The Impact of CEO Turnovers on Earnings Management

during the Global Financial CrisisA Cross-sectional Analysis of North-American Firms

Erasmus University Rotterdam

Faculty of Economics & Business

Supervisor master thesis: Dr. Y. Wang

Name: Alex Eshuis

Student-ID: 291598

Contact: alexeshuis@hotmail.com or 291598ae@student.eur.nl

Table of Contents

Acknowledgement, Abstract

Chapter 1........................................................................................................................................4

1.1. Introduction.................................................................................................................................4

Chapter 2 Evidence on Earnings management.............................................................................8

2.1. Introduction.................................................................................................................................8

2.1.1. How earnings are managed..................................................................................................8

2.1.2. The Agency Theory.............................................................................................................10

2.1.3. Corporate Governance Mechanisms..................................................................................10

2.1.4. Investor protection.............................................................................................................12

2.2. The effect of the Asian Financial Crisis of 1999 on Earnings Management................................12

Chapter 3 Management & Shareholders: Conflicting Interests..................................................14

3.1 Management’s Function in Reporting Earnings..........................................................................14

3.2. The Role of SOX on Management’s Function.............................................................................14

3.3. Attitude towards Risk.................................................................................................................15

3.4. The Alignment in Objectives between Management and Shareholders.....................................16

3.4.1. Concerns Surrounding Options...........................................................................................17

3.4.2 The Horizon Dilemma.........................................................................................................19

Chapter 4 CEO Turnovers and Earnings Management................................................................20

4.1. CEO Turnovers and Earnings Management...............................................................................20

4.1.1. Routine Departures.................................................................................................................21

4.1.1. Routine Departures.............................................................................................................21

4.1.2 Non-Routine Departures.....................................................................................................21

4.1.3. Incoming Executives...........................................................................................................23

4.2. Industry specifics.......................................................................................................................24

4.3. Impression Management...........................................................................................................24

Chapter 5 Research Design......................................................................................................26

5.1. Hypothesis.................................................................................................................................26

5.2.1. Competing Models in Detecting Earnings Management....................................................27

5.2.2. Difference in Procedures....................................................................................................28

5.2.3. Accounting for firm performance.......................................................................................29

5.3. Sample.......................................................................................................................................30

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5.4. Methodology.............................................................................................................................31

5.5 Estimating Performance Matched Discretionary Accruals..........................................................32

5.6 Expectations...............................................................................................................................34

Chapter 6 Results......................................................................................................................36

6.1 Descriptive Statistics of the Model Coefficients..........................................................................36

6.2.1 Descriptive Statistics for Discretionary Accrual Measures....................................................37

6.2.2 Correcting for firm performance..........................................................................................39

6.2.3 Sensitivity Analysis...............................................................................................................40

6.2.4 Motivation for Decreased Earnings Management...............................................................41

Chapter 7 Conclusion................................................................................................................45

7.1 Conclusion..................................................................................................................................45

7.2 Measurement errors...................................................................................................................48

Table of Literature.........................................................................................................................49

References....................................................................................................................................53

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Acknowledgement

I would like to express my truthful gratitude to my supervisor, Dr. Yue Wang, for providing

suggestions and valuable advices that allowed me to realize this thesis. I would also like to thank my

parents for all of their continuous support during the writing process.

Abstract

This paper attempts to add to the small body of existing literature concerning the effect of different

economic environments on earnings management. In this case research is done on the relation between

non-routine CEO turnovers and income decreasing earnings management (‘big bath’) during the

Global Financial Crisis that started towards the end of 2007. By using (discretionary)accruals as a

proxy for earnings management, I use Kothari et al.’s (2005) cross-sectional modified Jones model for

detecting signs of negative earnings management during the 2008 (crisis) period. The research sample

consists of 194 observations of non-routine CEO turnovers that occurred during the 2008 period in the

United States of America. Additionally, this sample is controlled for firm performance by subtracting

the discretionary accruals of the matched firms from the discretionary accruals of the original sample.

Matching is done on basis of a near-similar level of ROA and Market Capitalization. In this paper

evidence is found of negative discretionary accruals during the year of the non-routine CEO turnover.

Thereby implying that during times of crisis newly appointed CEOs also partake in negative earnings

management or ‘big bath’ practices.

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Chapter 1

1.1. Introduction

Throughout the years a number of studies have touched on the existence of earnings

management by executives in the business world. The importance of fair -and adequate

accounting has had an increasing focus due to the large multitude of corporate scandals that

has occurred around the globe. The most notable being the World Com and Enron scandals in

2002 and 2001 respectively. Deliberately manipulating the companies’ earnings so that the

figures match a predetermined target certainly seems conceivable in times of economic

flourishing. But how does this change during different economic climates? More specifically,

how has the Global Financial Crisis (that started mid 2007) impacted management’s incentive

to manage earnings?

It became apparent in August 2007 that the subprime crisis could not be solved by the

financial markets, resulting in problems spreading beyond U.S. borders. According to the

National Bureau of Economic Research (NBER) the U.S. has ‘officially’ been in a recession

since December 2007. Their conclusion was formed by using real personal income, industrial

production as well as wholesale and retail sales as economic measures. These measures

reached a peak during the 2008 period.

Challenger, Gray, and Christmas Inc1 reported that the 2008 period has seen the number of

executives leaving their jobs in North America at its highest for a decade (1484 executives).

That tallies up to circa 6 CEOs giving up their position every working day of the year. These

numbers show that amidst the massive job cuts the individuals at the top are also feeling the

pressure. The economic crisis contributes to CEO turnovers2 by making the CEOs more

vulnerable with little room for error. Their firms and markets are in crisis, and in most cases

firm stocks are significantly down. In these harsh times the CEOs are under increased

pressure from employees and shareholders to improve performance. Boards are also

increasingly looking at whether they have the right man at the top during these times. Reason

for this is that the skills necessary for running a company in a rising market is often different

than operating and maintaining a prominent company in a down market. However, the main

purpose of this paper is not to evaluate whether the financial crisis contributes to the number

of CEO turnovers. Instead I would like to determine through research how (if at all) the

1 Challenger, Gray and Christmas Inc is a Chicago based executive recruitment firm.(http://www.management-issues.com/2009/1/16/research/ceo-turnover-hits-new-high.asp)2 In this paper a CEO turnover is defined as the changing of a Chief Executive Officer within a firm

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financial crisis changes the relationship between turnovers and the CEOs’ incentive to

manage earnings, when compared with CEO turnovers under normal market circumstances.

Earnings or ‘net income’ is arguably the most important item on a financial statement. They

give an indication as to what extent the firm has been pursuing its value-adding activities.

Given the importance of earnings, it is no surprise that executives have a large interest in how

earnings are reported. Executives make accounting choices within the framework of generally

accepted accounting principles. However, even though the accounting regulations that firms

experience are extensive, they include a certain amount of flexibility in a sense that it often

permits a choice or policy3. There are also certain areas in accounting that are not yet fully

regulated. These regulations therefore provide executives with some leeway to manage

earnings. And as evidence shows, executives tend to use this to their advantage. Like during

CEO turnovers; Empirical evidence suggests downwards earnings management in the year of

an executive change and upward earnings management in the preceding year (Murphy and

Zimmerman, 1993; Pourciau, 1993).

While it might seem arguable that firms which experience unforeseen accounting variations

during a CEO turnover are likely to be involved in some kind of financial reporting

manipulation, it can be challenging to determine. This lies with the difficulty to verify

whether the unforeseen accounting variations associated with a CEO turnover are due to

executives acting resourcefully at the expense of shareholders or by correct reporting of the

overall (poor)4 firm performance. Other papers have taken this into account by use of

‘impression management’ (Godfrey et al. 2003). Contrary to focusing on the accounting

numbers, impression management puts the spotlight on the graphical presentation of financial

figures in financial reports, where these graphs are manipulated to create a different

impression of company performance. If symptoms of earnings management as well as

impression management arise during a CEO turnover, it is more likely to point towards

deliberate resourceful behavior rather than the necessary changes due to economic changes in

firm performance (Godfrey et al. 2003). Al though Godfrey (2003) finds evidence of

impression management during CEO turnovers, these results are merely limited. This is the

reason why I have decided to take a different approach. Here Kothari et al.’s research (2005)

will be used as an example to distinguish between earnings management and firm

3 For example; the different methods of asset valuation. 4 Turnover tends to increase with poor firm performance (Kaplan and Minton, 2006)

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performance. In their research they’ve augmented popular models for detecting earnings

management by taking firm performance into account, and found that the augmented models

generated enhanced reliability in earnings management research. More information on this

method can be found in chapter Four.

Past research has shown how earnings management tendencies get affected through times of

crisis (Chia et al. 2007). This tendency to manage earnings is especially visible during

unplanned or non-routine5 CEO turnovers (Wells 2002). Since CEO turnovers during times of

poor firm performance contain relatively more non-routine turnovers than during prominent

times, one might conclude that there will be clear signs of increased earnings management

during the ongoing global financial crisis.

This paper will focus primarily on turnovers that took place in North-America. When

considering the failure and merging of a number of American financial firms (Fannie Mae,

Freddie Mac) following the subprime mortgage crisis I believe this crisis is more deeply

interwoven on US soil, allowing for more data to be gathered during research. Since the

whole of 2008 was characterized by a recession my research will mainly focus on this year.

In this thesis I’d like to add to the feeble existing body of literature concerning the effects of

different economic environments on earnings management by means of the following

research question;

How has the effect of non-routine CEO turnovers on earnings management in the

United States of America changed due to the Global Financial Crisis in 2008?

The following sub questions were formulated to aid in answering the research question:

1. What are the different factors that effect management’s incentive to manage

earnings?

2. What are the proven models and procedures in detecting earnings

management?

3. How do these models control for firm performance?

4. How do managements objectives contribute to earnings management?

5. What are the different types of CEO turnovers and how to these turnovers take

place?

5 Chapter Four will provide more information on routine and non-routine CEO turnovers.

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6. What is the effect of non-routine CEO turnovers on earnings management?

The second chapter encompasses extensive scientific literature necessary to understand

‘earnings management’ and the methodologies used in detecting this form of management. A

broad understanding of this phenomenon is essential in aiding my research. Chapter Two will

aim at answering the first three sub-questions, whereas Chapter Four will feature empirical

literature more closely related to our research question (which also aims at answering our

fourth and fifth sub-question). Chapter Three will provide the reader with background

information regarding management’s objectives within the firm and its contribution to

earnings management (thereby answering the fourth sub question). Finally, chapter five will

reveal the research design.

