Accruals-based and Real Earnings Management
in relation to the introduction of IFRS
Results from French Civil Law countries
Erasmus School of Economics
Master Thesis
Abstract: In 2005, the use of the International Financial Reporting Standards (IFRS) became
mandatory for all European listed companies. With a combination of stringent rules and
subjectivity, the new accounting standards tried to decrease the use of earnings
management. Earnings management can be performed by two methods: accruals-based and
real activities. The main question of this thesis is about the influence the introduction of IFRS
in 2005 on the use of the two methods for performing earnings management. With data of
95 companies from the French Civil law Countries The Netherlands, Belgium and France, and
the use of the Modified Jones model (1995) and the model developed by Roychowdhury
(2006) is tried to answer this main question. The results of the research show a significant
increase of accruals-based and no significant difference in the use of real earnings
management by the introduction of IFRS in 2005.
Author
Mick Enthoven (302957)
Supervisor
Mr. van der Boom
Date
13-02-2012
1
Preface
To complete the Master Accountancy, Auditing and Control, the master thesis has to be completed
as final assignment. The thesis could not have been completed without the help and support of some
persons I would like to thank in this section. First, I would like to thank my supervisor mister van der
Boom for his help during the whole process of writing the thesis. His help and support contributed in
many ways to this thesis.
My parents are the next persons I would like to thank. Their patience and support during all years of
education as well as during writing this thesis kept me encouraged to complete this study and finish
this thesis.
2
Table of Content
1 Introduction of the thesis
p 5
p 5
p 7
p 9
p 9
p 10
1.1 Introduction
1.2 Research question and relevance
1.3 Contribution to prior research
1.4 Methodology
1.5 Structure of the thesis
2 Research Approaches
2.1 Introduction
2.2 General research approaches
2.2.1 Positive Theories
2.3 Earnings management specific approaches
2.3.1 Accrual-based approach
2.3.2 Real activities manipulation approach
2.3.2.1 Manipulation of operating activities
2.3.2.2 Manipulation of investing activities
2.3.2.3 Manipulation of financing activities
2.4 Summary
3 Earnings Management and IFRS
3.1 Introduction
3.2 Earnings management
3.2.1 Definition of the term earnings management
3.2.2 Methods of Earnings Management
3.2.2.1 Accruals-based earnings management
3.2.2.2 Real earnings management
3.2.3 Incentives
3.2.4 Directions of earnings management
3.3 IFRS
3.3.1 Introduction
3.3.2 Advantages and Disadvantages of the mandatory use of IFRS
3.4 Models for measuring the use of earnings management
3.4.1 Accruals Approach
3.4.2 Accruals models
3.4.2.1 Healy (1985)
3.4.2.2 DeAngelo (1986)
3.4.2.3 Jones Model (1991)
3.4.2.4 Modified Jones Model (1995)
3.4.2.5 Kothari et al (2005)
3.4.3 Real activities Approach
3.4.3.1 Real Activities Manipulation
3.4.3.2 Real Activities Manipulation Models
3.4.3.3 Roychowdhury (2006)
3.4.3.4 Gunny (2010)
3.5 Summary
3
p 11
p 11
p 11
p 12
p 12
p 13
p 13
p 14
p 14
p 14
p 15
p 16
p 16
p 16
p 16
p 18
p 18
p 18
p 19
p 20
p 22
p 22
p 22
p 24
p 24
p 24
p 25
p 26
p 26
p 27
p 28
p 29
p 29
p 30
p 30
p 32
p 35
4 Related researches
p 38
p 38
p 38
p 44
p 47
4.1 Introduction
4.2 Earlier conducted researches
4.3 French Civil Law factors
4.4 Summary
5 Hypotheses
p 50
p 50
p 50
p 51
5.1 Introduction
5.2 Hypotheses development
5.3 Summary
6 Research Design
6.1 Introduction
6.2 Models for detecting Earnings Management
6.2.1 Modified Jones Model (1995)
6.2.2 Roychowdhury (2006)
6.3 Multiple Regression
6.4 Data sample
6.5 Data attainability
6.6 Summary
7 The Empirical Research
7.1 Introduction
7.2 Total amount of earnings management
7.2.1 Accruals-based earnings management coefficients
7.2.2 Real earnings management coefficients
7.3 Multiple regressions
7.3.1 Total amount of earnings management
7.3.2 Accruals-based earnings management
7.3.3 Real earnings management
7.4 Summary
8 Summary, Conclusions and Analysis
p 53
p 53
p 55
p 55
p 58
p 60
p 63
p 64
p 64
p 67
p 67
p 67
p 67
p 69
p 73
p 74
p 77
p 79
p 84
p 87
p 87
p 88
p 90
p 91
8.1 Summary of previous chapters
8.2 Answer of the main question
8.3 Limitations of this research
8.4 Further research
References
p 93
Appendices
Appendix 1 – Literature review
Appendix 2 – Companies used for this research
Appendix 3 – Results from SPSS
4
p 96
p 99
p100
1 Introduction of the thesis
1.1 Introduction
It is the 7th of May 2010; all prime ministers of the European countries agreed on providing Greece an
80 billion euro loan to improve their economic situation. Overspending increased the national debt
of Greece and got the country in a bad economic situation. In order to help Greece with its debt, the
International Monetary Foundation (IMF) supported Greece in November 2010 again with a loan of
30 billion euro and stated that Greece is increasing its economic stability by executing savings and
reformations. During this process of reformations, the annual deficit in 2010 of Greece appeared to
be even bigger than the European Community expected; a deficit exists of 10.5 percentage of Gross
Domestic Product (GDP) instead of the expected 9.6 percentage. As a consequence of this
unexpected higher level, the total debt of Greece became 143 percentage of the GDP, which implied
that their debt was bigger than the magnitude of their economy. When this news became public,
European Commissioner Olli Rehn of the Monetary Policy claimed that this unexpected higher level
of debt was not due to the detection of creative accounting.1 This was signalled by Commissioner
Rehn because values of the financial statements of Greece had been adjusted during their
examination for being admitted to the Euro. With the help of Goldman Sachs, the reported national
deficit was stated much lower than it truly was. By a financial construction provided by Goldman
Sachs, a part of Greek debt was not titled as national debt of Greece but as a debt of various banks
for the first fifteen years of the loan.2
With the use of creative accounting, in addition called earnings management, Greece adjusted its
financial situation and so misled the other European countries during their application for the Euro.
This manipulation of financial values and deception is considered black earnings management (Ronen
and Yaari 2008, p25). The distinction of whether earnings management is white, grey or black as
Ronen and Yaari (2008) distinguish earnings management, can be made by focussing on the
motivation behind the use of it. Considering the example of Greece, the intention of Greece was to
mislead the other countries in the European union in order to be admitted to the Euro, what is titled
by Ronen and Yaari (2008) as black earnings management. In order to be able to make a distinction in
earnings management Ronen and Yaari (2008) use the definition of Healy and Wahlen (1999) to
judge about a situation:
1
NOS file debt crisis - http://nos.nl/artikel/235738-tekort-griekenland-valt-hoger-uit.html - read 16th of May
2012
2
http://www.accountant.nl/Accountant/Nieuws/Goldman+Sachs+helpt+bij+creatief+boekhouden+Grieke.aspx
5
‘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 numbers’ (Healy and Wahlen 1999, p 368)
The important distinction made in the definition of Healy and Wahlen (1999) compared to other
definitions of earnings management, is that earning management is used to mislead other
stakeholders about the financial situation of the company. The example about Greece reveals the
deception of the other countries in the European Union by using earnings management. This
example is about misleading countries; these countries are ‘stakeholders’ of Greece by having
interest in the financial situation of Greece. A bad financial situation or maybe even bankruptcy may
influence the financial situation of the other countries in the European Union. This example can be
compared on micro-level by companies that have interest in a company with a bad financial
situation. The same can be performing with the misleading of the countries in the European Union
during the application of Greece to the Euro; managers may adjust the financial situation of a
company in order to mislead their stakeholders.
In order to abandon or at least reduce to possibilities of managers to mislead the stakeholders,
accounting standards are provided. These standards should ensure stakeholders that the numbers
provided in the financial statements present a true and fair view of the financial situation of a
company. One of the recent attempts of standard setters to provide this assurance is the
introduction of the International Financial Reporting Standards (IFRS) in 2005 which became
obligatory to adopt by all the stock exchange quoted companies in the European Union.
The IFRS were introduced to strengthen uniformity in accounting rules and regulations in order to
make the financial statements of companies more comparable and transparent. These aims of IFRS
should create more value for stakeholders by being better informed about the financial situation of a
company. These aims should be achieved by IFRS with the use of fair-value as most important
principle (EC No 1606/2002, p243/2).
Despite the introduction of these new standards, managers will still have incentives to use earnings
management; to achieve a personal and/or company target. To accomplish this target, earnings
management can be executed by using the method of adjusting accruals or real activities3. In
previous researches about the use of earnings management, generally only the accruals-based
3
Both real earnings management and real activities manipulation will be used to refer to the method of
earnings management by adjusting real business activities
6
method is used to detect the use of earnings management. But Graham et al. (2005) suggest that
firms switched to managing earnings by using real activities, possibly because this method, although
more costly, is likely harder to detect. This statement is strengthened by the following sentences of
Graham et al. (2005):
‘We find strong evidence that managers take real economic actions to maintain accounting
appearances. In particular, 80% of survey participants report that they would decrease discretionary
spending on R&D, advertising, and maintenance (…) to meet an earnings target. More than half
(55.3%) state that they would delay starting a new project to meet earnings target, even if such delay
entailed a small sacrifice in value (…).’ (Graham et al. 2005, pp. 32-35)
This possible switch by using more real activities for earnings management relative to accruals-based
earnings management is the origin of this research. First the influence of IFRS on the total amount of
the use of earnings management will be checked, before the possible substitution between the two
methods for managing the earnings will be investigated.
1.2 Research question and relevance
One of the goals of IFRS, as signalled in the introduction, is creating more transparency and reliability
of the financial statements which should have an effect on the (less) use of earnings management.
IFRS changed the regulations by combining rigid rules with subjective valuations in the valuation of
assets and liabilities for the composition of the financial statements.
Although IFRS have the objective to create a fair and true view of the financial situation, managers
will still search for possibilities to show a better financial position of a company; for their own or
company’s interest. According to Graham et al. (2005), real activities are used to manage earnings,
while only the accruals-based method generally was used to detect the use of earnings management.
In this thesis, the influence of the introduction of IFRS in 2005 on the use of the two methods for
detecting earnings management is investigated. With the data from three French Civil law countries
The Netherlands, Belgium and France, the possible influence of the introduction of IFRS is
investigated. The specific use of three French Civil law countries might have influence on the results
of the research by the characteristics of this type of law. The characteristics of the different types of
laws and the possible influence of the characteristics of the French Civil law on the outcome will be
commented in section 4.3.
7
The introduction of IFRS, the use of two methods for detecting earnings management and the use of
data from French Civil law countries; all these aspects provide the following main question of this
thesis:
Does a relation exists between the introduction of IFRS in 2005 and the choice of method of the use
of earnings management, accruals-based or real activities manipulation, in the French Civil law
countries The Netherlands, Belgium and France?
The answering of the main question will be supported by first answering the following sub-questions
of the thesis:
1
What general and specific research approaches are most appropriate for this thesis?
2
What are the definition and the purpose of the International Financial Reporting
Standards (IFRS)?
3
What is the influence of IFRS on the valuation of assets and liabilities in the financial
statements?
4
What is the content of the term earnings management?
5
In which way is the use of earnings management detected and measured?
6
What do prior literature and researches communicated about the relationship of IFRS
and the use of earnings management?
7
Which specific factors of French Civil law countries may influence the use of earnings
management and the transition to IFRS?
8
What hypotheses are formulated for this thesis?
9
In which way is the empirical part of the research designed?
10 What is the result of the empirical research?
11 What is the conclusion of this research?
The possible influence of the new accounting standards on the use of the different methods of
earnings management is what makes this research interesting. Has the introduction of IFRS
decreased the use of earnings management and what is its influence on the use of the two main
methods for managing the earnings? These possible changes in the use of earnings management can
be used to create a better understanding on in which way managers determine when and in which
way earnings are managed. The focus on French Civil law countries will present more insight on the
possible influence of the characteristics of this type of countries on the total amount of the use of
earnings management and the choice of method for performing earnings management.
8
1.3 Contribution to prior research
The contribution of this thesis to prior research will be that the possible influence of IFRS on the use
of earnings management and the method for executing this will be investigated, distinctive the check
on real activities manipulation. Accruals-based earnings management has already been researched in
other studies, while the use of real earnings management in scientific economic researches is relative
new. Lippens (2010) has performed a research on the influence of the introduction of IFRS on the use
of accruals-based and real earnings management. The main difference with this research is the data;
Lippens uses data from 6 countries, while this thesis specifies on three French Civil law countries. The
two methods of the use of earnings management in combination with specific factors like the
strength of the legal system in French Civil law countries presents more insight on which factors
might influence on the choices of managers to manage the earnings.
The focus on French Civil law countries presents a better view on what influence factors like the legal
and the political system in the countries might have or did have on the implementation of IFRS and
the use of different methods for managing the earnings. As will be commented in chapter 4, factors
like being a ‘code’ or ‘common’ law country for example will possibly have their influence on the
results. But this type of research in addition has its limitations; the results that are found will not be
generalizable for other types of law countries.
1.4 Methodology
In order to execute the research, the positive approach is chosen. The different general research
approaches that can be used for research are explained in more detail in chapter 2. The use of the
positive approach can be specified with the use of the Positive Accounting Theory (PAT) for this
research. The describing and predicting focus of this kind of research method was decisive in
choosing for the PAT-approach. As a component of the PAT, the agency theory has its influence in
this research by assuming that managers act with self-interest and that they do not always take into
account what possible influence their actions might have on other stakeholders. Acting in selfinterest can be one of the motivations for managers to use earnings management in its various ways.
Next to the determination of the general and specific approaches are used for this thesis, the
methods for detecting accruals-based and real earnings management is determined. Earnings
management by accruals will be measured by using the Modified Jones model (1995) and real
earnings management by the model developed by Roychowdhury (2006). The process for deciding to
choose for these models will be commented in sections 3.4.2 and 3.4.3.
9
These models will be used on a sample of 95 companies which contain listed companies from The
Netherlands, Belgium and France that meet the established criteria. With the use of the Wharton
Research Data Service (WRDS), the companies that meet the requirements are selected before the
data of these companies is obtained from the Thomson One Banker database. With the data, the
Modified Jones model (1995) and the model developed by Roychowdhury (2006) are executed.
These indications of the use of earnings management will be used to check for the possible influence
of the independent variables country, accounting standards and size on the dependent variables
total amount of the used earnings management, accruals-based and real earnings management. In
order to draw a conclusion about the use of earnings management in total and the possible
substitution effect in the methods of executing earnings management due to the introduction of
IFRS, the possible influence is checked by multiple regression.
1.5 Structure of the thesis
In order to get to an answer on the main-question of the thesis, each chapter provides an answer to
one or more of the sub-questions that are listed in the introduction. In chapter 2, sub-question 2
about research approaches, both general and the term earnings management-specific are
commented before sub-questions 3 and 4 are answered with the theoretical framework of the thesis;
earnings management and IFRS described in chapter 3. To answer subs-questions 6 and 7, after the
theoretical framework is provided, in chapter 4 prior researches and specific factors are reviewed.
After the review of all the relevant literature in the first four chapters, the chapters 5-8 focus on the
research design, the results of the research and the conclusions. Sub-question 8, which is about
developing the hypotheses, is answered in chapter 5. Next, sub-question 9 about the design of the
research will be answered in chapter 6. In chapter 7 the results of the empirical part of the research
will be provided, which is the answer on sub-question 10 before sub-question 11 about the
conclusion is answered in chapter 8.
10
2 Research Approaches
2.1 Introduction
Research in the field of accounting can be performed on many topics and each topic can be
approached from different angles. By using a different approach and angle, different aspects of a
topic will be investigated and highlighted. In this chapter, general- and earnings management
specific-approaches will be presented to present an overview on what approaches can be chosen
from and which approaches are chosen in this research.
2.2 General research approaches
On accounting different perspectives exist; it can be explaining, predicting, prescribing or describing
aspects and phenomena. Because no universal approach exists, several general research approaches
in the field of accounting are developed. According to Deegan and Unerman (2011), theories of
accounting can be divided in (1) inductive accounting theories, (2) predictive accounting theories and
(3) prescriptive (normative) accounting theories.
The inductive theories of accounting are the development of ideas or theories through observation.
By observation, common practices are codified in the form of doctrines or conventions of accounting
(Deegan and Unerman 2011, p 7).
The second type of accounting theories are the predictive theories which focus on explaining and
predicting, rather than prescribing accounting practices. Predicting and explaining phenomena by
observation, what inductive and predictive theories do, are classified as positive research
approaches.
The last type of accounting theories are prescriptive (normative) which are not based on
observations but on what the researcher believes should occur. These theories are based on norms,
values and beliefs held by the researchers proposing the theory (Deegan and Unerman 2006, p377378). A limitation of using these theories is that research is not necessarily based on observations
and consequently cannot be evaluated on whether the theory reflects actual accounting practice.
When comparing these different types of theories for this research, the positive research and more
specific the predictive theories of accounting will be most appropriate. With the use of data and
models, possible change in the total use of earnings management and a possible substitution effect
in the earnings management methods will be explained by the introduction of the new standards.
Having determined that the Positive approach is chosen for this research, this type of approach will
further be commented in the next section.
11
2.2.1 Positive Theories
Positive theories try to explain observed phenomena without indicating in which way things should
be (Schroeder, Clark, Cathey 2010, p 123). This explanatory attribute of positive theories continues
on what already was concluded in the previous section and strengthens the choice of the positive
theory in this research. The positive theories can be divided in the legitimacy, institutional,
stakeholder and the positive accounting theory (Deegan and Unerman 2011, p 255). The political
economy theories, as the legitimacy and stakeholder theories by Gray et al. (1996) together are is
defined as ‘the social, political and economic framework within which human life takes place.’ (Gray
et al. 1996, p 47). The society, politics and economics are inseparable, consequently all these aspects
should be considered when solving economic issues (Deegan and Unerman 2011, p 322).
The Positive Accounting Theory (PAT) ‘is concerned with explaining accounting practices. It is
designed to explain and predict which firms will and which firms will not use particular method (…)
but it says nothing as to which method a firm should use.’ (Watts and Zimmerman 1986, p 7). PAT is
about individuals and their relationship in providing resources to an organization and in which way
accounting is used by managers to assist in the functioning of these relationships (Deegan and
Unerman 2011, p256).
When the different research approaches are compared within the field of accounting, the conclusion
is that the Positive research approach with its fundament of observation and explanation is the most
appropriate approach in this research. More specifically, the Positive Accounting Theory (PAT)
developed by Watts and Zimmerman (1978) is the most appropriate specific approach because of its
explaining and predicting focus on the accounting practice. This explaining and predicting of
phenomena in this research is performing by checking the influence of the introduction of IFRS on in
which way and on which level the published earnings are managed.
2.3 Earnings management specific approaches
After the determination before that the Positive Accounting Theory (PAT) is most appropriate as
general approach, the focus will be on more specific approaches. In which way are the published
earnings managed? Which items in the financial statements are used to perform earnings
management? In this section, the accruals-based and real method for detecting earnings
management will be presented.
12
2.3.1 Accrual-based approach
The focus of the accruals-based method for detecting the use of earnings management can be on
different aspects of the accruals; the aggregation of the accruals, specific accruals and the
distribution of the accruals.
When the focus is on the aggregate accruals, the total amount of the accruals and the change in this
total amount are the measures of managements’ discretion over the earnings (McNichols 2000, p
316). In order to check for the economic circumstances of a company, important aspects that should
be checked for are non-discretionary factors like sales and Property, Plant & Equipment (PP&E) in
relation to the total accruals (McNichols 2000, p 316).
Research on specific accruals focuses on a single accrual that is sizable and requires substantial
judgment. McNichols (2000) points out that prior studies have found that managements’ discretion is
likely to be reflected in a specific accrual or set of accruals like bad debts, loss reserves and loan
losses for example (McNichols 2000, p 316).
The third and last approach for examining accruals is the examination of the statistical properties of
earnings to identify behaviour of earnings around a specified benchmark such as zero earnings or
prior quarters’ earnings. This approach developed by Burgstahler and Dichev (1997) and DeGeorge et
al. (1999) tests whether the amounts that differ from the benchmark are distributed smoothly or
reflect discontinuities (McNichols 2000, p 316).
When these approaches are compared to be used in this research, the finding is that the aggregate
accruals, the total amount of accruals, in this research will be used. The total amount of accruals will
be used to determine the total amount of earnings management by the accruals-based method.
Models like the Jones model (1991) and the Modified Jones model (1995) are aggregate accruals
models that focus on the residual of the regression of the total accruals controlling for
nondiscretionary factors (McNichols 2000, p317). Various models for detecting accruals-based
earnings management will be presented in section 3.4.
2.3.2 Real activities manipulation approach
The other general method for detecting the use of earnings management is by checking real
activities. Like the accruals-based method, the real activities manipulation can be executed in various
ways. The manipulation of earnings through this method can be executed by using operating,
investing and financing activities. The real activities manipulation method in more detail will be
13
explained by focussing on which activities and related financial statement items by managers are
manipulated.
2.3.2.1 Manipulation of operating activities
Operating activities generate the in- and outflows of cash in a company which determine the net
income of a company. These cash flows can be manipulated by adjusting the amount of discretionary
expenditures with the Research & Development (R&D) and Selling, General and Administrative
(SG&A) as most common manipulated expenditures. When expenditures like R&D do not
immediately generate revenues and income, it is likely that these discretionary expenditures are
used for real earnings management (Roychowdhury, 2006 p 340).
Next to the use of expenditures for real activities manipulation, sales and production are in addition
used to adjust the financial numbers. Roychowdhury (2006) defines sales manipulation as ‘(…)
managers’ attempts to temporarily increase sales during the year by offering price discounts or more
lenient credit terms.’ (Roychowdhury 2006, p 340)
Such price discounts should result in more cash inflow, but with a lower margin which will cause an
abnormal high ratio of production costs relative to sales (Roychowdhury 2006, p 340). In contrast to
the declined margins by giving price discounts on products, managers can increase the margin on
products by increasing the total production. When a firm produces more goods, fixed overhead costs
can be divided over a larger number of units which will decrease the cost of goods sold (COGS) and
consequently increase the firms’ operating margin. This is not allowed according to the accounting
principles, because it is in conflict with the matching principle; production and holding costs of the
over-produced items should be taken in the same period of the sales (Roychowdhury, 2006 p 340).
2.3.2.2 Manipulation of investing activities
Earnings in addition can be managed by using the income from sales of long-term assets for adjusting
earnings. Bartov (1993) concludes that managers choose the timing of asset sales that the income
from these sales smoothens inter-temporal earnings changes and mitigates accounting-based
restrictions in debt covenants (Bartov 1993, p 854). Other investing transactions that are likeable for
manipulation are business acquisitions, leases, issuance of convertible debt and equity investments.
These transactions are performed in order to increase the reported earnings and/or improve the
leverage ratios (Xu, Taylor, Dugan, 2007 p 210).
