What determines the amount of reported

goodwill impairment? - An investigation of Nasdaq Stockholm OMX (OMXS)

MASTER’S THESIS WITHIN BUSINESS ADMINISTRATION

THESIS WITHIN: Accounting

NUMBER OF CREDITS: 30 ECTS

PROGRAMME OF STUDY: Civilekonomprogrammet

AUTHORS: Gusten Friberg & Carl Åström Johansson

JÖNKÖPING May 2018

Acknowledgements

First, we would considerably like to thank our tutor Argyris Argyrou for providing us with

pragmatic and functional insights during the writing process. His knowledge has helped us to

use our academic abilities for the best possible outcome of our thesis.

Secondly, we would like to thank Toni Duras for advising us with statistical insights and

lastly, thank Oskar Eng and Annika Yström for brainstorming ideas and giving us mental

motivation during periods of uncertainty.

________________________________ ________________________________

Carl Åström Johansson Gusten Friberg

JÖNKÖPING, SWEDEN, 21st of May 2018

I

MASTER’S THESIS WITHIN BUSINESS ADMINISTRATION, ACCOUNTING

TITLE: What determines the amount of reported goodwill impairment?

- An investigation of Nasdaq Stockholm OMX (OMXS)

AUTHORS: Gusten Friberg & Carl Åström Johansson

TUTOR: Argyris Argyrou

DATE AND PLACE: 21st of May, Jönköping

KEY TERMS: Goodwill Impairment, IFRS 3, IAS 36, Economic Impairment,

Earnings Management, Corporate Governance, Big Bath, Income

Smoothing, Gender Diversity

Abstract

Background: The question on how to account for goodwill has long been a subject that causes

big debates among actors within financial accounting. In 2004, the IASB released a new

standard, IFRS 3 – Business Combinations, that changed the accounting for goodwill. The

interpretation for goodwill impairments according to IAS 36 has led to findings in studies that

show patterns of earnings management and that a possible gap exists between the standard

setter’s basic aim of IAS 36 and what actually is done by the practitioners.

Purpose: Examine what determines the amount of reported goodwill impairment for firms

listed on the Nasdaq OMX Stockholm (OMXS).

Method: To fulfil the purpose of the thesis, the authors takes a quantitative research approach

by a using a multiple linear regression model. The regression model is based on proxies for

economic impairment, earnings management and corporate governance mechanisms from

previous literature (Stenheim & Madsen, 2016; AbuGhazaleh, Al-Hares, & Roberts, 2011;

Riedl, 2004). The data used for the regression model has been collected from published annual

reports of 69 firms listed on the Nasdaq Stockholm OMX (OMXS), between the years 2007-

2016.

Conclusion: The findings of the thesis show that the accounting behaviour of “Big Bath” is

exercised for firms listed on the Nasdaq Stockholm OMX (OMXS). The proxies for economic

impairment have, to some extent, an impact on the amount of reported goodwill impairment,

but the majority of the proxies for corporate governance mechanisms does not affect the amount

of reported goodwill impairment. These findings might suggest that the standard IAS 36, which

regulates the accounting for goodwill, may not entirely fulfil its purpose of creating a more

transparent financial reporting.

II

Acronyms

EBITDA Earnings before interest, tax, depreciation and amortization

EU European Union

FAR Föreningen Auktoriserade Revisorer

(Association of Authorized Auditors)

FASB US Financial Accounting Standard Board

IASB International Accounting Standard Board

IFRS International Financial Reporting Standards

NED Non-executive director

OCF Operating cash-flow

OMXS Nasdaq Stockholm OMX

ROA Return on assets

TA Total assets

Clarification

Large Cap OMX Stockholm Large Capitalization

Mid Cap OMX Stockholm Medium Capitalization

Small Cap OMX Stockholm Small Capitalization

SPSS IBM SPSS Software (Statistical Analysis Software)

III

Table of contents

Acronyms ................................................................................................................................... 4

Clarification ................................................................................................................................ 4

1. Introduction ............................................................................................................................ 1

1.1 Identified research gap ...................................................................................................... 2

1.2 Purpose ............................................................................................................................. 3

1.3 Delimitations ............................................................................................................... 3

2. Literature review .................................................................................................................... 5

2.1 Goodwill ........................................................................................................................... 5

2.2 Goodwill impairment ........................................................................................................ 6

2.3 Financial Accounting Regulations .................................................................................... 7

2.4 Economic Impairment ...................................................................................................... 8

2.5 Earnings Management ...................................................................................................... 9

2.5.1 “Big Bath” and “Income Smoothing” ..................................................................... 10

2.5.2 Agency Theory ........................................................................................................ 11

2.5.3 Stewardship Theory ................................................................................................. 11

2.6 Corporate Governance Mechanisms ............................................................................... 12

2.6.1 Gender Diversity ..................................................................................................... 13

3. Hypotheses ........................................................................................................................... 16

4. Methodology ........................................................................................................................ 18

4.1 Research approach .......................................................................................................... 18

4.2 Research process ............................................................................................................. 18

4.3 Data collection ................................................................................................................ 19

4.3.1 Sample ..................................................................................................................... 20

4.4 Variables ......................................................................................................................... 22

4.4.1 Dependent ................................................................................................................ 24

4.4.2 Independent ............................................................................................................. 24

4.5 Regression model ........................................................................................................... 27

4.6 Research quality - Reliability & Validity ....................................................................... 27

5. Empirical results ................................................................................................................... 29

5.1 Descriptive statistics ....................................................................................................... 29

5.2 Multiple regression analysis ........................................................................................... 31

6. Analysis ................................................................................................................................ 34

6.1 Discussion ....................................................................................................................... 34

6.1.1 Control variable ....................................................................................................... 38

7. Conclusion ............................................................................................................................ 40

8. Discussion ............................................................................................................................ 42

8.1 Contribution .................................................................................................................... 42

8.2 Limitations ...................................................................................................................... 42

8.3 Ethical and social issues ................................................................................................. 43

8.4 Suggestions for further research ..................................................................................... 44

Bibliography ............................................................................................................................. 45

Appendix .................................................................................................................................. 55

Appendix 1 Regression analysis – year-dummies ................................................................ 55

Table 1 Exclusion of observations ...........................................................................................20

Table 2 Exclusion of firms .......................................................................................................21

Table 3 Variables used in the regression model ......................................................................23

Table 4 Year frequency of reported goodwill impairments......................................................29

Table 5 Descriptive statistics ...................................................................................................30

Table 6 Regression analysis .....................................................................................................32

Table 7 Hypotheses Rejection/Acceptance ..............................................................................34

1

1. Introduction

In this chapter, the authors first introduce the topic of goodwill accounting.The authors then

present the identified research gap, the purpose and delimitations of the thesis.

The question on how to account for goodwill has long been a subject that causes big debates

among all actors within financial accounting. Academics, standard setters and practitioners

have all faced problematic situations, when trying to develop a method for goodwill accounting

where theories are in line with the actual practice (Hughes, 1982).

Goodwill will be recognized, as an intangible asset, when an entity acquires another entity or

part of it (IFRS 3). The valuation of the goodwill is made by the acquiring firm, which makes

goodwill an asset that is specifically created from the firm’s own value estimations. Therefore,

goodwill cannot be sold or purchased as a separate item (IFRS 3; Hoggett & Edwards, 2000),

which makes it hard to distinguish and actually pinpoint what exactly creates this added value

of the goodwill (Holthausen & Watts, 2001).

The International Accounting Standard Board issued a new accounting standard, IFRS 3 -

Business Combinations, to solve and eliminate the use of the accounting method called pooling

of interest, which was heavily criticized under the previous standard at that time, IAS 22. IFRS

3 also changed the amortization system that was previously used under IAS 22. IFRS 3 stated

new rules that goodwill should be tested for impairment at the end of each financial year (IFRS

3). Goodwill impairment testing is not a straightforward process as it requires a comprehensive

knowledge on the acquisition method of accounting for business combinations (Seetharaman,

Sreenivasan, Sudha, & Tey, 2006; IFRS 3).

According to the standard IAS 36 - Impairment of Assets, the firm has to use their own

knowledge and ability to recognize a value reduction of the goodwill (IAS 36). Several studies

have shown patterns of earnings management among firms because of the different

interpretations of the standard for goodwill impairment (AbuGhazaleh, Al-Hares, & Roberts,

2011; Stenheim & Madsen, 2016; Riedl, 2004; IAS 36). Managers have the possibility to

influence the financial outcome of the year which has caused the most common critique of IFRS

2

3 that highlights the complicated way of testing for goodwill impairment (AbuGhazaleh, Al-

Hares, & Roberts, 2011).

AbuGhazaleh, Al-Hares, & Roberts (2011) and Stenheim & Madsen (2016) have examined the

size and occurrence of goodwill impairments. AbuGhazaleh, Al-Hares, & Roberts (2011) found

evidence that managers used discretionary actions when impairing for goodwill, especially in

connection with newly appointed CEOs, “Big Bath”, and “Income Smoothing” behaviours.

Stenheim & Madsen (2016) found evidence that showed on a connection between economic

impairment and reported goodwill impairment but on the other hand, the authors also found a

relation between reported goodwill impairment and incentives for earnings management

through the accounting behaviour of “Big Bath” (Stenheim & Madsen, 2016).

There are more factors than just earnings management that can affect the decision of goodwill

impairment. Corporate governance mechanisms have been seen to impact the behaviour and

performance of a firm in a positive way (Huson, Parrino, & Starks, 2001), by reducing conflicts

of interest between owners and managers (Shleifer & Vishny, 1997). The mechanisms do, for

example, consist of the characteristics and composition of the board. Obert, Suppiah, Zororo,

& Desderio (2015) studied the impact of gender diversity within firms’ board of directors and

found that the more number of women on the board, the less scandals and more contribution to

a carrying and social responsible acting. Women engage more in the actual decisions, by

attending more meetings and by collecting more information before decisions (Adams &

Ferreira, 2009). There has also, indirectly, been a positive relation between women on the board

and the financial performance of firms (Isidro & Sobral, 2015). Additionally, the European

Commission have taken action in the question on gender diversity within non-executive boards

for firms, and a proposal to a directive stating a 40 percent involvement for the underrepresented

gender by year 2020 has been presented (European Commission, 2012). In Sweden, females

are the underrepresented gender in the corporate boards for firms listed on Nasdaq Stockholm

OMX (OMXS) (SCB, 2017).