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Chapter 2 Evidence on Earnings management

2.1. Introduction

Healy and Wahlen (1999) provide us with the following description for earnings

management; Earnings management is the alteration of reported economic performance by

insiders to mislead some stakeholders or to influence contractual outcomes. In this sense

Burgstahler and Dichev (1997) provide extensive systematic evidence about whether (how

and why) firms avoid earnings decreases and losses. The authors find evidence that both cash

flow from operations and changes in working capital have been manipulated in order to

increase earnings. The reasoning behind this apparent earnings management has two

explanations. Firstly, managers opportunistically avoid reporting earnings decreases and

losses to decrease the cost imposed in transactions with stakeholders. The second explanation

is derived from the prospect theory (Kahneman and Tversky 1979) which states that the

largest gain in utility (hence the largest incentive to manage earnings) occurs when moving

from a relative or absolute loss to a gain. Burgstahler and Dichev (1997) provide empirical

evidence that earnings losses and decreases are often managed away. In fact, 8% to 12% of

firms with small pre-managed earnings decreases exercise discretion in reporting earnings

increases. Also, 30% to 44% of firms with slightly negative pre-managed earnings use

discretion in order to report positive earnings.

2.1.1. How earnings are managed

This ‘how’ section includes many variations to manage earnings. All though the main scope

of this thesis is not the reveal all methods, it is certainly relevant to include the most notable

of variations; Earnings are known to be managed through the following:

A choice from treatments that are accepted under GAAP, such as LIFO versus FIFO

for inventory valuation (Hughes, Schwartz, and Fellingham, 1988)

A decision on the timing of the adoption of a new standard or whether to write the

transition effect of the new standard on the income statement or as a retroactive

adjustment to stockholders’ equity on the balance sheet (Balsam, Haw, and Lilien,

1995)

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A point of view when GAAP requires estimates, such as asset valuation (Easton, Eddy

and Harris, 1993), asset write offs (Strong & Meyer, 1987) and the allowance for bad

debt (McNichols & Wilson, 1988)

Classifying items as above or below the line of earnings from continuing operations in

order to separate persistent earnings from transitory ones (e.g., Godfrey and Jones,

1999)

Timing the recognition of expenses and revenues through for example, timing the

sales of certain assets in order to smooth earnings (Bartov, 1993) and concluding

whether or not to capitalize expenses, such as brand name costs (Muller, 1999)

By making production and investment decisions, such as reducing R&D expenditures

(Baber, Fairfield, and Hagard, 1991) or manipulating selling and administrative

expenses (Gunny, 2005)

It should however be noted that evidence gained by an examination of restatements and of

enforcements cases of the Security and Exchange Commission (Dechow, Sloan, and

Sweeney, 1996) suggest revenue recognition as the largest single account subjected to

earnings management. Coffee (2005, p.10), for example, reports that in the SEC study of all

its enforcements proceedings over the 1997-2002 periods more than half (126 out of 227

matters) were deemed to entail improper revenue recognition.

Revenues are generally managed (to inflate earnings) using (amongst others) the following

approaches:

Channel stuffing; this is an example of rearranging transactions. The company inflates

its sales and earnings (accounts receivables) figures by consciously sending retailers

more merchandise then they are able to sell to the public market. These inflated

figures are usually very short lived as retailers generally send the excess items back to

the distributor (who must in turn re-adjust its accounts receivables).

Bill-and-hold transactions; these transactions allow a company to bill the customer on

the same day the transaction occurs, whilst delivering the goods on a later date. Bill-

and-hold transactions can be considered mere virtual transactions as nothing much

happens besides the recording of a bill of sale. By allowing the seller to receive

payments now, but making them wait a certain period before transferring, the finished

goods could be used to inflate revenues meant for forthcoming quarters.

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2.1.2. The Agency Theory

A key subject related to insider’s incentive to manage earnings can be found in the principal-

agent relationship depicted in the agency theory. This theory is a relationship, in which one

party (the principal) assigns work to another (agent), who executes that work (Eisenhardt

1989). A problem arises due to a twofold of reasons: (i) the agent and principal have divergent

goals and risk preferences and (ii) it is very difficult for the principal to determine whether the

agent has performed appropriately. The principal-agent relationship can be governed by

means of an efficient contract. In this light we can separate the contracts between behavior-

oriented (e.g. hourly wage) and outcome-oriented (stock options, commissions) contracts.

Jensen and Meckling (1976) find that when the contract between the agent and the principal is

of the ‘outcome’ variety, the agent is more likely to act in the interest of the principal. This

might suggest that executives would have less incentive to manage earnings when their

contracts are outcome-oriented.

Another measure to control for management opportunism relies on the information systems.

Since information systems advise the principal about what the agent is actually doing, the

agent realizes that the principal cannot be deceived. In this line Fama and Jensen (1983)

suggest that the information role that board of directors play can have a significant impact on

controlling for managerial behavior. In other words, when the board of directors can verify

managerial behavior, management is more likely to behave in the interest of the board.

Therefore it is safe to assume that companies that invest in their information systems

(effective board of directors, strong reporting procedures), reveal the agent’s behavior and in

turn decrease management’s incentive for opportunism.

A last adage to consider is that the information system is affected by the type of task that the

agent is responsible for. It is much harder for the principal to monitor the agent’s behavior if

its task lacks programmability (Eisenhardt, 1985, 1988). In her research Eisenhardt defines

programmability as the degree to which appropriate behavior by the agent can be specified in

advance. For example, the job of a truck driver is much more programmed than that of a

CEO. Therefore it will be significantly more difficult for the principal to monitor the CEOs

behavior in comparison with that of the truck driver.

2.1.3. Corporate Governance Mechanisms

There are a number of factors that influence insiders’ incentives pertaining to earnings

management. The influence of different corporate governance mechanisms can be considered

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as one of these factors. Yu (2006) examines two categories of governance devices, one being

internal (board structure and ownership concentration) and the other external (takeover

pressure and institutional ownership) in nature. The general consensus for internal governance

devices is that large shareholders play a more active role in monitoring and disciplining

managers than small shareholders. The type of board structure is also believed to effect firm

performance in that a small and independent board is more effective at making prompt

decisions and outside directors tend to be better monitors of management. On the other hand

institutional investors (external governance devices) have stronger incentives to discipline

managers than smaller investors.

The pressure of corporate takeovers is also a powerful form of governance to discipline

managers. However the understanding on the effectiveness of these corporate governance

devices on earnings management is still limited.

Yu (2006) attempts to find a relationship between the two using accruals (accounting

adjustments), but not all accruals are the result of earnings manipulation. They can be split

into discretionary6 (DA) -and non-discretionary7 accruals (NDA). A number of studies have

used DA’s as a proxy for earnings management. Yu (2006) concludes that firms with a

significantly high level of internal governance (e.g. higher ownership concentration and

smaller boards) manage earnings more, while firms with a higher level of external governance

(e.g. higher institutional holdings and higher takeover pressure) manage earnings less. These

results demonstrate that EM is mainly driven by conflict between insiders and outsiders. April

Klein (2002) lays claim to these findings by researching the relation between the composition

of the board or audit committee and apparent signs of EM. The primary function of the audit

committee is to oversee the firm’s financial reporting process to prevent fraudulent

accounting statements. It does so by meeting regularly with the firm’s outside auditors and

internal financial managers to review the business firm’s financial statements, internal

accounting controls and audit process. Klein finds a negative association between audit

committee or board independence and abnormal accruals. Most notably, strong results are

found when either the audit committee or the board has less than a majority of independent

directors. Thereby, suggesting that boards tailored to be more independent of the CEO are

more effective in monitoring the corporate financial accounting process.

6 Discretionary accruals are a non-obligatory expense that is yet to be realized but is recorded in the account books (such as anticipated bonus for management).7 Non-discretionary accruals on the other hand are an obligatory expense that has yet to be realized but is already recorded in the books (such as next month’s salary or any upcoming bills).

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2.1.4. Investor protection

While touching on the possible effects of the different corporate governance mechanisms on

earnings management, we mustn’t forget the presence of the protection of society from

insiders (management or controlling owners), better known as; investor protection. It is well

known that insiders conceal their private control benefits from outsiders (stakeholders) to

prevent any disciplinary action against them (Zingales 1994; Shleifer and Vishny 1997). In

this light, legal systems serve a purpose in protecting investors by conferring on the rights to

discipline (e.g. replace managers), as well as by enforcing contracts designed to limit insider’s

private control benefits.

Relatively strong legal systems that protect outsiders result in a reduction of managers’ need

to conceal their activities. Hence, Leuz et al. (2002) propose that earnings management is

more pervasive in countries where the legal protection of outside investors is weak, because in

these countries insiders enjoy greater private control benefits resulting in stronger incentives

to obscure firm performance. These firms are allocated into three different clusters based on

their countries characteristics: (1) outsider economies consisting of large stock markets,

strong investor rights, dispersed ownership, and strong legal enforcement (such as the United

States or United Kingdom); (2) insider economies with less developed stock markets, weak

investor rights, concentrated ownership but a strong legal enforcement (such as Sweden and

Germany); and (3) insider economies with weak legal enforcement (such as India and Spain).

These clusters are derived from prior work in the field (e.g., La Porta, Lopez-de-Silanes,

Shleifer and Vishny 1997; Ball, Kothari, and Robin, 2000). Leuz et al. (2002) find that

outsider economies with a relatively dispersed ownership, strong investor protection and large

stock markets exhibit lower levels of EM than insider economies with concentrated

ownerships, weak investor protection and less developed stock markets.

2.2. The effect of the Asian Financial Crisis of 1999 on Earnings ManagementIn light of the recent financial crisis one might wonder what the effects of different economic

environments are on the existence of earnings management. Chia et al. (2007) determine these

effects by using the Asian financial crisis of 1999 as an example. Gilson and Vetsuypens

(1993) propose that earnings management tends to decrease due to the fact that management’s

incentive shift from maximizing their accounting-based bonuses to saving their companies to

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preserve their jobs. On the other hand, management might also have an incentive to manage

earnings downwards to maximize financial support from the government as we have seen

happen in the United States and Europe recently. Chia et al. (2007) use the modified version

of the Jones cross-sectional model (1991) in detecting earnings management8. This model for

detecting earnings management will be explained in greater detail later in the chapter. Chia et

al. (2007) find evidence that there is a significant decrease in the use of increased earnings

management during a financial crisis. During the financial crisis, managers have expectations

of temporary poor earnings. When faced with such a situation, the managers’ incentives

would be to save their companies and preserve their jobs instead of attempting to maximize

their accounting-based bonuses. However, since this thesis centers on earnings management

tendencies with regards to incoming CEOs during 2008 the focus will lie more on the extent

of decreased earnings management (big bath) which is explained further in Chapter Four.

8 They use discretionary accruals as a proxy for earnings management.

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Chapter 3 Management & Shareholders: Conflicting Interests

3.1 Management’s Function in Reporting Earnings

This chapter will provide the reader with background information regarding management’s

objectives within the firm and its contribution to earnings management.

As mentioned by Desai, Hogan, and Wilkins (2006) senior management exhibit a leadership

role in producing and reporting earnings. Despite the fact that approving key managerial

decisions is mostly left to the board of directors, the reality is that executives make decisions

on a number of terrains concerning financing, operations and investments (such as capital

investments, designing and executing new business strategies, acquisition of securities, the

issuance of dividends etc.). To be able to make just decisions regarding these terrains

executives acquire superior knowledge of the firm and its economics. An example thereof can

be found in studies on insider trading (Beneish & Vargus, 2002), where insiders show a

tendency to buy stock when its undervalued and sell stock when its overvalued. With this

superior knowledge executives can use earnings management in two different ways. They can

either take advantage of the flexibility in accounting methods to enhance the transparency of

financial reports, or attempt to hide unfavorable news by misrepresenting or diminishing the

transparency of the financial reports.