2.3.2.3 Manipulation of financing activities
For the financing of a company, stocks can be issued on the stock market. These stocks can be used
14
as an instrument of manipulation by a company by repurchasing these stocks which decreases the
number of common shares outstanding and consequently may increase the earnings per share (Xu,
Taylor, Dugan, 2007 p211). But this statement only holds under the condition that the price-earnings
ratio is larger than the foregone rate of return on cash paid for the repurchase (Guay 2002; Hribar et
al. 2006). Hribar et al. (2006) find a disproportionately large number of Earnings per Share increasing
stock repurchases among firms that would have missed analyst expectations without these
repurchases.
Not only stocks itself, but in addition stock options can be used for manipulation by adjusting the
granting of stock options to maintain a trend of increasing earnings and to meet analysts’
expectations (Xu, Taylor, Dugan, 2007 p 212).
2.4 Summary
In order to answer sub-question 1 about the general and specific research approaches, the general
and the more specific accounting approaches that can be used in research have been presented.
With the focus on the general research approaches in the accounting, the normative and the positive
theories have been commented and the finding is that the positive theory and more specific the
Positive Accounting Theory (PAT) is the most appropriate approach in this research. With the use of
the PAT, observations will be used to check the possible influence of the new standards on the use of
earnings management.
After defining the general research approach, more specific approaches were commented to
understand what approaches by managers are used to manage the published earnings. Two general
methods exist to manage the published earnings; by accruals and real activities. The aggregation-,
specific or statistical proportions of accruals are used for management of the published earnings.
Focussing on real earnings management, operating, investing and financing activities can be used. In
this research, not all activities will be used to detect the use of real earnings management. Like
Roychowdhury (2006), only the manipulation of the operating activities is used for the detection of
real earnings management. The two general methods for detecting earnings management will be
further explained in section 3.2.2 and 3.2.3
15
3 Earnings Management and IFRS
3.1 Introduction
In this chapter the foundation of this research is further developed. Chapter 2 was about the
approaches that in this research will be used, while in this chapter the International Financial
Reporting Standards (IFRS) and the use of earnings management with its different aspects will be
presented. The content of the term earnings management is described in section 3.2 with the focus
on the definition, types, incentives, directions and methods of executing it. Section 3.3 is about IFRS
and the positive and the negative aspects of implementing these standards. Several developed
models for detecting the use of earnings management in section 3.4 will be presented to determine
together with related, earlier conducted researches which models will be used.
3.2 Earnings management
Earnings management is about influencing the published financial numbers to create an adjusted,
more likeable, financial situation than the actual situation. The use of earnings management is a
topic that has already been broadly commented in many studies, each using different aspects of it.
Researches have focused on the definition (Ronen and Yaari 2008; Healy and Wahlen 1999; Schipper
1989), on the incentives of persons (Healy and Wahlen 1999; Burgstahler and Eames 2006) and on
the directions of the use of earnings management (Burgstahler and Dichev 1997; Scott 2008). In
order to create a better understanding on what earnings management is about, why it is used and
what the consequences are of the use of it, all these aspects will be commented.
3.2.1 Definition of the term earnings management
The first aspect in the understanding of the term earnings management is the definition. Various
definitions exist which all have their own accentuation on specific parts of the broad topic earnings
management.
“It is always difficult to frame a useful definition for a broad subject. Precise definitions are likely to be
inadequate at best, and often positively misleading” (Paton 1922, p 3)
Supported by this statement of Paton (1922), Ronen and Yaari (2008) introduced three types of
earnings management distinguished by the intention of the manager. As described in chapter 1,
Ronen and Yaari (2008) distinguish the use of earnings management in white, grey or black. The
distinction made by Ronen and Yaari (2008) is executed by using the definition of Healy and Wahlen
(1999) as fundament (Ronen and Yaari 2008, pp. 25-26).
16
‘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 numbers’ (Healy and Wahlen, 1999, p 368)
Ronen and Yaari (2008) describe white earnings management as taking advantage of the flexibility in
the choice of accounting treatment to signal managers’ private information on future cash flows. This
type of earnings management is a legitimate way of using earnings management by adjusting to the
situation of the company in order to improve the quality of the financial statements (Ronen and Yaari
2008, p 25).
Grey earnings management is choosing an accounting treatment that is either economically efficient
or opportunistic by maximizing the utility of the management. The intention of management in this
situation determines whether this type of earnings management can be defined ‘good’ or ‘bad’.
The last type of earnings management defined by Ronen and Yaari (2008) is black earnings
management. This type is about of using practices to misrepresent or reduce transparency of the
financial reports, mostly referred to as fraud (Ronen and Yaari 2008, p 25). The definition of Healy
and Wahlen (1999) identified black earnings management because stakeholders are misled.
All definitions of the term earnings management can be divided in these types of earnings
management described by Ronen and Yaari (2008), differencing in accentuation. Schipper (1989)
accentuates that earnings management is a purposeful action of managers by defining earnings
management as
“...a purposeful intervention in the external financial reporting process, with the intent of obtaining
some private gain (as opposed to, say, merely facilitating the neutral operation of the process) (...)
Under this definition, earnings management could occur in any part of the external disclosure
process, and could take a number of forms. A minor extension to the definition would encompass
“real” earnings management, accomplished by timing investment or financing decisions to alter
reported earnings or some subset of it” (Schipper 1989, p 92)
The definition provided by Schipper (1989) describes a purposeful intervention with the intention of
obtaining some private gain which can be qualified, when referring to Ronen and Yaari (2008) as
black earnings management. The reason choosing for the definitions of Ronen and Yaari (2008) and
Schipper (1989) is that both definitions classify the use of earnings management good or bad by the
motivation behind the use of it. Because in this research is assumed that earnings management is
17
used purposefully to obtain private and/or business gain, the definition of Schipper (1989) is added
to highlight this plus that Schipper (1989) signals the use of real activities to manage the published
earnings.
3.2.2 Methods of Earnings Management
Before the definition of the term earnings management has been determined, next the methods for
managing earnings will be commented. In section 2.3 these methods were already presented by
defining which actions and aspects of the financial statements and transactions are used to perform
earnings management. In this section the two methods, accruals-based and real activities
manipulation are shortly commented.
3.2.2.1 Accruals-based earnings management
Accruals-based earnings management is managements’ exploitation of accounting discretion that is
allowed under General Accepting Accounting Principles (GAAP) (Xu, Taylor, Dugan 2007 p 196). This
accounting discretion is about selecting accounting methods and the estimation of numbers in order
to influence the financial values. The durability of assets can be adjusted in order to decrease or
increase the costs of an asset per year by dividing the total costs over a different total number of
years. Another balance sheet item for accounting discretion is account receivable. A risk exists that
debtors cannot pay their (total) debt; consequently estimations have to be performed concerning
how much of the debt is likely to be received. The determination of this amount is subjective so
amounts can easily be adjusted by managers (Epe and Koetzier 2002, p 33). These and other
accounts that are used for manipulation can be found in the models that focus on detecting the use
of accruals-based earnings management.
3.2.2.2 Real earnings management
Real earnings management is the attempt of management to alter reported earnings by adjusting
timing and scale of underlying business activities. Examples of these real business activities are R&D
expenditures, capital investments, and the production, sale and disposal of long-term assets ( Xu,
Taylor, Dugan, 2007 p196). Roychowdhury (2006) agrees with the illustration of Xu, Taylor and Dugan
(2007) by renaming real earnings management into real activities manipulation to emphasize that
real activities are involved in the management of the earnings.
18
Real activities manipulation is defined by Roychowdhury (2006) as
“(…) departures from normal operational practices, motivated by managers’ desire to mislead at least
some stakeholders into believing certain financial reporting goals have been met in the normal course
of operations.” (Roychowdhury 2006, p 337)
The different models that are developed to detect accruals-based and real earnings management will
be commented in section 3.4.
3.2.3 Incentives
The choice of method for executing earnings management might depend on the incentive a manager
has with the execution of it. Whether to use, how much use and in which direction earnings are
managed; it all depends on the intention of the manager. What does the manager want to achieve
with managing the earnings? According to Healy and Wahlen (1999), three incentives exist for
managing earnings: (1) capital market incentives, (2) contracting incentives and (3) regulatory
incentives.
The capital market incentive is about the expectation and the valuation of investments by investors
and by financial analysts. Accounting information is an important tool to support a proper valuation
of stocks (Healy and Wahlen 1999, p 10). Healy and Wahlen (1999) conclude after their review on the
capital market expectation and the valuation that some firms appear to manage earnings for stock
market reasons. This adjustment of accounting numbers to influence investor perceptions can in
addition be used at take-overs, hostile or structured. An acquiring firm may overstate their
performance to boost their share price and reduce the share exchange ratio (Palepu, Healy and Peek
2010, p 97).
The second incentive provided by Healy and Wahlen (1999) is about contracts written in terms of
accounting numbers. In order to align the incentives of the management and of the external
stakeholders, management compensation contracts are used (Healy and Wahlen 1999, p 375).
Although these contracts should align the different interests, Healy and Wahlen (1999) find evidence
for using accounting judgement by managers to increase the earnings-based bonus awards. Next to
managers’ contracts written in accounting numbers can debt covenants and the contractual
obligations in these covenants be an incentive for managers to manage the published earnings.
When managers are close to violating the debt covenants, they have an incentive to select
accounting policies and estimates to reduce the probability of covenant violation (Palepu, Healy and
Peek 2010, p 97). Focussing on accounting numbers, managers in addition may choose reporting
19
methods considering tax payments. In some countries a direct link exists between the financial
reporting and the tax reporting which creates incentives to forgo tax reduction in order to report
higher profits (Palepu, Healy and Peek 2010, p97).
The third incentive communicated by Healy and Wahlen (1999) is about the industry-specific and the
anti-trust regulations. Examples of industry-specific regulations are capital adequacy requirements of
banks and the requirement of meeting conditions of financial health by insurers. Because these
regulations commonly are stated in accounting numbers, incentives are created to manage the
income statement- and the balance sheet variables of interest (Healy and Wahlen 1999, p 10).
Regulators like the Antitrust Division and the Federal Trade Commission (FTC) institute commit
actions against corporations whose shares have earned an abnormal rate of return. Next to
regulations that create incentive for managers, the industry itself in addition does have its influence
on the reporting information; firms may not disclose information that is valuable for competitors
(Palepu, Healy and Peek 2010, p 98).
Next to the three incentives communicated by Healy and Wahlen (1999), Heemskerk and van der Tas
(2006) provide a fourth; the signalling and inside information incentive. The efficiency perspective of
the Positive Accounting Theory clarifies that choices are often explained based on the fact that these
methods best reflect the underlying financial performance of the entity (Deegan and Unerman 2011,
p 273). This signalling incentive in addition can be used to reassure stakeholders, like labour unions,
that the company is healthy by showing profit (Palepu, Healy and Peek 2010, p 98).
Burgstahler and Dichev (1997) provide two reasons that managers have for using earnings
management; “to decrease the costs imposed on the firm in transactions with stakeholders” and “an
explanation based on the prospect theory, which postulates an aversion to absolute and relative
losses” (Burgstahler and Dichev 1997, p 124). These reasons provided by Burgstahler and Dichev
(1997) might be a reason to increase earnings with the use of earnings management. When a
company shows a positive financial position, losses are averted and the conditions of a loan will
probably be favourable compared to a bad financial situation.
3.2.4 Directions of earnings management
Decreasing, smoothing or increasing the earnings; this is all possible with the use of earnings
management. The incentive of a manager determines in which direction the earnings are managed
towards; achieving a personal bonus by increasing the earnings or decreasing the earnings to avoid
an anti-trust investigation. Earnings management in addition can be used to avoid or to minimize
earning decreases and losses (Burgstahler and Dichev 1997, p 100).
20
Scott (2008) provides four patterns of the use of earnings management: income minimization,
maximizing, smoothing and taking a bath. Taking a bath is considered as a method of earnings
management with minimization of the income as direction. The pattern chosen by a firm may vary
due to changes in contracts, in levels of profitability, and in political visibility (Scott 2008, p 405).
When a firm has a period of organizational stress or reorganizations, a firm will due to this report a
loss but it might report an even bigger loss in order to enhance the probability of reporting profits in
the future. This “clearing the decks” is known as taking a bath by a company. This extreme form of
income minimization in addition can be executed by write-offs on assets, intangibles and R&D
expenditures for example. Motivations for this kind of behaviour are politically visibility and income
tax considerations.
Contrary to income minimization earnings can be managed to maximize income. This maximization
of reported net income can be used in order to receive a bonus or when a firm is close to debt
covenant violations (Scott 2008, p 405). Earnings can be maximized by either taking advantages of
past reserves or using future profits (Ronen and Yaari 2008, p 342).
The last pattern of the use of earnings management signalled by Scott (2008) is income smoothing.
Income smoothing by Fudenberg and Tirole (1995) is defined as
“the process of time profile manipulation of earnings to make to reported income stream less
variable, but at the same time not increasing the reported earnings over a long period” (Fudenberg
and Tirole 1995, p 75)
A motive for using income smoothing is the aversion of losses and the increase of certainty for both
the manager and the company. Smoothened earnings will create more certainty on the
compensation of a manager and will reduce the volatility of the covenant ratios over time which
signals to externals that the firm expects to have persistent earnings power (Scott 2008, p 405).
Before the definition, the methods, the incentives and the directions of the use of earnings
management have been reviewed, next the other important aspect in this thesis will be commented;
the International Financial Reporting Standards (IFRS).
21
3.3 IFRS
In order to prevent, or at least decline the use of earnings management by companies, the European
Parliament and the council of the European Union stated in EC Regulation No 1606/20024 that all
stock exchange quoted companies in the European Union in 2005 are obliged to adopt the
International Financial Reporting Standards (IFRS) in their consolidated annual financial report. In this
section the principles, the advantages and the disadvantages of these standards are presented.
3.3.1 Introduction
The IASB introduced the new reporting standards IFRS with the important aims of creating more
transparency and comparability in the annual financial reports (EC Regulation No 1606/2002,
p243/2). With these aims, an annual financial report should present a ‘true and fair view’ of the
financial situation and results of a company. In order to accomplish this, IFRS is characterised by both
rigidities and elements of estimation in association with the principle of fair value accounting
(Heemskerk and van der Tas 2006, p 574).
The principle of fair value accounting aims to incorporate more-timely information about gains and
losses on transactions in the financial statements, consequently positive and negative changes in
values are quickly adjusted (Ball 2006, p 12). The IFRS require that more assets and liabilities are
valued at fair, present value with the consequence that the change in value should be recorded in
the profit and loss account (Heemskerk and van der Tas 2006, p 574). This valuation at fair value,
presents for managers more possibilities to influence the financial statements by changes in the
estimations as a consequence that subjectivity can be a determinant in realising gains or losses (Ball
2006, p 13).
The components fair value accounting and the subjectivity of the value-determination by IFRS are
used in the next section in describing the advantages and the disadvantages of the mandatory use of
IFRS.
3.3.2 Advantages and Disadvantages of the mandatory use of IFRS
The IFRS were introduced as the standards that should prevent or at least decline the use of earnings
management and create more transparency and comparability in the financial statements (EC No
1606/2002, p 243/1). But what influence do the new standards have on managers’ behaviour and do
the standards really increase the value of the financial statements? Ball (2006) has performed
research on this by focussing on the positive and on the negative aspects of the introduction of IFRS
4
REGULATION (EC) No 1606/2002 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 19 July 2002 on the
application of international accounting standards
Official Journal of the European Communities 11.09.2002
22
for investors. According to Ball (2006) investors get more accurate, comprehensive and timely
financial statement information relative to the national standards they replace for public financial
reporting in most of the countries adopting them (Ball 2006, p 11). Because of the improved financial
reporting quality which reduces the risk for them of trading with a better-informed professional,
small investors will be able to anticipate better on the financial statement information. By using a
standardised reporting format, IFRS will eliminate many of the adjustments analysts historically have
made in order to make companies’ financial information internationally more comparable (Ball,
2006, p11). Like Ball (2006), Heemskerk and van der Tas (2006) in addition suggest that one of the
advantages of implementing IFRS is providing more transparency and comparability.
Next to the advantages, in addition on the use of IFRS some disadvantages exist. Remarkable is that
fair value accounting is qualified as both a positive and a negative aspect of the use of IFRS. The
determination of values by management may be an improvement when management determines
the fair value, but when management uses this subjectivity for their own interest fair value
accounting is a negative aspect of the use of IFRS (Ball 2006, p 9). Another disadvantage that is
signalled by Ball (2006) is that a general system of standards creates less competition among the
several systems of standards and that incentives of prepares will remain local which will create
quality differences between areas which will tend to be ‘swept under the rug’ of uniformity (Ball
2006, pp. 24-25).
Bolt-Lee and Smith (2009) have analysed IFRS researches that have been performed till the
presentation of their article. The article is an analysis of the benefits versus the costs of the
introduction of IFRS. Improvements like more transparency and generalization of the standards are
compared to the costs of the changing standards. The overall conclusion of Bolt-Lee and Smith (2009)
is that the benefits of the new standards might not exceed the costs of implementing them.
Heemskerk and van der Tas (2006) confirm these conclusions drawn by Bolt-Lee and Smith (2009)
and add to this that the standards are stringent, but that the application of the rules is subjective.
The strictness of the rules should decrease the use of earnings management, but the subjectivity of
fair value accounting creates more opportunities for using earnings management (Heemskerk and
van der Tas 2006, p 573).
When checking on the factor IFRS in this thesis, the question is whether the introduction of IFRS has
created a change in the use of earnings management. Several factors will have influence on the
implementation of IFRS and on the use of earnings management. Soderstrom and Sun (2007) state
that a successful implementation of IFRS depends on three factors: (1) the quality of the national
23
standards, (2) the country’s legal and political system and (3) the financial reporting incentives. In
section 4.3 these factors will be commented.
3.4 Models for measuring the use of earnings management
In order to investigate the influence of the adoption of IFRS on the use of earnings management, the
management of earnings has to be measured. In this section, two general methods for detecting the
use of earnings management, accruals-based and real activities, will be commented by showing the
models that can be used for both methods. Before the selection which model in this research will be
used, first the several models that have been developed are commented.
3.4.1 Accruals Approach
As already signalled in section 3.2.2.1, accruals-based earnings management is about the exploitation
of accounting discretion that is allowed based under GAAP (Xu, Taylor, Dugan 2007, p 196). This
accounting discretion is about selecting accounting methods and estimation of numbers in order to
influence the financial values.
In order to be able to detect whether management uses earnings management, models are
developed to highlight certain irregularities in accruals and distinct accruals in a discretionary and
non-discretionary part. Detecting earnings management by focussing on accruals can be executed in
several ways. Which accruals are used for earnings management and what is performed with these
accruals; the focus can be on the aggregation of accruals, specific accruals or on the distribution of
the accruals (McNichols 2000, p 314). In this research the focus will be on the aggregation of
accruals. The models that in the next sections will be commented, determine the amount of the nondiscretionary accruals. By subtracting this amount from the total amount of accruals, the
discretionary amount of accruals is determined. This amount is the indicator for the use of earnings
management; a value differing from zero indicates the use of earnings management. A positive value
indicates an increase of the use of earnings management and a negative value indicates a decrease in
the use of earnings management.
First the determination of the total accruals will be commented before the several models for
determining the discretionary accruals and their differences will be presented.
3.4.2 Accruals models
In this section the model of Healy (1985), DeAngelo (1986), Jones (1991), Modified Jones (1995) and
Kothari et al. (2005) will be commented. The Modified Jones model (1995) and Kothari et al. (2005)
are models with the Jones model (1991) as fundament. Each model has a different approach in
24
detecting the use of earnings management by using different variables and/or assumptions. Despite
these differences, all models use the same equation for measuring the total amount of accruals:
TAt = [ ΔCAt – ΔCASHt – ΔCLt + ΔDCLt – DEPt ]
(1)
TA = total amount of accruals
ΔCA = change in current assets
ΔCASH = change in cash equivalents
ΔCL = change in current liabilities
ΔDCL = change in debt included in current liabilities
DEP = depreciation and amortization expense
t = year index
This model provided by Dechow (1995) calculates the total amount of accruals by investigating
various balance sheet items which can used for adjustments as signalled in section 3.2.2.1.
The models of Healy (1985), DeAngelo (1986) and Jones (1991) differ in their approach in which way
to measure the non-discretionary component of the accruals. In order to create comparability and a
better understanding in which way the models differ from each other, the models represented in the
article of Dechow et al. (1995) will be commented in this thesis. The only exception is the model
developed by Kothari et al. (2005); this model was developed after the publication of Dechow et al.
(1995) and added to the discussion of the developed models because of its different perspective on
measuring accruals and the detection on the use of earnings management.
3.4.2.1 Healy (1985)
In order to estimate the use of earnings management, Healy (1985) states that two proxies exist for
discretionary accruals and accounting choices: total accruals and the effect of voluntary changes in
accounting procedures on earnings (Healy 1985, p 94). With the use of formula (1) the total accruals
are measured which are used to determine the non-discretionary accrual component. The nondiscretionary accruals are estimated by the mean total accruals from the estimation period:
NDAτ = Σ TAt / T
NDA = nondiscretionary accruals
TA = Total Accruals
t = year subscript for year included in the estimation period
25
τ = a year subscript indicating a year in the event period
Healy (1985) assumes that the use of earnings management occurs systematically. Consequently it is
possible according to Healy (1985) to use the estimated total amount of accruals over a period for
the determination of the non-discretionary accrual component. The period of estimation will be
determined by a period of a manager, which will maximize his expected future award by managing
the published earnings (Healy 1985, p 90). However, the limitation of this model is that Healy (1985)
assumes that non-discretionary accruals are constant over time and follow a white noise process
around a constant mean (Dechow et al. 1995, p 197). These assumptions do not always hold in
reality, which creates errors in the conclusions drawn by this model.
3.4.2.2 DeAngelo (1986)
DeAngelo (1986) elaborated on the model of Healy (1985), but the difference between the two
models is that DeAngelo (1986) restricts the estimation period for non-discretionary accruals to
previous’ year observation (Dechow et al. 1995, p 198).
NDAt = TAt-1
NDA = non-discretionary accruals
TA = total accruals
t = period index
Like Healy (1985), DeAngelo (1986) expects that non-discretionary accruals are constant over time.
When no constancy over time exists measurement of the accruals will be with errors (Dechow et al.
1995, p 198). This limitation of the models is considerable, because according to Kaplan (1985) nondiscretionary accruals should change in response to change in the economic circumstances (Dechow
et. al 1995, p198).
3.4.2.3 Jones Model (1991)
Jones (1991) created a model that differentiates from the previous commented models by not
assuming that the non-discretionary accruals are constant over time and by taking economic
circumstances into account. This is executed by not focussing on the total amount of accruals, but on
specific accruals. First, Jones (1991) determines the total amount of accruals by using formula (1).
Next the firm-specific parameters α1, α2 and α3 will be estimated by the following model in the
estimation period (Dechow et. al 1995, p 198):
TAt = a1 [1/At-1] + a2 [ΔREVt] + a3 [PPEt] + υt
26
TA = total accruals
ΔREV = change in revenues
PPE = gross property, plant and equipment
υ = error term
t = year index
The Ordinary Least Squares (OLS) a1, a2 and a3 are the estimations of α1, α2 and α3 in the
determination of the amount of non-discretionary accruals. OLS is useful when the relation between
a dependent and an explanatory variable needs to be tested. The OLS estimates are the parameters
that yield the minimum sum of the squared residuals (Chumney and Simpson 2006, p 94). With the
use of OLS, the non-discretionary accruals are determined by:
NDAt = α1(1/At-1) + α2(ΔREVt) + α3(PPEt)
A = total assets
ΔREV = change in revenues
PPE = gross property plant and equipment
α1, α2, α3 = firm-specific parameters
t = year index
The strength of this model compared to other models previous commented is the addition of the
variables change in revenue and Property, Plant and Equipment (PPE) to take changing conditions of
a company into account. Another important variable that by Jones (1991) is used to reduce
heteroscedasticity is the scaling of all variables by the total amount of assets (Jones 1991, p 212). The
limitation of this model is that the total amount of accruals will extract the discretionary component
of the accruals which causes that the estimation the use of earnings management is biased toward
zero (Dechow et al. 1995, p 199).
