Erasmus University Rotterdam
Erasmus School of Economics
Master Accounting, Auditing and Control
“Investor protection: a motive for
not cooking the books?”
A study on the impact of investor protection on income smoothing
“I didn’t cook the books. Instead, I incorporated them into a tasty
tuna noodle casserole!”
July 28th 2010
Author: Zeenat N.S. William
Supervisor: Dr C.D. Knoops
Co-reader: prof. dr M.A. van Hoepen RA
P ROLOGUE
The last couple of months were spent writing this thesis, the final element of the master
Accounting, Auditing and Control. During this period I received support from several
people and I would like to take this opportunity to show my gratitude.
First of all I wish to thank my supervisor Dr. C.D. Knoops for his feedback, critical view
and for motivating me at times. I also greatly appreciate the quick responses to my
questions and the fact that I could always stop by his office to brainstorm while enjoying a
cup of coffee or plain water.
My sincere gratitude goes out to my parents and brother who stood by me during this
period. Their words of wisdom, support and motivation have been of priceless value.
Thanks for loving me and having faith in me.
Further, I would like to thank my friends who stood by me and supported me in whichever
way; sometimes support came in the form of doing something fun or in the form of wise
words.
At last but definitely not least, I would like to thank PricewaterhouseCoopers for
providing me with a fun place to write my thesis in peace.
Thanks to all, for making this process bearable!
Hereby I proudly present to you five months of hard work.
- Zeenat William
2|Master thesis accounting, auditing and control
A BSTRACT
The focus of this thesis lies on the relationship between the occurrence of income
smoothing and the level of investor protection in a country. I will investigate whether
income smoothing is more pervasive in low investor protection countries than in high
investor protection countries. My expectations, which are based on previous studies, are to
find that income smoothing is more pervasive in low investor protection countries. In
order to measure both real income smoothing and artificial income smoothing two
measures, developed by Leuz et al. (2003), are used. From these two measures the
aggregate income smoothing score is derived. The investor protection variables used are
obtained from Djankov et al. (2007).
Several hypotheses are stated in this thesis, the most important one being that there exists
a relationship between the occurrence of income smoothing and the level of investor
protection in a country are researched by using statistical analysis in the form of
correlation matrices and a regression model. The statistical output however, does not
confirm any of the hypotheses formulated even though previous research provided
evidence that in countries with a high level of investor protection income smoothing is less
pervasive than in countries with low investor protection. This can be explained by the
population and sample. Also, the second income smoothing measure used has a broad
range and causes a significant change in the aggregate income smoothing score for certain
countries.
Keywords: earnings management, income smoothing, investor protection
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T ABLE OF C ONTENTS
Prologue .................................................................................................................... 2
Abstract..................................................................................................................... 3
Table of Contents...................................................................................................... 4
1.1
Research Question .......................................................................................... 8
1.2
Structure ......................................................................................................... 9
2
Earnings Management ..................................................................................... 11
2.1
The Difference between Earnings Management and Fraud ........................ 12
2.2
Income Smoothing........................................................................................ 13
2.2.1
2.3
3
Incentives for Smoothing Earnings ........................................................... 15
Conclusion .................................................................................................... 16
Accruals Methodology...................................................................................... 17
3.1
Accruals ......................................................................................................... 17
3.2
The Jones Model ........................................................................................... 18
3.2.1
Concerns regarding the Jones Model ...................................................... 20
3.3
The Modified Jones Model ........................................................................... 21
3.4
Conclusion .................................................................................................... 22
4
Other Models ................................................................................................... 23
4.1
Burgstahler and Dichev................................................................................. 23
4.2
The Imhoff and Eckel Model ......................................................................... 24
4.3
Conclusion .................................................................................................... 25
5
Corporate Governance ..................................................................................... 26
5.1
Investor Protection ....................................................................................... 28
5.1.1
Anti-self-dealing index .............................................................................. 29
5.2
Conclusion .................................................................................................... 30
6.3
Common-law vs. Code-law ........................................................................... 35
Barth, Landsman and Lang (2008) .......................................................................... 36
Jeanjean and Stolowy (2008) .................................................................................. 37
7
7.1
Studies on Earnings Management and Investor Protection ............................ 39
Earnings Management and Investor Protection .......................................... 39
Leuz, Nanda and Wysocki (2003)............................................................................ 39
Cahan, Liu and Sun (2008) ...................................................................................... 41
Wright, Shaw and Guan (2006) .............................................................................. 42
Nabar and Boonlert-U-Thai (2007) ......................................................................... 43
7.2
Conclusion .................................................................................................... 43
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8
Hypotheses and Research Design .................................................................... 45
8.1
Hypotheses ................................................................................................... 45
8.2
Measuring investor protection ..................................................................... 47
8.3
Measuring income smoothing ..................................................................... 48
8.3.1
Measuring real smoothing ........................................................................ 49
8.3.2
Measuring artificial smoothing ................................................................. 51
8.3.3
Measuring total income smoothing.......................................................... 51
8.4
Sample selection .......................................................................................... 52
8.5
Earnings Management Pre-IFRS and Post-IFRS ............................................ 54
9
Empirical study: Influence of investor protection on Income Smoothing ...... 55
9.1
Introduction .................................................................................................. 55
9.2
Hypotheses ................................................................................................... 55
9.3
Sample .......................................................................................................... 56
9.4
Descriptive statistics ..................................................................................... 56
9.5
Income smoothing measures ....................................................................... 58
9.6
Cluster analysis ............................................................................................. 60
9.7
Statistical analysis ......................................................................................... 63
9.7.1
Real income smoothing and artificial income smoothing ........................ 63
9.7.2
Aggregate income smoothing ................................................................... 64
9.7.2.1
Correlation matrix ................................................................................ 65
9.7.2.2
Regression analysis ............................................................................... 66
9. 8
Model assumptions ...................................................................................... 67
9.9
Results and Discussion .................................................................................. 70
10
Empirical study: Income smoothing in the pre-IFRS and post-IFRS period .. 74
10.1
Introduction .............................................................................................. 74
10.2
Income smoothing in the pre-IFRS period ................................................ 75
10.3
Income smoothing in the post-IFRS period .............................................. 77
10.4
Statistical analysis ..................................................................................... 78
10.4.1
Correlation matrix pre-IFRS period ....................................................... 78
10.4.2
Regression analysis pre-IFRS period...................................................... 78
10.4.3
Correlation matrix post-IFRS period...................................................... 79
10.4.4
Regression analysis post-IFRS period .................................................... 79
10.5
Results and Conclusions ............................................................................ 79
11.1
Limitations................................................................................................. 81
11.2
Suggestions for further research .............................................................. 82
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12
Thesis Conclusion ......................................................................................... 83
References .............................................................................................................. 85
Appendix A
Schematic overview of previous studies ....................................... 90
Appendix B
Variables downloaded from Worldscope ...................................... 92
Appendix C
Hierarchical K-Means cluster analysis .......................................... 93
Appendix D Scatter Plot ...................................................................................... 94
Appendix E
Residuals Statistics.......................................................................... 95
Appendix F Correlation Matrix and Model Summary Real Smoothing ............. 96
Appendix G
Correlation Matrix and Model Summary Artificial Smoothing .... 97
Appendix H Correlation Matrix and Model Summary pre-IFRS Period ............ 98
Appendix I Correlation Matrix and Model Summary post-IFRS Period ............ 99
Appendix J Earnings Management Measures from Leuz et al. (2003) ............ 100
6|Master thesis accounting, auditing and control
1
I NTRODUCTION
Several researchers posit that the occurrence of earnings management in a country will be
influenced by the level of investor protection in that country (Cahan et al. 2008, Leuz et al.
2003). Earnings management, which was at the base of several accounting scandals
(Enron: see Catanach and Catanach, 2003), has been researched and discussed extensively
in prior studies (Beneish 1999, Kinnunen et al. 1995). It can be described as a strategy of
generating accounting earnings, which is accomplished through managerial discretion over
accounting choices and operating cash flows (Phillips et al. 2003) as well as production
and investment decisions that reduce the variability of earnings. Several academic studies
have argued that there is a relation between weak corporate governance and poor financial
reporting, financial information fraud and earnings management (Dechow et al. 1996,
Beasly et al. 1999, Cohen et al. 2004). This has led to legislators and standard setters
setting more strict regulations regarding corporate governance. In the U.S. for instance, the
collapse of large firms such as Enron Corporation and WorldCom has caused the
government to enact the Sarbanes-Oxley Act (SOX) in 2002 (Brown et al. 2004). SOX set
new or enhanced standards for all U.S. public company boards, management and public
accounting firms in order to improve issues such as corporate governance.
The classical principal-agent problem describes the difficulties that arise due to
asymmetric information between the principal and the agent. The separation of corporate
managers from outside investors involves an inherent conflict; the two parties may not
have the same interests. The objective of the principal-agent relationship is that the agent,
who is hired by the principal, acts in the interests of the principal; this however is not
always how it folds out in practice. That is why corporate control mechanisms have been
developed over the years. These mechanisms are the means by which managers are
disciplined to act in the investors’ interests. Control mechanisms include both internal
mechanisms, such as managerial incentive plans, director monitoring, and external
mechanisms, such as outside shareholder or debt holder monitoring, the market for
corporate control, competition in the product market, the external managerial labour
market, and securities laws that protect outside investors against expropriation by
corporate insiders (Bushman and Smith, 2003). Investor protection, which is an external
corporate control mechanism, defines the laws and regulations to observe, safeguard and
enforce the rights and claims of a person in his role as an investor (Djankov et al. 2007).
7|Master thesis accounting, auditing and control
This includes advice and legal action. According to Boonlert-U-Thai, Meek and Nabar
(2006) accounting quality is of importance to financial statement users. They argue that
managerial discretion is an important determinant of accounting quality, and that the
degree to which this discretion is abused by managers depends on the extent to which
investors are protected by law. Not all countries have the same level of investor protection,
it differs between countries.
Thus, the extent to which controlling managers and other insiders can manage earnings
depends on the level of investor protection in that specific country. Without adequate
investor protection, as Boonlert-U-Thai, Meek and Nabar (2006) acknowledge, there
would be little appreciation for the need for good quality accounting information. It is
argued that managers who engage in forms of earnings management probably have
different incentives to do so.
1.1
R ESEARCH Q UESTION
The purpose of this research is to study the impact of external corporate governance,
especially investor protection, on the occurrence of earnings management. In the spirit of
foregone discussion the following research questioned surfaced:
“Does a strong investor protection environment reduce the incidence of income smoothing
in countries?”
For good understanding this thesis will first discuss the manifestation that is earnings
management. The different forms it comes in and the manner in which it is applied in
practice will be addressed. The title gave away that the focus of this thesis lies on income
smoothing, one of the many forms of earnings management; therefore I will give extensive
insight on this.
People do what they do for a reason; the same goes for managers who engage in earnings
management. Without a certain motive, managers would not manage earnings since it is
perceived by society as unethical. Therefore it is interesting to look at what pushes
managers to cooking the books. Over the years several researchers have established
models to measure earnings management. The most common used models and their pros
and cons will be discussed.
8|Master thesis accounting, auditing and control
Investor protection is another main variable in my research. To fully comprehend the
adventurous journey called my master’s thesis, it is helpful to know what this variable
entails.
The goal of aforementioned journey is to determine to what extent investor protection
affects the other main variable, earnings management, in this research. Several researchers
have done research on this topic; their findings will be highlighted.
As of January 1st 2005 all European Union countries have adopted International Financial
Reporting Standards (IFRS). Even outside the EU they are widely used nowadays.
However, this was not always the case. IFRS were adopted to harmonize global
accounting standards. Some proponents have argued that IFRS adoption will increase
investor protection and improve accounting quality. Later on I will discuss why IFRS are
so generally accepted in recent days. After having examined the effect of investor
protection on the occurrence of income smoothing, the influence of IFRS on income
smoothing will be examined. I will do this by measuring the level of income smoothing in
the pre-IFRS period (2000-2004) and the post-IFRS period (2005-2008).
1.2
S TRUCTURE
In order to answer the research question this thesis will first discuss the sub-questions to
ultimately formulate an answer to the main research question.
Chapter 2 discusses the phenomenon that is earnings management as well as income
smoothing. It will also elaborate on the distinction between earnings management and
fraud. And the incentives which motivate managers to engage in income smoothing will
be discussed.
Chapter 3 will shed light on several models which can be used to measure earnings
management in general. In order to fully understand the models accruals will be discussed
first. The concerns regarding the Jones model will be mentioned as well.
Chapter 4 provides insight on other non-accrual models which can be used to detect
earnings management. It will also discuss the Imhoff and Eckel model which focuses
specifically on income smoothing.
9|Master thesis accounting, auditing and control
Chapter 5 discusses the theoretical background on corporate governance and specifically
investor protection. The proxy for investor protection that I will use for the empirical
research will also be discussed here.
Some researchers are of the opinion that IFRS has an influence on the level of investor
protection. In order to get a better understanding of IFRS and the discussion surrounding it
chapter 6 will focus on IFRS and its implementation in several countries. The views of
proponents and opponents will be addressed here as well.
Chapter 7 will provide a detailed literature study on the relationship between earnings
management and investor protection.
Chapter 8 presents the hypotheses as well as the research design. In order to obtain the two
income smoothing measures several calculations have to be made. The formulas used will
also be presented here.
Chapter 9 discusses the statistical analysis and results for the first leg of this research; the
influence of investor protection on income smoothing.
Chapter 10 presents the empirical study for the second leg of this research; income
smoothing in the pre-IFRS and post-IFRS period.
Chapter 11 addresses the limitations regarding this research. Also, suggestions for future
research are presented in this chapter.
Chapter 12 reviews the literature and statistical analysis and concludes.
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2
E ARNINGS M ANAGEMENT
The definition that best captures the essence of earnings management is the following1:
“Earnings management occurs when managers use judgment in financial reporting and in
structuring transactions to alter financial reports to either mislead some stakeholders
about the underlying economic performance of the company or to influence contractual
outcomes that depend on reported accounting number” (Healy and Wahlen 1999, stated in
Ronen and Yaari 2008). Earnings management is a phenomenon that exists all over the
globe, but evidence has proved that the level of earnings management will differ among
countries (Braun and Rodriguez 2008). Some researchers are of the opinion that earnings
management can be prevented if the reason for engaging in earnings management is
known and how it is done (Erickson, Hanlon and Maydew 2006). There are several ways
to engage in earnings management2, but the largest account that has been used for earning
management is the recognition of revenues and expenses (Dechow, Sloan and Sweeney
1996). Often earnings management is carried out to smooth earnings. Management can
use the availability of accounting discretion to understate earnings in years of good
performance and create reserves for years of less good performance, this is called income
smoothing. Several studies suggest that earnings management can be limited by welldesigned corporate governance structures (Dechow, Sloan and Sweeney 1996, Cornett et
al. 2006).
Dividend-paying firms tend to manage earnings upward when their earnings would
otherwise fall short of expected dividend levels. This behaviour is evident only in firms
with positive debt and is more aggressive prior to the Sarbanes-Oxley Act, in high-payout
firms, in firms whose CEOs receive higher dollar dividends and have higher payperformance sensitivities (Daniel et al. 2008). Moreover, this earnings management
1
Ronen and Yaari (2008) discuss three categories of earnings management: beneficial, pernicious and
neutral earnings management. They argue that defining earnings management as a non-truth-telling strategy
marks it as pernicious, which means that earnings management is immoral even when it does not involve
fraud (p.29). Yet earnings management can be beneficial, which enhances the transparency of reports, or
neutral, which is manipulation of reports within the boundaries of compliance with bright-line standards. At
the end, they came to the conclusion that the definition by Healy and Wahlen (1999) best describes earnings
management.
2
Ronen and Yaari (2008) acknowledge that there are several methods to engage in earnings management
(p.32). Which are: choosing between treatment which are allowed under GAAP; the decision on the timing
of the adoption of a new standard; a judgment call when GAAP requires estimates; classification of items as
above or below the line of operating earnings in order to separate persistent earnings from transitory
earnings; structuring transactions to achieve desired accounting outcomes; timing the recognition of
expenses and revenues; real production and investment decisions; managing the transparency of the
presentation; managing the informativeness of earnings.
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behaviour appears to significantly impact the likelihood of a dividend cut. Research done
by Daniel, Denis and Naveen implied that managers treat expected dividend levels as an
important earnings threshold. If reported earnings are an important dividend threshold,
managers have the incentive to manage earnings upwards to avoid dividend cuts when
reported earnings would otherwise be below expected dividend levels (e.g., see Watts and
Zimmerman, 1986). In other words, even though managing earnings does not alter the
firm’s capacity to pay dividends by generating additional cash, managing earnings upward
still affects the firm’s ability to pay dividends by allowing the firm to circumvent
constraints imposed by the firm’s debt covenants (Daniel et al. 2008).
2.1
T HE D IFFERENCE BETWEEN E ARNINGS M ANAGEMENT AND F RAUD
Earnings management can be either within or outside the boundaries of the law and
standards. Earnings management within the law involves the actions which are allowed
within the rules, but which are not necessarily within the spirit of the rules. This however
means that the lines of the law are not crossed. GAAP generally allow for a certain degree
of interpretation. Manipulation that is outside the law constitutes fraud and is illegal
(Stolowy and Breton 2004). Examples of fraudulent actions are recording unearned or
uncertain revenue and recorded fictitious inventory. Falsified documents or deleted or
forged transactions are also considered to be fraudulent actions (Stolowy and Breton
2004). The actions which can be considered as earnings management, such as income
smoothing and big-bath accounting, normally remain within the boundaries of the law.
Managing earnings does not give a fair representation of the financial position and
therefore would not fit in the “fair representation zone” in the figure below. Manipulation
however, is not fraud and therefore not illegal.
Dechow and Skinner (2000) make a distinction between actions which violate GAAP and
actions which are within GAAP. Within GAAP there are three categories: conservative
accounting, neutral accounting and aggressive accounting. They distinguish between
fraudulent actions and actions which are aggressive, but still acceptable. This thesis will
focus on non-fraudulent actions.
The figure below is obtained from Stolowy and Breton, 2004.
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Fraud
Fraud
Manipulation
Manipulation
Fair representation
2.2
I NCOME S MOOTHING
As mentioned earlier, managers engage in income smoothing to reduce the amount of
variation in periodic earnings over time. Income smoothing can be seen as a particular
form of earnings management (Stolowy and Breton 2004). To exist, this form of
manipulation needs the firm to make large enough profits. A naturally smooth income
stream simply implies that the income generating process inherently produces a smooth
income stream (Eckel 1981).
There are two types of intentional smoothing. Real smoothing involves making production
and investment decisions that reduce the variability of earnings. Artificial or cosmetic
smoothing is achieved through accounting choices. So, management is responsible for the
occurrence of both real and artificial smoothing.
Eckel (1981) provided a clear overview of the types of income smoothing; the figure is
displayed below.
Income smoothing
Intentional smoothing by
Management
Artificial
smoothing
Natural smoothing
Real
smoothing
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Researchers have several models at their disposal when it comes to detecting income
smoothing. The accrual models (see chapter 3) as well as some other models are
applicable. Over the past decades several other models have been created to detect income
smoothing. The Imhoff and Eckel model, which will be discussed in chapter 4, and the
Albrecht and Richardson model, are two of such models.
Due to the discretion permitted by accounting policies managers have the flexibility to
adjust reported earnings. Real smoothing is less transparent and therefore harder to detect
(Ewert and Wagenhofer 2005). Prior research proved that managers, to their own benefit,
distort earnings to give a wrong impression (Healy 1985). For example, managers will
manipulate the numbers to increase their remuneration, to keep their jobs, to gain tax
advantages and so on (Stolowy and Breton 2004). There is another reason why managers
would engage in income smoothing. That is to communicate private information about
future earnings to investors; Ronen and Sadan (1998) argue that income smoothing
enhances the ability of external users to predict future income. Studies done by
Subramanyam (1996) as well as Tucker and Zarowin (2006) provided evidence that
managers use discretionary accruals to smooth income. He also provides evidence which
implies that income smoothing communicates information about future benefits. So,
managers smooth earnings with both current and future relative performance in mind
(DeFond and Park 1997). Thus, income smoothing can be seen as both positive and
negative. On the one side, the negative perspective is misleading the users of the financial
reports and on the other side it will provide the investors of the company with information
about future earnings (Ronen and Sadan 1980). The following two definitions will
describe the positive and negative effect of income smoothing. The positive aspect of
income smoothing is described by Ronen & Sadan (1981). They state that income
smoothing is ‘’a deliberate management’s attempt to signal useful information to users of
financial reports’’.
