.000 6.220 2.607 6.500 6.170 2.571 6.000 Attempt to Eliminate Bias 4.320 2.302 4.000 4.260 2.276 4.000 4.390 2.254 4.000 Happy/Pleased w/ Client Pref. 3.202 2.005 3.000 3.117 1.962 3.000 3.264 1.950 3.000 Angry/Disappointed w/ Client Pref. 3.730 2.649 3.500 3.883 2.641 4.000 3.857 2.588 4.000 Average Claim Importance 7.715 1.484 7.700 7.659 1.482 7.700 7.716 1.497 7.750 IOS – Client 3.190 1.357 3.000 3.210 1.414 3.000 3.230 1.426 3.000 IOS – Profession 5.100 1.723 5.000 5.000 1.710 5.000 4.940 1.785 5.000 Wonderlic Personnel Test 27.410 5.397 27.000 26.940 5.266 27.000 27.070 5.320 27.000 Cognitive Reflection Test 1.460 1.103 2.000 1.400 1.161 1.000 1.420 1.177 1.500 FFM – Agreeableness 4.690 0.651 4.778 4.670 0.673 4.778 4.658 0.663 4.722 FFM – Conscientiousness 4.223 0.736 4.143 4.250 0.730 4.143 4.277 0.760 4.286 FFM – Emotional Stability 4.114 0.802 4.222 4.102 0.810 4.222 4.060 0.824 4.222 FFM – Extraversion 3.968 0.776 3.900 3.967 0.738 3.900 3.930 0.726 3.900 FFM – Openness 4.060 0.672 4.143 4.034 0.689 4.143 4.084 0.700 4.143 REI – Rational 4.401 0.866 4.500 4.394 0.894 4.750 4.373 0.913 4.750 REI – Experiential 4.305 0.857 4.200 4.298 0.877 4.200 4.296 0.901 4.200 Need for (Cognitive) Closure 4.171 0.702 4.214 4.158 0.707 4.214 4.119 0.718 4.143 Fear of Negative Evaluation 3.844 0.831 3.833 3.857 0.766 3.833 3.873 0.792 3.875 Indecisiveness 2.963 0.675 2.933 2.950 0.591 2.933 2.979 0.566 3.000

Mean, standard deviation, and median statistics presented for each variable included in study three. The full sample statistics reflect responses from all auditors who assessed estimate reasonableness. Statistics are also presented separately for auditors who evaluated management’s preference as lacking conservatism and reasonableness, and for the sample who made such an evaluation and responded to all measures required for analysis in Figure 2. Refer to Appendix A for variable definitions.

Significant differences across samples investigated using Bonferroni (Games-Howell) post-hoc analysis in the presence of equal (unequal) variance based on Levene’s test. No significant differences were noted in comparing responses of the 70 auditors included in Figure 2 to the responses of the 94 auditors in the full sample or to the responses of 81 auditors who recognized management’s bias.

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APPENDIX A Variable Definitions

All Studies Measured With 11-Point Scales (0 – 10)

Estimate Reasonableness The participant’s assessment of how likely the auditor in the case is to evaluate the client’s recorded $1.25M estimate as reasonable, anchored by not likely (0) and likely (10).

Certainty of Estimate Reasonableness

The participant’s assessment of how certain they were of the recorded estimate’s reasonableness, anchored by not certain (0) and highly certain (10).

Attempt to Eliminate Bias The participant’s assessment of how hard they tried to eliminate management’s preference from their judgment, anchored by not much (0) and large amount (10).

Happy/Pleased w/ Client Preference

The average of participant’s assessments of how happy and pleased they were about management’s stated preference related to the estimate, both scales anchored by not at all (0) and very much (10).

Angry/Disappointed w/ Client Preference

The average of participant’s assessments of how angry and disappointed they were about management’s stated preference related to the estimate, both scales anchored by not at all (0) and very much (10).

Average Claim Importance The average of participant’s assessments of the importance of each potential claim considered by management in developing the client’s $1.25M accrual estimate. For each claim assessment, the scale is anchored by not important (0) and very important (10).

Study Three

Wonderlic Personnel Test

The number of questions correctly answered on the Wonderlic Personnel Test, a 12-minute test of general intelligence that correlates highly with full-scale IQ tests (Dodrill 1981; Edinger, Shipley, Watkins, and Hammett 1985).

Cognitive Reflection Test

The number of questions correctly answered on the Cognitive Reflection Test, a three-item test assessing an individual’s ability to pursue alternatives past a seemingly obvious incorrect answer (Frederick 2005; Toplak, West, and Stanovich 2011).