3.4.2.4 Modified Jones Model (1995)
Dechow et al (1995) adjusted the model of Jones (1991), which resulted in the Modified Jones Model
(1995). The formula for determining the total amount of accruals (TA) is similar to the formula used
with the Jones model (1991); the difference in the determination of the non-discretionary accruals
component. The difference with the Jones model (1991) is in order to eliminate the assumption that
discretion is exercised over revenues; the change in revenues is adjusted for the change in the
receivables (Dechow et al. 1995, p 199). This modification has resulted in the following equation for
determining the non-discretionary accruals:
27
NDAt = α1 (1/At-1) + α2 (ΔREVt – ΔRECt) + α3 (PPEt)
A = total assets
ΔREV = change in revenue
ΔREC = change in net receivables
PPE = gross property plant and equipment
t = year index
The reason for this modification is that it is assumed that discretion on recognition of revenue on
credit sales is easier than exercising discretion over the recognition of revenue on cash sales (Dechow
et al. 1995, p 199).
With the determination of the total amount of accruals and the non-discretionary component, the
discretionary component can be determined. This discretionary component is adjustable by
management and consequently an indication for the use of earnings management.
3.4.2.5 Kothari et al (2005)
Kothari et al. (2005) have a different perspective compared to the previous described models in
which way accruals should be measured for detecting the use of earnings management. According to
Kothari et al. (2005), performance matched discretionary accrual measures are the key to success in
detecting the use of earnings management. Accruals are correlated with a firm’s contemporaneous
and past performance (Gunny 2010, p 167).
The reason Kothari et al. (2005) have chosen for performance matched discretionary accrual
measures, is the misspecification of the Jones (1991) and modified-Jones model (1995) when
companies experience extreme performance (Kothari et al. 2005, p 166). According to Kothari et al.
(2005), because of the use of accounting conservatism and the use of earnings management
incentives which are the base of the other approaches like the Jones Model (1991) and Modified
Jones Model (1995) no linear relation exists between the current and the future performance
(Kothari et al. 2005, p 170).
The estimation of the discretionary accruals starts with the determination of the total amount of
accruals (TA), which is determined by the use of the Modified Jones Model (1995). Compared to the
Modified Jones Model (1995), the formula for determining the total amount of accruals shows two
different variables: change in Sales and in Return on Assets (ROA). Change in Sales is equal to ΔREVt –
28
ΔRECt that is used in the Modified Jones model (1995), consequently the only difference between
this model and the Modified Jones model (1995) is the addition of the variable ROA.
With this addition, Kothari et al. (2005) determines the OLS coefficients by:
NDAt = α1 [1/At-1] + α2 [ΔSALESt]+ α3 [PPEt]+ α4 [ROAt (or t-1)]
NDA = Non-discretionary Accruals
A = total amount of assets
ΔSALES = the change in Sales scaled by lagged total assets
PPE = Property, Plant and Equipment scaled by lagged total assets
ROA = Return on Assets
t = year index
Each firm-year observation will be matched with another observation from the same industry and
year with the closest return on assets in the current year, ROAit (Kothari et al. 2005, p 174). With the
use of a t-test, the significance of the mean discretionary accruals is assessed (Kothari et al. 2005, p
175).
Before the most-used accrual-based approaches have been presented, next will be commented the
use of real earnings management approaches before will be decided which accruals-based approach
in this research will be used.
3.4.3 Real activities Approach
Based on a survey executed by Graham et al. (2005) next to the accruals-approach, the manipulation
of real activities for managing the earnings is increasing. The results of the survey suggest that
managers are switching to managing earnings by using real activities instead of the use of accruals
(Graham et al. 2005, p 66). Because of the fact that this approach is relatively ‘new’, not many
models have been developed yet to detect the use of real activities manipulation. Consequently, only
two models, the models developed by Roychowdhury (2006) and Gunny (2010), will be commented
and will be explained in which way they differ from each other.
3.4.3.1 Real Activities Manipulation
Real earnings management is the adjustment of the scale and the timing of business activities by
management. By these adjustments, the value of business activities will change which influences the
financial position of a company (Schipper 1989, p92). In order to detect the use of real earnings
management, the focus is on operating, investing and financing activities of a company. These
29
activities will be checked by comparing their actual level with a ‘normal’ level that is determined by
models developed by Roychowdhury (2006) and Gunny (2010). A difference between these levels is
indicative for the management of the published earnings; a positive value for increasing and a
negative value for decreasing earnings management
These models developed by Roychowdhury (2006) and Gunny (2010) will in the next sections be
commented; the similarities and the differences will be explained. A limitation of both models is that
no evidence exists on the validity of both models. Tests have been executed on the validity of the
proxies used in the models (Zang 2005, Gunny 2006) but no evidence exists on the validity of the
models. Consequently the decision is based on previous real earnings management studies (Cohen et
al. 2008; Cohen and Zarowin 2010; Lippens 2010 and Zang 2012) and their choice of model for
detecting the use of real activities manipulation.
3.4.3.2 Real Activities Manipulation Models
In order to detect real activities manipulation, the models of Roychowdhury (2006) and Gunny (2010)
are commented. Each model will be explained, limitations will be noted and finally the conclusion will
be drawn by choosing the method by checking earlier conducted researches on real earnings
management.
3.4.3.3 Roychowdhury (2006)
The focus of Roychowdhury (2006) is on sales manipulation, reduction of discretionary expenses and
overproduction. In order to investigate this, patterns in cash flow from operations (CFO),
discretionary expenses and production costs for firms close to the zero earnings benchmark are
investigated (Roychowdhury 2006, p 339). Dechow et al. (1998) investigated the relation between
earnings and cash flows and developed a model to test this relation. With the model of Dechow et al.
(1998) as fundament, the normal levels of CFO, production costs and discretionary expenses are
derived for every firm-year.
Following Dechow et. (1998), the cash flow from operations is expressed as a linear function of sales
and change in sales in the current period (Roychowdhury 2006, p344). This linear function is
estimated by running the following regression:
30
CFOt / At-1 = α0 + α1*(1/At-1) + β1*(St/At-1) + β2*(ΔSt/At-1) + εt
(1)
CFO = Cash Flow of Operations
A = Total Assets
S = Sales
ε = Error term
t = Period index
With the use of the coefficients derived with the historical data, the ‘normal’ level of CFO is
determined which is compared to the actual level of the CFO. The difference between these levels is
indicative for the use of real earnings management. This way of determining the indicative value for
real earnings management, in addition is used for the variables COGS, inventory growth and
production costs.
COGSt/At-1 = α0 + α1*(1/At-1) + β*(St/At-1) + εt
(2)
COGS = Costs of Goods Sold
A = Total Assets
S = Sales
ε = Error term
t = Period index
ΔINVt/At-1 = α0 + α1*(1/At-1) + β1*(ΔSt/At-1) + β2*(ΔSt-1/At-1) + εt (3)
INV = Inventory
A = Total assets
S = Sales
ε = Error term
t = Period index
These two equations for determining the normal level of COGS and change in Inventory are the basis
for determining the normal level of the production costs. Based on these two equations together, the
equation for determining the normal level of production costs is defined:
31
PRODt/At-1 = α0 + α1*(1/At-1) + β1*(St/At-1) + β2*(ΔSt/At-1) + β3*(ΔSt-1/At-1) +
εt
(4)
PROD = production costs
A = Total assets
S = Sales
ε = Error term
t = Period index
The last regression is about discretionary expenses like R&D, advertising and maintenance expenses.
These expenses are most likely to be used for earnings management when these expenditures not
immediate generate revenue and income. The ‘normal’ level of discretionary expenses is determined
by investigating the linear function of contemporaneous sales (Roychowdhury 2006, p 340). But
Roychowdhury (2006) states that when this linear function is used, managers who upward sales to
increase the reported earnings in a year, will have an outcome of this regression with unusually low
residuals, even when discretionary expenses are not reduced. Consequently the discretionary
expenses are expressed as a function of the lagged sales (Roychowdhury 2006, p 345):
DISEXPt/At-1 = α0 + α1*(1/At-1) + β*(St-1/At-1) + εt
(5)
DISEXP = discretionary expenses; R&D, SG&A and Advertising expenses
A = Total assets
S = Sales
ε = Error term
t = Period index
With the use of the five regressions stated before, the ‘normal’ levels of the variables are
determined. The difference between the actual and the ‘normal’ level of the variables is indicative
for the use of earnings management. Roychowdhury (2006) compares suspect firm-years with the
rest of the sample for the detecting of earnings management. A regression with the abnormal level
of a variable as dependent variable will check the influence of control variables like size and marketto-book ratio (Roychowdhury 2006, p 349-350).
3.4.3.4 Gunny (2010)
The research of Gunny (2010) focuses on four aspects that are demonstrated to be used for real
activities manipulation by empirical evidence in prior literature (Gunny 2005, Roychowdhury 2006,
Zang 2006). These four types are (1) R&D expenses, (2) SG&A expenses, (3) timing of sale and gain
32
report of fixed assets and (4) overproduction. In order to understand whether earnings are managed
or ‘normal’, Gunny (2010) developed models to estimate the expected (i.e. ‘normal’) level of all four
expenses or gains associated with the use of real earnings management (Gunny 2010, p862).
The first proxy for the use of real earnings management is a discretionary expense, the R&D expenses
of a company. Baber et al. (1991), Dechow and Sloan (1991), Bushee (1998), Bens et al. (2002) and
Chen (2004) provide evidence that the R&D expenses are used to achieve various income objectives
(Gunny 2010, p 858-859). With the evidence of these researches and the models developed by
Berger (1993) and Roychowdhury (2006), Gunny (2010) expresses the normal level of R&D expense
by the following model:
RDt / At-1 = α0 + α1*(1/At-1) + β1*MVt + β2*Qt + β3*(INTt / At-1) + β4*(RDt-1 /
At-1) + eR&Dt (1)
RD = R&D expense
A = Total assets
MV = The natural log of market value
Q = Tobin’s Q
INT = Internal funds
ε r&d = Error term
t = Year index
The second proxy for the use of real earnings management is the SG&A expenses. The normal level
of SG&A is estimated by the following model:
SGAt / At-1 = α0 + α1*(1/At-1) + β1*MVt + β2*Qt + β3*(INTt / At-1) + β4*(ΔSt /
At-1) + β5*(ΔSt / At-1) * DD + eSG&At (2)
SGA = Selling, General & Administrative expenses
A = Total assets
MV = The natural logarithm of market value
Q = Tobin’s Q
INT = Internal funds
S = Total sales
DD = Indicator variable equal to 1 when total sales decrease between t - 1 and t, zero otherwise
33
ε sg&a = Error term
t = Year index
The second equation is about the determination of the normal level of SG&A expenses. In the
equation, the same elements of the first equation of Gunny (2010) are used plus controls for “sticky”
cost behaviour which implies that the magnitude of a cost increases by increased sales in greater
than the magnitude of a cost decrease by an equal decrease in sales (Gunny 2010, p 864).
Bartov (1993) and Herrman et al. (2003) provide evidence for the relation between the sales of fixed
assets and the use of earnings management to avoid negative earnings growth; debt covenants
violations and operating income. Consequently Gunny (2010) provides a model to estimate the
normal level of gain on asset sales:
GainAt / At-1 = α0 + α1*(1/At-1) + β1*MVt + β2*Qt + β3*(INTt / At-1) + β4*
(ASalest / At-1) + β5*(ISalest / At-1) + eAsset t (3)
GainA = income from asset sales
A = Total assets
MV = The natural logarithm of market value
Q = Tobin’s Q
INT = Internal funds
ASales = Long-lived assets sales
ISales = Long-lived investment sales
ε assets = Error term
t = Year index
Gunny (2010) based the equation on Bartov (1993) and Herrman et al. (2003) and presumes that
there is a monotonic relation between income from asset sales, asset sales and investment sales.
The last proxy used by Gunny (2010) is the level of the production costs. According to Gunny (2010),
a relation exists between the level of sales and the ‘normal’ production costs belonging to that.
When production costs are abnormally high for a given sales level, it can be an indication of the use
of sales manipulation due to price discount or COGS manipulation due to overproduction
(Roychowdhury 2006, p340). In order to determine whether production costs are abnormally high,
the normal level of product costs is determined:
34
PRODt / At-1 = α0 + α1*(1 / At-1) + β1*MVt + β2*Qt + β3*(St/At-1) + β4*(ΔSt /
At-1) + β5*(ΔSt-1 / At-1) + eProductiont (4)
PROD = Costs of Goods Sold plus change in inventory
A = Total assets
MV = The natural log of market value
Q = Tobin’s Q
S = Sales
ε production = Error term
t = Year index
This model for estimating the normal level of production is based on Dechow et al. (1998) and
Roychowdhury (2006) with the addition of the market value and Tobin’s Q.
All these models (1-4) express the ‘normal’ level of the different expenses and gains. Comparing the
‘normal’ levels with the actual levels can be detecting an indication that real earnings management
by firms is used.
The two models for estimating the use of earnings management by real activities have been
commented; the model that will be used for this research will be determined. The models of
Roychowdhury (2006) and Gunny (2010) are comparable; both models use some similar proxies. The
use of similar proxies shows that Gunny (2010) used the model of Roychowdhury (2006) as a
fundament together with other researches in developing the estimation models. Differences in the
models are the use of CFO by Roychowdhury (2006) and the variable sales of fixed assets by Gunny
(2010).
In determining which model is most appropriate for this research, the validity of the models cannot
be used because of lack of evidence as discussed in transition from section 3.4.3.1 to 3.4.3.2. Based
on previous researches (Cohen et al. 2008; Cohen and Zarowin 2010; Lippens 2010 and Zang 2012)
the decision is that the model of Roychowdhury (2006) is most used and will consequently be used in
this research.
3.5 Summary
In this chapter the two main topics of this research, the introduction of IFRS and earnings
management have been presented. With the review of these two topics, sub-questions 2 - 5 will be
answered.
35
The strength of IFRS is the use of fair-value accounting as an instrument to incorporate more-timely
information in the annual financial consolidated statements. This instrument should create more
transparency and comparability of financial statements of European stock exchange quoted
companies (EC No 1606/2002, p243/2). Besides these advantages, disadvantages exist like the
subjectivity in determining the value of assets and the liabilities creates an incentive for management
to determine the value best for their own interest. The question is whether the advantages of the
new standards exceed the disadvantages. The possible success of the implementation of IFRS,
according to Soderstrom and Sun (2007) will be determined by (1) the quality of the national
standards, (2) the country’s legal and political system and (3) the financial reporting incentives. These
factors for success will be explained further in section 4.3.
The main topics of this research are the introduction of IFRS in 2005 and the use of earnings
management. Earnings management is a broad topic consequently it is hard to define one total
definition of it. Consequently, Ronen and Yaari (2008) divided earnings management in white, grey
and black in which the incentive of a manager is determinative on which type of earnings
management is executed. Assumed is that the action of using earnings management by a manager is
purposeful. The incentive that is determinative in characterizing the use of earnings management can
be (1) a capital market incentive, (2) a contracting incentive or (3) a regulatory incentive. Depending
on an incentive, the direction of earnings management will be determined by a manager. The
direction of earnings management will be chosen to create the best value for the managers and/or
the company.
This management of earnings can be realised by two general methods; by accruals and by real
activities. In order to detect the use of earnings management by accruals, several models have been
developed. To present an overview of the different models, section 3.4.1 contains models of Healy
(1985), DeAngelo (1986), Jones (1991), Modified Jones (1995) and Kothari et al. (2005). After
checking various related earlier researches (Heemskerk, van der Tas 2006; Cohen, Dey, Lys 2008;
Lippens 2010), is decided that the Modified Jones model in this research will be used for checking the
use of accruals-based earnings management.
Next to the accruals-based method, real earnings management is used to adjust the financial
numbers and values. The use of real earnings management can be measured by the use of the model
developed by Roychowdhury (2006) and Gunny (2010). A big limitation of both models is that no
evidence exists on the validity of the models. Tests have been performed on the validity of the
proxies in the models used (Zang 2005, Gunny 2006) but no evidence on the validity of the models
36
exists because no data of companies exists that have proven adjusted values by the using of real
earnings management. Consequently the decision is based on previous real earnings management
studies and their use of a model. This fundament of previous studies on the use of real earnings
management (Cohen et al. 2008; Cohen and Zarowin 2010; Lippens 2010 and Zang 2012) reveals that
the model of Roychowdhury (2006) is most common used and consequently in this research will be
used for detecting the use of real earnings management. In which way this model will be used will be
further explained in chapter 6 the research design.
The next chapter concerns prior scientific economic research about the thesis object based on that in
chapter 5 the hypotheses for this research will be determined.
37
4 Related researches
4.1 Introduction
In this chapter, earlier conducted, similar researches will be described by what they investigated, in
which way they executed their research and finally their findings. With the use of these researches,
their conclusions and the possible influence of the factors of the French Civil Law countries The
Netherlands, Belgium and France in section 4.3 commented, will in chapter 5 the hypotheses be
determined.
4.2 Earlier conducted researches
In this section, the researches of Tendeloo and Vanstraelen (2005); Ewert and Wagenhofer (2005);
Heemskerk and van der Tas (2006); Cohen, Dey, Lys (2008); Jeanjean and Stolowy (2008); Lippens
(2010) and Callao and Jarne (2010) will presented. These seven researches will be presented in order
of the publication date.
o
Tendeloo and Vanstraelen (2005) – EM under German GAAP versus IFRS
The research of Tendeloo and Vanstraelen (2005) is about German companies that have early
adopted IFRS and whether they have engaged significantly less in earnings management compared to
companies in Germany that report based on German GAAP (Tendeloo and Vanstraelen, 2005, p 1).
The sample of the research consists of German listed companies, containing 636 firm-year
observations in the period of 1999 – 2001. Germany can be classified as a code-law country with
weak investor protection rights (La Porta et al. 2000). This can have its influence on the results of the
implementation of IFRS. The first hypothesis states that compared to companies reporting based on
German GAAP firms that have adopted IFRS will engage less in earnings management. The other two
hypotheses contain the effect of audited by a Big 4 audit firm and cross-listed on well-developed
international capital markets on the adoption of IFRS and the effect on the use of earnings
management. The hypotheses are tested with the use of the cross-sectional version of the Jones
model (Jones, 1991).
The results of Tendeloo and Vanstraelen (2005) suggest difference exists in the earnings
management behaviour between early adopters of IFRS and the companies that reported based on
German GAAP. IFRS-adopters manage their earnings more with discretionary compared to
companies that use German GAAP. The influence of a Big 4 auditor is observable; this variable
reduces engaging in earnings smoothing. But no evidence in this research is found that the
38
implementation of IFRS in Germany is associated with a lower use of earnings management
(Tendeloo and Vanstraelen 2005, p 177).
Limitations of this research is that although there has been controlled for various earnings
management incentives, other incentives may exist that have not been controlled for. Second is that,
although there was controlled for much of hidden reserves by including them in the accruals, it was
not possible to check for them all.
o
Ewert and Wagenhofer (2005) – Economic effects of tightening accounting standards to
restrict earnings management
In order to reduce the amount of managed earnings, the IFRS were introduced as stricter accounting
standards with the fair-value as most important principle. This strictness of the accounting standards
is investigated by Ewert and Wagenhofer (2005). Several authors, like Schipper (2003), state that
tighter accounting standards may create a substitution effect of accruals-based to real earnings
management, which is counteracting with the standard-setters’ intention (Ewert and Wagenhofer
2005, p 1102).
With the use of the model of Fischer and Verrecchia (2000) which is about the managerial reporting
bias in a uncertain capital market and the manager’s reporting objective, Ewert and Wagenhofer
(2005) analyse the rational expectations equilibriums of two strategic players and the use of earnings
management. Two strategic players, one risk-neutral manager and a competitive, risk-neutral capital
market, are used to check this rational expectations equilibrium. This equilibrium is mathematically
checked, therefore no sample is used in this research. The reason of Ewert and Wagenhofer (2005) to
choose for this type of research is because according to them, it is about the decision behind the use
of earnings management and not about the underlying process. An accounting system records
transactions and events according to the accounting standards in force (Ewert and Wagenhofer 2005,
p 1103-1104). Next to the focus on both methods of earnings management, accruals- and real
activities-based, is the intention behind the management investigated. Managers’ interest is driven
by factors like accounting-based bonus program, debt covenant tied to accounting numbers or
upcoming tenure decisions.
The managers’ decision in using accruals-based earnings management is investigated in combination
with the tightness of the accounting standards. The tightness of the accounting standards makes it
more costly for a manager to perform accruals-based earnings management. The effect of tighter
accounting standards on the choice of accruals- and real earnings management, the quality of
39
reported earnings, the level of the use of earnings management and the cost of earnings
management; Ewert and Wagenhofer (2005) investigate it all.
Ewert and Wagenhofer (2005) concluded that the tighter accounting standards increased the quality
of the published earnings, but some consequences exist that may outweigh this benefit. These
consequences are that the total amount of managed earnings and the use of real compared to
accruals-based earnings management has increased.
o
Heemskerk and van der Tas (2006) – Veranderingen in resultaatsturing als gevolg van de
invoering van IFRS
This research is about the influence of the use of IFRS on the extent of managing results by
managers. IFRS uses strict criteria for the use of accounting methods which present the impression of
fewer possibilities for managing results. But Heemskerk and van der Tas (2006) in addition signal the
fact that IFRS next to stricter criteria in addition has situations that mangers have to use subjective
estimations. The question is whether IFRS is able to improve the transparency and so decrease
managers’ influence on results. The hypotheses that are used to test this are that less ‘discretionary
accruals’ and ‘accruals’ are used for managing result and result equalisation.
The data that are used for the research are data from companies that before the mandatory IFRS
implementation already used IFRS. After eliminating the company that did not comply with the
requirements, the sample contained 160 companies from Germany and Switzerland. With the use of
the Modified Jones Model (1995) the discretionary part of the accruals is determined. With this
dependent variable, the influence of the independent variables accounting standards, country,
industry and size on the use of earnings management are tested. Only the variable standard had a
significant, positive influence on the amount of the discretionary accruals (Heemskerk and van der
Tas 2006, p577). This positive influence of the use of IFRS is indicative for Heemskerk and van der Tas
(2006) to conclude that IFRS did not create a reduction in the use of discretionary accruals. This in
addition is the case when the focus is on the use of accruals for result equalisation.