The negative aspect of income smoothing can be described as follows: ‘’ the process of
manipulating the time profile of earnings reports to make the reported income stream less
variable, while not increasing reported earnings over the long run’’ (Fudenberg and
Tirole, 1995, pp. 75). More about managers’ incentives will follow in the next section.
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2.2.1
I NCENTIVES FOR S MOOTHING E ARNINGS
The classical perception people have of income smoothing is that of an opportunistic
management tool to manipulate financial statements. Ronen and Sadan (1980), however,
propose that income smoothing is not as evil as one might think. Manipulating accounts is
indeed a managerial activity (Dye 1988). But managers will engage in income smoothing
to either opportunistically gain private benefits at the expense of shareholders (Cahan, Liu
and Sun 2008) or to efficiently communicate private information about future earnings to
outsiders (Beidleman 1973, Ronen and Sadan 1980, Wang and Williams 1994). So,
smoothed earnings may enable external users to predict future income (Ronen and Sadan
1980). Suppose that it is common knowledge that whenever there is a change in
depreciation policy this is done to boost earnings until the bad time passes. The reader
then knows that when the firm changes a depreciation policy and publicizes it, he can
undo the change to calculate the underlying truth. This shows how managers can
communicate private information to outsiders through income smoothing.
Managers may or may not believe in market efficiency. If they do not, they may attempt to
smooth earnings. Stolowy and Breton (2004) listed some of the private benefits that can
encourage managers to engage in income smoothing. The following are some the of main
incentives: managers may manipulate numbers to reduce the cost of capital, to decrease
the overall risk of the company to minimize income tax, to satisfy the external demand of
existing shareholders, to increase their own remuneration, to avoid violating the debt
covenants or incurring political costs. Fudenberg and Tirole (1995) argue that managers
who are concerned about their job security will be more likely to engage in income
smoothing.
Depending on the incentives of the manager, earnings can be managed either upwards or
downwards. For example, if the manager’s compensation is based on earnings, he will be
motivated to increase earnings, so that he will receive a higher compensation. On the other
hand, if the manager’s objective is to minimize income tax, he will be more encouraged to
manage earnings downwards (Scholes et al. 1992)
Cahan et al. (2008) found evidence that managers in weak investor protection countries
are more likely to use income smoothing to gain private benefits, while managers in high
15 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
investor protection countries are more likely to use income smoothing to provide outsiders
with private information about expected earnings.
2.3 C ONCLUSION
Earnings management is a strategy used by the management of a company to deliberately
manipulate the company's earnings so that the figures match a pre-determined target.
There is however a difference between earnings management and fraud. Income
smoothing is just one of the many forms of earnings management. As mentioned, income
smoothing can be seen as a way for management to diminish the variability of income
numbers. Managers’ incentives can vary; they may engage in income smoothing to
enhance their own benefits or to communicate private information about future earnings to
outsiders. Depending on managers’ incentives, earnings can be managed either upwards or
downwards.
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3
A CCRUALS M ETHODOLOGY
In this chapter the accruals prediction models will be discussed. The models used to detect
earnings management can either be executed in a time-series3 or a cross-sectional setting4.
Both a time-series model and a cross-sectional model use a three-step approach to break
down total accruals into discretionary and non-discretionary accruals (Dechow et al.
1995). Prior research has used various accrual prediction models to detect earnings
management. The discretionary accruals can be estimated from these accrual models.
However, not all models are equally accurate (Dechow et al.1995, Kang and
Sivaramakrishnan 1995).
Over the years several researchers have attempted to model normal accruals. Ronen and
Sadan (1981), Healy (1985), DeAngelo (1988) and Dechow and Sloan (1991) made
significant contributions to the development of accrual models. But the Jones model is by
far the most important contribution to the accruals prediction models. In order to get a
good grasp of the accruals models, it is necessary to have some knowledge about accruals.
3.1
A CCRUALS
In order to identify earnings management in general most researchers have approached the
issue by detecting discretionary accruals. To fully understand how earnings management
is detected, one should have certain knowledge of accruals.
Accruals arise when there is a discrepancy between the timing of cash flows and the
timing of accounting recognition of the transaction (Ronen and Yaari 2008). Normally,
reported revenues must equal total cash inflows and total accruals must equal zero over a
firm’s lifetime. Accruals can be divided into three categories: accruals that result from
normal accruals (non-discretionary accruals), accruals that result from managed earnings
(discretionary accruals) and reversals. Non-discretionary accruals are accruals that arise
from transactions made in the current period that are normal for the firm given its
performance level and business strategy, industry conventions, macro-economic events
3
A time-series model involves a sequence of data, typically measured at successive times, at often uniform
time intervals. The objective of this type of model is to predict future events based on past events. Timeseries models enable researchers to determine whether reported earnings for a series of years would have
been more or less smooth if a particular variable had been excluded as a determinant of income (Dechow et
al. 1995).
4
Cross sectional models focus on the relationship between different variables at a certain point in time. In
contrast to time-series models these models relate to how variables affect each other at the same time.
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and other economic factors (Ronen and Yaari 2008). These are in contrast to discretionary
accruals, which arise from transactions made or accounting treatments chosen to manage
earnings (Ronen and Yaari 2008). There is also another group of accruals, known as
reversals, which are accruals originating from transactions made in previous periods. Most
empirical research ignores reversals, because they cannot be observed (Gillan 2006). A
problem with measuring earnings management is that a change in total accruals can be
caused by both a change in non-discretionary accruals and the accumulation of
discretionary accruals. Therefore it is of importance that researchers understand what can
be expected of normal accruals, so that the managed accruals can be identified.
3.2
T HE J ONES M ODEL
One of the most discussed models is the Jones model. This model was developed by Jones
while she was examining U.S. firms during import relief investigations by the U.S.
International Trade Commission. The Jones model divides the time series of a company’s
earnings into two periods, the estimation period and the event period. An assumption of
this model is that the firm does not manage its earnings before the event, so discretionary
accruals amount to zero in the estimation period.
Phase 1: in the estimation period the normal accruals are calculated by applying the
following equation:
𝑁𝐷𝐴𝑖𝑡
𝑇𝐴𝑖𝑡
1
𝛥𝑅𝐸𝑉𝑖𝑡
𝑃𝑃𝐸𝑖𝑡
=
= 𝛼̂𝑖 [
] + 𝛽̂1𝑖 [
] + 𝛽̂2𝑖 [
] + 𝜀𝑖𝑡
𝐴𝑖𝑡−1
𝐴𝑖𝑡−1
𝐴𝑖𝑡−1
𝐴𝑖𝑡−1
𝐴𝑖𝑡−1
(𝐸𝑞. 1)
Where
NDA =
normal accruals
TA
=
total accruals;
A
=
assets;
REV
=
revenues;
PPE
=
gross property, plant, and equipment;
ε
=
error term;
i
=
index for firm, i=1, 2… N.
T
=
index for the period (year) in the estimation period,
t
=
1, 2… T.
18 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Δ
=
change in a given variable.
The regression produces estimates of the coefficients 𝛼̂𝑖 , 𝛽̂1𝑖 , 𝛽̂2𝑖 . The PP&E (gross
property, plant and equipment) coefficient is negative, because PP&E determines the
depreciation expense. Most researchers agree that the coefficient on change in sales should
be positive (Ronen and Yaari, 2008, p. 405), because of the fact that there is a relationship
between changes in accounts receivable and accounts payable.
Phase 2: The parameters 𝛼̂𝑖 , 𝛽̂1𝑖 , 𝛽̂2𝑖 are put into Eq.1, in order to ultimately calculate the
discretionary accruals.
Total accruals can be derived from the financial data of the firm, TAip.
𝑇𝐴𝑖𝑝 = (𝛥𝑡𝑜𝑡𝑎𝑙 𝑐𝑢𝑟𝑟𝑒𝑛𝑡 𝑎𝑠𝑠𝑒𝑡𝑠 − 𝛥𝑐𝑎𝑠ℎ)
− (𝛥𝑡𝑜𝑡𝑎𝑙 𝑐𝑢𝑟𝑟𝑒𝑛𝑡 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 − 𝛥𝑠ℎ𝑜𝑟𝑡 𝑡𝑒𝑟𝑚 𝑑𝑒𝑏𝑡 − 𝛥𝑡𝑎𝑥𝑒𝑠 𝑝𝑎𝑦𝑎𝑏𝑙𝑒)
− 𝑑𝑒𝑝𝑟𝑒𝑐𝑖𝑎𝑡𝑖𝑜𝑛 𝑒𝑥𝑝𝑒𝑛𝑠𝑒 (𝐸𝑞. 2)
Normal accruals are estimated from the change in sales and PP&E, deflated by the
beginning-of-the-period assets, given the coefficients estimated in Eq. 1:
𝑇𝐴̂𝑖𝑝
𝛥𝑅𝐸𝑉𝑖𝑝
𝑃𝑃𝐸𝑖𝑝
1
= 𝛼̂𝑖 [
] + 𝛽1𝑖 [
] + 𝛽̂2𝑖 [
]
𝐴𝑖𝑝−1
𝐴𝑖𝑝−1
𝐴𝑖𝑝−1
𝐴𝑖𝑝−1
(𝐸𝑞. 3)
The abnormal accruals are fully equated with discretionary accruals. The discretionary
accruals can be calculated by deducting the normal accruals from the total accruals:
𝑢𝑖𝑝 = 𝑇𝐴𝑖𝑝 − 𝑇𝐴̂𝑖𝑝 (𝐸𝑞. 4)
Where
TA = Total accruals
TÂ = Normal accruals
19 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
3.2.1
C ONCERNS REGARDING THE J ONES M ODEL
A number of researchers have questioned the Jones model, among which Ronen and Yaari
(2008). They placed question marks on the assumption that firms do not engage in
earnings management in the estimation period. They wonder whether it is realistic to
assume that earnings have not been managed. In order to find out whether earnings
management during the estimation period taints the tests, they conducted simulations of
the Jones model assuming that firms manage depreciation during estimation periods. Their
results confirm that if earnings management occurs during the estimation period it will
indeed contaminate the tests. Their evidence, however, proves that the Jones model is
efficient in testing whether there is an existence of earnings management (Ronen and
Yaari, 2008, p. 410).
Some research questions the validity of equating abnormal accruals with discretionary
accruals. Healy stated that variations in accruals can be a result from changing business
conditions and change in strategy and operating decisions rather than from earnings
management (Healy 1996).
Another concern regards the sample size. A small sample increases the chance of a type II
error, which occurs when there’s an erroneous acceptance of the null hypothesis that firms
do not manage earnings (Ronen and Yaari, 2008, p. 415). Jones used a small sample of 23
firms in her study. According to Bartov et al. (2002) the median number of observations
for estimating normal accruals is 140 in a cross-sectional analysis compared to 8
observations in a time-series analysis.
Incomplete and contaminated data also pose as a threat. An error in the calculation of
total accruals can lead to an erroneous measurement of discretionary accruals. Researchers
cannot always prevent this from happening, since they rely on public data.
Several researchers have developed accruals models in order to try to improve the Jones
Model5. Many researchers make comparisons with tests using the Jones model and the
Modified Jones model (Kothari et al. 2005, Holthausen et al. 1995); from which I
concluded that it is an important alternative to the Jones model. Therefore, this paper will
only discuss the modified Jones model by Dechow, Sloan and Sweeney in the next
section.
5
Ronen and Yaari (2008) extensively discuss the modifications on the Jones model, which are the modified
Jones model of Dechow, Sloan and Sweeney (1995), the forward-looking model of Dechow, Richardson and
Tuna (2003), the performance adjusted models (Kang and Sivaramakrishnan (1995); Dechow and Dichev
(2002); Kothari, Leone and Wasley (2005)) and the synthesis model of Ye (2006).
20 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
3.3
T HE M ODIFIED J ONES M ODEL
In the previous section it was mentioned that a small sample increases the chance of a type
II error in the results of the Jones model. The focus, however, does not lay on this type of
error, but on the type I error. This is an erroneous rejection of the null hypothesis that the
firm does not manage earnings. Major concern lays with this type I error because it
incorrectly indicates that earrings have been managed (Ronen and Yaari, 2008, p. 433).
Because of these errors there was need for improvement of the Jones model. Dechow,
Sloan and Sweeney (1995) developed the modified Jones model. The difference between
the Jones model and the modified Jones model is the treatment of accounts receivable. In
the estimation period the same procedure is used as in the standard Jones model. The
difference between these two models becomes apparent in the second stage (the event
period) when estimating normal accruals. The normal accruals are computed by
multiplying the estimated coefficient of the change in sales by the change in cash sales
instead of the change in sales. So the change in accounts receivable is deducted from the
change in revenues.
The normal accruals in the event period are calculated by applying the following equation:
𝛥𝑅𝐸𝑉𝑖𝑝 − 𝛥𝐴𝑅𝑖𝑝
𝑃𝑃𝐸𝑖𝑝
1
𝑁𝐷𝐴𝑖𝑝 = 𝛼̂𝑖 [
] + 𝛽̂1𝑖 [
] + 𝛽̂2𝑖 [
]
𝐴𝑖𝑝−1
𝐴𝑖𝑝−1
𝐴𝑖𝑝−1
(𝐸𝑞. 5)
Where
𝑁𝐷𝐴𝑖𝑝 =
normal, non-discretionary accruals of firm i in period p;
𝐴𝑖𝑝−1 =
lagged assets of firm i;
REV =
revenues;
AR =
accounts receivable;
PPE =
PP&E;
Δ=
change;
𝛽̂1𝑖 =
the coefficient of total revenues in the estimation period. It is estimated
from the regression of accruals on Δ𝑅𝐸𝑉𝑖 and 𝑃𝑃𝐸𝑖 .
21 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Evidence provided by Ronen and Yaari proves that both models detect attempts to manage
earnings. The modified Jones model, however, is less susceptible to type II error than the
Jones model.
3.4
C ONCLUSION
This chapter discussed the several models available to researchers. Generally, the Jones
and Modified Jones model are the most common models used to measure earnings
management. These models are not used to measure income smoothing, however. The
Imhoff and Eckel model is mostly used to measure income smoothing, but there are
alternatives. These alternatives will not be further elaborated on in the remainder of this
thesis. The aforementioned model will be discussed in the following chapter.
22 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
4
O THER M ODELS
In the previous chapter the accruals models were discussed. There are however, many
models to measure earnings management without the help of accruals. This chapter will
focus on only one of such non-accruals models. This is the model developed by
Burgstahler and Dichev and will be the first one to be discussed. The second model to be
discussed is the Imhoff and Eckel model, which is a framework developed especially to
detect or identify income smoothing.
4.1
B URGSTAHLER AND D ICHEV
Several studies showed that managers have incentives to report systematic increases in
earnings and positive earnings (Barth et al. 1995). Burgstahler and Dichev provide
evidence that managers avoid reporting decreases in earnings and losses. With the help of
pooled cross-sectional distributions they showed that the frequencies of small earnings
decreases and small losses are abnormally low, while the frequencies of small earnings
increases and small positive earnings are abnormally high. This is evidence that earnings
are being managed. According to Burgstahler and Dichev (1997) about 8-12 % of firms
with small pre-managed earnings decreases manipulate earnings in order to report
earnings increases, and 30-44% of firms with small pre-managed losses manage earnings
to report positive earnings (Burgstahler and Dichev, 1997, p. 101). Earnings are
manipulated through both cash flow from operations and adjustments in working capital.
Earnings management to avoid earnings decreases is likely to be reflected in crosssectional distributions of earnings changes in the form of unusually low frequencies of
small earning decreases and unusually high frequencies of small earnings increases. The
same goes for small losses and small positive earnings. This is an alternative way to
determine whether earnings are being manipulated.
A discussion followed after Burgstahler and Dichev (1997) pointed out that the
discontinuities in earnings distributions around zero is evidence of earnings management.
Even though there are researchers who acknowledge the findings by Burgstahler and
Dichev (Jacob and Jorgensen 2007), there are also opponents. Durtschi and Easton (2004),
for instance, say that the discontinuities cannot be solely explained by earnings
management. They also provide evidence that there are other factors contributing to the
discontinuities, such as scaling and sample selection (Durtschi and Easton 2004, 2009).
23 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Dechow, Richardson and Tuna (2003) and Beaver, McNichols and Nelson (2003) mention
that discontinuity in earnings distribution may be driven by other factors, such as
exchange listing requirement and different tax treatment of profits and losses.
4.2
T HE I MHOFF AND E CKEL M ODEL
The great majority of researchers examine ex post data in order to identify income
smoothing behaviour. Those researchers examining ex post data have assumed the same
conceptual framework; if the variability of normalized earnings generated by a specified
expectancy model is lessened by the inclusion of a potential smoothing variable utilized
by the firm, then the firm has 'smoothed income' (Eckel 1981).
Eckel (1981) developed a conceptual framework in which he suggests that firms can
choose accounting variables in order to minimize the variability of their net income. The
study by Eckel was based on earlier work by Imhoff (1977). Imhoff (1977) was the first
one that suggested that income smoothing could be measured by comparing the variance
of sales to the variance of income. The type of income smoothing behaviour that Eckel is
attempting to identify is artificial smoothing. Because of the fact that real smoothing
represents an underlying economic reality it is not relevant to his study.
In an attempt to distinguish firms that smooth their income artificially from real smoothing
firms, he wanted to create a measure that can be used to do empirical research on this
topic. He stated that a firm is classified as an income smoother when the coefficient of
variation for the one-period change in sales in is greater than the coefficient of variation
for the one-period change in income; this is the first part of the testing procedure. In
symbols:
𝐶𝑉𝛥𝑆 > 𝐶𝑉𝛥𝐼 (𝐸𝑞. 6)
Where:
𝐶𝑉𝛥𝑆 =
√𝑉𝑎𝑟𝑖𝑎𝑛𝑐𝑒 𝛥𝑆
𝑀𝑒𝑎𝑛 𝑉𝑎𝑙𝑢𝑒𝛥𝑆
(𝐸𝑞. 7)
24 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
𝐶𝑉𝛥𝐼 =
√𝑉𝑎𝑟𝑖𝑎𝑛𝑐𝑒 𝛥𝐼
𝑀𝑒𝑎𝑛 𝑉𝑎𝑙𝑢𝑒 𝛥𝑆
(𝐸𝑞. 8)
If the variance of ∆S throughout the years in relation to the mean ∆S of the industry is
greater than the variance of ∆I throughout the years in relation to the mean ∆I of the
industry, a firm can be identified as an income smoother.
The second part of the dual testing procedure then is to determine whether or not the
𝐶𝑉
firm’s 𝐶𝑉 𝛥𝐼 is significantly less than the industry average. If this indeed is the case, the
𝛥𝑆
firm would be identified as an income smoother (Eckel 1981). I will not elaborate on the
model of Eckel, because it is not relevant for my further research.
4.3
C ONCLUSION
Burgstahler and Dichev argued that by looking at pooled cross-sectional distributions they
could determine whether earnings were being manipulated or not. Burgstahler and
Dichev’s method however, was considered highly controversial, because several
researchers proved that other factors contributed to the discontinuities.
