THE RELATIONSHIP BETWEEN CORPORATE GOVERNANCE AND MERGERS …

THE RELATIONSHIP BETWEEN CORPORATE

GOVERNANCE AND MERGERS & ACQUISITIONS

A CASE STUDY ON US BANK HOLDING COMPANIES

Before, During, and After the Global Financial Crisis

E.D.W.G. Lips, November 2016

THE RELATIONSHIP BETWEEN CORPORATE GOVERNANCE AND MERGERS & ACQUISITIONS


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Master Thesis Finance

Tilburg School of Economics and Management, Tilburg University

Department of Finance

Student E.D.W.G. Lips

ANR 11 40 69

Supervisor A. Vlachaki

Second Reader Dr. O.G. De Jonghe

Date of submission November 30th, 2016



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Preface

During the last couple of months I have been working on this thesis in order to successfully

complete my Masters in Finance, and marks the end of my time as a student. Writing my thesis has given

me practical insight of my study, which will hopefully bring me much value for the future. It was a time of

learning, through ups and downs, and took perseverance. Especially with regards to the data collection, I

had a rough time, however in the end I am very pleased with the results.

Hereby, I would like to take this opportunity for a word of gratitude, as I would like to specially

thank some people for their assistance during the whole process. First of all, I would like to thank my

supervisor Mina Vlachaki, for the useful meetings and for providing me with valuable feedback. Next, I

would like to thank Wouter Becker, my parents, other family members, and friends for their love and

support. In addition, I would like to especially thank my dear friends Maxime Stoopen and Kimberly

Kremer, for their love and support, and for picking me up when I was down.

Eveliene Lips

Tilburg, November 2016

“Strength does not come from physical capacity.

It comes from an indomitable will.”

-Mahatma Gandhi-



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Abstract

The purpose of this study is to connect the topics Corporate Governance and Mergers & Acquisitions

(M&As). As a result of the fact that most M&As end up failing, this study has tried to shed a light into the

problem in order to gain a possible solution. In order to do so, M&A financial performance measured by

Cumulative Abnormal Returns over four event windows, surrounding an M&A announcement, pre-

announcement, and post-announcement, are analyzed for a sample of acquiring Bank Holding Companies

(BHCs) in the United States (US) over the period 2005-2015. It is found that M&A announcements have a

negative impact on the M&A financial performance. Thereafter, this study tests how three corporate

governance mechanisms, board independency, the number of blockholders, and CEO pay-for-performance

relate to M&A financial performance. In addition, it is tested whether these corporate governance

mechanisms have different impact on M&A financial performance, before, during, and after the Global

Financial Crisis. Data for this study has been retrieved from several data sources and contains 138 US based

domestic M&A observations. Based on several regressions over the full sample, empirical evidence is found

for a positive impact of board independency on M&A financial performance. However, having two or more

blockholders is shown to have a negative impact on M&A financial performance for BHCs. Before the

crisis a negative impact of having two or more blockholders, and CEO pay-for-performance is found.

Whereas after the crisis, a negative impact is found for CEO pay for performance, but a positive impact

was found on having two or more blockholders. No empirical evidence is found on the impact of board

independency before and after the crisis.

As a result of this study, new insights have been gained into the research field of corporate

governance and M&A financial performance. In addition, the results serve as a guidance for BHCs to adjust

their corporate governance structure in order to improve their M&A financial performance.

Keywords: Corporate Governance, Mergers & Acquisitions, Bank Holding Companies, M&A, BHC,

Global Financial Crisis, Board Independency, Blockholders, CEO pay-for-performance



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Table of contents

Preface 3

Abstract 4

1. Introduction 7

2. Literature review and hypothesis development 10

2.1 M&A 10

2.1.1 M&A Performance 11

2.2 Corporate Governance 13

2.2.1 Corporate Governance within the US 14

2.2.2 Corporate Governance Mechanisms 14

2.2.2.1 Board independence 16

2.2.2.2 Blockholders 17

2.2.2.3 CEO pay-for-performance 17

2.3 The Global Financial Crisis 18

3. Methodology and data 20

3.1 Data selection and resources 20

3.2 Empirical methodology and variables 22

3.2.1 Dependent variable – M&A performance 22

3.2.2 Independent variables – Corporate governance 25

3.2.2.1 Variable of interest 1: Board independence 26

3.2.2.2 Variable of interest 2: Blockholders 26

3.2.2.3 Variable of interest 3: CEO pay-for-performance 27

3.2.3 Control variables 27

3.2.3.1 Control variable 1: Method of payment 27

3.2.3.2 Control variable 2: Size 28

3.2.3 Regressions 29

3.3 Descriptive statistics 31



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4. Empirical results 34

4.1 Regression results 34

4.1.1 Regression 1: M&A performance 34

4.1.2 Regression 2: Board independency 35

4.1.3 Regression 3: Blockholders 37

4.1.4 Regression 4: CEO pay-for-performance 38

4.1.5 Regression 5: The full model 40

4.2 Regression results – Before, during, and after the Global Financial Crisis 43

4.2.1 The impact of the variables of interest before the crisis 45

4.2.2 The impact of the variables of interest during the crisis 50

4.2.3 The impact of the variables of interest after the crisis 50

5. Conclusion 55

References 59

Appendices 64

Appendix A. Multicollinearity 64

Appendix B. Regression results from the OLS regressions 65



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1. Introduction

In the last decades, a great amount of attention has been paid to Mergers & Acquisitions, not only

from an academic perspective, but also from the business world as well as from the media. The banking

industry provides an interesting setting to analyze the impact of M&As as it has undergone a considerable

consolidation which included a large number of M&As between large banking institutions (Houston &

Ryngaert, 1994). The discussion on why M&As are conducted has generated an extensive amount of

research over the past, and the common motive naturally is that the acquiring firm considers the acquisition

to be a profitable investment, since firms strive for value maximization (Jensen, 1986). Besides organic

growth, a much practiced strategy is growth by acquisitions. Therefore, previous research has aimed to

explain this growth strategy by studying the performance of an M&A. While some studies show a slight

positive value effect, most previous studies report a neutral or even negative effect on the shareholder value

of the acquiring firm (Alexandridis et al., 2010; Hannah & Wolken, 1989; and Houston & Ryngaert, 1994).

This study is in accordance with most of these previous studies, and finds that M&A announcements have

a negative impact on the M&A financial performance for our sample on BHCs in the US over the period

2005-2015. The M&A financial performance will be measured by Cumulative Abnormal Returns (hereafter

called: CARs), which is simply the sum of all abnormal returns over the period of interest (Bodie et al.,

2010). CARs capture the total firm-specific stock movement for an entire period when the market might be

responding to new information. One possible explanation for this negative impact could be the Hubris

Hypothesis of Roll (1986) that shows that bidding firms tend to overpay for their targets as managers can

be too optimistic and overconfident about the prospects of the merged firm. Another explanation for these

value destroying acquisitions can be given by the so-called ‘agency problem’, that is in essence the problem

of separation of ownership and control (Hart, 1995).

Corporate governance is generally described as ‘all activities and processes which ensure that

directors and managers act in the interest of the firm and are accountable for their use of those assets’

(Passenheim, 2009). As it is the system by which firms are directed and controlled, implementing the right

corporate governance mechanisms could help solve the problem regarding the negative impact of M&As

on its financial performance. However, according to Adams and Mehran (2003) there is a systematic

difference between the corporate governance of financial firms and manufacturing firms, thus indicating

that corporate governance structures are industry specific. Therefore, as stated by Cornett et al. (2009)

within the banking industry corporate governance mechanisms are determined to maximize BHCs

performance, by maximizing shareholders wealth.

By looking at past events, an independent observer would argue that the US corporate governance

system is in poor condition. Some well-known failures on corporate board and governance are, amongst



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others: Enron, WorldCom, Tyco, Adelphia, and Global Crossing. As these failures brought concerns on the

US its corporate governance, legislative and regulatory changes were made. This change was the so called

‘Sarbanes-Oxley Act of 2002’ (SOX), in which new corporate governance guidelines from the NYSE and

NASDAQ were discussed (Holmstrom & Kaplan, 2001). The SOX commanded for changes affecting CEO

compensation, shareholder monitoring, and board monitoring. Even though the concept of corporate

governance exists of several components, three will be studied in more detail in this research. The reason

‘board independency’, ‘blockholders’, and ‘CEO pay-for-performance’ have been chosen to investigate is

based on the fact that according to the literature these play an important role. Boards having more

independent board members are arguably in a better position to monitor and control managers, and will

face better stock returns and operating performance (Dunn, 1987; Rosenstein and Wyatt, 1990;

Subrahmanyam et al., 1997). By having blockholders, managers who fail to create shareholder value might

be influenced by for instance a threat of the blockholders to take over the firm or to replace management.

This leads to managers acting in the interest of the shareholders, hence creating shareholder value (Bethel

et al., 1998; Denis & McConnell, 2003). In addition, previous studies have shown that linking CEO pay to

firm performance was key to optimization of shareholder’s wealth (Bruce et al., 2005). As these corporate

governance mechanisms should help to align the interests of the board of directors, the blockholders, and

the CEO with that of the shareholders, one could expect that these mechanisms will positively relate to the

M&A financial performance of BHCs. In order to find support for this expectation the following main

research question has been formulated:

‘Is there a positive relationship between corporate governance mechanisms and M&A financial

performance for BHCs?’