A limitation of this research is the focus on Germany and Switzerland, resulting that the use of IFRS
can have a different influence in other countries because of country-specific regulations. Another
limitation is the limited dataset; too few IFRS adopted companies exist to present a fair view on the
influence of the use of IFRS on managing result and the equalization of it.
o
Cohen, Dey, Lys (2008) – Real and Accrual based EM in the pre and post SOX periods
40
In this research the influence of the introduction of the Sarbanes-Oxley Act (SOX) in 2002 on real and
accrual-based earnings management has been investigated. Because this research is about the
Sarbanes-Oxley act, the focus is on the possible substitution in the method of managing published
earnings. With the research of Graham et al. (2005) about the substitution of accruals-based for real
earnings management as fundament, the hypothesis about earnings management is that the level of
the use of real earnings management has increased and the level of accruals-based earnings
management has decreased after the passage of SOX . The hypothesis stated for this is that
managers’ choices of accounting practices are influenced by the impact of these accounting methods
on their compensation.
A sample period of 1987 – 2005 has been used to investigate the stated hypotheses. This period is
divided in the period prior and after the introduction of SOX. Both periods were again divided in the
period before the major corporate scandals (1987 – 1999) and the period immediately preceding the
passage of SOX when the major scandals occurred (2000 – 2001). The sample consisted of 8,157
firms representing 87,217 firm-year observations for the substitution hypothesis. Because data was
attainable for a smaller period (1992-2005), the compensation hypothesis is tested with the use of
2,018 firms and 31,668 firm-year observations.
In order to estimate the use of accruals-based earnings management, the Cross-sectional version of
the Modified Jones model (1991) was used. After calculating the Total Accruals (TA) and the Normal
Accruals (NA), a robustness tests with performance-matched discretionary accruals was used,
supported by the research of Kothari et al. (2005). The proxies that are used for the use of real
earnings management are three manipulation methods: acceleration of the timing of sales, increased
production for lower COGS and decreases in discretionary expenses. To identify this possible
manipulation, the normal levels of CFO, discretionary expenses and production costs are determined
with the use of the model developed by Dechow et al. (1998). Cohen, Dey and Lys (2008) use many
control variables: audit firm, change in GDP, market value of equity, period, bonus compensation,
(un)exercisable options and new options.
The findings of the research by Cohen, Dey and Lys (2008) are that the use of earnings management
in general steadily increased over the whole period and particularly after the passage of SOX. Next to
the increase in the use of earnings management in general, the level of the use of accrual-based
earnings management declined over time, while the level of the use of real earnings management
increased significantly after the passage of SOX. The results in addition indicate that the increase in
41
accrual-based earnings management prior to SOX was simultaneous with a shift in the fraction of
equity-based executive compensation.
o
Jeanjean and Stolowy (2008) – Do accounting standards matter? An exploratory analysis of
earnings management before and after IFRS adoption
This research of Jeanjean and Stolowy (2008) contributes to the scientific economic literature with
the concentration on firms in countries in which early adoption of IFRS was not possible for the
transition date (Jeanjean and Stolowy 2008, p481). The focus is on firms from Australia, France, and
the United Kingdom that changed compulsory to the use of IFRS which eliminates sample selection
bias.
Jeanjean and Stolowy (2008) analysed the distribution of earnings to check whether companies have
managed their earnings to avoid losses any less after the implementation of IFRS than before the
compulsory implementation of IFRS in 2005. Earnings management is identified with the use of
statistical properties of earnings to identify thresholds. With the ratio of small reported profits to
small reported losses, discontinuities in distributions is measured. With this, the distribution of
earnings is analysed and checked whether earnings are managed to avoid losses any less after the
implementation of IFRS. A basic sample of 1146 firms with 5051 firm-year observations is used to
test whether this was the case.
Jeanjean and Stolowy (2008) concluded that the pervasiveness of the use of earnings management
did not decline after the introduction of IFRS, and even increased in France. Sharing rules was not
sufficient in itself to create a common business language (Jeanjean and Stolowy 2008, p 493).
o
Lippens (2010) – The mandatory introduction of IFRS as a single accounting standard in the
Eu and the effect on EM
The research of Lippens (2010) investigated the influence of the adoption of IFRS on the level of
earnings management in the European Union. Lippens (2010) uses the hypotheses of a substitution
effect of accrual-based and the use of real earnings management and a different effect for each
country. With the use of the adjusted Modified Jones model (1995) the discretionary accruals are
measured. For the estimation of real earnings management, Lippens (2010) uses proxies of
Roychowdhury (2006); the abnormal level of cash flow from operations and the abnormal level of
production costs.
42
These models are used on a sample of the listed companies from Belgium, Denmark, Finland, Italy,
The Netherlands and Sweden. Financial institutions, utility companies, companies with negative
equity, total or discretionary accruals above 100% of lagged total assets and companies with not all
available data are excluded from the sample. This sample, which is not specified in the sample
description, are used for a regression analysis with the pre-IFRS (2000-2004) and post-IFRS period
(2005-2006). The study of Lippens controlled for the following variables: year, IFRS, ROA, and CFO,
employees, leverage, industry and country.
The research of Lippens (2010) indicates that the adoption of IFRS has increased the use of accrualsbased earnings management. Next to the accruals-based, in addition the use of real earnings
management has strictly increased. Although both methods of earnings management increased
according to Lippens (2010), the adoption of IFRS creates the substitution of accruals-based to real
earnings management. Because different countries have been investigated, a general conclusion for
all countries is hard to draw. The adoption of IFRS did not have a significant influence on the level of
the use of earnings management. This can be explained as IFRS having the same effect on the relative
levels of earnings management in various countries or as that IFRS are being ineffective in restricting
earnings management all together (Lippens 2010, p 97).
o
Callao and Jarne (2010) Have IFRS affected Earnings Management in the European Union?
Callao and Jarne (2010) have performed research on the use of discretionary accounting practices in
the European Union and the influence of the adoption of IFRS on this. Combined with this, countryspecific factors and firm features were investigated on whether they have significant influence on the
results.
The sample of this research contains 1408 non-financial firms listed in 11 EU member states
accounting for 5632 observations. The analysis is performing for the period of 2003-2006 which is
split in two sub-periods with the introduction of IFRS on the 1st of January 2005 as division-moment.
The model of Larcker and Richardson (2004) is used to determine the use of accruals-based earnings
management. The model of Larcker and Richardson (2004) is an extended version of the Modified
Jones model (1991) proposed by Dechow et al. (1995). Larcker and Richardson (2004) extended the
Modified Jones model (1995) by including the variables Book-to-Market (BM) value and the Cash
Flow of Operations (CFO) into the model. The reason Larcker and Richardson (2004) included these
variables in their tests is that the incentives to manage earnings vary in response to growth
opportunities (BM) and current operating performance (CFO).
43
The results of Callao and Jarne (2010) show that in the period after the adoption of IFRS in Europe,
the use of earnings management measured by discretionary accruals has intensified. The results
suggest that the increase in the use of earnings management after the adoption of IFRS might be
caused by some room for manipulation based on the international standards compared to the local
standards. Some country- and firm specific factors for explaining this accounting discretion are
tested: business size, leverage, investor protection and legal enforcement. Business size and leverage
appeared to have a significant relationship with the use of discretionary accruals.
Before several scientific economic research that earlier have been conducted have been present,
next the influence of these researches on this research will be presented. The findings in these
researches about the influence of the adoption of IFRS on the total amount of the use of earnings
management and method of executing this will be used in defining in chapter 5 concerning the
hypotheses in this research. All the before presented researches, did research on the amount of the
use of earnings management executed by accruals and/or real activities changed by the introduction
of IFRS. Focussing on the total level of the use of earnings management, the findings in the previous
researches is that no evidence exists for a decline in the use of earnings management (Tendeloo and
Vanderstraelen 2005; Heemskerk and van der Tas 2006; Jeanjean and Stolowy 2008) and that
evidence exists for an increase of the use of earnings management after the introduction of IFRS
(Ewert and Wagenhofer 2005; Cohen, Dey and Lys 2008; Lippens 2010; Callao and Jarne 2010).
Concerning the use of the two methods in executing the use of earnings management, just two
studies (Cohen, Dey, Lys 2008; Lippens 2010) commented that check for a possible substitution effect
of the methods. Both studies assume a substitution effect of the use of accruals-based earnings
management to the use of real earnings management. The conclusion of both studies is that this
assumption is valid; the introduction of IFRS creates a substitution effect of the accruals-based to the
real earnings management.
Because of their connection with this research, these findings are indicative for this research.
However, the different circumstances the researches have been performed in have their influence on
the outcome. No research that has been presented before is similar to this research, because of
factors like investor protection by which French Civil Law differ from other types of law countries
which will create differences in the outcomes. These factors will be commented in the next section.
44
4.3 French Civil Law factors
Before researches about the influence of the introduction of IFRS on the use of earnings
management have been commented, next the focus will be on the distinction of this research
compared to these earlier conducted studies. The results of a research may be influenced by a
country-specific factor or a common factor of more than one country. In this research, the focus is on
countries with the French Civil Law; this type of law has its own characteristics but in addition the
countries that are labelled as French Civil Law differ from each other. In order to understand the
characteristics of French Civil Law countries, the general characteristics will be presented, but in
addition the countries will be commented separately when they do not comply with the general
characteristic.
First the distinction between the civil and the common law. The civil law uses statutes and
comprehensive codes to order legal material. Currently three common families of law within the
civil-law exist: French, German and Scandinavian (La Porta et al. 1998, p 1118). This research focusses
on the French Civil Law family including the countries The Netherlands, Belgium and France. The
common law does not use the contributions of scholars to shape the law, but used judges to resolve
disputes. Examples of countries that use this type of law are The United States of America, Canada,
Australia and India.
When comparing these families, the Scandinavian and German law create average shareholders and
creditors’ protection in which the French civil law provides the weakest protection. Before some
differences between the different civil law countries have been described, because of the use of this
type of countries in this research, next the characteristics of the French civil law will be further
explained.
For a successful implementation of IFRS and what type of earnings management by managers is
used, certain factors are essential. Are the local GAAP of a country already in line with the new
international standards and what protection for investors is already provided by the legal system? As
already mentioned in section 3.3 the three main factors that influence a successful implementation
of IFRS are (1) the quality of the standards that were used before IFRS, (2) the country’s legal and
political system and (3) the financial reporting incentives of companies in that country. (Soderstrom
and Sun 2007, p 695)
The first factor of influence is the quality of the local GAAP in The Netherlands, in Belgium and in
France that was used before the introduction of IFRS. “The UK, Ireland and the Netherlands are the
European countries of which the national accounting approaches comply the most with IAS” (Haller
45
2002, p 170) Haller (2002) states that the standards used in The Netherlands already are in
conformity with IAS, which creates the expectation of no significant difference in the management of
the published earnings between the financial reports based on Dutch GAAP and on IFRS (Haller 2002,
p 171). According to Haller (2002), Belgium and France, together with the other European Union
countries, changed their national laws that companies may base their consolidated financial annual
statements based on IAS or on US GAAP instead of their domestic rules (Haller 2002, p 169). This
statement shows that for companies it was possible to apply already with the standards that are in
conformity with IFRS before these in 2005 were obligatory introduced. Because this was a possibility,
this does not imply that companies indeed apply to this. But the companies that used US GAAP
before 2005 are excluded from the sample and consequently is assumed that the accounting
standards used before 2005, are already in conformity with IFRS which creates that the transition to
IFRS more easily.
The second factor of influence described by Soderstrom and Sun (2007) is the country’s legal and
political system, which is checked by the level of investor protection. According to La Porta et al.
(1998), common-law protects investors the most and French Civil Law countries the least (La Porta et
al. 1998, p1139). This low level of protection is expressed in the low level of information that is
communicated to investors.
Another aspect of the country’s legal and political system is the legal enforcement strength. The legal
enforcement strength is measured by the efficiency of the judicial system, the corruption and the
accounting standards. When checking for French Civil Law countries compared to other types of civil
law countries and common law countries, the French Civil Law countries have the lowest scores on
all three aspects. This implies that the French Civil Law countries have the lowest score on meeting
conditions of the judicial system, have the highest corruption level in their governments and report
the lowest amount of financial information (La Porta et al. 2000, p 10). However, based on
Burgstahler et al. (2006), for both The Netherlands and Belgium a high level of legal enforcement
strength exists. However, France does not score well on legal enforcement strength, in this situation
it is hard to express an opinion on the legal enforcement strength of the sample used in this
research.
The last country-specific factor commented is the financial reporting incentives of companies in The
Netherlands, Belgium and France. Financial reporting is about finding an equilibrium of the costs for
disclosing financial information and the benefit of meeting contracting parties’ demand for
information (Soderstrom and Sun 2007, p 691). The amount of disclosed and requested depends on
46
four factors: (1) financial market development, (2) capital structure, (3) ownership structure and (4)
tax system (Soderstrom and Sun 2008, p 691-695).
The development on the financial market is about the demand for information to reduce the
information asymmetry. When an information asymmetry exists, adverse selection may rise due to
hard differentiating between good and bad firms (Soderstrom and Sun 2008, p 691). Burgstahler et
al. (2006) conclude that public firms in contrast to private firms in countries with large and highly
developed equity market engage less in the use of earnings management (Burgstahler et al. 2006, p
36).
The structure of ownership in addition is a motive of financial reporting; when a firm is owned by a
small amount of people, low incentives exist for financial reporting. When the same people both
execute and control the activities, financial reporting to outsiders is not necessary. When foreign
investors in the financing are included, due to a lack of knowledge the demand for information will
be higher. Ownership concentration is a substitute for legal protection. This is because: (1)
shareholders need more control to avoid being expropriated by managers, (2) small investors are not
interested in purchasing stocks due to less protection (Soderstrom and Sun 2008, p 694).
The last factor of influence on the incentive for financial reporting is the tax system in a country.
Several ways exist a tax system can affect the quality of earnings: (1) earnings are less likely to reflect
the underlying business in a country with a close linkage between financial accounting income and
the taxable income (Guenther and Young, 2000) (2) A high tax rate will increase the incentive to
reduce taxable income. (3) A country’s tax authority has statutory power in verifying a company’s
profits.
When checking for these financial reporting incentive factors with the research, no information
asymmetry exists because all companies are listed and have many external funders. Concerning the
tax system, because of the lack of information about the tax system of The Netherlands, Belgium and
France and its influence on financial reporting and the use of earnings management, it is hard to
draw a conclusion. Concerning the factors information asymmetry and the structure of ownership, all
companies in the intended sample are listed and consequently obliged to publicly report their
financial information. This is in line with the structure of the ownership of the companies; many
shareholders creates a high incentive for financial reporting.
4.4 Summary
In this chapter some earlier conducted, related researches are commented to realise a view on how
47
similar, related researches have been executed and what the findings are of these researches. These
researches have been commented shortly before the factors of influence on the transition to IFRS
have been commented related to The Netherlands, Belgium and France. With this context, the subquestions 6 and 7 about prior literature and researches and the French Civil Law specific factors have
been answered. This information will be used for the determination of the hypotheses in chapter 5.
All the researches commented in section 4.2, concern the influence of the new accounting standards
on the use of earnings management. When checking the findings of these researches about the
change in the total amount of the use of earnings management based on the new accounting
standards, the use of earnings management did not decline (Tendeloo and Vanderstraelen 2005;
Heemskerk and van der Tas 2006; Jeanjean and Stolowy 2008) or even an increase in the use of
earnings management exists (Ewert and Wagenhofer 2005; Cohen, Dey and Lys 2008; Lippens 2010;
Callao and Jarne 2010).
Concerning the determination of a substitution in the use of earnings management methods has
occurred, just two studies (Cohen, Dey, Lys 2008; Lippens 2010) are usable. Both studies investigate
the total amount of the use of earnings management and a possible substitution effect in the
methods concerning the use of earnings management. Both studies assume that the introduction of
the new accounting standard has created a substitution effect of the use of accruals-based to the use
of real earnings management. The findings of the studies are unanimous; a substitution effect exists
in the use of accruals-based to the use of real earnings management.
This research distinguishes from these researches by checking the use of both accruals-based and the
use of real earnings management and the focus on French Civil law countries. The influence of the
factor French Civil law is checked by three factors that have influence on a successful transition from
local GAAP to IFRS according to Soderstrom and Sun (2007): (1) the quality of the standards that
were used before IFRS, (2) the country’s legal and political system, and (3) the financial reporting
incentives of companies in that country.
Analysing whether local GAAP was already in conformity with IFRS, the findings suggest that the
GAAP in The Netherlands already was in conformity with these standards, but this is not assured in
Belgium and in France. In these countries it was possible to apply to the accounting principles
prepared by IAS but this was not obliged. However, companies that applied US GAAP as accounting
principles in 2004 are excluded from the sample. Consequently is assumed that in addition to The
Netherlands, the companies from Belgium and France were already in conformity with the
accounting principles of the IFRS.
48
The second factor of influence is the country’s legal and political system. According to La Porta et al.
(1998), French Civil Law countries have the weakest form of investor protection compared to other
types of law. Another indicator to check for the country’s legal and political system is the legal
enforcement strength of a company. Both The Netherlands and Belgium have a high score on this
indicator in contrast to France (La Porta et al. 2000, p 10). The last factor commented to check the
influence of the French Civil law is the financial reporting incentives of companies. Because all
companies that will be used for this research are listed, their financial information is publicly
available. Further information about the sample that will be used for the research, will be
commented in section 6.4.
By executing the research, some factors that possible have their influence on the use of earnings
management before and after the implementation of IFRS are tested. The influence of the quality of
the accounting standards used before IFRS is checked by comparing the use of earnings management
before and after the implementation of IFRS. The country’s legal and political system is tested by
comparing the use of earnings management in The Netherlands on one hand and Belgium and France
on the other hand. The last factor, the financial reporting incentives of companies, is not tested
because the companies that will be investigated are obliged to publicly report their financial
information.
Before the empirical part of this research is performed, in the next chapter the hypothesis will be
determined.
49
5 Hypotheses
5.1 Introduction
The important aspects of this thesis, the use of earnings management and IFRS, and earlier
conducted, related research in previous chapters have been commented. The findings of this earlier
part of this research will be used as guideline for determining in this chapter the hypotheses.
5.2 Hypotheses development
In order to achieve a better functioning of the internal market, a single set of international
accounting standards for preparing the consolidated financial statements of publicly traded
companies by the IASB was introduced (EC No 1606/2002, p243/1). This better functioning of the
internal market should be accomplished by providing a high degree of transparency and
comparability of the financial reports provided by all international publicly traded companies
according to the European Parlement (EC No 1606/2002, p243/2). With fair-value accounting as
important principle of IFRS, IFRS should increase the quality of the published reports, including a
decrease in the use of earnings management. Many researches (Tendeloo and Vanstraelen (2005),
Ewert and Wagenhofer (2005), Heemskerk and van der Tas (2006), Jeanjean and Stolowy (2008),
Lippens (2010) and Callao and Jarne (2010)) have researched whether the use of IFRS indeed
decreased the use of earnings management. The overall findings of these researches, as commented
in chapter 4, are that the use of earnings management by the introduction of IFRS did not decrease
and sometimes even increased.
Although previous researches in general detected no decrease in the use of earnings management,
specific circumstances causes that this conclusion cannot just be adopted for this research. One of
the differences is that all commented researches were executed with data from another country or a
combination of countries. Next to this factor, other factors exist that influence the transition from
the local GAAP to IFRS. According to Soderstrom and Sun (2007), three factors can be distinguished:
(1) the quality of the standards used before IFRS, (2) the country’s legal and political system and (3)
the financial reporting incentives of companies (Soderstrom and Sun 2007, p 695).
When investigating these factors in combination with the French Civil law characteristics as signalled
in section 4.3, the assumption is that it is hard to draw an overall vision on the influence of these
factors concerning all intended to select three countries. No general finding by earlier conducted
researches on the influence of IFRS on the use of earnings management and the fact that the local
GAAP was already in conformity with IFRS, consequently the next hypothesis is stated:
50
H1
The total degree of the use of earnings management did not change by the transition from local
GAAP to IFRS in 2005 in The Netherlands, in Belgium and in France
Next to the sum, will the use of accruals-based and real earnings management independently before
and after the introduction of IFRS is tested. Graham et al. (2005) found evidence that managers,
despite the higher costs, switch from accruals-based earnings management to real activities
manipulation because it is possibly harder to detect (Graham 2005, p 32-35). This finding is
confirmed by the researches of Cohen, Dey, Lys (2008) and Lippens (2010). Cohen, Dey, Lys (2008)
investigated the level of earnings management, both accruals-based and real earnings management,
before and after the introduction of SOX. The results of Cohen, Dey, Lys (2008) indicate that earnings
management increased preceding SOX. Next to this, the level of accrual-based earnings management
declined while the level of real earnings management increased significantly after the passage of SOX
(Cohen, Dey, Lys 2008, p 785). Lippens (2010) investigated the influence of the mandatory adoption
of IFRS in 2005 and its influence on the level of earnings management. According to Lippens (2010)
the use of both methods for executing earnings management increased after the adoption of IFRS.
Another conclusion of Lippens (2010) was the substitution of both methods for executing earnings
management.
The switch from accruals-based to real earnings management which has occurred according to
Graham et al. (2005), Cohen, Dey, Lys (2008) and Lippens (2010) by new accounting standards will be
investigated. Therefore, the second hypothesis is stated:
H2
There has been a substitution effect from using accruals-based to real earnings management by
managers after the introduction of IFRS in 2005 in The Netherlands, Belgium and France
5.3 Summary
A single set of accounting standards exists for a better functioning of the market by creating more
transparency and comparability of annual financial statements; these were the main purposes of the
IAS with the introduction of IFRS. When these purposes of IFRS are linked to this research, the
purposes of the adoption of IFRS by managers should decrease the use of earnings management.
According to earlier conducted researches (Tendeloo and Vanstraelen (2005), Ewert and Wagenhofer
(2005), Heemskerk and van der Tas (2006), Jeanjean and Stolowy (2008), Lippens (2010) and Callao
and Jarne (2010)), the adoption of IFRS did not decrease the use of earnings management; it did not
change or even increased. Because of specific circumstances in these researches, the findings of
51
these researches cannot just be adopted concerning this research. Next to specific factors of the
intended sample, factors exist that influence the transition from local GAAP to IFRS: (1) the quality of
the standards used before IFRS, (2) the country’s legal and political system and (3) the financial
reporting incentives of companies. Because of no general findings by earlier conducted researches on
the influence of the adoption on the use of earnings management and the fact that the local GAAP
was already in conformity with the IFRS, the next hypotheses have been stated:
H1
The total degree of the use of earnings management did not change by the transition from local
GAAP to IFRS in 2005 in The Netherlands, in Belgium and in France
H2
After the introduction of IFRS in 2005 in The Netherlands, Belgium and France by managers a
substitution effect exists from using accruals-based to the use of real earnings management.
With the determination of the hypotheses that will be tested in chapter 7, sub-question 8 will be
answered.
52
6 Research Design
6.1 Introduction
In order to test the influence of IFRS on the use of earnings management, first the amount of the use
of earnings management has to be determined. This amount is determined by focussing on the
amount of discretionary accruals for the accruals method and the difference between the ‘normal’
and the actual level concerning the real activities manipulation method.
Concerning the accruals-based method, the discretionary part of the accruals has to be determined
by subtracting the non-discretionary part of the accruals of the total amount of the accruals. The
determination of the total amount and the non-discretionary part of the accruals will be performed
with the use of Modified Jones Model (1995).
In section 6.2.2, the method for detecting real earnings management is commented. First the
‘normal’ level of the real earnings management indicative variables is determined with the model
developed by Roychowdhury (2006) before the difference between the ‘normal’ and actual level is
determined as indication for real earnings management.