Before Eckel a number of researchers had conducted studies; however, the conceptual
framework for most of these studies tended to be similar with differences limited to the
sample of firms, the expectancy model used, the time-frame studied, or the soothing
objects and smoothing variables considered (Eckel 1981). Therefore he developed his own
model which is widely used in the field of detecting income smoothing. These two
models, however, will not be discussed in the remainder of this thesis, because I will be
using the measurements developed by Leuz et al. (2003). The objective is to determine
whether income smoothing decreases in high investor protection countries while using the
anti-self-dealing index. Also, I will be looking at a pre-IFRS and post-IFRS period.
25 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
5
C ORPORATE G OVERNANCE
According to Gillan and Starks (1998), corporate governance can be defined as the system
of laws, rules and factors that control the operations of a company. Corporate governance
can be divided into two distinct groups, internal and external corporate governance (Gillan
2006). Management, who is required to act in the interests of stakeholders, and the board
of directors are the basic parts of internal governance. External corporate governance is
concerned with the company’s need to raise capital; shareholders and debt holders provide
firms with capital. Laws and regulations as well as markets are elements of external
governance that are of most interest to researchers (Gillan 2006). The distinction between
internal and external governance defines the fact that there is a separation in publicly
traded firms between the individuals that manage the firm’s capital and the ones that
provide capital. Gillan (2006) divides external corporate governance further into five
groups:
i.
Law/Regulation: federal law, self regulatory organizations:
The impact of law on shareholder wealth; the impact of the SOX implementation
on governance and wealth
ii.
Markets (1): capital markets, the market for corporate control, labor markets,
product markets
Capital markets: Gillan discusses the importance of ownership structure to
corporate governance. For example, concentrated institutional ownership
moderates executive compensation (Hartzell and Starks 2003, stated in Gillan
2006).
Market for corporate control: Looks at the association between aspects of
governance and the market for corporate control. For example, CEOs of firms that
are acquired receive compensation in line with what they would have eraned had
they remained in the CEO position (Hartzell et al 2004, stated in Gillan 2006).
Labor markets: This particular group focuses on CEOs, board members and
members of senior executive teams. For instance, both managers and board
members’ behavior is regulated by labor market forces and reputation concerns.
Good performance can lead to better career opportunities (Fama and Jensen 1983,
stated in Gillan 2006).
26 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Product markets: This category looks at product market competition and its
relation to different aspects of corporate governance, including compensation
structure and CEO turnover. E.g. researchers found that the frequency of CEO
turnover is greater in more competitive industries (DeFond and Park 1999, stated
in Gillan 2006).
iii.
Markets (2) Capital Market Information:
This group focuses on the connection between capital market information
providers and corporate governance. For example, certain parties such as securities
analysts provide the market with information about firms.
iv.
Markets (3) Accounting, Financial and Legal services: services from parties
external to the firm:
The focus of this group lies on the link between the market for services and
corporate governance. A good example is the relationship between firms and their
external auditor.
v.
Private sources of External Oversight: media and external lawsuits:
The media and external lawsuits are the two private sources of external oversight.
The media takes in a primary role in reporting on firms’ corporate behavior. This
media oversight urges managers and directors to employ “socially correct
behavior”.
The relationship between earnings management, especially income smoothing, and
corporate governance is often the result of the principal-agent relationship between owners
and managers (Ronen and Yaari 2008). Managers are hired to act in the interests of the
owners; this however is not always how it turns out in reality. Managers tend to act in their
own interest, at the expense of the other stakeholders. Therefore, owners and regulators
are challenged to implement a system that obliges managers to act in the interests of all
stakeholders and make the “right decisions”. In this thesis the focus will lie on laws and
regulations which are in place to protect investors against the selfish behaviour of
managers and other controlling insiders.
27 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
5.1
I NVESTOR P ROTECTION
Investor protection refers to how well investors are protected by law from expropriation
by managers and controlling shareholders of firms (Cahan et al. 2008). Previous research
has established that earnings smoothing is less prevalent in strong investor-protection
countries (Leuz et al. 2003, Boonlert-U-Thai et al. 2006). A country’s laws and
regulations provide the underlying framework upon which its financial system functions.
The legal system establishes clear ownership rights, contract laws, commercial codes, and
bankruptcy procedures. Uncertainty is also reduced through effective enforcement. Such a
legal environment minimizes information asymmetry and investor uncertainty. Because
the legal and regulatory environment largely determines the reliability of publiclyavailable information, information asymmetry will be lower for firms operating in stronger
investor protection environments (Brockman and Chung 2008). Rules can come from
different sources such as company, security, bankruptcy, takeover and compensation laws.
When investors finance a firm, they face the risk that they will not see returns on their
investments because controlling shareholders or managers expropriate them. This is one of
the reasons why investors should be protected. Examples of actions they should be
shielded against include insiders who steal profits; insiders who sell the assets, the output
or additional securities they own in the firm to another firm they own, below market
prices; overpaying executives;
insiders who install unqualified family members in
managerial positions (La Porta et al. 2000). It comes down to the fact that outside
investors should be protected against insiders who rather benefit themselves than return
the money to investors. Investors obtain certain rights or powers that are protected through
laws and regulations. Voting for directors, receiving dividends on pro-rata terms,
participation in shareholders meetings are some of the protected shareholders rights.
Several researchers have studied corporate governance and its relationship to the legal
protections afforded shareholders and creditors. The introduction of the Sarbanes-Oxley
Act demonstrates that law and regulation do have influences on corporate governance
(Linck et al 2005, Cohen et al. 2005). To a large extent shareholders and creditors finance
firms because their rights are protected by the law. Laws are necessary to shield investors
from insiders’ selfish behaviour, but enforcement of laws is equally important as their
contents. India and Pakistan are examples of countries where the investor protection laws
are strong, but the de facto strength is weak. Without a good functioning legal system
which protects investors, external finance would not work well (La Porta et al. 1997).
28 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
In most countries laws and regulations are enforced in part by market regulators, in part by
courts and in part by market participants. The extent, to which these laws protect investors
however, can vary between countries because of differences in corporate law and the
enforcement of the law (La Porta et al. 1998). Prior research documents greater financial
transparency in countries with strong investor protection (Bhattacharya et al. 2003).
The earlier discussed index by La Porta et al. (1998) is not the only index available to
researchers. Other indexes have been developed over the years.
5.1.1
A NTI - SELF - DEALING INDEX
Djankov et al. (2007) developed the anti-self-dealing index, which relies on the same basic
dimensions of corporate law, but defines them with more precision. This index is
calculated for 72 countries based on legal rules prevailing in 2003. These 72 countries are
classified by their legal origin. Both the original and the revised anti-director rights indices
summarize the protection of minority shareholders in the corporate decision-making
process, including the right to vote. The index covers the following six areas: (1) vote by
mail; (2) obstacles to the actual exercise of the right to vote (i.e., the requirement that
shares be deposited before the shareholders’ meeting); (3) minority representation on the
board of directors through cumulative voting or proportional representation; (4) an
oppressed minority mechanism to seek redress in case of expropriation; (5) preemptive
rights to subscribe to new securities issued by the company; and (6) the right to call a
special shareholder meeting (Djankov et al. 2007).
Djankov et al. (2007) examine several areas of law relevant to the transaction and
summarize them with two indices: an index of public enforcement and an index of the
private control of self-dealing. The latter index can be divided into two components; an
index of ex ante private control of self-dealing and an index of ex post private control of
self-dealing.
According to Djankov et al. (2007) the first major area that the law can seek to regulate is
the approval process. The law can also seek to regulate the approval process by mandating
extensive disclosure by the company and the related party. Data on approval requirements
and immediate disclosures is summarized through an ex ante private control of selfdealing.
29 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Djankov et al. (2007) consider the ease with which minority shareholders can prove
wrongdoing to be the second major area that the law can regulate. The disclosure
requirements after the transaction is approved and the ease of proving wrongdoing are
combined into an index of ex post private control of self-dealing.
The anti-self-dealing index is then created by averaging the indices of ex ante and ex post
private control of self-dealing.
5.2
C ONCLUSION
Investor protection is a form of external corporate governance. The objective is to protect
investors from expropriation by controlling insiders. These insiders tend to put their own
interests before those of the shareholders. In order to prevent this from happening
legislators need to put mechanisms in place which will keep managers from behaving
opportunistically. Laws regarding investor protection are not necessarily the same in
different countries. Djankov et al. (2007) acknowledged these differences and developed
investor protection indices for 72 countries. Previous work by La Porta et al. (2000) is
considered to be outdated and flawed. Therefore this research will use the anti-self-dealing
index.
30 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
6
I NTRODUCTION OF IFRS
With the globalization of financial markets in sight, regulators came up with the notion
that adopting common standards for financial reporting would lead to harmonization of
corporate accounting practices. The International Financial Reporting Standards (from
here on IFRS), which were formerly known as International Accounting Standards (IAS),
were chosen as the common language for financial reporting by Europe and several other
countries. Many countries have agreed to require or allow adoption of IFRS. Japan, for
instance, will converge to IFRS in 2011. Brazil, Canada, China and India have all set
formal timelines by which they wish to converge to IFRS (Jeanjean and Stolowy 2008).
Table 2 gives an overview of the IFRS adopters. As of January 1st, 2005 all firms listed in
the European Union are required to prepare their consolidated financial statements
conform the International Financial Reporting Standards.
One of the aspects that welcomed IFRS is the fact that IFRS are the product of one
independent, private-sector body, and have arisen in response to demand, from capital
markets and not as a result of specific political initiatives by governments (Whittington
2005).
IFRS are more “principles-based” than “rules-based”. Principles-based systems issue
generic accounting standards. This means that not every controversial issue is discussed
but ambiguity about major processes as record keeping and measurement is kept
(Carmona and Trombetta 2008). Nelson (2003) stated that “principles-based” refers to
fundamental understandings that inform transactions and economic events. This is in clear
contrast to “rules-based” standards which include specific criteria, examples, scopes,
restrictions, exceptions etc. According to Carmona and Trombetta (2008) the global
acceptance of IFRS resulted from its openness and flexibility. Both of which are
fundamental in accommodating diverse institutional settings and traditions (common-law
and civil law) under shared standards.
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6.1
IFRS IN E UROPE
In contrast to current standards, the original International Accounting Standards were
descriptive and provided several alternative treatments (Van Tendeloo en Vanstraelen
2005). As a result comparison between countries was made difficult. For this reason and
the additional flexibility of IAS, many criticized these standards. In cooperation with the
international Organization of Securities Commission (IOSCO) the IASC made substantial
revisions to the IAS, which are nowadays widely used (Carmona and Trombetta 2008).
The European Parliament issued a regulation (1606/2002/EC) which requires all EU listed
firms to prepare consolidated financial statements based on IFRS by 2005. However, it
was allowed to prepare the subsidiary financial statements in accordance with IFRS before
the mandatory introduction in 2005. In some countries, among which Germany, Austria,
Belgium, France, Italy and Switzerland, it was possible for firms to adopt IFRS before the
mandatory introduction.
IAS (International Accounting Standards), which are the predecessors of IFRS, were
issued by the International Accounting Standards Committee (IASC) during the period
1973 until 2000. The successor body to the IASC, The International Accounting Standards
Board (IASB), issued International Financial Reporting Standards, which include
standards issued not only by the IASB but also by the IASC, some of which have been
amended by the predecessor 6 . The board of IASC formed the Standing Interpretations
Committee (SIC) in 1997. It was founded with the objective of developing interpretations
of International Accounting Standards (IASs) to be applied where the standards are silent
or unclear. The International Financial Reporting Interpretations Committee replaced the
former Standing Interpretations Committee (SIC) in March 2002. IFRS enclose all
standards and interpretations.
Countries with diverse national cultures equally applied the IFRS standards. In Europe
countries with rules-based systems (Germany) as well as principles-based systems (the
UK) have adopted IFRS. At the same time, a common-law country like the UK and codelaw countries like Belgium and the Netherlands have also adopted these standards. This
global acceptance of IFRS results from its principles-based nature as well as its openness
and flexibility.
6
The IASB recognizes standards issued by the IASC.
32 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
6.2
P ROPONENTS VS . O PPONENTS
Academics and practitioners have argued exhaustively about the actual benefits of
mandatory adoption of new standards across countries. There are arguments which are in
favour of IFRS adoption and back up the idea that IFRS would improve accounting
quality. But there are also arguments to the contrary.
As mentioned earlier, companies in the European Union are obliged to prepare their
consolidated financial statements in accordance with IFRS starting January 1st 2005. The
European Commission had the following arguments for mandating one set of accounting
rules across the entire EU (European Union 2002):
1. The establishment of a single set of internationally accepted high quality financial
reporting standards (compared to the many different local standard in force). The
key target of this harmonization is firms listed on financial markets.
2. To contribute “to the efficient and cost-effective functioning of the capital market”.
The Commission’s goal is to protect investors, by maintaining (or increasing)
confidence in the financial markets, which would then reduce the cost of capital for
firms in the EU.
3. To increase the overall global competitiveness of firms within the EU and thereby
improve the EU economy.
Proponents of adopting IFRS argued that common standards will improve the
comparability of financial statements of firms across different countries. This would result
in more efficient competition between international funds. The proponents however, are
basing these benefits on the assumption that mandatory use of IFRS increases
transparency and reporting quality. Several studies show that this is not necessarily the
case. Callao et al. (2007) investigated whether IFRS increased the usefulness of financial
statement information in Spain. Their findings show that local comparability of financial
statements has diminished after the adoption of IFRS. Their results also showed that the
relevance of financial reporting did not improve after adopting IFRS. Even though there’s
no significant short-term improvement, Callao et al. acknowledge that improved value
may be gained in the medium to long-term. Ewert and Wagenhofer’s (2005) research
33 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
shows that tightened accounting standards increase the quality of earnings, but it also
increases real and accounting earnings management. Panaanen and Lin (2009) found
evidence which indicates that accounting quality has not improved but worsened after the
mandatory adoption of IFRS in Europe.
Research by Hail and Leuz (2006) showed that the documented benefits of first-time
voluntary adopters were short-lived; it is possible that these benefits can be enjoyed for a
short period of time for first-time mandatory adopters as well.
Proponents who argue that IFRS adoption will increase transparency say so because IFRS
reduce the amount of reporting discretion relative to many local GAAP and, in particular,
push firms to improve their financial reporting (Jeanjean and Stolowy 2008). As
mentioned above, Ewert and Wagenhofer 2005 found evidence to support this argument.
Daske et al. (2008) found evidence that market liquidity increases around the time of the
introduction of IFRS and that firms’ cost of capital decreases.
They also discovered that only in countries where firms have incentives to be transparent
and where there is a strong legal enforcement, the capital-market benefits occur.
Reducing the reporting discretion however, can restrain firms from making information
public through their financial statements (Watts and Zimmerman 1986). Another argument
of opponents is that a single set of standards might not represent the different national
institutional settings and traditions. This is the main reason why different accounting
standards emanated in the first place.
Another frequently used argument by proponents is the increased comparability of
financial statements after adoption of IFRS. This assumption is based on the notion that
IFRS reporting will decrease costs for investors to compare firms across markets and
countries (Armstrong et al. 2006). So, common use of IFRS would enable investors to
differentiate between lower and higher quality firms. The ease of comparison persuades
managers to reduce earnings management. Having common standards could facilitate
cross-border investment and the integration of capital markets (Jeanjean and Stolowy
2008). As a result of this, firms’ investor base could be expanded (Merton 1987).
Opponents are doubtful about the notion that IFRS alone is sufficient in improving
informativeness or comparability. As long as firms have different reporting incentives,
reporting behaviour is expected to differ (Leuz and Oberholzer-Gee 2006, Ball et al.
34 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
2003). The application of accounting standards involves considerable judgement and the
use of private information. Consequently, IFRS provide firms with substantial discretion,
just like any other set of accounting standards. To what extent managers make use of this
discretion depends on firm-specific characteristics (reporting incentives and operating
characteristics), and countries’ legal institutions. Countries’ legal institutions take in a
primary role in explaining accounting quality after IFRS adoption. Strict enforcement
regimes and institutional structures provide strong incentives for high-quality financial
reports after the introduction of IFRS reporting (Jeanjean and Stolowy 2008).
6.3
C OMMON - LAW VS . C ODE - LAW
Historically, legal systems, combined with other political and economical differences,
created much diversity within accounting systems. As a result meaningful comparison of
financial reports across borders was difficult. Europe is the origin of many legal systems:
English, German, French and Scandinavian, and thus, prior to harmonization, there were
extremely diverse, country-specific accounting systems (Soderstrom and Sun, 2007).
Rules differ systematically by legal origin, which can be English, French, German, or
Scandinavian. English law is common-law, made by judges and subsequently incorporated
into legislature. French, German, and Scandinavian laws, however, are part of the scholar
and legislator-made civil-law tradition (La Porta et al. 1997). Legal rules from the several
traditions differ in content as well as in the history of their adoption. In the protection
against expropriation by insiders, common-law countries protect both shareholders and
creditors the most, French civil-law countries the least, and German civil-law and
Scandinavian civil-law countries somewhere in the middle.
Common-law arises from individual action in the private sector (Ball et al. 2000). Legal
rules in the common-law system are usually made by judges, based on precedents and
inspired by general principles such as fairness (La Porta et al. 2002, p.1158; La Porta et al.
2000, p.9). Judges are expected to rule on new situations by applying these general
principles even when specific conduct has not yet been described or prohibited in the
statutes. Accounting standards in common-law countries are mostly set by private
organizations such as the FASB in the United States. The purpose of these standard setters
is to satisfy investor needs for information (Soderstrom and Sun 2007).
35 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
While common-law systems allow for individual judgement, laws in code-law systems are
made by legislatures; it allows governments to control setting and interpretation of laws.
Accounting standards in these countries are a part of commercial law instituted by courts
and are therefore primarily influenced by governmental priorities. In code-law countries
judges are not supposed to go beyond the statutes and apply fairness opinions (La Porta et
al. 2002).
So when a corporate insider finds a loophole in the statutes which allows him to
expropriate outside investors can do so without fear of an adverse judicial ruling.
Common-law countries have the strongest protection of outside investors, which includes
shareholders as well as creditors (La Porta et al. 2000). Previous research provides
evidence that the magnitude of earnings management is on average higher in code-law
countries with low investor protection rights, compared to common-law countries with
high investor protection rights (Leuz et al., 2003).
6.4
P REVIOUS S TUDIES
B ARTH , L ANDSMAN AND L ANG (2008)
These researchers examined the accounting quality before and after the introduction of
IFRS for a sample of 327 firms that voluntarily adopted IAS between 1994 and 2003.
According to Barth et al. (2008) improvement of accounting quality is possible if the
standard setters succeed in limiting management’s opportunistic discretion in determining
accounting amounts by removing allowable accounting alternatives. More stringent
enforcement could also lead to an increase of accounting quality. They do acknowledge
however, that there are two limitations to their assumption that financial statements based
on IAS are of higher quality than those based on domestic standards. The first one is that
the domestic standards may be of higher quality than IAS. Secondly, weak enforcement of
standards could lead to lower quality. Their evidence showed that firms which adopted
IAS engaged less in earnings management compared to the pre-adoption period. They also
found evidence showing more timely loss recognition and more value relevance of
accounting amounts. Barth et al. (2008) suggested that their findings could party be
attributed to differences in firms’ incentives as well as the varying economic environments
of the sample firms.
36 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Barth et al. (2008) included in their sample firms which voluntarily adopted IFRS (this
was possible in some countries such as Germany). Therefore their study suffers from a
sample selection bias, because only firms which saw an advantage in the adoption of IFRS
would actually adopt it voluntarily. Van Tendeloo and Vanstraelen (2005) investigated
whether firms in Germany that voluntary adopted IFRS showed lower earnings
management. Their results indicated that there is no difference in earnings management
behaviour of IFRS-adopters and companies reporting under German GAAP. This research,
like the study by Barth et al. (2008), suffers from a sample bias.