In order to test the main research question, this study looks M&As involving publicly traded BHCs

for the period beginning January 1, 2000 and ending December 31st, 2015. The timeframe is deliberately

chosen due to a lack of available data, and so that possible effects form the Global Financial Crisis could

also be shown in the results. The reason for only testing BHCs from the US can be justified as most available

data has been gathered in the US.

By performing this research, insight will be gained into different ways corporate governance

mechanisms can be set up and designed in order to increase M&A financial performance. These findings

can have general implications for both the academic as well as the corporate world. Some of the findings

of this study are in accordance with previous literature, and empirical evidence is found on the importance

of board independency which has a statistically significant positive impact on M&A financial performance.

Therefore, BHCs for instance might want to rethink the way their board of directors are build up. On the



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other hand, it is found that having two or more blockholders has a negative impact on M&A financial

performance for BHCs. Thus BHCs might want to readjust the allocations of their assets to make sure they

have zero or one blockholder present. Before the crisis a statistically significant negative impact of having

two or more blockholders, and CEO pay-for-performance is found. Whereas after the crisis, a negative

impact is found for CEO pay for performance, but a positive impact was found on having two or more

blockholders. No empirical evidence is found on the impact of board independency before and after the

crisis.

From the academic point of view, the results of this study add new value since new knowledge has

been added in both the research field of corporate governance along with M&A. Furthermore, it adds value

to the research on the possible explanations of and the finding of solutions for the high failure rate of

acquisitions.

The remainder of this thesis is organized as follows. Section 2 discusses the theory on M&A

performance and corporate governance according to a literary review and concludes hypotheses for testing

the main research question. Thereafter, section 3 explains how the data is gathered and develops a

methodology to test the data. Then, section 4 describes the results of the empirical analysis. At last, section

5 will provide a conclusion, discusses limitations of this study and makes suggestions for future research.



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2. Literature review and hypothesis development

The most relevant theories for this study are discussed in this section. It begins by clarifying M&A

and M&A performance. Several measures of M&A performance will be discussed, concluding with the

best fitted measure of M&A performance for conducting the research for this thesis. Hereafter, this chapter

discusses corporate governance and the corporate governance mechanisms used for this study. Finally, it

the Global Financial Crisis is discussed.

2.1 M&A

Whenever two or more firms (and their assets) consolidate it is called an M&A. However, there is

a clear distinction between mergers and acquisitions. Mergers are two or more firms forming a new firm

by combining their resources. Whereas with an acquisition, by offering money or stock, one firm purchases

one or more other firms (Giacomazzi et al., 1997). Hence, since both cases create a ‘new’, both cases will

be studied in this thesis.

The discussion on why M&As are conducted has generated an extensive amount of research over

the past, however the most common motive is basically that the purchasing firm considers the acquisition

to be a profitable investment, since firms strive for value maximization (Jensen, 1986). However, according

to Bower (2001), M&As are not only related to value maximization, as they are also conducted for various

different strategic activities, namely: to deal with overcapacity through consolidation in mature industries,

to roll-up competitors in geographically fragmented industries, to extend into new products or markets, as

a substitute for research and development, or to exploit eroding industry boundaries by inventing an

industry. Other reasons might be related to efficiency gains by creating synergies and economies of scale,

to gain market power, or to remove any agency costs by removing incompetent target management

(Andrade et al., 2001). However, those strategic activities are mostly considered for financial reasons. Thus,

as factors concerning investment decisions also influence M&A activities, M&As can be seen as another

form of investing.

M&As have different parts or so called ‘phases’ in its process. Previous literature shows that there

are several approaches on these phases, as they vary from two to seven phases. Schweiger and Weber (1980)

for example divide the M&A process into the pre-merger and implementation phase. Whereas, Kazemek

and Grauman (1989) identify seven phases, namely: assessment, joint planning, issues analysis, structure

selection, securing approvals, final planning, and implementation. Another example is the approach of Zollo

and Singh (2004), who identified due diligence, negotiation, and integration as the phases of an M&A

process. However, comparing previous literature, the process can be split up into two main phases, namely:

pre-M&A and post-M&A.



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2.1.1 M&A Performance

As written in the English dictionary, performance is the measure of how well a person, machine,

etc. does a piece of work or an activity. When conducting an M&A, the primary purpose is mostly to

improve overall performance (Lubatkin, 1983). Thus, M&A performance stands for the measure of how

well the M&A improved the firm. Hence, M&A performance can be measured in different means. However,

for this study a specific measure of M&A performance needs to be determined to study the result.

According to Zollo and Meier (2008) prior research has shown little or no consensus both across

and within the disciplines on how to measure acquisition performance, as M&A performance is by its nature

an extremely complex concept. They conclude that there is no individual which is suffice to measure M&A

performance. On the contrary, Qui et al. (2014) state that there can be a measure of M&A performance, as

they write that “the performance of M&A hinges not only on macro and micro economic factors like

economic cycles, merger waves, and the potential synergies between acquirers and targets, but also on such

non-economic factors as the personal gains and losses of target and acquirer management teams” (p. 23).

With respect to non-economic factors, there is a considerable amount of empirical literature

concluding that managers conduct bad M&As that destroy shareholder value. For instance, Moeller et al.

(2005) indicate that the merger wave in the late 1990s generated shareholder value destruction in an

enormous scale. In addition, Jensen (1986) show that managers use the firm’s free cash flow, at the expense

of shareholders, to conduct M&As in order to create their own business empire. Moreover, Qui et al. (2014)

show that managers of public takeover targets trade off shareholder value, like premiums, for their own

personal benefits during corporate takeovers. Andrade et al. (2001) show that the acquirer’s announcement

period abnormal returns are on average negative. In addition, Mulherin and Boone (2000) and Bruner (2005)

show, when studying US-based acquirers, negative statistically significant abnormal returns. Also Beitel et

al. (2004) report that most of the US literature shows statistically significant and negative abnormal returns

for the shareholders of acquirers. On the other hand, Bruner (2002) states that M&As do create an increase

in shareholder value, and discusses whether M&A in general pays off. One of his main measurements of

M&A profitability is by looking at reported financial performance. Bruner (2002) concludes that “the

announcement returns on stock for the merging firms is significantly associated with the improvement in

post-merger operating performance, suggesting that anticipated gains drive the share prices at

announcement” (p. 60).

The Hubris Hypothesis of Roll (1986) however states that bidding firms tend to overpay for their

targets, and he discusses several reasons and evidence why those firms tend to overpay. It states that when

there is a premium paid for acquiring a target, the discounted growth opportunities of the target must be

greater than the premium paid in order to generate positive outcomes of the M&A. However, as managers

can be too optimistic and overconfident about the prospects of the merged firm, most firms tend to overpay



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for their targets, and their returns will decline and thus show negative returns for the acquiring firms

compared to the market returns. Most of the previous studies related to the banking industry, and in addition

previous literature for all M&As, confirm this Hubris Hypothesis for the bidding firms in the banking

industry (Alexandridis et al., 2010; Hannah & Wolken, 1989; Houston & Ryngaert, 1994).

This study will focus primarily on the consequences for shareholders, since the board of directors

have a considerable responsibility to their shareholders. It can thus be stated that previous literature with

regards to the banking industry and M&A performance and the value creation for shareholders has shown

no clear consensus. Though, mostly the Hubris Hypothesis by Roll (1986) is found true, in case that the

acquiring firm’s stock returns will be lower than the market’s return.

However, the main idea is that shareholders offer managers a compensation contract which is tied

to the shareholder its wealth changes (Bacidore et al., 1997). Thus, as Blair (1996) confirms, maximization

of the shareholder returns are assumed by the finance model and the market myopia, even though they differ

on how to best attain this objective. As stated by Bodie et al. (2010) “an event study describes a technique

of empirical financial research that enables an observer to assess the impact of a particular event on a firm’s

stock price” (p. 353). By conducting an event study, the abnormal returns to shareholders in the period

surrounding a transaction can be measured (Bruner, 2002). When following Bruner (2002), this study would

measure an M&A its financial performance by abnormal returns as these show whether the market sees the

M&A as value creating since this is simply the raw return less some benchmark of what investors required

that day. However, a concern surrounding event studies using abnormal returns arises from the leakage of

information which occurs when information regarding a relevant event is released before the official public

release (Bodie et al., 2010). This leads to the fact that abnormal returns might be a poor indicator. Thus, as

Bodie et al. (2010) conclude: “A better indicator would be the cumulative abnormal return, which is simply

the sum of all abnormal returns over the period of interest. The cumulative abnormal return thus captures

the total firm-specific stock movement for an entire period when the market might be responding to new

information.” (p. 354). In paragraph 3.1.1 it will be explained how M&A financial performance by the

cumulative abnormal return will be calculated and measured. The benchmark will be the return on a large

market index, namely the Standard & Poor’s 500 index (hereafter named: S&P500). In addition, M&A

performance will be called M&A financial performance from this point on as this study will not calculate

overall performance but the financial aspect of it. In paragraph 3.1.1 the calculations and measurements for

M&A financial performance will be explained.

