The Pennsylvania State University

The Graduate School

The Mary Jean and Frank P. Smeal College of Business Administration

CHANGES IN INTERNAL CONTROLS AND AUDITOR EFFORT AROUND

THE INITITAION OF A CHIEF ACCOUNTING OFFICER (CAO) POSITION

A Dissertation in

Business Administration

by

Dan Russomanno

© 2014 Dan Russomanno

Submitted in Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy

December, 2014

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The dissertation of Dan Russomanno was reviewed and approved* by the following:

Orie E. Barron

Professor of Accounting / PwC Research Fellow

Dissertation Advisor

Committee Chair

Mark W. Dirsmith

Deloitte & Touche Professor of Accounting

Steven Huddart

Smeal Chair Professor in Accounting

Department Chair of Accounting

Henock Louis

KPMG Professor of Accounting

Donald C. Hambrick

Evan Pugh Professor and Smeal Chaired Professor of Management

*Signatures are on file in the Graduate School.

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ABSTRACT

I examine whether the addition of a Chief Accounting Officer (CAO) to the top

management team improves firms’ internal controls and allows a reduction in efforts by the

firms’ external auditors. I find firm size, auditor quality, and acquisition or restructuring activity

significantly increases the likelihood of a firm having a CAO position. After controlling for

factors associated with the decision to create the CAO position, I find that firms that establish a

CAO position on their top management team improve their internal control system more than

firms without a CAO position on their top management team. In addition, CAO firms realize a

reduction in auditor fees following the addition of a CAO position on their top management

team. Overall, these findings suggest that the introduction of a CAO position to the top

management team substantively improves the quality of firms’ internal control over financial

reporting and a reduction in the auditors’ assessment of the firms’ control risk.

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TABLE OF CONTENTS

List of Tables ...................................................................................................................................v

Acknowledgements ........................................................................................................................ vi

1.0 Introduction ................................................................................................................................1

2.0 Background and Hypotheses ......................................................................................................8

2.1.1 Background - Internal Control .............................................................................................8

2.1.2 Hypothesis 1 – Internal Control and the CAO Position .....................................................10

2.2.1 Background – Auditor Effort ............................................................................................14

2.2.2 Hypothesis 2 – Auditor Effort and the CAO Position .......................................................15

3.0 Data ..........................................................................................................................................17

3.1 Identification of firms with a CAO. ......................................................................................17

3.2 Current limitations to using a change based CAO measure. ................................................18

3.3 Audit, financial, and corporate governance data. .................................................................18

4.0 Research Design.......................................................................................................................19

4.1. The propensity to have a CAO position ...............................................................................21

4.2. Propensity-score matching ...................................................................................................27

4.3. Covariate balance of the propensity-score matched sample ................................................28

5.0 Results ......................................................................................................................................30

5.1.1 Mean differences – the CAO treatment effect on internal controls ...................................30

5.1.2 Probit regression – the CAO treatment effect on internal controls ....................................32

5.1.3 Probit regression – cross-sectional test of the CAO association on internal controls .......33

5.2.1 Mean differences – the CAO treatment effect on auditor effort ........................................34

5.2.2 Least squares regression – the CAO treatment effect on auditor effort .............................36

5.2.3 Least squares regression – cross-sectional test of the CAO association on auditor effort 37

6.0. Conclusion ..............................................................................................................................38

References ......................................................................................................................................41

Appendix A: CAO Questionnaire ..................................................................................................45

Appendix B: Examples of CAO biographies disclosed in 10-K filings ........................................47

Appendix C: An example of a CAO job posting ...........................................................................48

Appendix D: Firm-year with a CAO Position ...............................................................................51

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LIST OF TABLES

Table 1: Variable descriptions .......................................................................................................54

Table 2: Summary statistics, partitioned by CAO, for firm years with required data used to

estimate the propensity to have a CAO.

Panel A: Firm-year attrition ........................................................................................................56

Panel B: Firm-year observations by year, reports with an internal control weakness by year,

and observations by industry ......................................................................................................56

Panel C: Firm-year descriptive statistics.....................................................................................57

Table 3: Estimates of the first-stage propensity to have a CAO ....................................................58

Table 4: Summary statistics, partitioned by CAO, for the propensity-score matched sample.

Panel A: Firm attrition ................................................................................................................59

Panel B: Firm-year observations by year and industry ...............................................................59

Table 5: Test of covariate balance of the propensity-score matched sample in the pre-period .....60

Table 6: Mean difference tests of the CAO treatment effect on reporting an internal control

weakness, ICW ...............................................................................................................................61

Table 7: Estimates of the second-stage likelihood of reporting an internal control weakness, ICW

........................................................................................................................................................62

Table 8: Cross-sectional estimate of the likelihood of reporting an internal control weakness,

ICW ...............................................................................................................................................63

Table 9: Mean difference tests of the CAO treatment effect on auditor fees scaled by the square

root of assets, FEES_SQASSETS ...................................................................................................64

Table 10: Estimates of the second-stage natural log of external auditor fees, LNFEES ..............65

Table 11: Cross-sectional estimate of the natural log of external auditor fees, LNFEES .............66

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ACKNOWLEDGEMENTS

I am indebted to my dissertation chair, Orie Barron, for supporting me throughout the

many peaks and troughs of the dissertation process. Thank you for your generous amount of

care and guidance. I promise to “pay it forward” to my future students.

I am grateful for the valuable comments, time, and support from my other committee

members: Mark Dirsmith, Don Hambrick, and Henock Louis. Additionally, I am thankful for

the countless conversations and insights from Dan Givoly, Steve Huddart, and Adrienne Rhodes.

Moreover, I would like to thank many family members and friends, at home and in Happy

Valley, for their support throughout this transformative journey.

Finally, to my first and most influential teacher in life - my mother, Michele Russomanno

- thank you for your persistent love and support. Each day I draw on your countless lessons.

Your advice to “take things one step at a time” has certainly served me well.

This research was supported by funding from the Smeal College of Business. All errors

contained are my own.

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1.0 Introduction

Firms typically maintain a Chief Executive Officer (CEO) and a Chief Financial Officer

(CFO) position over their organizational lifespans. Aside from these two senior officers,

significant variation exists in the composition of top management teams across organizations.

For example, approximately 20% of the firms in this study’s sample have a separate Chief

Accounting Officer or Controller position (henceforth, the CAO position) on their top

management team.

Executive officers occupying the CAO position at most firms typically possess

significant accounting expertise and responsibility. With the exception of one other study (see

Rhodes and Russomanno, 2014), the decision to have a CAO, or consequences associated with

initiating a CAO position has received little attention by researchers. This gap in the literature is

noteworthy since the decision to have a CAO suggests: a major structural choice where

significant accounting responsibilities are spread over top level executives (e.g., the CAO and

CFO), an additional organizational layer, an investment in an additional executive position, and

an investment in the costs to support such a position.

There are many unanswered questions regarding the benefits and costs of having a CAO

position. For instance, why do some firms have a CAO on their top management teams while

others do not? Specifically, are there any factors which increase the demand for additional

accounting expertise and leadership offered by a CAO on the top management team?

Furthermore, is this accounting focused position associated with changes in accounting or

auditing related outcomes? Evidence to suggest which determinants contribute to the likelihood

of having a CAO and whether substantive changes in accounting or auditing related outcomes

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occur around the initiation of a CAO position is a large undertaking requiring a careful

examination of these aforementioned questions.

In this study, I take a step towards providing insight into understanding the CAO

phenomena. Specifically, I develop a refined CAO determinants model and examine whether

two important audit related outcomes, the report on the effectiveness of internal controls and

external auditor effort, change around the initiation of a CAO position.

An attention-based theory of firm behavior suggests firm outcomes are the result of how

firms channel and distribute the attention of their decision-makers on the top management team

(Ocasio, 1997). Given the scarce supply of managerial attention, its optimal usage is of great

concern to both managers and researchers. CEOs and CFOs are frequently tasked with many

issues. Bounded rationality forces these managers to allocate their attention across many

responsibilities.

Indeed, there are indications that there is an expansion of tasks demanding the attention

of the traditional CFO position. Over the last decade, the role of the CFO has evolved

significantly from being the financial gatekeeper to becoming more of a strategic partner and

advisor to the CEO (McKinsey, 2008). McKinsey finds 88% of 164 CFOs surveyed reported

that their CEOs expected them to be more active participants in shaping the strategy formulation

of their organizations. Initiating a CAO position may be a response firms have to the increase in

tasks demanding the attention of CFOs. Other things being equal, the establishment of a CAO

position may indicate management or other governance mechanisms, decided to devote more

attention to and investment in accounting and financial reporting matters.

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As part of my research, I conducted semi-structured interviews with CAOs across

publically listed firms to ascertain the attention placed on accounting between CAOs and CFOs

(see appendix A– CAO questionnaire). Preliminary responses suggest CAOs allocate most of

their time (over 80%) to accounting or accounting-related issues. In contrast, CAOs report that

their firms’ CFOs spend a smaller portion (about 10%) of his or her time on accounting or

accounting-related matters.1 One CAO of a large multinational firm stated, “Our CFO is the

public face of our firm’s financials – but I handle nearly all decisions impacting the financial

statements.” While another CAO stated, “Our CFO has implemented a ‘need-to-know’ policy

related to accounting matters since he or she has become spread too-thin on investor relations

and strategic initiatives.” Examining the accounting consequences associated with the CAO

position seems particularly important and timely given CAOs (CFOs) appear to be increasingly

(decreasingly) involved in accounting matters.

Given the growing demands facing CFOs and the inevitability of more limited attention

they may pay to accounting related matters, the creation of a separate CAO position is likely to

improve the financial reporting function of the business. This is particularly true since the CAO

position typically brings to the table additional accounting expertise and experience. CAOs

typically maintain a certified public accounting (CPA) license, have significant public

accounting experience, and have several years of financial statement sign-off experience. CAOs

typically report to other members of top management (e.g., their CFOs, or their CFOs and

1 The main non-accounting responsibilities occupying CAOs’ time were supporting due diligence related to mergers

and acquisitions, interacting with credit rating agencies, and administrative responsibilities. The main non-

accounting responsibilities occupying CFOs’ time relates to investor relations, strategy formulation, mergers and

acquisitions, and financing activities.

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CEOs), direct controllers across divisions, and focus on overseeing and monitoring SEC

reporting functions (Sammer, 2006; Rhodes and Russomanno, 2013).

The intuition that the expertise and experience accompanying the CAO position may

benefit accounting follows Hambrick and Mason’s (1984) “upper-echelons” theory, which

predicts organizational outcomes, strategic choices and performance levels, are partially

predicted by the managerial background characteristics of the top management team. Despite the

potential benefits offered to accounting by the CAO position’s expertise and experience, not all

publically listed firms choose to have this position on the top management team.

On the other hand, the creation of a new CAO position may simply be an idle step devoid

of substance designed to placate investors and the external auditor. This could happen in the

wake of discoveries of poor quality financial reporting where the position may be created

without the investment in, or commitment to internal control or financial reporting matters. If

this is indeed the case, the CAO position likely does little to improve the design or operations of

internal controls, or to change the firm’s attitude towards strengthening its internal control

system. Therefore, it remains unclear whether firms initiating a CAO position are better at

remediating and preventing internal control issues. Thus, the first objective of this study focuses

on providing empirical evidence as to whether the existence of a CAO position affects the

quality of the firm’s internal controls over financial reporting.

If the addition of a CAO position has a substantive effect on the attention and efforts of

the company in the areas of internal controls and financial reporting, one would expect that the

effort level of the firm’s auditor may change as well. The audit risk model suggests actions that

lower the auditor’s assessment of control risk may reduce the auditor’s effort (see Hogan and

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Wilkins, 2008). The new CAO position may be accompanied by an increase in attention to the

control environment and investment in control and reporting matters. Such additional effort may

reduce control risk and allow performance of the audit with fewer billable hours and lower fees.

Thus, auditors may reduce their effort if the new CAO position credibly reduces control risk.

This expectation seems particularly true in the long run.

However, predictions based on the audit risk model remain unclear since uncertainty

exists on how consistently and often auditors apply the audit risk model across engagements

(Barron, Pratt, and Stice, 2001). Moreover, it is unclear whether CAOs are associated with

changes in the quality of internal controls. Additionally, firms that increase managerial attention

on accounting may also prefer to have their external auditors maintain a high level of effort until

any remaining accounting issues are resolved. In the short run, auditors may maintain or

increase their effort at firms with accounting issues even with the addition of a CAO position. If

auditors perceive the creation of a CAO position as “window dressing” without substantive

changes in the firm’s behavior, the effort exerted by the external auditor may not change

following the introduction of such a position. The effect of establishing a CAO position on

auditors’ behavior remains an empirical question. Therefore, the second objective of the study

seeks to determine whether external auditor effort changes in the wake of creating a CAO

position.

Comprehensive top management team data beyond CEOs and CFOs is not readily

available. Therefore, I gather firm-year CAO data by analyzing the names and titles of

individuals signing the 10-K and mentioned in the management team disclosure. For a firm-year

to be identified as having a CAO, a person holding the title CAO (e.g., “accounting officer”,

“CAO”, “chief accountant”, “principal accountant”, or “controller”) must (1) appear, with the

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title of CAO in the signature section of the 10-K, (2) not concurrently hold the title of CFO (e.g.,

“financial officer”, “finance officer”, “CFO”), and (3) belong to the company’s “management

team” as disclosed in the 10-K.

I control for factors that may influence the choice to create the CAO position by

constructing a model for the propensity to have the CAO position, and then form a propensity-

score matched-pair sample of pre- and post-CAO firm-year observations. The CAO propensity

model suggests an increased likelihood of having a CAO for larger firms, firms with large

auditors, and firms with acquisition or restructuring activity. The acquisition and restructuring

determinant is consistent with the conjecture that CFOs at firms with such activity may face

greater strategic demands for their attention, which may increase the demand to have a CAO to

assist with accounting matters.

