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How do Behavioral Indicators of Audit Committee Effectiveness Influence

Audit Effort?

Sanaz Aghazadeh*

Lehigh University

College of Business and Economics

339 Rauch Business Center

621 Taylor Street

Bethlehem, PA 18015-3117

Tel +1-610-758-2816

Fax +1-610-758-5992

Email [email protected]

Yoon Ju Kang

Lehigh University



621 Taylor Street


Tel +1-610-758-3426

Fax +1-610-758-5992


Marietta Peytcheva

Lehigh University



621 Taylor Street


Tel +1-610-758-2818

Fax +1-610-758-5992


April 2014

*Corresponding author

We would like to acknowledge research support from The Martindale Center for the Study of

Private Enterprise at Lehigh University. We thank Jeffrey Cohen, Ganesh Krishnamoorthy,

Tamara Lambert, Arnold Wright, and participants of the Lehigh University Singleton

Workshop Series.

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How do Behavioral Indicators of Audit Committee Effectiveness Influence Audit Effort?

SUMMARY

We test competing hypotheses based on the theory of process accountability and the audit risk

model (ARM), to determine how audit committee (AC) effectiveness impacts audit effort.

Process accountability theory predicts that audit effort will be highest when the AC is most

effective, i.e., it engages in more proactive meeting behavior and asks probing questioning of the

auditors. In contrast, the ARM predicts that audit effort will be highest when the AC is least

effective, because auditors’ assessment of a weak tone at the top will lead auditors to increase

their assessment of control risk, leading to higher audit effort. We test these competing

hypotheses in 2x2 between-participants experiment with practicing auditors, in which we

manipulate AC questioning behavior (probing vs. non- probing) and AC proactive behavior

(more vs. less proactive). Results provide support for the ARM: we find that audit effort is

highest under non- probing AC questioning and less proactive AC meeting behavior, and that

this effect is mediated by auditors’ assessment of tone at the top. Interestingly, we also find more

effective ACs increase auditors’ process accountability; however, this does not ultimately

increase audit effort. Audit effort is instead increased by auditors’ assessment of a weak tone at

the top, associated with less effective ACs.

Keywords: audit effort; audit committee effectiveness; corporate governance; tone at the top

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I. INTRODUCTION

Firms implement corporate governance monitoring mechanisms so that the interests of

shareholders and managers are aligned (Jensen and Meckling 1976). With the responsibility to

effectively oversee the financial reporting and auditing process, audit committees (hereafter

ACs), along with management and auditors are part of the three-legged stool that ensures the

integrity of the financial reporting process (Center for Audit Quality 2010; Turley and Zaman

2007). The recent implementation of AS No. 16 Communication with the AC highlights the

importance of the AC’s role in the audit process and increases the likelihood of the AC affecting

the overall financial reporting quality. Despite the importance of ACs’ impact, little empirical

evidence exists regarding its effect on the financial reporting and auditing process. Our study

fills this void by examining the impact of AC effectiveness on audit effort.1

AC behaviors while overseeing the financial reporting and auditing process are indicative of

AC effectiveness. One significant way in which effective ACs fulfill their oversight duty is by

challenging the judgments and assumptions underlying significant accounting estimates (Beasley

et al. 2009; Gendron and Bédard 2006; Gendron et al. 2004; Kang 2014). Exhibiting proactive

behavior by asking for non-routine (i.e., unexpected) meetings with the auditor is another way

ACs can effectively oversee the financial reporting process (Beasley et al. 2009; KPMG 2012;

Turley and Zaman 2007). In this study, we experimentally examine how such behavioral

indicators of AC effectiveness (i.e., asking probing questions and exhibiting proactive meeting

behavior) affect auditors’ perception of the AC and how that ultimately influences audit effort.2

1 Consistent with the PCAOB’s emphasis on both the nature and extent of audit procedures (PCAOB 2013; AS 5, 11,

12), we define and measure audit effort to incorporate both the diagnosticity as well as the quantity of audit

procedures designed by the auditor. 2 Following prior literature, we define probing questions as those that challenge the respondent to justify their

judgment or decision-making process (Kang 2014; Pomeroy 2010).

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We use (1) process accountability theory and (2) the audit risk model (ARM hereafter), to

develop competing hypotheses regarding how auditors are likely to respond to AC effectiveness.

First, we examine the implications of process accountability theory. Process accountability

suggests that when auditors are accountable to supervisors and other evaluators for their decision

process, audit effort increases, judgment biases decrease and auditors’ judgment accuracy

improves (Ashton 1992; Johnson and Kaplan 1991; Tan 1995; DeZoort et al. 2006). This theory

is applicable in the auditor–AC relationship where the AC essentially holds auditors accountable

for their judgment and decision processes regarding significant accounting issues in the process

of overseeing the financial reporting and auditing process (Audit Committee Collaboration

Group 2012; Fornelli and Cobb 2013; PwC 2013). This theory holds that auditors will likely

experience greater process accountability given a more effective AC, which will lead to greater

audit effort.

The ARM, however, suggests a contrasting effect of AC effectiveness on audit effort.

Auditors use the ARM to assess audit risk by evaluating control risk, inherent risk, and detection

risk in order to plan their level of audit effort (AICPA 1983). Auditors evaluate tone at the top as

part of their assessment of control risk (COSO 1992, 2013). We predict that auditors will

perceive AC effectiveness as a signal of strong tone at the top, and therefore an indicator that

control risk is low. As a result, auditors will decrease their audit effort in response to the low

control risk. Thus, the process accountability and the ARM frameworks suggest differing effects

for AC effectiveness on audit effort, and we provide an experimental test of these competing

predictions.