3.2. The Role of SOX on Management’s FunctionThe introduction of the Sarbanes-Oxley Act (SOX) in 2002 has redefined management’s

reporting duties. The increased financial reporting responsibility bestowed upon management

can be found in sections 302 and 404 of the Act.

Section 302(a): This section requires that the principal executive officer and the

principal financial officer (or individuals performing similar functions) certify in each

quarterly or annual report. With this certification the individual is attesting to the

following: (1) He or she has reviewed the report;

(2) Based on the individuals’ knowledge, the reviewed report does not consist of any

fallacious statement of material fact or omit to state a material fact in order to make

the created statements non-misleading;

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(3) The financial statements and all other financial data included in the financial report

fairly present in all material respect the results of operations and the financial

condition of the issuing firm for the period applicable to the report (again based on the

individuals’ knowledge).

Section 404: This section requires issuers to publish information in the annual

statement concerning the scope and adequacy of the internal control procedures and

structures for financial reporting. The effectiveness of internal controls shall also be

assessed in the declaration.

So how do we assure that the officer in question ascertains sufficient knowledge to justify

certification? Section 302(a)-4 of the Act requires certifying officers to be accountable for

establishing and maintaining internal controls. In doing so they should provide specific

requirements for an evaluation and for bringing internal control deficiencies (including means

to correct these measures) to the attention of the auditor and audit committee.9 In addition,

failure to comply with section 404 of the Act will result in the manager not being allowed to

certify the financial report. The cost of failing to comply with honest reporting and disclosure

have become significantly more severe, often involving both fines and incarceration. So it

seems that the introduction of the Sarbanes-Oxley Act has increased the cost executives bare

for managing earnings for personal gain.

One must wonder however to what extent the implementation of SOX would have even been

necessary if the goals of the managers would have been aligned, or existing mechanisms

would have been able to align, with the goals of the shareholders. More on the difference

between management and the shareholders objective function will be brought forward in

paragraph 3.4.

3.3. Attitude towards RiskBasically, management’s wealth comprises three different areas: the firm’s financial capital,

other capital not related to the firm and human capital. More often than not a manager’s

human capital is firm specific and can therefore not be diversified away. Unlike general

human capital that can be leveraged in other employment, firm specific human capital hinders

management from diversifying away the risk involved in this portion of capital optimally

(e.g., Agrawal and Mandelker, 1987). This suggests that the average executive’s tolerance of 9 As stipulated in sections 302(a)-4(A), 302(a)-4(C), 302(a)-5 & 302(a)-6 of the Sarbanes-Oxley Act

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risk is likely to be lower than that of the shareholder, which often leads to investment

decisions that are too conservative for the shareholders’ liking (Nohel and Todd, 2002).

To induce management into being more risk-taking requires designing a compensation

package that enables a convex payoff (which is riskier that a concave or linear payoff). The

idea behind a convex payoff schedule is that it has a marginally escalating reward. Hence, the

concave compensation formula gives the manager more for low outcomes and less for high

outcomes than a convex schedule, thus making it less risky (Yaari, 1991, 1993). In this light,

options can be used to alternate manager’s risk-taking behavior (Rajgopal and

Shevlin, 2002).

3.4. The Alignment in Objectives between Management and ShareholdersThe most noted difference between managements’ and shareholders’ objectives is that unlike

management, shareholders are not a homogeneous group. As the following cite from Richard

Olson (Swiss fund manager) posted in The Wall Street Journal10 further clarifies:

People aren’t rational, and they don’t all think alike. Some are quick-trigger speculators who pop in

and out of the market hundreds of times a day. Some are corporate treasurers, deliberately buying or

selling big contracts to fund a merger or hedge an export risk. Some are central bankers, who trade

only occasionally, and at critical moments. Others are long-term investors who buy and hold for

months or years.

In their research Hart (1995) and Ronen et al (2002) find that shareholders tend towards two

objectives. Some want the firm to maximize long-term value, while others lean more towards

maximizing the short-term value because they plan to sell their shares in the near future.

Evidence suggests a number of reasons for the differing in objectives between management

and shareholders:

As mentioned management’s portfolio consists of firm-specific human capital that,

unlike shareholders capital, cannot be diversified away;

Management has access to different company perks than shareholders. Additionally

some production and investment decisions the firm makes induces personal costs on

management alone;

10 Mandelbrot Benoit B. and Richard L. Hudson; A look at market––moving numbers––literally, July 27, 2004, C1, C6

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The decision making horizon of the manager is different from that of the investor and

the firm.

These points will be explained in more detail during the rest of this chapter.

Jensen & Meckling (1976) mention manager’s consumption of a company’s resources under

the name agency costs. Some examples of these perks are; the use of company airplanes,

membership in clubs and medical coverage. The problem here lies with the fact that

management enjoys every dollar of every perk while only bearing a fraction (relatively much

lower equity holding) of the costs. A possible solution for buffering management’s private

consumption can be found in designing compensation based on equity (Balsam, 2002): stocks,

options, and/or an added requirement that managers hold a minimum number of shares.

However, equity based contracts isn’t the perfect solution. Leone, Wu and Zimmerman (2006)

mention for example the presence of limited liability, which protects management’s

compensation from downward risk. In other words, firms and shareholders may experience

losses on bad investments, but the losses from these investments aren’t reflected in

management’s compensation.

Another notable problem is that management’s compensation does not get designed by

shareholders directly. This task is left up to the board of directors. The situation can arise that

the board is captured by the CEO. In this case the executive might get paid beyond the

maximum level. In case options are a part of the executives’ compensation, he/she can reduce

risk by smoothing earnings (Huang, 2005) or take unexpected actions that inflate the market

price of his/her options by increasing the volatility of the firm’s performance (Grant,

Markarian, and Parbonetti, 2007).

3.4.1. Concerns Surrounding Options

There are several concerns revolving around options as compensation means in modern

research. The first concern involves around whether incentives should increase or decrease

with the riskiness of the firms performance. Since the outcome of a firm’s performance is

already risky by itself, why should management get relatively riskier incentives in order to

encourage the executive into taking the desirable action? On the other hand, since the

shareholder-management relationship is characterized by moral hazard11, the shareholder

needs to impose risk to induce the manager to exercise effort instead of shirking his/her duty.

11 The scope of moral hazard is greater in case the firm is relatively riskier.

17

Guay (1999) proposes that options are good at imposing risk due to the fact that they are only

valuable if the market price has risen when they are exercised. Hence, to enrich him/herself

the manager has to take appropriate actions in order to increase the company’s value.

However, since these incentives are affected by earnings, compensation might cause the

executive to manage earnings instead of taking the appropriate action (Bushman & Smith,

2001).

Another point in question concerns the efficiency of options in aligning shareholder

objectives with managements’ incentives. Several studies argue that this efficiency is driven

by economic dynamics. Here empirical literature (Himmelberg, Hubbard, and Palia, 1999)

attempts to determine variables related to moral hazard, these being: R&D intensity,

advertising intensity, investment rate, cash flow, capital intensity and size. Further research

lead Himmelberg et al (1999) to conclude that management ownership and firm performance

are determined by commonplace firm-specific factors. Thus, an incentive contract can be

made uncomplicated without sacrificing much efficiency.

However the extensive use of stocks/options for incentive purposes does have its

consequences. That is, managers sell most of their exercised options immediately after

exercise (Lakonishok & Lee, 2001). On these grounds Ofek and Yermack (2000) state the

following: When keeping the modern portfolio theory in mind, managers that receive additional stock

should sell these shares or do so similarly with other shares they already own. This should be done in

order to diversify away the unsystematic risk related to concentrating wealth into a single asset.

Managers undergo a higher risk than investors due to the correlation between human capital value

and firm performance the executive inherits (mentioned in section 3.3. Attitude towards Risk). In

their study Ofek and Yermack (2000) segmented their data into subsamples based on whether

executives are in possession of as many shares as those awarded in new grants of stock

options. They found, for higher-ownership executives, active selling during years with new

option awards. Much of the incentive impact of these executives’ stock based pay is nullified

due to the existence of these sales.

A related question concerns the affects of SOX on executive compensation. Despite the fact

that several researchers (Cohen, Dey, and Lys, 2005; Carter, Lynch, and Zechman, 2006) find

that SOX made compensation less risky (due to a decrease in the bonus component and an

increase in the fixed salary component), practitioners believe the effects of SOX on

compensation to be minimal. Despite much public criticism concerning abnormal executive

18

compensation and the fact that the typical board structure for setting executive pay is seldom

effective, minute systematic changes appear to have occurred (Coglianese and Michael, 2006).

3.4.2 The Horizon Dilemma

A distinct reason for the incongruence in objectives between managers and shareholders can

be found in the differing of their decision-making horizon. Executives have to cope with

concerns that last their entire working career. A crucial part of his/her career consists out of

building a good reputation by realizing positive performances during their tenure at past firms

(Gibbons & Murphy, 1992). Narayanan (1985) believes that this reputation building

encourages managers to sacrifice shareholder’s value. The logic here lies with the fact that

managers who are recognized as having a high ability tend to reap a higher compensation.

Hence, they invest in short-term projects that yield a higher short-term output in order to be

perceived as having a higher ability. This however does not necessarily have to apply to all

executives. It is more likely to apply to managers at the beginning of their tenure. In their

research Allgood and Farrell (2003) show that during the five years of his/her tenure the

probability of the CEO leaving the firm increases, and declines from there on.

Another aspect to take into account is that of relatively older executives. These executives

have shorter working horizons, and will therefore experience a smaller impact on their

reputation. When nearing the end of his/her tenure, the manager’s investment horizon may be

longer than his/her remaining tenure with the firm. This will likely induce the manager to take

actions that increase short-term earning at the cost of the firm’s long-term value. Gibbons and

Murphy (1992b) put further emphasis on the importance of tenure in the conflict of interest

between shareholders and managers. They find that (on average) an increase of 10% of

shareholders wealth accounts for a 1.7% change in monetary compensation for CEO’s less

than three years from retirement. In contrast, CEO’s that are more than three years from

retirement experience a 1.3% change in monetary compensation.

The horizon dilemma, in particular turnovers, has important implications on earnings

management. Namely, an approaching departure decides the remaining horizon of the

departing CEO, while the CEO vacancy starts the clock for the incoming CEO.

With this in mind, the following chapter will focus on the presence of earnings management

particularly surrounding CEO turnovers.

19

Chapter 4 CEO Turnovers and Earnings Management

4.1 CEO Turnovers and Earnings ManagementSince a CEO turnover involves two phases (namely the departing CEO-the predecessor- and

the incoming CEO-the successor), it presents two distinct decision making opportunities and

therefore two independent earnings management issues. In theory the departing CEO may

attempt to inflate earnings for the following reasons: - disguise poor firm performance to

avoid forced separation, - to collect a higher bonus in the last year of the job (assuming

his/her bonus is performance based), - or to obtain better employment after stepping down.