The propensity score matched sample used to test my hypotheses consists of 82 CAO

treatment firms (i.e., firms that initiate a CAO position) matched to 82 control firms from 2005

to 2010. I use internal control weaknesses reported in the audit opinions issued on the

effectiveness of internal controls over financial reporting to proxy for the quality of internal

controls. Following extant auditor effort literature, I use auditor fees to proxy for auditor effort

(e.g., O’Keefe, Simunic, and Stein, 1994; Bell, Landsman, and Shackelford, 2001; Chaney, Jeter,

and Shivakumar, 2004). I then test my hypotheses concerning the effects of initiating a CAO

position on the quality of firms’ internal controls and auditor effort.

The findings show that relative to the matched control firms, CAO treatment firms report

85% (80%) fewer internal control weaknesses in the first (second) year following the initiation of

a CAO position. The findings further show that relative to the matched control firms, CAO

treatment firms’ incur auditor fees approximately 12% (10%) lower in the first (second) year

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following the initiation of a CAO position. I interpret these findings as evidence consistent with

an improvement in the quality of firms’ internal controls over financial reporting and a reduction

in auditor effort following the initiation of a CAO position.

This paper makes a number of contributions to the auditing literature. The finding on the

effect of a CAO position on the quality of the firms’ internal controls contributes to previous

work on the determinants of internal control deficiencies. Findings from Doyle, Ge, and McVay

(2007a) and Ashbaugh-Skaife, Collins, and Kinney (2007) suggest firm attributes, such as size,

leverage, acquisition activity, and operational complexity impact the quality of internal controls.

However, these studies do not address the means by which firms can strengthen their internal

control system given these firm attributes are fairly stable and difficult to change, at least in the

short term. My findings contribute to the internal control literature by documenting an

improvement in internal control quality following the introduction of a CAO position.

The finding on the reduction in auditors’ efforts in the wake of the addition of a CAO

position corroborates prior research (see Hogan and Wilkins, 2008) documenting a positive

association between control risk and auditor effort. The internal control benefits offered by

initiating a CAO position may influence auditors’ assessment of control risk and ultimately

impact the auditors’ effort. This reduction in auditors’ efforts suggests evidence consistent with

firms being able to manage their control risk through the initiation of a CAO position.

The remainder of this paper proceeds as follows. Section 2 provides background details

and develops hypotheses. Section 3 explains the data and methodology taken to identify firms

with a CAO. Section 4 presents the propensity-score matched-pair research design while section

5 reports the results. Finally, section 6 offers concluding remarks and suggestions for future

research.

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2.0 Background and Hypotheses

2.1.1 Background – Internal Control:

Internal control over financial reporting has been recognized as important for ensuring

high-quality financial reporting (e.g., COSO, 1987; Kinney, 2000; Johnstone, Li, and Rupley,

2011).2 Effective internal controls help to reduce the risk that financial statement misstatements

go undetected and uncorrected during the regular course of business. Section 404 (b) of the

Sarbanes-Oxley Act of 2002 requires external auditors of public companies with accelerated filer

status to issue an opinion on management’s assertions about the effectiveness of internal

controls.3

The auditor’s reporting requirements regarding internal controls were codified in AS No.

2 (PCAOB, 2004), and later superseded by AS No. 5 (PCAOB, 2007). Auditors of accelerated

filers must obtain and document an understanding of their clients’ business and operating

environment. As part of the integrated audit, the auditor must document its understanding of the

client’s internal control system and to test internal controls in order to evaluate its design and

operating effectiveness.

The auditor may observe an internal control deficiency (ICD) while gathering evidence in

order to issue an opinion on the effectiveness of internal controls. ICDs exist when either the

2 Auditing Standard No. 5 defines internal controls over financial reporting as a process designed by or under the

supervision of the company’s principal executive and principal financial officers, or persons performing similar

functions, and affected by the company’s board of directors, management, and other personnel, to provide

reasonable assurance regarding the reliability of financial reporting and the preparation of financial statements for

external purposes in accordance with GAAP (PCAOB, 2007). 3 A firm becomes an accelerated filer if its worldwide float is at least seventy-five million dollars. The Dodd-Frank

Wall Street Reform and Consumer Protection Act of 2010 permanently exempts non-accelerated, publically traded

companies from having the auditors opine on their internal controls over financial reporting (Dodd-Frank, 2010).

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design or operation of a control does not allow management or their employees to prevent or to

detect financial statement misstatements in a timely basis during the regular course of business

(AS No. 5, Appendix 3). Conditional on its likelihood and magnitude, an ICD may be classified

further as a significant deficiency or material weakness. Significant deficiencies are less severe

than material weaknesses, yet important enough to merit attention by those responsible for

oversight of the company's financial reporting (AS No. 5, Appendix 11).4 A stand-alone

deficiency will not result in an audit opinion that internal controls are ineffective. However, the

combination of deficiencies may result in a material weakness which requires the auditor to

report a material weakness in internal control, ICW, and to issue an opinion that internal controls

over financial reporting are not effective. An ICW suggests a reasonable possibility that a

material misstatement in the company's financial statements will not be prevented or detected in

a timely basis during the normal course of business (AS No. 5, Appendix 7).5

Ashbaugh-Skaife et al. (2007) and Doyle et al. (2007a) are amongst the two earliest

studies to document determinants of internal control deficiencies. The combined findings of

Ashbaugh-Skaife et al. and Doyle et al. suggest firm characteristics such as operating

complexity, restructuring and acquisition activity, accounting risk, auditor turnover, size, firm

age, and growth increase the risk that firms have ICDs (see Leone, 2007, for additional

discussion). Hoitash, Hoitash, and Bedard (2009) and Johnstone et al. (2011) find an association

with weak corporate governance and with ICWs. These firm characteristics are likely fixed in

the short run and prior studies do not address the issue of how exactly firms can improve their

4 Auditors communicate material weaknesses and significant deficiencies to audit committees and management, and

communicate any remaining control deficiencies deemed not material and not significant only to management. 5 Auditing Standard No. 5, Appendix 7 defines the reasonable possibility of an event as the likelihood of the event as

either "reasonably possible" or "probable," consistent with terms used in Financial Accounting Standards Board

Statement No. 5, Accounting for Contingencies.

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internal control quality. Thus, it remains unclear what feasible actions firms pursue to strengthen

their internal control systems.6

In terms of consequences, several studies find a higher cost of equity capital (Ashbaugh-

Skaife, Collins, Kinney, and Lafond, 2009) for firms reporting internal control deficiencies.

Moreover, Cheng, Dhaliwal, and Zhang (2013) find increased investment inefficiency;

Hammersley, Myers, and Shakespeare (2007) find a negative market reaction; and Hogan and

Wilkins (2008) document higher auditor fees associated with the disclosure of internal control

deficiencies.

2.1.2 Hypothesis 1 – Internal Control and the CAO position:

It is important to examine if substantive accounting benefits are realized from the

initiation of a CAO position. Dirsmith, Covaleski, and Samuel (2014) articulate Fombrun’s

(1986) reasoning that forms of organizational structure, in this case, the choice to have or not

have a CAO position, may simultaneously serve as: substantive technological solutions to the

instrumental problems of production within the organization’s infrastructure (e.g., reporting an

internal control weakness or paying high auditor fees); political exchanges among contending

organizational and institutional factions within the organization’s socio-structure of exchange

relations; and social interpretations inside the organization and with its external, institutional

constituents (e.g., external auditors) within a superstructure of shared norms and values. Thus,

the presence of the CAO position might simultaneously play a substantive and/or symbolic role

6 Choi, Choi, Hogan, and Lee (2013) examine internal control weaknesses of Korean companies required to disclose

the number of employees of the firm involved in the implementation of internal controls. Choi et al. (2013) find the

proportion of employees involved in the implementation of internal controls is negatively associated with disclosing

an internal control weakness. Human resource details regarding the implementation of internal controls are not

disclosed in the United States and thus, not controlled for in this study.

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in organizations, with the relative dosage of each varying within the context of a particular

organization.

Well-designed controls should prevent or detect and correct material misstatements when

designed and operating correctly. CAOs often maintain a certified public accounting (CPA)

license, have significant public accounting experience, and have several years of financial

statement sign-off experience. Their responsibilities are focused on overseeing accounting

functions, as well as leading and monitoring the day-to-day accounting activities (Sammer, 2006;

Rhodes and Russomanno, 2014). Thus, CAOs likely offer a relevant skill set to assist with

effectively managing the remediation of internal control weaknesses in a timely manner (see

appendix B for examples of CAO biographies disclosed in the 10-K, and appendix C for an

example of a CAO job posting).

Moreover, CAOs often report to other members of top management, CFOs or CFOs and

CEOs, and support the audit committee.7 This reporting structure likely allows for the timely

communication of accounting matters to the top decision makers within an organization, and the

deployment of resources required to strengthen an internal control system.

Hambrick and Mason’s (1984) “upper-echelons” theory suggests strategic choices, which

lead to organizational outcomes, are partially predicted by the background characteristics (e.g.,

age, functional tracks, career experiences, and education) of the top management team.8 My

research provides insight into the general career experiences and credentials of CAOs.

Considerate of the upper-echelons perspective, the expertise and experience of individuals

7 Members of the top management team can support the audit committee. However, top management cannot sit on

the audit committee. Such participation would inhibit the independence of the audit committee. 8 Within the accounting literature, findings support the existence of a relationship between disclosure and the

background characteristics of management. For example, Bamber, Jiang, and Wang (2010) consider the “upper-

echelons” theory and find management’s unique disclosure styles are associated with observable background

characteristics of CEOs, CFOs, and General Counsel.

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occupying most CAO positions likely benefits firms making the strategic choice to manage

internal control issues and factors contributing to external auditor effort.

In a study examining the relation between CAOs and financial reporting quality, Rhodes

and Russomanno (2014) find financial statements from CAO firms are less likely to be restated

and have less severe restatements. However, this early study is silent as to whether changes in

internal control quality or auditor effort occur around the initiation of the CAO position.

Although both should contribute to higher financial reporting quality, neither effective internal

controls nor a higher level of auditor effort are necessary to file financial statements free of

material misstatements. Moreover, neither effective internal controls nor a higher level of

auditor effort guarantees filing accurate financial statements. It could be the case that CAO

firms have superior accountants capable of producing accurate estimates independent of the

internal control system or guidance from external auditors. My study empirically examines

changes in internal control quality and auditor effort to provide insight into our early

understanding of accounting outcomes associated with the CAO position.

A greater attention of top management to accounting issues likely strengthens the overall

tone set by top management over the accounting function. Preliminary responses from

interviews I conducted with CAOs (see appendix A – CAO questionnaire) suggests that the

interviewed CAOs spend over 80% of their time on accounting and accounting related matters

whereas these CAOs report their CFOs spend only about 10% of their time on these matters.

Indeed, the National Commission on Fraudulent Reporting states the tone set by top management

is the most important factor contributing to the integrity of the financial reporting process

(COSO, 1987). AS No. 5 considers the tone set by top management to have spillover effects on

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the effectiveness of internal controls (PCAOB, 2007).9 The tone set by top management plays a

large role in the control environment which influences managements’ identification of risk,

choices on how to record transactions and to communicate responsibilities, decisions on control

policies and procedures, and the monitoring of internal control performance over time. Initiating

a CAO position likely helps to set a tone that accounting and internal control related matters are

indeed a high priority of the top management team.

The choice to create a separate CAO position may not necessarily reflect management’s

greater attention to the accounting function. Instead, it could be a result of personalities or an

organization’s structural preferences. Even if the choice relates to pre-existing accounting

issues, it could simply be an idle step devoid of substance designed to placate investors and the

external auditor. Thus, the addition of the CAO position may serve to create the impression of

greater managerial attention to internal controls and financial reporting without the investment

in, or commitment to internal control and reporting matters to substantively change the quality of

internal controls.

Finally, although all firms likely have a senior accountant position supporting the CFO –

not all firms have such a position on the top management team. Thus, the elevation of an

accounting officer to the top management team may have little or no effect on the quality of

internal controls. In any case, my analysis is heavily biased against finding results consistent

with my hypotheses if including a CAO on the top management team is in fact trivial. Whether

or not the introduction of a CAO position is associated with an improvement in internal control

9 Insufficient control consciousness by management, management lacking the qualifications and training to meet

their responsibilities over financial reporting, the misrepresentation by client personnel to the auditor, and

management’s ability and attitude toward overriding controls are just a few potential control environment

deficiencies that may result in a material weakness, and an audit report indicating internal controls are not effective

(AU 265, Appendix).

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quality remains an empirical question. I therefore test the following hypothesis:

H1: The addition of a CAO to the executive management team reduces the likelihood of

reporting a weakness in internal controls over financial reporting.

2.2.1 Background – Auditor Effort:

The external auditor’s assessment of control risk may change if the addition of a CAO

position affects the quality of internal controls. Whereby, the auditor’s effort required to gather

evidence to support the opinion on the financial statements could change if the quality of internal

controls affects the auditor’s assessment of control risk. I discuss the audit risk model below in

order to outline the potential relation between changes in the quality of internal controls around

the initiation of a CAO position and changes in auditor effort.

Auditing Standard No. 8 (PCAOB, 2010) describes audit risk as the product of the risk of

material misstatement and detection risk. Audit risk represents the risk that the auditor issues an

unmodified opinion when in fact the financial statements are materially misstated.

Misstatements can arise from errors, which are unintentional, or fraud, which is intentional.

Misstatements may include, but are not limited to inaccuracies in the collection or processing of

data, departures from generally accepted accounting principles, omissions, incorrect estimates or

judgments, or the inappropriate selection or application of accounting policies.

The risk of a material misstatement exists independent of the auditor’s effort to audit and

detect misstatements. Although it is difficult to disentangle into its risk components, the risk of a

material misstatement is the product of inherent risk and control risk. The auditor assesses

inherent risk as the susceptibility of a relevant assertion to a material misstatement, assuming

there are no related controls. Alternatively stated, inherent risk can be thought of as the risk of a

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material misstatement coming from outside the boundary of the firm’s accounting system.

Whereas, control risk is the risk that a material misstatement will not be prevented, or detected

and corrected in a timely basis by the client’s internal control system. 10 The auditor assesses

control risk as the risk that the client’s internal control system fails to catch the misstatement.

Management is responsible for establishing and maintaining effective internal controls.

The auditor cannot change the quality of the client’s internal control system from low to high, or

vice-versa. The auditor can only assess the client’s control risk which is positively associated

with the risk of a material misstatement. The auditor’s assessment of the risk of a material

misstatement helps to shape the auditor’s decision on its planned level of detection risk.