We test our predictions using a 2 X 2 between-participants experiment with Big-4 auditors,

where the extent to which the AC engages in questioning behavior (probing vs. non-probing) and

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the extent of AC’s proactive behavior (more vs. less proactive) are manipulated. Participants are

asked to assume that they are a member of an audit engagement team and are preparing for an

upcoming AC meeting. Participants in the more proactive condition are informed that the chair

of the AC has recently requested an additional, non-routine, meeting to further discuss the AC’s

general expectations of the audit. Participants in the less proactive condition do not receive this

request from the AC, and therefore prepare for a routine meeting. It is important to note that the

additional meeting in our experiment does not imply any additional risk factors being present as

participants were told the AC is simply asking to meet to discuss their general expectations for

the current year audit. In preparation for the upcoming AC meeting, the participants review the

prior year’s file regarding an inventory obsolescence issue. The file contains a brief description

of the accounting issue and the AC’s questions/comments (probing vs. non-probing). Participants

are then informed that their audit team is revisiting the inventory obsolescence issue and are

asked to develop a plan for the current year’s audit, including their description of audit

procedures needed to address the inventory obsolescence issue. We use these procedures to

create our measure of audit effort. A critical feature of our measure of audit effort is that it

incorporates both the extent and the nature of audit procedures proposed by the auditor,

consistent with auditing standards and PCAOB guidance (e.g., PCAOB 2013; AS 5, 11, 12).

We find support for the predictions based on the ARM. This framework suggests that audit

effort is highest under less probing AC questioning and less proactive behavior. Moreover, we

find that this effect is mediated by auditors’ assessment of tone at the top. Specifically, a more

effective AC that is more proactive or asks probing questions, leads auditors to assess tone at the

top as strong and to reduce their audit effort as a response to decreased control risk.

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As expected, we also find that an AC that is more proactive and asks probing questions

increases auditors’ process accountability. Interestingly, however, we do not find evidence that

an increase in process accountability results in greater audit effort. Together, the findings suggest

that a more effective AC increases both auditors’ perceived accountability pressure and auditors’

assessment of a strong tone at the top. However, the effect of tone at the top dominates over the

effect of accountability pressure in determining auditors’ behavior.

Our research makes several contributions to the accounting and auditing literature. First,

generally, our study adds to the limited line of literature on ACs and how they affect the financial

reporting process (Cohen et al. 2002, 2010; Beasley et al. 2009; Gendron and Bédard 2006).

Second, we contribute to the sparse literature on tone at the top by providing evidence that the

impact of AC effectiveness on audit effort is mediated by auditors’ assessment of tone at the top,

leading auditors to modify their audit plans related to accounting issues that arise during the

audit process. Relatedly, our study is the first to examine the joint effects of auditors’ process

accountability and auditors’ assessment of the client’s tone at the top on audit effort, and to

determine which of the two factors is more influential in determining auditor behavior. Third,

while prior research shows that AC attitudes affect how auditors communicate with the AC (e.g.,

Fiolleau et al. 2013), we show how AC effectiveness impacts audit effort, which should

ultimately affect the overall quality of the audit. Therefore, our results are likely to be of interest

to regulators, investors, and corporate boards, especially given the passage of AS 16

Communications with the AC which encourages two way communications between the AC and

auditors. Finally, while regulators and standard setters seem to believe that greater AC

effectiveness will lead to greater audit effort and ultimately higher audit quality (e.g., AS 16),

our study shows that greater AC effectiveness may actually lead to lower audit effort.

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The paper is organized as follows. Section II provides an overview of the background

literature. Section III develops the theory and presents our hypotheses. Section IV describes the

methodology, section V presents the results, and section VI concludes.

II. BACKGROUND

Prior literature examines AC effectiveness in terms of both inputs and process variables

(DeZoort et al. 2006). For example, studies focusing on input variables have examined how the

different characteristics of the AC, such as independence (e.g., Klein 2002; Abbott et al. 2004) or

financial expertise (e.g., Bédard et al. 2004, Abbott et al. 2004; Dhaliwal et al. 2010) influence

AC effectiveness. Studies focusing on process variables have examined the effects of the number

of meetings held with the external auditor and questioning behavior of the AC (e.g., Abbott et al.

2004; Fiolleau et al. 2013). In this study, we hold constant the inputs and examine AC

effectiveness by focusing on the process that the AC exerts in conducting their oversight role.

We specifically focus on two process variables that prior literature has isolated as important

determinants of AC effectiveness: (1) AC’s questioning behavior and (2) the extent to which

they are proactive in their oversight duty.3

AC Questioning Behavior

One way in which ACs can fulfill their oversight duty and protect shareholder interests is by

questioning the auditor about the assumptions that underlie critical accounting estimates (NACD

2010; Gendron et al. 2004; Gendron and Bédard 2006; Beasley et al. 2009; Kang 2014). The

NACD specifically states that “AC members should pay particular attention to the issues

3 It is important to note that an AC can exhibit only one, both, or none of these behaviors; that is, the two

variables are orthogonal. For example, although the AC, as described in Turley and Zaman (2007), tends not to

engage in probing questioning behavior, the AC exerts great influence through additional, unscheduled meetings

with the auditors. Conversely, proactive meeting behavior by the AC can be coupled with a lack of probing

questioning behavior: meetings between the AC and auditors that are held with impressively high frequency often

involve superficial comments and lack of any probing questioning by the AC (e.g., Beasley et al. 2009).

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identified by management and … question assumptions that underlie critical accounting

estimates” in fulfilling their oversight duty and protecting shareholder interests (NACD 2010, 8).

The need for increased questioning by ACs is especially evident given recent findings that show

ACs are rarely involved in resolving contentious issues between the auditor and management

(Gibbins et al. 2001; Cohen et al. 2002, 2010;Gibbins et al. 2007). Prior research finds that the

extent of questioning that auditors expect of the AC influences the amount of information

auditors actually communicate to the AC, where auditors tend to provide more information to

ACs with reputations for greater involvement and more intense questioning style (Fiolleau et al.