The incoming CEO on the other hand will undertake in earnings deflating (“earnings bath” or

“big bath”) measures. Here the incoming CEO lowers the earnings in the year of his/her

introduction with the opportunity to blame the poor performance on the predecessor. This also

gives a good plateau for the incoming CEO to base his future earnings on.12

Wells (2002) investigates if and to what extent earnings management occurs around the time

of a CEO change in Australian firms using a modified Jones model to estimate unmanaged or

expected accruals. Evidence is presented of incoming CEO’s reducing income in the year of

the CEO change which is consistent with the term ‘earnings bath’. This is achieved by the

manipulation of abnormal and extraordinary items.

Besides using the accruals to investigate earnings management, one can use a set of different

financial variables to get an insight on the subject. Murphy (1992) achieves this by describing

the behavior of financial variables surrounding CEO turnovers. The following financial

variables were mentioned in his paper: Research & Development, Advertising, Capital

Expenditures, Accounting Accruals, Accounting Earnings, Sales, Assets and Stock Prices.

Little evidence is found to support the hypothesis that outgoing CEOs exercise their discretion

over financial variables to increase their earnings based compensation prior to their departure.

The decline of R&D, Advertising, Capital Expenditures and Accounting Accruals are mostly

explained by poor firm performance rather that financial discretion. On the other hand there is

evidence of incoming CEOs taking an earnings bath similar to Wells’ (2002) investigation.

12 The incoming CEOs tendency to engage in decreased earnings management during the 2008 crisis period will

gain special attention during this paper since the research sample contains CEO turnovers during 2008.

20

4.1.1. Routine DeparturesAs prior study show (e.g. Denis and Kruse, 2000; McNeil, Niehaus, and Powers, 2004) the

average annual CEO turnover rate is between 5% and 15%. This rate is significantly related to

performance, where poor firm performance shows a higher turnover rate than firms which

exhibit good performance. A CEO change can happen under different circumstances. It can

either be a routine (peaceful and orderly) or a non-routine (all remaining cases) departure. In

case of an orderly departure the CEO is finishing his/her term and will terminate the

employment with the company. The company usually has a well planned turnover strategy

and a successor that is groomed to follow the outgoing CEO. More often than not an outgoing

CEO will remain in the board of directors, meaning that he/she is in a position to monitor the

actions of the incoming CEO, thereby decreasing the chances of earnings management

(Vancil, 1987).

Because past CEOs often find themselves becoming directors (Brickley, Coles and Linck,

1999) it is understandable they tend to lean towards earnings management. They do this in

their final years in order to increase the probability of being hired as directors. Brickley et al.

find that the performance in the departing CEO’s final four years is positively related to the

following; (1) the probability of the CEO maintaining his/her board seat after departure, and

(2) a chance at securing other post departure board seats. Reitenga and Tearney (2003) extend

their research by examining CEO turnovers during a four year time span before departure.

These examined CEO turnovers are only the result of a routine turnover and are controlled for

CEO stock ownership, corporate governance factors and the retention of a board seat after

retirement. Reitenga and Tearney find evidence of earnings management in the departing

CEOs’ final two years. This evidence was found to be more substantial when the CEO

retained his/her board seat after retirement. They also find that earnings management in the

last year of the job tend to be mitigated by independent directors and CEO stockholdings.

These findings lay emphasis on the importance of corporate governance13.

4.1.2 Non-Routine Departures

Non-routine departures are largely associated with poor firm performance (Murphy and

Zimmerman, 1993; Defond and Park, 1999; Huson, Parrino and Starks, 2001). Since sudden

departure has no association with performance by a precise formula, researchers have

13 For more on corporate governance mechanisms refer to pg. 9.

21

developed several metrics. Puffer and Weintrop (1991) for example, examine earnings that

have failed to meet analysts’ forecasts. Defond and Park (1999) link performance to

competition in the industry by adjusting earnings to median industry performance. Yet some

link turnover to events that are traumatic to the company. Gilson (1989) examines senior

management changes at firms experiencing bankruptcy, default, or privately restructuring

debt to avoid bankruptcy (financially distressed firms). He finds that in any given year 52% of

these financially distressed firms experience turnover in senior management, as oppose to

19% for firms that are extremely unprofitable, but are not under financial distress.

From detecting poor firm performance to taking action for forced departure is a process that

usually takes about 2-3 years (Denis and Kruse, 2000). It is not easy to ask an executive to

leave due to poor performance. The manager is generally given some time to prove him- or

herself. In addition, proper information must be gathered, feedback must be obtained, and so

on, until the majority of the board opts for resignation. This leaves the CEO with ample time

to manage earnings in order to slow down the leak of disadvantageous information. To

compensate for his/her performance he/she might try to increase earnings giving a better

image of his/her performance. Pourciau (1993) investigates the relation between non-routine

executive turnovers and discretionary accounting choices. In her investigation she tests the

hypothesis of whether in certain situations managers make discretionary accounting choices to

benefit their own interest in the case of non-routine CEO changes. Contrary to belief, her

research shows that departing CEO’s record accruals and write-offs to decrease earnings in

the year of their departure. She gave the following alternative explanations for her results: 1)

Misspecification of the time horizon in the research, 2) there was inadequate control for firm

performance so the results may also be caused by poor firm performance, 3) Managers were

unable to predict his/her termination, 4) and the increase in monitoring due to poor firm

performance.

In covering up poor firm performance through means of earnings management, one might

wonder to what extent taking this risk is worth it. That is, on the one hand, covering up bad

performance has the benefit of delaying a forced departure. The downfall on the other hand,

when fraud is discovered, may be more damaging than involuntary departure when the

executive faces the possibility of monetary penalties and/or incarceration. Desai, Hogan, and

Wilkins (2006) observe a sample of 146 firms that experience turnover whilst restating

earnings in the 1997-1998 periods. They found that 59.6% of restating companies experience

22

turnover in a top managerial position within 2 years of restatement, in contrast to only 34.9%

of age-, size- and industry-matched companies. Additionally, only 15% of discharged

executives were able to secure a similar position at another firm, in contrast to 21% of

discharged executives at the control firms. Through these findings Desai et al. suggest that

displaced managers of restatement firms endure significant losses in reputation.

4.1.3. Incoming Executives

A CEO change should not be taken likely. It may be followed by a number of occurrences,

some being the following: restructuring that effect the composition and level of assets (Nam

and Ronen, 2008), divesture of poorly performing assets (Weisbach, 1995), an alteration in

business strategy (Bloningen & Wooster, 2003), and the departure of other key individuals in

the management team (Hayes, Oyer and Schaefer, 2002). From the beginning the incoming

executive is put under a lot of pressure to show results. During his/hers tenure he/hers is,

among other things, responsible for creating a benchmark in the first term of his performance

given the fact that he has control over the reported earnings. Thus, it should come as no

surprise that an abundance of studies find incoming CEO’s taking a bath by recording big

charges in their first term, followed by an increase in earnings in the ensuing year. As briefly

mentioned before in section 3.1.1 (Vancil, 1987) this theory tends to hold providing the

departing CEO does not remain in the firm as a director.

With respect to Pourciau’s (1993) investigation, she finds incoming executives recording

accruals and write-offs to decrease the earnings in the year of the turnover and increase

earnings the following year. However her results are not corrected for firm performance so the

results may also be caused by this. In line with the findings of Pourciau (1993) are the results

of Wells (2002) where “earnings baths” seemed to occur especially in the case of non-routine

CEO turnovers.

The question is however whether the large write-offs to decrease earnings should be attributed

to earnings management or actions more closely related to efficiency-enhancement. Nam and

Ronen (2008) examine the market response to the incoming executive and the announcement

of the write-off by the firm experiencing the CEO turnover. They find that markets

differentiate between EM and efficiency-enhancing actions. Specifically, the market’s

reaction seems to be sensitive to; whether the write-offs are due to restructuring, the

23

manager’s performance in previous engagements (reputation) and the incoming CEO’s

expertise concerning the industry in which the firm operates.

4.2. Industry specificsBesides the usual circumstances (poor performance, ending tenure) that cause a CEO change,

there are also other factors that are of influence. In this section I will discuss how the type of

industry the firm is operating in, influences CEO turnovers. With this in mind there can be

two possible cases. The first one being that a firm operates in a homogeneous industry, where

there are a large number of similar firms operating. The second case involves a heterogeneous

industry where there are a small amount of similar firms operating in that industry.

Parrino’s study (1997) concludes that in homogeneous industries, poorly performing CEOs

are easier to identify and cheaper to replace than in heterogeneous industries. The likelihood

of a forced turnover followed by the appointment of a CEO from the same industry increases

in a homogeneous industry. This implicates that in an industry with similar firms, the chances

of a non-routine turnover are greater than in a heterogeneous industry.

4.3. Impression ManagementIn the case of Impression Management the focus lies on the manipulation of graphs to give the

stakeholders a more favorable impression of the performance of the managers. Although this

paper will not focus on impression management, it is important to bring to light, since

research shows that earnings management and impression management do not occur

simultaneously. Managers may also have the incentives to manage both earnings and

impressions (Godfrey et al. 2003). Godfrey et al. (2003) investigate earnings management and

the presentational format of graphs around the change of CEOs. Here the presentational

format of graphs is seen as impression management. The authors argue that incoming

managers have incentives to manage earnings and also to manipulate the graphs in financial

reports in a favorable way. The benefit about observing earnings management and impression

management at the same time is that it allows distinguishing between alternative explanations

for any case of earnings management. Evidence is found to support the hypothesis of

downward earnings management in the year of a CEO turnover. Also limited evidence is

found of unfavorable impression management of key financial variable graphs. In the year

following the CEO turnover, evidence is found to support upward earnings management. In

turn some evidence is found supporting favorable impression management in the year

24

following a CEO turnover. These results appear to be strongest in the case of an executive

resignation instead of a retirement.

25

Chapter 5 Research Design

5.1. HypothesisWhen confronted with a CEO turnover, the incoming CEO manages the financial reports by

attributing poor performance to his/her predecessors while also creating a plateau to increase

future performance based compensation based on accounting data (e.g. big bath, earnings

bath). This will create a more desirable plateau from which future earnings can be compared.

Different researches share the same results where the incoming CEO takes a big bath which is

usually followed by an increase in earnings in the following year (Godfrey et al. 2003;

Murphy 1992; Pourciau 1993; Wells 2002).

Pourciau (1993) and Godfrey et al. (2003) show evidence that the outgoing CEOs decrease

earnings in the year of the CEO change. These results seem to be contradicting the results of

Wells (2002) and Murphy (1992) which state that the outgoing CEOs increase the earnings in

the year of their departure. Most likely this is done with the intention to acquire a larger bonus

right before the departure, which can be a clear example of the difference in goals between the

principle and agent (agency theory). It seems that there is not a common ground in whether

the outgoing CEO increases or decreases the earnings in the year of the CEO change.