Detection risk is the risk that the auditor will not detect a material misstatement that exists in a

relevant assertion. It is positively related to the amount of planned work required to audit the

financial statements. The auditor can select the effort (i.e., nature, extent, and timing of audit

procedures) in order to meet the level of acceptable audit risk set by the auditor and to obtain

sufficient and appropriate audit evidence to support the audit opinion. The auditor controls

detection risk and must always conduct substantive tests. However, the amount of substantive

tests may be reduced (increased) when controls can (cannot) be relied upon with a high degree of

confidence.

2.2.2 Hypothesis 2 – Auditor Effort and the CAO position:

The audit risk model suggests the auditor plans to increase (decrease) the amount of

10 The assessment of control risk covers five interrelated components of internal controls within the Committee of

Sponsoring Organizations (COSO, 1992; COSO, 2004; COSO, 2013) framework: the control environment, risk

assessment, control activities, information and communication, and monitoring.

16

effort to gather evidence in order to reduce (increase) planned detection risk.11 The negative

relation between control risk and planned detection risk implies a positive relation between

control risk and the auditor’s effort. Thus, actions that lower the auditor’s assessment of control

risk, such as strengthening the firm’s internal controls over financial reporting, may reduce the

auditor’s effort. If the addition of a new CAO position incrementally strengthens the internal

control system, one would expect the performance of the audit with fewer billable hours and

lower fees following the initiation of a CAO position.

Hogan and Wilkins (2008) find auditors’ fees, a proxy for the auditors’ efforts, are

negatively related to managements’ early disclosure of internal control deficiencies, a proxy for

control risk. However, it remains unclear how consistently and frequently auditors apply the

audit risk model in practice when planning the audit or deciding how much evidence to obtain in

order to meet the level of acceptable audit risk (e.g., Barron, Pratt, and Stice, 2001; Bedard,

1989; Mock and Wright, 1999).12 Also, it remains unclear which managerial actions firms

pursue in order to influence the auditors’ perception of control risk.

Furthermore, if the auditor perceives the creation of a CAO position as “window

dressing” without the expectation of a substantive change in the firm’s behavior, the effort

exerted by the external auditor may not change following the introduction of such a position.

Auditors may exert the same, or even a higher level of effort on audit engagements until the

remediation of ICWs is maintained over multiple engagements. How the establishment of a

11 Auditors should not simply leave audit risk above the acceptable audit risk level (i.e., leave detection risk high) or

accept higher fees without supplying additional effort to increase the amount of evidence to form an opinion on the

financial statements, as such a decision would be a violation of auditing standards.

17

CAO position affects auditors’ behavior also remains an empirical question. I therefore test the

following hypothesis:

H2: The addition of a CAO to the executive management team reduces the auditor

fees incurred by the firm.

3.0 Data

3.1 Identification of firms with a CAO:

I gather firm-year CAO data from analyzing the names and titles of individuals signing

the proxy statement on behalf of the registrant in 10-K filings contained in the SEC’s Edgar

database. Pursuant to Section 13 or 15(d) of the Securities and Exchange Act of 1934, certain

individuals must sign the 10-K on behalf of the registrant. If the position exists at the filer, the

principal executive officer, principal financial officer, controller or principal accounting officer

must sign the signature section of the 10-K.13 Any individual occupying one or more of these

positions must sign the 10-K and indicate the capacity in which they sign the report. Therefore,

CAO signatures in 10-K filings are required when the position exists at a firm and are not the

result of either a random or voluntary signing preference.

For a firm-year to be identified as having a CAO, a person holding the title CAO (e.g.,

“accounting officer”, “CAO”, “chief accountant”, “principal accountant”, or “controller”) must

(1) appear, with the title of CAO in the signature section of the 10-K, (2) not concurrently hold

the title of CFO (e.g., “financial officer”, “finance officer”, “CFO”), and (3) belong to the

company’s “management team” as disclosed in the 10-K. See appendix D for an example of the

signature section, the named executive officers, and the press release for a firm-year with a CAO

13 These signatures typically include the CEO and CFO; however, these signatures are not the SOX section 302 CEO

and CFO certifications. CAOs are not required to provide a SOX section 302 certification unless of course, the

CAO is also the CEO or CFO or otherwise mandated by the SEC.

18

position. In the example presented in appendix D, the CAO indicator equals one from meeting

the identification criteria.

3.2 Current limitations to using a changed based CAO measure:

An alternative to a firm-year based CAO variable would be to proxy for the change in

CAO status, where ∆CAO would equal one when the three identification criteria are met

following a year when the identification criteria is not met. The challenge with respect to

conducting empirical analysis with a change based CAO measured is insufficient variation in the

data. The presence of the CAO position tends to be sticky over time. That is, firms with

(without) a CAO tend to uphold their CAO choice. Few instances where ∆CAO = 1 and many

instances where ∆CAO = 0 results in insufficient variation in this variable of interest, and

presents convergence challenges when using a non-linear model with many control variables.

Furthermore, operationalizing a change based measure presents additional empirical

challenges given firms’ CAO status changes from 1 to 0 at times. That is, some firms appear to

be eliminating, or consolidate their CAO position into another executive officer position. Upon a

closer inspection, these infrequent “disappearances” result from the departure of the CAO from

the firm, or the promotion of the CAO to the CFO position. CAOs promoted to the CFO position

then serve a dual role (i.e., CFO-CAO) at least in the short term. Soon thereafter, firms select to

either backfill the CAO position, or abstain from filling the legacy position. Future research

interested in carefully examining the determinants related to a change based CAO measure may

be fruitful, and possible as more CAO data is gathered over time.

3.3 Audit, financial, and corporate governance data:

The remaining required data are from available sources. Audit Analytics provides

19

auditor fee, auditor opinion, and other audit related data. All financial accounting data comes

from Compustat. Finally, a corporate governance estimate based on institutional ownership is

calculated from data available in CRSP.

4.0 Research Design

Executives often are chosen precisely because they have the "right" background or

temperament to carry out actions hoped for by the board of directors or other controlling parties

(Hambrick and Mason, 1984). Hambrick and Mason note the occurrence of a particular set of

executive backgrounds in a firm is not a random process and any research design must

accommodate this, and interpretation of any research results must be tempered by it. With

respect to my study, determinants of the quality of the internal control system, the cost to have

the financial statements audited, and pre-existing financial reporting issues may influence a

firm’s choice to add a CAO to the executive management team. If left unaddressed, this

potential self-selection problem may lead to spurious inferences regarding the relation between

the treatment and outcome of interest from statistical tests (Francis, Lennox, and Wang, 2012).

I utilize propensity-score matching (Rosenbaum and Rubin, 1983) to control for pre-

existing observable factors that may influence CAO self-selection and follow steps outlined by

Armstrong, Jagolinzer, and Larcker (2010) to implement a propensity-score matched-pair

research design. 14 First, I estimate the probability of having a CAO in a firm-year with a logistic

regression model. The coefficients from this model are used to assign a propensity-score to each

firm-year to proxy for the probability of having a CAO at time t conditional on a firm’s

14 Another method to address this potential self-selection problem would be to use a two-stage instrumental variable

approach (Heckman, 1979). In this setting, a valid instrument would be a variable that is correlated with adding a

CAO, but uncorrelated with the error terms in second stage models for the outcome variables of interest. At this

time, I am unaware of a valid instrument to proxy for the choice to add a CAO that satisfies these requirements.

20

observable factors (i.e., covariates) at time t-1. Second, matches in the pre-period, t-1, are made

between firms with the same state of internal controls, same industry, smallest difference in

propensity-score, and a difference in CAO status in following year, t. Third, I examine the

covariate balance between the CAO treatment and control firms in the pre-period to ensure

systematic differences do not exist between the groups. Fourth, I estimate the average CAO

treatment effect on audit outcomes by testing for differences in means in reporting an internal

control weakness and auditor fees incurred in the post-CAO period, t+1 and t+2.

This propensity-score matched-pair research design has been operationalized most

recently within the audit literature by Cheng, Dhaliwal, and Zhang’s (2013) study documenting

the positive relation between internal control weaknesses and investment inefficiency. As noted

by Armstrong et al. and later by Cheng et al., this research design offers several attractive

features. First, it relaxes the assumption of a constant functional relationship with the outcome

variables of interest and it is robust to misspecification of the linear functional form.15 Second, it

controls for dimensions beyond simply matching on size, year, and industry. Third, it allows for

a stronger causal inference about the treatment effect on the outcome of interest when adequate

covariate balance between the CAO treatment and the control group in the pre-period exists.

Finally, the propensity-score matched-pair research design relaxes the need for separate

indicator variables for each match in cross-sectional tests. Rather, tests of differences in the

outcomes of interest in the post-CAO period adjust for the influences of each match by taking the

difference between each matched-pair before testing whether the mean difference is significantly

15 Prior research often selects a control firm for each treatment firm with a partial-match on several dimensions (e.g.,

year, industry, and size). With such an approach, the treatment effect would be inferred by the estimated coefficient

on a variable indicating the period treatment firms switch to having a CAO (e.g., TREAT*POST) and other factors

are controlled for through their inclusion of regression estimation. If the true relationship between the controls and

the outcome variable is inconsistent with the functional form imposed by the research design, a partial-matched

econometric method will produce biased parameter estimates (Armstrong et al., 2010).

21

different from zero in the direction hypothesized. Relaxing the need to control for each match

with separate indicator variables is critical in my study since non-linear models rely on

asymptotic theory, and controlling for each match prevents convergence when running a cross-

sectional non-linear model (e.g., predicting the likelihood of reporting an internal control

weakness) over relatively few observations.

4.1 The propensity to have a CAO position:

Determinants of internal control weaknesses, external auditor fees, and other firm

characteristics may influence a firm’s choice to have a CAO. The CAO propensity model in

equation (1) encompasses many empirical associations documented to influence the likelihood of

reporting an internal control weakness and external auditor fees. The logistic regression in

equation (1) estimates the propensity of having a CAO in year t based on controls in the prior

year, t-1 for the i th firm:

Pr (CAOi,t = 1) = a0 + ∑ bi x ICW&FeeDeterminantsi,t-1 + ∑ ci x ICWDeterminant i,t-1

+ ∑ di x FeeDeterminant i,t-1 + et (1)

As stated in detail in section 3.1, the dependent variable CAO equals one when an officer

(1) with the title CAO appears in the signature section of the 10-K, (2) is not concurrently

holding the title of CFO, and (3) is identified as an executive officer of the company’s

management team. CAO equals zero otherwise.

The independent variables in equation (1) are classified into one of three groups:

ICW&FeeDeterminant includes determinants correlated with the likelihood of reporting a material

weakness in internal controls over financial reporting, ICW, and determinants of the natural

logarithm of auditor fees, LNFEES; ICWDeterminant includes determinants mostly shown to be

correlated with reporting an ICW; and FeeDeterminant includes determinants mostly shown to be

22

correlated with LNFEES. The variable measurements within each classification are summarized

in table 1.

[Insert table 1 about here.]

The first group of control variables, ICW&FeeDeterminant, considers determinants which

overlap the internal control weakness and auditor fee literature. Doyle et al. (2007a) find that

smaller (SIZE), younger (FIRMAGE), financially weaker (LOSS), and more complex firms

(SEGMENTS) are more likely to report an ICW.16 Moreover, Cheng, Dhaliwal, and Zhang,

2013, document a negative relationship between corporate governance, measured with

institutional ownership (IO), and the likelihood of reporting an ICW.17 Within the auditor effort

literature, larger, financially weaker, more complex, and higher institutional ownership tend to

have higher auditor fees (see Hay, Knechel and Wong’s, 2006 meta-analysis of auditor fees).

The second group of control variables, ICWDeterminant, are determinants used mostly

within the internal control literature. Doyle et al. (2007a) find firms with rapid growth

(EXTREMEGROWTH) and multi-national financial reporting complexity (FOREIGNTRAN) are

more likely to report an ICW. Additionally, firms with a going concern report (GC),

experiencing a financial reporting irregularity (RESTATEMENT), and with a lower market-to-

book ratio (MB) have an increased likelihood of reporting an ICW.

The third group of control variables, FEEDeterminant, are determinants used mostly

16 I acknowledge that size largely determines auditor fees. With respect to the propensity model in equation (1), my

findings remain qualitatively similar when substituting alternative proxies for size such as the market value of equity.

Table 5 suggests there is not a significant difference in the mean of SIZE (p-value = 0.930) between the CAO treatment

and control groups in the pre-period. In an untabulated analysis, there is not a significant difference in LnAssets

between the treatment and control groups in the post-period. Furthermore, the test of a difference in auditor effort

between the two groups uses auditor fees scaled by the square root of assets to adjust for the positive relationship

between fees and assets, and to adjust for the non-linearity between fees and size (see table 9). The combined evidence

does not indicate differences in assets, or an alternative size proxy, explains my findings. 17 In the spirit of Hoitash et al.’s findings, I operationalize institutional ownership (IO) as a governance proxy and an

indicator variable (IO_AVAILABLE) to minimize the loss of observations due to the availability of CRSP data.

23

within the auditor effort literature. Firms with acquisition or restructuring related activity

(ACQORREST), a change in auditors (AUDITORTURNOVER), higher quality auditors (BIG4),

higher discretionary current accruals (DISCACC), goodwill impairment (GWIMPAIRMENT),

higher levels of inherent risk (INVENTORY) and (RECEIVABLES), higher litigation risk

(LITRISK)18, a modified independent audit opinion on the accuracy of the financial statements

(MODOPINION), and growth (SALESGROWTH) typically incur higher auditor fees. All

continuous variables are winsorized at the 1% and 99% level and standard errors from estimating

equation (1) are clustered at the firm level.

Panel A of table 2 contains a summary of the sample composition and attrition of firm-

year observations used in the propensity model for the period 2005 through early 2010.

Approximately 20% of the 21,184 firm-year observations have a CAO. After consideration for

data requirements, there are 11,173 firm-year observations (3,069 firms) assigned a propensity-

score estimating the likelihood of having a CAO. Information presented in panel B of table 2

indicates the retail, computer, and service industries have the highest frequency of having a CAO

while the agriculture, mining, and electrical industries have the lowest frequency of having a

CAO.