IOS – Client The participant’s assessment of how they view the auditor-client relationship (perceived independence) based on the Identification of Other in Self scale (Aron, Aron, and Smollan 1992; Tropp and Wright 2001). Measured with seven images of progressively-overlapping circles inscribed with the words ‘Auditor’ and ‘Client.’ The image with no overlap (1) indicates the highest level of perceived independence, while the image with the greatest overlap (7) indicates the lowest level of perceived independence.

IOS – Profession The participant’s assessment of how they identify with the auditing profession (professional responsibility) based on the Identification of Other in Self scale (Aron et al. 1992; Tropp and Wright 2001). Measured with seven images of progressively-overlapping circles inscribed with the words ‘Auditor’ and ‘Profession.’ The image with no overlap (1) indicates the highest level of professional responsibility, while the image with the greatest overlap (7) indicates the lowest level of professional responsibility.

(This appendix is continued on the next page)

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Appendix A (Continued)

Measured With 6-Point Scales (1 - 6 a)

FFM – Agreeableness

Average response to the measures from the Five Factor Model assessing one’s agreeableness, which reflects cooperative and compassionate facets of personality (Barrick and Mount 1991; Poropat 2009).

FFM – Conscientiousness

Average response to the measures from the Five Factor Model assessing one’s conscientiousness, which reflects organized, consistent, striving, and self-disciplined facets of personality (Barrick and Mount 1991; Poropat 2009).

FFM – Emotional Stability

Average response to the measures from the Five Factor Model assessing one’s emotional stability, which reflects a lack of impulsiveness, and calm and secure facets of personality (Barrick and Mount 1991; Poropat 2009).

FFM – Extraversion

Average response to the measures from the Five Factor Model assessing one’s extraversion, which reflects social facets of personality (Barrick and Mount 1991; Poropat 2009).

FFM – Openness

Average response to the measures from the Five Factor Model assessing one’s openness, which reflects imagination and curiosity facets of personality and is inversely related to conservatism (Barrick and Mount 1991; Parkinson and Taggar 2006; Poropat 2009).

REI – Rational

Average response to the measures from the Rational-Experiential Inventory assessing one’s preference for the use of logic in a problem-solving context (Pacini and Epstein 1999).

REI – Experiential

Average response to the measures from the Rational-Experiential Inventory assessing one’s preference for the use of intuition in a problem-solving context (Pacini and Epstein 1999).

Need for (Cognitive) Closure Average response to the measures from the Need for (Cognitive) Closure scale assessing one’s perceived need to delve into a problem and/or achieve understanding (Cacioppo, Petty, and Feng Kao 1984).

Fear of Negative Evaluation

Average response to the measures from the Fear of Negative Evaluation scale assessing one’s concern with the impression that they make (Leary1983).

Indecisiveness

Average response to the measures from the Indecisiveness scale assessing one’s ability to come to a decision (Frost and Shows 1993).

a Each scale item is defined as follows: strongly disagree (1), disagree (2), slightly disagree (3), slightly agree (4), agree (5), and strongly agree (6). Refer to Appendix C for tests of convergent and discriminant validity.

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APPENDIX B Independent Estimate Prompt

Please enter your estimate of the client’s dollar loss for each item in the table below. Each estimate should be within the range provided. Please add up your individual estimates once they are entered.

Claims included in the client’s memo

Potential Range

(in thousands) Your

Estimate For Each Claim Low High

Safety commission fines $ 0 $ 100 $

Repair costs for the building – insurance deductible 50 50

Medical costs for the client’s employees 75 125

Business interruption claims made by the client’s customer 0 175

Settlement costs for the client’s employees 0 475

Smoke damage to adjacent buildings 250 550

Medical costs for employees of the adjacent businesses 60 100

Business interruption claims made by the adjacent businesses 0 325

Settlement costs for employees of the adjacent businesses 0 475

Smoke damage to inventory in adjacent building 200 525

Total individual dollar loss estimates (a) $ Given the estimation uncertainty in the overall loss estimate, enter the amount (zero or greater) that you would add as additional reserve for any other potential expenses.

(b) $

Add up your total individual dollar loss estimates and additional reserve. This is you independent estimate of the client’s liability.

(a)+(b) $

All underlining and boldface are identical to that used in the experimental instrument.