Therefore this paper will focus primarily on the possible big bath event that different

researchers share the same results on. Based on the evidence pertaining to incoming CEOs in

the United States (Godfrey et al. 2003; Murphy 1992; Pourciau 1993), this thesis assumes that

the pre-crisis period in the United States (before 2007) shows signs of decreased earnings

management in the year of the CEO turnover.

The goal here is to figure out whether signs of earnings bath are still as notable through times

of financial crisis as they are through times of economic flourishing or otherwise. Kothari et

al.’s (2005) research controlled for firm performance by use of a control sample, which is

created by matching the sampled firms on the ground of performance in the same industry. I

will use the same method to control for firm performance during 200814.

Recently the world has been confronted with the Global Financial Crisis. The effects of this

crisis cannot only be felt in the financial world but also in other industries. This brings an

interesting opportunity to investigate how these troubling times affect the accounting world in 14 More on Kothari’s research in the following section (5.2.3. Accounting for firm performance)

26

relation to earnings management. Research will take place in the period where the financial

crisis was most apparent, namely in 2008. This paper acknowledges that during the financial

crisis firms will endure a limit in earnings performance. Managers will feel a growing

pressure from external stakeholders (by means of increased monitoring and scrutiny activities)

to produce credible earning reports, which would inescapably imply a decrease in the level of

earnings management. However, these external stakeholders are also highly aware of the

chance that during times of crisis firms exhibit lower earnings performance. At the same time

management also knows that any drop in reported earnings will be accepted or tolerated in

light of the financial crisis. In line with this and the above mentioned evidence pertaining to

incoming CEOs in the United States, I have created the following hypothesis:

H1: during the 2008 crisis period firms experiencing a CEO turnover increase the level of

negative discretionary accruals, thereby reducing the earnings.

5.2.1. Competing Models in Detecting Earnings Management

The analysis of earnings management focuses on the insiders’ use of discretionary accruals as

was briefly mentioned by Yu (2006). Such research requires a model for estimating the

discretionary components embedded in reported income. Dechow et al. (1995) evaluate the

relative performance of competing models by comparing the specification and power of

commonly used test statistics. The specification quality of the test statistic is measured by the

frequency in which they generate Type I errors15. Type II errors16 are also measured in

determining the power of the model used. Dechow et al. (1995) consider five models that

have been used in extant earnings management literature. Firstly, they consider the Healy

(1985) model. Healy tests for earnings management by comparing the mean total accruals17

across the earnings management partitioning variable. DeAngelo’s model (1986) tests for

earnings management by calculating first the differences in total accruals under the

assumption that the expected value of these first differences are zero when there is no

earnings management present.

Both these models rely on the assumption that NDA’s are constant. Jones (1991) relaxes this

assumption in introducing the Jones model. In her model she attempts to control the effect of

changes in a firm’s economic circumstances on NDA’s. In doing so her model estimates about 15 Type I errors occur when the null hypothesis that earnings are not systematically managed is rejected when in fact the null is true.16 Type II errors arise when the null hypothesis that earnings are not systematically managed is not rejected when this is false.17 Scaled by lagged total assets

27

one quarter of the variation in total accruals. The only downfall lies in her assumption that

revenues are non-discretionary. Imagine a situation where an insider accrues revenues that

have not yet been received and it is unlikely whether the revenues have been earned. Through

an increase in account receivables this will result in an increase of total accruals. Although the

Jones model allocates this as being a NDA, clearly it is discretionary in nature. This was

reason enough to introduce the modified Jones model which eliminates the tendency of the

standard model in measuring discretionary accruals with errors when discretion is exercised

over revenues. The last model used by Dechow et al. (1995) is known as the Industry model.

Similar to the Jones model this model also relaxes the constant NDA assumption. As an adage

this model assumes that the variations in determinants of NDA are common across firms in

the same industry.

Dechow et al. (1995) find that all18 models appear well specified when applied to a random

sample of firm years. However, all of the models generate tests of low power for earnings

management of economically plausible magnitudes. They also concluded that all models

reject the null hypothesis of no earnings management at rates exceeding the specified test

levels when applied to the samples of firms experiencing extreme financial performance.

Although the results are modest, they deem the modified Jones model to be the best at

detecting EM.

5.2.2. Difference in Procedures

What the above mentioned models have in common is that they are assessed on the basis of

time series analysis. Recent evidence reported by Guay et al. (1996), Dechow et al. (1995)

and Kang and Shivaramakrishan (1995) suggest however that time series version of the sJones

and mJones models estimate discretionary accruals with considerable imprecision. In lieu of

time series models, cross-sectional procedures19 are now more widely employed in earnings

management research (Peasnell et al. 2000). Peasnell et al. (2000) attempt to add to the

existing body of work in this area by providing evidence on the performance of three

alternative cross-sectional procedures for estimating the managed components of working

capital accruals. In addition to evaluating the performance of standard- and modified cross-

sectional Jones models, they also develop and test a new cross-sectional model classified as

the ‘margin model’. The upside to this model is its improved economic intuition, which in

turn should lead to a better estimate of normal accruals. The downside however is that 18 Healy model, DeAngelo model, standard Jones model, modified Jones model and Industrial model. 19 Cross-sectional data refers to data collected by observing many subjects (such as firms or countries) at the same point in time, or without taking differences in time in regard.

28

discretionary accruals are determined using ‘revenue’ as a variable. This variable may already

be contaminated by earnings management as was discussed in the explanation of the standard

Jones model above. To generate tests of higher power Peasnell et al. (2000) find that their

tested models (in addition to having a high specification) generate relatively powerful tests for

economically plausible levels of accruals management when using the cross-sectional instead

of time-series procedures. They conclude that the standard- and modified Jones models are

found to be more powerful for revenue and bad debts manipulations. In contrast, the margin

model appears to be more powerful at detecting non-bad debt expense manipulations.

5.2.3. Accounting for firm performance

If we were to make use of the competing models for detecting earnings management, our

conclusions would rely critically on our ability to accurately measure the discretionary

accruals. The existing models however are not known for being able to generate highly

accurate estimations. What these models lack is the ability to distinguish between executive

opportunism and the truthful reporting of a firm’s underlying economic performance, as

already mentioned in the introduction. Kothari et al. (2005) adjust for earnings management

by using a control sample, which is created by matching the sampled firms on the grounds of

performance in the same industry. In other words, firms are believed to be using earnings

management when these firms appear to be manipulating earnings at a rate higher (lower)

than the comparison sample. So what performance measure should be used in finding the

‘performance matched’ discretionary accruals? Kothari et al. (2005) recommend using the

return on assets (ROA) performance measure. Their recommendation are based on the fact

that prior research (see, for example, Barber and Lyon 1996, 1997; Lyon et al. 1999;

Ikenberryet al. 1995) finds matching based on ROA to yield better specified and more

powerful tests compared to other measures.

In their research Kothari et al. (2005) perform an analysis on the discretionary accrual

estimations by comparing the specification and power of the Jones and mJones model to their

augmented counterpart. They find that under most circumstances the performance matched

discretionary accruals are relatively powerful and tend to be the best specified measure of

discretionary accruals.

5.3. SampleThe sample of this study consists of non-routine CEO changes that occurred during 2008.

These observations are extracted by use of the Executive Compensation product provided by

29

COMPUSTAT North America. This service allows one to select specific variables

surrounding CEOs, including information regarding their date left as CEO and the CEOs

reason for leaving its position. Consistent with prior discretionary accrual research (Dichev et

al. 1997 and Luez et al. 2002) firms lacking sufficient data to compute total accruals will be

excluded from the sample. Since I am using OLS regression in order to determine the relevant

coefficients I am obliged to exclude all industries lacking sufficient observations for the

control sample. The minimum amount of observations allowed in this thesis is set at 50. In

order to negate imprecise regression-model-based discretionary accrual estimates I also

exclude all firm year observations with less than ten observations per 2-digit SIC industry.

Furthermore, similar to prior research, I exclude regulated firms (e.g. financial institutions,

SIC 6000 to 6999) because of the fact that they have different earnings reporting incentives

than their non-regulated counterparts. The available sample of firm year observations

experiencing CEO turnovers during 2008 is 8359. Since I am only interested in firms

experiencing non-routine CEO turnovers I also exclude observations where the CEO

turnovers are deemed to be routine in nature (i.e. firms where the CEO retires from his/her

post). Since research is done here by matching firms based on performance and industry

membership, I will use stratification to group firm population into relatively homogenous sub-

samples (stratified sampling)20. After excluding all of the abovementioned observations I am

left with a sample of 194 non-routine CEO turnovers spread over 8 SIC industries (sub-

samples). See table 1 on the next page for an overview of the non-routine turnovers per

industry as illustrated on the next page. Furthermore, these 8 industries amount to a control

sample size of 482 observations with at least 50 observations per 2-digit SIC industry.

20 http://www.coventry.ac.uk/ec/~nhunt/meths/strati.html, accessed on the 10th of Febuary 2009.

30

2-Digit SIC

Industry Sector No. of non-routine CEO changes

%

13 Oil & Gas Extraction 10 5.235 Industrial & Commercial Machinery & Computer

Equipment32 16.5

36 Electronic & Other Electrical Equipment & Components

37 19.1

37 Transportation Equipment 11 5.738 Measuring, Analyzing & Controlling Instruments 17 8.749 Electric, Gas, & Sanitary Services 23 11.856 Apparel & Accessory Stores 12 6.273 Business Services 52 26.8

Total 194 100

Table 1: Non-routine CEO turnovers segmented by SIC industry classification

Once I’ve identified the U.S. firms that will be included in the sample, I can use the

COMPUSTAT Industrial Annual and Research files to determine whether these firms have

sufficient data to compute the relevant accruals needed to estimate the performance matched

modified Jones model. The fact that the Global Financial Crisis is fairly recent makes data

availability a concern. The large number of firms in the United States of America will provide

more information on the crisis which will help to improve the test results and aid the problem

of data availability.

5.4. MethodologyThe first thing to consider in the methodological approach is defining a method for detecting

earnings management. In this light ‘accruals’ are a tool often used for moving profit and

losses between the different accounting periods and are probably the most frequently used

means for earnings management (McNichols, 2000). But as already mentioned (in section 5.1)

only the discretionary accruals (DA) are a result of earnings manipulation and these have been

31

used as a proxy for earnings management in a number of studies. Ergo this thesis will use the

discretionary accruals as a proxy for earnings management. There are several competing

models used in detecting discretionary accruals. Dechow et al. (1995) compare the efficiency

of these models and conclude (although the results are modest) that the modified Jones model

is the best for detecting EM. Hence, we will determine the level of DA using the modified

Jones model. I’ve decided to conduct research using the cross-sectional procedure, due to the

evidence gained by Peasnell et al. (2000) that accruals models when estimated in a cross-

sectional setting have a tendency to yield more powerful tests than their time series

equivalent. As an adage I should also mention that using the time series equivalent would

make it difficult to compare the findings, since it is difficult to filter out result biases due to

the introduction of IFRS in 200521 and the financial crisis that already started to show effects

in the middle of 200722.