In conclusion, as summarized by Bruner (2002) previous studies have shown various results on

measuring the significant effect of an M&A announcement on stock returns. Some show that M&As have

positive significant effect on the stock returns of the bidding firm, while others show a negative significant

effect or even no significant effect. With regards to the banking industry, the results are mostly in line with



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the Hubris Hypothesis by Roll (1986), suggesting that the acquiring firm’s stock returns will underperform

compared to the market. Therefore, at first, it needs to be tested by an event study, whether M&A

announcements have a significant negative effect on stock returns of the acquiring BHC; thus, the first

hypothesis of this study will be:

Hypothesis 1: Do M&A announcements have a significant negative effect on the stock returns of the

acquiring BHCs?

2.2 Corporate Governance

In the past, before the 1980s, management was loyal to the firm and there was little reason to focus

on the shareholders. Boards were cozy with management, which weakened board oversight, and managerial

pay was weakly related to stock market performance (Holmstrom & Kaplan, 2001). Over the years the

concept of corporate governance has been widely debated, and changed substantially. Nowadays corporate

governance is generally described as ‘all activities and processes which ensure that directors and managers

act in the interest of the firm and are accountable for their use of those assets’ (Passenheim, 2009). It is the

system by which firms are directed and controlled, concerned with holding the balance between economic

and social goals and between individual and communal goals (Clarke, 2007).

Moreover, corporate governance, which is a subarea in finance, takes into account the question of

how managers can be monitored and motivated best to behave in the best interest of the owners of the firm,

the stockholders (Damodaran, 2014). In most advanced market economies the problem of corporate

governance is reasonably solved, in that they have assured the flows of enormous amounts of capital to

firms, and actual return of profits to the stakeholders (Shleifer & Vishny, 1997). However, this does not

suggest that the problem of corporate governance has been completely solved. Within most firms, including

BHCs, there is a conflict of interest between the shareholders and the managers. For example, managers

may not put in enough effort, having interest in wasteful investments, or use the firm its money for the

wrong purposes. Implementing the right corporate governance mechanisms could help solve the agency

problem, which is in essence the problem of the separation of ownership and control (Hart, 1995). However,

according to Adams and Mehran (2003) there is a systematic difference between the corporate governance

of financial firms and manufacturing firms, thus indicating that corporate governance structures are industry

specific. In addition, Doidge et al. (2007) show that country characteristics are the most important

determinant of a firm its governance. Therefore, this study will only target corporate governance within the

US, which will be discussed in paragraph 2.2.1. Furthermore, there remains a disagreement on how good

or bad existing corporate governance mechanisms are. Hence, as the subject of corporate governance is of

tremendous practical importance, several mechanisms of corporate governance will be addressed in



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paragraph 2.2.2 of this section, concluding with separate paragraphs explaining the best fitted mechanism

of corporate governance for conducting the research done for this thesis.

2.2.1 Corporate Governance within the US

As written before, this study will only focus on M&As and its performance within the US Moreover,

country characteristics influence corporate governance, making it country specific. Therefore, this study

will solely look at corporate governance from the US

Within the US corporate governance changed rather drastically. Evidence showed that the

underlying substance for this change has been that managers have become more focused on stock prices

(Holmstrom & Kaplan, 2001). Looking at past events, an independent observer would think that the US

corporate governance system is in poor condition. Some well-known failures on corporate board and

governance are: Enron, WorldCom, Tyco, Adelphia, and Global Crossing amongst others. These failures

brought concerns on the US its corporate governance, leading to a legislative and regulatory change. This

change was the so called ‘Sarbanes-Oxley Act of 2002’ (hereafter named, SOX), in which new corporate

governance guidelines from the NYSE and NASDAQ were discussed (Holmstrom & Kaplan, 2001). The

SOX commanded for changes affecting CEO compensation, shareholder monitoring, and board monitoring.

It included amongst others provisions with restrictions on insider trading, regulation and enhanced financial

disclosure, as well as provisions focusing on increasing power, responsibility, and independence of the

board of directors (Holmstrom & Kaplan, 2001). This leads to shareholders being able to monitor the board

of directors of the firm more easily, hence this transparency leads to less fraudulent events.

2.2.2 Corporate Governance Mechanisms

Alike the change in concept of corporate governance, the mechanisms have evolved over time.

Jensen (1986) determines corporate governance mechanisms by his free cash flow theory in which he shows

that leveraged buyouts result in corporate governance mechanisms that through improved operating

efficiency reduce agency costs and increase firm value. The mechanisms for corporate governance which

he determines are: debt, ownership of equity, and the presence of active investors. On the other hand, Daily

et al. (2003) consider a board structure, managerial compensation contracts, and ownership concentration

as corporate governance mechanisms to control for the agency problem. Cornett et al. (2009) have another

approach on corporate governance mechanisms, as they define that “a bank’s use of a governance

mechanism is determined by the relative benefits and costs of each as they align the interest of managers

with those of shareholders” (p. 415). They state that it can therefore be concluded that all governance

mechanisms are endogenously determined to maximize BHCs performance, thus maximizing shareholders

wealth. However, as written before, the SOX commanded for changes affecting CEO compensation,



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shareholder monitoring, and board monitoring, therefore this study will focus on corporate governance

mechanisms corresponding to each one of these subjects within corporate governance.

One of the most important elements of corporate governance is the role of outside directors as

monitors of management, as they provide relevant complementary knowledge and carry out tasks that

involve serious problems regarding the separations of ownership and control (Fama & Jensen, 1983).

Empirical evidence on the effect of board composition on firm performance is mixed, however Brickley

and James (1987) find that the number of outside directors is significantly lower on boards of banks that

are located in states that do not allow for M&As. Hence, the proportion of outsiders on a board of directors

plays an important part within M&As and their performance. Therefore, board independence will be the

first corporate governance mechanisms studied in this thesis, and will be described in paragraph 2.2.2.1.

In addition to the board of directors playing an important role in corporate governance, the

blockholders also play a serious role in corporate governance. Blockholders are defined as large

shareholders who at least own 5% of the shares of a firm (Holderness, 2009; Thomsen et al., 2006). One

could assume that their large size in stake gives them great power in the decision-making process of the

firm and stronger motives to ensure shareholder value maximization. However, a main question raised by

prior literature is whether blockholders contribute to the solution of the problem regarding the separation

of ownership and control, or whether they exacerbate rather than solve this problem (Edmans, 2013).

Holderness and Sheehan (1988) find that when majority stocks from blockholders are sold, the stock prices

increase. In addition, Bethel et al. (1998) find that purchasing block shares is associated with improvements

in shareholder value. Hence, previous studies show in some form the positive impact by the presence of

blockholders on general firm performance, as they can use their influence to force management to make

decisions that increase overall shareholder value (Denis & McConnell, 2003). Therefore, it can be

concluded that having blockholders in a firm is of importance in corporate governance, the influence of

blockholders will be the second corporate governance mechanism used in this study, and will be described

in paragraph 2.2.2.2.

Brecht et al. (2003) study several corporate governance mechanisms. They state that the agency

theory defends executive compensation schemes which unrealistically assume that stock prices cannot be

manipulated. However, Nell Minow, a corporate governance expert, explains that options are very

motivational, but firms must be careful with what they are asking managers to motivate1. Hence, it can be

stated that CEOs are driven by both implicit and explicit incentives, and that they are highly concerned

about performance as their pay is linked to performance and it can affect their future career opportunities

(Brecht et al., 2003). In addition, past corporate board and governance failures in the US lead to criticized

1 New York Times, 17 February 2002.



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CEO compensation (Holmstrom & Kaplan, 2001). Therefore, besides board independency and

blockholders, the third corporate governance mechanisms studied in this thesis will be CEO pay-for-

performance, and will be described in paragraph 2.2.2.3.

2.2.2.1 Board independence

Board of directors are not simply a product of regulation, they are also a part of the market solution

to the contracting problems inside most organizations (Hermalin & Weisbach, 2001). Here independent

outsiders usually fulfill the monitoring part of the board. Multiple researchers have different opinions on

whether a board should contain a majority or a minority of outsiders in the board for an organization to

perform best. For instance, the agency theory by Fama and Jensen (1983) suggests that the board is a

monitoring mechanism, as well as its need for potential contributions of inside directors. Adams et al. (2010)

argue that previous studies have examined the overall performance of firms with different kind of boards,

leading to little or no difference in overall performance. However, as this study focusses on financial

performance of the firm, there are several studies looking at the actions of outside directors and which find

that boards dominated by outsiders tend to be more shareholder-friendly than boards dominated by insiders

(Adams et al., 2010). Thus, adopting the point of view for this thesis that boards dominated by independent

outsiders are arguably in a better position to monitor and control managers, and will face better stock returns

and operating performance (Dunn, 1987; Rosenstein and Wyatt, 1990; Subrahmanyam et al., 1997). For

instance, Byrd and Hickman (1992) show that acquiring firms with a board of directors which has more

than 50% independent outsider directors have higher announcement-date abnormal returns in comparison

to other bidders. On the other hand, Yermack (1996) finds no empirical evidence for the relationship

between the percentage of outside directors of a firm and firm performance. Therefore, this study will aim

to find whether the statement made by Byrd and Hickman (1992), Dunn (1987), Rosenstein and Wyatt

(1990) and Subrahmanyam et al. (1997) is true. Therefore, it can be assumed that the higher the number of

independent directors on a board, the more it will offer a higher level of corporate governance to

shareholders. Thus, this study will assume that improving corporate board functioning by a majority of

independent directors should thus yield to positive effects in M&A financial performance measured by

CARs. Hence, leading to the next hypothesis:

Hypothesis 2: Ceteris paribus, do boards with greater oversight, measured by board independence, lead to

better M&A financial performance?