Mean differences across the pooled observations used to develop the CAO propensity

model in panel C of table 2 indicate CAO firm-years report fewer internal control weaknesses

(ICW = 0.023, p-value = 0.000). This mean difference in ICW is consistent with H1, and CAO

firm-years having higher quality internal controls before controlling for self-selection bias. On

the other hand, CAO firm-years incur higher auditor fees (FEES_SQASSETS = -1.590, p-value =

18 Firms from high litigation risk industries are expected to pay higher auditor fees (Francis, Philbrick, and Schipper,

1994) given auditors are sensitive to litigation risk (Barron, Pratt, and Stice, 2001).

24

0.026; LNFEES = -0.609, p-value = 0.000; FEES = -1,559, p-value = 0.000). These larger audit

fees are not consist with H2; however, this difference may be the joint product of CAO firm-

years consisting of larger firms (LNASSETS = -1.168, p-value = 0.000) and assets explaining a

significant portion of audit fees.

Additionally, at the less than 10% level of statistical significance, the mean differences

suggest CAO firm-years have a higher FIRMAGE and IO; lower MB, SALESGROWTH, and

LITRISK; more SEGMENTS, FOREIGNTRAN, ACQORREST, BIG4, GWIMPAIRMENT, and

MODOPINION; and fewer instances of AUDITORTURNOVER, LOSS, and RESTATEMENT.

The tests for differences suggest that firms with and without a CAO in the full sample differ

across almost every dimension captured in table 2, and highlights the importance of controlling

for these differences in the multivariate analysis.

[Insert table 2 about here.]

It is difficult to predict the direction and significance of many of the coefficients on the

control variables in the propensity model given the lack of research on the CAOs. However, I

offer a few expectations regarding the associations some of the control variables may have with

likelihood of having a CAO based on comments raised during my semi-structured interviews

with CAOs.

I expect firms with acquisition or restructuring related activity to have a higher

probability of having a CAO. This expectation stems from CAOs commenting that strategic

demands consume a majority of their CFOs’ time, and / or the genesis of the CAO position at

their firm was the consequence of a merger or acquisition. Thus, firms may have an increased

demand for a CAO to assist with accounting matters when simultaneously managing acquisition

or restructuring related activities.

25

I also expect larger firms and firms with larger auditors, a proxy shown to be highly

correlated with size, to have a higher propensity to have a CAO. This expectation is consistent

with CAOs conveying their firms retain audit services from the large auditing firms. Thus,

larger firms with larger auditors may have an increased demand for the potential benefits offered

by the CAO position.

Table 3 presents coefficient estimates for the propensity of having a CAO based on the

model specified in equation (1). With two-tailed p-values less than 0.10, the coefficients on

SIZE (0.000; p-value = 0.025), FIRMAGE (0.434; p-value = 0.000), IO (0.865; p-value = 0.000),

LOSS (-0.378; p-value = 0.000), SEGMENTS (0.006; p-value = 0.088), MB (-0.163; p-value =

0.000), ACQORREST (0.654; p-value = 0.093), BIG4 (0.654; p-value = 0.000), LITRISK (-

0.509; p-value = 0.000), INVENTORY (-0.634; p-value = 0.048) and SALESGOWTH (0.236; p-

value = 0.010) are statistically significant predictors of a firm having a CAO. Taken together,

size, maturity, institutional ownership, operating complexity, acquisition and restructuring

activity, auditor quality, and growth are associated with an increased likelihood, while financial

weakness, market-to-book value, litigation risk, and inventory are associated with a reduced

likelihood a having a CAO in the following year.

As expected, there is an increased likelihood of having a CAO for firms with

ACQorREST activity. This is noteworthy as this activity likely stems from the top management

team’s strategic choices. Thus, CFOs at firms with acquisition and restructuring activity may

face greater strategic demands for their attention which may increase the demand to have a CAO

to assist with accounting matters. Moreover, it is worth emphasizing that SIZE and BIG4, which

is highly correlated with auditor fees and the likelihood of reporting an ICW, significantly

26

increases the probability of having a CAO.19 Therefore, it is important to ensure the CAO

treatment and control groups are comparable in size when making statistical inferences of the

CAO treatment effect on audit outcomes.

Overall, the propensity model has a max re-scaled R-squared of 0.14. To approximate

the predictive accuracy of the propensity model, I estimate the area under the ROC (receiver

operating characteristic) curve. The estimated area under the ROC curve is 0.71. Following

Metz's (1978) guidance, this suggests the propensity model does a “fair to good job” at

predicting actual CAO status for a given year.20 The coefficients from this model are used to

assign a propensity-score to each firm-year to proxy for the probability of having a CAO in year

t conditional on observable factors in year t-1.

[Insert table 3 about here.]

Beyond these observable determinants, there may be other factors influencing the CAO

decision. For example, changes in the top management position, such as CEO or CFO turnover,

or incentives of top management to misreport, such as pay for performance sensitivity, may be

associated with the likelihood of having a CAO. At this time, requiring these measures without

additional manual collection (e.g., relying on a data set with limited coverage, such as Execucomp)

results in a reduction of 28 matches in the final matched sample size.

Furthermore, measures for audit committee effectiveness may garner further insight into

the choice to have a CAO. Currently, detailed survey instruments on audit committees which

consider the frequency the audit committee meets (e.g., Kalbers and Fogarty, 1993) do not overlap

19 In an untabulated analysis, BIG4 is decomposed into PWC, E&Y, KPMG, and D&T. The coefficient on each big

four firm was positive and significant. This suggests negative assurance that the decision to have a CAO is not

concentrated only within certain large auditors. 20 A model with low explanatory power effectively induces random matching, which increases the likelihood that

inferences will be confounded by correlated omitted variables (Armstrong et al., 2010).

27

my sample period. Moreover, requiring audit committee measures without additional manual

collection (e.g., relying on a data set with limited coverage, such as Riskmetrics) results in an

additional reduction of 13 matches in the final matched sample.21 Future research may want to

examine audit committee and other top management attributes, such as turnover and incentives, as

more CAO, audit committee, and compensation data becomes available.

4.2 Propensity-score matching procedure:

Year t indicates the year in which a treatment firm initiates a CAO position. All CAO

treatment firms must have four years of available data from one pre-period year (t-1) prior and

two post-period years (t+1 and t+2) after the initiation of the CAO position. Panel A of table 4

presents the sample attrition from the 3,069 firms with a propensity-score to the 82 treatment

firms in the matched-pair sample.

Firms tend to remediate ICDs as quickly as possible (Hammersley, Myers, and Zhou,

2012). Therefore, I restrict each matched-pair to have the same state of internal controls in the

pre-period. This restriction ensures the same percentage of ICWs between the CAO treatment

and control groups in the pre-period and eliminates the mean reverting tendency attributed to

reporting an ICW from causing spurious inferences about the average CAO treatment effect on

the quality of internal controls. A unique control firm, a firm with required data that does not

have a CAO in the same years t-1 through t+2, is matched to a CAO treatment firm in the pre-

period with the same state of internal controls, industry, and smallest difference in propensity-

score. The control firm selected within the specified caliper range (see Austin, 2011 on caliper

21 Moreover, covariate balance between the treatment and control matches is not achieved when controlling for CEO

turnover or audit committee size.

28

matching) has the closest propensity-score compared to its CAO treatment firm without

replacement.22

This matching procedure yields 164 firms, consisting of 82 treatment firms matched to 82

control firms, over 656 firm-years. Since CAOs are added to the top management team at

different points throughout the year, I drop the CAO switch year, t, and retain the 492 pre- and

post-CAO years for tests related to H1 and H2. Although audit committees contract directly with

the external auditors regarding fees, top management may exert indirect influence over the

negotiation process. Dropping the switch year eliminates the potential noise from the influence

CAOs may exert on fee negotiations related to year t, conditional on the amount of time serving

on the top management team in year t.

Panel B of table 4 summarizes the year and industry information for the propensity-score

matched-pair sample over the potential CAO switch years of 2005 through early 2010. The

matched-pairs are well balanced across industries. In addition, the industry composition for the

matched-pair sample is similar to the firm-year observations used to estimate the propensity

model. Industrials, computers, and service industries have the highest frequency of initiating a

CAO position while the transportation and electrical industries have the lowest frequency of

initiating a CAO position.

[Insert table 4 about here.]

4.3 Covariate balance of the propensity-score matched sample:

Covariate balance exists if both the CAO treatment and control groups appear similar in

22 Following Austin (2011), I maximize the number of matches while minimizing the chance of a bad match by

setting a caliper width equal to 0.2 times the standard deviation of the mean propensity scores.

29

the pre-period. A high degree of covariate balance is necessary to properly account for the

confounding effects of the observed control variables used to match the observations (Armstrong

et al., 2010). Parametric t-tests of the differences in matched pair means and non-parametric

Wilcoxan rank tests of differences in medians assess the covariate balance between the control

and CAO treatment groups in the pre-period.23

Table 5 presents the means, medians, and test results of differences in means and

medians. The p-values of the t-test and Wilcoxan rank test suggest the matching procedure

achieved a high degree of covariate balance. Specifically, all twenty-one t-tests and Wilcoxon

rank tests of differences are not statistically significant (two-tailed p-value > 0.10). This

suggests the CAO treatment and control matched pairs appear similar in the pre-period, but for

the choice to initiate a CAO position in year t. Thus, differences in these observed variables

across the CAO treatment and control groups are not likely to confound the estimate of the

average treatment effect of adding a CAO on the outcomes of interest.

Regarding the outcomes of interest, there is not a statistically significant difference in

ICW (0.000, p-value = 1.000) or FEE_SQASSETS (-0.590, p-value = 0.900) in the pre-period.24

Moreover, alternative measures of differences in auditor fees, FEES (-230,729; p-value = 0.750)

and LNFEES (-0.100, p-value = 0.520), are not statistically significant. Therefore, the CAO

treatment and control matched pairs have the same level of internal control quality and receive

comparable amounts of auditor effort in the pre-period. This high degree of comparability

mitigates the role mean reversion may play in any changes in audit outcomes in the post-period.

23 Unlike the t-test, the Wilcoxan rank test is a non-parametric test that does not assume normality of the data. This

is a particularly attractive feature since my study has a number of dichotomous variables. 24 The difference in mean ICW of 0.000, between the control and CAO treatment firms, is by design. It is the result

of the matching procedure. Section 4.2 discusses details on the matching procedure.

30

[Insert table 5 about here.]

5.0 Results

5.1.1 Mean differences – the CAO treatment effect on internal controls:

H1 predicts that on average, adding a CAO to the executive management team reduces

the likelihood of a firm reporting an internal control weakness. I interpret a smaller mean of

reporting an ICW for the CAO treatment firms in the post-CAO period as evidence consistent

with H1.

Table 6 presents the results for the average treatment effect of the CAO position on the

quality of the firm’s internal control system. In panel A of table 6, there is no difference (mean

difference = 0.000, p-value = 1.000) in ICW between the control (0.070) and CAO treatment

(0.070) firms in the pre-period. However, in year t+1, the mean ICW for control firms (0.130) is

larger than the mean ICW for the CAO treatment firms (0.020). This mean difference of 0.110

(one-tailed p-value = 0.010) and the mean difference-in-difference of -0.110 (one-tailed p-value

= 0.005) are statistically significant at the less than 1% level. CAO treatment firms realized 85%

(i.e., 1 – (.02/.13)) fewer instances of reporting an ICW relative to the control firms one year after

initiating a CAO position.

Panel B of table 6 tests the change in mean ICW between the pre- period and year t+2.

Again, the control and treatment firms have the same mean ICW in the pre- period. However, in

year t+2, the mean ICW for control firms (0.050) is larger than the mean ICW for the CAO

treatment firms (0.010). This mean difference of 0.040 (one-tailed p-value = 0.090) and the

difference-in-difference of -0.040 (one-tailed p-value = 0.084) are statistically significant at the

less than 10% level. CAO treatment firms had 80% (i.e., 1 – (.01/.05)) fewer instances of

reporting an ICW relative to the control firms two years after initiating a CAO position.

31

Given management faces incentives to remediate ICWs as quickly as possible

(Hammersly et al., 2012), time likely explains a significant portion of the narrowing in the

difference in internal control quality between the control and CAO treatment firms. The ICW

descriptive statistics for the 11,173 firm-year observations used in the propensity model are

reported in panel B of table 2. These statistics assist with putting the mean ICWs of the

propensity-matched sample from panels A and B table 6 into context.

Year over year, the instances of reporting an ICW have decreased steadily. In 2005,

18.5% of SOX 404 (b) opinions report an ICW whereas in 2010, only 3.5% reported an ICW.

This confirms that on average, firms do remediate ICWs over time. However, firm-years without

a CAO (i.e., CAO = 0) reported an ICW more often than firm-years with a CAO (i.e., CAO = 1)

for each year from 2005 through 2010. Although it is well noted, this time series effect does not

explain the difference between the control and CAO treatment groups in the post-period for at

least two reasons. First, each match occurs over the same years. Secondly, the risk of mean

reversion playing a differential role between the treatment and control groups over time is

eliminated because each match has the same ICW report in the pre- year.

In an untabulated analysis, closer inspection of the persistence of ICWs occurring in the

CAO initiation year t, the mean ICW for both CAO treatment firms and control firms is 0.10

(mean difference = 0.000, p-value = 1.000). Each CAO treatment firms remediated its ICWs

from year t by the next year, t+1. In contrast, the control firms remediated about 50% of their

ICWs from year t by the next year, t+1. This suggests firms that initiate a CAO position are

timelier at remediating internal control weaknesses. Taken together, the average treatment effect

of adding a CAO reduces the likelihood of reporting an internal control weakness, consistent

with H1.

32

[Insert table 6 about here.]