To estimate the discretionary accruals we characterize the total accruals (TA) as follows;

(1)

where

= all the independent variables are scaled by lagged assets to correct for firm size.

= the revenues in year (t) less the revenues in year (t-1).

= net receivables in year (t) less net receivables in year (t-1).

= gross of property, plants and equipment in (t).

= the residuals from the mJones model are considered as the discretionary accruals since

is a proxy for non-discretionary accruals.

However Kothari et al. (2005) remind us that the original Jones and mJones model fail to

completely control for firm performance. I control for the influence of prior firm performance

on discretionary accruals by use of matching the performance on the basis of a firms return on

assets. The reason for using ROA for performance matching has been addressed earlier in the

paper. Taking this into account we add an additional independent variable to the mix, thereby

augmenting the mJones model as follows;

21 http://www.atosorigin.com/en-us/Business_Insights/Reports/IFRS_Achieving_2005/default.htm22 http://www.globalissues.org/article/768/global-financial-crisis

32

(2)

5.5 Estimating Performance Matched Discretionary Accruals

To estimate the discretionary accruals on the basis of performance matching I will use a four

step process as used by B.Cotten(2008) in his research on earnings management prior to

initial public offering. The first step requires determining the level of total accruals, which is

represented by equation 3 (direct method) below;

(3)

Where:TA = Total accruals

EXBI = Income before extraordinary items and discontinued operations

CFO =Cash flow from operations

The CFO is determined by subtracting the ‘extraordinary items and discontinued operations’ from the net

cash flow of operating activities. The i and t are firm and time superscripts, respectively.

Use of the direct method over the balance sheet method23 is recommended by Cotton (2008)

and Hribar and Collins (2002) due to the fact that the balance sheet method has a tendency to

produce substantial errors in accrual estimation. Particularly, if the variable used to indicate

whether earnings management is present, is correlated with discontinued operations or the

occurrence of mergers and acquisitions, researchers might erroneously conclude the existence

of earnings management when there is none.

The second step consists of estimating the non-discretionary accruals using equation 4 and 5,

where these equations represent the cross-sectional modified Jones model. The non-

discretionary part of accruals is calculated using the following equation;

23 TACCt = (DCAt - DCLt - DCasht + DSTDEBTt – DEPTNt) where: TACC=Total accruals, DCA=change in current assets, DCL=change in current liabilities, DCash=change in cash and cash equivalents, DSTDEBT=the current maturities of long term debt and other short term debt included in current liablilities, and DEPTN=depreciation and amortization expense.

33

(4)

Where:

NDA= Non-discretionary accruals (scaled by lag total assets)

REV= the change in revenuesΔREC= the change in receivablesΔ

PPE= gross of property, plant and equipment

Assets= total assets

Here i, j and t represent firm, industry and time superscripts, respectively. The estimated betas are

industry and time specific and are calculated using the following equation:

(5)

Having estimated the non-discretionary component allows me to move on to step 3 of the process;

determining the discretionary accruals (DA). I find these DA (scaled by lagged total assets) by

subtracting the scaled non-discretionary accrual component (found by using equation 4) from each

firms actual total accruals scaled by lagged assets (TA*), represented by equation 6;

(6)

All though in this situation we have successfully managed to find the DA, we do not know whether

these accruals are a result of prior or current year’s performance. As mentioned before, these

models lack the ability to distinguish between executive opportunism and the truthful

reporting of a firm’s underlying economic performance. Controlling for this brings us to the

last step of the process. Here, each firm experiencing non-routine CEO turnovers in 2008 is

matched with a control firm not experiencing any turnover in the same year. The control firms

are chosen on the grounds of being from the same industry (2-digit SIC), having a relatively

similar total market value24 and the closest ROA to that of the firms experiencing CEO

turnovers. Finally, the DA of the matched firms is subtracted from the DA of the

24 Total Market Value is defined as the market capitalization plus the market value of debt

34

corresponding firms. Thus, the performance matched DA (PDA) is estimated using the

following equation, where c is the control firm superscript;

(7)

5.6 Expectations

The findings of Chia et al. (Asian Financial Crisis, 2007) has led me to believe that during

times of crisis earnings management will be less prominent because of the fact that

management’s incentive shifts from maximizing their accounting-based bonuses to saving

their companies to preserve their jobs. However we are dealing with a slightly different

situation. Namely, incoming CEOs have the incentive to blame their predecessors should poor

performance arise during their first year as CEO. So I believe that a different set of incentives

play a role for incoming CEOs during times of crisis. As already mentioned in the

introduction, the present Global Financial Crisis will have dire consequences for firm

performance resulting in larger numbers of CEO turnovers. These CEO turnovers exhibit

relatively more of the non-routine kind. I’ve also mentioned that prior research (Peter Wells,

2002) finds EM especially visible during non-routine CEO turnovers. Hence, I believe that we

will find signs of earnings management during the Global Financial Crisis of 2008/2009

partly due to the fact that the (predominant amount) of turnovers are non-routine, and non-

routine turnovers exhibit stronger signs of earnings management. These results might also be

intensified during times of crisis since companies are tempted to overstate charges, because

when earnings take a major hit Wall Street will in theory look beyond a one-time loss and

focus only on future earnings (Arthur Levitt, former head of SEC). Lastly, downwards

earnings management practices could also serve to maximize financial support from the

government as we have seen happen in the United States in 2008 (more on this later in section

6.2.4).

35

Chapter 6 Results

6.1 Descriptive Statistics of the Model Coefficients

This section includes the estimation of the regression coefficients necessary for calculating

the non-discretionary accruals. Predicting the sign of the change in revenues less the change

in receivables ( ) can prove to be a tough challenge. Revenues are typically related to

income increasing accruals, an increase in sales can have an increasing affect on some

working capital accounts, as well as income decreasing accruals on other accounts (e.g. trade

creditors). However, empirical research generally leans towards the sign being positive. The

expected sign of gross property, plant, and equipment on the other hand is expected to be

negative, since PPE exhibits a positive association with amortization and depreciation (which

has a decreasing effect on accruals).25

Descriptive statistics of the cross-sectional modified Jones model parameters are stipulated in

Table 2. Where % and % represent the amount of times the first en second

regression coefficients yielded the correct predicted sign. The parameters are provided per 2-

digit SIC industry. As an adage Table 3 provides the frequencies of the model coefficients to

get an overview of the tendencies per variable included.

SIC

13 -0.643 0.179 -0.109 0.060 -0.106 0.009 0.461 25 100P Value 0.000 0.024 0.000

35 -0.428 0.193 0.054 0.037 -0.098 0.027 0.147P Value 0.052 0.268 0.000

25 Goncharov and Zimmerman (2006)

36

36 -0.709 0.113 0.116 0.134 -0.215 0.044 0.228P Value 0.000 0.452 0.000

37 -0.105 0.127 0.021 0.016 -0.136 0.031 0.360P Value 0.659 0.498 0.000

38 -0.176 0.115 0.011 0.041 -0.156 0.029 0.189P Value 0.142 0.781 0.000

49 -0.714 0.129 0.012 0.038 -0.049 0.003 0.329P Value 0.000 0.647 0.000

56 1.306 0.974 0.023 0.064 -0.166 0.019 0.572P Value 0.327 0.803 0.000

73 -0.569 0.107 -0.136 0.027 -0.153 0.027 0.244P Value 0.000 0.000 0.000

Table 2: Model coefficients segmented by industry classification

Mean St.Dev Median Min Max-0.258 0.24212

6-0.480 -0.714 1.306

-0.001 0.116165

0.017 -0.136 0.116

-0.135 0.023622

-0.138 -0.215 -0.049

Table 3: Mean estimates

Table 2 shows the estimate to be significant up to the 5% level for only 2 out of the 8

industries. Moreover the predicted sign for this estimate only proves to be correct around 25%

of the time. When referring to Table 3 we can see that the mean value of this regression

coefficient is -0.001. With the median being less sensitive to extreme scores, I find a

significantly different median value of 0.017. However following the t-test I find the value of

mean to be insignificant with a p-value of 0.974. The t-statistic, mean and median

highlights the lack of relation between and working capital accruals,

which is consistent with prior research (Peasnell, Pope & Young (1999); Krishnan (2003)).

However, with regards to the regression coefficient related to PPE ( ), table 2 shows

that all of the 8 industries incur significance up to the 1% level. In addition I find that all of

the 8 industries included in my research generated the correct expected sign. Table 3 provides

us with a mean regression coefficient of -0.135. Again to account for any extreme values that

might be present in any of the included industries I refer to the median, which is -0.138 and

closely resembles the mean value estimation. The mean proves to be significant with

a p-value of 0.000. Consistent with prior research, I am confident to have found a fair

37

approximation of the regression coefficient relating to the gross of property, plant and

equipment. Furthermore, the mean of the regressions across industries average out to

about 32 percent. I also find some traces of heteroskedasticity amongst the industries using

the White’s Test, where the regressions controlled for heteroskedasticity tend to show slightly

different standard errors. The relatively low explanatory power of the regressions and the

presence of heteroskedasticity indicate the discretionary accruals estimations might exhibit

econometric problems when using the modified Jones model. This is consistent with prior

research (Subramanyam, 1996; Guay et al., 1996; Wells, 2002), where the Jones model

reported considerable imprecision in estimating the discretionary accruals.

6.2.1 Descriptive Statistics for Discretionary Accrual Measures

After having established the regression coefficients per industry I can determine the level of

non-discretionary and discretionary accruals for both the control sample and the sample

containing the non-routine CEO turnover. The measurements for the control- and original

sample are presented in Table 4 and 5, respectively.

Variables Mean St Dev Median

Min Max

EBXI 69.25 1239.28 10.24 -7304.69 12334CFO 404.27 1382.83 83.46 -1009 18812TA -335.02 1018 -46.36 -7592.81 1164.53TA/ -0.107 0.127 -0.065 -0.955 0.161

NDA -0.086 0.106 -0.052 -0.954 0.115DA -0.021 0.102 -0.0035 -0.606 0.299P Value 0.001Table 4: Accrual measurements for control sample. Where EBXI stands for Income Before Extraordinary

Expenses and Discontinued Operations, CFO stands for Cash Flow from Operations, TA stands for Total

Accruals, TA/ stands for Total Accruals divided by one year lagged assets (to control for firm

size), NDA stands for Non-Discretionary Accruals and DA for Discretionary Accruals. Both variables are

scaled by lagged total assets. The p-value is determined for the estimation of DA. N=482

Variables Mean St Dev Median Min MaxEBXI -32.47 854.64 4.129 -4244 5387CFO 436.88 1192.99 98.92 -1274 9596TA -469.35 1414.21 -111.47 -12352 1462TA/Assets

-0.113 0.0999 -0.085 -0.469 0.161

NDA -0.072 0.091 -0.058 -0.466 -0.458

38

DA -0.041 0.1224 -0.0311 -0.458 -0.33P Value 0.000Table 5: Accrual measurements for original sample. Where EBXI stands for Income Before Extraordinary

Expenses and Discontinued Operations, CFO stands for Cash Flow from Operations, TA stands for Total

Accruals, TA/ stands for Total Accruals divided by one year lagged assets (to control for firm

size), NDA stands for Non-Discretionary Accruals and DA for Discretionary Accruals. Both variables are

scaled by lagged total assets. The p-value is determined for the estimation of DA. N=194

Table 4 & 5 show total accruals as the difference between income before extraordinary

expenses and discontinued operations and cash flow from operations (direct method)26. You’ll

notice that the matched control sample (Table 4) exhibits negative total accruals and non-

discretionary accruals. The average total accruals of these 482 observations are about -10.7%

of lagged total assets, while the non-discretionary accruals average out to -8.6% of lagged

total assets. Consistent with prior research the negative nature of these variables is largely due

to depreciation. That leaves us with a discretionary accrual value of circa -2.1% of lagged

total assets. This does not necessarily have to entail the presence of earnings management.