J EANJEAN AND S TOLOWY (2008)
Contrary to the earlier discussed study by Barth et al. (2008), Jeanjean and Stolowy (2008)
did research on the effect of the mandatory introduction of IFRS standards on accounting
quality. They specifically looked at earnings management. These researchers employed
the Burgstahler and Dichev (1997) methodology. So irregularities in distributions will be
an indication of earnings management. This is one of the caveats of their paper, but
according to them using another model was not an option because adoption of IFRS was at
the moment of their research too recent to provide enough data for researchers. Australia,
France and the UK were included in their study, because all three countries first adopted
IFRS in 2005. Australia however is a non-European common-law country, whereas France
is a code-law European country and the UK a common-law European country. Their
evidence showed that after the transition to IFRS, the pervasiveness of earnings
management increased in France (code-law) and remained stable in the UK (common-law)
and Australia (common-law). Concluding, the evidence shows that sharing rules is not a
sufficient condition to create a common reporting language. Management incentives and
national institutional factors play a key role in setting financial reporting standards. This
conclusion overlaps with the argument by Ball et al. (2003) that the adoption of a common
set of standards is a necessary condition for high quality information, but not necessarily a
sufficient one.
6.5
S UMMARY
This chapter discussed the adoption of IFRS in order to harmonize the global accounting
practices. More than 100 countries have agreed to either allow or require companies to
37 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
prepare their financial statements in accordance with IFRS. Even though many
practitioners and regulators expect that the adoption of these standards will lead to
increased comparability and transparency of financial statements, there are experts who
are doubtful. Several studies have attempted to research the effect, but there is no
unanimous outcome. There are however expectations that in the long-run the effects will
be more valuable.
From the results of previous studies one can conclude that in order to conduct proper
research on the link between IFRS adoption and earnings management the legal tradition
of countries must be taken into account. Jeanjean and Stolowy (2008) detected an increase
in earnings management in France, a code-law country. La Porta et al. (1998), who were
the first to conduct research on the legal system’s effect on a country’s financial system,
found that common-law countries have better accounting systems and better protection of
investors than code-law countries. Mandatory or voluntary adoption can also influence the
outcome of IFRS adoption. Barth et al. (2008) did research on voluntary adoption of IFRS
in Germany and found that earnings management decreased. This is in clear contrast to the
results from Jeanjean and Stolowy, who conducted research on the mandatory adoption of
IFRS. The difference between the results can be caused by firms’ incentives; it is likely
that only firms which saw an advantage in the IFRS adopted it voluntarily (Leuz and
Verrechia 2000).
38 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
7
S TUDIES ON E ARNINGS M ANAGEMENT AND I NVESTOR P ROTECTION
7.1
E ARNINGS M ANAGEMENT AND I NVESTOR P ROTECTION
Research identified investor protection as a key factor in earnings management activities
(La Porta et al. 2000). Studies showed that earnings management will decrease in a strong
investor protection environment, because strong protection constrains insiders’ private
control benefits. Also, managers in weak investor protection countries will use earnings
management for more opportunistic motives (Cahan et al. 2008). This is in contrast to
managers in strong investor protection countries, who want to communicate private
information about future earnings to outsiders (Leuz et al. 2003, Cahan et al. 2008).
Company insiders can use their control over the firm to gain personal benefits at the
expense of stakeholders (Watts and Zimmerman 1990). They can choose accounting
methods that are beneficial to their interests. Since insiders have this advantage over
outsiders, they need to mask/cover these private control benefits, because if detected
outsiders will take disciplinary actions (Leuz et al. 2003). This is an incentive for
managers to mislead stakeholders through earnings management.
L EUZ , N ANDA AND W YSOCKI (2003)
A number of studies have conducted research on the relationship between earnings
management, specifically income smoothing, and investor protection. Leuz, Nanda and
Wysocki (2003) were among the first ones to present evidence that the level of outside
investor protection determines the quality of financial information reported to outsiders.
They examined the differences in earnings management in 31 countries. Prior to their
research there were studies that identified investor protection as a key factor in corporate
policy choices (La Porta et al. 2000). For this reason they decided to test the influence of
investor protection on earnings management. They reasoned that insiders’ private control
benefits can be limited by strong and well-enforced outsider rights. Thus insiders will be
less motivated to manage earnings. Managers have incentives to manage earnings so that
their private control benefits will be concealed from the outside world and the true
performance of the company will not be revealed. In their study the researchers suggest
that the occurrence of earnings management is higher in countries with weak legal
protection of outsiders, than in countries with strong outsider rights protection. In order to
investigate to which extent this proposition is accurate, they performed an analysis and
39 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
created four proxies that capture the extent to which insiders use their accounting
discretion to conceal their firm’s performance. The following proxies were used:
i.
The country’s median ratio of firm-level standard deviation of operating income
and operating cash flow
ii.
The country’s Spearman correlation between change in accruals and change in
operating cash flow
iii.
The country’s median ratio of absolute value of accruals to absolute value of
operating cash flow
iv.
The country’s ratio of the number of small profits to small losses where small is
less than 1 percent of lagged total assets
Since earnings management manifests itself in different forms, Leuz et al. (2003) designed
these four proxies to capture various earnings management practices, including income
smoothing. The first two proxies (i and ii) measure earnings smoothing and the latter two
(iii and iv) measure earnings discretion. An aggregate earnings management score was
constructed to mitigate potential measurement error; the four earnings management
measures were ranked and aggregated. This score is the average of a country’s earnings
smoothing score and earnings discretion score.
In order to provide evidence on the patterns in earnings management among countries, the
31 countries were classified in three categories: 1. Outsider economies with large stock
markets, dispersed ownership, strong investor rights, and strong legal enforcement; 2.
Insider economies with less-developed stock markets, concentrated ownership, weak
investor rights, but strong legal enforcement and, 3. Insider economies with weak legal
enforcement.
Leuz et al. (2003) used the institutional variables from La Porta et al. (1997, 1998), as
their primary measure of investor protection, among which are the following: legal origin,
legal tradition, outside investor rights, legal enforcement, importance of the equity market,
ownership concentration and the disclosure index. This index measures the inclusion or
omission of 90 accounting items in firms’ 1990 annual reports, and hence captures firms’
disclosure policies at the country level. Now that the general set-up and methodology is
explained, the findings of this study will be presented.
Their empirical results reveal that investor protection plays an important role in
international differences in corporate earnings management. The evidence suggest that
40 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
firms in countries with developed equity markets, dispersed ownership structures, strong
investor rights, and legal enforcement engage in less earnings management. So, the
pervasiveness of earnings management is increasing in private control benefits and
decreasing in outside investor protection. The researchers argue that managers have
incentives to manage earnings and that these incentives will vary with the level of investor
protection in the country. Leuz et al. (2003), however, have one concern; the influence of
other institutional variables, which are correlated with investor protection, on earnings
management. One specific factor that is a cause for concern is the influence of accounting
rules and firms’ ownership structures on earnings management. They admit that these
institutional factors are complementary and therefore difficult to isolate.
C AHAN , L IU AND S UN (2008)
The objective of this study is to investigate whether investor protection influences the
efficient communication of private information through income smoothing. They posit
that income smoothing increases earnings informativeness more for firms in countries
with strong investor protection than for firms in countries with weak investor protection.
Earnings informativeness refers to the informativeness of current and past earnings about
future earnings and cash flows (Tucker and Zarowin 2005). As Leuz et al. (2003) proved,
the level of earnings management varies between high and low investor protection
countries. Cahan et al. (2008) examine whether the incentives for earnings management
varies between high and low investor protection countries. Leuz et al. (2003) examined the
level of earnings management in different countries and argued that managers have
incentives to engage in earnings management. Cahan et al. (2008) coincide with this
statement and expand the underlying motive for earnings management. They are of the
opinion that there are two interpretations regarding the underlying motive for earnings
management; opportunism is the primary motivation in both low and high investor
protection countries or earnings management is motivated by opportunism in low investor
protection countries, but is motivated by the efficient communication of private
information in high investor protection countries. In order to investigate this view they
examined the informativeness of income smoothing.
Since this study focuses on income smoothing alone and not earnings management as a
whole, Cahan et al. (2008) only used the second proxy defined by Leuz et al. (2003). They
calculated the Spearman correlation between changes in total accounting accruals and
41 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
changes in operating cash flows and used the negative correlation as a measure of income
smoothing. In order to measure investor protection they only used the legal enforcement
index from La Porta et al. (1998), contrary to Leuz et al. (2003) who used all 9 variables
from La Porta et al. (1998). The legal enforcement index is measured as the mean score
across three legal variables used in La Porta et al.: (1) the efficiency of the judicial
system, (2) an assessment of rule of law and (3) the corruption index.
By examining data from 44 countries, they came to the same conclusion as Leuz et al.
(2003); the incidence of earnings management increases (decreases) in countries with
weak (strong) investor protection. They found that the underlying motive for earnings
management indeed differs between high and low investor protection countries: managers
in weak investor protection countries are more likely to use income smoothing for
opportunistic reasons while managers in strong investor protection countries are more
likely to use income smoothing to convey their private information about future earnings.
They also found evidence to substantiate their hypothesis that income smoothing improves
earnings informativeness more greatly for firms in countries with strong investor
protection than in countries with weak investor protection.
W RIGHT , S HAW AND G UAN (2006)
The objective of this study is to extend the work by Leuz et al. (2003) and to investigate
whether Leuz et al.’s country clusters are overly broad. In contrast to the other studies
discussed in this chapter, Wright, Shaw and Guan use the modified Jones model to detect
earnings management. The U.K and the U.S. share similar legal environments, large stock
markets, dispersed corporate ownership and strong investor rights (La Porta et al. 1997).
So, they should be categorized in the same country cluster. According to theories provided
by Leuz et al. (2003) earnings management should be similar and infrequent in both
countries and their evidence supported this theory. However, this study by Wright, Shaw
and Guan shows that their theory does not hold up. The evidence indicates that managers
of MBO (management buy-outs) firms in the U.S. managed earnings to a greater extent
than their colleagues in the U.K. Even though there are numerous similarities between the
U.K. and the U.S., there are various cultural and organizational differences between these
two countries as well (Hofstede 2001).
42 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
There is one major limitation to Wright et al. study; they limited their sample to one
specific group, management buy-outs (MBO’s). The researchers acknowledge that there is
a possibility that earnings management in the U.K. would be different in other settings.
N ABAR AND B OONLERT -U-T HAI (2007)
The two first discussed studies focused on the legal origin differences and corporate
governance in earnings management in an international context. Nabar and Boonlert-UThai investigated the role of both investor protection and national culture in explaining
cross-national differences in earnings management. They examined if and how culture
influences managers’ earnings management behavior. Leuz et al. (2003) admitted that
other factors may also contribute to earnings management, Nabar and Boonler-U-Thai
proposed and substantiated that national culture is one of these other factors.
In their analysis they used the aggregate earnings management score developed by Leuz et
al. (2003) as the proxy for earnings management. Their measurement for culture consists
of four cultural variables developed by Hofstede (1980, 2001).
The evidence from their analysis shows that earnings management is influenced by both
investor protection and culture. Their evidence confirms the findings from Leuz et al.
(2003); earnings management is low in countries with high outside investor protection.
Earnings management is high in high uncertainty-avoidance (one of the Hofstede proxies)
countries and low in English-speaking countries. Also, their evidence proved that earnings
management is influenced by both investor protection and culture. National culture affects
managers’ earnings discretion but not earnings smoothing.
To measure investor protection, two institutional variables defined by La Porta et al.
(1998) were used; outside investor rights and legal enforcement. The aggregate earning
management scores in this study differ slightly from the ones reported by Leuz et al.
(2003), because this sample consists of 30 countries whereas the sample used by Leuz et
al. consisted of 31 countries. Both studies, however, yield the same empirical results.
7.2
C ONCLUSION
Leuz et al. (2003) argued that managers have incentives to manage earnings to obscure the
firm’s true performance in order to hide their private control benefits from outsiders.
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Investor protection reduces management’s ability to gain private benefits at the expense of
outside shareholders; therefore the level of investor protection in a country will influence
the incentives of managers. All four studies provided conclusive evidence that in countries
with a strong investor protection environment, the incidence of earnings management is
lower than in countries with weak investor protection. Cahan et al. (2008) argued and
proved that opportunism is not always the reason for engaging in earnings management;
their findings indicate that earnings management can be motivated by the efficient
communication of private information in high investor protection countries (Cahan et al.
2008). Nabar et al. (2007) proved that there are indeed other factors contributing to
earnings management, such as culture.
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8
H YPOTHESES AND R ESEARCH D ESIGN
This chapter will explain the research design in detail. The objective of the empirical
research is to determine whether firms in high investor protection countries engage less in
income smoothing. In the previous chapters several studies were discussed, which focused
on the relationship between investor protection and earnings management. These studies
however, focused on all forms of earnings management whereas I will only measure the
level of income smoothing. In most of these studies the La Porta index was used as a
measurement for investor protection, this index however is based on legislation dating
from 1993, which is outdated. Hence, my research. The following research question lies at
the base of this thesis:
“Does a strong investor protection environment reduce the incidence of income smoothing
in countries?”
I expect the results of my empirical research to show that income smoothing indeed
decreases due to a strong investor protection environment, because previous research
indicated that investor protection is an important factor in explaining income smoothing.
This chapter is divided in several sections, some with subsections. In the first section the
hypotheses will be formulated. It will also contain my expectations for the empirical
research, which are based on previous studies discussed throughout the chapters of this
thesis. The second section will address the measurement of investor protection. As
mentioned earlier, the La Porta indices were widely used to measure investor protection. I,
however, will use a revised and more recent index, which is the anti-self-dealing index
defined by Djankov et al. (2007). Section three will focus on the measurement of income
smoothing. Followed by a fourth section, in which I will elaborate on the sample selection
process. Finally, a summary will be given.
8.1
H YPOTHESES
Real smoothing involves decisions that reduce the volatility of economic earnings, while
artificial smoothing involves both overstatement and understatement of economic
earnings: low earnings are overstated and high earnings are smoothed out. Since accruals
management does not reduce the firm’s value as much it seems more appealing to insiders
than real smoothing. On the other hand, real smoothing has the added benefit that it is less
transparent and thus much harder to detect and deter (Ewert and Wagenhofer, 2005). In
45 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
the study by Leuz et al. (2003) four different measures were defined in order to capture
management of earnings. Real income smoothing is one of the forms earnings
management manifests itself in, so it was necessary to determine a measure to capture this
form of managing earnings. The measure is a country’s median ratio of the firm-level
standard deviation of operating earnings divided by the firm-level standard deviation of
cash flow from operations. Low values of this measure show that insiders use their
accounting discretion to smooth income. The statistics of this measure in the study by
Leuz et al. (2003) show that earnings are smoother in Continental Europe and Asia than in
Anglo-American countries. Even though I will be using another index than the one used
by them, I expect to find the same outcome. Based on the previous discussion I formulated
the following hypothesis:
H1:
Real income smoothing is more pervasive in countries with weak investor
protection than in countries with strong investor protection
Income smoothing consists of two types of smoothing, real and artificial. In previous
research (Leuz et al. 2003) the pervasiveness of artificial smoothing in several countries
has been researched. The measure which was used to get an indication of this form of
earnings management is the contemporaneous Spearman correlation between changes in
accounting accruals and changes in operating cash flows. The empirical results showed
that earnings smoothing is more pervasive in countries like Greece and Japan than in
countries like Japan and the U.S. In their research Greece and Japan are considered low
investor protection countries, based on the indexes from La Porta et al. (1998). This
research, however, will use another index to classify countries as either high or low
investor environment countries. After having compared the La Porta index and the antiself-dealing index that I will be using, I foresee no major changes in the classification of
low and high investor protection countries. So, I expect my results not to differ
significantly from the results by Leuz et al. (2003).
The foregone discussion led me to formulate the following hypothesis:
H2:
Artificial income smoothing is more pervasive in weak investor protection
countries
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The aforementioned components of income smoothing will determine the aggregate
measure for income smoothing.
H3:
Total income smoothing is negatively related to private enforcement and public
enforcement
H4:
Real income smoothing in the post-IFRS period is low in countries with weak
investor protection
H5:
Artificial income smoothing in the post-IFRS period is more pervasive in weak
investor protection countries
Today, there is enough data available to do a comparison between pre-IFRS period and a
post-IFRS period in levels of income smoothing. This will show whether IFRS adoption
has reduced the smoothing of earnings.
8.2
M EASURING INVESTOR PROTECTION
In the available literature several researchers have established indices to measure investor
protection. Leuz et al. (2003) used the La Porta index in their study, which focused on the
relationship between earnings management and investor protection. The indices from La
Porta et al. (1998) were based on laws in force around 1993 and are available for 49
countries. Their anti-director rights index, however, has been criticized by several
researchers for its ad hoc nature, for mistakes in its coding, and most recently for
conceptual ambiguity in the definitions of some of its components (Pagano and Volpin,
2005).
There is an alternative index that can be used; the more recent and revised anti-selfdealing index defined by Djankov, La Porta, Lopez-de-Silanes and Shleifer (2007). This
index generally works better than the former anti-director rights index (Djankov et al.
2007).
47 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
The following facts have led me to believe that the anti-self-dealing index is suitable for
my research:
i.
This index is more applicable for my research, because it is based on legal rules
prevailing in 2003, in contrast to the anti-director rights index which is based on
rules in effect around 1993.
ii.
The investor protection indices are constructed for 72 countries, which enables me
to conduct research on the 31 countries my thesis will focus on.
iii.
Djankov et al. (2007) clearly state that their index is based on controllers of
companies who act in their own interest at the expense of other investors, but who
follow the law regarding disclosure and approval procedures. This means that the
index is based on interests that are relevant for earnings management. They do not
address cases of corporate crime.
8.3
M EASURING INCOME SMOOTHING
As I mentioned earlier, insiders can conceal changes in the economic performance of the
firm in two ways:
1. By their real operating decisions (real smoothing) and,
2. By their financial reporting choices (artificial smoothing)
For both forms of smoothing, measurements have been developed by Leuz et al. (2003),
which I will use in my statistical analysis. For managers and other controlling insiders,
real smoothing has the added benefit that it is less transparent and thus much harder to
detect and deter than artificial smoothing (Ewert and Wagenhofer, 2005). Real smoothing
involves making production and investment decisions so that the variability of earnings
can be reduced.
The analytical literature offers insights into the incidence of artificial smoothing in
principal–agent relationships. When the agent knows current earnings and has an
imperfect signal on future earnings, the agent smoothes the first-period report around the
future signal when he is restricted to communicating only the current period’s outcome.
48 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
The smoothing objects are the variables whose variations over time are to be controlled
(Kamin & Ronen, 1978; pp. 141, 145). The objects are chosen by the management
regarding aimed at their incentives for income smoothing. Empirical studies which
investigated income smoothing show that the most used object is income.
8.3.1
M EASURING REAL SMOOTHING
Real income smoothing measures the degree to which insiders reduce the variability of
reported earnings by altering the accounting component of earnings. The measure is a
country’s median ratio of the firm-level standard deviation of operating earnings divided
by the firm-level standard deviation of cash flow from operations. The equation is as
follows:
𝐼𝑆1 =
𝜎(𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑒𝑎𝑟𝑛𝑖𝑛𝑔𝑠)
(𝐸𝑞. 9)
𝜎(𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑐𝑎𝑠ℎ 𝑓𝑙𝑜𝑤)
The following calculations will enable me to calculate the outcome for the measure of real
income smoothing (IS1):
𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠 =
𝐶𝑎𝑠ℎ 𝐹𝑙𝑜𝑤 𝐶𝑜𝑚𝑝𝑜𝑛𝑒𝑛𝑡 =
𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝐼𝑛𝑐𝑜𝑚𝑒
(𝐸𝑞. 10)
𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
(𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝐼𝑛𝑐𝑜𝑚𝑒 − 𝐴𝑐𝑐𝑟𝑢𝑎𝑙𝑠)
(𝐸𝑞. 11)
𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
Cash flow from operations is computed indirectly by deducting the accrual component
from earnings. This is done because of unavailability of direct information on firms’ cash
flows in many countries.