5.1.2 Probit regression– the CAO treatment effect on internal controls:

Unlike univariate analysis based on the pooled sample in table 2, the analysis in table 6

based on the propensity-score matched sample controls for various firm characteristics and

therefore is less subject to confounding effects. Relative to regression analysis, this design is

also considered superior in that it does not impose a linearity assumption for the relations

between these firm characteristics with the likelihood of reporting an internal control weakness

or auditor fees (Armstrong et al., 2010). Nevertheless, I conduct a robustness test to control for

time-specific determinants of reporting an internal control weakness with a probit regression

summarized in equation (2): 25

Pr (ICW=1)i,t = B0 + B1TREATMENTi,t, + ∑ Bi x ICWDeterminanti,t, + et (2)

ICW is the proxy for the quality of internal controls over financial reporting and equals

one if the auditor issues a SOX 404 (b) opinion that internal controls over financial reporting

contain a material weakness and zero otherwise. Table 7 presents the three time specific

estimates of the second–stage likelihood of reporting an ICW. The regressions are run for each

time period to isolate the treatment effect over time. The first column presents coefficient

estimates for the determinants in the pre-period. The pre-period is the year prior to the treatment

firms initiating a CAO position and also the year that the matches are made. Given the covariate

balance between the control and CAO treatment firms reported in table 5, I do not expect to find

a significant coefficient on TREATMENT in year t-1. The coefficient estimate of 0.186 on

TREATMENT is not statistically significant (p-value = 0.592). This suggests there is not a

25 As mentioned in section 4, the propensity-score matched-pair research design relaxes the need for separate

indicator variables for each match in cross-sectional tests. I plan to control for each match in cross-sectional tests

when more observations become available. At this time, doing so fails to satisfy the convergence criteria in a cross-

sectional non-linear model used to predict the likelihood of reporting an internal control weakness.

33

statistical difference in the likelihood or reporting an ICW between the control and CAO

treatment firms when controlling for other determinants of reporting an ICW in the pre-period,

year t-1.

The two rightmost columns of table 7 present coefficient estimates for the first (t+1) and

second (t+2) year following the treatment firms’ initiation of a CAO position. I interpret a

statistically significant negative coefficient (i.e., B1 < 0) on TREATMENT in the post-period as

evidence consistent with H1. The coefficient estimates of -0.956 (one-tailed p-value = 0.013) in

year t+1 and -0.773 (one-tailed p-value = 0.042) in year t+2 on TREATMENT are statistically

significant at the less than 5% level. This suggests CAO treatment firms have a lower likelihood

of reporting an ICW in each of the two years following the initiation of the CAO position relative

to the control firms that do not have a CAO position. The findings of this robustness test provide

evidence consistent with an improvement in the quality of the internal control system over

financial reporting for firms initiating a CAO position even after controlling for changes in

known determinants of reporting an ICW.

The combined evidence in tables 6 and 7 controls for the self-selection factors

influencing the decision to have a CAO and is consistent with H1. The addition of a CAO to the

executive management team appears to reduce the likelihood of reporting a weakness in internal

controls over financial reporting.

[Insert table 7 about here.]

5.1.3 Probit regression – cross-sectional test of the CAO association on internal controls:

Many studies utilize cross-sectional tests to explain the likelihood of reporting an internal

control weakness. In this test, I relax the propensity score matching technique and do not control

for CAO self-selection. I examine the association CAO firm-years have with reporting an

34

internal control weakness with the following cross-sectional probit regression:

Pr (ICW=1)i,t = B0 + B1CAOi,t, + ∑ Bi x ICWDeterminanti,t, + et (3)

Again, ICW is the proxy for the quality of internal controls over financial reporting and

equals one if the auditor issues a SOX 404 opinion that internal controls over financial reporting

contain a material weakness and zero otherwise, CAO is an indicator for firm-years with a CAO

position, and the ICWDeterminant variables remain as previously defined.

This cross-sectional test does not control for CAO self-selection. Thus, CAO is likely

correlated with the error term resulting in a biased regression coefficient on CAO. I report these

results for future research interested in utilizing cross-sectional tests examining internal control

weaknesses inclusive of CAO data. I expect a negative coefficient on CAO given SIZE is

positively associated with CAO, and SIZE is negatively associated ICW.

As predicted, the coefficient estimate of -0.057 on CAO is negative and statistically

significant (p-value = 0.094) in table 8. This suggests CAO firm-years have a lower likelihood

of reporting an ICW with a cross-sectional test that does not control for CAO self-selection.

[Insert table 8 about here.]

5.2.1 Mean differences – the CAO treatment effect on auditor effort:

I interpret smaller auditor fees for CAO treatment firms, relative to the matched control

firms, in the post-period as evidence consistent with H2. H2 predicts that on average, adding a

CAO to the executive management team reduces the effort supplied by auditors.

Table 9 presents the results of the average treatment effect of the CAO position on the

auditors’ efforts. It has been consistently documented that size explains a majority of the

variation in auditor fees. 26 Therefore, the outcome of interest for this test, FEES_SQASSETS,

26 As much as seventy percent of the variation in auditor fees is attributed to size alone (Hay et al., 2006; Bell,

Knechel, and Willingham, 1994).

35

follows prior literature and deflates auditor fees by the square root of assets to linearize the

relation between fees and size, and to reduce heterogeneity of variance due to size (Simunic,

1980; Kinney, Palmrose, and Scholz, 2004; Engel, Hayes, and Wang, 2010).

In panel A of table 9, the mean FEES_SQASSETS for the control (57.380) and CAO

treatment (57.970) firms are not statistically different (mean difference = -0.590; p-value =

0.440) in the pre- period. However, in year t+1, the mean FEES_SQASSETS for control firms

(62.760) is larger than the CAO treatment firms (55.360). The mean difference of 7.410 (one-

tailed p-value = 0.060) and the difference-in-difference of -8.000 (one-tailed p-value = 0.097) are

statistically significant at the less than 10% level. CAO treatment firms’ FEES_SQASSETS are

approximately 11.8% (i.e., 7.410 / 62.760) lower than the control group in the first year

following the initiation of the CAO position.

To corroborate the 11.8% estimate of the average CAO treatment effect on auditor fees, I

conducted an untabulated analysis of the average actual auditor fees for the control ($3,915,095)

and treatment ($3,427,865) firms in year t+1. The difference of $487,230 is about 12.44% (i.e.,

$487,230 / $3,915,095) lower for the CAO treatment firms relative to the matched control firms

one year following the initiation of the CAO position.

Panel B of table 9 tests for changes in FEES_SQASSETS between the pre- period and

year t+2. Again, there is not a statistically significant difference in mean FEES_SQASSETS

between the control and CAO treatment firms in the pre- period. However, in year t+2, the mean

FEES_SQASSETS for control firms (58.260) is larger than the CAO treatment firms (51.700).

This mean difference of 5.530 (one-tailed p-value = 0.080) is statistically significant at the less

than 10% level and approximately 9.5% (i.e., 5.530 / 58.260) lower than the control group in the

second year following the initiation of the CAO position. My primary inference on the treatment

36

effect is based on the level difference in scaled auditor fees in the post-CAO period. However,

the difference-in-difference of -6.120 (one-tailed p-value = 0.141) is not statistically significant.

[Insert table 9 about here.]

5.2.2 Least squares regression – the CAO treatment effect on auditor effort:

Similar to the multivariate robustness test described in section 5.1.2, I conduct a

robustness test to control for time-specific determinants of auditor fees, with a traditional linear

regression analysis summarized in equation (3):

LNFEESi,t = B0 + B1TREATMENTi,t, + ∑ Bi x FeeDeterminanti,t, + et (3)

LNFEES proxy for auditor effort and equals the natural logarithm of auditor fees. The

ideal proxy for auditor effort would consist of details related to billable hours worked for each

audit engagement. Absent of this information, I follow previous studies and utilize the natural

log of auditor fees (e.g., O’Keefe, Simunic, and Stein, 1994; Bell, Landsman, and Shackelford,

2001; Chaney, Jeter, and Shivakumar, 2004). Table 10 presents the three time specific estimates

of the second–stage natural logarithm of auditor fees. The first column presents coefficient

estimates for the determinants in the pre-period. Again, the pre-period is the year prior to the

treatment firms initiating a CAO position. I do not expect to find a significant coefficient on

TREATMENT in year t-1 given the covariate balance between the control and CAO treatment

firms presented in table 5. The coefficient estimate of -0.062 on TREATMENT is not statistically

significant (p-value = 0.365) in the pre-period. This suggests there is not a difference in

LNFEES between the control and CAO treatment firms when controlling for other determinants

of auditor fees in year t-1.

The two rightmost columns of table 10 present coefficient estimates for the first (t+1) and

second (t+2) years following the treatment firms’ initiation of a CAO position. I interpret a

37

statistically significant negative coefficient (i.e., B1 < 0) on TREATMENT in the post-period as

evidence consistent with H2 that on average, adding a CAO to the executive management team

reduces the auditor fees incurred by the firm. The coefficient estimates of -0.148 (one-tailed p-

value = 0.027) in year t+1 and -0.107 (one-tailed p-value = 0.070) in year t+2 on TREATMENT

are statistically significant at the less than 5% and 10% level, respectively. This suggests that

after controlling for other known determinants of auditor fees, the CAO treatment firms have

lower auditor fees in each of the two years following the initiation of the CAO position.

This modification in auditor behavior is consistent with lower control risk resulting from

the improvement in the quality of internal controls, and additional attention placed on accounting

at the executive management level. Taken together, the combined evidence in tables 8 and 9

controls for the self-selection factors influencing the decision to have a CAO and is consistent

with H2. The addition of the CAO position to the executive management team appears to reduce

the auditor fees incurred by the firm.

[Insert table 10 about here.]

5.2.3 Least squares regression – cross-sectional test of the CAO association on auditor effort:

Many studies utilize cross-sectional tests alone to explain auditor effort. In this test, I

relax the propensity score matching technique and do not control for CAO self-selection. I

examine the association CAO firm-years have with auditor fees with the following cross-

sectional regression:

LnFEESi,t = B0 + B1CAOi,t + ∑ Bi x FeeDeterminanti,t + et (4)

LNFEES proxy for the auditor’s effort and equals the natural logarithm of auditor fees,

CAO is an indicator for firm-years with a CAO position, and the FeeDeterminant variables

remain as previously defined.

38

This cross-sectional test does not control for CAO self-selection. Thus, CAO is likely

correlated with the error term resulting in a biased regression coefficient on CAO. Although

inferences may be spurious, I report my findings for future research interested in utilizing cross-

sectional tests examining auditor effort with CAO data. I expect a positive coefficient on CAO

given SIZE is positively associated with CAO, and SIZE explains a significant amount of the

variation in LNFEES.

Table 11 presents the regression results for the natural logarithm of auditor fees. As

predicted, the coefficient estimate of 0.255 on CAO is positive and statistically significant (p-

value = 0.000). This suggests CAO firm-years are associated with higher amounts of auditor

effort in a cross-sectional test that does not control for CAO self-selection.

[Insert table 11 about here.]

6.0 Conclusion:

This paper examines whether the addition of a Chief Accounting Officer (CAO) to the

executive management team is associated with changes in firms’ internal control quality and

auditors’ effort. I control for internal control quality, auditor fee, and governance determinants

that may influence the choice to create the CAO position with a propensity-score matched-pair

research design. I find firms that establish a CAO position strengthen their internal control

system relative to their propensity-score matched-pair control firms. Specifically, CAO

treatment firms have 85% (80%) fewer instances of reporting an internal control weakness in the

first (second) year following the initiation of a CAO position. I also find evidence that CAO

firms experience a reduction in auditor fees following the addition of a CAO position. In

particular, relative to the matched control firms, CAO treatment firms’ incur auditor fees that are

about 12% (10%) lower in the first (second) year following the initiation of a CAO position.

39

My findings contribute to the auditing literature in a number of ways. Prior research

(e.g., Doyle, Ge, and McVay, 2007a; Ashbaugh-Skaife, Collins, and Kinney, 2007) suggests firm

attributes, such as size and operating complexity, which are fairly stable and difficult to change

at least in the short term, influence the quality of internal controls. I contribute to the internal

control literature by providing evidence consistent with firms being able to manage internal

controls with the addition of a CAO to the executive management team.

The finding of a reduction in the auditor’s efforts in the wake of the addition of a CAO

position is consistent with Hogan and Wilkins’ (2008) finding that control risk is positively

associated with auditor effort. However, my findings contribute to the auditor effort literature by

providing evidence consistent with firms being able to manage their control risk, which

ultimately manifests in external auditor fees, by initiating a CAO position on the top

management team.

Finally, my findings extend the early understanding of the CAO position by presenting

evidence of firms with CAOs being more effective and timely at the remediation of internal

control weaknesses. The substantive changes in accounting outcomes around the creation of the

CAO position suggests the CAO position is more than a symbolic gesture about management’s

attitudes towards financial reporting and internal controls.

Since it appears the CAO position improves audit outcomes, future research may want to

examine whether the additional attention CFOs’ have to focus on non-accounting related matters

by adding the CAO position benefits the firm in other ways. For example, one could examine

whether firms’ merger and acquisition decisions or overall performance improves after adding a

CAO position. Such research would contribute towards answering the larger question as to

whether a net benefit is achieved from creating a CAO position.

40

Moreover, future research may want to examine the perceived “disappearance” of the

CAO position from companies over time. Why does this happen? My early thoughts based on a

cursory investigation of these instances suggest these disappearances are generally the result of

the CAO’s promotion to the CFO position. In any case, further empirical evidence is needed to

develop a fuller understanding of the CAOs’ career progression, and consequences of promoting

a CAO to the CFO position.

41

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45

Appendix A: CAO Questionnaire

Assigned Number: 10XX Responses Received Date: XX/XX/XXXX

1. BACKRGROUND, REPORTING, & RESPONSIBILITIES:

a. Is the CAO at your organization, on the executive management team?

___ Yes ___ No ___ Unsure [Space left for Comments]

b. Does the CAO at your organization, serve on the audit committee?

___ Yes ___ No ___ Unsure [Space left for Comments]

___ Yes ___ No ___ Unsure [Space left for Comments]

___ Yes ___ No ___ Unsure [Space left for Comments]

e. Does the CAO at your organization report to the CEO?

___ Yes ___ No ___ Unsure [Space left for Comments]

f. Does the CAO at your organization report to the CFO?

___ Yes ___ No ___ Unsure [Space left for Comments]

g. Does the CAO at your organization report to the Board of Directors?

___ Yes ___ No ___ Unsure [Space left for Comments]

h. Does internal audit report to the CAO at your organization?

___ Yes ___ No ___ Unsure [Space left for Comments]

2. COMMENTS & TESTIMONIALS:

[Add your response here.]