As signalled in section 3.4 about the detection of the use of earnings management, both accrualsbased and real earnings management models need regression coefficients to determine the use of
earnings management. Because these coefficients first need to be determined, the determination of
these coefficients for both methods is commented first. With these coefficients, the nondiscretionary part of the accruals and the ‘normal’ level of the real earnings management variables
will be determined.
The next step is to use the discretionary accruals, the difference between the ‘normal’ and the actual
level of the real earnings management indicating variables and the sum of both methods, indicating
the total amount of earnings management, as independent variables in the multiple regressions. In
all three multiple regressions which are performed and commented in section 7.3, the independent
variables country, accounting standard and size will be used to check their influence on the use of
earnings management. Before the influence of the independent variables on the dependent variable
is commented, first the assumptions have to be met. According to Norušis (1995), following
assumptions have to be met before regressions are performed:
53
 The relationship between the dependent and the independent variables is linear
 For each combination of values of the independent variables, the distribution of the
dependent variable is normal with a constant variance (Norušis 1995, p 473)
In order to test the strength of the linear relationships the statistical tolerance will be measured. This
tolerance is the proportion of the variability of a variable that is not explained by its linear
relationships with the other independent variables (Norušis 1995, p 484). This tolerance in addition is
known as the multicollinearity of data which is checked with the Correlations table. When the
correlation between the variables exceeds 0.9, multicollinearity is present which influences the
results of the test negatively. The second assumption about the normal distribution of the dependent
variable is checked by a histogram and a normal probability plot.
After this, the Adjusted R Square about the explanatory power of the model, the significance of the
model and the sign, size and significance of the coefficients of the independent variables are
commented. The results of the multiple regressions will be used to answer the stated hypotheses.
Based on the before overview of the research, each part will be commented separately. In this
chapter will the Modified Jones Model (1995) and the model developed by Roychowdhury (2006) be
commented in combination with the data sample in section 6.2. The data sample and the data
attainability will be explained in section 6.3 and 6.4.
6.2 Models for detecting Earnings Management
In this section, the Modified Jones Model (1995) and the model developed by Roychowdhury (2006)
will be explained by showing the steps that have to be taken to conclude whether earnings have
been managed by accruals and real activities.
6.2.1 Modified Jones Model (1995)
The Modified Jones Model (1995) is an adjusted version of the Jones Model (1991) and developed by
Dechow et al. (1995). The Modified Jones Model (1995) uses the following equation to determine the
total amount of accruals:
TAi,t = [ ΔCAi,t – ΔCLi,t – ΔCASHi,t + ΔSTDLi,t – DEPi,t ] / (Ai,t-1) (1)
TA = total amount of accruals
ΔCA = change in current assets
ΔCL = change in current liabilities
54
ΔCASH = change in cash equivalents
ΔSTDL = change in debt included in current liabilities
DEP = depreciation and amortization expense
A = accruals
t = year index, range 1997 - 2007
i = firm index, range 1 - 95
The determination of the total amount of accruals is the first step in the process of detecting
earnings management by accruals. Because the values of all the independent variables of the formula
are known, the total amount of accruals can be determined. The firm index shows that the total
sample contains 95 companies, which will further be explained in section 6.3.
The second step in the determination of the use of accruals-based earnings management is about the
focus on specific accruals and the estimation of the parameters α1, α2 and α3. Now that the total
amount of accruals is determined, the variables assets, revenues and PPE are used to estimate the
firm-specific parameters a1, a2 and a3.
Tai,t = a1 [1/Ai,t-1] + a2 [ΔREVi,t] + a3 [PPEi,t] + υi,t
TA = total accruals
A = total assets
ΔREV = change in revenues
PPE = gross property, plant and equipment
υ = error term
a1, a2, a3 = regression coefficients
t = year index, range 1997 – 2001
i = firm index, range 1 – 95
The regression coefficients will be calculated with the use of data from the period 1997-2001 of all
variables to measure the degree to which a dependent variable changes by a change of the
independent variable. Although the Thomson One Banker, the database that is used for this research,
gives data till 1970, the information of most companies ends at 1997. Consequently the period of
1997-2001 is chosen as the historical period for this research to ensure completeness of information.
With the use of SPSS, the regression coefficients and in addition the overall explaining power of the
model as well as the significance of the individual variables will be determined. In combination with
55
the R Square, the explanation power of independent variables on the dependent variable, the
reliability of the outcomes is determined.
With the use of the regression coefficients a1,a2 and a3 as estimations of α1, α2 and α3, the
determination of the amount of non-discretionary accruals is determined by using the following
formula:
NDAi,t = α1 (1/Ai,t-1) + α2 (ΔREVi,t – ΔRECi,t/Ai,t-1) + α3 (PPEi,t)
NDA = Non-discretionary accruals
A = total assets
ΔREV = change in revenues
ΔREC = change in net receivables
PPE = gross property plant and equipment
α1, α2, α3 = regression coefficients
t = year index, range 2002 - 2007
i = firm index, range 1 - 95
The change in revenues is determined by using the change in the amount of Sales. When the nondiscretionary part of the accruals is determined, the final step is the determination of the
discretionary part of the accruals.
DAi,t = TAi,t – NDAi,t
DA = Discretionary Accruals
TA = Total Accruals
NDA = Non-Discretionary Accruals
t = year index, range 2002 – 2007
i = firm index, range 1 – 95
When the amount of discretionary accruals is determined for each year, this amount can be used as
dependent variable in a multiple regression to determine whether accounting standards, country and
size has influence of the amount of accruals-based earnings management. With a fundament of
earlier conducted related researches (Kothari et al. 2005; Tendeloo and Vanstraelen 2005;
Heemskerk and van der Tas 2006; Lippens 2010), the variables country and size are added to the
56
multiple regression to check their influence on the use of earnings management. The results of the
multiple regressions can be found in section 7.3.
6.2.2 Roychowdhury (2006)
In order to determine the level of real earnings management, the model of Roychowdhury (2006) will
be used. For this research, the variables cash flow from operations (CFO), costs of goods sold (COGS),
change in inventory (ΔINV) and production costs (PROD) are used. The normal level of these variables
is estimated by the model developed by Roychowdhury (2006) which follows the model developed
by Dechow et al. (1998).
The first equation is about the determination of the normal level of CFO, by expressing this as a linear
function of sales and change in sales in the current period (Roychowdhury 2006, p 344):
CFOi,t / Ai,t-1 = a0 + a1*(1/Ai,t-1) + b1*(Si,t/Ai,t-1) + b2*(ΔSi,t/Ai,t-1) + εt,
CFO = cash Flow of Operations
A = total assets
S = sales
ΔS = change in Sales
a1, a2, b1, b2 = regression coefficients
ε = error term
t = year index, year 1997 - 2001
i = firm index, range 1 – 95
This way of determining the ‘normal’ level and comparing this normal level to the actual level is in
addition used for COGS, inventory growth and production costs as variables for the other methods of
manipulation. The normal level of COGS is expressed by:
COGSi,t/Ai,t-1 = a0 + a1*(1/Ai,t-1) + b*(Si,t/Ai,t-1) + εt
COGS = Cost of Goods Sold
A = Assets
S = Sales
a0, a1, b = regression coefficients
ε = error term
t = year index, year 1997 - 2001
i = firm index, range 1 - 95
57
Comparable to the determination of normal level of COGS is the normal level of the change in
inventory determined. The difference between the determination of the normal levels is the addition
of the variable change in sales in the previous year scaled by total assets in the previous year.
ΔINVi,t/Ai,t-1 = a0 + a1*(1/Ai,t-1) + b1*(ΔSi,t/Ai,t-1) + b2*(ΔSi,t-1/Ai,t-1) + εt
ΔINV = change in inventory
A = total assets
ΔS = change in Sales
a0, a1, b1, b2 = regression coefficients
ε = error term
t = year index, year 1997 - 2001
i = firm index, range 1 - 95
With the use of the equations of COGS and change in inventory can the equation of the production
costs be determined. Roychowdhury (2006) defines production costs as the sum of COGS and the
change of inventory, which is expressed in the following equation (Roychowdhury 2006, p 345):
PRODi,t/Ai,t-1 = a0 + a1*(1/Ai,t-1) + b1*(Si,t/Ai,t-1) + b2*(ΔSi,t/Ai,t-1) + b3*
(ΔSi,t-1/Ai,t-1) + εt
PROD = production costs
A = total assets
S = sales
ΔS = change in Sales
a0, a1, b1, b2, b3 = regression coefficients
ε = error term
t = year index, year 1997 - 2001
i = firm index, range 1 - 95
The last equation of Roychowdhury (2006) is about the determination of the ‘normal’ level of
discretionary expenses. Because of a lack of data on Research and Development (R&D) and Selling,
General and Administrative (SG&A) expenses, this equation has been omitted. Like Lippens (2010),
the determination of the use of real earnings management will be done by checking the variables
cash flow of operations, costs of goods sold, inventory and production costs.
58
Now that the values of the accruals-based and real earnings management has been determined, will
these values be used as dependent variables in a multiple regression. But before these values will be
used as dependent variable, will the sum of both methods, the total amount of earnings
management, be used as dependent variable. With the use of the multiple regressions, the influence
of the variables country, accounting standard and size is checked on the total amount of earnings
management, accruals-based and real earnings management.
6.3 Multiple regression analysis
The last step concerning this research is performing the multiple regressions based on the research
by Heemskerk and van der Tas (2006) and analysing the results in chapter 7. With the use of the
multiple regression analysis, the influence of the independent variables Accounting Standard,
Country and Size on the dependent variables total amount of earnings management, accruals-based
and real earnings management will be examined.
The total amount of the use of earnings management is determined by using the sum of the amount
of accruals-based and the use of real earnings management. The average amount of all the real
earnings management indicating variables together with the amount of accruals-based earnings
management is the total amount of earnings management. Because the amount of the use
ofearnings management can be both negative and positive, the absolute value in the regression is
used (Heemskerk and van der Tas 2006, p 576).
This total amount of earnings management is used as dependent variable and will be tested by the
independent variables country, accounting standard and size. The independent variable country
investigates the influence of a significant difference exists in the use of earnings management in The
Netherlands compared to Belgium and France. Because the number of companies from Belgium is
not large as will be commented in the next section, the data from Belgium and France are combined.
This in combination with the distinction of The Netherlands compared to Belgium and France when
investigating the specific factors of the French Civil law countries according to La Porta et al. (1998)
as signalled in section 4.3, substantiated the decision to combine Belgium and France. Consequently,
the multiple regression for the total amount of earnings management will be:
| TotalEM (i,t) | = γ1 + γ2 (Country) + γ3 (Standard) + γ4 (Size) + ε
| TotalEM (i,t) | = the absolute value of the total amount of earnings management, scaled by
assets in the previous period
Country = Country investigated (0 = The Netherlands 1 = Belgium & France)
59
Standard = Accounting Standard (0 = local GAAP 1 = IFRS)
Size = The company size, distinction by total assets (0 = small 1 = large)
γ1, γ2, γ3, γ4 = regression coefficients
ε = error term
t = year index, year 2002-2007
i = firm index, range 1-95
In order to perform the multiple regressions, assumptions have to be met. These assumptions will be
commented here. Multicollinearity and normal distribution will be checked by the table Correlations,
a histogram and Normal Probability Plot. After this, the results of the regression will be commented
by checking the Model Summary, ANOVA and Coefficients table. By checking these tables, the
explanatory power, significance of the model and sign, size and significance of the coefficients are
commented. By the results of the independent variable accounting standard, will the influence of
IFRS on the total amount of the use of earnings management be checked.
The same procedure will be used for the multiple regressions with the discretionary accruals and the
real earnings management as dependent variables. First the assumptions will be checked, before the
sign, the size and the significance of the coefficients are commented. The next multiple regressions
will be used to check the influence of the independent variables on the dependent variables the
discretionary accruals and the real earnings management:
| DACC (i,t) | = γ1 + γ2 (Country) + γ3 (Standard) + γ4 (Size) + ε
| DACC (i,t) | = the absolute value of the discretionary accruals, scaled by assets in
the previous period
Country = Country investigated (0 = The Netherlands 1 = Belgium & France)
Standard = Accounting standard (0 = local GAAP 1 = IFRS)
Size = The company size, distinction by total assets (0 = small 1 = large)
γ1, γ2, γ3, γ4 = regression coefficients
ε = error term
t = year index, year 2002-2007
i = firm index, range 1-95
60
| REM (i,t) | = γ1 + γ2 (Country) + γ3 (Standard) + γ4 (Size) + ε
| REM (i,t) | = the absolute value of the real of earnings management, scaled by assets in the
previous period
Country = Country investigated (0 = The Netherlands 1 = Belgium & France)
Standard = Accounting Standard (0 = local GAAP 1 = IFRS)
Size = The company size, distinction by total assets (0 = small 1 = large)
γ1, γ2, γ3, γ4 = regression coefficients
ε = error term
t = year index, year 2002-2007
i = firm index, range 1-95
The analysis of the multiple regression will indicate the influence of the independent variables on the
dependent variable. The independent variable accounting standard is determinative for whether
hypothesis 2 about the possible substitution effect is approved or rejected.
In order to perform all these statistical tests and regressions, data is necessary. In the next sections,
the data sample and the attainability of the data is commented.
6.4 Data sample
With the Wharton Research Data Service (WRDS), all listed companies in The Netherlands, Belgium
and France active in the period of 2002-2007 were determined. Because of an equal comparison of
periods before and after the introduction of IFRS in 2005 and the influence of the financial crisis
which became visible in 2008, the period of 2002-2007 was chosen. This total of companies was
reduced by checking whether these companies meet all stated requirements. These stated
requirements are: (1) listed during the whole period 2002 – 2007 (2) non-financial company (3) the
use of local GAAP before the transition to IFRS (4) transition from local GAAP to IFRS in the year
2005. After the checking for these requirements, the sample contains 95 companies.
The sample was reduced to 95 companies, but started with all listed companies from The
Netherlands, Belgium and France. Because the research period is 2002-2007, the companies have to
be listed during this period. Companies that became listed after 2002 or were not listed anymore in
2007 are executed from the sample. After this first requirement, the sample contained 408
companies.
After checking on listed during the period 2002-2007, the sample is checked on the SIC-code of the
companies. Companies with SIC-codes 600-699 are banks, insurance companies and real estate
61
investors.5 According to Heemskerk and van der Tas (2006) the accruals of financial institutions differ
too much from companies in other sectors. Consequently, companies with SIC-code 600-699 are
excluded from the sample. Because earlier requirements already eliminated all the companies with a
SIC-code 600-699, this requirement has not eliminated a company; the sample still contained 408
companies.
Because this research is about the use of earnings management and the influence of the new
accounting standards IFRS, the transition from local GAAP to IFRS is of importance. Companies need
to have applied local GAAP till 2004 and made an obliged transition to IFRS in 2005. The obliged
transition from local GAAP to IFRS in 2005 decreased the number of companies that meet all
requirements to 283 companies.
The data of these 283 companies was attained by the Thomson One Banker database. Not all data of
all companies was available, the companies of which not all data was available were removed from
the sample. After this, the final sample for this research contains 95 companies. The distribution of
these companies is 50 companies from The Netherlands, 5 from Belgium and 40 from France. This
final sample will be used for the research; a list of all companies in the sample is presented in
appendix 2 on page 99.
6.5 Data attainability
All the data that is needed for this research can all be found in the annual reports of the 95 selected
companies which are publicly available because all companies are stock exchange quoted. In order to
get easy access to all these data, the Thomson One Banker database is used. Both the historical data
that is used to determine the regression coefficients as the data for the research period are available
in this database. The Thomson One Banker database is the only database used to collect data; this
decreases the quantity of the selected companies because only companies with full data-disclosure
are selected but it increases the quality of the sample because of the uniformity in the value
determination of variables.
6.6 Summary
In this chapter the research design is commented, which is the answer on sub-question 9. The
research design is about the models for determining the accruals-based and the real earnings
management, the multiple regressions and the analysis of the results. In order to perform the models
and the regressions, data is necessary. Only the data from companies that meet certain requirements
is used.
5
http://www.sec.gov/info/edgar/siccodes.htm
62
With the use of the Modified Jones Model (1995), historical data, regression coefficients are
estimated to determine the amount of non-discretionary accruals. By subtraction these nondiscretionary accruals of the total accruals, the amount of discretionary accruals is determined which
is the indication of the use of accruals-based earnings management.
Real earnings management is checked for by the model developed by Roychowdhury (2006).
Roychowdhury (2006) uses the variables cash flow of operations (CFO), Cost of Goods Sold (COGS),
change in inventory (ΔINV), production costs (PROD) and discretionary expenses (DISEXP) to
determine the use of real earnings management. Because of a lack of information about the
discretionary expenses, the variable discretionary expenses is left out in this research like Lippens
(2010). For the variables CFO, COGS, ΔINV and PROD is the ‘normal’ level determined and compared
to the actual level. The difference between the actual and the ‘normal’ level is indicative for the
amount of earnings management with this variable. The average amount of the four variables will be
used as the amount of earnings management by real activities.
These indication values for the use of accruals-based and real earnings management are both used as
dependent variables in multiple regressions. Before the two methods are used separately, the sum of
both methods will be used as the total amount of earnings management as dependent variable in a
multiple regression. With the use of the multiple regressions, the influence of the independent
factors country, accounting standard and size on the use of earnings management is examined.
Noticeable is the use of the independent variable country; The Netherlands is compared to Belgium
and France. The reason for this is the small amount of data from Belgium and the differences
between The Netherlands compared to Belgium and France according to La Porta et al. (1998) when
checking the outcome of certain law-factors as commented in section 4.3.
The models described need input to be performed, which will be data from stock exchange quoted
companies from The Netherlands, Belgium and France. Not every company is suitable for this
research, the restrictions the selected companies need to comply are (1) listed during the whole
period 2002 – 2007 (2) non-financial company (3) the use of local GAAP before the transition to IFRS
(4) transition from GAAP to IFRS in the year 2005. The data of the companies is attained with the use
of the Thomson One Banker database. When data of a company is missing, the company will be
excluded from the sample instead of checking another database. The consequence of this is that the
data sample is not large but it increases the quality of the sample by the uniformity in the value
determination of variables. The quality of the sample is of more importance than a larger sample
because the sample still contains 95 companies.
63
With the use of the data of the 95 selected companies, the regression coefficients are determined
and the multiple regressions performed. The regression coefficients for the determination of the
non-discretionary accruals and the ‘normal’ level of real earnings management variables will be
commented by checking the explanatory power of the independent variables by the adjusted R
Square and the sign, the size and the significance of the coefficients. By determining the amount of
non-discretionary accruals and the ‘normal’ level of the real earnings management variables, the
discretionary accruals and the difference between the ‘normal’ and actual level of the real earnings
management variables can be determined that indicate the use of earnings management. These two
indications for the use of earnings management together with the sum of both methods are used as
dependent variables in the multiple regressions. The independent variables country, accounting
standard and size are used to test their influence on the use of earnings management in total, by
accruals and by real activities. Before the influence of these independent variables is checked, first
the assumptions of multicollinearity and the normal distribution are checked at every multiple
regression separately by the table of Correlations, a histogram and a Normal Probability Plot. After
this, the Model Summary and the ANOVA Table are commented to check the explanatory power of
the independent variables and the significance of the model. Finally, the sign, the size and the
significance of the coefficients of the independent variables are commented in chapter 7 to check
whether hypothesis 1 and 2 are approved or rejected.
In the next section, the research will be performed and commented. First, regressions are performed
to determine the values of coefficients that are necessary to determine the amount of nondiscretionary accruals and the ‘normal’ level of real earnings management indicative variables. With
the results that are commented in section 7.2.1 and 7.2.2, it is possible to determine the amount of
earnings management by both accruals and real activities. In section 7.3 the results of the multiple
regressions with the amount of accruals-based and real earnings management and the sum of both
methods as dependent variables are commented.
64
7 The results
7.1 Introduction
In the chapter before the research design has been determined. In this chapter the results will be
presented. In section 7.2 the regression coefficients for determining the amount of earnings
management by both methods are determined and commented. In section 7.3 the multiple
regressions are commented to check on the influence of the introduction of IFRS, the different
countries and the size of the selected companies on the total amount of earnings management and
the amounts of the use of earnings management by the accruals-based and real method.
7.2 Regression Coefficients
The first step in the process of checking the influence of the transition to IFRS on the use of earnings
management is the determination of regression coefficients. With the use of the regression
coefficients, determined with the use of data from the period 1997-2001, the non-discretionary part
of the accruals and the ‘normal’ level of the real earnings management indicating variables are
determined.
7.2.1 Accruals-based earnings management coefficients
The determination of the use of accruals-based earnings management is performed by checking the
amount of discretionary accruals. This amount is determined by the subtraction of the nondiscretionary part of the accruals of the total amount of accruals. The total amount of accruals is
determined with formula 1 as signalled in section 6.2.1:
TAi,t = [ ΔCAi,t – ΔCLi,t – ΔCASHi,t + ΔSTDLi,t – DEPi,t ] / (Ai,t-1) (1)
TA = total amount of accruals
ΔCA = change in current assets
ΔCL = change in current liabilities
ΔCASH = change in cash equivalents
ΔSTDL = change in debt included in current liabilities
DEP = depreciation and amortization expense
t = year index
i = firm index
With the use of the total amount of accruals, the estimated regression coefficients for the nondiscretionary accruals are determined. These regression coefficients are calculated with data from
65
the period 1997-2001 and SPSS. SPSS provides more information about the test than just the
regression coefficients. In the text only the tables Summary and Coefficients are provided; the
ANOVA table is available in appendix 3. For the determination of the amount of earnings
management by real activities, next only the table Coefficients will be provided; other results of SPSS
are available in appendix 3.
Model Summary
Model
1
R
R Square
.544a
Adjusted R
Std. Error of the
Square
Estimate
.296
.291
.16852
a. Predictors: (Constant), PPE / A (t-1), 1 / A / (t-1), Change S / A (t-1)
Important information based on SPSS is the reliability of the test and the correlation between the
various variables. Based on the table Model Summary, the correlation between the dependent and
independent variables which can be found by checking the adjusted R Square is 0.291. This value can
be interpreted as 29.1% of the amount of Total Accruals is explained by the independent variables.
Next to the importance of the correlation between the dependent variable and the independent
variables, are the coefficients important for the determination of the non-discretionary part of the
accruals.
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
-.572
.015
1 / A (t-1)
3.420
.298
Change S / A (t-1)
.044
PPE / A (t-1)
.248
Coefficients
Beta
t
Sig.
-38.843
.000
.444
11.475
.000
.011
.155
3.988
.000
.037
.258
6.661
.000
a. Dependent Variable: TA / A (t-1)
The regression coefficients have been determined by checking for the coherence of the various
independent variables with the dependent variable. The determination of the regression coefficients
has been executed with historical data, data from the period 1997-2001. The results of the historical
data will present an estimation of the coherence of the variables for determining the nondiscretionary accruals part in the research period 2002-2007. When investigating the outcome of the
regression, the coefficients α0, α1, α2 and α3 in column Beta (B) are respectively -0.572; 3.420;
66
0.044; and 0.248. This shows a positive slope exists of the independent variables on the dependent
variable.
Another important aspect of the table Coefficients is the significance of the variables. When checking
the table, a significance of 0.000 exists for all variables. In the researches commented in chapter 4, a
significance level of 5% is used, when applicable. No reason exists to change this level; the level of 5%
(0.05) will be used to test the significance. All variables with their coefficients appear to be
significant.