2013). We extend this line of research by examining how AC’s questioning behavior goes on to

ultimately affect audit effort.

AC Proactive Meeting Behavior

In addition to asking probing questions, increasing the frequency4 in which the AC meets

with the auditors is suggested as a way of increasing AC effectiveness as well as increasing audit

effort (KPMG 2012). Prior research finds supporting evidence for greater frequency of AC

meetings being associated with higher financial reporting quality (Abbott et al. 2004; Bédard et

al. 2004; Stewart and Munro 2007; Xie et al. 2003; DeFond et al. 2005). However, Turley and

Zaman (2007) find that ACs’ impact in routine situations is limited and therefore, emphasize the

need to initiate non-routine meetings between the AC and auditors. Turley and Zaman further

assert that unpredicted, non-routine meetings between the AC and the auditor are more likely to

influence the tone at the top compared to routine meetings as “[a]d hoc meetings … help to

encourage a climate that is conducive for raising concerns (p. 15).” However, there is little

empirical evidence on how non-routine meetings called by the AC actually influence the

behaviors of auditors and ultimately the quality of the audit. Our study addresses this issue.

4 In our study, the AC initiates an additional, non-routine meeting with the auditor.

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III. THEORY AND DEVELOPMENT OF HYPOTHESES

Predictions Based on Auditor’s Process Accountability

First, we examine the impact of AC effectiveness on audit effort through the lens of

accountability theory. This lens of examination emphasizes the AC’s oversight role over the

auditor and focuses on the fact that, in the process of overseeing the financial reporting and

auditing process, the AC essentially holds auditors accountable for their judgment and decision

processes regarding significant accounting issues (Audit Committee Collaboration Group 2012;

Fornelli and Cobb 2013; PwC 2013).

Psychology research distinguishes between two types of accountability: process

accountability and outcome accountability. In contrast to outcome accountability, process

accountability implies that decision makers are held accountable for the quality of their decision

processes, regardless of the outcome of their decisions (Tetlock 1983, 1985; Lerner and Tetlock

1999). Process accountability has many positive effects on judgment quality. Specifically,

studies find that process accountability increases the integrative, complexity of thought (Tetlock

1983; Tetlock and Boettger 1989; Suedfeld et al. 1992).5 Siegel-Jacobs and Yates (1996) also

find that process accountability encourages decision makers to incorporate all relevant

information into their decisions, and that it reduces the variability of individual judgments. Other

studies show process accountability also increases cognitive effort, improves calibration, and

reduces decision biases (Tetlock1992; Tetlock et al. 1989; Tetlock and Kim 1987; Siegel-Jacobs

and Yates 1996). Individuals who are held process accountable are also more likely to attend to

critical decision information (Tetlock, 1992).

5Integrative complexity of thought is defined as both perceiving various perspectives of an issue [differentiation] and

identifying cognitive connections that synthesize these perspectives [integration](Tetlock and Boettger 1989).

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Auditing research also documents beneficial effects of process accountability on auditors’

judgment. Process accountability improves auditors’ decision accuracy (Ashton 1990, 1992) and

efforts to justify their decisions (Koonce et al. 1995). Process accountability also increases audit

effort, and decreases the variance in auditors’ judgments (Johnson and Kaplan 1991; DeZoort et

al. 2006). Peecher et al. (2013) extend these findings and propose that, in order to improve audit

quality, regulators should shift their emphasis toward greater process accountability. With their

oversight and responsibility for auditor appointment and dismissal, ACs can serve as a critical

source of accountability pressure for the auditor (Cohen et al. 2010; Fiolleau et al. 2013). Under

this perspective, a more effective AC will be more likely to ask auditors to justify their

judgments and decisions and thereby, facilitate greater accountability pressure.

Process accountability theory predicts that the greater accountability pressure resulting from

greater AC effectiveness will motivate auditors to increase their audit effort. Since ACs that ask

probing questions and are more proactive in their meeting behavior are likely to be perceived as

more effective compared to ACs only exerting one of the two behaviors or those that show

neither of the two behaviors, such ACs should induce the highest level of accountability pressure.

In other words, the theory of process accountability holds that audit effort will be greatest when

the AC engages in both probing questioning and proactive meeting behavior by inducing the

highest level of accountability. This predicted interaction based on the theory of process

accountability is hypothesized below as H1a. H1b further describes the predicted mechanism

(i.e., process accountability) that underlies the hypothesized effect of AC effectiveness on audit

effort in H1a.

H1a: Audit effort will be highest under probing AC questioning and AC proactive meeting

behavior.

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H1b: Process accountability will mediate the effect of AC effectiveness on audit effort.

Predictions Based on the ARM

Contrary to the predictions laid out in the prior section based on the theory of process

accountability, the well-known ARM predicts an alternative and contrasting possible effect of

AC effectiveness on audit effort. Specifically, the ARM predicts that the use of probing

questions and proactive meeting behavior by the AC may lead to lower audit effort.

The ARM was developed as a planning tool to help auditors assess audit risk (AICPA 1983;

Cushing et al. 1995). The model decomposes audit risk into three components: control risk,

inherent risk, and detection risk. Auditing standards require auditors to use the ARM in planning

their required audit effort as a function of the assessed risk of material misstatement on the audit

(AICPA 1983; Houston et al. 1999; Kizirian et al. 2005). Given a certain level of acceptable

audit risk, audit effort is determined based on auditors’ assessments of the control risk and

inherent risk elements of ARM (Libby et al. 1985; Houston et al. 1999; Bell et al. 2005; Budescu

et al. 2012). For example, if auditors assess control risk as high, they can increase audit effort –

the extent and nature of audit procedures performed – to achieve the desired low level of

detection risk. In this study, we focus on one important element of control risk: tone at the top

(COSO 1992, 2013).