1.1 Identified research gap

Several studies have been made within the topic of determinants for reported goodwill

impairment for firms reporting under the International Accounting Standard Board’s regulation

(AbuGhazaleh, Al-Hares, & Roberts, 2011; Stenheim & Madsen, 2016; Saastamoinen &

3

Pajunen, 2016). AbuGhazaleh, Al-Hares, & Roberts (2011) and Stenheim & Madsen (2016)

examined determinants of reported goodwill impairments for firms listed on the London Stock

Exchange while Saastamoinen & Pajunen (2016) examined determinants for firms listed on the

Nasdaq OMX Helsinki (OMXH). No studies can be found that have examined determinants for

the amount of reported goodwill impairment for firms listed on the Nasdaq Stockholm OMX

(OMXS), reporting under the IASB’s regulations. Consequently, the research contributes to the

topic of goodwill and what determines the amount for reported goodwill impairment.

1.2 Purpose

The purpose of this thesis is to examine what determines the amount of reported goodwill

impairment for firms listed on the Nasdaq OMX Stockholm (OMXS). In order to do so, this

thesis uses proxies from previous studies (AbuGhazaleh, Al-Hares, & Roberts, 2011; Stenheim

& Madsen, 2016; Riedl, 2004) as determinants for economic impairment, earnings management

and corporate governance mechanisms, and in addition, the impact of female board

representation by considering the gender diversity of the board, based on the European

Commission's proposed legislation for gender equality (European Commission, 2012). The

research contributes to the topic of goodwill and what determines the amount of reported

goodwill impairment.

1.3 Delimitations

The thesis will be based on firms listed on the Nasdaq OMX Stockholm (OMXS), on the 31st

of December 2017. The listed firms at this particular time, are studied between the years 2007-

2016. The thesis does not cover firms that do not have goodwill in their balance sheets and

firms that have goodwill in their balance sheet but have not reported any goodwill impairment.

Furthermore, this thesis does not cover firms with a broken fiscal year, firms reporting in

another currency than the Swedish Krona (SEK) and firms within the financial industry (FTSE

International Limited, 2012).

A regression analysis will be used to examine what determines the amount of reported goodwill

impairment, and to do so, data will be collected for proxies of economic impairment, earnings

management and corporate governance mechanisms. This examination will be done by stating

hypotheses based on previous literature within the topic of goodwill impairment. From the

4

result of the regression analysis, the hypotheses will either be rejected or not rejected. The data

collection will be done using the databases Thomson Reuters Eikon Datastream, Retriever

Business and the published annual reports of the firms.

5

2. Literature review

In this chapter, the authors first introduce the topic of goodwill accounting, followed by a

collection of previous studies, theories and concepts on the topic of goodwill impairment,

earnings management and corporate governance mechanisms.

2.1 Goodwill

Goodwill is calculated by adding up the value of the consideration transferred, the amount of

non-controlling interest and the fair value of previous equity interest. This value is then

subtracted with the net amount of the assets acquired and liabilities assumed at the acquisition

date and is created as an asset (IFRS 3). Cañibano, García-Ayuso, & Sánchez (2000) argued

that goodwill should be seen equal to the tangible assets with expected future value, but that the

value is created by intangible investments like new technology, advertising and human

resources. The variety of intangible factors that are said to be part of goodwill result in an asset

that is very specific for each and one of the firms and will consequently be affected when a firm

experiences financial distress (Holthausen & Watts, 2001).

Goodwill could be defined as the difference between the market value of a firm and the sum of

the fair value of the firm’s individual assets, i.e. the realised value the firm would gain by selling

them of individually. Goodwill is created for a firm when gaining value from the synergies of

the assets that the firm has, i.e. using a portfolio of assets in the most optimal way (Feltham &

Ohlson, 1995; Scott, 2009; Storå, 2013).

The different ways of defining goodwill has also been seen to influence the international

standard setter’s work and consequently, a possible gap exist between the regulation in IFRS 3

and what actually is done by the practitioners (Detzen & Zülch, 2012). This gap could be

explained by the standard setter’s attempt to combine both a top-down and bottom-up

perspective (Brännström & Giuliani, 2011). The top-down perspective defines goodwill as

future earnings that the acquiring firm expect to gain due to the acquisition (Johnson & Petrone,

1998). Goodwill is, in the top-down perspective, a group of assets that the acquiring company

cannot fully value or define (Brännström & Giuliani, 2011). In the bottom-up perspective,

goodwill is instead seen as an asset that was not in the balance sheet of the acquired firm, and

therefore, the asset could be called “hidden assets” (Colley & Volkan, 1988).

6

2.2 Goodwill impairment

IFRS 3 changed the accounting for goodwill from amortization to annual impairment tests.

Some experts claimed that the re-establishment and adoption of amortization would more

validly reflect the economic benefits acquired in a business combination for a more truthful

measurement. (European Financial Report Advisory Group, 2014; KPMG, 2014). Additionally,

the impairment test, compared to the annual amortization, is costly and complicated and since

the standard requires an extensive assessment in its interpretation, it creates a risk of false and

inaccurate measurements of the goodwill (European Financial Report Advisory Group, 2014;

International Financial Reporting Standards, 2014a, January; International Financial Reporting

Standards, 2014b, September; International Financial Reporting Standards, 2014c,

December).

The annual impairment test was perceived to create a more transparent base for the accounting

for goodwill, as managers would be able to provide users with better information on future

earnings, cash-flows and growth in the financial statements (European Financial Report

Advisory Group, 2014). Managers may use their discretionary position in impairment testing

to convey private information to the investors in order for them to better make assumptions on

future economic events (Schatt, Doukakis, Bessiux-Ollier, & Walliser, 2016). Managers may

also use their discretionary position to exercise earnings management, that creates an

environment in which the information on goodwill impairment is irrelevant to the investors

(Watts, 2006). To counteract this, detailed information on the goodwill impairment ought to be

provided, i.e. valid explanations on the impairment decision will be better received from

investors (Knauer & Wöhrmann, 2016). Johansen & Plenborg (2013) showed that investors

were most interested in the notes relating to IFRS 3 and IAS 36. Additionally, the investors

were not satisfied with this particular information provided in these notes, i.e. information on

how the impairment test had been done, as investors did not fully comprehend the complex

valuation. Johansen & Plenborgs’ (2013) study can be explained by the findings of Dye (2001)

and Verrecchia (2001), that managers, to some extent, does not want to provide additional

information on economic events that may come to hurt the firm financially, e.g. when

competitors can take use of this information (Mazzi, Andre, Dionysiou, & Tsalavoutas, 2017).

7

Hirschey & Richardson (2003), Bens & Heltzer (2005), Li & Meeks (2006), showed that the

impairment of goodwill had a negative effect on the stock price in a short-term perspective,

which could be explained by the absence of additional information with regards to the

impairment losses of goodwill and the willingness by the investors to have this information

(Johansen & Plenborg, 2013). Cheng, Peterson, & Sherrill (2015) found that the impairment of

goodwill resulted in negative stock price reactions by the market and at the same time, the

authors found that the impairment of goodwill has positive impact on the stock price in a long-

term perspective, as stakeholders recognize that an impairment of goodwill, that occurs from

an earlier acquisition, as a positive event (Cheng, Peterson, & Sherrill, 2015).

The recognition of impairment is a crucial accounting mechanism in financial reports

(Amiraslani, G., & Pope, 2013; André, Filip, & Paugam, 2015; Roychowdhury & Martin,

2013), however, an untimely recognition of goodwill impairments has been shown to take place

in the US-market, which challenges this accounting mechanism (Li & Sloan, 2017; Filip,

Jeanjean, & Paugam, 2015; Ramanna & Watts, 2012; Hayn & Hughes, 2006). Furthermore,

André, Filip & Paugam (2015) also found evidence in European firms for this untimely

recognition. This is of importance, as economic impairment should be faithfully reflected in a

corresponding impairment loss (Ramanna & Watts, 2009; Riedl, 2004; Francis, Hanna, &

Vincent, 1996).

2.3 Financial Accounting Regulations

The latest edition of IFRS 3 was issued in 2008 and was an improvement and joint project

between the US Financial Accounting Standard Board (FASB) and the International

Accounting Standard Board (IASB) (IFRS 3; Deloitte Global Services Limited, u.d.). IFRS 3

defines a business combination as realized when an acquirer obtains control over one or more

businesses through transactions or other events (IFRS 3; FAR AB, u.d.). The big difference

between IAS 22 and IFRS 3 was how the accounting for goodwill should be done. According

to IAS 22, goodwill that occurred when businesses where combined should be amortized on a

yearly regular basis (IFRS 3). According to IFRS 3, goodwill should now instead be tested for

impairment on annual basis. This resulted in the creation of goodwill as an asset that can be

held in the balance sheet indefinitely (IFRS 3; Sherill, 2016). The change from amortization-

and-impairment system to an only-impairment system resulted in an increase of goodwill

8

balances reported and a case study made on the Swedish market, showed a 50 percent increase

of goodwill balances reported post-IFRS 3 (Hamberg, Paananen, & Novak, 2012).

IAS 36 - Impairment of assets (IAS 36), stipulates that goodwill should be annually tested for

impairment. The objective behind IAS 36 aims to secure that a firm's assets are not carried at

an amount that exceed the recoverable amount of the asset (IAS 36). The recoverable amount

is the highest of the value in use, and fair value less costs of disposal (IAS 36). IAS 36 states

that an asset shall be tested for impairment if the firm recognizes indicators of a reduction in

the value of the asset. One indication of this reduction is if the recoverable amount for the cash

generating unit(s), that the goodwill has been allocated to, is less than the carrying amount of

the unit(s). When allocating the goodwill to the cash-generating units, the smallest group of

assets that are able to generate cash flows from ongoing use and that has a cash-flow that is

separated from other groups or assets, is recognized (IAS 36). If so, an impairment should be

recognized with an amount the size as the difference between the recoverable and carrying

amount. The firm cannot recognize an impairment and reduce the carrying amount of the

goodwill below the highest of: (1) if measurable, the asset’s fair value less costs of disposal (2)

if determinable, the asset’s value in use and (3) zero (IAS 36). The standard imposes further

restrictions specifically for goodwill, which requires the asset to be tested for impairment at

least annually, and once recognized, the impairment cannot be reversed (IAS 36).

2.4 Economic Impairment

Literature on the goodwill impairment topic has examined a number of variables that might

reflect economic impairment, e.g. a decrease in the operating cash flow between years

(Stenheim & Madsen, 2016; Francis, Hanna, & Vincent, 1996; Segal, 2003; Riedl, 2004;

AbuGhazaleh, Al-Hares, & Roberts, 2011). An accurate economic impairment of goodwill

cannot be observed since no separate market to determine the actual and current value of

goodwill exist. As a result, existing literature has used a number of proxies to investigate the

undetectable goodwill impairment determinants. The faithfulness of goodwill impairments can

then be discriminated by examining the validity of these proxies for economic impairment

(Stenheim & Madsen, 2016).