The coefficients that are found in this regression analysis are used to determine the nondiscretionary part of the accruals. In order to determine this non-discretionary part, the coefficients
are combined with the outcome of the independent variables. The value of the independent
variables is determined by using data from the period 2002-2007. The combination of coefficients
and independent variables will present the non-discretionary part of the accruals for the period
2002-2007. But because the discretionary part of the accruals is the indicator for the use of earnings
management, the non-discretionary part of the accruals, which just has been determined, is
subtracted from the total amount of accruals. The amount of the discretionary accruals is used as
dependent variable in a multiple regression to check the influence of the independent variables
country, accounting standard and size. But before the multiple regressions are commented will first
the regression coefficients of the real earnings management indicating variables be commented.
7.2.2 Real earnings management coefficients
The method of managing earnings by adjusting real activities is the other method that will be used to
determine the use of earnings management. Like Lippens (2010), the variables cash flow of
operations, costs of goods sold, change in inventory and production costs are used as indicators for
the use of real earnings management.
In contrast to the regression with the accruals-based method, will next only the table Coefficients be
present, the rest of the results are available in appendix 3. But like the previous regression, will the
explanatory power of the test, the coefficients and the significance of the coefficients be
commented. The coefficients, determined with historical data from the period 1997-2001, that are
found by the regressions will be used to determine the ‘normal’ level of the use of real earnings
management indicating variables for the period 2002-2007. The difference between the ‘normal’ and
the actual level of the variable is used as dependent variable in the multiple regression that is
commented in the next section. Before this, the results of the regressions are commented.
67
Cash Flow from Operations
The first indicator for the use of real earnings management that will be commented is the cash flow
of operations. The outcome of SPSS shows a R Square of 0.081, which implies that the correlation
between the cash flow of operations with the variables Change in Sales / A (t-1); 1 / A (t-1) and Sales
/ A (t-1) is 8,1%, which is a low percentage. When investigating the ANOVA-table, a significance of
0.000 is noted. This shows that a significant relationship exists between the dependent variable and
one or more of the independent variables.
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.105
.011
1 / A (t-1)
.144
.211
S / A (t-1)
-.009
.061
Change S / A (t-1)
Coefficients
Beta
t
Sig.
9.293
.000
.030
.680
.497
.007
-.085
-1.332
.184
.011
.347
5.476
.000
a. Dependent Variable: CFO / A (t-1)
The result of SPSS of most importance is the table with the coefficients. When checking this table,
first the significance of the independent variables is checked. Only a significant relationship exists
between CFO and Change in Sales, both scaled by Assets (t-1) (0.000). The relationships of CFO with
the other two variables, 1 / Assets (t-1) and Sales / Assets (t-1) are not significant (resp. 0.497 and
0.184).
Next to the significance of the variables, the B-values are in addition of importance. The regression in
SPSS has determined the coefficients that will be used to determine the ‘normal’ level of cash flow of
operations. The table shows the values α0 0.105; α1 0.144; α2 -0.009; and α3 0.061. With the
determined coefficients, it is possible to determine the ‘normal’ level of the cash flow from
operations in the period 2002-2007.
Costs of Goods Sold
The second variable for determining the use of real earnings management is the costs of goods sold
(COGS). Like the cash flow of operations, will the regression of the model of COGS be commented.
Notable about the model summary of the regression for the COGS is the high value of the R Square:
0.957; a high correlation of 95.7% exists between COGS and the independent variables Sales / Assets
68
(t-1) and 1 / Assets (t-1). The ANOVA table shows a significant relation between the COGS and one or
more of the independent variables (0.000).
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Coefficients
Std. Error
(Constant)
-.166
.019
1 / A (t-1)
-.206
.403
S / A (t-1)
.896
.009
Beta
t
Sig.
-8.848
.000
-.005
-.511
.610
.979
102.770
.000
a. Dependent Variable: CGOS / A (t-1)
The table of coefficients indicates a significant relation between the COGS and the Sales, both scaled
by Assets (t-1), but no significant relationship with the variable 1 / Assets (t-1) (0.610). For
determining the ‘normal’ level of COGS, the following coefficients will be used: α0 -0.166; a1 -0.206
and α2 0.896.
Inventory
The model summary of the regression performed with the dependent variable change in inventory
and the corresponding independent variables indicates a correlation of 28.1% between the
dependent variable inventory and the independent variables change in sales, change in sales (t-1)
and 1 / Assets (t-1).
The ANOVA table shows a significant relation (Sig. 0.000) between the dependent variable change in
Inventory / Assets (t-1) and the predictors Change in Sales / Assets (t-1), Change in Sales (t-1) / Assets
(t-1) and 1 / Assets (t-1).
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.006
.003
1 / A (t-1)
-.057
.115
.058
-.008
Change S / A (t-1)
Change S (t-1) / A (t-1)
a. Dependent Variable: Change INV / A (t-1)
69
Coefficients
Beta
t
Sig.
1.774
.077
-.019
-.494
.622
.004
.538
13.701
.000
.007
-.043
-1.100
.272
The coefficients table shows that one coefficient is significant and two are not. Only the variable
change in Sales / Assets (t-1) is significant with a significance level of 0.000. The other variables are
not significant with values of 0.272 and 0.622. The other aspect of the Coefficients table is the Bvalue of the variables; the coefficients of the independent variables. The coefficients that are used
for the determination of the normal level of inventory are α0 is 0.006; α1 is -0.057; α3 is 0.058 and
α4 is -0.08.
Production Costs
The last variable that is used for the determination of the use of real earnings management is
production costs. Like with the variable COGS, a high value of the R Square (0.956) exists, which
indicates a high correlation (95.6%) between the production costs and the variables that are used as
independent variables for the production costs. These variables are Change in Sales (t-1), 1 / Assets
(t-1), Change in Sales / Assets (t-1) and Sales / Assets (t-1). The ANOVA table shows a significant
relationship (sig. 0.000) between the dependent variable Production Costs and the independent
variables, which are just signalled.
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
-.216
.023
1 / A (t-1)
-.434
.422
S / A (t-1)
.950
Change S / A (t-1)
Change S (t-1) / A (t-1)
Coefficients
Beta
t
Sig.
-9.545
.000
-.010
-1.028
.304
.013
1.011
70.853
.000
-.055
.022
-.035
-2.485
.013
-.093
.027
-.034
-3.452
.001
a. Dependent Variable: PROD / A (t-1)
The table Coefficients shows that three variables and their coefficients are significant and one is not
significant. Only the variable 1 / Assets (t-1) is not significant (0.304), the variables Sales / Assets (t-1)
(0.000); Change in Sales / Assets (t-1) (0.013) and Change in Sales (t-1) / Assets (t-1) (0.001) are
significant. The coefficients of the independent variables are: 1 / Assets (t-1) -0.434; Sales / Assets (t1) 0.950; Change in Sales / Assets (t-1) -0.055 and Change in Sales (t-1) / Assets (t-1) -0.093.
With the coefficients that are found in the regressions, the ‘normal’ level of the variables cash flow of
operations, costs of goods sold, and change in inventory and production costs will be determined.
This ‘normal’ level is compared to the actual levels; the difference is indicative for the use of real
earnings management.
70
The difference between the ‘normal’ and actual level of the real earnings management indicating
variables will be used as dependent variable in a multiple regression in the next section. But before
both methods are used as dependent variables separately, will the sum of both methods indicating
the total amount of the use of earnings management, be used as dependent variable in a multiple
regression. Further explanation and the outcomes of the multiple regression will be commented in
the next section.
7.3 Multiple regressions
Multiple regression analyses indicate the influence of independent variables on a dependent variable
(De Vocht 2007, p 198). In this research, the total amount of earnings management, the amount of
earnings management by accruals and real activities are used as dependent variables. The
independent variables accounting standards, country and size are used to test whether and, if so,
how much influence the variables have on the different dependent variables.
Before the multiple regression analyses are performed, some assumptions have to be met. The first
assumption is about the sample size; according to Tabarnick and Fiddel (1996), the sample size of a
multiple regression should exceed 50 plus 8 times the number of independent variables (Tabarnick
and Fidell 1996, p 132). The size of the sample is 95, which exceeds the required number of 74. Other
assumptions that have to be met are:
 All variables are interval- or ratio scaled variables
 There is a theoretical causal relation between the dependent and independent variables
 The model is linear
 There is no multicollinearity
 For every combination of values of the independent variables is the population a normal
distribution of the dependent variable, where these normal distributions have the same
variance (De Vocht 2009, p 199)
The first assumption is about the variables; all variables should be interval- or ratio scaled. When a
variable is not interval- or ratio scaled like the variable country, the values of the variable are
changed into ratios by replacing names by numbers. According to earlier conducted, related
researches, the variables that are tested should have a relation. The regressions will tell us more
about the influence and relation between the dependent and independent variables.
71
The sample will be tested on outliers by checking for data that exceeds three times the standard
deviations, like SPSS suggests. By determining the mean and standard deviation of the samples, the
outliers are determined and eliminated from the sample. In order to create a data set that is
sufficient for performing the multiple regressions, the mean value and standard deviation of the
relevant dataset are determined. The values of the dataset that exceed three times the standard
deviation are excluded from the dataset.
By elimination this values from the total of 570 company-years, 530 company-years are used for the
regression with the total amount of earnings management, 534 company-years for the accrualsbased method and 529 company-years for the real method as dependent variable. The results of the
three multiple regressions provided by SPSS are commented in the next sections. Before the results
of a regression are commented will the assumptions of multicollinearity and normal distribution be
commented. When the correlation between the variables exceeds 0.9, multicollinearity is present
which influences the outcome of the test negatively. The normal distribution is of the dataset is
checked by a histogram and a normal probability plot.
After these assumptions have been commented, the outcome of the model is commented. What do
the tables Model Summary, ANOVA and Coefficients express about the correlation and the
significance of both the total test as the coefficients of the independent variables. Not all results will
be commented including the tables and figures belonging to these results. When the table or figure
are not included in the text, there will be referred to the relevant table or figure that is available in
appendix 3. The results of the multiple regressions, will present an overview on the influence of the
independent variables country, accounting standard and size on the use of accruals-based, real and
the total amount of earnings management.
In the next sections, the results of the multiple regressions are commented.
7.3.1 Total amount of Earnings management
The first multiple regression is about the influence of the variables country, accounting standard and
size on the dependent variable total amount of earnings management. The dataset of 530 companyyears is first screened on the assumptions of multicollinearity and normal distribution. As available in
appendix 3, the correlations between the various variables show no value higher than 0.9 which
indicates no multicollinearity. The distribution of the dataset appears not to be entirely normal
distributed. The sample is skewed, which could influence the results that are found in the multiple
regression.
72
Before the assumptions have been commented, next the strength of the model and the regression
coefficients will be commented. The Model Summary indicates by the Adjusted R Square that a low
percentage (5.1%) of the variance of the total amount of earnings management is explained by the
independent variables country, accounting standard and size.
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.237a
1
Adjusted R
.056
.051
.11047
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Total Earnings Management
The next aspect of the multiple regressions that will be commented is the outcome of the varianceanalysis in the ANOVA table. With this analysis, the significance of the total model is tested. The Ftest shows that the total model is significant (0.000).
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.381
3
.127
Residual
6.419
526
.012
Total
6.799
529
F
10.398
Sig.
.000a
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Total Earnings Management
Before has been determined the total model is significant, next the question is whether in addition
all the coefficients of the independent variables are significant. In the table Coefficients, the sign, the
size and the significance of the independent variables are presented; these results are in relation to
the dependent variable total earnings management. When investigating the significance of the
independent variables, with a significance level of 0.05, the independent variables country and size
are significant and the variable accounting standard is not significant. This indicates that a significant
difference exists between The Netherlands on one hand and Belgium and France on the other hand.
The sign of the coefficient is negative (-0.110) which indicates that in Belgium and in France less
earnings management is used compared to The Netherlands. With this statement is assumed that
earnings are managed upwards. It is in addition possible that in Belgium and in France, more earnings
are managed downwards, compared to The Netherlands. As commented in section 3.2.4, earnings
can be managed in various directions. This assumption is used for the variable size. According to the
73
coefficient of the variable size, it appears that larger companies use significant less earnings
management compared to smaller companies.
The last independent variable that is commented is the variable accounting standard which is the
indicator whether hypothesis 1 is approved or rejected. When checking the independent variable
accounting standard, can be concluded that no significant (sig. 0.470) difference exists between the
total use of earnings management based on local GAAP and on IFRS. Consequently hypothesis 1 is
approved; the introduction of IFRS in 2005 did not create a significant change in the total use of
earnings management in The Netherlands, in Belgium and in France.
Coefficientsa
Model
1
Unstandardized
Standardized
Coefficients
Coefficients
B
(Constant)
Country
Accounting Standard
Size
Std. Error
Beta
Collinearity
Correlations
t
Sig.
18.285
.000
Zero-order
.169
.009
-.025
.010
-.110
-2.594
.010
-.131
.007
.010
.031
.722
.470
.032
-.044
.010
-.196
-4.598
.000
-.207
Partial
Statistics
Part
Tolerance
-.112 -.110
.990
1.011
.031
1.000
1.000
-.197 -.195
.990
1.010
.031
a. Dependent Variable: Total Earnings Management
Before the two general methods for managing earnings are commented separately, the results of the
multiple regression of the total amount of earnings management and the conclusion concerning
hypothesis 1 are summarized.
Based on the investigation of the dataset of this multiple regression, it appears that the distribution
of the dataset is slightly skewed but no multicollinearity exists. The Model Summary indicates that
5.6% of the variance of the total amount of earnings management is explained by the independent
variables country, accounting standard and size, which is a low percentage. Despite this low
explanatory power, the ANOVA table shows that the total model is significant. Next, the table
Coefficients is commented with the sign, with the size and with the significance of the independent
variables. The table shows that the independent variables country and size are significant in contrast
to the variable accounting standard.
7.3.2 Accruals-based earnings management
Before the influence of the variables country, accounting standard and size on the total amount of
earnings management is commented; next the influence of these variables on the two general
methods for executing earnings management will be commented. In this section the accruals-based
74
VIF
method will be commented and in the next section the real method. The amount of discretionary
accruals is used as dependent variable and the same independent variables as in the previous
multiple regressions will be used. After investigating for data that exceeds three times the standard
deviation, 6 company-years from the dataset were excluded which resulted in a dataset of 534
company-years to perform the regression with.
Like the previous regression first the assumptions on the mulitcollinearity and on the normal
distribution will be commented before the results of the multiple regression. The table Correlations
shows that no value is higher than 0.9; consequently no multicollinearity exists. Other elements of
interest for the assumptions are available in appendix 3. Like the previous regression, the dataset is
not entirely normal; the dataset is a bit skewed which could have its influence on the results that are
found.
Before the assumptions are commented; next the results of the multiple regression will be reviewed.
According to the Adjusted R square in the Model Summary, a low explanatory power (2.3%) exists of
the variance of the discretionary accruals by the independent variables country, accounting standard
and size.
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.168a
1
Adjusted R
.028
.023
.10356
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Discretionary Accruals
Despite that the Model Summary shows low explanatory power of the independent variables on the
dependent variable, the F-test in the ANOVA table shows that the total model is significant (0.002).
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.165
3
.055
Residual
5.684
530
.011
Total
5.848
533
F
5.118
Sig.
.002a
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Discretionary Accruals
The table Coefficients shows the sign, the size and the significance of the independent variables in
relation to the dependent variable discretionary accruals. First the significance of the independent
75
variables; the variables country and the size are significant (resp. 0.01 and 0.009), the variable
accounting standard is not significant (0.624). With this results, can be concluded that a significant
difference exists between the two groups of countries, respectively group 1 The Netherlands and
group 2 Belgium and France, and large and small companies. The negative sign for both variables
indicate less use of accruals-based earnings management in Belgium and in France and larger
companies, compared to The Netherland and smaller companies. Like in the multiple regressions
with the total earnings management as dependent variable, it is assumed that earnings are managed
upwards.
The independent variable accounting standard appeared to be not significant (0.624). The transition
from local GAAP to IRS did not create a significant change in the use of accruals-based earnings
management. Although the change is not significant, the sign of the variable Accounting Standard is
positive (0.21), which could be indicative for an increase of the accruals-based earnings management
after the introduction of IFRS. But because the result is not significant, this is only indicative and
cannot be concluded.
Coefficientsa
Unstandardized
Standardized
Coefficients
Coefficients
Correlations
Collinearity Statistics
Std.
Model
B
1
.159
.009
-.023
.009
.004
-.024
(Constant)
Country
Accounting Standard
Size
Error
Beta
t
Sig.
Zero-order
Partial
Part
Tolerance
VIF
18.469
.000
-.111
-2.578
.010
-.123
-.111
-.110
.988
1.012
.009
.021
.491
.624
.023
.021
.021
1.000
1.000
.009
-.112
-2.606
.009
-.124
-.112
-.112
.988
1.012
a. Dependent Variable: Discretionary Accruals
Although the result of variable accounting standard is not significant, it is indicative for an increase of
accruals-based earnings management after the introduction of IFRS.
7.3.3 Real earnings management
The last multiple regression will be with the average value of the four real earnings management
indicative variables as dependent variable and the variables country, accounting standard and size as
independent variables. The average absolute value of the variables cash flow from operations, cost of
goods sold, change in inventory and production costs is used as dependent variable.
76
The sample is first investigated on outliers, which resulted in the elimination of 11 company-years
and decreases the number of company-years in the dataset to 529. The table Correlations shows low
correlations between the variables by which is concluded that no multicollinearity exists. When the
dataset is investigated on normal distribution, the distribution is not entirely normally but a bit
skewed, like previous tests. As in addition concluded with the previous regression, this skewness
could have its influence on the results of the regression. The table Correlations and the histogram on
normal distribution are available in appendix 3.
Before the dataset has been analyzed on whether it meets the assumptions, it is time to investigate
the strength and the significance of the model and the test. The Adjusted R Square in the Model
Summary shows a value of 0.000 indicating that no explanatory power of the variance of real
earnings management exists by the independent variables.
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.074a
1
Adjusted R
.005
.000
.05538
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Real Earnings Management
This inability in explaining the variance of real earnings management is strengthened by the notsignificance of the model. A possible explanation for the model not to be significant is that the
average value of the negative and the positive values has been used which could create zero-bias.
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.009
3
.003
Residual
1.610
525
.003
Total
1.619
528
F
Sig.
.961
.411a
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Real Earnings Management
The finding of the not-significance of the model is strengthened and in addition visible in the table
Coefficients; all independent variables are not significant. The variable country indicates that no
difference exists in the use of real earnings management between The Netherlands, Belgium and
France. When the variable accounting standard is investigated, it implies no difference between local
GAAP and IFRS and the variable size shows no difference between large and small companies.
77
Coefficientsa
Unstandardized
Standardized
Coefficients
Coefficients
Model
B
Std. Error
1
(Constant)
.062
.005
Country
.002
.005
Accounting Standard
.007
Size
.004
Collinearity
Correlations
Beta
t
Sig.
Zero-order
Partial
Statistics
Part
Tolerance
13.287
.000
.022
.504
.615
.026
.022
.022
.991
1.010
.005
.059
1.360
.175
.060
.059
.059
1.000
1.000
.005
.035
.811
.418
.038
.035
.035
.990
1.010
a. Dependent Variable: Real Earnings Management
When investigating the results for hypothesis 2 about the substitution between the accruals-based
and the real method for managing earnings, the results suggest that the use of real earnings
management increased (0.59) after the introduction of IFRS. In the previous section was indicated
that in addition accruals-based earnings management increased (0.021) after the introduction of
IFRS. The results of both the total amount as the accruals-based and the real method indicate that
the use of earnings management increased after the introduction of IFRS. But because the test with
real earnings management as dependent variable appeared to be not significant, the results of this
regression are not strong. Because of the results from both regressions, no significant results,
hypothesis 2 is rejected. The introduction of IFRS in 2005 did not create a substitution from accrualsbased to the use of real earnings management.
Because the test with real earnings management as dependent variable was not significant, the
variables for determining the amount of real earnings management are tested separately. By
investigating the variables separately, it is possible to check whether the introduction of IFRS has
created a significant difference in the use of one or more of the variables independently. The results
are shortly highlighted by showing the ANOVA and the Coefficients table; all other results of the
multiple regressions are available in appendix 3. By investigating the ANOVA table, the significance of
the test is commented and the Coefficients table shows whether the independent variables country,
accounting standard and size have significant influence on the dependent variables.
Cash Flow from Operations
ANOVAb
Model
1
Sum of Squares
Regression
VIF
df
Mean Square
.026
3
.009
Residual
1.077
559
.002
Total
1.103
562
78
F
4.423
Sig.
.004a
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Cash Flow from Operations
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.059
.004
Country
-.004
.004
Accounting Standard
-.002
Size
-.012
Coefficients
Beta
t
Sig.
16.309
.000
-.041
-.980
.328
.004
-.027
-.642
.521
.004
-.140
-3.326
.001
a. Dependent Variable: Cash Flow from Operations
In order to determine the significance of both the model and the coefficients of the independent
variables, the tables ANOVA and Coefficients in this section will be commented. The ANOVA table
shows that the test with the Cash Flow from Operations as dependent variable is significant (0.004).
The Coefficients table shows that only the independent variable size has a significant influence
(0.001) on the Cash Flow of Operations. The results of the two other variables, country and
accounting standard, show no significant differences. Investigating these results for hypothesis 2, no
significant difference exists in the amount of Cash Flow of Operations comparing to local GAAP and
IFRS.
Costs of Goods Sold
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.037
3
.012
Residual
6.566
554
.012
Total
6.603
557
F
Sig.
.372a
1.046
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Costs of Goods Sold
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.129
.009
Country
.015
.009
79
Coefficients
Beta
t
.067
Sig.
14.341
.000
1.571
.117
Accounting Standard
.002
.009
.007
.171
.864
Size
.006
.009
.027
.637
.525
a. Dependent Variable: Costs of Goods Sold
Contrary to the model of the regression with the Cash Flow from Operations as dependent variable,
is the model with Costs of Goods Sold (COGS) as dependent variable not significant (0.372) according
to the ANOVA table. Next to the not significance of the model in addition are all the coefficients of
the independent variables not significant. Because the model is not significant, the results are not
reliable. The only indication this test presents in relation to hypothesis 2 is that no significant
difference exists in the use of COGS as manipulative variable based on local GAAP and based on IFRS.
Change in Inventory
ANOVAb
Model
1
Sum of Squares
df
Mean Square
Regression
.080
3
.027
Residual
.639
559
.001
Total
.719
562
F
Sig.
.000a
23.312
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Change in Inventory
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Country
Accounting Standard
Size
Std. Error
.042
.003
-.018
.003
.005
-.013
Coefficients
Beta
t
Sig.
15.142
.000
-.253
-6.304
.000
.003
.064
1.615
.107
.003
-.181
-4.498
.000
a. Dependent Variable: Change in Inventory
The model with the Change in Inventory as dependent variable in the multiple regression shows that
both the model and two of the three independent variables are significant. The variables country and
size have a significant negative coefficient, indicating that less earnings management is used in
Belgium and in France compared to The Netherlands and larger companies compared to smaller
companies. But for hypothesis 2, the independent variable accounting standard is determinative and
this variable shows no significant difference in Change in Inventory based on local GAAP and on IFRS.
80
Production Costs
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.077
3
.026
Residual
7.441
555
.013
Total
7.517
558
F
Sig.
.126a
1.914
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Production Costs
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.130
.010
Country
.000
.010
Accounting Standard
.023
Size
.004
Coefficients
Beta
t
Sig.