Tone at the top is an essential component of the COSO framework (COSO 1992, 2013;

Kizirian et al. 2005). Establishing and maintaining a strong tone at the top is one of the most

important governance tasks of ACs (Vera-Muñoz 2005; KPMG ACI 2013; Center for Audit

Quality 2010). AC members view setting a strong tone at the top as their principal responsibility

(Beasley et al. 2009). Therefore, auditors are likely to view AC’s setting of a strong tone at the

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top in the organization as a signal to AC effectiveness. Consistent with the theoretical predictions

of the ARM, this signal about tone at the top should in turn affect audit effort.

Specifically, we expect that when the AC engages in probing questioning and/or is proactive

in its meeting behavior, auditors will perceive the AC as an effective monitor and will assess its

tone at the top as strong. The ARM suggests that the auditor’s assessment of a stronger tone at

the top will lead the auditor to reduce audit effort. In contrast, when the AC is not probing in its

questioning behavior and is not proactive in its meeting behavior, auditors will assess tone at the

top as being the weakest compared to situations where the AC engages in one of the two

behaviors or both. The ARM predicts that the auditor should increase audit effort in this situation.

This predicted interaction based on the ARM is hypothesized below as H2a. H2b further

describes the predicted mechanism (i.e., auditors’ assessment of tone at the top) that underlies

the hypothesized effect of greater AC effectiveness on audit effort in H2a.

H2a: Audit effort will be highest under non-probing AC questioning and less proactive AC

meeting behavior.

H2b: Auditors’ assessment of tone at the top mediates the effect of AC effectiveness on audit

effort.

IV. METHOD

Participants

Participants in the study were 133 senior and staff auditors from a Big 4 audit firm. The

experiment was conducted during training sessions of the firm. From the original sample of 133

auditors to whom the study was distributed, we excluded two participants who provided

incomplete instruments, as well as four experienced manager participants, who were the

instructors of the training sessions at which the study was conducted. Our tests are conducted

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with the remaining sample of 127 auditors: 67% associates and 33% senior associates.

Participants had a mean of 17 months of audit experience (std. dev. = 8.16), with a mean age of

24 years (std. dev. = 2.39); 47% of the participants were male, and 89% of participants reported

they had experience in auditing inventory.6

Experimental Design

Independent Variables

We employ a 2 × 2 between-participants design to examine our research question with the

extent to which the AC engages in questioning behavior and AC proactive behavior as

manipulated variables. The first factor, AC questioning behavior is manipulated at two levels

(probing vs. non-probing) using information regarding the questioning behavior of the AC in a

previous meeting with the auditors. The participants in the probing condition see a list of

questions that are probing in nature while the participants in the non-probing condition see a list

of general non-probing comments given by the AC. The list of questions/comments was based

on actual responses from AC members who participated in the Kang (2014) study and was

subsequently reviewed by one of the two audit experts described below. Exhibit 1 provides the

details of this manipulation.

The second factor, AC proactive behavior, is also manipulated at two levels. In the less

proactive AC condition, participants were informed that scheduled meetings with the AC occur

every quarter, and the upcoming meeting with the AC is described as a routine, previously

scheduled quarterly meeting. In the more proactive AC condition, auditors were informed that

scheduled meetings the AC occur every quarter, and the first quarterly meeting with the AC had

6 We use staff level auditors as our participants as they are the ones primarily responsible for planning the audit and

executing day-to-day audit procedures. As Cohen et al. (2002) note, “if they (staff level auditors) do not have a

comprehensive understanding of governance factors, they may be insufficiently impounding information on

governance.”

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occurred in the previous month. Participants were next informed that the chair of the AC

requested an additional, previously unscheduled, meeting with the audit team, for the purpose of

further discussing the AC’s general expectations for this year’s audit, and reviewing the audit

team’s planning for the audit. It is important to note that it was made clear to the participants that

the additional meeting in our experiment did not imply any additional risk being present as the

purpose of the meeting was to simply discuss the AC’s expectations for the current audit year.

Exhibit 2 provides the details of this manipulation.

The AC’s independence and competence characteristics were kept constant across all

conditions. Participants were informed that all five members of SCA’s AC qualify as

independent directors, and that two AC members qualify as financial experts, as defined by the

SEC. Participants were further informed that their client – a publicly-traded company and an

accelerated filer – had been a client of their audit firm for the past 9 years, and had always

received unqualified opinions on its financial statements and on its internal control over financial

reporting.

Dependent Variables

Our primary dependent variable is audit effort. We define audit effort in terms of inputs, with

a specific focus on the audit procedures performed by the auditor (IAASB 2011; PCAOB 2013).

Generally accepted auditing standards require that the auditor perform appropriate audit

procedures to gather sufficient and appropriate audit evidence (IAASB 2011; PCAOB 2013; AS

15). Specifically, the PCAOB emphasizes the importance of both the nature and the extent of

audit procedures (e.g., PCAOB 2013; AS 5, 11, 12). Consistent with the PCAOB’s emphasis, our

measure of audit effort incorporates the diagnosticity as well as the quantity of audit procedures

designed by the auditor.

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Audit effort was measured by a factor score composed of two variables: the number of audit

procedures and the diagnosticity of audit procedures.7 After examining the experimental case,

participants were informed that their audit team had decided to perform three basic audit

procedures.8 Participants were then instructed to assess whether additional procedures need to be

performed, and to list any additional procedures they deem necessary (up to five), in order of

importance. These lists were used to develop the measure of the number of audit procedures (one

component of audit effort).