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APPENDIX C Tests of Convergent and Discriminant Validity

Five Factor Model (FFM)

FFM - Agree FFM - Cons FFM - ES FFM - Extra FFM - Open FFM_agree_M1 0.650 FFM_agree_M2 0.753 FFM_agree_M3 0.597 FFM_agree_M4 0.776 FFM_agree_M5 0.640 FFM_agree_M6 0.610 FFM_agree_M7 a 0.606 FFM_agree_M8 a 0.459 FFM_agree_M10 a 0.555 FFM_cons_M1 0.403 FFM_cons_M3 0.680 FFM_cons_M4 0.653 FFM_cons_M5 0.726 FFM_cons_M7 a 0.528 FFM_cons_M8 a 0.659 FFM_cons_M9 a 0.655 FFM_ES_M1 0.442 FFM_ES_M3 a 0.585 FFM_ES_M4 a 0.443 FFM_ES_M5 a 0.868 FFM_ES_M6 a 0.783 FFM_ES_M7 a 0.867 FFM_ES_M8 a 0.828 FFM_ES_M9 a 0.855 FFM_ES_M10 a 0.502 FFM_extra_M1 0.595 FFM_extra_M2 0.537 FFM_extra_M3 0.681 FFM_extra_M4 0.660 FFM_extra_M5 0.702 FFM_extra_M6 a 0.785 FFM_extra_M7 a 0.708 FFM_extra_M8 a 0.606 FFM_extra_M9 a 0.663 FFM_extra_M10 a 0.676 FFM_open_M1 0.538 FFM_open_M2 0.737 FFM_open_M3 0.716 FFM_open_M4 0.523 FFM_open_M5 0.588 FFM_open_M6 0.532 FFM_open_M7 0.629 Cronbach's alpha b 0.817 0.744 0.878 0.863 0.764

(This appendix is continued on the next page)

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Appendix C (Continued)

Rational-Experiential Inventory (REI)

REI - Rat REI – Exp. REI_rat_M1a 0.856 REI_rat_M2 a 0.855 REI_rat_M3 0.764 REI_rat_M4 0.714 REI_exp_M1 0.787 REI_exp_M2 0.809 REI_exp_M3 0.876 REI_exp_M4 0.890 REI_exp_M5 0.702 Cronbach's alpha b 0.814 0.874 Need for (Cognitive) Closure Scale Fear of Negative Evaluation Scale Indecisiveness Scale NFC FNE IND NFC_M1 0.611 FNE_M1 0.722 IND_M1 0.655 NFC_M2 0.676 FNE_M2 a 0.615 IND_M2 a 0.509 NFC_M3 a 0.724 FNE_M3 0.826 IND_M3 a 0.774 NFC_M4 a 0.745 FNE_M4 a 0.616 IND_M4 0.543 NFC_M5 a 0.562 FNE_M5 0.676 IND_M5 a 0.533 NFC_M6 0.462 FNE_M6 0.777 IND_M6 a 0.709 NFC_M9 a 0.438 FNE_M7 a 0.763 IND_M7 0.541 NFC_M10 0.748 FNE_M8 0.594 IND_M8 a 0.645 NFC_M11 0.801 FNE_M9 0.774 IND_M9 a 0.550 NFC_M12 a 0.603 FNE_M10 a 0.707 IND_M10 0.681 NFC_M13 0.655 FNE_M11 0.751 IND_M11 0.689 NFC_M14 0.581 FNE_M12 0.708 IND_M12 0.669 NFC_M15 0.707 IND_M13 0.464 NFC_M17 a 0.669 IND_M14 0.441 IND_M15 0.626 Cronbach's alpha b 0.887 0.911 0.873

Rotated component matrices (component matrices) presented for the FFM and REI (NFC, FNE and IND scales) from factor analyses using principle components extraction. Varimax rotation with Kaiser normalization was applied to scales with multiple sub-scales. Only loadings greater than 0.40 are shown. The following measures are excluded due to loadings less than 0.40 and are not used for variable calculation: FFM_agree_M9, FFM_cons_M2, FFM _cons_M6, FFM _cons_M10 a, FFM _ES_ M2, FFM _open_M8 a, FFM _open_M9 a, FFM _open_M10 a, REI_rat_M5 a, NFC_M7 a, NFC_M8 a, NFC_M16 a, NFC_M18. Refer to Appendix A for variable definitions. a Measure reverse coded b All alphas are above 0.70, indicating that our constructs exhibit good convergent validity (Kline 2011).

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APPENDIX D Correlation Matrix for the Structural Equation Model Variables

Variables 1 2 3 4 5 6 7 1 Estimate Reasonableness 1.000 2 Certainty of Reasonableness 0.695*** 1.000

3 Attempt to Eliminate Bias -0.307*** -0.234* 1.000 4 Happy/Pleased w/ Client Pref. 0.208* 0.403*** 0.030 1.000 5 IOS-Client 0.116 0.112 -0.177 0.249** 1.000 6 FFM - Conscientiousness 0.026 -0.073 0.030 -0.343*** -0.012 1.000 7 FFM - Openness 0.112 -0.069 -0.033 -0.133 -0.111 0.029 1.000

*, **, and *** denote two-tailed significance at the 10%, 5%, and 1% levels, respectively. Refer to Appendix A for variable definitions.