Proxies have previously been studied on three aggregation levels: macroeconomic-, industry-

and firm level, by looking at variables linked to impairment losses. On a macroeconomic level,

an economic recession can be shown through increases in unemployment rates. A recession

9

will negatively affect firm performance and hence cause goodwill impairments to be reported

more often (Francis, Hanna, & Vincent, 1996; Segal, 2003; Riedl, 2004). Dah (2016) found

evidence that during times of recession, there is a greater rise in agency problems1, with

managers exploiting their position for private gains, which in turn will negatively affect the

already possible poor performance of the firm. Firm performance is also dependent on the

industry it operates within, and negative financial performance for the industry as a whole will

consequently affect the individual firm negatively. This will consequently result in a greater

likelihood of impairment losses (Francis, Hanna, & Vincent, 1996; Segal, 2003; Riedl, 2004).

On a firm level, previous literature has examined different metrics to explain the economic

impairment for firms, by examining performance and asset values (Stenheim & Madsen, 2016;

AbuGhazaleh, Al-Hares, & Roberts, 2011; Riedl, 2004). Poor prior performance has been seen

to have a great impact on the amount of reported goodwill impairment (Francis, Hanna, &

Vincent, 1996; Zang, 2008).

2.5 Earnings Management

The term earnings management is used to describe the accounting process, in which managers

exploit their position for private gain, by manipulating reported earnings in an attempt to reach

a desirable level of earnings. This is often to the concern of investors and stakeholders and

regarded as a signal that managers are acting opportunistically, when for example, trying to

smooth earnings of a financial report by taking discretionary actions. The term now also

includes and describes almost all forms of earnings manipulation, not just from a managerial

point of view. Practices such as “revolving doors”, i.e. when a firm hires an executive or

controller from their current audit firm, the use of managers discretion to secure a lending

agreement, or to window dress financial statements before initial public offerings. The literature

on earnings management has mostly investigated the occurrence and importance on unexpected

accruals, but recently, the focus has shifted more to studies on when the manipulation and

distribution of reported earnings result in significant changes in the income statement. (Nisar,

2009)

Field, Lys, & Vincent (2001) present three specific conditions that creates a rational reporting

strategy for earnings management in a firm, that may occur if and when:

1 Agency Theory, see section 2.5.2

10

1. There is an information asymmetry between stakeholders and the managers,

2. There is an interest conflict between the managers and stakeholders, and

3. Managers have a greater freedom of accounting choices.

If these three conditions are applicable, managers may gain benefits by engaging in some form

of earnings management (Field, Lys, & Vincent, 2001). The new legislations on how to account

for goodwill may open for earnings management behaviours (Masters-Stout, Costigan, &

Lovata, 2008), as the regulation do not pinpoint any clear valuation of goodwill, as it is specific

to each firm and the valuation is based on managers assumptions (IAS 36). Previous studies on

the subject of goodwill impairments has showed evidence of earnings management and

situations when these impairment losses will not be recognized by the management (Beatty &

Weber, 2006; Masters-Stout, Costigan, & Lovata, 2008; Zang, 2008; Ramanna & Watts, 2009;

AbuGhazaleh, Al-Hares, & Roberts, 2011; Hamberg, Paananen, & Novak, 2012; Saastamoinen

& Pajunen, 2016; Silvola, Huikku, & Mouritsen, 2010).

2.5.1 “Big Bath” and “Income Smoothing”

Hayn & Hughes (2006) showed in their study that managers take advantage of their discretion

to time the impairment in order to fulfil specific reporting targets, and by overstating

impairment losses (Francis, Hanna, & Vincent, 1996; Rees, Gill, & Gore, 1996; Riedl, 2004;

Zucca & Campbell, 1992). Zucca & Campbell (1992) showed that asset write-offs can

especially be seen in times when expected earnings have not been met pre-impairment. By

taking a “Big Bath”, managers have the possibility to improve future earnings, giving the

impression to stakeholders that the “crisis” are past the firm (Zucca & Campbell, 1992;

Alciatore, Dee, Eastion, & Spear, 1998) The practice of “Big Bath” may only influence the

impairment amount (Saastamoinen & Pajunen, 2016), and the decision to report impairment

losses can often be connected to compensation difficulties (Beatty & Weber, 2006; Watts,

2006), which is one of the main parts of the agency theory connected to incentives for managers

(Bednar, 2016).

When pre-impairment earnings are higher than expected, the reporting strategy “Income

Smoothing”, occurs more frequently, as a way to reach expected levels of earnings. Copeland

(1968:101) explains that the accounting strategy of “smoothing”: “...moderates year-to-year

fluctuations in income by shifting earnings from peak years to less successful periods”, in order

to reduce income volatility. The use of “Big Bath” and “Income Smoothing” was presented in

11

a model by Kirshenheiter & Melumad (2002), who showed them as components of a

“equilibrium reporting strategy”. “Income Smoothing” behaviour has been shown to occur in

connection with goodwill impairments, but the behaviour can be diminished through effective

corporate governance mechanisms (AbuGhazaleh, Al-Hares & Roberts, 2011), as employees

of an organization would provide work in the best interest for the objectives of the organization

and its shareholders, acting as “stewards”, which can confirm the basic assumption of the

Stewardship theory2 (Neubaum, 2013).

2.5.2 Agency Theory

The agency theory, try to explain the problem that arises in the situation when a principal hires

an agent to act in the principal's interests (Bednar, 2016). The agency theory can be recognized

in all different kind of situations and is not only applicable in the business world. In firms, the

agency theory can be shown through a separation between ownership (shareholders) and control

(managers). The shareholders, that are the owners of the publicly traded firm, hires the

managers (agents) to run the business and in an indirect point of view, create a return on the

investments that the shareholders have put in. The problem that arises is how the shareholders

should find incentives to make the managers act in the interest of the shareholders (Bednar,

2016). The reason for the managers to not act in the interest of the shareholders is based on the

information asymmetry that can occur between the managers and the shareholders (Zhang,

2012). This asymmetric information is created because of the involvement and difference in the

daily running of the business. The manager is the first actor to receive the most recent

information, in the guidance for decision making, and the shareholders will eventually get this

information when the manager chooses to pass it forward to them. The manager (agent) has the

opportunity to control what kind and amount of information the stakeholders (principals)

receives and therefore, the managers can act in their own interest instead of the stakeholders

(Zhang, 2012).

2.5.3 Stewardship Theory

The Stewardship theory tries to explain the situation where employees of an organization has

the intention to provide work in the best interest for the organization’s objective and its

shareholders. In comparison with the agency theory, organizational agents will instead serve as

2 Stewardship Theory, see section 2.5.3

12

“stewards”, with purposes beyond their own best interest, as they adopt and exercise an attitude

for a more unified performance and result. “Stewards” will act in line with organizational

behaviour to optimize their intrinsic benefits, but not by disregarding what is best for the

organization, but rather trying to enhance the outcome for others, rather than for themselves

(Neubaum, 2013).

The motivations for stewards acting for a collectivistic outcome, instead on the individualistic

behaviour that arises in the agency theory, has its basis from the individual's own psychological

mind-set and, likewise, the organizational approach to strengthen the stewardship structure. The

organization can moderate the accepted power distance levels, the level of employee

involvement and define and elevate the collectivistic spirit for employees. By encouraging

employees to develop their own abilities and obtain personal growth, stewards will actively

work to contribute to the firm as a whole and identify and act in accordance with the

organizational mission and objectives (Neubaum, 2013).

2.6 Corporate Governance Mechanisms

Corporate governance has become a well discussed topic in modern firms because of the

increased separation of ownership and control within firms (Chalevas & Tzovas, 2010).

Corporate governance is defined as the mix of procedures, rules, practices and policies that a

firm’s executives and the firm’s board of directors devote to fulfil their duties set by the

shareholders (Luhman & Cunliffe, 2013). Corporate governance is not only of importance for

the practice of the shareholders, but also for all the stakeholders of the firm. A stakeholder could

be, for example, the employees, other firms and/or the community that a firm is active within.

Corporate governance is of importance as it helps to balance the different interests,

responsibilities and rights that the firm has against its’ stakeholders, but also the interests,

responsibilities and rights that the stakeholder has against the firm. (Chaudhri, 2016)

There is no so called “best model” for how to construct the corporate governance mechanisms,

but still, there has been evidence that a firm’s performance can increase by actively working

with these mechanisms (Perry & Shivdasani, 2005). The basic assumption on what should be

resolved with corporate governance mechanisms is that it should help to improve the agency

problem that arises in a firm, and additionally, create confidence for the stakeholders due to

better behaviour practiced by the management (Chaudhri, 2016).

13

In year 1992, The Cadbury Report was published and was among the first official guidelines

for firms to act in line with corporate governance mechanisms (University of Cambridge, u.d.).

This publication has also been seen as the starting point for the research that has been done in

the field of corporate governance, with a large part of the research focusing on how corporate

governance will impact the financial accounting reporting. Karamanou & Vafeas (2005) found

evidence that the corporate governance mechanisms impact the disclosure quality of the reports

and that stronger corporate governance mechanisms lead to better and more valid accounting

of the annual reports. Other studies also focused on the reason behind this improvement of the

financial reports. The findings indicate that the characteristics of the board, such as more board

activity and more independent non-executive board members has a negative effect on earnings

management and a positive effect on the quality of the financial reporting (Lipton & Lorsch,

1992; Yermack, 1996; Chtourou, Bedard, & Courteau, 2001; Xie, Davidson, & DaDalt, 2003;

Farber, 2005; Vafeas, 2005; Peasnell, Pope, & Young, 2005; Davidson, Goodwinn-Stewart, &

Kent, 2005; Ebrahim, 2007; Koh, LaPlante, & Tong, 2007) . At the same time, Verriest &

Gaeremynck (2009) and AbuGhazaleh, Al-Hares, & Roberts (2011) found that the level of

corporate governance mechanisms in a firm influence the accounting for goodwill impairment.

An increased level of strong and functional corporate governance mechanisms results in a

greater frequency of impairments. This may be explained by the forcing effect of the

mechanisms to reflect a more accurate picture of the firm to improve the firm value (Verriest

& Gaeremynck, 2009).

2.6.1 Gender Diversity

Another corporate governance mechanism that can affect the reported goodwill impairment is

the gender diversity of the board of directors. In November 2012, the European Commission

decided to take actions in the question on gender diversity within non-executive boards for

firms registered in the member states. This was strongly supported by the European Parliament

and resulted in a proposal to a directive that states a quantitative objective of 40 percent should

count for the underrepresented gender by year 2020 (European Commission, 2012). To secure

that merit and qualifications remains in focus, the firms that do not reach the 40 percent

allocation has to argue and present information on why this is not the case (Jourová, 2016).

Spain, France and Finland, has already implemented gender quotas in their national law

(Bianco, Ciavarella, & Signoretti, 2015), in contrast to Sweden, that has no present stated

14

regulation about gender diversity. However, the Swedish Corporate Governance Code

recommends a gender equality as far as possible (Swedish Corporate Governance Board, 2016).

The underrepresented gender in Swedish corporate boards for firm listed on OMXS was in

November 2017, women, which represented 32 percent of total board members (SCB, 2017).