Since present day accrual models estimate discretionary accruals with a slight inconsistency

due to their low explanatory power and the presence of heteroskedasticity (page 36) the

decreasing tendency of managed earnings is most likely related to financial distress during the

financial crisis. Table 5 also exhibits negative total accruals and non-discretionary accruals.

The original sample of 194 non-routine CEO turnovers experiences a mean total accrual of -

11.3% of lagged total assets, while the non-discretionary accruals average out to about -7.2%

of non-discretionary accruals. This of course leaves a lot of space for the discretionary

accruals (which is a proxy for earnings management). This value averages out to -4.1% of

lagged total assets. This proves to be significant at the 1% level. I thereby accept the first

hypothesis where in the original Firms sample of 2008 the level of negative discretionary

accruals increases in the year of change reducing firm earnings. However, no significant

conclusions of earnings management can be made until this sample is corrected for firm

performance. Information concerning whether the discretionary accruals for the original

sample still prove to be significant after these are corrected for firm performance will be

handled in the next subsection.

6.2.2 Correcting for firm performance

26 The direct method is chosen above its balance sheet counterpart as motivated in section 5.5

39

The following graph shows the discretionary accrual tendencies across the thirteen observed

industries. The discretionary accruals pertaining to the original sample (containing non-

routine CEO turnovers) is represented in the graph by the acronym DA O, while the

discretionary accruals of the matched control sample uses DA C as its acronym.

The graph shows how the general tendency of discretionary accruals is more severe in the

original sample than its matched counterpart. In fact, out of the 8 industries included in the

original sample 7 of them managed to exceed the level of discretionary accruals that is

achieved by the matched control sample. As mentioned before, to test whether the

discretionary accruals are of statistical significant value we need to correct for firm

performance by subtracting the DA of the control sample from that of the original sample.

Which leaves us with the performance matched DA (PDA).

N Mean Difference Lower Upper t p valuePDA 194 -0.0205 -0.0549 0.0113 -2.624 0.034Table 6: T-test for the performance matched discretionary accruals.

Table 6 shows that even when the discretionary accruals pertaining to the original sample are

controlled for firm performance they still manage to exhibit strong signs (p value: 0.034) of

40

decreasing earnings management with a significance value up to 5%. Amongst the industries

this averages out to about -2.05% of lagged total assets, with the highest level of decreased

earnings management reaching up to nearly -5.5% of lagged total assets. The relatively low t-

value allows me to conclude that the PDA significantly differ from zero, thereby accepting H1

where after controlling for firm performance the original Firms sample still contains signs of

decreased earnings management during the 2008 crisis period. To try to put that into

perspective I’ve measured the mean value of total assets for the original sample of 2007 (all

variables in the regression were scaled by lagged total assets for 2008). This amounts to a

mean value of circa US$5,385,499,000 for total assets in 2007. Considering the average

percentage of discretionary accruals equals -2.05% of lagged total assets, it would mean the

estimate of the level of performance matched decreasing earnings management could equal

circa –US$118,481,000 with a standard deviation of US$78,868,000. This could amount to a

material misrepresentation in company annual reports during times of crisis.

6.2.3 Sensitivity Analysis

Even though the modified Jones model exhibits more power than other existing accruals

model in detecting earnings management, it has still managed to receive considerable

criticism. Dechow et. al (1995) and Guay et. Al (1996) for example, comments on the

imprecision of the Jones model in finding discretionary accruals. To lessen the measurement

error problem of the Jones model I apply a new variable to the model as done in an article by

Chan, Jegadeesh and Sougiannis (2004). In their paper they included a cash flow variable

(CF-Jones) to the model to estimate between non-discretionary and discretionary accruals.

The inclusion of this variable is motivated by Dechow (1994) where he shows evidence that

changes in cash flows are largely and negatively related to accruals. This negative association

takes place because generally accepted accounting principles allow executives to use accruals

in order to modify the timing of cash flows, so that earnings can closely reflect the underlying

performance of the company. To answer for the strong negative relation, the CF-Jones model

includes the change in cash flows (where is a proxy for the change in net cash flow

from operating activities) as the third variable in equation 8. The mean estimates of the model

are stipulated in table 7 where all of the eight industries exhibited a negative relation to

accruals, significant to the 5% level.

(8)

41

Mean St.Dev Median Min Max-0.208 0.21212

5-0.480 -0.614 1.246

0.004 0.103165

0.015 -0.148 0.123

-0.135 0.023620

-0.137 -0.228 -0.052

-0.429 0.062463

-0.426 -0.623 -0.167

Table 7: Mean estimates CF-Jones model. N=482

Finally, table 8 summarizes the result of the t-test with regards to the performance matched

discretionary accruals using the CF-Jones model, where there are significant (p=0.2) signs of

negative discretionary accruals.

Table 8: Performance matched discretionary accruals using the CF-Jones model

The use of the CF-Jones model as a robustness check has produced near similar results

pertaining to the existence of decreased earnings management in 2008. Furthermore, the mean

of the regressions across industries using the CF-Jones model average out to about 39

percent, which is a rise in explanatory power of nearly 7% when compared to the results

generated by the modified Jones model.

6.2.4 Motivation for Decreased Earnings Management

So what could be the possible reasons for management to partake in decreasing earnings

management during times of financial crisis instead of taking accrual increasing measures to

dampen the blow of financial hardship?

42

N Mean Difference Lower Upper t p valuePDA 194 -0.0179 -0.0482 0.0137 -3.02 0.020

As mentioned in chapter 4, the core level for managements earnings tendencies are related to

the firm’s performance in relation to a certain benchmark. The benchmark can be set in a

number of different ways. It could relate to previous periods performance (to show current

year’s performance improvement), expectations of analysts (where to end goal is to meet or

beat these expectations), or whatever benchmark is set in managements compensation

contract. You can imagine their desire to manage earnings upwards to realize a bonus boost if

managers fall just a few cents short of hitter the target. This is probably the reason why firms

missing their target by a few cents is tens of times less likely to happen than firms making or

exceeding their target (Burgstahler & Dichev, 1997; DeGeorge, Patel and Zeckhauser, 1999). To get more in line with the findings in Table 4, different incentives arise when firms exhibit poor performance in times of crisis during which firms are likely to be way below their targets. Firstly, it is unlikely that any amount of earnings management will help executives reach their targets. Secondly, the cost of being even worse is minimal when the firm is already way below target. This is the situation in which ‘big-bath’ accounting takes place. Here firms will make big provisions for bad debts, take large restructuring charges and other income decreasing accounting measures. This will result in expenses that would not be recognized in the future and will thereby lead to future income boosts. Additionally, executives enjoy greater credit for turning around a firm, even though an essential portion of the turnaround may be due to the accounting choices made (Mohanram, 2003).

Evidence shows companies experiencing non-routine CEO turnovers as eager to overstate

large charges beyond the level done by matched firm’s not experiencing any turnovers. This

earnings level tendency does not seem to be mitigated by the financial crisis. In a speech by

Arthur Levitt (former head of SEC) he claims:”By regularly assessing the efficiency and

profitability of their operations, firms remain competitive. However, problems arise when we

see large charges associated with company restructuring. Giving them the so called

“earnings bath”, these charges help the firms to “clean-up” their balance sheet. Companies

are tempted to overstate these charges, because when earnings take a major hit Wall Street

will in theory look beyond a one-time loss and focus only on future earnings. So if these

charges are conservatively estimated with a little extra padding, these so called

43

“conservative” estimations are miraculously reborn as income when estimates change or

future earnings fall short.”

Another plausible reason for decreased earnings management incentives could be related to

the prospective to maximize financial benefits and support in the form of bailouts from the

U.S. Government (Chia, Lapsley and Lee; 2007). The U.S. Government has made a number

of bailouts during the 2008 crisis period. Although the bulk of these bailouts pertain to the

financial industry (which is similar to prior research, excluded from mine), the automotive

industry was also granted one27. The automotive industry is represented in my research by the

2-digit SIC Code number of 37. Although this sector contains a much too small amount of

non-routine CEO turnover observations to make any significant suggestions (11

observations), the graph on page 39 does show a much larger discrepancy in decreased

earnings management measures. In line with the conclusion of Jones’ (1991) study, firms

portraying a poorer financial situation by a drop in reported earnings via decreased earnings

management are likely to be seen as having more chance to receive more financial aid and

government assistance. Thus, in the context of the operating environment this paper shows

that the earnings management incentive is dependent upon what executives perceive as

benefits outweighing the costs.

27 ProPublica: an independent, non-profit newsroom that produces investigative journalism in the public interest; http://www.propublica.org/special/government-bailouts: 01/04/2010, 2:49 PM

44

Chapter 7 Conclusion

7.1 Conclusion

As reported by Challenger, Gray, and Christmas Inc the 2008 period has seen the number of

executives leaving their jobs in North America at its highest for a decade (1484 executives).

That tallies up to circa 6 CEOs giving up their position every working day of the year. These

numbers show that amidst the massive job cuts the individuals at the top are also feeling the

pressure. The financial crisis contributes to CEO turnovers by making the CEOs more

vulnerable with little room for error. Their firms and markets are in crisis, and in most cases

firm stocks are significantly down. In these harsh times the CEOs are under increased

pressure from employees and shareholders to improve performance. Adding to that it should

be noted that it is much harder for the principal to monitor the agent’s behavior if its task

lacks programmability (Eisenhardt, 1985, 1988). Eisenhardt defines programmability as the

degree to which appropriate behavior by the agent can be specified in advance. For example,

the job of a truck driver is much more programmed than that of a CEO. Therefore it will be

significantly more difficult for the principal to monitor the CEOs behavior in comparison with

that of the truck driver.

45

Despite the fact that approving key managerial decisions is mostly left to the board of

directors, the reality is that executives make decisions on a number of terrains concerning

financing, operations and investments (such as capital investments, designing and executing

new business strategies, acquisition of securities, the issuance of dividends etc.). To be able to

make just decisions regarding these terrains executives acquire superior knowledge of the

firm and its economics. An example thereof can be found in studies on insider trading

(Beneish & Vargus, 2002), where insiders show a tendency to buy stock when its undervalued

and sell stock when its overvalued. With this superior knowledge executives can use earnings

management in two different ways. They can either take advantage of the flexibility in

accounting methods to enhance the transparency of financial reports, or attempt to hide

unfavorable news by misrepresenting or diminishing the transparency of the financial reports.