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2.2.2.2 Blockholders

Blockholders, otherwise known as ‘large shareholders’, are shareholders who at least hold 5% of

the firm its shares (Bhagat and Black, 2000; Holderness, 2009). They play a serious role in corporate

governance as the large size of their stakes give them great motives to monitor the managers of the firm

(Edmans, 2013). Thus, blockholders may discipline and influence managers, who fail to create shareholder

value, by for instance threatening to take over the firm or replacing management (Bethel et al., 1998; Denis

& McConnell, 2003). This may lead to improved firm performance as managers may feel pressured and

change their incentives reducing the problem of separation of ownership and control.

Holderness (2009) finds prove that blockholders play an important role in the US, as 96% of all the

firms contains at least one blockholder. Regarding M&As, Shleifer and Vishney (1986) prove that having

blockholders in targeted firms has a positive impact on the occurrence of acquisitions and that it lowers

acquisition premiums. In addition, as mentioned before, Holderness and Sheehan (1988) as well as Bethel

et al. (1998) all conclude that the selling and purchasing of blockholders improve stock prices and increase

shareholder value. Therefore, as past studies show the importance of blockholders within corporate

governance and have found a positive relation between the number of blockholders and firm performance,

a comparable influence might be found on the firm its M&A financial performance measured by CARs.

Hence, the following hypothesis has been formulated:

Hypothesis 3: Ceteris paribus, more blockholders within BHCs will lead to better M&A financial

performance?

2.2.2.3 CEO pay-for-performance

CEO pay-for-performance is, like the expression is saying, the salary or compensation paid to the

CEO based on how well one works. The pay-for-performance sensitivity and shareholders wealth

maximization is a well-documented subject in the financial literature. Earlier researches have shown that

there has been considerable disagreement about whether the structure of CEO compensation is designed so

that executive decision making is directed toward maximizing firm performance (Tosi & Gomez-Mejia,

1989). One of the main challenges in executive compensation is to make sure that CEO, amongst all other

executives, acts in the best interest of the firm’s shareholders and to erase the incentives not to act in the

utmost interest of the shareholders (Geiler & Renneboog, 2010). Jensen and Murphy (1990) state that in

order to encourage CEO’s to maximize shareholders wealth, boards should create compensation contracts

that are performance or stock price oriented. Abowd (1990) finds that CEO payment of an incremental raise

of 10% due to a good stock market performance leads to a 400 to 1200 basis point increase in expected

total shareholder return. As argued before, it can be stated that CEOs are driven by both implicit and explicit



18

incentives, and that they are highly concerned about performance as their pay is linked to performance and

it can affect their future career opportunities (Brecht et al., 2003).

CEO compensation consists usually of both short-term and long-term components of compensation,

where short-term includes base salary and annual bonuses, and long-term includes stock options and

restricted stock. CEOs are being rewarded by using equity-based compensation more often, known as long-

term incentive schemes (Datta et al., 2001). Equity-based compensation is defined as the options and

restricted stock that a CEO commonly receives as part of their compensation (Bebchuk & Grinstein, 2005).

In prior research shows that linking CEO pay to firm performance was key to optimizing shareholder’s

wealth (Bruce et al., 2005). Thus, rewarding a CEO with stocks and options is a way to let them act in the

best interest of the firm’s shareholders as you connect the CEOs personal wealth with the performance of

the firm. Therefore, this study will try to find whether higher levels of CEO pay-for-performance,

determined by equity based compensation, will have a positive effect on BHCs M&A financial performance

measured by CARs, leading to the next hypothesis:

Hypothesis 4: Ceteris paribus, do BHCs with higher levels of CEO pay-for-performance lead to better

M&A financial performance?

2.3 The Global Financial Crisis

The Global Financial Crisis was a situation in which the value of financial institutions or assets

dropped rapidly, and is most often associated with a panic or a run on the banks, in which investors sold of

their assets or withdrew money from their savings accounts with the expectation that the value of those

assets would drop if they remained at the financial institution2. It started with the subprime mortgage crisis,

which reached a critical stage within the first week of September 2008, due to the bankruptcy of Lehman

Brothers. Now the financial crisis entered an acute phase marked by failures of prominent US banks and

European banks, and it became the worst economic disaster since the Great Depression of 1929. As the

crisis now developed, stock markets fell worldwide, and financial regulators attempted to coordinate efforts

to contain the crisis. As noted, various studies give different definitions of a crisis, with different time

periods. According to Frankel and Saravelos (2012) the Global Financial Crisis lasted from September 2008

to March 2009. As the falling of Lehman Brothers was due to September 2008 and was marked the

beginning of the acute phase of the financial crisis, the time period for the crisis indicated by Frankel and

Saravelos (2012) is used for indicating the financial crisis within this study. However, as they point out in

their research that this is rather a tight period, the period indicated for the Global Financial Crisis this

2 Definition retrieved from: http://www.investopedia.com/terms/f/financial-crisis.asp



19

research will be from July 2008 to July 2009. Erkens et al. (2012) shows that stock returns were negative

during the crisis, and that firms with greater external monitoring by for instance higher institutional

ownership, block holdings, and more independent boards had worse stock returns than other firms during

the crisis.

The Global Financial Crisis was changing the scenery for M&As and identified new M&A targets

that showed a shift with significant impact to our global business practices. The M&A wave which had

built up since 2002 went over, as the number of deals declined substantially since 2007 (Ravichandran,

2009). According to Ravichandran (2009), as the recent financial crisis, the financial markets were being

exposed to a volatile and uncertain environment, and markets moved into a vicious cycle of assets

deleveraging, price drops, and investor redemptions. The National Commission on the Causes of the

Financial and Economic Crisis in the US declared in their report ‘Final Report of the National Commission

on the Causes of the Financial and Economic Crisis in the United States, 2011’ that the key cause of the

crisis were the dramatic failures of corporate governance at many important financial institutions (Beltratti

& Stulz, 2012). Thus, one would expect that BHCs with better governance performed better during the

crisis. As discussed before, boards with higher independence, firms with greater amount of blockholders,

and a CEO with a higher pay-for-performance ratio are proxies for good corporate governance. However,

for instance Beltratti and Stulz (2012) find that shareholder-friendly-boards created more value for

shareholders before the crisis, but during the crisis these were associated with poor outcomes. Thus, finding

no support for analyses that attribute an important role to governance in the crisis, since banks with more

shareholder-friendly boards generally performed worse during the crisis. In addition, Ang and Mauck (2011)

who make a distinction between distressed and non-distressed targets, show empirically that acquirers do

not benefit from the acquisition of distressed firms in a crisis, due to significantly negative short term returns.

But, Beltratti and Stulz (2009) find that there is no evidence that banks with better corporate governance

perform better during the crisis, in contrast they find that banks with more shareholder-friendly boards

performed worse during the crisis. In addition, Fahlenbrach and Stulz (2011) find evidence that banks did

not perform better during the crisis if the CEO had better incentives aligned with those of the shareholders.

Thus, rewarding the CEO with equity based compensation to let them act in the interest of the firm’s

shareholders did not result in higher returns of the firms during the crisis.

This study tests whether M&As of US BHCs have an impact on the firm’s financial performance,

and if there are corporate governance mechanisms that improve the firm’s financial performance in case of

an M&A. Hence, since the sample incorporate the Global financial Crisis, and no previous literature is

found on the effect of the Global Financial Crisis on M&A financial performance of specifically US BHCs,

and the influence of the corporate governance mechanisms chosen for this study, all hypothesis (1 to 4) will

be tested before, during, and after the Global Financial Crisis.



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3. Methodology and data

At first this section shows how the data used for this study is gathered. Thereafter, the

methodological model that is used in this study will be described. Moreover, it will discuss how the

dependent and independent variables will be measured. At last, it will discuss why and how there will be

made use of control variables.

3.1 Data selection and resources

To start gathering data a sample period is set, which consists of M&As involving publicly traded

BHCs for the period beginning January 1, 2000 and ending December 31st, 2015. The timeframe is

deliberately chosen so that possible effects form the Global Financial Crisis could also be shown in the

results. According to Frankel and Saravelos (2012) the Global Financial Crisis lasted from September 2008

to March 2009. However, as they indicate in their research that this is rather a tight period, the period

indicated for the Global Financial Crisis this research will be from the 1st of July 2008 to the 31st of July

2009.