The topic of gender equality has emerged in the study field for businesses and the impact of

increased women involvement in the top management systems within a firm has been discussed

(Bilimoria, 2000; Dezsö & Ross, 2012; Terjesen, Sealy, & Singh, 2009). Some studies show

differences in the way women and men are acting as leaders in businesses. Schuh, o.a. (2014)

argued that women are often less power-hungry then men in the same positions within firms,

which can be explained by the observed reduced power-orientation behaviour that women have

(Adams & Funk, 2012). These differences will also have impact on how decisions are made

and if actions are in line with the self-interest of the manager or not and when serving as a

gender minority on the board, women are able to make a greater contribution to the decision-

making (Kanadlı, Torchia, & Gabaldon, 2018).

When taking place in a board, women are more involved in the work and are attending more

meetings of the board then their male colleagues that will result in greater alignment with the

interest of the shareholders by overriding the board member’s own interest (R.B. Adams, D.

Ferreira, 2009). The problem connected to the agency theory could be reduced if this happens

(Carter, Simkins, & Simpson, 2003). In 2005, Ryan & Haslam (2005b) found evidence that

firms more often choose to elect women as CEOs or board members when they are facing bad

financial performance. The findings questioned Judges (2003) earlier arguments that boards

with only male members were the ones who performed best. An increased number of women

on the board was not the cause of the bad performance, but a bad performance was rather a

trigger for appointing women (Ryan & Haslam, 2005b).

When selected as a board member, women are exposed for a higher level of valuing and testing,

to see if they really are the best candidate for the position (Bygren & Gähler, 2012), and is

considered as gender discrimination (Gregory-Smith, Main, & O'Reilly, 2014). When selecting

a woman for the board, the woman on the board are classified as independent against the firm

(Adams & Ferreira, 2009). The influence of the independency leads to better performance of

the firm, especially with focus on productivity (Joy, Carter, Wagener, & Narayanan, 2007;

McKinsey & Co, 2007; Mckinsey & Co, 2008; McKinsey & Co, 2010; Wilson & Altanlar,

15

2009; Rohner & Dougan, 2012). There are studies that has showed the opposite effect of the

gender impact on a firm’s performance. Gregory, Jeanes, Tharyan, & Tonks (2013) and Shamil,

Shaikh, Ho, & Krishnan (2014) argues that the market reaction and the performance of a firm

depends on so much more variables than just the gender diversity of the board. There can be

times during the measuring period that are biased for female directors and correcting itself when

adding more variables. Ahern & Dittmar (2012) made a study looking into the effects of the

stated law in Norway, that requires gender diversity level of at least 40 percent in corporate

boards and found that the regulation had the opposite effect and resulted in negative impact on

the valuation of the firms.

16

3. Hypotheses

In this chapter, the authors present the hypotheses used in the thesis. First, a small

background for the assumptions of the hypothesis is presented by the authors, followed by the

stated hypothesis.

This thesis will use empirical proxies to examine the economic impairment of goodwill. The

proxies used are: change in return on assets, change in operating cash flow and pre-impairment

book-to-market value. The assumption about using proxies is in line with previous studies

(Francis, Lennox, & Wang, 2010; Riedl, 2004; Beatty & Weber, 2006; Lapointe-Antunes,

Cormier, & Magnan, 2008; Zang, 2008; Stenheim & Madsen, 2016; AbuGhazaleh, Al-Hares,

& Roberts, 2011). The above discussion leads to the following hypothesis:

H1: Firms that experience a negative change in financial performance are more likely to

report a higher amount of goodwill impairment.

To “take a bath”, i.e. the accounting practice “Big Bath”, can take place when the result of the

period is worse than expected. An even worse result will be reported for the period by

recognizing impairments that are abnormally high. With this, the managers postpone the

indirect income to the future periods, often the two following years (Kirshenheiter & Melumad,

2002). The above discussion leads to the following hypothesis:

H2a: Firms that experience an abnormally high negative change in pre-impairment earnings

are more likely to report a higher amount of goodwill impairment.

During “good times” of firm performance, earnings management can be seen in the shape of

“Income Smoothing”. When management are facing higher pre-impairment earnings than

expected, they can use write-offs to end up with reported earnings that will be closer to the

expected financial goals for the period and therefore show on good managerial practices of the

firm (Zucca & Campbell, 1992; Kirshenheiter & Melumad, 2002). The above discussion leads

to the following hypothesis:

H2b: Firms that experience an abnormally high positive change in pre-impairment earnings

are more likely to report a higher amount of goodwill impairment.

17

Firms with strong or more efficient corporate governance mechanisms have been found to

reduce financial fraud and create a more correct and fair financial accounting of the firm

(Peasnell, Pope, & Young, 2005; Davidson, Goodwinn-Stewart, & Kent, 2005; Mulgrew &

Forker, 2006; Ebrahim, 2007; Koh, LaPlante, & Tong, 2007). When looking at corporate

governance mechanisms that has been seen to affect the financial reporting within firms more,

the number of independent members of the board and the level of board activity are both vital

indicators (Verriest & Gaeremynck, 2009; Farber, 2005; Vafeas, 2005; Peasnell, Pope, &

Young, 2005; Davidson, Goodwinn-Stewart, & Kent, 2005; Ebrahim, 2007; Koh, LaPlante, &

Tong, 2007). Additionally, the gender diversity of the board has been seen to impact the

accounting actions and the quality of financial reporting. An increased level of women on the

board leads to better financial reporting (Joy, Carter, Wagener, & Narayanan, 2007; McKinsey

& Co, 2007; McKinsey & Co, 2010; Mckinsey & Co, 2008; Wilson & Altanlar, 2009; Rohner

& Dougan, 2012). The above discussion leads to the following hypothesis:

H3: Firms with strong corporate governance mechanisms are more likely to report a higher

amount of non-opportunistic goodwill impairment.

18

4. Methodology

In this chapter, the authors first introduce the research approach and research process used

in the thesis. After this, the variables used in the thesis are presented by the authors, followed

by the data collection. Last, the regression model and the research quality are presented by

the authors.

4.1 Research approach

To meet the purpose of this research, existing theory (AbuGhazaleh, Al-Hares, & Roberts,

2011; Stenheim & Madsen, 2016; Riedl, 2004), that have stated theoretical propositions for the

determinants and variables used as proxies for economic impairment, occurrences of earnings

management and corporate governance mechanisms, is used. These proxies are connected to

observable variables, that have been used in order to develop hypotheses and the collection of

quantitative data. In addition, this thesis add two variables with regards to the impact of female

board representation.

The quantitative research approach uses a multiple regression analysis, which is consistent with

previous made studies (AbuGhazaleh, Al-Hares, & Roberts, 2011; Stenheim & Madsen, 2016;

Riedl, 2004), were a multiple regression analysis is used to examine what determines the

amount of reported goodwill impairment. Consequently, the results of the model used in this

research could be compared with the findings from previous studies.

Including and testing for several variables allows the research to examine the impact of each

individual variable (Easterby-Smith, Thorpe, & Jackson, Management & Business Research,

2015). Each observation is specific for each and one of the firms since the goodwill impairment

can take an positive infinite number of values, i.e. the variable is continual (Pallant, 2010:148).

This leads to a choice of a multiple linear regression, that fits best for regression analysis with

dependent variables with infinite valuation.

4.2 Research process

The regression model is used to test the hypotheses stated in section 3. Hypotheses and is run

in SPSS using the sample group of 154 firm-year observations for 69 firms. By examining the

19

p-values of the independent variables, any particular significance to the dependent variable is

observable (Saunders, Lewis, & Thornhill, 2009; Donnelly, 2013). These p-values are

examined at significance levels of 1 percent, 5 percent and 10 percent. Consistent with Stenheim

& Madsen (2016), the regression is run with year-dummies to control for any significant

differences between years. This is especially of interest in order to examine if any particular

significance can be found for specific years and if conclusions can be drawn to the aftermath of

the financial crisis between the years 2007-2010 (Sveriges Riksbank, 2018). The variables used

for the regression analysis, all consist of a calculated value as described in Table 3. From this,

the effect of each individual independent variable to the dependent variable is observable. The

relationship between the independent variables and dependent variable is observable by looking

at the positive or negative value of the ẞ-coefficient (Saunders, 2009). In order to understand

and interpret the variables, SPSS is used to retrieve descriptive statistics on the mean-(average),

min-, max value, standard deviation and the 25th and 75th percentile of the observations in the

sample group.

The variance inflation factor (VIF), which is the inverse of the tolerance value, is used to check

for multicollinearity between variables and a VIF value above 10 will indicate a strong

collinearity (Saunders, Lewis, & Thornhill, 2009). If any strong indications for collinearity is

found for the variables, the regression model will be modified by excluding variables to secure

the reliability of the regression model (Saunders, Lewis, & Thornhill, 2009).

4.3 Data collection

The data used in the thesis is collected by the authors using the two databases Retriever Business

and Thomson Reuters Eikon Datastream. The databases complement each other since they are

able to provide different data used in the thesis. Manual collection of data on the board

characteristics is retrieved from published annual reports of the sampled firms. The annual

reports are also used to collect missing data that cannot be provided by Retriever Business or

Thomson Reuters Eikon Datastream. To construct some of the variables, data is also being

collected corresponding to year 2006.

20

4.3.1 Sample

The sample group used for the thesis is created by firms listed on OMXS at 31st of December

2017. To compose the sample group, the three trading lists, large capital, mid capital and small

capital is used. A ten-year period is selected for the research, between the years 2007-2016. The

authors chose to start in year 2007 where the correction from earlier national accounting

regulations impacts has been settled, since firms listed on the OMXS are required to implement

International Accounting Standards issued by IASB after 2005 (European Commission, 2002).

Additionally, the choice of the time-period for the sample group is made to secure an

appropriate number of firm-year observations with goodwill impairments and increase the

validity of the research, as the observed time-period exceeds the previous similar research done

(Riedl, 2004; AbuGhazaleh, Al-Hares, & Roberts, 2011; Stenheim & Madsen, 2016;

Saastamoinen & Pajunen, 2016). The data that confirms if goodwill exists in the balance sheet

or not for the listed firms is collected by using Retriever Business. To collect data on the amount

of reported goodwill impairment, EBITDA, OCF and ROA, Thomson Reuters Eikon

Datastream is used. The collection of the number of board members, characteristics of the board

members, share price, the number of shares, result of previous and present year, total liabilities

and total intangible assets is done by manual collection of the annual financial reports published

by each and one of the firms in the sample group. The data used in this research is classified as

secondary data.