13.595
.000
-.002
-.036
.972
.010
.100
2.357
.019
.010
.018
.419
.675
a. Dependent Variable: Production Costs
Like the model of with Costs of Goods Sold as dependent variable, this model with Production Costs
as dependent variable is not significant. Because of this non-significance of the model, the results are
not strong and consequently will the results be commented but no conclusion will be drawn based
on this model. The Coefficients table shows one significant and two variables that are not significant.
Notable is that the variable accounting standard is significant which has not happened in all other
regression models. But because the model is not significant, this result will not be used for
hypothesis 2 about the substitution from accruals-based to real earnings management.
The conclusion of the four variables for determining real earnings management as dependent
variables in a multiple regression is that the models with dependent variables Cash Flow from
Operations and Change in Inventory are significant, in contrast to the models with the dependent
variables Costs of Goods Sold and Production Costs. When the significant models are checked on the
significance of the independent variable Accounting Standard, it appears that this variable is not
significant in both tests. Because of this, the result is that the transition from local GAAP to IFRS did
not create a significant difference in the use of real earnings management. Although no significance
in the outcome of the independent variable accounting standard exists, the results of the use of the
81
four variables separately could be used for further research in the use of real earnings management
and the use of variables to test real earnings management.
7.4 Summary
In this chapter, the research has been performed and the results are commented. With this
information, sub-question 10 about the research of this thesis is commented and answered. The
abnormal level of earnings management-indicating variables are used for the detection of the use of
earnings management. For the accruals-based method, the discretionary part of the accruals is
determined but before this is possible, regression coefficients needed to be determined. In order to
detect the indication for the use of earnings management; the discretionary part of the accruals with
the use of historical data, the non-discretionary part of the accruals is determined which is
subtracted from the total amount of accruals. This in addition has to be performed for the method of
the use of real earnings management. The ‘normal’ levels of the variables cash flow of operations,
costs of goods sold, change in inventory and production are determined by using historical data in a
regression to determine the regression coefficients. With these coefficients and the data from the
period 2002-2007, the ‘normal’ level of the variables in that period is determined. The difference
between the ‘normal’ and the actual level is indicative for the use of real earnings management.
The amount of the discretionary accruals, the difference between the ‘normal’ and the actual level of
the real earnings management indicating variables and the sum of both methods indicating the total
amount of the use of earnings management in multiple regressions are used as dependent variables.
In these multiple regressions, the influence of the independent variables country, accounting
standard and size is tested. After the elimination of the outliers, the dataset for the total amount of
earnings management contains 530 company-years, for the accruals-based method 534 companyyears and for the real method 529 company-years.
With the multiple regressions, the influence of the independent variables on the dependent variable
is analysed. The independent variable country checks the difference in earnings management in The
Netherlands compared with Belgium and France. Belgium and France are combined for two reasons.
The first reason is that only five companies from Belgium meet the requirements, which makes the
results from Belgium solely not strong. The second reason for the combination Belgium with France
is the differences between The Netherlands and Belgium and France when investigating specific
factors according to La Porta et al. (1998). The second independent variable is accounting standards
which investigate the possible influence of the introduction of IFRS in 2005, by comparing the use of
earnings management based on local GAAP and based on IFRS. The last independent variable is the
82
variable size. With this variable, the use of earnings management by small and large companies is
compared.
Before the variables of the multiple regressions have been commented, next the multiple regressions
will be analysed. First the total amount of earnings management is used as dependent variable. The
regression analysis shows that two of the three independent variables are significant. The signs of
the variables country and size are significant negative. The total amount of earnings management is
less in Belgium and France compared to The Netherland and large companies use less earnings
management than small companies. With this statement is assumed that earnings are managed
upwards. The variable accounting standard is not significant which indicates that no significant
difference exists in the total amount of earnings management based on local GAAP and based on
IFRS. A consequence of this result concerning the accounting standards is that hypothesis 1 is
confirmed; The total degree of the use of earnings management did not change by the transition
from local GAAP to IFRS in 2005 in the Netherlands, in Belgium and in France.
The other two multiple regressions that have been performed, investigated the influence of the
variables country, accounting standards and size on respectively the use of the accruals-based and
real method for managing earnings. First the accruals-based method is used as dependent variable in
the multiple regression. The Coefficients table of the multiple regression shows again that the
variables country and size are significant, bot with a negative sign. In Belgium and France is less
accruals-based earnings management used compared to The Netherlands and larger companies use
less accruals-based earnings management compared to small companies with the assumptions that
earnings are managed upwards. The coefficient of the variable accounting standard is not significant
which implies that no significant difference in the use of accruals-based earnings management exists
based on local GAAP and based on IFRS.
The multiple regression analysis for the real method of earnings management shows no significant
results. Both the ANOVA table about the significance of the test as the significance of the
independent variables show no significance. Consequently the findings is that the test shows no
significant difference between the local GAAP and IFRS. But because of this result, the four variables
that are used for the determination of real earnings management are tested separately. This could
present some insight in which variables might have caused the non-significance of the test. The tests
with the four variables separately show that the variables Cash Flow from Operations and Change in
Inventory have significant tests in contrast to the variables Costs of Goods Sold and Production Costs.
83
The sign and significance of the independent variable accounting standard is determinative for
whether hypothesis 2 about the possible substitution effect of the accruals-based and real method is
rejected or approved.
According to the hypothesis, the sign of the coefficient accounting standard should be negative for
accruals-based and positive for real earnings management. When investigating these coefficients, a
positive coefficient appears for both accruals-based (0.021) and real (0.059) earnings management.
But the regression with real earnings management as dependent variable is not significant, which
indicates no significant difference between the use of real earnings management under local GAAP
and IFRS.
Consequently hypothesis 2
After the introduction of IFRS in 2005 in The Netherlands, Belgium and France by managers a
substitution effect exists from using accruals-based to the use of real earnings management
will be rejected
84
8 Summary, Conclusions and Analysis
8.1 Summary
In 2005, the International Financial Reporting Standards (IFRS) were introduced to give more a true
and fair view of the financial situation of a company and increase the transparency and comparability
of financial statements with fair-value accounting as the most important principle (Heemskerk and
van der Tas 2006, p 574). The principle of fair value accounting should be accomplished with the use
of both rigid rules and subjective measurements. According to Heemskerk and van der Tas (2006),
the strictness of the rules should decrease the use of earnings management, but the subjective
measures give more opportunities for using earnings management (Heemskerk and van der Tas
2006, p 573).
Earnings management is about influencing financial numbers to create an adjusted view of the
financial situation. Ronen and Yaari (2008) distinguish earnings management in three categories of
earnings management; white, grey and black, with the motive for using earnings management as the
method for distinguishing between the categories. In this research, all categories of earnings
management are tested; there is no selection on the category of earnings management. The
different categories only demonstrate the different motives behind the use of earnings management.
In order to investigate the influence of the introduction of IFRS in 2005 on the use of earnings
management, the Positive Accounting Theory (PAT) is used in combination with the models for
detecting earnings management. For the detecting of accruals-based earnings management the
Modified Jones Model (1995) and for real earnings management the model developed by
Roychowdhury (2006) is used. These models have been chosen after checking various related, earlier
conducted researches (Heemskerk and van der Tas 2006; Cohen, Dey and Lys 2008; Lippens 2010;
Zang 2012).
With these earlier conducted researches as a fundament, the hypotheses were stated. The
conclusion of earlier conducted related researches (Heemskerk and van der Tas 2006; Lippens 2010)
in combination with the influence of the French Civil Law factors was decisive for the direction the
hypotheses were stated in. Consequently, the hypotheses state that the introduction of IFRS did not
lead to a change in the total amount of earnings management and that IFRS caused a substitution
from accruals-based to real earnings management.
85
8.2 Conclusions and Analysis
After the discussion of the fundament of the research, next the following main question will be
answered with the results of this research:
Does a relation exist between the introduction of IFRS in 2005 and the choice of method of the use
of earnings management, accruals-based or real activities manipulation, in the French Civil law
countries The Netherlands, Belgium and France?
In order to answer this question, the hypotheses are tested with three multiple regression analyses.
With the multiple regressions, the influence of the independent variables accounting standard,
country and size on the dependent variables total amount of earnings management and the methods
accruals-based and real earnings management are examined.
Before the main question about the substitution effect of the two general methods for executing
earnings management was tested, the total amount of earnings management was used as
dependent variable in the multiple regression. In hypothesis 1 was stated that the introduction of
IFRS in 2005 did not create a change in the total amount of the use of earnings management. The
multiple regressions indicate that indeed no significant difference exists between the total amount of
the use of earnings management before and after the introduction of IFRS in 2005. This conclusion
reveals that hypothesis 1 is approved; the results show no significant change in the total amount of
earnings management based on local GAAP and IFRS. This can possibly be explained by the influence
of the local GAAP on the transition. The local GAAP of The Netherlands especially was already in line
with the guidelines of the IFRS, which possible creates a smooth transition and no difference in the
use of earnings management. When investigating the other independent variables in the regression,
country and size, both variables appear to be significant. It appears that in The Netherlands the total
amount of managed earnings is significant higher compared to Belgium and France, assumed that
earnings are managed upwards. The variable size shows that large companies appear to use
significant less earnings management compared to small companies.
The difference in the total use of earnings management in The Netherlands and Belgium and France
might be explained by the difference in French Civil Law factors. A difference exists in legal
enforcement strength; Burgstahler et al. (2006) conclude that The Netherlands and Belgium have a
high score on this factor in contrast to France. Because the group of Belgium and France companies
contained 5 Belgium and 40 French companies, it might be that the difference between The
Netherlands and France in legal enforcement strength has created a significant difference in the total
use of earnings management. But this result in the total use of earnings management is in contrast
86
with what was expected. More legal enforcement strength was assumed to decrease the use of
earnings management but the results do not support this. Further research on the connection of
legal enforcement strength and the amount of earnings management could indicate whether this
result stands alone or that the connection is proven to be valid. Another notable result is about the
size of the companies. Expected was that no significant difference exists in the use of earnings
management between large and small firms because of all variables were scaled by the total amount
of assets and by results of earlier conducted research of Heemskerk and van der Tas (2006).
The second hypothesis is about the possible substitution between the accruals-based and real
method for executing earnings management. According to earlier researches (Cohen, Dey, Lys 2008;
Lippens 2010) on the possible substitution of accruals-based and real earnings management, there is
concluded that a substitution effect exists from accruals-based to real earnings management. This
statement is adopted in this research by using this statement as hypothesis 2. The analysis of the
multiple regressions with accruals-based earnings management as dependent variable shows that
the introduction of IFRS did not create an significant increase in the use of this method for executing
earnings management. The regression with the real method as dependent variable appears to be not
significant for both the test as all the independent variables. Because of this non-significance, the
variables that are used for the determination of real earnings management are tested separately as
dependent variables in a multiple regression. This shows two significant (CFO and ΔINV) and two not
significant tests (COGS and PROD) and all tests show no significant difference between local GAAP
and IFRS.
According to hypothesis 2, after the introduction of IFRS in 2005 in The Netherlands, Belgium and
France by managers a substitution effect exists from using accruals-based to the use of real earnings
management. The multiple regression with the accruals-based method as dependent variable shows
no significant difference based on local GAAP and on IFRS. This in addition is applicable for the
regression with real earnings management as dependent variable; the model and the significant
were not significant. Based on these results hypothesis 2 is rejected; no significant substitution effect
of accruals-based to real earnings management after the introduction of IFRS in 2005 in The
Netherlands, Belgium and France has been detected. When investigating the significance of the two
other variables, country and size, only the significant tests of the variables separately are used. These
two tests with CFO and ΔINV as dependent variables show a significant difference for the
independent variable size in both tests and a significant difference for the independent variable
country in the test with ΔINV as dependent variable.
87
With the use of the outcome of the hypotheses, the main question about the relation between the
introduction of IFRS and choice of method for executing earnings management is answered. No
significant relation exists between the introduction of IFRS in 2005 and the choice of method of the
use of earnings management, accruals-based or real activites manipulation, in the French Civil law
countries The Netherlands, Belgium and France.
8.3 Limitations
The research that has been performed has its limitations which can have its influence on the
outcome of the research. These factors will be signalled in this section.
The first limitation is about the companies that have been used to create a research sample. All the
companies from the sample are listed and established in The Netherlands, Belgium or France.
Because 3 French Civil law countries in the sample are used, will the result of the research not be
generalizable for other countries, especially when the countries are not French Civil law. French Civil
law countries have specific characteristics, like the lowest level of investor protection (La Porta et al.
2000, p 8).
The second limitation is about the data of the companies that have been used. The data is from the
period 1997-2007; the data of 1997-2001 to determine the regression coefficients and 2002-2007 as
the research period. The most recent year is 2007, which is not recent. There could have been
already a different situation in the use of earnings management by companies. The crisis of the
recent years could have its influence on the results. This is the reason for not implementing years
after 2007 but it in addition creates that the results are less useful because of the different
circumstances of the research period and the current period.
Another limitation of the data is the limitation of the use of the year 2004 for the determination of
the values of 2005. Certain variables for determining the values for year 2005 had to use data from
2004. The use of different accounting standards in these years, local GAAP in 2004 and IFRS in 2005,
could have influence on the determination of the values of 2005 and in addition on the results of the
research.
Another limitation that is related to the data is about the distribution of the dataset that is used for
the executing of the multiple regressions. Results from SPSS show that all the datasets are not
entirely normal distributed but a bit skewed. This skewness of the dataset could influence the
outcome of the multiple regressions.
88
The significance of certain variables and low explanatory power of some tests are limitations of this
research. All variables in determining the amount of accruals-based earnings management were
significant, but this was not the case for real earnings management. For all indicative variables, CFO,
COGS, INV and PROD, was the variable 1 / A (t-1) not significant. Next to this variable were the
variable S / A (t-1) in the model of CFO and ΔS (t-1) / A (t-1) in the model of INV not significant. These
variables make the models less useful for determining the use of earnings management.
When investigating the tests that have been performed, some of them have very low explaining
power. A low R Square percentage implies that a small part of the dependent variable is explained by
the independent variables that are used. For better results in explaining the dependent variable,
other independent variables have to be used. This is an aspect for further research that is described
in the next section.
8.4 Further research
In order to realise a better understanding on the influence of the introduction of IFRS on the use of
earnings management, more research needs to be performed. With the use of the limitations of this
research, some aspects that need to be investigated are commented.
The use of a bigger amount and more current data should improve the understanding of the
influence of IFRS on the use of earnings management. Past years, the situation of the macro
economy has changed by a financial crisis which could have its influence on the use of earnings
management. Earnings might have been increased to publish a positive representation of a company
during a financial difficult period or companies might have taking a bath to start fresh in a financial
better period.
Another aspect for further research is the study of more countries. IFRS is obliged for all listed
companies in the European Union, which implies that some countries that have implemented IFRS
are not investigated. Possibly will the introduction of IFRS in these countries present another view on
the use of earnings management. A variety of countries have implemented IFRS and specific factors
of these countries have their influence on the use of earnings management based on IFRS. Not all
French Civil law countries in Europe have been investigated; results from these countries could
strengthen or weaken the results in this research.
The final aspect of this research that is highlighted is the correctness of the model for detecting the
use of real earnings management. As signalled during the discussion of the models developed by
Roychowdhury (2006) and Gunny (2010); no model for detecting real earnings management has
89
been proven to be valid. The proxies that are used in the models are valid, but the model has not.
Further research should prove whether the models that are developed are valid.
90
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93
Appendix 1 Literature review
AUTHOR
OBJECT RESEARCH
SAMPLE
METHODOLOGY
CONCLUSION
Ball R. (2006)
Discussion on the
advantages and
disadvantages of
the implementation
of IFRS for investors
n/a
Literature review
Due to large implementation of
the standards, convergence in
standards has been achieved. But
the question is whether there will
be local differences among the
countries that have implemented
IFRS. Next to this, the value of
‘fair value accounting’ is
questioned.
Bolt-lee C. and
Smith L.M.
(2009)
Highlight of IFRS
research,
conversion US
GAAP to IFRS
investigated
n/a
Literature review
Questionable whether the
benefits of the new standards will
exceed the costs of transition
Burgstahler D.
and Dichev I.
(1997)
Checking whether
firms manage
earnings to avoid
earnings decreases
and losses
Total number of
observations is
64.644 with a
total of
observations per
year varying
from
approximately
3000 to 4000
Cross-sectional distributions
of earnings
Earnings are managed to avoid
earnings decreases or losses. This
is done mostly with cash flow
from operations and changes in
working capital
Burgstahler D.
and Eames M.
(2006)
Do managers
manage earnings in
order to avoid
reporting earnings
lower than analyst
forecasts?
25.951
observations in
the period 1986 2000
Jones model (1991) and the
Matsumoto model (2002)
Earnings are managed both
upwards and downwards to
achieve zero and small positive
earnings surprises. Both operating
cash flow and discretionary
accruals are managed
Cai,L.
Courtenay, S.
and
Rahman, A.
(2008)
Whether adoption
and enforcement of
IFRS leads to a
reduction of
earnings
management
102.636 firmyear
observations in
32 countries
during 20062006
Accruals approach:
Comparing mean difference
in earnings management
and Ordinary Least Square
Regressions
Earnings management did decline
at countries that have adopted
IFRS, with an important role for
the level of enforcement.
Cohen, Dey, Lys
(2008)
The influence of the
Sarbanes-Oxley Act
(SOX) on the use of
earnings
management, both
real and accrualbased
A sample
consisting 2,018
firms and 31,668
firm-year
observations in
the period of
1992-2005
Accruals-based: modified
cross-sectional Jones model
(1991)
Earnings management increased
over the sample period, with
meeting or beating prior year’s
earnings numbers, analysts’
forecasts and avoiding losses as
incentives. There is an increase in
earnings management in the
period preceding the passage of
SOX. Next to this, the level of
accrual-based earnings
management declined and the
Real earnings management:
use of model developed by
Dechow et al. (1998) for
normal level of CFO, COGS,
inventory growth,
production cost and
94
discretionary accruals
level of real earnings
management activities increased
significantly suggesting a
substitution-effect
Gunny (2010)
The examination of
the extent to which
real earnings
management
affects operating
performance by
meeting earnings
benchmarks
Differs per type
of real earnings
management;
minimum of
28,308
observations and
4,028 firms
Real earnings management
by R&D, SG&A, assets sales
and production costs are
detected by own developed
models
Real earnings management is
positively associated with firms
meeting benchmarks. Managers
try to attain benefits that allow
better future performance or
signalling.
Healy P.M. and
Wahlen J.M.
(1999)
Review of the
academic evidence
on earnings
management and
its implications for
accounting
standards setters
and regulators
n/a
Literature review
Earnings management literature
currently provides only modest
insights for standard setters.
Reasons for managing earnings
are influencing stock market
perceptions, increase
management compensation,
reduce the likelihood of violating
lending agreements and to avoid
regulatory intervention
Heemskerk,
M.J.L. and Tas,
L.G. (2006)
Determine whether
earnings
management has
declined by
focussing on early
adopters of IFRS
160 German and
Swiss early IFRSadopting
companies
Modified Jones Model
Earnings Management by
discretionary accruals did not
decline. Contrary to this, the use
of it might even have increased
Jeanjean, T. and
Stolowy, H.
(2008)
The effect of the
mandatory
introduction of IFRS
on earnings quality
1146 France,
U.K. and
Australian
companies (early
adopters) in the
period 20022006
Wilcoxon rank-sum test
The pervasiveness of earnings
management did not decline after
the implementation of IFRS, it
even increased in France
Lippens, M.
(2010)
Whether the
mandatory
adoption of IFRS by
all listed companies
in the EU has led to
significant lower
levels of earnings
management
Listed companies
from Belgium,
The Netherlands,
Denmark, Italy,
Sweden
Cross-sectional Jones Model
and model of
Roychowdhury
Both accruals-based and real
earnings management increased
after implementation of IRFS. The
methods are used as substitutes
McNichols M.F.
(2000)
Discussion of tradeoffs associated with
three research
designs commonly
used in the
earnings
management
n/a
Aggregate accruals, specific
accruals and distribution of
earnings
The trade-off in approaches
depends on the central question,
objective method and incentives
of a research
95
literature:
aggregate accruals,
specific accruals
and the distribution
of earnings
Soderstrom N.
and Sun K.J.
(2007)
Review the change
in accounting
quality and the
determinants
causing this
following
widespread IFRS
adoption in the EU
n/a
Literature review
Accounting quality depends on:
(1) quality of standards, (2)
country’s legal and political
system and (3) financial reporting
incentives
Ronen and Yaari
(2008)
Give insight in the
theory, practice
and research that is
done about
earnings
management
n/a
Literature review including
explanations of different
methodologies
n/a
Roychowdhury
(2008)
Whether managers
manipulate real
activities to avoid
reporting annual
losses
In the period of
1987 and 2001
are 21,758 firmyears, 36
industries and
4252 individual
firms tested
Own models estimate
normal levels of sales,
discretionary expenditures
and COGS to compare this
with the real numbers
Real activities manipulation is
used to avoid losses and/or
negative annual forecast errors
Tendeloo, B.
and Vanstraelen,
A. (2005)
Whether voluntary
adoption of IFRS is
associated with
lower earnings
management
636 German
listed companies
Aggregate Accruals: Crosssectional Jones Mode
(regression)
There is no difference in earnings
management found comparing
companies using IFRS and
companies using German GAAP.
Xu, Taylor and
Dugan (2007)
Review of real
earnings
management
literature
n/a
Literature review on
evidence, models,
consequences and
investors’ reactions on real
earnings management
n/a
96
Appendix 2 Companies used for this research
The Netherlands
AKZO NOBEL N.V.
GOUDA VUURVAST HLD
KONINKLIJKE KPN NV
SIMAC TECHNIEK NV
AMSTERDAM COMM
GRONTMIJ
KONINKLIJKE TEN CATE
SLIGRO FOOD GROUP NV
ARCADIS NV
HEINEKEN HOLDING
MEDIQ NV
SMIT INTERNATIONALE
BALLAST NEDAM NV
HEINEKEN N.V.
N.V. PORCELEYNE FLES
STERN GROEP NV
BATENBURG TECHN
HUNTER DOUGLAS N.V.
NEDFIELD
TELEGRAAF MEDIA
BE SEMICONDUCTOR IND
IMTECH NV
NEWAYS ELECTRONICS
TKH GROUP N.V.
BETER BED HOLDING
KENDRION NV
NUTRECO N.V.
UNILEVER N.V.
BRUNEL INTERNATIONAL
KON. BOSKALIS WESTM.
ORANJEWOUD NV
USG PEOPLE N.V.
CROWN VAN GELDER
KON. ECONOSTO N.V.
ORDINA NV
WEGENER N.V.
CSM NV
KONINK. WESSANEN
POSTNL
WITTE MOLEN NV
DOCDATA NV
KONINKLIJKE AHOLD NV
RANDSTAD HOLDING
WOLTERS KLUWER N.V.
ERIKS N.V.
KONINKLIJKE BAM GRP
ROOD MICROTEC
GAMMA HOLDING NV
KONINKLIJKE DSM N.V.
ROTO SMEETS GROUP NV
ALCATEL-LUCENT SA
DYNACTION SA
GROUPE EUROTUNNEL
NRJ GROUPE
BOIRON SA
ERAMET SA
GROUPE FLO SA
PRODUITS CHEMIQ
BOLLORE
ETAM DEVELOPPEMENT
GROUPE GUILLIN SA
REXEL S.A.