The dependent variable of this study is M&A financial performance, which is measured by CARs

on the shares of the acquiring firm of the M&A. The data used for indicating M&As within this study is

retrieved from the ‘Thomson One Banker’ (also called: TOB) database. As this study is specified on certain

firms and variables, and to be able to generate CARs surrounding M&A announcements, data gathered

needed to meet the following selection criteria:

(I) The M&A must have taken place between 01/01/2000 and 12/31/2015;

(II) Only M&As from BHCs (specified by SIC 6000, 6081, 6029, 6082, 6021, 6712, 6022) are

included, no other industries will be tested;

(III) The acquiring BHC as well as the target BHC must be located in the US;

(IV) Both the acquirer and the target BHCs must be publicly listed;

(V) Only M&As which were completed are allowed in the dataset;

(VI) The percentage of shares owned by the acquirer after the transaction must be equal to or higher

than 51.



21

Table I: Session details Thomson Reuters Database (retrieved on: 10/11/2016)

Request Hits Request Description

0 - DATABASES: Domestic Mergers, 1979-Present (MA, OMA)

1 - Date Announced: 01/01/2000 to 12/31/2015 (Custom) (Calendar)

2 6790 Target All SIC : 6000, 6081, 6029, 6082, 6021, 6712, 6022

3 5704 Acquiror All SIC : 6000, 6081, 6029, 6082, 6021, 6712, 6022

4 2887 Target Public Status : P

5 2711 Acquiror Public Status : P

6 2711 Target Nation : US

7 2681 Acquiror Nation : US

8 818 Deal Attitude : F, H, N

9 753 Deal Status : C

10 747 Percent of Shares Owned after Transaction: 51 to <= HI

From the Thomson Reuters database 747 observations are gathered. In table I the amount of hits

after each criteria is shown. In this study, in contrast to prior research, there is no limit regarding the

transaction value considered to minimize losing observations. For measuring the M&A financial

performance by CARs, stock prices (P) for every acquiring firm are retrieved from Datastream. However

in order to do so, CUSIP codes from Thomson Reuters had to be converted in ISIN codes by Datastream,

which causes missing observations. In addition, the equally weighted total return index for the S&P500 is

retrieved.

Besides using the Thomson One Banker database for retrieving all data regarding the dependent

variable used for this study, other databases are used to retrieve data regarding the variables of interest and

the control variables. Data regarding the number of directors as well as their individual role name, for

indicating whether a director is independent or not, are retrieved from BoardEx. Orbis is used to retrieve

(by hand) data concerning the number of blockholders per acquiring firm. In addition, Execucomp is used

for gathering data on CEO compensation. At last, for retrieving data on the control variables, Thomson

Reuters was again used for gathering data on the method of payment for each observation, and Compustat

is used to gather data on the total assets per acquiring firm.

When gathering all data, missing observations occur for the dependent variable, as well as for the

variables of interest and the control variables. Therefore, the final sample consists of 138 observations with

which the hypotheses of this study will be tested. When an M&A announcement took place during a non-

trading day (weekend), the closest trading day will become the event date.



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3.2 Empirical methodology and variables

For conducting this study, and to give answer to the hypotheses mentioned in section 2, certain

variables are used. The following paragraphs present the methodological model used, and discuss the

variables. Moreover, it shows how certain variables are calculated and measured. At first, the dependent

variable is explained, followed by the independent variables. Thereafter, the control variables are addressed.

3.2.1 Dependent variable – M&A performance

The dependent variable in this study is M&A performance. There are many potential methods that

can be used for measuring M&A performance. As Puffer and Weintrop (1991) state, a positive abnormal

return means that the performance of the firm exceeds the market its expectations, and a negative abnormal

return indicates that the performance of the firm fails to meet the expectations of the market. Thus, a positive

abnormal return would indicate a successful M&A, and a negative abnormal return would indicate an

unsuccessful M&A. Therefore, as an indicator of M&A financial performance, the positive or negative sign

of the abnormal return from the stock market can be used. However, as discussed in section 2, there are

concerns surrounding the leakage of information, which can cause that a small group of investors will

perceive information before the official public release. Bodie et al. (2010) therefore come up with a better

indicator for measuring the impact of an event, namely: CAR. Therefore, this study will measure M&A

performance by the CAR, also following prior research by amongst others: Reinganum (1985), Puffer and

Weintrop (1991), Hayward and Hambrick (1997). These researchers find that CARs are a proper measure

for M&A performance, as it reflects on whether the performance exceeds or fails to meet the market its

expectations.

As Bodie et al. (2010) write that empirical financial research with respect to impact on a firm’s

stock price must be done by conducting an event study, this type of study will be used for this research.

However, to get to the final measure of M&A financial performance by the ‘event study’ method some

steps need to be made with the data as described in paragraph 3.1. As previously written, an event study

examines the abnormal returns to shareholders in the period surrounding the announcement of a transaction

(Bruner, 2002). The announcement date of an M&A will be used instead of the effective date, as the

announcement is the moment when information about the event becomes publicly known. Thus, the

reaction of the stock market can be captured more precisely, which is in accordance with the Efficient

Market Hypothesis (hereafter named: EMH) (Bodie et al., 2010). The EMH embraces three forms of

information efficiency. The first one is the weak form of information efficiency, in which the hypothesis

claims that all past publicly information is known to everybody and is transferred into the stock price of the

firm. The second one is the semi-strong form of information efficiency, which is similar to the weak form

in which all past publicly information is known to everybody and is transferred into the stock price of the



23

firm. However, this semi-strong form of information efficiency adds that the stock price will instantly

change to reflect new public information, which in case of this study is the M&A announcement. The third

form of the EMH is the strong form of information efficiency in which all of the information available is

immediately being transferred into the stock price of a firm. Thus, also the so called ‘insider information’

influences stock prices in the strong form of the EMH. Bodie et al. (2010) show that at the day of the

announcement, called day 0, the CAR for a sample of takeover candidates increases substantially, thus

representing a large and positive abnormal return on the announcement date. However, directly after the

announcement date there are no longer significant increases or decreases in the CAR. Therefore, it could

be stated that once new information becomes public stock prices will react to the news. Thus, the event

study naturally arises from the semi-strong form of information efficiency explained by the EMH, as stock

prices change in response to new (unpredictable) information.

In order to detect whether an M&A announcement has statistically significant impact on stock

prices, the event study methodology is performed. The idea of this methodology is to check whether stock

returns significantly outperform and/or underperform vis-à-vis market returns around the announcement

date. Thus, to conduct this event study, the announcement date, share prices and a market index are required.

First, the returns are generated from the stock prices for all acquiring BHCs that conducted an

M&A. The returns used for this study are log-returns which are considered to deal with the problem of

outliers (Fergusson & Platten, 2006). By using the following equation (1) the logarithmic returns are

calculated:

𝑅𝑒𝑡𝑢𝑟𝑛𝑖,𝑡 = ln(𝑃𝑖,𝑡+1

𝑃𝑖,𝑡) (2)

Where:

- i = a stock or market

- P = the price of a stock or market

- t = a day

Next, an estimation window on which the expected average return can be calculated must be

specified. In the estimation window, by employing the market model regression, the beta of each stock is

estimated, which captures the relationship between the stock ‘i’ and the market index. Aktas et al. (2007)

test multiple estimation windows, and show that regardless of the length of the estimation window, they get

similar abnormal returns on the event day. Thus, following Aktas et al. (2007) and Liargovas and Repousis

(2011) the estimation window for this study contains 100 trading days. In order to observe abnormal stock

price movements, we are interested in the so called ‘event window’. For this study multiple event windows

are tested as we are interested in the pre-announcement returns ([-5,0]), the post-announcement returns

([0,5]), and returns surrounding the announcement date ([-10,10], and [-1,1]), which is consistent with the



24

literature. [t1, t2] represents the time interval, beginning at t1 days before the event date, and ending at t2

days past the event date. The event window may contain information leakage prior to the announcement

(Liargovas & Repousis, 2011). Therefore, to exclude the impact of the possible leakage of information on

the announcement, the interval for the estimation window ends 30 trading days prior to the announcement.

In figure 1, the timeline around an event is shown.

Figure 1. Timeline around an event.

Where, T1 is 130 trading days before the event, T2 is 30 trading days before the event, t1 is 10, 5, 2 or 1 trading day(s) prior to the

event, t2 is 10, 5, 2 or 1 trading day(s) after to the event, and t0 is the event which is the M&A announcement date.

Before defining what abnormal returns are, the normal return has to be defined. For calculating the

normal return, the S&P 500 equally weighted index returns (excluding dividends) are gathered from CRSP,

and used for calculating the expected average return. By using the estimated beta and the market index

returns the normal return will be calculated by following equation (2):

𝑁𝑅𝑖,𝑡 = 𝛼𝑖 +𝛽𝑖𝑅𝑚,𝑡 +𝜀𝑖,𝑡 (2)

Where:

- 𝑁𝑅𝑖,𝑡 = The expected normal return on security i over period t;

- 𝛼𝑖 = The security its average return in a period with zero market return;

- 𝛽𝑖𝑅𝑚,𝑡 = The co-movement with the market, with 𝛽𝑖 being the measure of sensitivity to the market return

on security i, and 𝑅𝑚,𝑡 being the market’s rate of return on the equally weighted market index over period t;

- 𝜀𝑖,𝑡 = The error term of firm i over period t, which is assumed to be zero.