Research find that the incoming CEO leans towards undertaking in earnings deflating

(“earnings bath” or “big bath”) measures. Here the incoming CEO lowers the earnings in the

year of his/her introduction with the opportunity to blame the poor performance on the

predecessor. This also gives a good plateau for the incoming CEO to base his future earnings

on. With respect to Pourciau’s (1993) investigation, she finds incoming executives recording

accruals and write-offs to decrease the earnings in the year of the turnover and increase

earnings the following year. However her results are not corrected for firm performance so the

results may also be caused hereby. In line with the findings of Pourciau (1993) are the results

of Wells (2002) where “earnings baths” seemed to occur especially in the case of non-routine

CEO turnovers.

Al though Godfrey (2003) finds evidence of impression management during CEO turnovers,

these results are merely limited. This is the reason why I have decided to take a different

approach in detecting earnings management. Kothari et al.’s research (2005) has been used as

an example to distinguish between earnings management and firm performance. In their

research they’ve augmented popular models for detecting earnings management by taking

firm performance into account, and found that the augmented models generated enhanced

reliability in earnings management research.

Past research has shown how earnings management tendencies get affected through times of

crisis (Chia et al. 2007). By means of this thesis I’d like to add to the feeble existing body of

literature concerning the effects of different economic environments on earnings management

by means of the following research question;

46

How has the effect of non-routine CEO turnovers on earnings management in the United

States of America changed due to the Global Financial Crisis in 2008?

In finding an answer to the research question the following hypothesis has been developed;

H1: during the 2008 crisis period firms experiencing a CEO turnover increase the

level of negative discretionary accruals, thereby reducing the earnings.

H1: After controlling for firm performance the level of negative discretionary accruals

averages out to about -2.05% of lagged total assets amongst the 8 industries researched, with

the highest level of negative earnings management reaching up to nearly -5.5% of lagged total

assets. The relatively low t-value allows me to conclude that the performance matched

discretionary accruals significantly differ from zero. By rejecting the null hypothesis of no

earnings management after controlling for firm performance I conclude that the original Firms

sample still contains signs of decreased earnings management during the 2008 crisis period.

Similar to my expectations I believe that a different set of incentives play a role for incoming

CEOs during times of crisis. As already mentioned in the introduction, the present day Global

Financial Crisis has had dire consequences for firm performance resulting in large numbers of

CEO turnovers. These CEO turnovers are predominantly of the non-routine kind. I’ve also

mentioned that prior research (Peter Wells, 2002) finds earnings management especially

visible during non-routine CEO turnovers. Hence, I have found clear signs of earnings

management during the Global Financial Crisis of 2008/2009 partly due to the fact that the

(predominant amount) of turnovers are non-routine, and non-routine turnovers exhibit

stronger signs of earnings management. Since the focus here lies on the year of the turnover in

2008, there are stronger signs of decreasing earnings management consistent with the findings

of Godfrey et al. 2003; Murphy 1992; Pourciau 1993; Wells 2002.

So what could be the possible reasons for management to partake in decreasing earnings

management during times of financial crisis instead of taking accrual increasing measures to

dampen the blow of financial hardship?

Different incentives arise when firms exhibit poor performance in times of crisis during which firms are likely to be way below their targets. Firstly, it is unlikely that any amount of earnings management will help executives

47

reach their targets. Secondly, the cost of being even worse is minimal when the firm is already way below target. This is the situation in which ‘big-bath’ accounting takes place. Here firms will make big provisions for bad debts, take large restructuring charges and other income decreasing accounting measures. This will result in expenses that would not be recognized in the future and will thereby lead to future income boosts. Additionally, incoming executives enjoy greater credit for turning around a firm, even though an essential portion of the turnaround may be due to the accounting choices made (Mohanram, 2003).

Another plausible reason for decreased earnings management incentives could be related to

the prospective to maximize financial benefits and support in the form of bailouts from the

U.S. Government (Chia, Lapsley and Lee; 2007). In line with the conclusion of Jones’ (1991)

study, firms portraying a poorer financial situation by a drop in reported earnings via

decreased earnings management are likely to be seen as having more chance to receive more

financial aid and government assistance.

7.2 Measurement errors

The measurements in this paper are not without its faults. The mean of the regressions

across industries average out to about 34 percent, meaning that the dependent variables only

explain circa 34 percent of the result pertaining to the dependent variable. I also find some

traces of heteroskedasticity amongst the industries using the White’s Test, where the

regressions controlled for heteroskedasticity tend to show slightly different standard errors.

Although the presence of heteroskedasticity does not introduce biases of inconsistencies in the

regression coefficients, it can cause the standard errors to be underestimated. This in turn can

cause relationships to be statistically significant when in fact they are too weak to be

differentiated from zero. The relatively low explanatory power of the regressions and the

presence of heteroskedasticity indicate the discretionary accruals estimations might exhibit

econometric problems when using the modified Jones model. This is consistent with prior

research (Subramanyam, 1996; Guay et al., 1996; Wells, 2002), where the Jones model

reported considerable imprecision in estimating the discretionary accruals.

48

Another cause for concern lies with the identification of the firms within 2-digit SIC

industries. The train of thought in estimating the regression coefficients per industry is that it

is assumed that all firms within that industry exhibit a relatively similar coefficient estimate

pertaining to the dependent variables. Therefore the use of the 2-digit SIC (similar to prior

research) might not be a good proxy for segmenting industries. The major economic group

with a 2-digit SIC of 37 (Transportation Equipment) for example, contains industries ranging

from Motor Vehicles and Car Bodies (3711) to Aircraft Parts and Equipment (3728). Since

my research estimates the mean of discretionary accruals from each individual firm within the

2-digit SIC industry, it is not hard to imagine that these two differing industries exhibit

dissimilar coefficient estimates pertaining to dependent variables.

49

Table of LiteratureAuthors Body of work Sample Methodology ResultsDavid Burgstahler, Iia Dichev (1997)

Search for evidence about whether (how and why) firms avoid earnings decreases and losses.

Compustat databases for the years 1976-1994 consisting of 65000 firm observations, excl regulated firms.

Pooled cross-sectional empirical distribution of scaled earnings changes and levels of earnings

8% to 12% of firms with earnings decreases and 30% to 44% of firms with negative earnings exercise discretion

Frank Yu (2006) Examination of insider incentive change when confronted with different corporate governance mechanisms.

Yermack(1995) dataset from 1984-1991 consisting of 2736 firm-year observations from 346 publicly listed firms in the United States.

mJones model using DA as a proxy for earnings management

Firms with a high level of internal governance manage earnings more than firms with a high level of external governance.

Christian Leuz, Dhananjay Nanda and Peter D. Wysocki (2002)

Pervasiveness of EM in countries with different investor protection mechanisms.

8616 firms (excl regulated firms) residing in 31 different countries from 1990-1999.

Allocation of firms in clusters based on countries characteristic and creating proxies to capture EM pervasiveness.

Outsider economies with dispersed ownership, high investor protection and large stock markets exhibit lower levels of EM.

Chia, Lapsley and Lee (2007)

Determining the extent of EM during a financial crisis by using the Asian crisis of 1997 as an example.

Using the PACAP and Worldscope database to derive 383 firm-observations for the fiscal years of 1995-1998

mJones cross-sectional model using DA as a proxy for EM.

There is a significant decrease of EM during the Asian financial crisis of 1997.

Patricia Dechow, Richard Sloan and Amy Sweeney (1995)

Evaluating the relative performance of competing EM models by comparing the specification and power of commonly used test statistics.

All random samples are derived from Compustat between 1950-1999. (1) a randomly selected sample of 1000 firm years; (2) samples of 1000 firm-years randomly selected from a pool containing

The specification quality of the test statistic is measured by the frequency in which they generate Type I errors. Type II errors are also measured in determining the power of the model used.

All tested models appear well specified (limited Type I errors). However they generate low power for EM of economically plausible magnitudes. Although the results are modest, the modified

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firms experiencing extreme financial performance; (3) samples of 1000 randomly selected firm years in which a fixed amount of accrual manipulation has been artificially introduced; and (4) a sample of 32 firms that are subject to SEC enforcement actions for allegedly overstating annual earnings in 56 firm years.

Jones model is deemed the best at detecting EM.

Peasnel, Pope and Young (2000)

Assessing the relative performance of cross-sectional procedure over time-series procedures.

Firms on datastream from 30 June 1990- 31 May 1997 consisting out of 4352 firm-year observations from different 837 firms.

The specification quality of the test statistic is measured by the frequency in which they generate Type I errors. Type II errors are also measured in determining the power of the model used.

The cross-sectional models generate relatively powerful tests for economically plausible tests for accruals management.

Peter Wells (2002) Search if and to what extent earnings management occurs around the time of a CEO change.

100 largest ASX firms based on market capitalization in the years 1984-1994 in Australia.

Modified Jones model to estimate unmanaged or expected accruals.

Incoming CEO’s reduce income in the year of the CEO change by manipulating abnormal and extraordinary items.

Kevin Murphy (1992) Describes the behavior of financial variables surrounding CEO turnovers.

Forbes annual surveys of 1630 executives during a 1971-1989 period & Compustat data from 1965-1989.

Investigate growth rates of 8 variables using cross-sectional time-series regressions.

Little evidence of outgoing CEOs manipulating earnings. Evidence of incoming CEOs engaging in downward earnings

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management in year of the change.

Robert Parrino (1997) Report evidence on factors that influence management turnovers.

31 CEOs in the period 1970-1989 chosen based on certain criteria. Data obtained from Forbes surveys, Wall Street Journal’s succession announcements and COMPUSTAT.

Cross-sectional regression model

In homogeneous industries, poor CEOs are easier to identify and cheaper to replace than heterogeneous industries. In a homogeneous industry the likelihood of a forced turnover and an appointment of a CEO from the same industry increase.

Susan Pourciau (1993) The relation between non-routine executive turnovers and discretionary accounting choices.

73 executive turnovers during the period of 1985-1988.

Random walk model is used to estimate expected earnings and accruals.

Incoming executives decrease the earnings in turnover year and increase it next year. Outgoing executives decrease earnings in departure year.

Jayne Godfrey, Paul Mather, Alan Ramsay (2003)

Earnings Management and Impression Management around the change of CEOs.

63 public listed firms that have had a CEO change from 1992-1998 in Australia.

Random walk model to measure unexpected accruals & Binomial tests on graphs & Joint tests.

Downward earnings management in CEO change year. In the year after the CEO change, upward earnings management and favorable impression management.

Kothari, Leone and Wasley (2005)

Performance matched discretionary accruals measures.

Firm-year observations from the COMPUSTAT Industrial Annual, and Research files from 1962 through 1999. Excluding firms with insufficient data

Comparing the specification and power of the Jones-, mJones-, and augmented models.

The performance matched discretionary accruals are relatively powerful and tend to be the best specified measure of discretionary accruals.

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to compute Total Accruals.

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