The second component of audit effort, diagnosticity of audit procedures, was measured by

examining the procedures proposed and assigning a diagnosticity score to the set of procedures

proposed by each participant. Two highly experienced audit partners, who were blind to the

hypotheses and experimental conditions, reviewed the procedures proposed by the participants

and coded their overall diagnosticity on a scale of 0 to 10.9 The task consisted of re-assessing the

adequacy of an inventory obsolescence reserve that had been assessed in the prior-year audit.

The company had recently implemented a new and successful business strategy, and the slow-

moving inventory related to the old business strategy. Thus, proposed procedures such as

“observe annual physical count of inventory”, “cut-off procedure” or “physical inspection of a

sample of inventory” were deemed non-diagnostic to the task in question. Procedures such as

“verify saleable price with market”, “perform analytical procedures over selling prices vs.

historical information, demand for products and market share”, “LCM analysis comparing the

7The factor score was obtained using principal components analysis; the two variables loaded on a single factor with

eigenvalue of 1.50; the factor explained 75% of the variance in the data. 8 The three procedures were: (1) Inquire with financial management regarding possible obsolescence of inventory; (2)

Discuss possible obsolescence and overstock of inventory with operating personnel; (3) Obtain an understanding of

the company’s methodology for establishing the obsolescence reserve. 9 One of the audit partners was an expert with over 15 years of field audit experience and over 20 years of

experience at the National Office of a Big 4 firm as a leader in the areas of audit policy, audit quality, and risk

management. The other audit partner had over 20 years of audit experience and was a member of the National

Professional Standards group of one of the second-tier international audit firms.

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cost to last sold price”, or “obtain industry reports to gain understanding of valuation issues”,

were deemed diagnostic to the task at hand. Any disagreement with respect to procedure

diagnosticity was discussed and resolved between the coders.

Case Materials and Procedures

The case used in this study relates to inventory obsolescence and is based on Kang (2014).

The participants are asked to assume the role of a senior in charge of the audit. Participants first

review the background information about the audit client which includes details regarding the

client’s industry, the auditor-client relationship, and information regarding the nature of the

upcoming meeting with the AC (routine vs. non-routine). To ensure participants are attentive of

the information regarding the meeting with the AC, auditors are asked to mark the day of the

described meeting on a calendar provided to them as part of the case materials. After reviewing

the background information, participants are provided with audit results and AC communication

details regarding the past year’s audit in order to prepare for the upcoming AC meeting. The

previous year’s audit results provide a description of a significant accounting estimate related to

inventory, management’s initial judgment of the write-down, and the audit team’s conclusion

regarding the write-down.

The communication with the AC on the inventory obsolescence issue includes

questions/comments that are said to be representative of the types of questions/comments that the

AC typically asks in meetings with the audit team. Participants in the probing (non-probing)

condition receive questions outlined in Exhibit 1. To ensure participants carefully consider these

communication details, participants are asked to summarize what is required to satisfy the

questions/comments of the AC. Subsequently, participants review information (materiality

information, inventory levels, and management’s estimated write-down) in preparation for

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planning the current year audit of inventory. This information outlines the details of a possible

inventory obsolescence issue for the current year. After reviewing this information, participants

respond to a set of dependent measures (discussed above). The experiment concludes by asking

several process measures questions, manipulation check questions, and demographic questions.

As described earlier in the theory and hypotheses development section, our two process

measures of interest are tone at the top and process accountability. We measure tone at the top by

explicitly asking the participants to rate the AC’s tone at the top on a scale of -3 (extremely weak)

to +3 (extremely strong). We measure process accountability using questions that are commonly

used in process accountability manipulations in psychology literature (Tetlock and Boettger 1989;

Tetlock and Kim 1987; Markman and Tetlock 2000; Siegel-Jacobs and Yates 1996; Brtek and

Motowidlo 2002; Tetlock et al. 1989; Kennedy 1993). Specifically, we ask the participants to

rate on a scale of -3 (extremely less than average) to +3 (extremely more than average), (i) the

extent to which they believed the AC would require them to justify their responses, (ii) the extent

to which they believed the AC would evaluate the quality of their decisions, and (iii) the extent

to which they believed the AC would require them to explain the process they followed in

making their judgments and decisions (italics added). The responses to these three questions are

converted to a scale (Cronbach’s alpha = 0.87), to examine whether process accountability

mediates the effect of AC effectiveness on overall audit effort.

(Insert Exhibit 1 Here)

V. RESULTS

Manipulation Checks

We tested the effectiveness of the AC questioning behavior manipulation with two questions

which asked participants to what extent they believe the questions/comments from SCA’s AC

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were (1) challenging, and (b) scrutinizing. Responses were measured on 7-point scales (0 = not

at all; 6 = extremely). Results from t-tests (t = 3.14, p = 0.002; t = 3.36; p = 0.001) showed that

participants in the probing condition believed the AC’s questions/comments were both more

challenging (mean = 2.65, std. dev. = 1.31) and more scrutinizing (mean = 2.27, std. dev. = 1.39)

than participants in the non-probing condition (mean = 1.84, std. dev. = 1.58; mean = 1.36, std.

dev. = 1.65). The effectiveness of the AC proactive behavior manipulation was tested with

participants’ agreement with the statement that this year, SCA’s AC had requested an additional

meeting with the audit team (-3 = strongly disagree, 3 = strongly agree). A t-test (t = 9.21, p <

0.001) showed that participants in the more proactive condition agreed more with this statement

(mean = 2.42; std. dev. = 1.01) than participants in the less proactive condition (mean = -0.17,

std. dev. = 2.03). The manipulations of AC proactive behavior and questioning behavior were

therefore successful.