BOUYGUES SA
ETS. MAUREL ET PROM
HAVAS SA
RHODIA
BRICORAMA SA
FAURECIA SA
HERMES INTERNATIONAL
RUBIS SA
CARREFOUR S.A.
FRANCE TELECOM SA
HYPARLO
SAGA SA
COLAS SA
GASCOGNE
JACQUET METAL
STE FERM CAS MUN CAN
COMPAGNIE GENERALE
GAUMONT SA
L'OREAL SA
SYNERGIE SA
CS COMMUN & SYSTEMES
GDF SUEZ
M6 - METROPOLE TV
TELEVISION FRANCA 1
DISTRIBORG GROUPE
GROUPE DANONE SA
MEDASYS SA
TIPIAK SA
Belgium
D'IETEREN S.A.
ETABLISSEMENT DELHAI
SIPEF SA
SOLVAY SA
SPADEL SA
France
97
Appendix 3 Results from SPSS
Total Accruals
Variables Entered/Removedb
Variables
Model
1
Variables Entered
Removed
PPE / A (t-1),
Method
. Enter
1 / A (t-1),
Change S / A (t-1)
a. All requested variables entered.
b. Dependent Variable: TA / A / (t-1)
Model Summary
Model
R
R Square
.544a
1
Adjusted R
Std. Error of the
Square
Estimate
.296
.291
.16852
a. Predictors: (Constant), PPE / A (t-1), 1 / A (t-1), Change S / A (t-1)
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
F
5.616
3
1.872
Residual
13.376
471
.028
Total
18.991
474
Sig.
.000a
65.916
a. Predictors: (Constant), PPE / A (t-1), 1 / A (t-1), Change S / A (t-1)
b. Dependent Variable: TA / A (t-1)
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
-.572
.015
1 / A (t-1)
3.420
.298
Change S / A (t-1)
.044
PPE / A (t-1)
.248
a. Dependent Variable: TA / A (t-1)
98
Coefficients
Beta
t
Sig.
-38.843
.000
.444
11.475
.000
.011
.155
3.988
.000
.037
.258
6.661
.000
Cash Flow of Operations
Variables Entered/Removedb
Variables
Model
1
Variables Entered
Removed
Change S / A (t-1),
Method
. Enter
1 / A (t-1),
S / A (t-1)
a. All requested variables entered.
b. Dependent Variable: CFO / A (t-1)
Model Summary
Model
R
R Square
.295a
1
Adjusted R
Std. Error of the
Square
Estimate
.087
.081
.11898
a. Predictors: (Constant), Change S / A (t-1), 1 / A (t-1), S / A (t-1)
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
F
.634
3
.211
Residual
6.667
471
.014
Total
7.302
474
Sig.
.000a
14.941
a. Predictors: (Constant), Change S / A (t-1), 1 / A (t-1), S / A (t-1)
b. Dependent Variable: CFO / A (t-1)
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.105
.011
1 / A (t-1)
.144
.211
S / A (t-1)
-.009
.061
Change S / A (t-1)
a. Dependent Variable: CFO / A (t-1)
99
Coefficients
Beta
t
Sig.
9.293
.000
.030
.680
.497
.007
-.085
-1.332
.184
.011
.347
5.476
.000
Costs of Goods Sold
Variables Entered/Removedb
Variables
Variables
Entered
Removed
Model
1
S / A (t-1),
Method
. Enter
1 / A (t-1)
a. All requested variables entered.
b. Dependent Variable: CGOS / A (t-1)
Model Summary
Model
R
.979a
1
Adjusted R
Std. Error of the
Square
Estimate
R Square
.957
.957
.22764
a. Predictors: (Constant), S / A (t-1), 1 / A (t-1)
ANOVAb
Model
1
Sum of Squares
Regression
Residual
Total
df
Mean Square
550.718
2
275.359
24.458
472
.052
575.177
474
F
Sig.
5313.918
.000a
a. Predictors: (Constant), S / A (t-1), 1 / A (t-1)
b. Dependent Variable: CGOS / A (t-1)
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
Coefficients
Beta
(Constant)
-.166
.019
1 / A (t-1)
-.206
.403
S / A (t-1)
.896
.009
a. Dependent Variable: CGOS / A (t-1)
100
t
Sig.
-8.848
.000
-.005
-.511
.610
.979
102.770
.000
Change in Inventory
Variables Entered/Removedb
Variables
Model
1
Variables Entered
Removed
Change S (t-1) / A (t-1),
Method
. Enter
1 / A (t-1),
Change S / A (t-1)
a. All requested variables entered.
b. Dependent Variable: Change INV / A (t-1)
Model Summary
Model
R
R Square
.534a
1
Adjusted R
Std. Error of the
Square
Estimate
.285
.281
.06461
a. Predictors: (Constant), Change S (t-1) / A (t-1), 1 / A (t-1), Change S
/ A (t-1)
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
F
.785
3
.262
Residual
1.966
471
.004
Total
2.752
474
Sig.
62.713
.000a
a. Predictors: (Constant), Change S (t-1) / A (t-1), 1 / A (t-1), Change S / A (t-1)
b. Dependent Variable: Change INV / A (t-1)
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.006
.003
1 / A (t-1)
-.057
.115
.058
-.008
Change S / A (t-1)
Change S (t-1) / A (t-1)
a. Dependent Variable: Change INV / A (t-1)
101
Coefficients
Beta
t
Sig.
1.774
.077
-.019
-.494
.622
.004
.538
13.701
.000
.007
-.043
-1.100
.272
Production Costs
Variables Entered/Removedb
Variables
Model
1
Variables Entered
Removed
Change S (t-1) / A (t-1),
Method
. Enter
1 / A (t-1),
Change S / A (t-1),
S / A (t-1)
a. All requested variables entered.
b. Dependent Variable: PROD / A (t-1)
Model Summary
Model
R
R Square
.978a
1
Adjusted R
Std. Error of the
Square
Estimate
.957
.956
.23687
a. Predictors: (Constant), Change S (t-1) / A (t-1), 1 / A (t-1), Change S
/ A (t-1), S / A (t-1)
ANOVAb
Model
1
Sum of Squares
Regression
Residual
Total
df
Mean Square
F
580.414
4
145.103
26.370
470
.056
606.784
474
Sig.
2586.240
.000a
a. Predictors: (Constant), Change S (t-1) / A (t-1), 1 / A (t-1), Change S / A (t-1), S / A (t-1)
b. Dependent Variable: PROD / A (t-1)
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
-.216
.023
1 / A (t-1)
-.434
.422
S / A (t-1)
.950
Change S / A (t-1)
Change S (t-1) / A (t-1)
Coefficients
Beta
t
Sig.
-9.545
.000
-.010
-1.028
.304
.013
1.011
70.853
.000
-.055
.022
-.035
-2.485
.013
-.093
.027
-.034
-3.452
.001
a. Dependent Variable: PROD / A (t-1)
102
Multiple Regressions
Total Earnings Management
Descriptive Statistics
Mean
Std. Deviation
N
Total Earnings Management
.1386
.11337
530
Country
.4491
.49787
530
Accounting Standard
.5000
.50047
530
Size
.5151
.50024
530
Correlations
Total Earnings
Accounting
Management
Pearson Correlation Total Earnings Management
Size
-.131
.032
-.207
-.131
1.000
-.008
.102
.032
-.008
1.000
-.004
-.207
.102
-.004
1.000
.
.001
.230
.000
Country
.001
.
.431
.010
Accounting Standard
.230
.431
.
.465
Size
.000
.010
.465
.
Total Earnings Management
530
530
530
530
Country
530
530
530
530
Accounting Standard
530
530
530
530
Size
530
530
530
530
Accounting Standard
Size
Total Earnings Management
N
Standard
1.000
Country
Sig. (1-tailed)
Country
Variables Entered/Removedb
Variables
Model
Variables Entered
1
Country,
Removed
Method
. Enter
Accounting
Standard, Size
a. All requested variables entered.
b. Dependent Variable: Total Earnings Management
103
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.237a
1
Adjusted R
.056
.051
.11047
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Total Earnings Management
ANOVAb
Model
Sum of Squares
1
Regression
df
Mean Square
F
.381
3
.127
Residual
6.419
526
.012
Total
6.799
529
Sig.
.000a
10.398
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Total Earnings Management
Coefficientsa
Model
1
Unstandardized
Standardized
Coefficients
Coefficients
B
(Constant)
Country
.169
.009
-.025
.010
.007
-.044
Accounting Standard
Size
Std. Error
Beta
Correlations
t
Sig.
Zero-order
Partial
Collinearity Statistics
Part
Tolerance
VIF
18.285
.000
-.110
-2.594
.010
-.131
-.112
-.110
.990
1.011
.010
.031
.722
.470
.032
.031
.031
1.000
1.000
.010
-.196
-4.598
.000
-.207
-.197
-.195
.990
1.010
a. Dependent Variable: Total Earnings Management
Collinearity Diagnosticsa
Variance Proportions
Accounting
Model
Dimension
Eigenvalue
Condition Index
1
1
2.813
1.000
.03
.04
.04
.04
2
.536
2.291
.00
.40
.53
.03
3
.460
2.472
.00
.38
.08
.63
4
.191
3.843
.97
.18
.35
.30
a. Dependent Variable: Total Earnings Management
104
(Constant)
Country
Standard
Size
Casewise Diagnosticsa
Total Earnings
Case Number
Std. Residual
Management
Predicted Value
Residual
95
3.390
.55
.1763
.37446
127
3.661
.57
.1693
.40440
128
4.407
.66
.1693
.48687
188
4.514
.63
.1319
.49861
234
4.062
.62
.1693
.44875
271
3.478
.56
.1763
.38420
a. Dependent Variable: Total Earnings Management
Residuals Statisticsa
Minimum
Predicted Value
Maximum
Mean
Std. Deviation
N
.0998
.1763
.1386
.02682
530
-.17027
.49861
.00000
.11015
530
Std. Predicted Value
-1.448
1.403
.000
1.000
530
Std. Residual
-1.541
4.514
.000
.997
530
Residual
a. Dependent Variable: Total Earnings Management
105
106
Accruals-based Earnings Management
Descriptive Statistics
Mean
Std. Deviation
N
Discretionary Accruals
.1392
.10475
534
Country
.4457
.49751
534
Accounting Standard
.5019
.50047
534
Size
.5112
.50034
534
Correlations
Discretionary
Accounting
Accruals
Pearson Correlation
Size
1.000
-.123
.023
-.124
Country
-.123
1.000
-.011
.108
.023
-.011
1.000
-.008
-.124
.108
-.008
1.000
.
.002
.297
.002
Country
.002
.
.401
.006
Accounting Standard
.297
.401
.
.431
Size
.002
.006
.431
.
Discretionary Accruals
534
534
534
534
Country
534
534
534
534
Accounting Standard
534
534
534
534
Size
534
534
534
534
Size
N
Standard
Discretionary Accruals
Accounting Standard
Sig. (1-tailed)
Country
Discretionary Accruals
Variables Entered/Removedb
Variables
Model
Variables Entered
1
Country,
Removed
Method
. Enter
Accounting
Standard, Size
a. All requested variables entered.
b. Dependent Variable: Discretionary Accruals
107
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.168a
1
Adjusted R
.028
.023
.10356
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Discretionary Accruals
ANOVAb
Model
Sum of Squares
1
Regression
df
Mean Square
F
.165
3
.055
Residual
5.684
530
.011
Total
5.848
533
Sig.
.002a
5.118
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Discretionary Accruals
Coefficientsa
Unstandardized Standardized
Coefficients
Collinearity
Coefficients
Correlations
Statistics
Std.
Model
1
B
(Constant)
Country
Accounting Standard
Size
Error
.159
.009
-.023
.009
.004
-.024
Beta
t
Sig.
Zero-order
Partial
Part
Tolerance
VIF
18.469
.000
-.111
-2.578
.010
-.123
-.111
-.110
.988
1.012
.009
.021
.491
.624
.023
.021
.021
1.000
1.000
.009
-.112
-2.606
.009
-.124
-.112
-.112
.988
1.012
a. Dependent Variable: Discretionary Accruals
Collinearity Diagnosticsa
Variance Proportions
Model
Dimension
Eigenvalue
Condition Index
(Constant)
1
1
2.809
1.000
.03
.04
.04
.04
2
.540
2.282
.00
.39
.52
.04
3
.461
2.470
.00
.39
.07
.63
4
.191
3.834
.97
.17
.36
.29
a. Dependent Variable: Discretionary Accruals
108
Country
Accounting Standard
Size
Casewise Diagnosticsa
Discretionary
Case Number
Std. Residual
Accruals
Predicted Value
Residual
91
3.013
.47
.1594
.31205
126
3.869
.56
.1594
.40066
188
4.071
.56
.1403
.42158
238
3.088
.48
.1594
.31975
279
3.104
.48
.1594
.32149
a. Dependent Variable: Discretionary Accruals
109
110
Real Earnings Management
Descriptive Statistics
Mean
Std. Deviation
N
Real Earnings Management
.0680
.05538
529
Country
.4537
.49832
529
Standard
.4953
.50045
529
Size
.5217
.50000
529
Correlations
Real Earnings
Management
Pearson Correlation
Sig. (1-tailed)
N
Real Earnings Management
Country
Standard
Size
1.000
.026
.060
.038
Country
.026
1.000
.009
.097
Standard
.060
.009
1.000
.010
Size
.038
.097
.010
1.000
.
.276
.085
.190
Country
.276
.
.422
.013
Standard
.085
.422
.
.410
Size
.190
.013
.410
.
Real Earnings Management
529
529
529
529
Country
529
529
529
529
Standard
529
529
529
529
Size
529
529
529
529
Real Earnings Management
Variables Entered/Removedb
Variables
Model
Variables Entered
1
Country,
Removed
Method
. Enter
Standard, Size
a. All requested variables entered.
b. Dependent Variable: Real Earnings Management
111
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.074a
1
Adjusted R
.005
.000
.05538
a. Predictors: (Constant), Country, Standard, Size
b. Dependent Variable: Real Earnings Management
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.009
3
.003
Residual
1.610
525
.003
Total
1.619
528
F
Sig.
.411a
.961
a. Predictors: (Constant), Country, Standard, Size
b. Dependent Variable: Real Earnings Management
Coefficientsa
Model
1
Unstandardized
Standardized
Coefficients
Coefficients
B
Std. Error
(Constant)
.062
.005
Country
.002
.005
Standard
.007
Size
.004
Correlations
Beta
t
Sig.
Zero-order
Collinearity Statistics
Partial
Part
Tolerance
VIF
13.287
.000
.022
.504
.615
.026
.022
.022
.991
1.010
.005
.059
1.360
.175
.060
.059
.059
1.000
1.000
.005
.035
.811
.418
.038
.035
.035
.990
1.010
a. Dependent Variable: Real Earnings Management
Collinearity Diagnosticsa
Variance Proportions
Model
Dimension
Eigenvalue
Condition Index
1
1
2.825
1.000
.03
.04
.04
.04
2
.525
2.319
.00
.42
.54
.03
3
.458
2.485
.00
.37
.10
.62
4
.192
3.832
.97
.18
.32
.31
a. Dependent Variable: Real Earnings Management
112
(Constant)
Country
Standard
Size
Casewise Diagnosticsa
Real Earnings
Case Number
Std. Residual
Management
Predicted Value
Residual
95
4.265
.30
.0681
.23620
109
4.776
.33
.0616
.26453
129
4.647
.32
.0616
.25734
196
3.097
.23
.0616
.17153
274
4.220
.31
.0720
.23373
277
4.497
.32
.0681
.24903
401
4.884
.34
.0706
.27046
402
3.893
.29
.0706
.21562
403
4.458
.32
.0706
.24691
443
3.212
.25
.0706
.17787
a. Dependent Variable: Real Earnings Management
Residuals Statisticsa
Minimum
Predicted Value
Maximum
Mean
Std. Deviation
N
.0616
.0745
.0680
.00409
529
-.07198
.27046
.00000
.05523
529
Std. Predicted Value
-1.565
1.593
.000
1.000
529
Std. Residual
-1.300
4.884
.000
.997
529
Residual
a. Dependent Variable: Real Earnings Management
113
114
Real Earnings Management Variables
Cash Flow from Operations
Variables Entered/Removedb
Variables
Variables
Entered
Removed
Model
1
Method
Country,
. Enter
Accounting
Standard, Size
a. All requested variables entered.
b. Dependent Variable: Cash Flow from Operations
Model Summaryb
Model
R
R Square
.152a
1
Adjusted R
Std. Error of the
Square
Estimate
.023
.018
.04390
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Cash Flow from Operations
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.026
3
.009
Residual
1.077
559
.002
Total
1.103
562
F
Sig.
4.423
.004a
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Cash Flow from Operations
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Std. Error
.059
.004
Country
-.004
.004
Accounting Standard
-.002
Size
-.012
115
Coefficients
Beta
t
Sig.
16.309
.000
-.041
-.980
.328
.004
-.027
-.642
.521
.004
-.140
-3.326
.001
a. Dependent Variable: Cash Flow from Operations
Casewise Diagnosticsa
Case Number
Std. Residual
CFO
Predicted Value
Residual
92
3.763
.22
.0565
.16518
94
3.288
.20
.0565
.14436
208
3.100
.19
.0589
.13606
230
3.796
.23
.0589
.16665
255
4.662
.26
.0589
.20467
266
3.313
.20
.0589
.14542
272
3.030
.18
.0465
.13302
281
4.555
.26
.0565
.19995
470
4.387
.24
.0429
.19256
471
4.078
.22
.0429
.17900
a. Dependent Variable: Cash Flow from Operations
Residuals Statisticsa
Minimum
Predicted Value
Maximum
Mean
Std. Deviation
N
.0405
.0589
.0495
.00675
563
-.05871
.20467
.00000
.04378
563
Std. Predicted Value
-1.340
1.390
.000
1.000
563
Std. Residual
-1.337
4.662
.000
.997
563
Residual
a. Dependent Variable: Cash Flow from Operations
116
117
Costs of Goods Sold
Variables Entered/Removedb
Variables
Variables
Entered
Removed
Model
1
Method
Country,
. Enter
Accounting
Standard, Size
a. All requested variables entered.
b. Dependent Variable: Costs of Goods Sold
Model Summaryb
Model
R
R Square
.075a
1
Adjusted R
Std. Error of the
Square
Estimate
.006
.000
.10887
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Costs of Goods Sold
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.037
3
.012
Residual
6.566
554
.012
Total
6.603
557
F
Sig.
.372a
1.046
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Costs of Goods Sold
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.129
.009
Country
.015
.009
Accounting Standard
.002
Size
.006
a. Dependent Variable: Costs of Goods Sold
118
Coefficients
Beta
t
Sig.
14.341
.000
.067
1.571
.117
.009
.007
.171
.864
.009
.027
.637
.525
Casewise Diagnosticsa
Case Number
Std. Residual
COGS
Predicted Value
Residual
147
5.844
.77
.1305
.63624
271
3.491
.51
.1349
.38008
430
5.794
.78
.1451
.63076
431
3.881
.57
.1451
.42257
432
4.750
.66
.1451
.51713
466
3.734
.56
.1510
.40651
a. Dependent Variable: Costs of Goods Sold
Residuals Statisticsa
Minimum
Predicted Value
Maximum
Mean
Std. Deviation
N
.1290
.1510
.1399
.00817
558
-.14643
.63624
.00000
.10857
558
Std. Predicted Value
-1.338
1.359
.000
1.000
558
Std. Residual
-1.345
5.844
.000
.997
558
Residual
a. Dependent Variable: Costs of Goods Sold
119
120
Change in Inventory
Variables Entered/Removedb
Variables
Variables
Entered
Removed
Model
1
Method
Country,
. Enter
Accounting
Standard, Size
a. All requested variables entered.
b. Dependent Variable: Change in Inventory
Model Summaryb
Model
R
R Square
.333a
1
Adjusted R
Std. Error of the
Square
Estimate
.111
.106
.03382
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Change in Inventory
ANOVAb
Model
1
Sum of Squares
df
Mean Square
Regression
.080
3
.027
Residual
.639
559
.001
Total
.719
562
F
Sig.
.000a
23.312
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Change in Inventory
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Country
Accounting Standard
Size
Std. Error
.042
.003
-.018
.003
.005
-.013
a. Dependent Variable: Change in Inventory
121
Coefficients
Beta
t
Sig.
15.142
.000
-.253
-6.304
.000
.003
.064
1.615
.107
.003
-.181
-4.498
.000
Casewise Diagnosticsa
Change in
Case Number
Std. Residual
INV
Predicted Value
Residual
91
3.720
.17
.0421
.12580
106
4.408
.20
.0467
.14906
112
3.088
.15
.0467
.10443
116
3.086
.14
.0338
.10437
119
3.353
.16
.0421
.11340
132
4.262
.18
.0338
.14411
144
4.540
.20
.0467
.15352
168
3.757
.17
.0467
.12704
198
4.946
.21
.0467
.16724
220
3.627
.16
.0338
.12265
229
3.171
.15
.0421
.10723
459
3.550
.14
.0157
.12004
537
3.249
.14
.0286
.10986
560
4.259
.17
.0240
.14403
562
3.261
.14
.0286
.11026
563
5.254
.21
.0286
.17766
a. Dependent Variable: Change in Inventory
Residuals Statisticsa
Minimum
Predicted Value
Maximum
Mean
Std. Deviation
N
.0110
.0467
.0290
.01193
563
-.04653
.17766
.00000
.03373
563
Std. Predicted Value
-1.503
1.482
.000
1.000
563
Std. Residual
-1.376
5.254
.000
.997
563
Residual
a. Dependent Variable: Change in Inventory
122
123
Production Costs
Variables Entered/Removedb
Variables
Variables
Entered
Removed
Model
1
Method
Country,
. Enter
Accounting
Standard, Size
a. All requested variables entered.
b. Dependent Variable: Production Costs
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.101a
1
Adjusted R
.010
.005
.11579
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Production Costs
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.077
3
.026
Residual
7.441
555
.013
Total
7.517
558
F
Sig.
.126a
1.914
a. Predictors: (Constant), Country, Accounting Standard, Size
b. Dependent Variable: Production Costs
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
.130
.010
Dummy_Country3
.000
.010
IFRS_local0_IFRS13
.023
Dummy_Size_0small_1big3
.004
a. Dependent Variable: Production Costs
124
Coefficients
Beta
t
Sig.
13.595
.000
-.002
-.036
.972
.010
.100
2.357
.019
.010
.018
.419
.675
Casewise Diagnosticsa
Case Number
Std. Residual
PROD_ABS
Predicted Value
Residual
95
3.996
.62
.1533
.46269
109
3.682
.56
.1303
.42627
130
4.323
.65
.1533
.50050
147
5.568
.80
.1533
.64465
274
3.829
.60
.1575
.44337
277
5.492
.79
.1533
.63595
431
4.863
.72
.1530
.56306
432
3.558
.56
.1530
.41195
433
4.351
.66
.1530
.50377
a. Dependent Variable: Production Costs
Residuals Statisticsa
Minimum
Predicted Value
Maximum
Mean
Std. Deviation
N
.1299
.1575
.1437
.01174
559
-.15722
.64465
.00000
.11547
559
Std. Predicted Value
-1.178
1.169
.000
1.000
559
Std. Residual
-1.358
5.568
.000
.997
559
Residual
a. Dependent Variable: Production Costs
125
126