Table 1 – Exclusion of observations

Firm-year observations N Percentage

Firms listed on Nasdaq OMX Stockholm (OMXS)

Dec. 31 2017 (nr. observations)3160 100,00%

Observations classified within the financial industry -430 -13,61%

Non-existing goodwill in the balance sheets -954 -30,19%

Non-impairment observations -1276 -40,38%

Observations with data incomplete or missing, broken fiscal

years, other reporting currency than SEK, or not listed at Nasdaq

OMX Stockholm (OMXS)

-346 -10,95%

Final sample (Firm-year observations) 154 4,87%

21

Table 2 – Exclusion of firms

Table 1 and Table 2 show the sampling process in the thesis. The large-, mid and small capital

lists for the OMXS consisted of 316 firms in 31st of December 2017. For the chosen time period,

3160 possible firm-year observations are found. The first exclusion from the sample are made

in line with previous studies made (Stenheim & Madsen, 2016; AbuGhazaleh, Al-Hares, &

Roberts, 2011; Riedl, 2004) and is based on the industry classification of the firm. The firms in

the sample that are classified as a financial institution according to the Industry Classification

Benchmark are excluded, which includes banks, insurance firms, real estate firms and financial

service firms (FTSE International Limited, 2012). The exclusion of financial institution firms

is made because of the tougher regulations that these types of firms faces, which leads to a loss

in comparability to other industries (Stenheim & Madsen, 2016; AbuGhazaleh, Al-Hares, &

Roberts, 2011; Riedl, 2004). This reduce the sample with 43 firms and 430 firm-year

observations. Secondly, 954 firm-year observations are excluded from the sample since no

goodwill is reported for the observed period. Third, 1276 firm-year observations are not found

to report any goodwill impairment for the observed period and are therefore excluded. The two

criteria, goodwill in the balance sheets and reported goodwill impairments, is chosen to be

made, since the hypotheses of the thesis is designed to only be applicable to firm-years with

reported goodwill impairments. Lastly, a reduction of the sample group is made by excluding

the firm-year observations where no data is found, when there is a broken fiscal year, or the

financial reporting is made in another currency than the Swedish Krona (SEK) or if the firm is

not listed on the OMXS. This reduce the sample with 346 observations.

The final sample consisted of 154 observations [4,87 percent out of total possible observations]

from 69 firms [21,84 percent out of total number of firms] during the time period 2007-2016.

I ndividual firms N Percentage

Firms listed on Nasdaq OMX

Stockholm (OMXS) Dec. 31 2017316 100,00%

Firms excluded by sampling process -247 -78,48%

Final Sample nr. of firms 69 21,84%

22

4.4 Variables

The variables in this thesis is used in previous studies (Stenheim & Madsen, 2016;

AbuGhazaleh, Al-Hares, & Roberts, 2011; Riedl, 2004; Saastamoinen & Pajunen, 2016),

except for the variables related to gender diversity. To secure a comparability of the research,

all continuous variables from these previous studies used in the regression model, are either

adjusted for goodwill impairment reported, scaled for total assets or defined as lagged measures

(i.e. t-1), consistent with previous studies (Stenheim & Madsen, 2016; AbuGhazaleh, Al-Hares,

& Roberts, 2011; Riedl, 2004; Saastamoinen & Pajunen, 2016). The variable

NUM_WOMEN_BOARD is adjusted as the variable NON_EXE, since both variables are

defined as a fraction of the total number of board members of firm i at time t. This correction

protects the thesis from potential proportionality issues in the data used, and therefore, there is

no exclusion of outliers for the variables used in the regression analysis (AbuGhazaleh, Al-

Hares, & Roberts, 2011).

23

Table 3 – Variables used in the regression model

Variable explanation

Dependent variable

IMP_AMOUNT (t )

Reported goodwill impairment (positive

amount) of firm i, period t, scaled by total

assets at time t-1 .

I ndependent variables

ΔROA (i, t, t-1 )Changes in pre-impairment return on assets

of firm i , from period t-1 to t .

ΔOCF (i, t, t-1 )

The change in operating cash flows for firm i

from period t-1 to t scaled by total assets at

the end of t -1

BM (i, t )Pre-impairment book-to-market of firm i ,

time t .

BATH (i, t )

Changes in pre-impairment earnings of firm i

from period t-1 to t , scaled by total assets at

time t-1 , a dichotomous variable that takes the

value when below the median of nonzero

negative values of this variable; otherwise 0.

SMOOTH (i, t )

Changes in pre-impairment earnings of firm i

from period t-1 to t , scaled by total assets at

time t-1 , a dichotomous variable that takes the

value when above the median of nonzero

positive values of this variable; otherwise 0.

BOARD_SIZE (i, t) Natural logarithm of number of board

members of firm i time t .

BOARD_MEET (i, t) Natural logarithm of number of board

meetings of firm i time t .

NONEXE (i,t )

Number of independent non-executive

directors, scaled by total number of board

members of firm i , time t .

NUM_WOMEN_BOARD (i, t )Number of women on board scaled by total

number of board members of firm i , time t.

EU_WOMEN_BOARD (i, t)

Variable equals 1 if firm i fulfill criteria of at

least 40 % women on board in period t ;

otherwise 0.

Control variable

SIZE (i, t)Natural logarithm of total assets of firm i ,

time t-1 .

24

4.4.1 Dependent

The dependent variable used in the multiple regression model represent the amount of reported

goodwill impairment for the firm, IMP_AMOUNT. The definition of IMP_AMOUNT, follows

previous studies, that the amount of reported goodwill impairment of firm i, for year t was

scaled by the value of total assets for year t-1 (Stenheim & Madsen, 2016; AbuGhazaleh, Al-

Hares, & Roberts, 2011; Saastamoinen & Pajunen, 2016). This makes the amount of goodwill

comparable among the observations used in the research.

4.4.2 Independent

The independent variables are divided into three subsections; economic impairment, earnings

management and corporate governance mechanisms.

4.4.2.1 Hypothesis H1, - Proxies for Economic Impairment

∆ROA: Changes in return on assets can be used as an indicator for firm performance and asset

values (Stenheim & Madsen, 2016; AbuGhazaleh, Al-Hares, & Roberts, 2011; Francis, Hanna,

& Vincent, 1996; Kvaal, 2005; Riedl, 2004; Segal, 2003; Sellhorn, 2004; Zang, 2008).

Predicted outcome between ROA and IMP_AMOUNT: ( - ).

- A larger amount of goodwill impairment is reported for firms with negative changes in

return on assets.

∆OCF: Changes in operating cash flows can be used as an indicator for firm performance and

asset values (Stenheim & Madsen, 2016; Francis, Hanna, & Vincent, 1996; Riedl, 2004; Segal,

2003; Sellhorn, 2004; Kvaal, 2005; Zang, 2008). Predicted outcome between ∆OCF and

IMP_AMOUNT: ( - ).

- A larger amount of goodwill impairment is reported for firms with negative changes in

operating cash flows.

BM: Book-to-market ratio can be used as an indicator for impairment losses (Stenheim &

Madsen, 2016; AbuGhazaleh, Al-Hares, & Roberts, 2011; Francis, Hanna, & Vincent, 1996;

Kvaal, 2005; Riedl, 2004; Segal, 2003; Sellhorn, 2004). The book-to-market ratio of a firm

consists of the valuation of the firm made by the market and the firm's own valuation of their

25

books, mostly done in directions of accounting regulation. Predicted outcome between BM and

IMP_AMOUNT: ( + ).

- A larger amount of goodwill impairment is reported for firms with a high book-to-

market ratio.

4.4.2.2 Hypotheses H2a, H2b - Proxies for Earnings Management

BATH: When pre-impairment earnings are lower than expected, impairment losses are larger,

as the accounting behaviour of “Big Bath” occurs. There is no generally proved method to

measure the occurrence of “Big Bath” and therefore, the variable is more used as an indicator

of this accounting behaviour in this thesis (Higson, 2003; Stenheim & Madsen, 2016;

Kirshenheiter & Melumad, 2002; Alciatore, Dee, Eastion, & Spear, 1998; Zucca & Campbell,

1992). Predicted outcome between BATH and IMP_AMOUNT: ( - ).

- A larger amount of goodwill impairment is reported when changes in pre-impairment

earnings between periods, scaled by total assets, when below the median of nonzero

negative values of this variable.

SMOOTH: When pre-impairment earnings are higher than expected, impairment losses are

larger, as the reporting strategy of “Income Smoothing” occurs. There is no generally proved

method to measure the occurrence of “Income Smoothing” and therefore, the variable is more

used as an indicator of this reporting strategy in this thesis (Stenheim & Madsen, 2016;

Kirshenheiter & Melumad, 2002). Predicted outcome between SMOOTH and IMP_AMOUNT:

( + ).

- A larger amount of goodwill impairment is reported when there are changes in pre-

impairment earnings between periods, scaled by total assets, when above the median of

nonzero positive values of this variable.

4.4.2.3 Hypotheses H3, - Proxies for Corporate Governance Mechanisms

BOARD_SIZE: The quality of the financial reporting and the occurrence of earnings

management actions are affected by the number of board members. A larger board is an

indicator for better financial reporting and less occurrence of earnings management actions

26

(Xie, Davidson, & DaDalt, 2003). Predicted outcome between BOARD_SIZE and

IMP_AMOUNT: ( + ).

- A larger amount of non-opportunistic goodwill impairment is reported when there is an

increased number of board members.

BOARD_MEET: The board activity, i.e. the frequency of board meetings, are positively

associated with the quality of the financial reporting and an increased number of board meetings

for the fiscal year improves earnings quality (Xie, Davidson, & DaDalt, 2003; Vafeas, 2005).

Predicted outcome between BOARD_MEET and IMP_AMOUNT: ( + ).

- A larger amount of non-opportunistic goodwill impairment is reported for firms with a

higher frequency of board meetings.

NON_EXE: There is a higher quality of the financial reporting when there is a higher

percentage of non-executive board members that are classified as independent members. The

independence reduces the incentives for earnings management (Davidson, Goodwinn-Stewart,

& Kent, 2005). Predicted outcome between NON_EXE and IMP_AMOUNT: ( + ).

- A larger amount of non-opportunistic goodwill impairment is reported when there is a

higher percentage of non-executive board members.

NUM_WOMEN_BOARD: The gender diversity of the board has an impact on the firm

performance. An increased number of women in the board improves the quality of financial

reporting (Joy, Carter, Wagener, & Narayanan, 2007; Wilson & Altanlar, 2009; Rohner &

Dougan, 2012). Predicted outcome between NUM_WOMEN_BOARD and IMP_AMOUNT:

( + ).

- A larger amount of non-opportunistic goodwill impairment is reported when there is a

larger number of women on the board.