As mentioned earlier, the measure is the country’s median ratio of the firm-level standard
deviation of operating earnings divided by the firm-level standard deviation of cash flow
from operations. First, the standard deviation of operating earnings divided by the standard
deviation of operating cash flow is calculated for each firm per country. Afterwards the
median of all the firm-level ratios is calculated and this number is the country measure.
49 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
The financial variables are scaled by the lagged value of total assets, because of the large
differences in median firm size. By doing so a comparison across firm size can be made.
When calculating the total earnings, the operating income is used as a measure. Distinctive
about this income is that items that only appear once, the so-called non-recurring items,
are excluded by this income. This results only in elements of income that are related to the
ordinary operations of a business. These non-recurring items are not related to the daily
operations of a firm. By taking the income from continuing operations you are able to
better compare the earnings from consecutive sample years, because the non-recurring
items ‘disturb’ the annual earnings.
Before being able to calculate the cash flow component, the accruals need to be
determined first. For this purpose, Dechow (1995) uses the following equation:
𝐴𝑐𝑐𝑟𝑢𝑎𝑙𝑠 = (∆𝐶𝐴𝑖𝑡 − ∆𝐶𝑎𝑠ℎ𝑖𝑡 ) − (∆𝐶𝐿𝑖𝑡 − ∆𝑆𝑇𝐷𝑖𝑡 − ∆𝑇𝑃𝑖𝑡 ) −
𝐷𝑒𝑝𝑡𝑖𝑡 7 (𝐸𝑞. 12)
Where
ΔCA
= change in current assets
ΔCASH
= change in cash
ΔCL
= change in current liabilities
ΔSTD
= change in debt included in current liabilities (short term debt)
ΔTP
= changes in income taxes payable
Dept
= depreciation and amortization expense
The purpose of this equation is to calculate the change in earnings by taking current assets
as starting point. Since accruals measure the difference between earnings and the cash
flow, it is interesting to measure the difference between the changes in both elements. In
order to calculate the accruals, the change in cash (ΔCASH) has to be excluded from the
current assets. The change in debt included in current liabilities (ΔSTD) is excluded from
accruals since this is related to financing transactions and therefore is no part of the
operating transactions. The change in income taxes payable (ΔTP) is excluded since this
also is not a part of the operating income. Finally, the depreciation and amortization
7
Changes of the variables above are calculated by year t – year t-1
50 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
expenses are also excluded. If a firm does not report information on taxes payable or
short-term debt, the change in both variables is assumed to be zero.
8.3.2
M EASURING ARTIFICIAL SMOOTHING
If insiders want to smooth earnings they can also do so by smoothing earnings artificially.
The discretion permitted by accounting policies introduces flexibility that allows managers
to adjust reported earnings to produce a smoother income stream. Managers or controlling
shareholders are in the position to accelerate the reporting of future revenues or delay the
reporting of current costs to hide poor current performance. Previous research has shown
us that as long as managers have discretion over accounting choices, they smooth reported
income and the rate of growth in income (Tucker and Zarowin, 2006).
Accounting accruals buffer cash flow shocks and result in a negative correlation between
changes in accruals and operating cash flows. Large magnitudes of this correlation
indicate smoothing of reported earnings that does not reflect a firm’s underlying
performance. Therefore, Leuz et al. (2003) used the contemporaneous Spearman
correlation between changes in total accounting accruals and changes in operating cash
flows as a measure for earnings smoothing.
The measure for artificial income smoothing (IS2) that I will be using is the following:
𝐼𝑆2 = 𝜌(∆𝑎𝑐𝑐𝑟𝑢𝑎𝑙𝑠, ∆ 𝑐𝑎𝑠ℎ 𝑓𝑙𝑜𝑤 𝑓𝑟𝑜𝑚 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛𝑠) (𝐸𝑞. 13)
8.3.3
M EASURING TOTAL INCOME SMOOTHING
An overall summary measure of income smoothing can be constructed for each country.
For both income smoothing measures, countries are ranked such that a higher score
suggests a higher level of earnings management. This means that the outcomes of the real
smoothing measure (IS1) and the artificial smoothing measure (IS2) for all 31 countries
will be ranked. Both rankings will then be averaged, which will result in the aggregate
income smoothing measure. This score will determine the level of smoothing in a country,
51 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
i.e. a high score indicates a high level of income smoothing, while a low score indicates a
lower level of income smoothing in that particular country.
To test the last hypothesis, I will employ the multiple regression stated below.
𝒀𝒕 = (𝜷𝟎 + 𝜷𝟏 𝑿𝟏 + 𝜷𝟐 𝑿𝟐 + 𝜷𝟑 𝑿𝟑 ) + 𝜺𝒊 (𝐸𝑞. 14)
Where
𝑌 𝑡 = Aggregate income smoothing for year t
𝑋1 = Ex ante private control of self-dealing
𝑋2 = Ex post private control of self-dealing
𝑋3 = Public enforcement
𝜀𝑖 = Error term represents unexplained variation in the dependent variable
The dependent variable, aggregate income smoothing, can be predicted by three
independent variables. Two of these variables form the anti-self-dealing index. This index
consists of the average of two indexes, which are the ex ante private control of self-dealing
and ex post control of self-dealing. The third variable that I will use is the public
enforcement index from Djankov et al. (2007). These indices have been defined by
Djankov et al. (2007) for 72 countries classified by their legal origin.
8.4
S AMPLE SELECTION
The sample will consist of observations in 31 countries, in the period 2000 till 2008. The
countries which will be included in this study are the same 31 countries investigated by
Leuz et al.(2003). In order to be included in the sample they must have at least 300 firmyear observations for a number of accounting variables, such as total assets, sales, net
income and operating income. Each firm must have income statement and balance sheet
information for at least three consecutive years. The data is drawn from the Thomson One
Banker database. Banks and financial institutions are excluded from the empirical
52 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
research. The final sample consists of 21.297 non-financial firms. The firms included
operate in different industries which can be identified by the following codes.
Table 1
IBC Code
Industry
1000
Basic Materials
3000
Consumer Goods
5000
Consumer Services
4000
Health Care
2000
Industrials
9000
Technology
6000
Telecommunications
7000
Utilities
The 31 countries that will be used are selected for two main reasons. First, because my
research focuses on complementing and extending the research of Leuz et al. (2003),
therefore the same 31 countries they included in their sample are selected. Secondly, all of
these countries are hyperinflation-free in the sample period. High inflation may affect the
income smoothing measurements used.
Because of the large sample, it is useful to cluster the companies so that the patterns in
earnings management among countries can emerge. By employing a country cluster
analysis the countries can be categorized in three clusters, each containing countries with
similar legal and institutional characteristics:
1. Countries with high investor protection;
2. Countries with medium investor protection,
3. Countries with low legal enforcement.
53 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
8.5
E ARNINGS M ANAGEMENT P RE -IFRS AND P OST -IFRS
As of January 1st 2005 all European Union member countries have adopted IFRS. These
standards reduce the amount of reporting discretion and therefore improve transparency
and comparability. Also, managing earnings will be more difficult and if done, easier to
detect. In order to test this argument made by proponents of IFRS, I will be looking at the
level of income smoothing in the pre-IFRS period (2000-2004) and the post-IFRS period
(2005-2008) in certain EU member states. Within the sample of 31 countries there are 14
EU member states.
54 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
9
E MPIRICAL STUDY : I NFLUENCE OF INVESTOR PROTECTION ON I NCOME S MOOTHING
9.1
I NTRODUCTION
The first part of the empirical study, the influence of investor protection on earnings
management, is performed in this chapter. Several sub questions discussed in chapter 1
will be answered. First the hypotheses researched in this chapter will be shortly reviewed
again. The parameters for the 31 countries will also be presented. Afterwards the results
and conclusions regarding hypotheses 1 to 3 will be presented.
9.2
H YPOTHESES
The first three hypotheses that were formulated in the previous chapter will be tested in
this chapter. As noted earlier, earnings management can present itself in the form of real
smoothing as well as artificial smoothing. The standard used to measure the former is a
country’s median ratio of the firm-level standard deviation of operating earnings divided
by the firm-level standard deviation of cash flow from operations. The first hypothesis will
test whether investor protection affects real smoothing. This leads to the first hypothesis to
be tested.
H1:
Real income smoothing is more pervasive in countries with weak investor
protection than in countries with strong investor protection
Besides real smoothing I will also measure the impact of investor protection on artificial
smoothing. The measure used is the contemporaneous Spearman correlation between
changes in accounting accruals and changes in operating cash flows. The data is not
normally distributed; therefore it is necessary to use the Spearman correlation, which deals
with non-parametric data. The following hypothesis is formulated.
H2:
Artificial income smoothing is more pervasive in weak investor protection
countries
The first two measures can be ranked in such a way that a higher score implies a higher
level of income smoothing. These rankings of the aforementioned components of income
55 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
smoothing will then be used to determine the aggregate measure for income smoothing.
This leads to the third hypothesis to be tested in this chapter.
H3:
Aggregate income smoothing is negatively related to private enforcement and
public enforcement
9.3
S AMPLE
From the Thomson One Banker database I retrieved data for 21.492 companies across 31
countries. Not all companies are included in the final sample however, because in order to
be included in the sample each firm must have financial data available for at least three
consecutive years. Due to a lack of information on total current assets, cash and
investments, total current liabilities, short term debt, income taxes and depreciation many
were excluded. Also, financial institutions were excluded. The final sample consists of
20.367 firms.
9.4
D ESCRIPTIVE STATISTICS
Table 2
Descriptive statistics
Country
# Firms
IFRS adopter
Median firm sales in $
Australia
1.346
Yes
336.432
Sweden
282
Yes
360.521
Finland
108
Yes
401.123
Canada
893
No8
350.632
United States
9
4.573
No
Norway
110
Yes
190.812
Denmark
101
Yes
210.567
1.041
Yes
223.365
Netherlands
121
Yes
430.865
France
645
Yes
260.932
Switzerland
164
No10
470.485
United Kingdom
4.597.532
8
The use of IFRS will be required for Canadian publicly accountable profit-oriented enterprises for financial periods
beginning on or after 1of January 2011
9 The SEC released its proposed written roadmap in November 2008 and reaffirmed its commitment to one global set of
accounting standards in a statement released in February 2010.
10 Registrants at the main board of the SIX (Swiss Stock Exchange) are required to use either IFRS or US GAAP.
56 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Singapore
507
No11
193.451
Germany
671
Yes
424.641
South Africa
223
Yes12
483.573
Hong Kong
749
Yes13
267.311
Belgium
94
Yes
362.115
Austria
64
Yes
287.912
14
552.187
Japan
Pakistan
3.354
99
No
No15
30.423
16
59.603
65.841
Thailand
374
No
Philippines
136
Yes17
Taiwan
576
No
18
272.692
Ireland
48
Yes
178.513
Indonesia
267
No19
82.167
Korea
997
No20
548.948
Malaysia
792
No21
101.567
Italy
216
Yes
411.316
Greece
247
Yes
43.561
Spain
94
Yes
392.873
Portugal
52
Yes
190.654
India
1.432
No22
176.469
Mean
657.29
-
278.720
267
-
270.00
978.57
-
152.06
Min
48
-
30.42
Max
4573
-
552.19
Median
Standard deviation
11
SFRS (Singapore Financial Reporting Standards) will fully converge with IFRS by 2012.
As of January 1st 2005 all listed companies are required to report according to IFRS.
13 As of 2005, Hong Kong Financial Reporting Standards (HKFRS) are identical to International Financial Reporting
Standards.
14
The Accounting Standards Board of Japan has agreed to resolve all inconsistencies between the current JP-GAAP and
IFRS wholly by 2011.
15 Not all IFRS/IAS are obligatory for listed companies.
16 IFRS will be converged with local GAAP; some standards will be adopted as TAS (Thai GAAP) in 2011 and some in
2013. Full convergence is expected by January 1, 2013.
17 IFRS is required for consolidated and standalone/separate financial statements
18 Starting 2013 all listed companies will have to report according to IFRS.
19 Indonesia is planning to converge with IFRS by 2012.
20 Early adoption of IFRS, with exception of financial institutions, is permitted from 2009. Adoption of IFRS is required
for all listed companies and certain financial institutions from 2011.
21 The Malaysian Accounting Standards Board (MASB) announced on August 1, 2008, plans to bring Malaysia to full
convergence with IFRS by January 1, 2012.
22 Financial statements must be prepared according to Indian GAAP. The Institute of Chartered Accountants of India
(ICAI) has announced that IFRS will be mandatory in India for financial statements for the periods beginning on or after
1 April 2011.
12
57 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
9.5
I NCOME SMOOTHING MEASURES
This subsection will take a closer look at the real and artificial income smoothing
measures for each of the 31 countries. Table 3 shows the values of both incomes
smoothing measures as well as the aggregate income smoothing measure.
Income smoothing measure 1 (IS 1) should be interpreted as follows: low values indicate
that controlling insiders smooth income. From the table can be concluded that India is the
country with the lowest value of this measure, which means that insiders use their
accounting discretion to manage the firm’s income. IS 1 is computed by dividing the
median ratio of the firm-level standard deviation of operating earnings by the firm-level
standard deviation of cash flow from operations. Dividing it by the cash flow from
operations takes care of the problem with differences in variability of economic
performance across firms. IS 1 values for most EU countries lie around the mean (0.579).
The values for the PIGS23 and Austria however are well below the mean and show strong
evidence of income smoothing.
Income smoothing measure 2 (IS 2) measures the correlation between changes in
accounting accruals and cash flows from operations. Controlling insiders are in the
position to use accounting discretion to misrepresent the cash flow from operations. They
can delay the recognition of current profit to create reserves for the future in case the
future performance will not be as good as the current performance. Large negative
correlations are an indication for income smoothing. For example, income smoothing is
more pervasive in Greece and Korea, than in the US and Canada. The table below shows
that India is the country with the largest IS 2 value. Once again, the PIGS have values that
show strong evidence of income smoothing.
The aggregate income smoothing measure is computed by adding up the rankings of IS 1
and IS 2 and dividing the total by two. The first two measures are ranked in such a way
that a higher score indicates a higher level of earnings management. India had for both
IS 1 and IS 2 respectively the lowest and highest values, so it is only logical that India will
have the highest aggregate income smoothing score.
23
PIGS: Portugal, Italy, Spain and Greece
58 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Table 3
Income smoothing measures
IS 124
IS 225
India
0.328
-0.901
31
Portugal
0.398
-0.898
29.5
Indonesia
0.518
-0.834
24
Spain
0.430
-0.83
28
Korea
0.507
-0.819
24.5
Italy
0.489
-0.812
25.5
Greece
0.365
-0.805
27.5
Malaysia
0.486
-0.804
25
Taiwan
0.508
-0.802
22
Ireland
0.500
-0.790
23
Pakistan
0.529
-0.747
19.5
Thailand
0.515
-0.740
20
Philippines
0.501
-0.738
21
Japan
0.559
-0.731
16.5
South Africa
0.636
-0.699
13
Switzerland
0.677
-0.691
11.5
Singapore
0.655
-0.673
11.5
Belgium
0.557
-0.657
15
Germany
0.608
-0.656
12
Hong Kong
0.552
-0.654
14.5
UK
0.704
-0.644
8.5
USA
0.847
-0.637
6
Netherlands
0.599
-0.610
11
France
0.574
-0.605
11
Canada
0.835
-0.594
5.5
Austria
0.437
-0.571
16.5
Norway
0.625
-0.553
7.5
Denmark
0.602
-0.512
8
Sweden
0.844
-0.472
3
Finland
0.719
-0.432
3.5
Australia
0.851
-0.421
1
Mean
0.579
-0.688
16
Country
24
25
Aggregate IS score
IS 1 = σ(Operating earnings)/σ(Operating cash flows)
IS 2 = ρ (Δ Accruals, Δ Operating cash flows)
59 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Median
0.557
-0.691
15
Standard deviation
0.138
0.129
8.57
Min
0.328
-0.901
1
Max
0.851
-0.421
31
9.6
C LUSTER ANALYSIS
In order to provide evidence on the patterns of income smoothing within a group of
countries with similar institutional characteristics, it is necessary to perform a k-means
cluster analysis. By dividing the countries in three clusters based on the level of investor
protection in each country, I will be able to determine whether income smoothing is more
pervasive in high or low investor protection countries. The k-means cluster analysis is
based on three investor protection variables from Djankov et al. (2008) which are: ex ante
private control of self-dealing, ex post private control of self dealing and the public
enforcement index. In order to get a good grasp of these variables I will elaborate more on
them.
Table 4
Investor protection variables
The anti-self dealing index is the average of ex ante and ex post private control of self-dealing
Country
Ex-ante private
Ex-post private
Anti-self-
Public
control of self-
control of self
dealing index
enforcement
dealing
dealing
Austria
0.00
0.42
0.21
1.00
Greece
0.08
0.37
0.23
0.50
Korea
0.25
0.67
0.46
0.50
Portugal
0.22
0.75
0.49
1.00
Italy
0.08
0.69
0.39
0.25
Taiwan
0.42
0.70
0.56
0.00
Switzerland
0.08
0.45
0.27
0.50
Singapore
1.00
1.00
1.00
1.00
Germany
0.14
0.42
0.28
1.00
Japan
0.22
0.74
0.48
0.00
Belgium
0.39
0.69
0.54
0.50
Hong Kong
1.00
0.93
0.96
0.00
60 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
India
0.33
0.76
0.55
0.50
Spain
0.22
0.52
0.37
0.75
Indonesia
0.81
0.56
0.68
0.00
Thailand
1.00
0.70
0.85
0.00
Pakistan
0.17
0.65
0.41
0.75
Netherlands
0.06
0.36
0.21
0.00
Denmark
0.25
0.68
0.47
0.75
Malaysia
1.00
0.90
0.95
1.00
France
0.08
0.68
0.38
0.50
Finland
0.14
0.78
0.46
0.00
Philippines
0.06
0.42
0.24
0.00
United Kingdom
1.00
0.85
0.93
0.00
Sweden
0.17
0.51
0.34
1.00
Norway
0.42
0.45
0.44
1.00
South Africa
1.00
0.63
0.81
0.00
Canada
0.33
0.97
0.65
1.00
Ireland
0.78
0.80
0.79
0.00
Australia
0.89
0.69
0.79
0.50
United States
0.33
0.97
0.65
0.00
Self-dealing is often referred to as investor expropriation; the individuals who control a
corporation (managers, controlling shareholders etc.) are in the position to use their power
to benefit themselves instead of sharing corporate wealth with other investors. Such
diversion of firm resources to their controllers is referred to in literature as ‘private
benefits of control’. The law plays a crucial role in controlling corporate self-dealing.
There are various forms of self-dealing: excessive compensation, executive perquisites,
transfer pricing, and appropriation of corporate opportunities and plain theft of corporate
assets (Shleifer and Vishny, 1997). There are different ways to deal with corporate selfdealing. One extreme solution is to leave the problem to the market forces and hope that
the problem will be sorted out. The other extreme solution is to prohibit all conflicted
transactions. Both of these are not likely to be implemented in societies, because of their
extreme character. In between these two extremes there are several options. One of them is
to facilitate private enforcement of good behavior which basically focuses on extensive
disclosure, approval procedures for transactions and facilitation of private litigation when
self-dealing is suspected. Society can also use the approach in which it relies on public
enforcement which discourages wrongdoing through sanctions such as fines and prison
61 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
terms for the controlling shareholder(s). (Djankov et al. 2008). The anti-self-dealing index
(average of the ex ante and ex post private control of self-dealing indexes) measures the
obstacles that the controlling shareholder must overcome in order to increase his own
benefits. A higher anti-self-dealing index means that more obstacles need to be overcome,
so it is more difficult for controlling shareholders or managers to serve their own benefits.
Transactions involving conflicts of interest can be regulated by the law in such a way that
the terms and conditions are similar to the ones that would exist in an arm’s length
transaction. The law can also facilitate expropriated minority shareholders who are
seeking remedy through the courts or via fines and criminal sanctions on the ones who
expropriated them.