Appendix

Confidential Questionnaire on the Chief Accounting Officer (CAO) Position (page 1 of 2)

The purpose of this study, procedures to follow, duration, statement of confidentiality, right to ask

questions, and statement on voluntary participation were provided to each participant; however,

suppressed here for brevity.

d. Does the CAO at your organizations have public accounting experience (e.g., PwC, KPMG,

Grant Thornton, etc.)?

a. When was the CAO position created at your firm? What factor(s) or people (titles e.g.: CFO,

Board of Directors, audit committee, etc.) drove this decision?

c. Does the CAO at your organization maintain her / his certified public accounting (CPA)

license?

46

Appendix A: CAO Questionnaire (continued)

[Add your response here.]

[Add your response here.]

[Add your response here.]

[Add your response here.]

[Add your response and comments here.]

3. TIME ALLOCATION:

[Add your response here.]

[Add your response here.]

d. Which non-accounting activities consume most of the CFO’s time?

Appendix (continued)

Confidential Questionnaire on the Chief Accounting Officer (CAO) Position (page 2 of 2)

CAOs and CFOs may spend time on non-accounting related activities, such as investor relations,

assisting the CEO with strategy, and financing activities. Based on your experience,

approximately:

a. What percent of a CAO’s time is allocated to: accounting related matters_______? non -

accounting related matters_______?

b. Which non-accounting activities consume most of the CAO’s time?

c. What percent of a CFO’s time is allocated to: accounting related matters_______? non -

accounting related matters_______?

b. Does the CAO at your organization participate in matters related to internal controls (e.g., the

design or operation of internal controls, the documentation or remediation of internal control

deficiencies )?

c. Do you believe that having a CAO improves the internal control environment at the firm (e.g.,

the speed internal control issues are resolved)?

d. Who primarily manages the external auditor relationship (CAO, CFO, CAO & CFO, someone

else) ?

e. Do you think auditors believe firms with a CAO have a better 'tone at the top'?

f. Why do you think some firms have a separate CAO on the executive management team, while

other firms choose to have their CFO serve a dual role (i.e., as the CAO & CFO)?

47

Appendix B: Examples of CAO biographies disclosed in 10-K filings

Cellstar Corporation, 2003

http://www.sec.gov/Archives/edgar/data/913590/000093066103000881/d10k.htm

Raymond L. Durham has served as Vice President and Corporate Controller since February 2001,

Corporate Controller from November 1999 until January 2001, and acting Corporate Controller from July

1999 until November 1999. From March 1997 until July 1999, Mr. Durham served as Director of Audit

Services for the Company. Prior to joining the Company, he was with KPMG LLP, an international

independent accounting firm, from 1986 until 1997 where he held several positions including Audit

Senior Manager from 1990 until 1997. Mr. Durham is a certified public accountant.

SAKS Incorporated, 2004

http://www.sec.gov/Archives/edgar/data/812900/000119312504062258/d10k.htm

Donald E. Wright was promoted to Executive Vice President and Chief Accounting Officer in February

2001. Prior to that, he served as Senior Vice President of Finance and Chief Accounting Officer since

joining the Company in April 1997. Prior to joining the Company, Mr. Wright was a Partner with

Coopers & Lybrand LLP (the predecessor firm to PricewaterhouseCoopers LLP).

Sprint Nextel Corporation, 2008

http://www.sec.gov/Archives/edgar/data/101830/000119312509040575/d10k.htm

Christopher J. Gregoire, Vice President and Principal Accounting Officer. He was appointed Principal

Accounting Officer in October 2008. He served as Vice President and Assistant Controller of Sprint

Nextel from August 2006 through October 2, 2008. Prior to joining Sprint Nextel, he served as a Partner

at Deloitte from August 2003 through July 2006 and as a Senior Manager at Deloitte from 2000.

48

Appendix C: An example of a CAO job posting

(https://www.linkedin.com/jobs2/view/21875594)

Position

Chief Accounting Officer at GT Advanced Technologies

Overview Reporting to the CFO, the Chief Accounting Officer will lead GT’s accounting, controllership

and external financial reporting functions. This individual will partner with senior executive

management and operating unit finance and business leaders to ensure priorities are aligned with

corporate objectives and financial controls. The successful candidate will be responsible for all

accounting policies, procedures, reporting controls, financial compliance, accounting services

and process improvement. As a key leader within GT’s global organization, the CAO will be

responsible for mentoring and guiding a team of approximately 15 accounting professionals.

The company is seeking an individual with outstanding financial leadership, coaching/mentoring

and business process improvement capabilities. The ideal candidate will be highly strategic,

with strong business acumen, leadership skills, and unquestioned integrity. The role will be

instrumental in helping the company identify and maximize business opportunities, while also

playing a key role in ensuring day-to-day financial control. Given the strategic importance of

this role the CAO will have substantial interaction with the CEO, Audit Committee and global

executive team. This successful candidate will be expected to take on additional responsibilities

across the organization in due time.

Key Duties & Responsibilities

• Provide leadership and oversight of all aspects of the controllership and accounting functions of

the organization including payroll, accounts payable, billings and receivables, internal audits,

external audits, and SOX requirements.

• Be responsible for timely and accurate dissemination of financial reports and leadership

highlighting major issues and trends and commentary on variances from plan, prior year and

forecast.

• Lead initiatives to improve operating efficiencies within the finance organization and across the

company. These initiatives could include streamlining key business processes, driving system/IT

enhancements and improving staff productivity.

• Maintain and further implement the system of internal controls throughout the company.

Ensure that the appropriate control systems are in effect across the company and that they are

appropriately updated as required by business changes to insure the integrity of reported results

and to maintain Sarbanes-Oxley compliance. Extend control systems throughout the operating

management team to allow the company to scale without loss of control discipline.

• Serve as an indispensable advisor/business partner to the CFO in all corporate controllership

matters to drive value creation.

• Manage quarterly and annual reporting including the completion of financial statements and

footnotes, management’s discussion and analysis encompassing review of all new accounting

matters, application of judgment, and significant matters for discussion with disclosure

committee.

• Provide accurate management information, sourcing data from across the company. Control

49

the flow and integrity of data. Help broaden and deepen management information to meet

operating and strategic decision-making needs.

• Manage the external audit relationship and the preparation of all audit committee materials.

Lead the resolution of all complex technical accounting matters including revenue recognition

issues.

• Support ad hoc analyses for the leadership team and Board of Directors as appropriate or

requested.

• Support the selection, negotiation and due diligence processes for acquisition targets. Oversee

and coordinate the financial and accounting diligence efforts and integration process. Manage

consolidation of accounting and reporting requirements for acquisitions.

• Hire, retain and develop a world-class financial staff to meet the future needs of the company,

developing successor plans for key staff positions and high potential individuals. Continually

enhance the skill levels of the group, manage performance and provide personal and career

growth through leadership and example. Communicate regularly on issues and needs within the

finance team. Build a confident, knowledgeable and effective team.

• Maintain the integrity of the company’s financial systems and data. Provide leadership in the

integration of systems, data and workflow to promote improved management information and

operating efficiency.

Competencies

• Financial Acumen and Stewardship: In the context of a global company that has been built

through acquisitions and organic growth, the successful candidate will bring exceptional

technical accounting skills and elevate the level of operational focus and decision support

without adversely affecting the company’s ability to report timely and accurate financial

information. Finding the ideal balance between business support and compliance/technical

accounting rigor will be critical.

• Business Partnership/Leadership: The successful candidate will gain credibility with senior

operating and financial executives by displaying superior communication skills and consistently

delivering outstanding work product in a timely fashion; creating a team atmosphere in which

people work together effectively to produce superior results; and mentoring and coaching the

finance team and helping them advance within the organization. In a fast paced and rapidly

changing environment where influencing skills and collaboration are critical, the successful

candidate will help to create a highly efficient and service-oriented finance organization by

examining both the operational and financial dimensions of the business; implementing process

improvements; and enhancing the quality of forecasting, KPI tracking and financial reporting.

Desired Skills and Experience

• The ideal candidate will have a minimum of 5 years’ experience as a CAO / Corporate

Controller with 15-plus years of progressive financial management experience with publicly

traded, high growth, multi-national/global, diversified high technology manufacturing

companies.

• Leadership responsibility for the GAAP/Non-GAAP accounting, SEC financial reporting, and

financial systems management of a global public company. Competent technical accounting

skills including dealing with complex accounting and revenue recognition issues.

• Expertise in issues specific to high volume manufacturing environments including cost

accounting, factory cost pools, standard cost, variance analysis and overhead

50

absorption. Demonstrated ability to drive product cost reduction and operating expense

rationalization initiatives.

• Experience managing domestic and international financial operations and audits.

• Experience with Enterprise Resource Planning systems supporting finance, accounting and

reporting; the ideal candidate will have experience improving processes in the context of

efficient and effective use of financial systems and reporting tools. Experience in an SAP

environment required.

• CPA, Big Four accounting experience with a bachelor’s degree in Accounting, Finance or a

related degree. MBA preferred.

• Effective interpersonal skills; must be able to relate to and work cross-functionally with a wide

variety of professionals across different cultures. A certain level of travel will be required to

GT’s locations domestically and in Asia.

• Evident leadership skills; a demonstrated record of building strong teams, setting high

performance standards, challenging people to excel, and eliciting their sustained high

performance.

• Impeccable integrity; words and actions must continually reinforce this characteristic.

• Exceptional communication skills; experienced and effective in interacting with senior

executives and line management at all levels. Credible, persuasive and clear in both oral and

written presentations.

About this company

GT Advanced Technologies, Inc. is a diversified technology company with innovate crystal

growth equipment and solutions for the global solar, LED and electronics industries. The

products we develop help drive the growth of the renewable energy industry by improving

performance and lowering cost. Our expanding foundation of products reflects our strategic

commitment to driving growth opportunities for the company and in our continued investment in

R&D.

51

Appendix D: Firm-year with a CAO position (i.e., CAOi,t = 1).

For a firm-year to be labeled as a CAO firm-year, a person holding the title CAO (e.g., “accounting officer”, “CAO”, “chief

accountant”, “principal accountant”, or “controller”) must (1) appear, with the title of CAO in the signatures section of the 10-K, (2)

not concurrently holding the title of CFO (e.g., “financial officer”, “finance officer”, “CFO”), and (3) belong to the company’s

“management team” as disclosed in the 10-K filed by the company. The 10-K filing with the SEC for Analog Devices, INC is

available at http://www.sec.gov/Archives/edgar/data/6281/000095012309065635/b76910e10vk.htm . See notation of the three criteria

in the example below:

(1.)

(2.)

52

Appendix D: Firm-year with a CAO position (i.e., CAOi,t = 1) - continued

(3.)

53

Appendix D: Firm-year with a CAO position (i.e., CAOi,t = 1) - continued

Analog Devices, INC’s 8-K filing with the SEC for its press release indicating the promotion of the corporate controller position to the

corporate controller, and chief accounting officer (CAO) position is available at the following link and provided below:

https://www.sec.gov/Archives/edgar/data/6281/000095013508007715/b73110adexv99w2.htm:

54

Variable

Variables of Interest:

CAO = one when an officer (1.) with the title CAO (e.g., “accounting officer”,

“CAO”, “chief accountant”, “principal accountant”, "controller") appears

in the signature section of the 10-K, (2.) is not concurrently holding the title

of CFO (e.g., “financial officer”, “finance officer”, “CFO”), and (3.) is

identified as an executive officer of the company’s “management team” as

disclosed in section 4 or section 10 within the 10-K. CAO equals zero

otherwise.

TREATMENT = one for firms with required data that initiate a CAO position in year t and

retain the CAO position in the post- period. TREATMENT equals zero for

the propensity-score matched control firms that do not have a CAO position

in years t-1 through t+2.

Outcomes of Interest:

ICW = one if the auditor issues a SOX 404 opinion that internal controls over

financial reporting contain a material weakness and zero otherwise.

FEES_SQASSETS = the annual external audit fees scaled by the square root of assets.

LNFEES = the natural logarithm of the annual external audit fees.

FEES = the annual external audit fees (in thousands).

Determinants of ICWs & Audit Fees:

SIZE = assets (in millions).

FIRMAGE = the natural logarithm of the number of years of Compustat data for each firm

at time t.

IO = the portion of institutional ownership in the firm.

IO_AVAILABLE = one when institutional ownership data is available and zero otherwise.

LOSS = one if income before extraordinary items was negative in the current or either

of the two previous years and zero otherwise.

LNASSETS = the natural logarithm of assets.

SEGMENTS = the number of operating, business, and geographic segments.

Determinants of reporting an ICW:

EXTREMEGROWTH = one when the year-over-year percentage change in sales is in the top

industry-year quintile and zero otherwise.

FOREIGNTRAN = one if the firm has non-zero foreign currency translation adjustments and

zero otherwise.

GC = one if a firm receives a going concern opinion during the year and zero

otherwise.

MB = the market value of a firm's equity scaled by its assets at year end.

RESTATEMENT = one if a restatement is disclosed in either of the prior two years and zero

otherwise.

Determinants of Audit Fees:

ACQORREST = one when a firm has acquisition or restructuring costs and zero otherwise.

AUDITORTURNOVER = one if a firm experienced an auditor change and zero otherwise.

BIG4 = one if the financial statements for the year were audited by one of the four

largest accounting firms and zero otherwise.

DISCACC = discretionary current accruals estimated following Jones, 1991 by two digit

SIC code.

Table 1

Variable descriptions.

55

GWIMPAIRMENT = one if a firm recognized a goodwill impairment during the year and zero

otherwise.

INVENTORY = total inventory divided by lagged total assets.

LITRISK = one for firms with SIC codes in a high litigation risk industry (Francis,

Philbrick, and Schipper, 2004) and zero otherwise. High litigation risk

industries include: 2833 through 2836, 3570 through 3577, 3600 through 3674,

5200 through 5961, 7370 through 7374, and 8731 through 8734.

MODOPINION = one when the financial statement audit report includes anything other than a

standard unqualified audit opinion and zero otherwise.

RECEIVABLES = total accounts receivable divided by lagged total assets.

SALESGROWTH = the year-over-year percentage change in sales.