EU_WOMEN_BOARD: The gender diversity of the board has an impact on the firm

performance. An increased number of women in the board improves the quality of financial

reporting (Joy, Carter, Wagener, & Narayanan, 2007; Wilson & Altanlar, 2009; Rohner &

Dougan, 2012). To secure this quality of financial reporting, the EU recommends a 40 percent

level of female board members. Predicted outcome between EU_WOMEN_BOARD and

IMP_AMOUNT: ( ? )

27

4.4.2.4 Control-variable

Consistent with previous studies, SIZE is used as a control variable in previous studies

(AbuGhazaleh, Al-Hares, & Roberts, 2011; Stenheim & Madsen, 2016; Saastamoinen &

Pajunen, 2016).

SIZE: The reporting practice of a firm can be affected by the size of the firm. Therefore, it

would be legitimate to consider this variable when running the regression analysis for the

amount of reported goodwill impairment. For larger firms, there is often an increased pressure

from its stakeholders about complying with the accounting regulations (Watts & Zimmerman,

Positive Accounting Theory: A Ten-Year Perspective, 1990). A small firm may instead lack

the resources necessary for making an accurate impairment test (Bens, Heltzer, & Segal, 2011;

Chalmers & Godfrey, 2011; Jarva, 2009).

4.5 Regression model

𝐼𝑀𝑃_𝐴𝑀𝑂𝑈𝑁𝑇𝑡

= 𝛼0 + 𝛼1𝛥𝑅𝑂𝐴𝑖,𝑡,𝑡−1 + 𝛼2𝛥𝑂𝐶𝐹𝑖,𝑡,𝑡−1 + 𝛼3𝐵𝑀𝑖,𝑡 + 𝛼4𝐵𝐴𝑇𝐻𝑖,𝑡

+ 𝛼5𝑆𝑀𝑂𝑂𝑇𝐻𝑖,𝑡+ 𝛼6𝐵𝑂𝐴𝑅𝐷_𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝛼7𝐵𝑂𝐴𝑅𝐷_𝑀𝐸𝐸𝑇𝑖,𝑡

+ 𝛼8𝑁𝑂𝑁𝐸𝑋𝐸𝑖,𝑡 + 𝛼9𝑁𝑈𝑀_𝑊𝑂𝑀𝐸𝑁_𝐵𝑂𝐴𝑅𝐷𝑖,𝑡

+ 𝛼10𝐸𝑈_𝑊𝑂𝑀𝐸𝑁_𝐵𝑂𝐴𝑅𝐷𝑖,𝑡 + 𝛼11𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝜖𝑖,𝑡

The regression model is used to test the hypotheses stated in section 3. Hypotheses and is run

using the full sample of observations (n=154).

4.6 Research quality - Reliability & Validity

The reflection regarding the value of the research is done through the two segments of reliability

and validity (Bryman & Bell, 2013). The reliability can for example be seen if the research

replicates previous studies made in the field and the results and findings are similar, by this, a

consistency is found (Saunders, Lewis, & Thornhill, 2009). In this thesis, the reliability is

shown in using a regression model, measuring determinants of the amount of goodwill

impairment, collected from previous made studies (AbuGhazaleh, Al-Hares, & Roberts, 2011;

Stenheim & Madsen, 2016).

28

The number of variables used in the regression analysis/model in this thesis, have also had an

impact on the reliability and the validity and have been selected in consideration of what

previous studies have used (AbuGhazaleh, Al-Hares, & Roberts, 2011; Stenheim & Madsen,

2016; Riedl, 2004). The increased number of independent variables have also been motivated

by the statement that reported goodwill impairments can be affected by many different factors

(Francis, Lennox, & Wang, 2010). By including a wide range of variables that has been tested

before, that can have a possible impact on the amount of the reported goodwill impairment, the

research reliability may increase. However, not all variables used in previous studies are

included in the regression model and additionally, two non-previously tested variables has been

included in this thesis (AbuGhazaleh, Al-Hares, & Roberts, 2011; Stenheim & Madsen, 2016;

Riedl, 2004). These choices make the thesis not fully consistent with previous studies and could

come to harm the reliability of the thesis.

The second segment of the value of research is the validity which reflects how well the results

and models used in the research actually reflect the reality (Bryman & Bell, 2013). The validity

in this thesis have been secured by being attentive of where the data has been collected from.

The data collection has been made by using databases with information presented from publicly

published reports that are approved by auditors. Additionally, the complementing data,

collected manually, was collected from the audited publicly published reports. Likewise, the

motivation behind this choice was to collect data that would lead to better validity of the

research.

The selected time frame for the observations is also something that could impact the validity of

the research. The time frame used in this thesis could impact the results, since the years 2008-

2009 was heavily affected by the financial crises (Rani & Torres, 2011), that affected the

Swedish economy between the years 2007-2010 (Sveriges Riksbank, 2018). This recession

could lead to abnormal observations that will impact the result of the thesis. To solve this

potential dilemma of external validity, an expanded time frame, compared to earlier studies

made, is used in order to recognize potential changes in the trends (Bryman & Bell, 2013).

29

5. Empirical results

In this chapter, the authors present the empirical results of the thesis; the descriptive statistics

and the results of the multiple regression.

5.1 Descriptive statistics

The sample, used in the thesis, consists of 154 observations, between the years 2007-2016.

Table 4 shows the frequency of reported goodwill impairment observations for the ten-year

period. As seen in Table 4, a higher frequency of goodwill impairments was reported between

the years 2008 and 2011.

Table 4 – Year frequency of reported goodwill impairments

The descriptive data for the variables used in the multiple regression analysis is presented in

Table 5 below. Table 5 is constructed with the descriptive data of the dependent variables

presented in the upper part of the table and is followed by descriptive data for the independent

variables and control variable used in the regression model.

Year Reported goodwill impairment

observations (final sample)

Percentage of reported goodwill

impairment observations (final

sample)

2007 13 8,4%

2008 16 10,4%

2009 23 14,9%

2010 19 12,3%

2011 24 15,6%

2012 11 7,1%

2013 14 9,1%

2014 13 8,4%

2015 9 5,8%

2016 12 7,8%

Total 154 100,0%

30

Table 5 – Descriptive statistics

There is a big range for the amount of reported goodwill impairment among the observations

used. The impairment amount has a minimum value of 34 000 SEK and a maximum value of 4

984 000 000 SEK with a mean value of 214 432 629 SEK. Fifty percent of the amount of

reported goodwill impairment for the sample group is between 8 000 000 SEK and 103 650 000

SEK. When the average (mean) firm in the sample group report goodwill impairment, the size

of the impairment represents 28 percent [0,283] of the total assets of the firm. There is a big

range between the size of the firms in the sample group. The average firm reports total assets

of 18 228 741 429 and fifty percent of the firms report assets between 662 757 750 SEK and

26 915 500 000 SEK, which show on big differences for the size of firm in the sample group.

The variables, ∆ROA, ∆OCF and BM, associated with economic impairment, show on big

differences between the max- and min values.

The average board of directors for the sample group used in the thesis consists of 7 board

members and fifty percent of the observations reported a board of directors consisting of 6 to 8

board members. The minimum value of 3 board members follows the Swedish corporate law,

which requires a minimum of 3 board members for a publicly traded firm (Justitiedepartementet

L1, 2005, 18:46). For the sample group, a range from no women at all (min) up to 5 female

Nr. of

observationsMean Median Std. Deviation Minimum Maxmimum

25% 75%

Amount of

Reported

Goodwill

Impairment

154 214 432 626 33 200 000 603 709 579 34 000 4 984 000 000 8 000 000 103 650 000

I MP_AMOUNT 154 0,283 0,011 1,919 0,000 21,677 0,001 0,051

Number of Board

Members154 7 7 2 3 10 6 8

Number of

Female Board

Members

154 2 2 1 0 5 1 2

Number of

Independent

NED

154 6 6 2 1 10 5 7

Total Number of

Board Meetings154 11 10 4 5 32 8 13

ΔOCF (i,t,t-1) 154 7,085% 0,155% 381,470% -1692,353% 3890,463% -2,503% 3,523%

Total Assets (t-1) 154 18 228 741 429 4 360 450 000 32 233 337 904 26 475 000 251 000 000 000 662 757 750 26 915 500 000

ΔROA (i,t,t-1) 154 -1,042 -0,002 13,054 -102,833 46,459 -0,028 0,032

BM (i,t) 154 -0,220 0,090 1,935 -16,040 3,780 -0,223 0,363

BATH/SMOOTH 154 0,415 -0,003 13,329 -97,755 94,051 -0,051 0,029

Percentile

31

board members (max) can be observed for NUM_WOMEN_BOARD, and the mean value of

female board members for the sample used is 2. A big range can also be observed for the number

of independent NEDs, from minimum of 1 to a maximum of 10, with a mean value of 6. The

variable BOARD_MEET shows on a min value of 5 up to a max value of 32 meeting per year,

with a mean value of 11 meetings per year.

5.2 Multiple regression analysis

The authors test the hypotheses by running a multiple regression analysis in SPSS3. The output

from the regression analysis is presented in Table 6 below. The table provides information about

the predicted relationship between the independent variables and the dependent variable, the

Standardized Beta Coefficient (ẞ), Standard errors, the significance level (p-value) and the

Variance Inflation Factor (VIF). The p-values of the variables that meet the significance are

respectively marked at a 10 percent- (*), 5 percent- (**) and 1 percent-level (***) in the table.

If a variable is significant, the ẞ-coefficient, can statistically significantly, show how a one-

unit-change in the independent variable will change the outcome for the dependent variable.

Table 6 also present the value of the Adjusted R2 (coefficient of determination). The Adjusted

R2-value represents the amount of variance for the dependent variable that the independent

variables used in the regression model explain and is used to check if the regression analysis

has any explanatory power or not. The regression analysis results in an Adjusted R2-value of

31,5 percent, i.e. the variance in the amount of reported goodwill impairment for the period

2007-2016 is explained up to 31,5 percent by the multiple linear regression model in this thesis.

3 The whole regression was run with year-dummies to examine if there are any significant differences between the

years.

Regression analysis run with year-dummies, see Appendix 1

32

Table 6 – Regression analysis

The variable ∆OCF [-0,394 ẞ] follow the predicted outcome and is significant at a level of 1

percent [p<0,001], i.e. if there is a decrease in the operating cash flow between the previous

and current period, a higher amount of reported goodwill impairment for the current period will

be observed. The variables ∆ROA [0,165 ẞ] and BM [-0,067 ẞ] does not follow the predicted

outcome and are not significant at any level tested [p=0,110 and p=0,358].

The effect of the variables related to earnings management; BATH [-0,396 ẞ] and SMOOTH

[0,114 ẞ], both followed the predicted outcome. The variable BATH is significant at a level of

1 percent [p<0,001], which show that if there is an abnormally decreased EBITDA from the

previous to the current period, an increased amount of reported goodwill impairment in the

current period will be observed. The variable SMOOTH is not significant [p=0,263].