After having performed the cluster analysis based on the three investor protection
variables 3 clusters appeared. Table 5.1 shows these three clusters. The first cluster is
defined by a high ex ante private control of self-dealing index. This means that several
disclosures have to be made by all parties in a transaction and that the transaction must be
approved by disinterested shareholders. The ex post private control of self-dealing index is
also fairly high for this cluster, which shows that the countries in cluster 1 empower
shareholders to sue the parties in a transaction for damages. Shareholders are also
facilitated in proving wrongdoing. Countries in cluster 1 score high on public
enforcement; shareholders can seek justice through fines and jail sentences against
expropriators. So, the countries in cluster 1 can be referred to as high investor protection
countries. The second cluster is characterized by rather low indices of ex ante private
control of self-dealing and medium to high indices of ex post private control of selfdealing. The economies in cluster 2 can be identified as medium investor protection
countries. The third cluster consists of countries with low to medium indices of both ex
ante private control of self-dealing and ex post private control of self-dealing. The public
enforcement index however, is very low for these countries. Therefore this cluster consists
of the low investor protection countries. It seems that cluster 2 lies in between the high
and low investor protection countries respectively cluster 1 and cluster 3. But when
looking at the Euclidean distances it becomes clear that cluster 1 and 2 are slightly closer
to each other than cluster 2 and 3.
Table 5.1 shows the membership of the three clusters and table 5.2 shows the mean values
of investor protection variables per cluster.
62 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Table 5.1 Cluster membership
Countries are sorted by aggregate income smoothing score.
Country
Cluster 1
Australia
Singapore
Malaysia
Cluster 2
Sweden
Canada
Norway
Denmark
France
Switzerland
Germany
Belgium
Austria
Pakistan
Korea
Greece
Spain
Portugal
India
Cluster 3
Finland
United States
United Kingdom
Netherlands
South Africa
Hong Kong
Japan
Thailand
Philippines
Taiwan
Ireland
Indonesia
Italy
Table 5.2 Mean values of investor protection variables by cluster
Ex ante private control of selfdealing
Ex post private control of selfdealing
Public enforcement index
9.7
Cluster 1
0.96
Cluster 2
0.21
Cluster 3
0.53
0.86
0.60
0.70
0.83
0.75
0.02
S TATISTICAL ANALYSIS
At the beginning of this chapter the three hypotheses applicable to this chapter were
stated. This section will start off by looking at the correlations and multiple regression in
order to test the first and second hypothesis. Afterwards I will discuss the results of the
multiple regression used to test the third hypothesis.
9.7.1
R EAL INCOME SMOOTHING AND ARTIFICIAL INCOME SMOOTHING
The multiple regressions includes three variables which are ex ante private control of selfdealing, ex post private control of self-dealing and the public enforcement index. The first
two variables are both entered into the model first, because previous research has led me
63 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
to believe that these are important factors (predictors) in predicting income smoothing.
The third variable, public enforcement is entered last.
The dependent variable is the real income smoothing measure (IS1). The correlation
matrix can be found in appendix F. From this matrix I learned that there are no significant
correlations between the aggregate income smoothing score and any one of the three
predictors. Leaving this important aspect aside, the correlations are all positive, which is
the exact opposite of my expectations. A positive relationship would mean that whenever
investor protection increases income smoothing increases as well.
The model summary, which can also be found in appendix F, presents the values of the
multiple correlation coefficients between the predictors and real income smoothing. The
first two predictors predict a measly 6.9% of the variation in income smoothing. When the
third predictor is entered 7% is accounted for. So, these three predictors do not explain
much of the variation in real income smoothing.
In order to test whether the level of investor protection in a country influences the
occurrence of artificial income smoothing a hierarchical multiple regression is executed.
The SPSS output is presented in appendix G. The correlation matrix produces Pearson
correlation coefficients between every pair of variables and reveals that there is no
significant relationship between any of the variables. This means that in contrast to the
correlations from the real income smoothing analysis, the correlations between artificial
smoothing and two of the investor protection variables are negative. But I cannot draw any
accurate conclusions from these correlations, because of the fact that they are not
significant.
The model summary shows that the three variables hardly explain 2% of the variation in
artificial income smoothing. So, the three predictors used in the model are not good at
predicting the variation in the dependent variable.
9.7.2
A GGREGATE INCOME SMOOTHING
This section will discuss the statistical analysis for the aggregate income smoothing
measure and its outcome in detail by looking at the results of the correlation matrix and
the regression analysis.
64 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
9.7.2.1
C ORRELATION MATRIX
We will first take a look at the correlation between the aggregate income smoothing score
and investor protection variables. The correlation matrix in table 6 shows that there are no
significant correlations between the aggregate income smoothing score and any one of the
investor protection variables. Usually, social scientists accept any probability value below
0.05 as being statistically meaningful and so any probability value below 0.05 is regarded
as indicative of genuine effect (Field, 2005).
Table 6
Correlations
Aggregate IS
Pearson Correlation
Ex ante private
Ex post private
control of self-
control of self-
Public
dealing
dealing
enforcement
Aggregate IS
1.000
-.288
-.274
.275
Ex ante private control of
-.288
1.000
.540
-.224
-.274
.540
1.000
-.095
.275
-.224
-.095
1.000
.
.058
.068
.067
.058
.
.001
.113
.068
.001
.
.306
.067
.113
.306
.
Aggregate IS
31
31
31
31
Ex ante private control of
31
31
31
31
31
31
31
31
31
31
31
31
self-dealing
Ex post private control of
self-dealing
Public enforcement
Sig. (1-tailed)
Aggregate IS
Ex ante private control of
self-dealing
Ex post private control of
self-dealing
Public enforcement
N
self-dealing
Ex post private control of
self-dealing
Public enforcement
When we disregard (for a moment) the fact that the correlations are not significant, and
only look at the predictors, it becomes clear that the coefficients are rather small (R=0.224
and R=0.95). The only correlation that is fairly high is the correlation between ex post
private control of self-dealing and ex ante private control of self-dealing(R=0.540). It
appears that, if the correlations were significant, the predictors are measuring different
65 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
things. The first predictor, ex ante private control of self-dealing, comes close to being
significant (p=0.058) and has the highest correlation with the aggregate income smoothing
score. If it were significant it is this predictor that would predict income smoothing the
best.
Furthermore, this matrix shows that there is no multicollinearity; there are no correlations
higher than 0.9.
9.7.2.2
R EGRESSION ANALYSIS
The model used in my research is a hierarchical regression, see section 8.3.3. As
mentioned earlier the ex ante and ex post private control of self-dealing indexes are
entered first. The model summary represents this method. Model 1 refers to the first stage
in which only the first two predictors are included in the model; this gives a correlation of
0.320. When all three predictors are included in the model (Model 2) the correlation
increases to 0.389.
From the model summary we can conclude that the ex ante and ex post private control of
self-dealing indexes only account for 10.3% of the variability in the outcome. When the
third predictor is added, 15.1% of the variability in the outcome is accounted for by the
three predictors. Including the last predictor, public enforcement, did not give an outcome
which explains a relatively large amount of the variation in income smoothing.
Table 7
Model
Model Summary
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.320a
.103
.039
8.39986
2
.389b
.151
.057
8.31817
Durbin-Watson
1.684
a. Predictors: (Constant), Ex post private control of self-dealing, Ex ante private control of self-dealing
b. Predictors: (Constant), Ex post private control of self-dealing, Ex ante private control of self-dealing,
Public enforcement
c. Dependent Variable: Aggregate IS
I already discussed whether or not the model has improved the ability to predict the
outcome variable. As we’ve seen this is not the case with this model, only 15.1% of the
income smoothing in countries is explained by the three predictor variables. Now I will
move on to address the parameters of the model. The beta values are presented in table 8
66 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
and give information about the relationship between income smoothing and each investor
protection variable.
The values for ex ante private control of self dealing and ex post private control of selfdealing are both negative which represents a negative relationship between these
predictors and income smoothing. The correlation between income smoothing and public
enforcement however, has a positive sign. This is in clear contrast to what I expected.
Table 8
Coefficients
Model
Standardized
Unstandardized Coefficients
B
1
Std. Error
(Constant)
23.131
5.922
Ex ante private control of
-4.687
5.051
-7.751
9.852
(Constant)
20.732
6.172
Ex ante private control of
-3.377
5.111
-8.138
4.676
Coefficients
Beta
t
Sig.
3.906
.001
-.197
-.928
.361
-.167
-.787
.438
3.359
.002
-.142
-.661
.514
9.761
-.176
-.834
.412
3.752
.227
1.246
.223
self-dealing
Ex post private control of
self-dealing
2
self-dealing
Ex post private control of
self-dealing
Public enforcement
a. Dependent Variable: Aggregate IS
9. 8
M ODEL ASSUMPTIONS
In order to draw conclusions about a population based on a regression analysis done on a
sample, several assumptions have to be met according to Field (2005). It is necessary to
know whether these assumptions are broken, because if they are broken one cannot draw
accurate conclusions about reality. If the assumptions are met the coefficients and
parameters of the multiple regression are unbiased and the regression model can be
accurately applied to the population. I will elaborate more on these 9 assumptions and
discuss whether they are true or not for this research.
67 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Type of variables
It is required that the variables are either quantitative or categorical and the outcome
variable must be quantitative, continuous and unbounded. Assumption is met.
Non-zero variance
There should be some variation in the value of the predictors. Assumption is met.
No perfect multicollinearity
Two or more predictor variables should not have a perfect linear relationship. The
predictors should not correlate too highly. Multicollinearity only forms a threat for
multiple regression ( not for a linear regression) because there are more than one
predictors. If the collinearity between predictors is perfect it will be impossible to obtain
unique estimates of the coefficients, because there are many combinations of coefficients
that would give the same estimates.
A good way to identify multicollinearity is the variance inflation factor (VIF) which gives
an indication whether a predictor has a strong linear relationship with the other predictors.
Field (2005) states that according to Myers a value of 10 as a VIF value is the point at
which you should start worrying.
The VIF values of the predictors in the multiple regression I used are all below 2 and
greater than 1. This indicates that there are no perfect linear relationships between the
predictors, so there is no reason for concern.
There is another statistic that can be used to discover whether predictors are dependent or
not, the tolerance statistic. For this statistic values below 0.1 are problematic (Field,
2005). The values for this statistic that I found confirm the findings mentioned above,
there is no perfect linear relationship between the predictors. The tolerance statistic values
are all greater than 0.1. See appendix E for SPSS output. Assumption is met.
Predictors are uncorrelated with ‘external variables’
External variables refer to the variables that have not been included in the regression
model, but which influence the outcome variable. The external variables should not
correlate with the variables included. If they do, the conclusions drawn from the model are
unreliable, because other variables could have predicted the outcome just as well. The
68 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
previous chapters have shed light on the variables that influence income smoothing. I have
taken these variables into account and therefore this assumption is met.
Homoscedasticity
The variance of the residual terms should be constant at each level of the predictor
variables. If this is not the case, there is said to be heteroscedasticity. No pattern can be
detected (see appendix D), thus this assumption is met.
Independent errors
This means that for any two observations the residual terms should be uncorrelated. The
Durbin-Watson test can be used to test this assumption. The Durbin-Watson test looks for
serial correlations between errors. The outcome of this test can vary between 0 and 4
whereas a value of 2 indicates that the residuals are uncorrelated. Values below 1 or
greater than 3 are causes for concern according to Field (2005). The Durbin-Watson value
for my research is 1.684, so there is no reason for concern. Assumption is met.
Normally distributed errors
This assumption assumes that the residuals in the model are random, normally distributed
variables with a mean of 0, which basically means that the differences between the model
and the observed data are zero or very close to zero. Differences that are greater than 3 are
not common and happen occasionally. The mean of the predicted variable score is close to
0.
The SPSS output in appendix E shows the necessary information; the standard
predictive value of the mean is 0.000. The assumption therefore is met.
Independence
This assumption simply means that all values of the dependent variable are independent.
The independence assumption is also met, because each value in my research comes from
a separate entity. Assumption is met.
Linearity
It is assumed that the relationship modeled is a linear one. This means that the mean
values of the outcome variable for each increment of the predictors lie along a straight
line. Appendix D provides a scatter plot from which we can conclude that there is a linear
relationship; there is no curve or whatsoever in this plot. This assumption is met.
69 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
I mentioned earlier that if the aforementioned assumptions are met, which is the case in
my research, one can draw accurate conclusions about reality. This however, does not
mean that the regression model used is the exact same as the model that I would have
obtained had I tested the entire population (Field, 2005). What the regression model used
actually tells me is that on average the regression model from the sample is the same as
the population model. Once again there is a but: It is possible that the sample may not be
the same as the population model, but the likelihood of them being the same is increased.
9.9
R ESULTS AND D ISCUSSION
The literature which I discussed in the first seven chapters of this thesis argued that there
is a relationship between the occurrence of income smoothing and the level of investor
protection in a particular country. Previous studies have provided evidence that a higher
level of investor protection will discourage controlling insiders from smoothing income,
so legal systems that protect outside investors reduce the need for insiders to conceal their
activities. This basically means that high investor protection countries have a low level of
income smoothing and low investor protection have a high level of income smoothing.
The correlation matrix showed that real income smoothing has a positive correlation with
all three of the investor protection variables, which is the complete opposite of what I
expected to find and what previous studies proved. The three variables only accounted for
7% of the variation in real income smoothing, which is extremely low. On top of it all,
none of the correlations are statistically significant. The first hypothesis cannot be
confirmed.
There is a negative correlation between artificial income smoothing and the ex ante private
control of self-dealing index as well as the ex post private control of self-dealing index.
Not one of these correlations is significant however, which restrains me from telling
whether the relationship is genuine or not. The three variables hardly account for 2% of
the variation in artificial income smoothing, which means that they are not good in
predicting the level of income smoothing. Thus, the second hypothesis cannot be
confirmed.
70 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
The results from the statistical analysis shown in the previous sections of this chapter
show that there is indeed a negative correlation between income smoothing and two out of
three investor protection variables. Despite this I cannot confirm any of the hypotheses
because these correlations are not significant and therefore I cannot confirm the
expectations I had. From the statistical analysis it appears that there is a positive
relationship between income smoothing and the level of public enforcement. This is the
exact opposite from that which I argued in the literature review of this thesis. This
correlation however is not significant, so I cannot say that this relationship is genuine.
Apart from having taken a look at the relationships between the occurrence of income
smoothing and the level of investor protection, I also tested what influence investor
protection has on income smoothing by deploying a hierarchical multiple regression. The
result of this regression is shown in table 7. This table shows that the first two predictors
account for 10.3% of the variability in the data. When the third predictor is entered in the
model this percentage increases to 15.1%. So, the third predictor accounts for 4.8% of the
variability. The third hypothesis cannot be confirmed either.
From the statistical analysis it became clear that there is no significant relationship
between investor protection and income smoothing. So, I will take a closer look at the
income smoothing measures presented in table 3 and compare them to the income
smoothing measures obtained by Leuz et al. (2003). Table 3 shows that the IS 2 measure
varies between -0.421 and -0.901 while the IS 2 measure obtained by Leuz et al. (2003)
varies between -0.722 and -0.928 (appendix J). Because the IS 2 measures in table 3 have
a broader range, the aggregate income smoothing score will also differ from the aggregate
earnings management score from Leuz et al. (2003). Appendix J presents the earnings
management measures for the study done by Leuz et al. (2003). When comparing this
table with table 3 it becomes clear that the aggregate scores for several countries indeed
differ significantly between this study and the previously mentioned study. Ireland for
instance, has an aggregate income smoothing score of 23 in this research, while in the
previous study it had a score of 5.1. The aggregate score in the previous study can also be
averaged out due to the fact that Luez et al. (2003) used four measures. Nonetheless, it is
remarkable that countries like Austria, Ireland, Switzerland, Singapore, India, Spain,
Denmark and Malaysia have such large differences in the aggregate scores. I believe that
these large differences can be explained by the large variance in the IS 2 measure.
71 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Throughout this thesis it must have become apparent that I expected to find a significant
negative correlation between the three investor protection variables and real income
smoothing. I also expected a significant negative correlation between the three predictors
and artificial income smoothing. Automatically, I assumed that if there would be a
significant negative correlation between the income smoothing measures and three
predictors separately, there would also be a significant negative correlation between the
aggregate income smoothing score and investor protection variables. The statistical
analysis however, clearly exhibits that none of these three expectations is met. Since there
is no significant relationship between income smoothing and the level of investor
protection I am not at liberty to say whether the occurrence of income smoothing is lower
in higher investor protection countries.
Nothing else rests me to do but try to explain why there are no significant correlations and
why this differs from previous research. Explanations can be sought in two corners: one,
there occurred a problem with the income smoothing measures and therefore also with the
aggregate income smoothing score or two, there is something wrong with the investor
protection indexes. Since the indexes are derived from Djankov et al. (2007) the latter
option is highly unlikely to be the case. In their research Djankov et al. (2007) state that
these indexes are better grounded in theory than the previous index, the anti-director rights
index constructed by La Porta et al (1998). The latter index was used in the work of Leuz
et al. (2003) and resulted in a significant negative correlation between the investor
protection variable and earnings management. So, it was only obvious to assume that a
new and improved index would lead to a significant negative correlation as well. Thus, the
second possible explanation, a problem with the investor protection variables, can be
rejected.
This means that the problem lies within the income smoothing measures. In order to
determine the income smoothing measures several formulas have been used, which I have
executed very accurately. I also took into consideration possible outliers, which are
atypical, infrequent observations. Because of the way in which the regression line is
determined outliers have a profound influence on the slope of the regression line and
consequently on the value of the correlation coefficient. A single outlier is capable of
considerably changing the slope of the regression line and, consequently, the value of the
72 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
correlation. Therefore, one should never base important conclusions on the value of the
correlation coefficient alone. For this reason I examined the scatter plots for the income
smoothing measures for each country.
The data used to calculate these measures have been obtained from a very reliable source,
Thomson One Banker. The significance of a correlation coefficient of a particular
magnitude will change depending on the size of the sample from which it was computed.
After comparing my research sample to that of Leuz et al. (2003) I noticed that there was a
relatively large difference in the sample population, their sample included 8.616 firms
whereas mine consisted of 21.492 firms. This large difference can be explained by small
and middle-sized companies (SMEs) that made their financial data available during the
sample period I have chosen, even though they are not always obliged to do so.
Controlling insiders of SMEs often have no incentives to smooth income, because these
firms often do not have to answer to shareholders in the same way large public firms need
to answer to shareholders. The principal-agent problem is not present in the same way it is
present in public firms. By including the SMEs in the sample there occurs a distortion in
the income smoothing scores. These distortions could have contributed to the results I
obtained.
In the text above I attempted to give a reasonable explanation for the results obtained. I do
have to admit that the results came as a surprise to me. I definitely was not prepared to
find that there is no significant negative correlation between income smoothing and the
level of investor protection. This made if quite difficult to find an explanation for the
findings of this research.
73 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
10
E MPIRICAL STUDY : I NCOME SMOOTHING IN THE PRE -IFRS AND POST -IFRS PERIOD
10.1
I NTRODUCTION
This chapter will discuss the second leg of this research, the influence of investor
protection on income smoothing in the pre-IFRS period and the post-IFRS period. The
goal of this second leg of research is to determine whether the introduction of IFRS has
had a significant influence on the occurrence of income smoothing. It became clear from
the first leg of this research that there is no significant relationship between income
smoothing and any of the investor protection variables. That however, will not withhold
me from continuing the remainder of the research. The two remaining hypotheses will be
tested in this chapter:
H4:
Real income smoothing in the post-IFRS period is low in countries with weak
investor protection
H5:
Artificial income smoothing in the post-IFRS period is more pervasive in weak
investor protection countries
The sample consists of 3.707 firms across 14 European Union countries. The original
sample included 3.860 firms, but a lack of data required a relatively small number of firms
to be excluded. Firms included in this sample are required to have data available for at
least three consecutive years.
Proponents of IFRS have argued that limiting accounting alternatives can increase
accounting quality and decrease the occurrence of earnings management. Barth et al.