Industry Classification = 18 industry classifications following Ge and McVay, 2005. compiled using

the following SIC codes: Agriculture 100–999; Mining: 1000–1299,

1400–1999; Food: 2000–2199; Textiles: 2200–2799; Drugs: 2830–2839,

3840–3851; Chemicals: 2800–2829, 2840–2899; Refining: 300–1399,

2900–2999; Rubber: 3000–3499; Industrial: 3500–3569, 3580–3659; Electrical:

3660–3669, 3680–3699; Miscellaneous Equipment: 3700–3839, 3852–3999;

Computers: 3579, 3670–3679, 7370–7379; Transportation: 4000–4899;

Utilities: 4900–4999; Retail: 5000–5999; Banks: 6000–6999; Services:

7000–7369, 7380–8999; Miscellaneous: 9000–9999.

Table 1

Variable descriptions (continued).

56

Required Data

Firm-years with CAO status: 16,896 79.8% 4,288 20.2% 21,184 100.0%

Previous line with required

internal control data: 12,130 57.3% 3,879 18.3% 16,009 75.6%

Previous line with required audit

fee data: 8,070 38.1% 3,103 14.6% 11,173 52.7%

Total Firm-Years over 3,069 Firms: 8,070 38.1% 3,103 14.6% 11,173 52.7%

Year

2005 1,273 70.1% 543 29.9% 1,816 16.3%

2006 1,608 72.1% 621 27.9% 2,229 19.9%

2007 1,643 72.9% 610 27.1% 2,253 20.2%

2008 1,679 73.0% 621 27.0% 2,300 20.6%

2009 1,648 72.8% 615 27.2% 2,263 20.3%

2010 219 70.2% 93 29.8% 312 2.8%

Total: 8,070 72.2% 3,103 27.8% 11,173 100.0%

Reports with an ICW by Year N % ICW=1 N % ICW=1 N % ICW=1

2005 256 20.1% 80 14.7% 336 18.5%

2006 221 13.7% 75 12.1% 296 13.3%

2007 174 10.6% 48 7.9% 222 9.9%

2008 131 7.8% 41 6.6% 172 7.5%

2009 81 4.9% 17 2.8% 98 4.3%

2010 9 4.1% 2 2.2% 11 3.5%

Total: 872 10.8% 263 8.5% 1,135 10.2%

Industry

Computers 1,523 82.8% 317 17.2% 1,840 16.5%

Retail 987 72.6% 372 27.4% 1,359 12.2%

Services 902 77.7% 259 22.3% 1,161 10.4%

Drugs 980 86.6% 152 13.4% 1,132 10.1%

Transportation 508 67.0% 250 33.0% 758 6.8%

Misc. Equipment 516 70.8% 213 29.2% 729 6.5%

Industrial 385 66.5% 194 33.5% 579 5.2%

Refinings 312 54.9% 256 45.1% 568 5.1%

Textiles 355 62.9% 209 37.1% 564 5.0%

Rubber 336 64.9% 182 35.1% 518 4.6%

Utilities 249 54.0% 212 46.0% 461 4.1%

Chemicals 227 65.4% 120 34.6% 347 3.1%

Banks 196 64.3% 109 35.7% 305 2.7%

Electrical 223 73.4% 81 26.6% 304 2.7%

Food 182 64.3% 101 35.7% 283 2.5%

Mining 123 68.3% 57 31.7% 180 1.6%

Other 41 100.0% - 0.0% 41 0.4%

Agriculture 23 71.9% 9 28.1% 32 0.3%

Micellaneous 2 17% 10 83% 12 0%

Total 8,070 72% 3,103 28% 11,173 100%

Table 2

Summary statistics, partitioned by CAO, for firm-years with required data used to estimate the propensity of

having a CAO in table 3.

Panel B: Firm-year observations by year, reports with an ICW by year, and observations by industry:

Panel A: Firm-year attrition:

CAO = 0 CAO = 1 Total

CAO = 0 CAO = 1 Total

57

Variable

Mean Std. Dev. Mean Std. Dev. Difference p-Value

Choice of Interest:

CAO 0.000 0.000 1.000 0.000 -1.000 0.000

Outcomes of Interest:

ICW 0.108 0.310 0.085 0.279 0.023 0.000

FEES_SQASSETS 55.858 33.775 57.449 34.241 -1.590 0.026

LNFEES 13.958 0.929 14.567 0.983 -0.609 0.000

FEES (in thousands) 1,898 2,713 3,457 4,004 -1,559 0.000

Determinants of ICWs & Audit Fees:

SIZE 2,706 10,803 6,914 16,686 -4,208 0.000

FIRMAGE 2.721 0.689 3.116 0.708 -0.394 0.000

IO 0.588 0.291 0.656 0.283 -0.068 0.000

IO_AVAILABLE 0.907 0.291 0.911 0.284 -0.005 0.431

LOSS 1.426 1.916 0.954 1.705 0.472 0.000

LNASSETS 6.398 1.489 7.566 1.586 -1.168 0.000

SEGMENTS 36.481 34.868 43.034 38.691 -6.552 0.000

Determinants of reporting an ICW:

EXTREMEGROWTH 0.203 0.402 0.157 0.364 0.046 0.000

FOREIGNTRAN 2.305 1.977 2.621 1.902 -0.316 0.000

GC 0.010 0.098 0.010 0.101 -0.001 0.756

MB 1.600 1.377 1.245 1.136 0.355 0.000

RESTATEMENT 0.112 0.315 0.095 0.294 0.017 0.012

Determinants of Audit Fees:

ACQORREST 0.337 0.473 0.410 0.492 -0.073 0.000

AUDITORTURNOVER 0.063 0.243 0.044 0.204 0.020 0.000

BIG4 0.844 0.363 0.930 0.255 -0.086 0.000

DISCACC 0.125 0.970 0.093 0.840 0.032 0.103

GWIMPAIRMENT 0.102 0.302 0.115 0.319 -0.013 0.038

INVENTORY 0.109 0.135 0.107 0.121 0.003 0.368

LITRISK 0.390 0.488 0.240 0.427 0.150 0.000

MODOPINION 0.555 0.497 0.624 0.484 -0.069 0.000

RECEIVABLES 0.155 0.134 0.151 0.114 0.004 0.108

SALESGROWTH 0.185 0.414 0.152 0.345 0.032 0.000

CAO = 0 CAO = 1 Total

See table 1 for variable descriptions.

Panel C: Firm-year descriptive statistics:

Table 2

Summary statistics, partitioned by CAO, for firm-years with required data used to estimate the propensity

of having a CAO in table 3 (continued).

58

Coefficient Wald χ2 p-valueINTERCEPT -2.471 86.023 0.000 ***

Determinants of ICWs & Audit Fees:

FEES_SQASSETS 0.001 1.437 0.231

SIZE 0.000 4.994 0.025 **

FIRMAGE 0.434 47.629 0.000 ***

IO 0.865 18.964 0.000 ***

IO_AVAILABLE -0.657 12.264 0.000 ***

LOSS -0.378 21.993 0.000 ***

SEGMENTS 0.006 2.908 0.088 *

Determinants of reporting an ICW:

EXTREMEGROWTH 0.022 0.058 0.810

FOREIGNTRAN 0.088 1.055 0.304

GC -0.218 0.477 0.490

MB -0.163 17.889 0.000 ***

RESTATEMENT -0.029 0.088 0.767

Determinants of Audit Fees:

ACQORREST 0.110 2.378 0.093 *

AUDITORTURNOVER -0.053 0.210 0.647

BIG4 0.654 22.958 0.000 ***

DISCACC 0.002 0.007 0.935

GWIMPAIRMENT 0.069 0.649 0.421

INVENTORY -0.634 3.896 0.048 **

LITRISK -0.509 29.704 0.000 ***

MODOPINION 0.039 0.504 0.478

RECEIVABLES -0.530 2.616 0.106

SALESGROWTH 0.236 6.662 0.010 ***

Firm/Year cluster Yes

Max re-scaled R -squared 0.14

Firm-year observations 11,173

Area under the ROC curve 0.71

See table 1 for variable descriptions. All continuous variables are winsorized at the 1% and 99% level.

Standard errors are clustered at the firm level. Two-tailed p-value indicating statistical significance at the

0.10, 0.05, and 0.01 levels are denoted with a *, **, and *** respectively.

Table 3

Estimates of the first-stage propensity to have a CAO.

where i and t represent firm and year respectively.

Logistic Regression for:

Pr(CAO i,t = 1) = a 0 + ∑b i x ICW&FeeDeterminanti, t-1 + ∑c i x ICWDeterminanti, t-1

+ ∑d i x FeeDeterminanti, t-1 + ε t

59

Firms with a CAO propensity-score (from panel A of table 2): 3,069

82

CAO treatment firms' firm-years: 328

Firm-Years

2005 33 50% 33 50% 66 10%

2006 74 50% 74 50% 148 23%

2007 82 50% 82 50% 164 25%

2008 82 50% 82 50% 164 25%

2009 49 50% 49 50% 98 15%

2010 8 50% 8 50% 16 2%

Total: 328 50% 328 50% 656 100%

Industry

Computers 52 55.3% 42 44.7% 94 14.3%

Industrial 32 42.1% 44 57.9% 76 11.6%

Services 28 43.8% 36 56.3% 64 9.8%

Misc. Equipment 24 50.0% 24 50.0% 48 7.3%

Retail 24 50.0% 24 50.0% 48 7.3%

Drugs 24 51.1% 23 48.9% 47 7.2%

Chemicals 20 50.0% 20 50.0% 40 6.1%

Utilities 20 50.0% 20 50.0% 40 6.1%

Textiles 20 51.3% 19 48.7% 39 5.9%

Banks 20 52.6% 18 47.4% 38 5.8%

Food 16 50.0% 16 50.0% 32 4.9%

Refinings 16 50.0% 16 50.0% 32 4.9%

Rubber 12 50.0% 12 50.0% 24 3.7%

Transportation 8 47.1% 9 52.9% 17 2.6%

Electrical 8 66.7% 4 33.3% 12 1.8%

Other 4 80% 1 20% 5 1%

Total 328 50% 328 50% 656 100%

This table presents firm attrition, year, and industry summary statistics between the propensity-

score matched CAO treatment and control firms with the same level of ICW in year t -1. See

table 1 for variable descriptions. CAO treatment firms initiate a CAO position in year t and

retain the CAO position in the post- period. In contrast, the propensity-score matched control

firms without replacement do not have a CAO position in years t -1 through t +2.

CAO treatment firms initiating a CAO position in year t with pre- (t -1)

and post- (t +1 and t +2) required data:

Table 4

Summary statistics, partitioned by CAO, for the propensity-score matched sample.

Panel A: Firm attrition:

Panel B: Firm-year observations by year, reports with an ICW by year, and observations by

Control Firms CAO Firms Total

60

Variable N

Control

Firms

CAO

Firms difference p-value

Control

Firms

CAO

Firms difference p-value

Outcomes of Interest:

ICW 82 0.070 0.070 0.000 1.000 0.000 0.000 0.000 1.000

FEES_SQASSETS 82 57.380 57.970 -0.590 0.900 55.096 49.336 5.760 0.726

FEES 82 3,183 3,387 -204 0.750 1,826 2,107 -281 0.778

LNFEES 82 14.460 14.560 -0.100 0.520 14.418 14.561 -0.143 0.932

Determinants of ICWs & Audit Fees:

FIRMAGE 82 3.000 3.090 -0.090 0.390 2.970 3.090 -0.120 0.307

IO 82 0.650 0.670 -0.020 0.700 0.718 0.753 -0.034 0.490

IO_AVAILABLE 82 0.910 0.900 0.010 0.790 1.000 1.000 0.000 1.000

LOSS 82 0.680 0.680 0.000 1.000 0.000 0.000 0.000 1.000

SEGMENTS 82 43.760 40.640 3.120 0.500 8.000 8.500 -0.500 0.241

SIZE 82 27,707 26,553 1,153 0.930 1,180 1,756 -576 0.673

Determinants of reporting an ICW:

EXTREMEGROWTH 82 0.130 0.070 0.060 0.200 0.000 0.000 0.000 0.302

FOREIGNTRAN 82 2.720 2.960 -0.240 0.390 1.000 1.000 0.000 0.327

GC 82 0.000 0.000 0.000 1.000 0.000 0.000 0.000 1.000

MB 82 1.550 1.650 -0.100 0.580 1.315 1.365 -0.050 0.550

RESTATEMENT 82 0.180 0.130 0.050 0.400 0.000 0.000 0.000 0.406

Determinants of Audit Fees:

ACQORREST 82 0.390 0.460 -0.070 0.350 0.000 0.000 0.000 0.296

AUDITORTURNOVER 82 0.040 0.040 0.000 1.000 0.000 0.000 0.000 1.000

BIG4 82 0.960 0.960 0.000 1.000 1.000 1.000 0.000 1.000

DISCACC 82 0.130 0.080 0.050 0.570 0.036 0.022 0.013 0.377

GWIMPAIRMENT 82 0.050 0.110 -0.060 0.150 0.000 0.000 0.000 0.267

INVENTORY 82 0.120 0.110 0.000 0.820 0.095 0.073 0.022 0.416

LITRISK 82 0.240 0.210 0.040 0.580 0.000 0.000 0.000 0.453

MODOPINION 82 0.610 0.660 -0.050 0.520 1.000 1.000 0.000 0.406

RECEIVABLES 82 0.180 0.160 0.020 0.260 0.142 0.130 0.011 0.269

SALESGROWTH 82 0.180 0.140 0.040 0.420 0.099 0.097 0.002 0.721

This table presents tests of differences between the propensity-score matched CAO treatment and control firms with the

same level of ICW in year t -1. See table 1 for variable descriptions. CAO treatment firms initiate a CAO position in year t

and retain the CAO position in the post-period where as their matched control firms without replacement do not have a

CAO position in years t -1 through t +2. Mean and median differences are reported. The Wilcoxan rank test is a non-

parametric test of a difference in medians. Two-tailed p-values indicating statistical significance at the 0.10, 0.05, and

0.01 levels are denoted with a *, **, and *** respectively.

Table 5

Test of covariate balance of the propensity-score matched sample in the pre-period.