The variable BOARD_SIZE [0,180 ẞ] follow the predicted outcome and is significant at a level

of 10 percent [p=0,053] which indicates that if there is an increased number of board members,

an increased amount of reported goodwill impairment will be observed. The variable

BOARD_MEET [0,052 ẞ] follow the predicted outcome, but for the variable NONEXE [-0,036

ẞ], the outcome was not as predicted, and both of the variables lack significance [p=0,485 and

p=0,605]. For the variables related to the gender diversity on the board,

NUM_WOMEN_BOARD [0,038 ẞ] follow the predicted outcome and the variable

EU_WOMEN_BOARD [-0,055 ẞ] have a negative ẞ-coefficient. However, none of the

Variable Predicted outcome β-coefficient Std-error p-value VIF

ΔROA (i,t,t-1) - 0,165 0,015 0,110 2,354

ΔOCF (i,t,t-1) - -0,394 0,046 0,000*** 1,892

BM (i,t) + -0,067 0,072 0,358 1,178

BATH (i,t) - -0,396 0,022 0,000*** 2,112

SMOOTH (i,t) + 0,114 0,019 0,263 2,289

BOARD_SI ZE (i,t) + 0,180 0,735 0,053* 1,919

BOARD_MEET (i,t) + 0,052 0,419 0,485 1,257

NONEXE (i,t) + -0,036 0,784 0,605 1,092

NUM_WOMEN_BOARD (i, t) + 0,038 1,242 0,691 1,992

EU_WOMEN_BOARD (i,t) ? -0,055 0,553 0,569 2,112

SI ZE_MV +/- -0,308 0,087 0,002*** 2,205

R R SquareAdjusted R

Square

Std. Error of the

Estimate

0,637 0,406 0,317 1,586

***. Correlation is significant at the 0.01 level.

**. Correlation is significant at the 0.05 level.

*. Correlation is significant at the 0.10 level.

33

variables are significant NUM_WOMEN_BOARD [p=0,691] and EU_WOMEN_BOARD

[p=0,569].

The control variable SIZE is significant at a level of 1 percent [p=0,002] and has a negative ẞ-

coefficient [-0,308 ẞ]. If the size of the firm increases, a decreased amount of reported goodwill

impairment will be observed.

34

6. Analysis

In this chapter, the authors present the analysis of the empirical results in chapter 5.

The analysis of the hypotheses is based on previous research and theories

presented in chapter 2.

6.1 Discussion

This thesis has tested 4 hypotheses to understand determinants for the amount of reported

goodwill impairment. The hypotheses tested is presented in Table 7 below. If the null

hypothesis is rejected and consequently, there is an acceptance of the alternative hypothesis, it

is marked with a ✔️. This thesis examines significance levels at 10 percent, 5 percent and 1

percent. For example, a significance level at 1 percent means that it is a 1 percent probability

of rejecting a true null hypothesis and therefore, possibly, making a Type Ⅰ Error. A Type Ⅰ

error arises when the null hypothesis is rejected but the null hypothesis is actually true for the

population (Donnelly, 2013).

Table 7 – Hypotheses – Rejection/Acceptance

Hypothesis

Acceptance of

alternative

hypothesis

H1: Firms that experience a negative change in

financial performance are more likely to report a

higher amount of goodwill impairment.

H2a: Firms that experience an abnormally high

negative change in pre-impairment earnings are

more likely to report a higher amount of goodwill

impairment.

✔️

H2b: Firms that experience an abnormally high

positive change in pre-impairment earnings are

more likely to report a higher amount of goodwill

impairment.

H3: Firms with strong corporate governance

mechanisms are more likely to report a higher

amount of non-opportunistic goodwill impairment.

35

The empirical results in this thesis does not show on a significance for the variable ∆ROA, i.e.

a change in ROA is not negatively associated with the amount of reported goodwill impairment.

When firms listed on OMXS experience a change in ROA, an increased amount of reported

goodwill impairment will not be observed. This finding is non-consistent to findings in previous

literature. AbuGhazaleh, Al-Hares, & Roberts (2011) and Stenheim & Madsen (2016) both

found a significant relationship that a change in ROA was negatively associated with the

amount of reported goodwill impairment.

The empirical results in this thesis show on a significance for the variable ∆OCF, i.e. if firms,

listed on OMXS, experience a negative change in the operating cash flow between the previous

and current period, an increased amount of reported goodwill impairment will be observed.

This finding is in line with findings in previous literature (Stenheim & Madsen, 2016;

AbuGhazaleh, Al-Hares, & Roberts, 2011), which found that if a firm has a reduction in the

level of operating cash flow between two periods, the firm will report an increased amount of

goodwill impairment. This finding is also consistent with the accounting regulation of

impairment of when there is an indication of a possible goodwill impairment-need (IAS 36).

This indicates that the aim of the regulation is reflected among firms listed on OMXS and that

the standard, IAS 36, provide firms with a foundation to reliably report the underlying financial

performance. If a firm experiences a change in financial performance, e.g. a decrease in sales

or the result of the year, a goodwill impairment test is more likely to indicate a need for

impairment (IAS 36).

The empirical results of the thesis indicate that the variable BM both lack significance and do

not follow the predicted outcome, i.e. a high book-to-market ratio will not affect the amount of

reported goodwill impairment. This finding is inconsistent with previous studies (Stenheim &

Madsen, 2016; AbuGhazaleh, Al-Hares, & Roberts, 2011) were the book-to-market ratio has

been seen to have a positive association with the amount of reported goodwill impairment. One

explanation for these findings might be that the cash-generating units for firms listed on the

OMXS are not to the same extent affected by changes in the market capitalization value as the

firms observed in previous studies. Even if there are negative speculations on the stock market

affecting the value of the market capitalization, the cash-generating units, that are part of the

operational activities within a firm, may not be affected. This explanation can to some extent

be confirmed by the findings that the amount of reported goodwill impairment is negatively

associated with a change in the operating cash flows.

36

The findings in the thesis only show on significance for one, out of three proxies for economic

impairment, and therefore, the null-hypothesis H1 cannot be rejected. The amount of the

reported goodwill impairment for firms, listed on OMXS, is not affected by a negative change

in the proxies used for economic impairment in this thesis.

Economic impairment in this thesis is examined by using proxies at a firm level, but still, the

financial performance of a firm is affected by other factors outside the firm. The sample used

in this thesis has been checked for a ten-year period between 2007-2016. During the years 2007-

2010 (Sveriges Riksbank, 2018), a recession affected many firms around the world, making

them face difficulties in their performance. This can explain why there is a higher frequency of

reported goodwill impairments between the years, 2008 and 2011, for firms listed on the

OMXS. Firms that are experiencing a bad performance for only one period can often regain

their position in the following years, but when a bad performance occurs throughout several

periods, e.g. in the case of a recession, a firm is more likely to experience a decline in their

financial performance (Francis, Hanna, & Vincent, 1996; Segal, 2003; Riedl, 2004), and

consequently, possible long-term problems in their performance and possible impairments of a

firm’s goodwill.

The empirical results showed a significance for the variable BATH, that followed the predicted

outcome. Therefore, the null hypothesis H2a is rejected and the alternative hypothesis H2a is

accepted. The acceptance of H2a is in line with previous studies, as AbuGhazaleh, Al-Hares, &

Roberts (2011), Stenheim & Madsen (2016) and Saastamoinen & Pajunen (2016) all found that

an abnormally high negative change in pre-impairment earnings had a significant impact on the

amount of reported goodwill impairment. A negative change in pre-impairment earnings could

create incentives for managers to act in self-interest, by “taking a bath”. The acceptance of the

alternative hypothesis H2a can be seen as an indication for the accounting behaviour “Big Bath”

and the occurrence of earnings management behaviours for firms listed on the OMXS, which

may show that the accounting management of firms listed on the OMXS uses their discretionary

position to manage earnings. Incentives for managers to manage earnings can be connected to

the basic assumption of the agency theory, and a possible information asymmetry between the

managers and the firm’s stakeholders. Most likely this information asymmetry will be reflected

in the notes when managers do not fully present the process and information of the goodwill

impairment test (Johansen & Plenborg, 2013).

37

Hypothesis H2b was tested to show on possible occurrences of the reporting strategy “Income

Smoothing”. The empirical results of this thesis showed that there is no significant effect on the

amount of reported goodwill impairment for firms with abnormally high pre-impairment

earnings listed on OMXS. Therefore, the null hypothesis of H2b is not rejected. The amount of

the reported goodwill impairment cannot be seen to be affected by abnormally high pre-

impairment earnings. To not reject the null hypothesis H2b is primarily in line with previous

literature. Neither Stenheim & Madsen (2016) or Riedl (2004) found any significant indication

on the effect of “Income Smoothing” for the amount of reported goodwill impairment. At the

same time, AbuGhazaleh, Al-Hares, & Roberts (2011) did find a significant relationship

between the variable SMOOTH and the amount of reported goodwill impairment. One

explanation for the finding in this thesis may be that Swedish firms gain more by reporting a

better performance than expected, instead of practicing the reporting strategy of “Income

Smoothing” and meet the planned target for the period. This can be an indication of

management's willingness to act as stewards, i.e. acting for a collectivistic outcome by

considering what is best for the organization and likewise, its stakeholders.

Hypothesis H3 was constructed to test if stronger corporate governance mechanisms have any

effect on the amount of reported goodwill impairment. The empirical results only showed

significance for one out of five variables that are used in the regression model, and therefore,

the null hypothesis H3 cannot be rejected.

The empirical results showed on a significance for the variable BOARD_SIZE that followed

the predicted outcome. If the board size increase for firms listed on OMXS, a higher amount of

goodwill impairment will be observed. This finding is inconsistent with the findings of

Stenheim & Madsen (2016), AbuGhazaleh, Al-Hares, & Roberts (2011) and Verriest &

Gaeremynck (2009), whom found that the size of the board does not affect the amount of

reported goodwill impairment. An explanation to the finding could be that an increased number

of board members reduces the option to act in self-interest of the individual board member, as

there are more individuals that can impact the actions taken by the board (Lipton & Lorsch,

1992; Yermack, 1996; Chtourou, Bedard, & Courteau, 2001; Xie, Davidson, & DaDalt, 2003;

Farber, 2005; Vafeas, 2005; Peasnell, Pope, & Young, 2005; Davidson, Goodwinn-Stewart, &

Kent, 2005; Ebrahim, 2007; Koh, LaPlante, & Tong, 2007).

38

The empirical results showed on no significance for the two variables BOARD_MEET and

NONEXE, i.e. the amount of reported goodwill impairment is not affected by a higher number

of board meetings or a higher number of independent non-executive directors on the board, for

firms listed on OMXS. These findings are inconsistent with the findings of AbuGhazaleh, Al-

Hares, & Roberts (2011), whom found that these corporate governance mechanisms had an

impact on the amount of reported goodwill impairment.