(2008) hypothesized that applying IAS would lead to higher quality financial data and
therefore less earnings management, their empirical research provided evidence that firms
applying IAS generally indeed evidence less earnings management. The IFRS countries
that are investigated are the 14 EU countries included in the original sample. These
countries, together with the income smoothing measures, are shown in table 9. The income
smoothing and investor protection measures are the same ones used in the previous part of
the research. Table 9 shows that the values of the income smoothing measures in the preIFRS period are relatively lower for some countries than the values of these measures in
the post-IFRS while some countries have higher values in the post-IFRS period. For
74 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
example, Germany and the Netherlands both show a lower IS1 value in the post-IFRS
period, while Portugal and Spain both have higher IS1 values in the post-IFRS period.
Table 9
Income smoothing measures pre-IFRS and post-IFRS
Country
IS 1
IS 2
2000 - 2004
0.367
2005 - 2008
0.376
2000 - 2004
-0.874
2005 - 2008
-0.879
Spain
0.345
0.452
-0.794
-0.765
Greece
0.284
0.375
-0.767
-0.942
Italy
0.447
0.474
-0.758
-0.755
Germany
0.562
0.514
-0.707
-0.621
France
0.499
0.495
-0.668
-0.640
Netherlands
0.574
0.503
-0.625
-0.654
Sweden
0.795
0.712
-0.572
-0.438
Belgium
0.543
0.556
-0.566
-0.636
United Kingdom
0.616
0.627
-0.563
-0.598
Austria
0.445
0.453
-0.548
-0.618
Finland
0.669
0.568
-0.544
-0.641
Denmark
0.580
0.567
-0.496
-0.362
Ireland
0.488
0.586
-0.355
-0.662
Mean
0.515
0.519
-0.631
-0.658
Median
0.521
0.509
-0.599
-0.641
Standard deviation
0.135
0.093
0.138
0.150
Min
0.284
0.375
-0.874
-0.942
Max
0.795
0.712
-0.355
-0.362
Portugal
10.2
I NCOME SMOOTHING IN THE PRE -IFRS PERIOD
First, the pre-IFRS period will be looked at. Table 10 presents the income smoothing
measures 1 and 2 for the pre-IFRS period (2000-2004) as well as the aggregate income
smoothing score. Previous research has been performed on this subject, but the results
have not been unanimous. Some researchers found evidence that indicated that firms
evidence more income smoothing in the post-IFRS period than in the pre-IFRS period,
while other researchers found that firms are less prone to engage in income smoothing in
the post-IFRS period than in the pre-IFRS period.
Panaanen and Lin (2009) investigated whether the quality of accounting numbers of
German companies under IAS differed under IFRS. Their results indicated that accounting
75 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
quality has decreased in the post-IFRS period. In the pre-IFRS period the researchers
looked at companies reporting under IAS, while companies in the post-IFRS period
reported under IFRS. Earnings reported by German companies in the pre-IFRS period
were more value relevant than in the post-IFRS period.
As noted earlier, Barth et al. (2008) did research on the influence of IAS on accounting
quality. Their sample consisted of 21 countries including Germany. They found that firms
switching to IAS/IFRS showed a higher quality financial reporting. The results indicate
that IAS/IFRS adopters are less inclined to engage in income smoothing, which is the
exact opposite of Paananen and Lin’s (2009) findings.
From table 10 it becomes clear that Portugal, Spain and Greece (all PIGS member
countries) have the highest aggregate score, which means that income smoothing was
strongly present in the pre-IFRS period in these countries.
Table 10
Aggregate income smoothing score pre-IFRS period
Country
IS 1
IS 2
Aggregate
IS
2000 - 2004
0.367
2000 - 2004
-0.874
2000-2004
Spain
0.345
-0.794
13
Greece
0.284
-0.767
13
Italy
0.447
-0.758
10.5
Germany
0.562
-0.707
8
France
0.499
-0.668
8.5
Netherlands
0.574
-0.625
6.5
Sweden
0.795
-0.572
4
Belgium
0.543
-0.566
6.5
United Kingdom
0.616
-0.563
4
Austria
0.445
-0.548
7.5
Finland
0.669
-0.544
2.5
Denmark
0.580
-0.496
3
Ireland
0.488
-0.355
5
Mean
0.515
-0.631
7.5
Median
0.521
-0.599
7.0
Standard deviation
0.135
0.138
3.7
Min
0.284
-0.874
2.5
Max
0.795
-0.355
13.0
Portugal
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13
10.3
I NCOME SMOOTHING IN THE POST -IFRS PERIOD
Table 11 contains the income smoothing variables for the post-IFRS period. The variables
are calculated by using the same formulas used in the first leg of this research. In the postIFRS period Greece is the country with the highest aggregate income smoothing score,
followed by Portugal and Spain. Low IS1 values indicate that income is smoothed. From
table 11 can be derived that in the post-IFRS period income is more likely to be smoothed
in e.g. Portugal than Sweden. Large negative correlations between changes in firms’
accruals and cash flows (IS2) imply that income smoothing is more pervasive in e.g.
Greece and Portugal than in Denmark and Sweden.
Table 11
Aggregate income smoothing score post-IFRS period
Country
IS 1
IS 2
Aggregate IS
2005 - 2008
0.376
2005 - 2008
-0.879
2005 - 2008
13
Spain
0.452
-0.765
12
Greece
0.375
-0.942
14
Italy
0.474
-0.755
10.5
Germany
0.514
-0.621
6
France
0.495
-0.640
8
Netherlands
0.503
-0.654
8.5
Sweden
0.712
-0.438
1.5
Belgium
0.556
-0.636
6
United Kingdom
0.627
-0.598
2.5
Austria
0.453
-0.618
7.5
Finland
0.568
-0.641
6
Denmark
0.567
-0.362
3
Ireland
0.586
-0.662
6.5
Mean
0.519
-0.658
7.5
Median
0.509
-0.641
7.0
Standard deviation
0.093
0.150
3.8
Min
0.375
-0.942
1.5
Max
0.712
-0.362
14.0
Portugal
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10.4
S TATISTICAL ANALYSIS
This subsection will focus on the statistical analysis. Similar to the multiple regression used
in the first leg of this research, the dependent variable is the aggregate income smoothing
score and the independent variables are the three investor protection measures. After having
studied the results of the first part of the research, it became clear that there was no
significant relationship between income smoothing and the investor protection variables. So,
it is only rational to assume that there will be no significant relationship between the
dependent and independent variables in this part of the research. Nonetheless, I will leave
my expectations and assumptions for what they are and proceed with the statistical analysis.
I will start off by looking at the correlation matrixes for both the pre- and post-IFRS period.
10.4.1 C ORRELATION MATRIX PRE -IFRS PERIOD
The correlation matrix in appendix H presents the Pearson correlations between every pair
of variables as well as the one-tailed significance levels in the pre-IFRS period. It shows that
there is a negative correlation between the aggregate income smoothing score and the ex
ante private control of self-dealing index as well as with the ex post private control of selfdealing. These correlations however are not significant and neither is the correlation
between public enforcement and the aggregate income smoothing score. So, I cannot say
that these variables will predict the level of income smoothing in a country. The table also
shows that there is no multicollinearity; there are no correlations higher than 0.9
10.4.2 R EGRESSION ANALYSIS PRE -IFRS PERIOD
In addition to the relationship discussed earlier a regression analysis is performed to
establish whether or not income smoothing in the pre-IFRS period is influenced by the
level of investor protection in a country. Once again, I used a hierarchical multiple
regression, whereby the ex ante and ex post private control of self-dealing have been
entered first. The model summary in appendix H shows values of the multiple correlation
coefficient between aggregate income smoothing and the ex ante and ex post private
control of self-dealing indexes of 0.390, which is neither high or low. The 𝑅 2 value
indicates that only 15.2% of the variability in income smoothing is accounted for by these
two predictors. When the third investor protection variable is entered into the model the
𝑅 2 value increases to 18.3%. This means that 81.7% is not explained by these three
78 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
variables. Thus there are other variables that have an influence on income smoothing
occurrence.
10.4.3 C ORRELATION MATRIX POST -IFRS PERIOD
Appendix I shows the correlation matrix for the post-IFRS period. As you can see there is
a negative correlation between aggregate income smoothing score and the ex ante private
control of self-dealing index. There is also a negative correlation between the aggregate
income smoothing score and the ex post private control of self-dealing index. These
negative correlations are in accordance with my expectations; a higher level of investor
protection causes a decrease in income smoothing. There is a problem however, the
correlations are not significant. Thus, the predictors do not predict the dependent variable.
10.4.4 R EGRESSION ANALYSIS POST -IFRS PERIOD
The statistical analysis will continue with a hierarchical regression analysis. The model
summary of this multiple regression is presented in appendix I and shows that 16.7% of
the variation in income smoothing can be explained by the ex ante and ex post private
control of self-dealing indexes. When the third variable is entered into the model this
percentage increases to 18.3%, so the public enforcement index accounts for an additional
1.6% of the variation in income smoothing. The three predictors account for a relatively
low percentage of the variability in income smoothing. This means that there are other
variables that have an influence of the occurrence of income smoothing.
10.5
R ESULTS AND C ONCLUSIONS
Earlier on it was mentioned that several researchers have investigated the implementation
of IFRS on the occurrence of income smoothing. The expected outcome of IFRS adoption
was a decrease in information asymmetry as well as a decrease in earnings management
e.g. income smoothing. These expectations were formed because of the fact that IFRS are
more precise and they admit a limited number of options; principles-based standards were
implemented and the number of accounting alternatives was limited. However, the
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researchers did not have one unanimous result. Paananen and Lin (2008) and Barth et al.
(2008) for example both had different results. Therefore it seemed interesting to me to
once again examine the result of IFRS implementation in the pre- and post-IFRS period.
But after having performed the first leg of this research it became clear that the predictors
were not able to predict the occurrence of income smoothing. So I suspected that the
second leg of this research would not have significant results. Unfortunately, this was
indeed the case.
The correlation matrix in appendix H showed that in the pre-IFRS period there is a
negative relationship between the aggregate income smoothing score and both the indexes
for ex ante and ex post private control of self-dealing. This was in accordance with my
expectations. The third variable, public enforcement, however, has an positive correlation
with income smoothing, which implies that as public enforcement increases the level of
income smoothing increases as well. All three correlations are invalid, since none of them
are significant. The fourth hypothesis cannot be confirmed.
In order to test the fifth and final hypothesis the last hierarchical regression is performed.
The SPSS output can be found in appendix I. The correlation matrix presents the
relationships between the aggregate income smoothing score and the three investor
protection variables as well as the relationships between the predictors themselves. Once
again the correlation between income smoothing and both the ex ante and ex post private
control of self-dealing indexes are negative, but not significant. The correlation between
income smoothing and public enforcement is not alone positive but very low and not
significant as well. The fifth hypothesis cannot be confirmed.
The statistical analysis regarding the pre- and post-IFRS period confirmed the suspicions I
had after performing the first leg of this research. The predictors are not capable of
predicting the dependent variable, income smoothing. Thus, I am not at liberty to say
whether income smoothing has decreased or increased in the post-IFRS period. The
empirical evidence also showed that the predictors do not account for much of the
variation in income smoothing. This means that there probably are other predictors that
can better predict income smoothing.
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11.1
L IMITATIONS
The goal of this thesis was to investigate whether or not the level of investor protection
has an influence on the occurrence of income smoothing and if so, in what way. It has to
be acknowledged that there are certain limitations to this research, which will be discussed
here.
Capturing income smoothing is not an easy task, therefore I have chosen to measure
income smoothing by using the measures developed by Leuz et al. (2003). These measures
have proven to capture income smoothing in a sufficient way in their research as well as in
research done by Lee et al. (2008). The findings of this thesis rely on the ability of the
measures to capture income smoothing. There are other models available to measure
income smoothing. There is a chance that if another measure was used, the results would
have differed from the current findings.
Earlier on it was mentioned that financial institutions have been excluded from the sample.
Mainly because the two income smoothing measures used require variables that are not
applicable to financial institutions. For instance, financial institutions do not rely as much
on assets as for example a textile production company.
Since the level of income
smoothing of financial institutions is not measured, it is possible that banks, insurance
companies etc. in high investor protection countries engage in income smoothing on a
relatively large scale. If the empirical research had proven that there is a significant
negative correlation between income smoothing and investor protection these findings
could not be generalized to all firms in the respective countries. As I mentioned earlier the
sample consists of both large and small and middle-sized firms. Controlling insiders of
SMEs often have no incentives to smooth income, because these firms often do not have
to answer to shareholders in the same way large public firms need to answer to
shareholders. Table 2 shows that the mean firm size for this sample is 278.720, which is
clearly lower than 316.657, the mean firm size for the sample used by Leuz et al. (2003).
By including the SMEs in the sample there occurs a distortion in the income smoothing,
which could have caused the correlations to be not significant.
Furthermore it is necessary to mention that there are other factors that are complementary
to insiders managing income. It is not an easy task to fully control for the potential impact
of all factors affecting investor protection. Because of this, an endogeneity bias is possible.
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Throughout this thesis I have consistently argued that strong investor protection
discourages controlling insiders from cooking the books. The empirical analysis however,
has not provided any evidence to corroborate this. As stated earlier controlling insiders can
act in their own interest and benefit themselves at the stakeholders’ cost. These private
control benefits are not greatly appreciated by stakeholders and when detected,
stakeholders will take action. One can argue that strong investor protection can encourage
controlling insiders to smooth income in order to cover up their private control benefits. In
this scenario, controlling insiders will engage in income smoothing to cover up their
control benefits in an attempt to escape higher penalties. The empirical evidence from this
research cannot confirm nor deny either one of the scenarios.
11.2
S UGGESTIONS FOR FURTHER RESEARCH
This research included 31 countries, which means that countries with very different
institutional characters are examined. As you have read the results from the statistical
analysis indicate that there is no relationship between income smoothing and investor
protection. Even though the three investor protection variable incorporate aspects of the
legal tradition and legal origin of countries, it might be useful to include these two
variables separately in the multiple regression. By doing this different results could be
obtained which could actually confirm that there exists a significant negative correlation
between the occurrence of income smoothing and the level of investor protection.
In chapter 9.9 I argued that the not significant results obtained can be caused by the
differentiation in the research sample. The current sample consists of all companies in
Thomson One Banker that reported their financial data for at least three consecutive years,
financial institutions excluded. The result of this was that small and medium sized firms
were also included. Their inclusion might have caused a distortion and resulted in the not
significant correlations. Therefore I would suggest that future research on this subject
would be done with a sample consisting of large public firms.
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12
T HESIS C ONCLUSION
Earnings management can best be defined as a strategy of generating accounting earnings,
which is accomplished though managerial discretion over accounting choices and
operating cash flows (Phillips et al. 2003) as well as production and investment decisions
that reduce the variability of earnings. It comes in different forms one of which is income
smoothing. Earnings management is a widespread phenomenon. Several studies suggest
that earnings management can be limited by well-designed corporate governance
structures. Numerous researchers have examined the phenomenon that is earnings
management. Over the years several models have been developed to capture earnings
management some of which have been discussed in the literature review.
The goal of this thesis however, was to examine the relationship between the occurrence
of income smoothing and the level of investor protection in 31 countries. Previous studies
have shown that there is a significant relationship between these two variables. Leuz et al.
(2003) found evidence that earnings management is more pervasive in low investor
protection countries than in high investor protection countries. In high investor protection
countries there are strong and well-enforced outsider rights in place which limit the private
control benefits of controlling insiders. There are, broadly taken, two reasons why
controlling insiders engage in income smoothing. One, the goal is to gain private benefits
at the expense of shareholders or two; the goal is to communicate private information
about future earnings to outsiders. Whatever the reason is for engaging in income
smoothing, the reported financial data is not a true representation of the firms
performance.
Over the years regulators have attempted to harmonize the global reporting practices. The
International Financial Reporting Standards, which were formerly known as International
Accounting Standards (IAS), were chosen as the common language for financial reporting
by Europe and several other countries. IFRS are said to be more precise than local
standards and they admit a limited number of reporting options. Therefore it is argued that
the implementation of IFRS will lead to less income smoothing. With regard to these
expectations, two hypotheses were tested.
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In order to determine whether income smoothing is more pervasive in low investor
protection countries it is necessary to divide the sample countries in clusters. This is done
by means of a hierarchical k-means cluster analysis. The investor protection variables used
to predict the dependent variable in the multiple regression are derived from Djankov et al.
(2007). The income smoothing measures used are derived from Leuz et al. (2003). As you
may know by now, income smoothing can appear in two forms: real income smoothing
and artificial income smoothing. Therefore, a measure for each of these forms is used.
From these two individual measures the aggregate income smoothing measures is created
which is the dependent variable in the multiple regression. The statistical analysis showed
that there is no significant negative correlation between the dependent veriable, income
smoothing, and the predictors, ex ante and ex post private control of self-dealing indices
and the public enforcement index. None of the hypotheses could be confirmed. The
research results lead to believe that there is no relationship between income smoothing and
the level of investor protection and thus I am not able to say whether the occurrence of
income smoothing is lower in high investor protection countries than in low investor
protection countries. The second leg of this research looked at the occurrence of income
smoothing in the pre- and post-IFRS period. Because of the fact that there is no significant
relationship between the predictors and income smoothing, I cannot say that income
smoothing is less pervasive in the post-IFRS period.
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R EFERENCES
Armstrong, C.S., Barth, M.E., Jagolinzer, A.D. and Riedl, E.J. 2006. Market reaction to
the adoption of IFRS in Europe. Stanford Research paper.
Ball, R., Kothari, S., Robin, A., 2000. The effect of international institutional factors on
properties of accounting earnings. Journal of Accounting Research 31, 183-221.
Ball, R., Robin, A., & Wu, J. S. (2003). Incentives versus standards: Properties of
accounting income in four east asian countries. Journal of Accounting and Economics,
36(1-3), 235-270.
Barth, M.E., Elliott, J.A., Finn, M.W., 1995. Market Rewards Associated with Increasing
Earnings Patterns, working paper
Barth, M., Landsman, W. and Lang M., 2008. International Accounting Standards and
Accounting Quality. Journal of Accounting Research, 46, 467-497.
Bartov, E., 1993. The timing of asset sales and earnings manipulation. The Accounting
Review, 68, 840–855.
Bartov, E., Gul, F.A., and Tsui, J.S.L., 2000. Discretionary-accruals models
and audit qualifications. Journal of Accounting and Economics, 30, 421–452.
Bartov, E., and Mohanram, P.S., 2004. Private information, earnings manipulation, and
executive stock option exercises. The Accounting Review, 79, 889–920.
Beaver, W. H., McNichols, M. F., & Nelson, K. K. 2003. Management of the loss reserve
accrual and the distribution of earnings in the property-casualty insurance industry.
Journal of Accounting and Economics, 35, 347-376.
Beaver, W., McNichols, M., & Price, R. 2007. Delisting returns and their effect on
accounting-based market anomalies. Journal of Accounting and Economics, 43, 341-368.
Beidleman, C.R., 1973. A Theory of Income and Dividend Smoothing Based on
Incumbency Rents", Journal of Political Economy, 103, 75-93.
Beneish, M.D. 1998. A call for paper: Earnings management. Journal of Accounting and
Public Policy, 17, 85–88.
Bhattacharya, U., Daouk, H., Welker, M., 2002. The world price of earnings opacity. The
Accounting Review 78, 3, 641-678.
Boonlert-u-thai, K., Meek, G., Nabar, S., 2006. Earnings Attributes and Investor
Protection: International Evidence, International Journal of Accounting, 41, 327-357.
Braun, G. and Rodriguez, R., 2008. Earnings Management and Accounting Values: A Test
of Gray (1988), Journal of International Accounting Research, 7, 1-23.
85 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Brockman, P., and D.Y. Chung, 2008. Investor Protection, Adverse Selection, and the
Probability of Informed Trading, Review of Quantitative Finance and Accounting 2, 111131.