Descriptive Statistics and Covariates

Panel A of Table 1 shows descriptive statistics for audit effort. As discussed in the Method

section, audit effort was measured with a factor score composed of two variables: number of

audit procedures and audit procedure diagnosticity. Panel B of Table 1 shows descriptive

statistics for the number of audit procedures, and Panel C shows descriptive statistics for audit

procedure diagnosticity. We observe the highest audit effort (mean = 0.308, std. dev. = 1.050) in

the condition in which the AC’s questioning behavior is non-probing and the AC is less

proactive in its meeting behavior.

(insert Table 1 here)

We conducted separate linear regressions for audit effort on demographic variables. While

participants’ age and gender were not significant predictors of audit effort, participants’ audit

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experience (measured in months) was a significant predictor of audit effort (t = 2.55, p = 0.012).

We therefore included audit experience as a covariate in the ANCOVA conducted for audit

effort.

AC Effectiveness and Audit Effort

Panel A of Table 2 shows the ANCOVA of audit effort on AC questioning behavior, AC

proactive behavior, and audit experience included as a covariate. We observe that AC

questioning behavior and audit experience have significant, but opposite in direction, effects on

audit effort. While audit experience increases audit effort (F = 6.96, p = 0.009), probing

questioning behavior of the AC leads to a significantly lower audit effort (F = 4.59, p = 0.034).

The effects of AC proactive behavior and the interaction are not significant.


Planned Contrasts

H1a proposed that audit effort will be highest under probing AC questioning and proactive

meeting behavior, and H2a proposed that audit effort will be highest under non-probing AC

questioning and less proactive meeting behavior. Panel B of Table 2 shows results from the

planned contrasts testing H1a and H2a. The planned contrast testing H1a (-1, -1, -1, 3) is not

significant (t = 0.16, p = 0.873), and H1a is not supported. However, the planned contrast testing

H2a (3, -1, -1, -1) is significant (t = 2.04, p = 0.022). H2a is therefore supported.

AC Effectiveness and Auditor Process Accountability

We next examine the effects of AC questioning behavior and AC proactive behavior on

auditors’ process accountability. Descriptive statistics for auditor process accountability

assessments are shown in Panel A of Table 3, and the ANCOVA is shown in Panel B. We

observe a main effect of AC questioning behavior on auditor process accountability: Probing

19

questioning behavior by the AC induces greater process accountability in auditors (mean = 1.26,

std. dev. = 0.88) than non-probing AC behavior (mean = 0.77, std. dev. = 1.20), and the effect is

significant F = 6.52, p = 0.012). However, no significant effects are observed for AC proactive

behavior, the interaction, or audit experience. Hence, H1b is not supported.


AC Effectiveness and Tone at the Top

Table 4 shows results for AC tone at the top. Panel A shows descriptive statistics for AC tone

at the top. As expected, participants assessed AC tone at the top to be weakest when the AC is

both non-probing in its questioning behavior and less proactive (mean = -1.13, std. dev. = 1.23).

AC tone at the top is assessed as strongest when the AC is both probing in its questioning

behavior and proactive (mean = 1.09, std. dev. = 0.98).

Panel B of Table 4 shows the ANCOVA for AC tone at the top. Both AC questioning

behavior (F = 68.41, p < 0.001) and AC proactive behavior (F = 5.69, p = 0.019) significantly

increase auditor assessment of the strength of AC tone at the top. The interaction term and the

audit experience covariate are not significant.


Effects of Tone at the Top and Auditor Process Accountability on Audit Effort

Table 5 shows the ANCOVA of in a model that includes audit effort as the dependent

variable and AC questioning behavior, AC proactive behavior, AC tone at the top and auditor

process accountability as independent variables, as well as the audit experience covariate. We

observe that, while the manipulated variables are no longer significant, stronger AC tone at the

top has a significant negative effect on audit effort (F = 6.69, p = 0.011). Further, auditor process

accountability does not have a significant effect on audit effort (F = 0.14, p = 0.711).

20


Mediation Tests

We conduct mediation tests (Baron and Kenny 1986) for the effect of auditor process

accountability and AC tone at the top on audit effort. We first examine H1b, which proposed that

process accountability mediates the effect of AC questioning behavior on audit effort. Although

we found that AC effectiveness increases auditor process accountability (see Table 3), AC

effectiveness did not increase audit effort (see Table 2), and process accountability had no

significant effect on audit effort (see Table 5). H1b is therefore not supported.

We next examine whether, as proposed in H2b, AC tone at the top mediates the effect of AC

questioning behavior on audit effort. We follow Baron and Kenny’s (1986) four steps for testing

of mediation. In a series of linear regressions, we find that: (step 1) AC questioning behavior is a

significant predictor of audit effort (b = -0.65, p = 0.005, one-tailed); (step 2) AC questioning

behavior is a significant predictor of tone at the top (b = 1.86, p < 0.001, one-tailed); and finally,

in a regression including both AC questioning behavior and tone at the top as predictor for audit

effort, (step 3) tone at the top is significant (b = -0.20, p = 0.004, one-tailed), but (step 4) AC

questioning behavior is no longer significant (b = -0.28, p = 0.155, one-tailed). A Sobel test

(Sobel 1982) provides further evidence that tone at the top mediates the effect of AC questioning

behavior on audit effort (Sobel z = -2.45, p = 0.007, one-tailed).

VI. CONCLUSION

Using the theory of process accountability and the ARM, this study predicts and tests two

competing hypotheses on how AC effectiveness impacts audit effort. Specifically, based on the

theory of process accountability, we predict that audit effort will be highest when the AC is most

effective (i.e., asks probing questions and is more proactive). In contrast, based on the ARM, we

21

predict that when the auditors view AC tone at the top as a signal of AC effectiveness and

decreased control risk, audit effort will be highest when the AC is least effective (i.e., asks non-

probing questions and is less proactive).