Previous studies made in the field of gender diversity has showed on improved financial

reporting quality and less actions made in self-interest when there is an increased number of

women on the board (Schuh, o.a., 2014; Adams & Funk, 2012; Adams & Ferreira, 2009; Ryan

& Haslam, 2005b). No comparison can be made with the results in this thesis since previous

studies have not included variables testing for gender diversity when investigating determinants

of goodwill impairment. The empirical results show no significance for the variables,

NUM_WOMEN_BOARD and EU_WOMEN_BOARD. For firms listed on OMXS, the gender

diversity of the board does not impact the amount of reported goodwill impairment which can

be explained by Gregory, Jeanes, Tharyan, & Tonks (2013) and Shamil, Shaikh, Ho, &

Krishnan (2014) findings that a firm's financial performance is dependent of more than just the

gender diversity of the board. It could be of interest to reflect upon the levels of gender diversity

on the board since the empirical results showed on different outcomes for the two variables.

These findings may show, that on order to be able to see the impact of a more equal gender

diversity of the board on the amount of reported goodwill impairment, a certain level of gender

diversity of the board must be reached (Kanadlı, Torchia, & Gabaldon, 2018).

6.1.1 Control variable

The empirical results show on a significance for the control variable SIZE, that is negatively

associated with the amount of reported goodwill impairment, i.e. if the size of the firm

increases, a decreased amount of reported goodwill impairment will be observed. One

explanation for this finding could be that a bigger firm is more exposed to the pressure from

stakeholders and therefore does not have the possibility to opportunistically report a higher

amount of goodwill impairment (Watts & Zimmerman, 1990). Another explanation could be

that firms have the possibility to do more accurate impairment tests. The resources spent on

these tests and the accuracy of the impairment tests may differ since the impairment test is

individualistic for each firm. Previous studies have found that smaller firms lack resources to

39

do correct impairment tests for goodwill. These smaller firms will instead report goodwill

impairments more frequently, to compensate for the possible errors that may occur because of

the minimal resources they can spend on the impairment test for one period (Bens, Heltzer, &

Segal, 2011; Chalmers & Godfrey, 2011; Jarva, 2009). This could be the case for firms listed

on the OMXS, as there are extremely large differences in the size of the firms in the sample

group.

40

7. Conclusion

In this chapter, the authors present the concluding thoughts of the thesis. The conclusions are

based on the findings in section 6. Analysis.

This thesis examines what determines the amount of reported goodwill impairment for firms

listed on the Nasdaq Stockholm OMX (OMXS) between the years 2007-2016. The standard

IFRS 3, changed the accounting for goodwill from yearly amortization to impairment tests, with

the aim to create a more transparent base and truthful valuation of goodwill. IASB asserted that

impairment testing would improve the accounting for goodwill (FAR AB, u.d.), as firms would

be able to provide more relevant and practical information of the financial performance and that

economic impairment would be reflected in corresponding goodwill impairment. Previous

literature has examined if economic impairment actually is the only factor determining goodwill

impairment for firms, or if there are other aspects affecting the decision to impair goodwill and

the goodwill impairment amount (Stenheim & Madsen, 2016; AbuGhazaleh, Al-Hares, &

Roberts, 2011; Saastamoinen & Pajunen, 2016) and findings show that the interpretation of

IFRS 3 has led to patterns on earnings management that affect the amount of reported goodwill

impairment. No studies have examined determinants for the amount of reported goodwill

impairment for firms listed on the Nasdaq Stockholm OMX (OMXS), reporting under the

IASB’s regulations.

A sample group consisting of 69 firms listed on Nasdaq Stockholm OMX (OMXS) at the 31st

of December 2017, studied over a ten-year period (2007-2016), resulted in a sample size of 154

firm-year observations after the sampling process, that is used in the thesis. Using the firm-year

observations, a multiple regression analysis was run by the authors to test for the chosen

determinant variables of the amount of reported goodwill impairment.

The empirical results show that the amount of reported goodwill impairment is not affected by

corporate governance mechanisms, however, a higher amount of reported goodwill impairment

can be observed when there is a larger number of board members. The amount of reported

goodwill impairment is affected by “Big Bath” actions, which might indicate that the regulation

of IAS 36 does not entirely fulfil its purpose to create a more transparent goodwill accounting

(FAR AB, u.d.). The reporting strategy “Income Smoothing” is not exercised by firms listed on

41

OMXS. A negative change in the financial performance for firms listed on OMXS does not

have an impact on the amount of reported goodwill impairment. However, a negative change

in the operating cash flow, has an impact on the amount of reported goodwill impairment which

indicates that the aim of the standard IAS 36 is reflected among firms listed on OMXS.

42

8. Discussion

In this chapter, the authors discuss the contributions of the thesis to the research field of

goodwill impairment. The authors also clarify the limitations of the thesis and the ethical and

social impact of the thesis. Finally, the authors present suggestions on further research within

the topic of goodwill accounting.

8.1 Contribution

The thesis contributes to the discussion of what determines the amount of reported goodwill

impairment for firms reporting under the IASB’s regulations. A contribution to the discussion

on goodwill impairment accounting, highlights the question on what has the biggest impact on

the amount of reported goodwill impairment; the regulation of accounting for goodwill,

accounting behaviour of earnings management or corporate governance mechanisms. Studies

on the topic of what determines the amount of reported goodwill impairment have not

previously examined firms listed on the Nasdaq Stockholm OMX (OMXS). Consequently, the

thesis can contribute to the field of accounting for goodwill by providing information from a

Swedish context in order to identify similarities and differences in what determines the amount

of reported goodwill impairment for firms reporting under IFRS.

8.2 Limitations

No strong assertions can be made on why the variables used in this thesis can be seen as

determinants for economic impairment, earnings management and stronger corporate

governance mechanisms, and more likely, they are possible explanations for the amount of

reported goodwill impairment (Stenheim & Madsen, 2016).

The data used in the thesis is retrieved from different sources; Thomson Reuters Eikon

Datastream, Retriever Business and published annual reports, and there may be differences on

how the data is presented among these three sources. Retrieving applicable data from multiple

sources is a common approach for academics that are conducting research within the accounting

field (Saunders, Lewis, & Thornhill, 2009). The authors are aware of the problems that may

arise when handling data from different sources. When there was a goodwill impairment for the

firm, retrieved from Thomson Reuters Eikon Datastream, but there was no goodwill asset

43

reported, retrieved from Retriever Business, the published annual report was used to resolve the

issue and collect the correct data.

A further limitation of the thesis that should be considered is the size of observations from the

sample group and to what degree the results of the thesis can be generalizable to the population

of firms listed on OMXS, as a smaller sample size will decrease the possibility to make general

assumptions about the population (Lantz, 2009; Saunders, Lewis, & Thornhill, 2009).

8.3 Ethical and social issues

The accounting for goodwill under IFRS 3, was perceived to better reflect the financial

performance of a firm, and that stakeholders could receive information, e.g. on future earnings

and cash-flows, that would be more relevant and accurate (FAR AB, u.d.). However, the finding

in this thesis show on patterns of earnings management with the accounting behaviour of “Big

Bath”. The accounting behaviour of “Big Bath”, and earnings management in general, could be

seen as unethical, since the actions taken by the management do not take the majority of the

stakeholders’ interest into account. The proxies of economic impairment and earnings

management are proposed explanations used to explain the determinants for the goodwill

impairment, and even if the variable BATH is significant, the occurrence of this accounting

behaviour may not be accurate for firms listed on OMXS. At the same time the finding of the

thesis can come to indicate that actions, within the regulation, has to be taken to solve the

problem of “Big Bath” behaviour.

Gender diversity can be seen as a neglectable topic, that is not necessary to consider when

talking about financial performance, since the thesis does not find any significant impact of

gender diversity on the amount of reported goodwill impairment. The findings of this thesis

could therefore be used as an unethical argument in the discussion on gender diversity. In order

to give a more accurate and reliable result of the impact of gender diversity within firms, more

research, with bigger sample groups, is needed. Additionally, investigating the amount of

reported goodwill impairment, may not be the most suitable way to determine the effect of an

increased gender diversified board on a firm’s financial performance.

44

8.4 Suggestions for further research

An interesting aspect to investigate would be to examine those firms that have reported an

impairment loss, and the generated cash flows of the following years for the firm. One of the

elements that should be reflected when calculating the value in use of the goodwill is the

expected future cash flows. It would be of interest to compare the amount of reported goodwill

impairment and the change in the future expected cash flows for the following periods.

Decreases in expected future cash flows should be reflected in the amount of reported goodwill

impairment if the cash flows are to be used as a base for valuation of goodwill as an asset.

Throughout the studies made on what determines the amount of reported goodwill impairment,

earnings management accounting behaviours and reporting strategies has been observed

(AbuGhazaleh, Al-Hares, & Roberts, 2011; Stenheim & Madsen, 2016; Saastamoinen &

Pajunen, 2016). Because earnings management is based on incentives for individuals,

differences may occur between cultures and it would be of interest to compare differences of

determinants between countries when investigating goodwill impairment.

The change from amortization to impairment testing of goodwill results in the possibility for

goodwill to remain in the balance sheet perpetually (Sherill, 2016). The asset is tested on an

annual basis to check if it still has value, i.e. to see if the economic benefits acquired still are

being realized (IAS 36). Therefore, a suggestion for further research would be to investigate

the valuation of a firm pre- and post the implementation of the impairment system and examine

how the value of the firm changes.

45

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Appendix

Appendix 1 Regression analysis – year-dummies

Variable Predicted outcome β-coefficient Std-error p-value VI F

ΔROA (i,t,t-1) - 0,165 0,015 0,110 2,354

ΔOCF (i,t,t-1) - -0,394 0,046 0,000*** 1,892

BM (i,t) + -0,067 0,072 0,358 1,178

BATH (i,t) - -0,396 0,022 0,000*** 2,112

SMOOTH (i,t) + 0,114 0,019 0,263 2,289

BOARD_SI ZE (i,t) + 0,180 0,735 0,053* 1,919

BOARD_MEET (i,t) + 0,052 0,419 0,485 1,257

NONEXE (i,t) - -0,036 0,784 0,605 1,092

NUM_WOMEN_BOARD (i, t) ? 0,038 1,242 0,691 1,992

EU_WOMEN_BOARD (i,t) ? -0,055 0,553 0,569 2,112

SI ZE_MV +/- -0,308 0,087 0,002*** 2,205

@2008 -0,076 0,637 0,454 2,314

@2009 -0,095 0,601 0,399 2,804

@2010 -0,156 0,622 0,147 2,564

@2011 -0,047 0,582 0,668 2,726

@2012 0,138 0,688 0,139 1,924

@2013 -0,075 0,655 0,446 2,171

@2014 -0,086 0,668 0,378 2,113

@2015 -0,054 0,739 0,551 1,840

@2016 -0,049 0,725 0,630 2,309

*. Correlation is significant at the 0.10 level.

***. Correlation is significant at the 0.01 level.

**. Correlation is significant at the 0.05 level.