Burgstahler, D., Dichev, I., 1997. Earnings management to avoid earnings decreases and
losses. Journal of Accounting and Economics 24, 99–129.
Cahan, S., Liu, G. and Sun, J., 2008. Investor Protection, Income Smoothing, and
Earnings Informativeness. Journal of International Accounting Research 7, 1, 1-24.
Cohen, D.A., Dey, A., and Lys, T.Z., 2005. Trends in earnings management and
informativeness of earnings announcements in the pre- and post-Sarbanes Oxley periods.
Callao, S., Jarne, J. I., and Laínez, J. A. 2007. Adoption of IFRS in spain: Effect on the
comparability and relevance of financial reporting. Journal of International Accounting,
Auditing and Taxation, 16, 148-178.
Carmona, S., & Trombetta, M. 2008. On the global acceptance of IAS/IFRS accounting
standards: The logic and implications of the principles-based system. Journal of
Accounting and Public Policy, 27(6), 455-461.
Cornett, M., Marcus, A., and Teheranian, H., 2008. Corporate Governance and pay-for
performance: The impact of earnings management. Journal of Financial Economics 87,
357–373.
Daniel, N., Denis, D. and Naveen, L., 2008. Do firms manage earnings to meet dividend
thresholds? Journal of Accounting and Economics, 45, 2-26
Daske, H., Hail, C., Leuz, C. and Verdi, R., Mandatory IFRS reporting around the World:
Early evidence of the Economic Consequences. Journal of Accounting Research 46
Dechow, P., Sloan, R., Sweeney, A., 1995. Detecting earnings management. The
Accounting Review 70, 193–225.
Dechow, P., Skinner, D., 2000. Earnings management: reconciling the views of
accounting academics, practitioners, and regulators. Accounting Horizons 14, 235–250.
DeFond, M., Hung, M., & Trezevant, R. 2007. Investor protection and the information
content of annual earnings announcements: International evidence. Journal of Accounting
and Economics, 43(1), 37-67.
Djankov, S., La Porta, R., Lopez-de-Silanes, F., Shleifer, A. 2007. The law and economics
of self-dealing. Journal of Financial Economics, 88, 430-463
Durtschi, C. and Easton, P., 2004. Earnings management? Alternative explanations for
observed discontinuities in the frequency distributions of earnings, earnings changes, and
analyst forecast errors.
86 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Dye, R.A., 1988. A Theory of Income and Dividend Smoothing Based on Incumbency
Rents", Journal of Political Economy, 103, 75-93.
Eckel, N., 1981, The Smoothing Hypothesis Revisited, Abacus , 77, 28-40
Erickson, M., Hanlon M., and Maydew, E.L., 2006. Is There a Link between Executive
Equity Incentives and Accounting Fraud? Journal of Accounting Research 44, 113-143.
Ewert, R. and Wagenhofer, A., 2005. Economic effects of tightening accounting standards
to restrict earnings management. The Accounting Review, 80, 1101–1124.
Fama, E. and Jensen, M., 1983. Seperation of Ownership and Control. Journal of law and
economics 16.
Field, A., 2005. Discovering Statistics using SPSS, Sage publications Ltd., London
Fudenberg, D. and Tirole, J., 1995. A Theory of Income and Dividend Smoothing Based
on Incumbency Rents", Journal of Political Economy, 103, 75-93.
Gillan, S., 2006. Recent Developments in Corporate Governance: An Overview. Journal
of Corporate Finance 12, 381- 402.
Hail, L. and Leuz, C., 2006. International differences in the cost of capital: Do Legal
Institutions and Securities Regulation matter? Journal of Accounting Research 44, 485531.
Healy, P., 1996. A discussion of a Market-based Evaluation of Discretionary Accruals
Models. Journal of Accounting Research 34.
Healy, P., Wahlen, J., 1999. A review of the earnings management literature and its
implications for standard setting. Accounting Horizons 13, 365–383.
Hofstede, G.H. 1980, Culture's Consequences: International Differences in Work-Related
Values, Beverly Hills: Sage Publication.
Hofstede, G.H. 2001, Culture's Consequences: Comparing Values, Behaviors, Institutions,
and Organizations across Nations, Thousand Oaks: Sage Publication Inc.
Holthausen, R. W., Larcker, D. F., and Sloan, R. G. 1995. Annual bonus schemes
and the manipulation of earnings. Journal of Accounting and Economics , 19, 29‐ 74.
Imhoff, E., 1977. Income Smoothing - A Case for Doubt, The Accounting Journal, 85100.
Jacob, J., & Jorgensen, B. N. 2007. Earnings management and accounting income
aggregation. Journal of Accounting and Economics, 43(2-3), 369-390.
Jeanjean, T., & Stolowy, H. 2008. Do accounting standards matter? an exploratory
analysis of earnings management before and after IFRS adoption. Journal of Accounting
and Public Policy, 27, 480-494.
87 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Lee, E., Walker, M. and Christensen, H.B., 2008. Mandating IFRS: its Impact on the Cost
of Equity Capital in Europe, Research Report.
Kamin, J.Y. and Ronen, J., 1978. The Smoothing of Income Numbers: Some Empirical
Evidence on Systematic Differences Among Management-Controlled and OwnerControlled Firms, Accounting, Organizations and Society, 3, 141-53.
Kothari, S.P., Leone, A., Wasley, C.E., 2005. Performance matched discretionary
accruals, Journal of Accounting and Economics, 39, 1, 163-197
La Porta, R., Lopez-de-Silanes, F., Shleifer, A., Vishny, R., 1997. Legal determinants of
external finance. Journal of Finance 52, 1131–1150.
La Porta, R., Lopez-de-Silanes, F., Shleifer, A., Vishny, R., 2000. Investor protection and
corporate governance. Journal of Financial Economics 58, 3–27.
Leuz, C., Nanda, D., Wysocki P., 2003. Earnings management and investor protection: an
international comparison. Journal of Finacial Economics 69, 5-5-527.
Leuz, C. and Oberholzer-Gee, F. 2006. Political relationships, global financing, and
corporate transparency: Evidence from Indonesia. Journal of Financial Economics, 81,
411-439
Leuz, C. and Verrecchia, R.E. 2000. The Economic Consequences of Increased
Disclosure. Journal of Accounting Research, 38, 91-124.
Linck, J. S., Netter, J.M, and Yang, T. 2006. Effects and unintended consequences of the
Sarbanes-Oxley Act on corporate boards. AFA 2006 Boston Meeting
Merle, E., Hanlon, M., and Maydew, E.L., 2006. Is there a link between executive
compensation and accounting fraud? Journal of Accounting Research, 44, 113–144.
Merton, R.C., 1987. A simple model of capital market equilibrium with incomplete
information. Journal of Finance 42, 483–510
Nabar, S. and Boonlert-U-Thai, K.K., 2007. Earning Management Investor Protection, and
National Culture. Journal of International Accounting Research 6, 2, 35-54.
Nelson, M. W. (2003). Behavioral evidence on the effects of principles- and rules-based
standards. Accounting Horizons, 17, 91.
Paananen M. and Lin H., 2009. The Development of Accounting Quality of IAS and IFRS
over Time: The Case of Germany. Journal of international accounting research 8, 31-55
Pagano, M. and Volping, P., 2005. The political economy of corporate governance.
American Economic Review, 95, 1005-1030.
Phillips, J., Pincus, M. and Rego, S.O., 2003. Earnings management: New Evidence Based
on Deferred Tax Expense., The Accounting Review, 78, 491-521.
88 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
Ronen, J. and Yaari, V., 2008. Earnings management: emerging insights in theory,
practice and research.
Scholes, M.S., Wilson, G.P. and Wolfson, M.A., 1992. A Theory of Income and Dividend
Smoothing Based on Incumbency Rents, Journal of Political Economy, 103, 75-93.
Shleifer, A., Vishny, R., 1997. A survey of corporate governance. Journal of Finance 52,
737–783.
Soderstrom, N.S. and Sun, K.J. 2007. IFRS Adoption and Accounting Quality: A review.
European Acounting Review,16, 675-702.
Stolowy, H. and Breton, G., 2004. Accounts Manipulation: A literature review and
Proposed Conceptual Framework. Review of Accounting and Finance 3, 1.
Thomas, J. and Zhang, X., 2000. Identifying unexpected accruals: a comparison of current
approaches.
Tucker, J. and Zarowin, H., 2006. Does Income Smoothing Improve Earnings
Informativeness? The Accounting Review 81, 1, 251-270.
Van Tendeloo, B., and Vanstraelen, A. 2005. Earnings management under german GAAP
versus IFRS. European Accounting Review, 14, 155-180.
Wang, Z. and Williams, T.H., 1994. A Theory of Income and Dividend Smoothing Based
on Incumbency Rents, Journal of Political Economy, 103, 75-93.
Watts, R.L. and Zimmerman, J.L. 1986. Positive Accounting Theory, Prentice-Hall,
London.
Whittington, G. 2005. The adoption of international accounting standards in the European
Union. European Accounting Review 14, 127–153.
Wright, C., Shaw, J. and Guan, L., 2006. Corporate Governance and Investor Protection:
Earnings Management in the U.K. and U.S. Journal of International Accounting Research
5, 1, 25-40.
89 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX A
Author
S CHEMATIC OVERVIEW OF PREVIOUS STUDIES
Object of
Sample
Methodology
Outcome
44 countries,
Earnings
Earnings
Study
Cahan, Liu
Investor
and Sun
protection,
Informativeness:
informativeness
Income
Model of Collins et
more
al. (1994)
associated
(2008)
smoothing and
55,357 firm
Earnings
year
Informativeness
observations,
Income smoothing:
Contemporaneous
Spearman
correlation
Period:
Investor protection:
is
positively
with
income smoothing in
countries with strong
investor
protection
than it is in countries
with weak investor
protection
1993 - 2002
Index from La Porta
et al. (1998)
Nabar and
Earnings
Boonlert-U-
Management,
Thai
Investor
(2007)
30 countries,
Protection, and
70,208 firm-
National
year
Culture
observations,
Earnings
Earnings
Management:
management
Aggregate earnings
management score
by Leuz et al. (2003)
Investor Protection:
Period:
1990 - 1999
Indices from La Porta
et al. (1998)
National Culture:
influenced by both
investor
and
protection
culture.
Also,
earnings
management
is
relatively
in
low
countries with high
outside
investor
protection, high in
high
Hofstede scores
is
uncertainty-
avoidance countries
90 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
(1980)
and low in English
speaking-countries.
Wright,
Corporate
Shaw and
Governance
Guan
and Investor
(2006)
Protection
2 countries,
The Modified Jones
Earnings
model (1995)
management in the
U.S. and the U.K. is
not
92 U.K. firms,
similar
and
infrequent.
Period:
1997 - 2002
63 U.S. firms,
Period:
1981 - 1988
Leuz,
Earnings
Nanda and
Wysocki
(2003)
Earnings
Firms
management
management: Four
with strong investor
and investor
different country-
protection
level measures of
less
earnings
management
management.
firms
protection
31 countries,
8,000 firms,
Period:
1990-1999
Aggregate earnings
measurement score.
in
in
in
countries
engage
earnings
than
countries
with weak investor
protection.
Investor protection:
La Porta index (1998)
91 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX B
V ARIABLES DOWNLOADED FROM W ORLDSCOPE
The variables used in my research are collected from the Worldschope database. Because
the names from this database differ from the names used throughout my thesis, I include
this list.
For instance, “Operating Income” can be found in the database under the name
“OperatingIncomeAfterDepr”
Cash
=
CashAndSTInvestment
Operating Income
=
OperatingIncomeAfterDepr
Current Assets
=
TotalCurrentAssets
Current Liabilities
=
TotalCurrentLiabilities
Short term debt
=
STDebtAndCurPortLTDebt
Depreciation and
Amortization expense =
DepreciationDeplAmortExpense
Taxes Payable
=
IncomeTaxesPayable
Total assets
=
TotalAssets
92 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX C
H IERARCHICAL K-M EANS CLUSTER ANALYSIS
Table .1
Distances between Final Cluster Centers
Cluster
1
2
1
di
me
nsi
on
0
3
.804
2
.804
3
.936
.936
.805
.805
Table .2
Number of Cases in each
Cluster
Cluster
1
3.000
2
15.000
3
13.000
Valid
31.000
Missing
1.000
Table .3
ANOVA
Cluster
Mean Square
Error
df
Mean Square
df
F
Sig.
ex-ante
dealing
control
of
self
.857
2
.078
28
10.968
.000
ex-post
dealing
control
of
self
.100
2
.029
28
3.401
.048
2.102
2
.035
28
60.391
.000
public enforcement index
93 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX D
S CATTER P LOT
94 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX E
R ESIDUALS S TATISTICS
Residuals Statistics
Minimum
Predicted Value
Maximum
Mean
Std. Deviation
N
27.9956
127.2022
80.4516
29.57064
31
-107.53355
185.11377
.00000
86.32516
31
Std. Predicted Value
-1,774
1,581
.000
1,000
31
Std. Residual
-1,182
2,034
.000 ,949
Residual
a. Dependent Variable: aggregate IS
95 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
31
A PPENDIX F
C ORRELATION M ATRIX AND M ODEL S UMMARY R EAL S MOOTHING
Correlations
Ex ante private
control of selfdealing
IS1
Pearson Correlation
IS1
Sig. (1-tailed)
Public
enforcement
1.000
.150
.263
.001
Ex ante private control of
self-dealing
.150
1.000
.540
-.224
Ex post private control of
self-dealing
.263
.540
1.000
-.095
Public enforcement
.001
-.224
-.095
1.000
.
.211
.077
.498
Ex ante private control of
self-dealing
.211
.
.001
.113
Ex post private control of
self-dealing
.077
.001
.
.306
Public enforcement
.498
.113
.306
.
IS1
31
31
31
31
Ex ante private control of
self-dealing
31
31
31
31
Ex post private control of
self-dealing
31
31
31
31
Public enforcement
31
31
31
31
IS1
N
Ex post private
control of selfdealing
Model Summary
Model
R
R
Square
Adjusted
R Square
Std. Error of
the Estimate
1
.263a
.069
.003
.13819
2
.265b
.070
-.033
.14067
Durbin-Watson
d
i
m
e
n
s
i
o
n
0
1.887
a. Predictors: (Constant), ex post private control of self-dealing, ex ante private control of self-dealing
b. Predictors: (Constant), ex post private control of self-dealing, ex ante private control of self dealing, public
enforcement
c. Dependent Variable: IS1
96 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX G
C ORRELATION M ATRIX AND M ODEL S UMMARY A RTIFICIAL S MOOTHING
Correlations
Ex ante private
control of selfdealing
IS2
Pearson Correlation
1.000
-.047
-.032
.120
Ex ante private control of
self-dealing
-.047
1.000
.540
-.224
Ex post private control of
self-dealing
-.032
.540
1.000
-.095
.120
-.224
-.095
1.000
.
.401
.432
.260
Ex ante private control of
self-dealing
.401
.
.001
.113
Ex post private control of
self-dealing
.432
.001
.
.306
Public enforcement
.260
.113
.306
.
IS2
31
31
31
31
Ex ante private control of
self-dealing
31
31
31
31
Ex post private control of
self-dealing
31
31
31
31
Public enforcement
31
31
31
31
IS2
N
Public
enforcement
IS2
Public enforcement
Sig. (1-tailed)
Ex post private
control of selfdealing
Model Summary
Model
R
R
Square
Adjusted R
Square
Std. Error of
the Estimate
1
.048a
.002
-.069
.133582
2
.123b
.015
-.094
.135163
Durbin-Watson
dimension0
1.063
a. Predictors: (Constant), ex post private control of self-dealing, ex ante private control of
self-dealing
b. Predictors: (Constant), ex post private control of self-dealing, ex ante private control of
self-dealing, public enforcement
c. Dependent Variable: IS2
97 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX H
C ORRELATION M ATRIX AND M ODEL S UMMARY PRE -IFRS P ERIOD
Correlations
Aggregate IS
Pearson Correlation
Public
enforcement
1.000
-.365
-.340
.341
Ex ante private control of
self-dealing
-.365
1.000
.646
-.451
Ex post private control of
self-dealing
-.340
.646
1.000
-.408
.341
-.451
-.408
1.000
.
.100
.117
.116
Ex ante private control of
self-dealing
.100
.
.006
.053
Ex post private control of
self-dealing
.117
.006
.
.074
Public enforcement
.116
.053
.074
.
Aggregate IS
14
14
14
14
Ex ante private control of
self-dealing
14
14
14
14
Ex post private control of
self-dealing
14
14
14
14
Public enforcement
14
14
14
14
Aggregate IS
N
Ex post private
control of selfdealing
Aggregate IS
Public enforcement
Sig. (1-tailed)
Ex ante private
control of selfdealing
Model
R
R
Square
Adjusted
R Square
Std. Error of
the Estimate
1
.390a
.152
-.002
3.71500
2
.428b
.183
-.062
3.82337
Durbin-Watson
d
i
m
e
n
s
i
o
n
0
.962
98 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX I
C ORRELATION M ATRIX AND M ODEL S UMMARY POST -IFRS P ERIOD
Correlations
Aggregate IS
Pearson Correlation
Public
enforcement
1.000
-.408
-.279
.073
Ex ante private control of
self-dealing
-.408
1.000
.646
-.451
Ex post private control of
self-dealing
-.279
.646
1.000
-.408
.073
-.451
-.408
1.000
.
.074
.167
.402
Ex ante private control of
self-dealing
.074
.
.006
.053
Ex post private control of
self-dealing
.167
.006
.
.074
Public enforcement
.402
.053
.074
.
Aggregate IS
14
14
14
14
Ex ante private control of
self-dealing
14
14
14
14
Ex post private control of
self-dealing
14
14
14
14
Public enforcement
14
14
14
14
Aggregate IS
N
Ex post private
control of selfdealing
Aggregate IS
Public enforcement
Sig. (1-tailed)
Ex ante private
control of selfdealing
Model
R
R Square
Adjusted
R Square
Std. Error of the
Estimate
1
.408a
.167
.015
3.81400
2
.428b
.183
-.062
3.95993
Durbin-Watson
d
i
m
e
n
s
i
o
n
0
.975
99 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l
A PPENDIX J
E ARNINGS M ANAGEMENT M EASURES FROM L EUZ ET AL . (2003)
EM 1, EM 2 and the Aggregate EM score are calculated using the same formulas discussed in chapter 8.
Country
EM
EM 2
Austria
Greece
Korea
Portugal
Italy
Taiwan
Switzerland
Singapore
Germany
Japan
Belgium
Hong Kong
India
Spain
Indonesia
Thailand
Pakistan
Netherlands
Denmark
Malaysia
France
Finland
Philippines
United Kingdom
Sweden
Norway
South Africa
Canada
Ireland
Australia
USA
0.345
0.415
0.399
0.402
0.488
0.431
0.473
0.455
0.510
0.560
0.526
0.451
0.523
0.539
0.481
0.602
0.508
0.491
0.559
0.569
0.561
0.555
0.722
0.574
0.621
0.713
0.643
0.649
0.607
0.625
0.765
-0.921
-0.928
-0.922
-0.911
-0.912
-0.898
-0.873
-0.882
-0.867
-0.905
-0.831
-0.850
-0.867
-0.865
-0.825
-0.868
-0.913
-0.861
-0.875
-0.857
-0.845
-0.818
-0.804
-0.807
-0.764
-0.722
-0.840
-0.759
-0.788
-0.790
-0.740
Mean
Median
Standard
Deviation
Min
Max
0.541
0.539
0.100
-0.849
-0.861
0.056
0.345
0.765
-0.928
-0.722
Aggregate EM
score
28.3
28.3
26.8
25.1
24.8
22.5
22.0
21.6
21.5
20.5
19.5
19.5
19.1
18.6
18.3
18.3
17.8
16.5
16.0
14.8
13.5
12.0
8.8
7.0
6.8
5.8
5.6
5.3
5.1
4.8
2.0
100 | M a s t e r t h e s i s a c c o u n t i n g , a u d i t i n g a n d c o n t r o l