Results show support for the predictions based on the ARM framework. Specifically,

auditors exerted the greatest amount of audit effort when the AC does not ask probing questions

and does not engage in proactive meeting behavior (i.e., least effective). Moreover, we find that

this effect is mediated by auditors’ assessment of tone at the top. Specifically, a more effective

AC that is more proactive or asks probing questions, leads auditors to assess tone at the top as

strong. This leads to a reduction in audit effort.

Interestingly, we also find that an AC that is more proactive and asks probing questions

increases auditors’ process accountability. However, we do not find evidence that an increase in

process accountability results in greater audit effort as process accountability theory suggests.

Together, the findings suggest that while a more effective AC increases both auditors’ perceived

accountability pressure and auditors’ assessment of a strong tone at the top, the effect of tone at

the top assessment dominates over the effect of accountability pressure in determining auditors’

behavior. These results are likely to be of interest to regulators, investors, and corporate boards,

especially given the passage of AS 16 Communications with the AC which encourages two way

communications between the AC and auditors.

Our research makes several contributions to the accounting and auditing literature. First,

broadly, our study adds to the limited line of literature on ACs and how they affect the financial

reporting process (Cohen et al. 2002, 2010; Beasley et al. 2009; Gendron and Bédard 2006).

Second, we contribute to the sparse literature on tone at the top, by providing evidence that the

effect of AC effectiveness on audit effort is mediated by auditors’ assessment of tone at the top.

22

Third, while prior research shows that AC attitudes affect how auditors communicate with the

AC (e.g., Fiolleau et al. 2013), we show how AC effectiveness impacts audit effort, which has

implications for the quality of the audit. Moreover, while regulators and standard setters seem to

believe greater AC effectiveness will lead to greater audit effort and ultimately higher audit

quality (e.g., AS 16), our study shows that greater AC effectiveness may actually lead to lower

audit effort due to auditor’s assessment of tone at the top.

This study also provides a basis for future research aimed toward obtaining a deeper

understanding of how AC effectiveness affects auditors’ judgment and decision making process.

While the current study focuses on the effect of AC’s questioning behavior and proactive

meeting behavior, future research could examine the impact of other characteristics of the AC

(e.g., financial expertise) on audit effort.

23

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27

EXHIBIT 1.Manipulation of Questioning Behavior

Panel A: Probing

What was your initial reaction when you saw management’s original estimate?

What was the key factor that led to the estimate changing from $4 million to only $970,000?

Exactly what type of supporting documentation did you gather to become comfortable with the

new estimate? How did you test that supporting documentation?

When you asked management to justify their new estimate, how did they react? Were they

willing to work with you on the issue or did they come across as being defensive?

Were there any other significant estimates that were modified during the audit process as a

result of the discussion with management?

Panel B: Non-Probing

It’s comforting to know you reached an agreement with management on the estimate.

It’s certainly a relief that the estimate wasn’t what management originally estimated it to be.

It’s good to know management was able to come up with a plan to sell the old inventory.

This is a good example of why management should always double-check their estimates.

We hope management’s strategy to sell the old inventory works out as they planned.

28

EXHIBIT 2.Manipulation of Proactive Behavior

Panel A. More Proactive

The first quarterly meeting with the audit committee occurred last month where you discussed

general planning for the audit. A week ago, the Chair of SCA’s audit committee requested an

additional meeting with your audit team. This meeting had not been previously scheduled.

During this additional meeting, SCA’s audit committee plans to further discuss their general

expectations for this year’s audit, as well as review your audit team’s planning for the audit.

The additional meeting is on November 7, 2012 at 2:00 pm. Please make a note of this meeting

on your calendar below. You may need to review this information later.

OCTOBER 2012

MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY

1 2 3 4 5

Previously

Scheduled

Quarterly

Meeting with

the Audit

Committee

NOVEMBER 2012


3 4 5 6 7

29

Panel B. Less Proactive

The first quarterly meeting is on November 7, 2012 at 2:00 pm. Please make a note of this

meeting on your calendar below. You may need to review this information later.

OCTOBER 2012


1 2 3 4 5

NOVEMBER 2012


3 4 5 6 7

30

FIGURE 1.Proposed Effects of AC Effectiveness and Audit Effort

Auditor

Process

Accountability

Probing

Audit Procedures

Diagnosticity

Audit Effort

Auditor

Assessment of

AC

Tone at the Top

Proactive

Number of Audit

Procedures

AC Effectiveness

+

+

–

+

31

FIGURE 2.Observed Effects of AC Effectiveness on Audit Effort

Probing

Audit Procedure

Diagnosticity

Audit Effort

Auditor

Assessment of

AC

Tone at the TopProactive

Number of Audit

Procedures

AC Effectiveness

+ –

32

TABLE 1. Descriptive Statistics

PANEL A. Audit Efforta

Mean (Std. Dev.)

AC Questioning Behaviorb

Non-probing Probing

Collapsed Across AC

Questioning Behavior

AC Proactive

Behaviorc

Less Proactive

0.31

(1.05)

n=31

-0.33

(0.79)

n=30

-0.01

(0.98)

n=61

More Proactive

0.04

(0.93)

n=33

-0.27

(1.13)

n=33

0.01

(1.03)

n=66

Collapsed Across

AC Proactive

Behavior

0.17

(0.99)

n=64

-0.17

(0.98)

n=63

PANEL B. Number of Audit Proceduresd

Mean (Std. Dev.)


Non-probing Probing

Collapsed Across AC


AC Proactive

Behaviorc

Less Proactive

2.00

(0.93)

n=31

1.43

(0.73)

n=30

1.72

(0.88)

n=61

More Proactive

1.76

(0.83)

n=33

1.88

(1.14)

n=33

1.82

(0.99)

n=66

Collapsed Across

AC Proactive

Behavior

1.88

(0.88)

n=64

1.67

(0.98)

n=63

33

PANEL C. Audit Procedure Diagnosticitye

Mean (Std. Dev.)