25

Hereafter, for each day in the event window, the difference between the realize returns and the

expected normal returns need to be calculated. The equation (3) used for calculating the abnormal returns

is:

𝐴𝑅𝑖,𝑡 = 𝑅𝑖,𝑡 −𝑁𝑅𝑖,𝑡 (3)

Where:

- 𝐴𝑅𝑖,𝑡 = The abnormal return on security i over period t;

- 𝑅𝑖,𝑡 = The return on security i over period t;

- 𝑁𝑅𝑖,𝑡 = The expected normal return on security i over period t as calculated above.

Next, the cumulative abnormal returns must be calculated. CAR is simply the sum of all abnormal

returns over the event window, and can be measured as represented in equation (4):

𝐶𝐴𝑅𝑖,𝑡1,𝑡2 = ∑ 𝐴𝑅𝑖,𝑡𝑡2𝑡=𝑡1

(4)

Where:

- 𝐶𝐴𝑅𝑖,𝑡1,𝑡2 = The cumulative abnormal return of firm i over period 𝑡1 till 𝑡2;

- 𝑡1 = The first day of the event window;

- 𝑡2 = The last day of the event window.

In conclusion, all these steps are made with the purpose of creating the dependent variable, M&A

financial performance, for this study. By creating this variable, it is checked whether M&As have a

significant effect on the stock returns of the acquiring BHCs. However, when running the t-test it must be

noticed that this provided non-robust standard errors. Therefore, 𝐶𝐴𝑅𝑖,𝑡1,𝑡2 must be regressed by the so

called ‘robust’ command in Stata as robust standard errors increase the reliability of the results3. It therefore

tests hypothesis 1, and is also used for testing hypothesis 2 to 4.

3.2.2 Independent variables – Corporate governance

The main variable of interest, also called the independent variable, of my study is corporate

governance. As described in paragraph 2.2.2., this study makes use of three governance mechanisms for

corporate governance. The next independent variables will thus be used in this study: board independence,

blockholders, and CEO’s pay-for-performance. In the next paragraphs these corporate governance

mechanisms will separately be explained.

3 Information by Princeton University Library. For more details, please see:

http://dss.princeton.edu/online_help/stats_packages/stata/eventstudy.html



26

3.2.2.1 Variable of interest 1: Board independence

The first variable of interest is board independence. Boards with over 50% of independent outsiders

are assumed to be able to monitor and control managers, which can lead to better stock returns and operating

profit (Byrd & Hickman, 1992). In this study it is tested whether higher levels of board independency will

lead to higher M&A financial performance. Therefore, a relative level of board independency must be

generated for each observation. Hence, this study will look at the fraction of independent directors relative

to total number of directors on the board, which is generally known as board size. In this thesis it is tested

whether boards with greater board independence have a positive impact on M&A financial performance,

and board independence will be measured by the following equation (5)4:

𝐵𝑜𝑎𝑟𝑑𝐼𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑒 = (𝑁𝑢𝑚𝑏𝑒𝑟𝑜𝑓𝑖𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡𝑑𝑖𝑟𝑒𝑐𝑡𝑜𝑟𝑠𝑜𝑛𝑡ℎ𝑒𝑏𝑜𝑎𝑟𝑑

𝐵𝑜𝑎𝑟𝑑𝑠𝑖𝑧𝑒) (5)

3.2.2.2 Variable of interest 2: Blockholders

The second corporate governance mechanism used in this study is the number of blockholders. As

previously described a blockholder can be defined as a large shareholder and an entity which holds at least

5% of the shares of a firm (Bhagat and Black, 2000; Holderness, 2009). This definition will be applied in

this study, and can be found in equation (6)5. To measure the effect of the number of blockholders on M&A

financial performance, a categorical variable is created for indicating the number of blockholders present

within each firm. The categorical variables are specified into two categories, which can be found in table

II. The dummy variable is created in which the value of ‘1’ indicates there are 2 or more blockholders

present in the acquiring BHC, and the value ‘0’ indicates that there are 0 or is 1 blockholder present in the

acquiring BHC.

𝐵𝑙𝑜𝑐𝑘ℎ𝑜𝑙𝑑𝑒𝑟𝑠 =≥ 5%ofsharesofafirm (6)

Table II. The overview of independent variable 2, the number of blockholders, as a categorical variable

Categorical variable Number of blockholders

0 ≤ 1 blockholders

1 ≥ 2 blockholders

4 Byrd and Hickman (1992) use the percentage of independent directors of board size. 5 Holderness (2009) defines blockholders as large shareholders who hold at least 5% of the shares of a firm. Therefore, equation

5 is created to show in a proper way how these blockholders are counted for in this study.



27

3.2.2.3 Variable of interest 3: CEO pay-for-performance

The third independent variable in this study to measure corporate governance is CEO pay-for-

performance. As written in section 2, previous literature suggests that CEOs are driven by both implicit and

explicit incentives, which makes them highly concerned about the firm’s performance as it is linked to their

pay (Brecht et al., 2003). To enhance shareholders wealth maximization a CEO needs to be encouraged to

perform in favor of the shareholders. This encouragement can be provided by equity-based compensation,

also known as the long-term incentive schemes (Datta et al., 2001). Thus, by rewarding a CEO with

restricted stock and stock options, otherwise known as equity-based compensation, they will be encouraged

to act in the best interest of the firm’s shareholders. This study will try to find whether higher levels of CEO

pay-for-performance, indicated by equity-based compensation, lead to better M&A financial performance.

Therefore, a relative level of CEO pay-for-performance must be generated for each observation. As

restricted stock and stock options are factors from total compensation which encourage a CEO to act in the

interest of the firm’s shareholders, this study will look at the fraction of a CEO its equity-based

compensation relative to total compensation. This is measured by the following equation (7)6:

𝐶𝐸𝑂𝑝𝑎𝑦 − 𝑓𝑜𝑟 − 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 =(𝑇𝑜𝑡𝑎𝑙𝑠𝑡𝑜𝑐𝑘𝑎𝑤𝑎𝑟𝑑𝑠+𝑡𝑜𝑡𝑎𝑙𝑜𝑝𝑡𝑖𝑜𝑛𝑎𝑤𝑎𝑟𝑑𝑠)

𝑇𝑜𝑡𝑎𝑙𝑐𝑜𝑚𝑝𝑒𝑛𝑠𝑎𝑡𝑖𝑜𝑛7 (7)

3.2.3 Control variables

Not only the variables mentioned above are determinants of the dependent variable; other variables

may also affect M&A financial performance. In testing the relationship between BHC’s M&A performance

and corporate governance, there must be control for factors which have been known to influence the market

reaction to BHCs mergers and acquisitions. Previous research shows two variables that affect M&A

financial performance measured by CARs. Therefore, I will make use of control variables that are

empirically proven have a significant effect on M&A financial performance. Though, not all variables on

which empirical evidence is found for having an effect on M&A financial performance are used since not

all were relevant. For instance, industry can be controlled for (Markides & Ittner, 1994); however, for this

study only the financial industry was tested. Therefore, the following control variables described in 3.2.3.1

and 3.2.3.2 are captured within the regressions of this study in order to get better empirical results.

3.2.3.1 Control variable 1: Method of payment

How a firm finances an M&A varies; they can be financed by all-cash bids, all-stock bids or a

combination of the two (Hayward & Hambrick, 1997). Moeller et al. (2004) show that acquisitions of public

6 Bebchuk and Grinstein (2005) use equity-based compensation as a percentage of total compensation. 7 Total compensation = (Salary + Bonus + Other Annual + Restricted Stock Grants + LTIP + Payouts + All Other + Value of

Option Grants) as defined by Bebchuk and Grinstein (2005).



28

firms which are paid for with cash only have significant positive abnormal returns. However, they find that

whenever an acquisition of public firms is paid for with equity, smaller firms gain significantly on the

announcement date. With regards to corporate governance, a payment in cash only is used when acquiring

managers have large ownership and highly value firm’s control (Amihud et al., 1990). In addition, the use

of cash may discourage competing offers for the target firm by other firms (Beltratti & Paladino, 2013).

Researchers as for instance, Mitchell and Stafford (2000), find that M&As show significant negative returns

in the long-run due to the fact that they were completely financed by stock. Thus, it can be concluded that

a clear distinction must be made between M&As financed by cash only and alternative forms of payment.

The data contains the following sorts of the so called ‘final consideration structure’: cash and stock

combination, stock only, unknown, cash only, choice between cash or stock or combination of both, other,

and choice between types of shares/stocks. However, in for this study, a distinction is made between two

different sorts of payment, hence a dummy variable is created in which the value of ‘1’ indicates that the

M&A was financed by only cash, and the value ‘0’ indicates all substitute methods of financing. These

dummy variables are shown in table III:

Table III. The overview of control variable 3, method of payment, as a dummy variable

Dummy variable Method of payment

1 M&A financed by cash-only

0 M&A financed by all other methods

3.2.3.2 Control variable 2: Size

Organizational size plays a very important role in M&A. Previous research indicates that between

the firms that are merging or acquiring the relative organizational size plays a very important role in

choosing the right partner to merge with or to acquire. Moeller et al. (2004) have found empirical evidence

that whenever firms buys other firms which are smaller it can result in sub-optimal outcomes, and buying

firms which are larger can result in underperformance, this can be due to ignorance or too much attention.