Mean

Matched Pair

t-Test Median

Matched pair

Wilcoxan Rank Test

61

Panel A:

N Control

Firms

CAO

Firms

Matched pair

Differencep-Value N

Control

Firms

CAO

Firms

Matched pair

Differencep-Value Diff-in-Diff p-Value

82 0.070 0.070 0.000 1.000 82 0.130 0.020 0.110 0.010 *** -0.110 0.005 ***

Panel B:

N Control

Firms

CAO

Firms

Matched pair

Differencep-Value N

Control

Firms

CAO

Firms

Matched pair

Differencep-Value Diff-in-Diff p-Value

82 0.070 0.070 0.000 1.000 82 0.050 0.010 0.040 0.090 * -0.040 0.084 *

Panel A compares the average ICW for years t -1 and t +1 between the propensity-score matched CAO treatment and control firms with the same level of ICWs in year t -

1. Panel B compares the average ICW for years t -1 and t +1 between the propensity-score matched CAO treatment and control firms with the same level of ICWs in year

t- 1. See table 1 for variable descriptions. CAO treatment firms initiate a CAO position in year t and retain the CAO position in the post- period whereas their matched

control firms without replacement do not have a CAO position in years t -1 through t +2. Differences reported are the mean difference of the 82 matched pairs. One-tailed

p-values indicating statistical significance at the 0.10, 0.05, and 0.01 levels are denoted with a *, **, and *** respectively.

Year = t + 2Year = t -1

Pre-period Post-period

Table 6

Mean difference tests of the CAO treatment effect reporting an internal control weakness, ICW.

Year = t -1 Year = t + 1

62

Coef. p-valuePred.

sign Coef. p-valuePred.

sign Coef. p-valueINTERCEPT -1.312 0.312 -0.957 0.347 0.977 0.671

Determinants of reporting an ICW:

TREATMENT 0.186 0.592 - -0.956 0.013 ** - -0.773 0.042 **

SIZE 0.000 0.257 0.000 0.019 ** -0.001 0.007 ***

MB -0.490 0.117 -0.004 0.983 -0.502 0.219

SEGMENTS 0.067 0.007 *** -0.006 0.766 -0.047 0.469

FIRMAGE -0.123 0.745 -0.200 0.551 0.114 0.855

LOSS 0.948 0.114 0.245 0.552 -0.669 0.364

RESTATEMENT 0.949 0.060 * 0.944 0.027 ** -3.933 0.000 ***

FOREIGNTRAN -0.058 0.907 1.307 0.013 ** 1.470 0.073 *

EXTREMEGROWTH 0.630 0.350 -0.802 0.040 ** -5.555 0.000 ***

GC 2.536 0.012 **

IO -1.487 0.109 -0.057 0.954 -1.459 0.566

IO_AVAILABLE 0.458 0.503 -0.270 0.751 -0.911 0.589

Max re-scaled R -squared 0.329 0.399 0.529

Firm-year observations 164 164 164

Year t -1

See table 1 for variable descriptions. TREATMENT equals 1 for firms that initiate a CAO position in year t and

retain the CAO position in the post-period. TREATMENT equals 0 for the propensity-score matched control

firms that do not have a CAO position in years t -1 through t +2. All continuous variables are winsorized at the

1% and 99% level. Two-tailed p-value indicating statistical significance at the 0.10, 0.05, and 0.01 levels are

denoted with a *, **, and *** respectively. One-tailed p-value indicating statistical significance at the 0.10,

0.05, and 0.01 levels are denoted with a *, **, and *** respectively for the predicted negative coefficient on

TREATMENT in the post-periods.

Table 7

Estimates of the second-stage likelihood of reporting an internal control weakness, ICW.

Pr(ICW i,t = 1) = B 0 + B 1 TREATMENT i,t + ∑B i x ICWDeterminanti, t + ε t

Post-period

Year t +1 Year t +2

Probit Regression for:

Pre-period

where i and t represent firm and year respectively.

63

Predicted Sign Coef. p-value

INTERCEPT -2.358 0.000 ***

Determinants of reporting an ICW:

CAO - -0.057 0.094 *

SIZE 0.000 0.000 ***

MB -0.142 0.000 ***

SEGMENTS 0.000 0.926

FIRMAGE 0.014 0.643

LOSS 0.361 0.000 ***

RESTATEMENT 0.841 0.000 ***

FOREIGNTRAN 0.173 0.000 ***

EXTREMEGROWTH 0.101 0.027 **

GC 0.617 0.000

IO -0.355 0.000 ***

IO_AVAILABLE 0.273 0.001 ***

Max re-scaled R -squared 0.1981

Firm-year observations 11,173

See table 1 for variable descriptions. CAO equals 1 for firms-years with a Chief Accounting Officer position on

the top management team and 0 otherwise. All continuous variables are winsorized at the 1% and 99% level.

Two-tailed p-value indicating statistical significance at the 0.10, 0.05, and 0.01 levels are denoted with a *, **,

and *** respectively. One-tailed p-value indicating statistical significance at the 0.10, 0.05, and 0.01 levels

are denoted with a *, **, and *** respectively for the predicted negative coefficient on CAO .

Table 8

Cross sectional estimate of the likelihood of reporting an internal control weakness, ICW.

Probit Regression for:

Pr(ICW i,t = 1) = B 0 + B 1 CAO i,t + ∑B i x ICWDeterminanti, t + ε t

where i and t represent firm and year respectively.

64

Panel A:

N Control

Firms

CAO

Firms

Matched pair

Differencep-Value N

Control

Firms

CAO

Firms

Matched pair

Differencep-Value Diff-in-Diff p-Value

82 57.380 57.970 -0.590 0.440 82 62.760 55.360 7.410 0.060 * -8.000 0.097 *

Panel B:

N Control

Firms

CAO

Firms

Matched pair

Differencep-Value N

Control

Firms

CAO

Firms

Matched pair

Differencep-Value Diff-in-Diff p-Value

82 57.380 57.970 -0.590 0.440 82 58.260 51.700 5.530 0.080 * -6.120 0.141

Panel A compares the average FEES_SQASSETS for years t -1 and t +1 between the propensity-score matched CAO treatment and control firms with

the same level of ICWs in year t -1. Panel B compares the average FEES_SQASSETS for years t -1 and t +2 between the propensity-score matched CAO

treatment and control firms with the same level of ICWs in years t -1. See table 1 for variable descriptions. FEES_SQASSETS is winsorized at the 1%

and 99% level to mitigate the influence of outliers. Audit fees are deflated by the square root of assets to adjust for the non-linear relation between fees

and size, and to reduce heterogeneity of variance due to size. CAO treatment firms initiate a CAO position in year t and retain the CAO position in the

post- period whereas their matched control firms without replacement do not have a CAO position in years t -1 through t +2. Differences reported are the

mean difference of the 82 matched pairs. One-tailed p-values indicating statistical significance at the 0.10, 0.05, and 0.01 levels are denoted with a *, **,

and *** respectively.

Year = t - 1

Year = t - 1 Year = t + 2

Table 9

Mean difference tests of the CAO treatment effect on audit fees scaled by the square root of assets, FEES_SQASSETS.

Pre-period Post-period

Year = t + 1

65

Coef. p-valuePred.

sign Coef. p-valuePred.

sign Coef. p-valueINTERCEPT 10.129 0.000 *** 9.971 0.000 *** 10.265 0.000 ***

Determinants of Audit Fees:

TREATMENT -0.062 0.365 - -0.148 0.027 ** - -0.107 0.070 *

LNASSETS 0.490 0.000 *** 0.509 0.000 *** 0.506 0.000 ***

INVENTORY -0.353 0.185 -0.564 0.041 ** -0.317 0.329

RECEIVABLES 0.466 0.115 1.108 0.002 *** 0.951 0.011 **

SALESGROWTH -0.063 0.413 -0.142 0.429 -0.151 0.372

MODOPINION -0.099 0.222 0.196 0.050 * 0.092 0.248

ACQORREST 0.089 0.253 0.147 0.125 0.209 0.027 **

DISCACC 0.129 0.145 0.006 0.771 -0.035 0.175

AUDITORTURNOVER 0.164 0.517 0.392 0.022 ** -0.339 0.020 **

GWIMPAIRMENT 0.052 0.721 -0.018 0.870 0.147 0.126

BIG4 0.312 0.185 0.128 0.673 -0.025 0.920

SEGMENTS 0.014 0.028 ** 0.002 0.597 0.005 0.145

FOREIGNTRAN 0.392 0.000 *** 0.428 0.000 *** 0.306 0.008 ***

LITRISK -0.151 0.084 * 0.047 0.543 0.061 0.534

LOSS 0.474 0.000 *** 0.306 0.001 *** 0.154 0.100 *

IO 0.663 0.000 *** 0.434 0.084 * 0.240 0.333

IO_AVAILABLE -0.492 0.015 ** -0.356 0.103 -0.315 0.149

R-squared 0.809 0.795 0.807

Firm-year observations 164 164 164

See table 1 for variable descriptions. TREATMENT equals 1 for firms that initiate a CAO position in year t

and retain the CAO position in the post-period. TREATMENT equals 0 for the propensity-score matched

control firms that do not have a CAO position in years t -1 through t +2. All continuous variables are

winsorized at the 1% and 99% level. Two-tailed p-value indicating statistical significance at the 0.10, 0.05,

and 0.01 levels are denoted with a *, **, and *** respectively. One-tailed p-value indicating statistical

significance at the 0.10, 0.05, and 0.01 levels are denoted with a *, **, and *** respectively for the predicted

negative coefficient on TREATMENT in the post-periods.

Year t -1 Year t +1 Year t +2

Table 10

Estimates of the second-stage natural log of external auditor fees, LNFEES .

LNFEES i,t = B 0 + B 1 TREATMENT i,t + ∑B i x FeeDeterminanti, t + ε t

Pre-period Post-period

Linear Regression for:

where i and t represent firm and year respectively.

66

Predicted Sign Coef. p-value

INTERCEPT 12.527 0.000 ***

Determinants of Audit Fees:

CAO + 0.255 0.000 ***

LNASSETS 0.000 0.000 ***

INVENTORY -0.081 0.190

RECEIVABLES 0.194 0.000 ***

SALESGROWTH -0.019 0.206

MODOPINION 0.199 0.000 ***

ACQORREST 0.323 0.000 ***

DISCACC -0.008 0.197

AUDITORTURNOVER -0.030 0.306

GWIMPAIRMENT 0.180 0.000 ***

BIG4 0.546 0.000 ***

SEGMENTS 0.025 0.000 ***

FOREIGNTRAN 0.384 0.000 ***

LITRISK -0.048 0.038 **

LOSS -0.040 0.011 **

IO 0.640 0.000 ***

IO_AVAILABLE -0.505 0.000 ***

R-squared 0.559

Firm-year observations 11,173

See table 1 for variable descriptions. CAO equals 1 for firms-years with a Chief Accounting Office

position on the top management team and 0 otherwise. All continuous variables are winsorized at

the 1% and 99% level. Two-tailed p-value indicating statistical significance at the 0.10, 0.05, and

0.01 levels are denoted with a *, **, and *** respectively. One-tailed p-value indicating statistical

significance at the 0.10, 0.05, and 0.01 levels are denoted with a *, **, and *** respectively for the

predicted positive coefficient on CAO .

Table11

Cross sectional estimate of the natural log of external auditor fees, LNFEES .

Linear Regression for:

LNFEES i,t = B 0 + B 1 CAO i,t + ∑B i x FeeDeterminanti, t + ε t

where i and t represent firm and year respectively.

Dan Russomanno University of Arizona

1130 E. Helen St. 301-W

Tucson, AZ 85721

Office: 520-621-0496

E-mail: drusso01@email.arizona.edu

EDUCATION:

The Pennsylvania State University, University Park, PA

Ph.D. in Business Administration – Accounting [2014]

Villanova University, Villanova, PA

Bachelors of Science in Accounting [May, 2003]

Bachelors of Business Administration in Finance and Management Information Systems [May, 2003]

Recipient of the Bartley Medallion for the highest G.P.A. and distinguished service

CPA LICENSE AND PROFESSIONAL MEMBERSHIPS:

Licensed as a CPA in New Jersey and New York

Member of the American Institute of Certified Public Accountants (AICPA)

RESEARCH:

“Changes in Internal Controls and Auditor Effort around the initiation of a Chief Accounting

Officer (CAO) Position.”

“Top Management Chief Accounting Officers (CAOs) and the Likelihood and Severity or

Restatements.” coauthored with Adrienne C. Rhodes [Assistant Professor at Texas A&M].

Presented at the 2013 AAA Annual Meeting, Anaheim, CA. [Best Paper Award, PhD Project

ADSA conference August, 2013 ]

“Compensation Disclosure Quality’s Impact on Financial Statement Users.”

CONFERENCES & SERVICE:

Reviewer & Discussant: AAA Annual Meeting – Anaheim, CA [2013]; Journal of Governmental &

Nonprofit Accounting [2013]; AAA Annual Meeting – FARS Section, Chicago, IL [2012]; and AAA

Mid-Atlantic Meeting – Philadelphia, PA [2012].

Conference Participation: AAA Annual Meeting, Anaheim, CA [2013]; AAA/Deloitte/J. Michael Cook

Doctoral Consortium, Lake Tahoe, CA [2013]; The Washington University Accounting Conference, St.

Louis, MO [2012]; AAA Annual Meeting, Washington, DC [2012]; The Pennsylvania State University

Accounting Conference, University Park, PA [2010 – 2012]; AAA Mid-Atlantic Regional Meeting and

Doctoral Consortium, Philadelphia, PA [2012]; and AAA Annual Meeting, Denver, CO [2011].

HONORS & AWARDS:

The Pennsylvania State University: J. Kenneth and Nancy N. Jones Scholarship [2009-2013];

Jane O. Burns Graduate Scholarship [2010, 2013] ; G. Kenneth Nelson Scholarship [2013]; The Frank P.

and Mary Jean Smeal Endowment Fund Scholarship [2010-2012]; Donald M. and Regina Harrison

Graduate Scholarship [2010-2012]; and the Smeal Competitive Doctoral Research Grant [2011-2012].

PROFESSIONAL EXPERIENCE:

Barclays Capital - New York City & Singapore – Assistant Vice-President [2008-2009]

Lehman Brothers - New York City, London & Tokyo - Assistant Vice-President [2006-2008]

PwC - New York City, NY - Senior Associate [2003-2006]