Non-probing Probing

Collapsed Across AC


AC Proactive

Behaviorc

Less Proactive

3.87

(2.35)

n=31

2.93

(1.39)

n=30

3.41

(1.98)

n=61

More Proactive

3.48

(1.86)

n=33

3.03

(1.67)

n=33

3.26

(1.77)

n=66

Collapsed Across

AC Proactive

Behavior

3.67

(2.10)

n=64

2.98

(1.52)

n=63

a Audit effort was measured with the factor composed of the measures for number of audit

procedures and audit procedure diagnosticity. b AC questioning behavior was manipulated at two levels: probing vs. non-probing.

c AC proactive behavior was manipulated at two levels: more proactive vs. less proactive.

d Number of audit procedures was measured by the sum of additional procedures deemed

necessary by participants. e

Audit procedure diagnosticity was measured on a 10-point scale, based on the assessment

made by a panel of two independent audit partners, about the diagnosticity of the additional

procedures that auditors deemed necessary.

34

TABLE 2. Effects of AC Questioning Behaviora and AC Proactive Behavior

b on Audit

Effortc

PANEL A. ANOVA of Audit Effortc

Source df MS F Sig.d

AC Questioning Behavior 1 4.26 4.59 0.034

AC Proactive Behavior 1 0.03 0.03 0.859

AC Questioning Behavior * Proactive

Behavior

1 2.53 2.73 0.101

Audit Experiencee

1 6.46 6.96 0.009

Error 122

PANEL B. Planned Contrasts

t Sig.d

H1a: Audit effort will be highest under probing AC questioning

and proactive meeting behavior.

0.16

0.873

H2a: Audit effort will be highest under non-probing AC

questioning and less proactive AC meeting behavior.

2.04

0.022

a AC questioning behavior was manipulated at two levels: probing vs. non-probing.

b AC proactive behavior was manipulated at two levels: more proactive vs. less proactive.

c Audit effort was measured with the factor composed of the measures for number of audit

procedures and audit procedure diagnosticity. d

ANOVA p-values are two-tailed, and contrast tests p-values are one-tailed if results are

directionally consistent with the hypothesis. e

Audit experience was measured in months..

35

TABLE 3.Effect of AC Questioning Behaviora and AC Proactive Behavior

b on Auditor

Process Accountabilityc

PANEL A. Descriptive Statistics

Mean (Std. Dev.)


Non-probing Probing

Collapsed Across AC


AC Proactive

Behavior

Less Proactive

0.80

(1.20)

n=31

1.16

(1.03)

n=30

0.97

(1.12)

n=61

More Proactive

0.74

(1.21)

n=33

1.35

(0.73)

n=33

1.04

(1.04)

n=66

Collapsed Across

AC Proactive

behavior

0.77

(1.20)

n=64

1.26

(0.88)

n=63

PANEL B. ANOVA of Auditor Process Accountability

Source df MS F Sig.




Behavior

1 0.49 0.43 0.511

Audit Experienced

1 1.09 0.98 0.325

Error 122



c Auditor process accountability was measured with a scale composed of the following three

questions. “To what extent do you believe SCA’s audit committee will: (a) require you to

justify your responses, (b) evaluate the quality of your decision processes, (c) require you to

explain to them the process you followed in making your judgments and decisions.” Responses

to the three questions were measured on 7-point scales (-3 = extremely less than average, 3 =

extremely more than average). d

Audit experience was measured in months.

36

TABLE 4.Effect of AC Questioning Behaviora and AC Proactive Behavior

b on AC Tone at

the Topc

PANEL A. Descriptive Statistics

Mean (Std. Dev.)


Non-probing Probing

Collapsed Across AC


AC Proactive

Behavior

Less Proactive

-1.13

(1.23)

n=31

0.73

(1.11)

n=30

-0.21

(1.50)

n=61

More Proactive

-0.46

(1.28)

n=33

1.09

(0.98)

n=33

0.32

(1.38)

n=66

Collapsed Across

AC Proactive

Behavior

-0.78

(1.29)

n=64

0.92

(1.05)

n=63

PANEL B. ANOVA of AC Tone at the Top

Source df MS F Sig.

AC Questioning Behavior 1 91.22 68.41 <0.001



Behavior

1 0.82 0.61 0.435

Audit Experienced

1 1.57 1.18 0.280

Error 122



c AC tone at the top was measured on a 7-point scale (-3 to 3) with participants’ responses to the

question: “As a member of the audit team, how do you rate SCA audit committee’s tone at the

top?” (-3 = extremely weak, 3 = extremely strong). d


37

TABLE 5.Effects of AC Questioning Behaviora, AC Proactive Behavior

b, AC Tone at the

Topc, and Auditor Process Accountability

d

PANEL A. ANOVA of Audit Efforte

Source df MS F Sig.




Behavior

1 1.87 2.10 0.150

AC Tone at the Top 1 5.95 6.69 0.011

Auditor Process Accountability 1 0.12 0.14 0.711

Audit Experiencef

1 7.58 8.52 0.004

Error 120



c AC tone at the top was measured on a 7-point scale (-3 to 3) with participants’ responses to the

question: “As a member of the audit team, how do you rate SCA audit committee’s tone at the

top?” (-3 = extremely weak, 3 = extremely strong). d

Auditor process accountability was measured with a scale composed of the following three

questions. “To what extent do you believe SCA’s audit committee will: (a) require you to

justify your responses, (b) evaluate the quality of your decision processes, (c) require you to

explain to them the process you followed in making your judgments and decisions.” Responses

to the three questions were measured on 7-point scales (-3 = extremely less than average, 3 =

extremely more than average). e

Audit effort was measured with the factor composed of the measures for number of audit

procedures and audit procedure diagnosticity. f


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