However, a more recent study by Tuch and O’Sullivan (2007) shows that smaller firms taking over larger

firms tend to have better post-M&A performance.

On the other hand, a BHC its size may play a role in the level of discretionary behavior of

management. Masulis et al. (2007) argue that a large firm its size may serve as a quite effective takeover

defense as it takes more resources to acquire a large firm, leading to managers of larger firms being more

entrenched and more likely to make value-decreasing acquisitions.

As Moeller et al. (2004) write: “We find that the size effect is robust. It holds (1) in the 1980s as

well as in the 1990s, (2) across subsamples of acquisitions constructed based on the form of payment or the



29

organizational form of the assets acquired, and (3) in regressions that control for firms and deal

characteristics.” (p. 226). Therefore, as there is empirical evidence that size has an effect on stock return,

to conduct this study, the control variable size (SI) will be measured by taking the log transformation of the

total assets of the firm, as shown in equation (8)8:

𝐹𝑖𝑟𝑚𝑆𝑖𝑧𝑒 = 𝐿𝑜𝑔(𝑡𝑜𝑡𝑎𝑙𝑎𝑠𝑠𝑒𝑡𝑠) (8)

3.2.3 Regressions

To test the first hypothesis of this study, an event study was conducted as described in paragraph

3.2.1. In order to test whether the corporate governance mechanisms used in this study have an impact on

the M&A financial performance of the BHCs, panel data is used. When testing the linear relationship

between our dependent variable and the variables of interest, for panel data the linear model in equations

(9) can be used for conducting the OLS regression:

𝑀𝐴𝑓𝑝𝑖,𝑡 = 𝛽0 +𝑥′𝑖,𝑡 𝛽 +𝑐′𝑖,𝑡 𝛾 +𝜀𝑖,𝑡 (9)

Where:

- 𝑀𝐴𝑓𝑝𝑖,𝑡 = M&A financial performance

- 𝑥′𝑖,𝑡 = The variable(s) of interest

- 𝑐′𝑖,𝑡 = A vector of control variables

Nevertheless, in our case the OLS regressions gives us rather low r-square values when testing the

effect of the variables of interest on the dependent variable (the results from the OLS regression can be

found in Appendix B, tables XXI – XXIV). Bao and Edmans (2011) state that M&A returns start from a

“clean slate” every time the starting point is zero instead of the return of the last M&A deal. They find that

M&A returns are notoriously noisy as they reflect the market’s reaction instead of a variable controlled by

management. In addition, they find that previous studies of M&A returns find low r-square values, which

imply that M&A returns are difficult to explain. However, as an extensive list of a combination of factors

is not able to explain the widespread variation in acquirer returns in a systematic way, then what does?

Golubov et al. (2015) find an answer to this problem, as they show that acquirer returns are best explained

by an unobserved, time-invariant, firm specific factor. They explore the fixed effects in acquirer returns,

and suggest that takeover gains are characterized by significant firm-level persistence. In this study, the

covariance between the variables of interest and controls is not zero, which will lead to the standard

endogeneity problem and to biased OLS estimates and leaves us with two remaining techniques to analyze

8 Masulis et al. (2007) uses the logarithm of the acquirer’s total assets in their empirical tests and report a significant coefficient.



30

our panel data; by fixed effects or random effects. By conducting a so called ‘Hausman specification test’,

it is shown that a random-effects model is resoundingly rejected, and thus the fixed effect model is used.

The fixed effects estimator allows us to control for variables you cannot observe or measure like cultural

factors or difference in business practices across firms; or variables that do not change across entities but

do change over time (i.e. national policies, federal regulations, international agreements, etc.). Thus, it

accounts for individual heterogeneity. The fixed effect model explores the relationship between the

variables of interest and the dependent variable within a firm. Each firm has its own individual

characteristics that may or may not influence the variables of interest. When using the fixed effects model,

it is assumed that something within the individual firm may impact or bias the variables of interest or the

dependent variable, and this needs to be controlled for. This is the rationale behind the assumption of the

correlation between firm’s error term and variables of interest. The fixed effect model removes the effect

of those time-invariant characteristics so the net effect of the variables of interest on the dependent variable

can be assessed. For this study, the firm fixed effect is used, as Golubov et al. (2015) prove that acquirer

returns are best explained by an unobserved, time-invariant, firm specific factor. The regressions with fixed

effects shows a highly statistically significant F-test in all cases, thus confirming that this model is

appropriate to use considering that all the coefficients in the model are different from zero. Moreover, a LR

test was conducted to test for heteroscedasticity, which is present. Thus, the standard errors must be

clustered by BHC to relax the assumption of homoscedasticity within each cluster, providing us with robust

standard errors. As mentioned before, the robust standard errors increase the reliability of the results. In

conclusion, the following equations (10-13) will be tested, for which the results will be shown in paragraph

4.1.1 to 4.1.5:

𝑀𝐴𝑓𝑝𝑖,𝑡 =𝛼𝑖 +𝛽𝐵𝐼𝑖,𝑡 +𝑐′𝑖,𝑡𝛾 +𝜀𝑖,𝑡 (10)

Where:


- 𝐵𝐼𝑖,𝑡 = Board independency


- 𝛼𝑖 = Firm FE

𝑀𝐴𝑓𝑝𝑖,𝑡 =𝛼𝑖 +𝛽𝐵𝐻𝑖,𝑡 +𝑐′𝑖,𝑡𝛾 +𝜀𝑖,𝑡 (11)

Where:


- 𝐵𝐻𝑖,𝑡 = Blockholders





31

𝑀𝐴𝑓𝑝𝑖,𝑡 = 𝛼𝑖 +𝛽𝑃𝑃𝑖,𝑡 + 𝑐′𝑖,𝑡𝛾 +𝜀𝑖,𝑡 (12)

Where:


- 𝑃𝑃𝑖,𝑡 = Pay for performance



𝑀𝐴𝑓𝑝𝑖,𝑡 = 𝛼𝑖 +𝛽1𝐵𝐼𝑖,𝑡 +𝛽2𝐵𝐻𝑖,𝑡 + 𝛽3𝑃𝑃𝑖,𝑡 + 𝑐′𝑖,𝑡 𝛾 +𝜀𝑖,𝑡 (13)

Where:


- 𝐵𝐼𝑖,𝑡 = Board independency

- 𝐵𝐻𝑖,𝑡 = Blockholders

- 𝑃𝑃𝑖,𝑡 = Pay for performance



3.3 Descriptive statistics

As explained previously, this study has been using event studies to generate the dependent variable

‘M&A financial performance’ of this study, measured by CARs on stock price of each BHC surrounding

an M&A announcement. Although the main event window of this study is [-10,10], multiple other event

windows have been tested in order to check differences. The other events that were chosen to represent in

the results are [-1,1] to show the effect closely surrounding the M&A announcement, [-5,0] to show the

effect pre-announcement, and [0, 5] to show the effect post-announcement. The descriptive statistics on the

dependent variable of this study with the above mentioned windows are shown in Table IV. This table

shows a summary of the acquiring BHC’s CARs per event window tested for M&A announcements. The

table reports the mean, standard deviation, minimum value and maximum value of the CARs per event

window. It shows that the CARs of the M&A deals are on average negative pre-announcement and

surrounding the announcement. This is not in line with prior research by Moeller et al. (2005) which show

that from 1980 through 2001 CARs are positive for the acquiring firm with an event window surrounding

the announcement. On the other hand, Andrade et al. (2001) as well as Mulherin and Boone (2000) show

that the announcement period abnormal returns for the acquirer are negative. Bruner (2002) summarizes

multiple studies showing positive and negative CARs over various event windows in different time periods,

some of them in line with the results of table IV, some of them not in line with those results. Looking at the

CARs of the post-announcement event window, this would be in line with some of the results Bruner (2002)



32

is showing. Next to that, when looking at the [-10,10] event window’s one notices relatively a large

minimum and maximum, indicating a rather extreme reaction of the market surrounding some M&A

announcements. For the other event windows, these reactions are quite modest.

Table IV. Descriptive Statistics of the Cumulative Abnormal Returns to acquiring firm shareholders

This table shows the descriptive statistics of the Cumulative Abnormal Returns over an estimation window of 100 trading days

starting at -30 trading days prior to the announcement (at t=0) with event windows pre-announcement [-5,0], post-announcement

[0,-5], and surrounding the announcement [-10,10] and [-1,1]. The sample consisted of 138 domestic M&A deals done by BHCs

within the US which took place during the period 2005 until 2015.

Acquirer CARs, based on an estimation window of 100 trading days

Event window Mean Std. Dev. Min Max N

[-10,10] -.000931 .097436 -.402569 .671405 2898

[-5,0] -.009071 .046262 -.155933 .251193 828

[-1,1] -.003872 .034355 -.099998 .132789 414

[0, 5] .003652 .043131 -.144502 .254205 828

Table V provides the descriptive statistics of the variables of interest and the control variables. The

table reports the mean, standard deviation, minimum value and maximum value per variable. For each

variable there are 138 observations, which corresponds to the number of M&A announcements this study

tests. All M&A announcements with a missing observation in one of the variables of interest or the control

variables was dropped from the sample. When looking at board independency, one could state that on

average boards have 81% independent board members, with a minimum of about 59% independent

directors on the board and a maximum of about 94% independent directors on the board. According to Byrd

and Hickman (1992), boards with over 50% of independent outsiders are assumed to be able to monitor and

control managers, which can lead to better stock returns. As the minimum of all observations on board

independency is above 50%, the regression that will be tested later on is assumed to show a positive impact

of board independency on M&A financial performance. However, for this research, it is studied whether a

higher percentage of board independency will lead to better M&A financial performance. For the variable

of interest ‘blockholders’ the average is 51%, indicating that there are slightly more BHCs with two or more

blockholders compared to BHCs with zero or one blockholder. As written before, Holderness (2009) finds

prove that blockholders play an important role in the US, as 96% of all the firms contains at least one

blockholder. This study is not testing whether the presence of blockholders will have a positive influence

on M&A financial performance, however it will test whether the presence of more blockholders will have

a positive impact on M&A financial performance compared to the presence of one or zero blockholder.

When looking at the last variable of interest ‘CEO pay-for-performance’, it can be noticed that the average

percentage a CEO gets paid in equity of the total compensation is about 36%. What is striking to see is that



33

the maximum shows that there is a CEO who gets 205% paid in equity of its total compensation, indicating

that the value of the options and restricted stock the CEO got as equity compensation is worth substantially

more than the compensation paid otherwise. Prior research shows that linking CEO pay to firm performance

was key to optimizing shareholder’s wealth (Bruce et al., 2005), therefore we are interested to study whether

higher levels of CEO pay-for-performance measured by the percentage of equity have a positive impact on

M&A financial performance. The control variable ‘method of payment’ shows that only about 7% of the

M&As were paid in cash. This is remarkable to see as previous literature shows that acquisitions of public

firms which are paid for with cash only have significant positive abnormal returns (Moeller et al., 2004),

and if there was paid otherwise, by for instance stocks, the M&A has a significant negative impact on the

returns (Mitchell and Stafford, 2000). One would therefore expect this percentage of ‘method of payment’

to be higher. At last, looking at the second control variable ‘firm size’, one can conclude that the average

value is 9.79 which is almost the exact middle between the minimum and maximum value. Therefore, it

can be concluded that on average the firms are not extremely large, hence not extremely small.

Table V. Descriptive Statistics of the variables of interest and control variables

This table shows the descriptive statistics of the variables of interest and the control variables. The variable of interest ‘Board

independency’ is a percentage of the number of independent board members divided by the total amount of members sitting on a

board in the year of the M&A announcement. The variable of interest ‘Blockholders’ describes how many shareholders hold >5%

of each BHC’s shares in the year of the M&A announcement, and is a dummy variable created that takes a value of ‘0’ when there

is ≤ 1 blockholder, and takes a value of ‘1’ when there are ≥ 2 blockholders present. ‘CEO pay-for-performance’ is the last variable

of interest, which stands for the percentage of equity payment over the total compensation a CEO got in the year of the M&A

announcement. The control variable ‘Method of payment’ is a dummy variable that takes a value of ‘1’ when the M&A was paid

by cash only, and takes a value of ‘0’ when the M&A was paid by another method. At last, the control variable ‘Firm size’ indicates

how large a firm is by taking the logarithm of the total assets of each BHC in the year of the M&A announcement. The sample

consisted of 138 domestic M&A deals done by BHCs within the US which took place during the period 2005 until 2015.

Variables of interest and control variables, based on an estimation window of 100 trading days

Variable Mean Std. Dev. Min Max N

Board independency .811969 .091850 .588235 .944444 138

Blockholders .514493 .501611 0 1 138

CEO pay-for-performance .360435 .343647 0 2.05 138

Method of payment .072464 .260199 0 1 138

Firm size 9.793916 1.484969 6.906796 14.41322 138



34

4. Empirical results

In this section I begin by showing the empirical evidence found by conducting several regressions,

including fixed effects, on the impact of M&A announcements on a BHC its financial performance

measured by CARs, and the impact of all variables of interest on the BHCs M&A financial performance

pre-announcement, post-announcement, and surrounding the announcement. At last, the empirical evidence

found on the impact of the Global Financial Crisis for each of the regressions used for this study is shown.

4.1 Regression results

For this study multiple regressions (which are defined in paragraph 3.2.3) have been tested over

previously defined event windows. The results will be shown in separate paragraphs concluding with the

full model. In order to test if all the variables of this study are highly correlated, a multicollinearity test was

conducted. This multicollinearity test showed that there were no variables that can be linearly predicted

from the others, and it can be found in Appendix A, table XX.

4.1.1 Regression 1: M&A performance

For testing the first hypothesis, an event study was conducted for the whole sample. The results

from the first regression are shown in table VI. From the four event windows tested only one is statistically

significant, which implies that empirically shareholders of acquiring BHCs have no significant gain or loss

compared to the market return. The event window pre-announcement [-5,0] is statistically significant

showing a negative impact of about -0.9% on the BHCs returns compared to the market return, and is in

line with previous studies of Alexandridis et al. (2010), Hannah and Wolken (1989), and Houston and

Ryngaert (1994). In addition, the event windows [-1,1] and [-10,10], which surround the announcement,

are not statistically significant, however economically confirming a negative impact on the BHCs returns

compared to the market return. Those event windows economically show that surrounding the M&A

announcement the acquiring BHCs returns will be -0.09% and -0.3% less than the market and are in line

with the previously named literature. Thus, it can therefore be stated that the value of the shareholders from

the BHCs tested will decrease in case of an M&A announcement during the years 2005 until 2015, as the

stock returns of the acquiring BHCs underperform the market index. Even though the regression outcomes

only show one statistically significant effect, the other figures also provide an evidence on the Hubris

Hypothesis of Roll (1986), since in shorter time windows tested, there is no statistically significant value

gain in the shareholders returns. Therefore, the first hypothesis on the fact that M&As have a significant

negative effect on the stock returns of the acquiring BHCs is confirmed. Even though, only the pre-

announcement event window shows a statistically significant result on the impact of an M&A



35

announcement on M&A financial performance, it can be assumed that the other event windows might report

some economic significance. In addition, we are also interested in the difference in impact of the variables

of interest on the dependent variable pre-announcement, post-announcement, and surrounding an M&A

announcement. Therefore, all event windows will be used for the next regressions, still the main focus will

be on the pre-announcement event window.

Table VI. Regression results of the event study on the dependent variable

This table reports the simple OLS regression of the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs, on

a constant. The standard errors are robust. These regressions are completed on four event windows, all with an estimation window

of 100 days starting at -30 trading days of the M&A announcement date (at t=0). The sample consisted of 138 domestic M&A

deals done by BHCs within the US which took place during the period 2005 until 2015.

Results of the event study for all acquirers

Event window [-10,10] [-5,0] [-1,1] [0,5]

CAR -.000931 -.009071** -.003872 .003652

*** p<0.01, ** p<0.05, * p<0.1

4.1.2 Regression 2: Board independency

For testing the second hypothesis, I first perform a fixed effects regression of the first variable of

interest, board independency, separately with the control variables on the CARs corresponding to the four

event windows used for this study. The variable of interest is calculated, as written in paragraph 3.2.2.1, by

dividing the number of independent directors of the board by the total number of directors on the board.

The results of the first fixed effects regression are shown in table VII. All the results show that higher board

independency, and thus having more independent directors in the board, has a positive impact on the returns

of an acquiring BHCs compared to the market. However, only two event windows, the post-announcement

and widely surrounding the M&A announcement event window, show statistically significant results. In

case of the post-announcement event window, which is statistically significant at a 10% level, this results

in 15.21% higher returns than the market, whereas for the event window widely surrounding the M&A

announcement, which is statistically significant at a 5% level, it results in even 40.30% higher returns than

the market. Both the pre-announcement event window and the event window closely surrounding the M&A

announcement are not statistically significant, however they economically show that higher levels of board

independency have a positive impact on M&A financial performance. These results are in accordance with

the previous literature where according to Dunn (1987), Rosenstein and Wyatt (1990), and Subrahmanyam

et al. (1997), boards dominated by independent outsiders are arguably in a better position to monitor and

control managers, and will face better stock returns and operating performance. Therefore, the effect of

having more independent board members to gain a better position in monitoring and controlling managers

leading the better stock returns, might in this case be true for the BHCs in our sample. Thus, it can be



36

concluded that, as far as this regression concerns, higher levels of board independency lead to better M&A

financial performance of BHCs measured by CARs.

Furthermore, the control variable method of payment reports a positive impact before the

announcement whenever there was paid by cash only for the M&A, whereas it reports a negative impact

on BHCs M&A financial performance post-announcement and surrounding the M&A-announcement.

However, these results are not statistically significant, thus it can only be assumed economically that

payment by cash only has a positive effect on the returns of the BHCs compared to the market pre-

announcement, but has a negative effect post-announcement and surrounding the M&A-announcement. On

the other hand, control variable firm size shows positive results. Thus, larger firms have better returns in

case of an M&A announcement.

To conclude on the effect of board independency on M&A financial performance the ‘full model’

will be tested in paragraph 4.1.5.

Table VII. Regression results on board independency and its effect on BHCs cumulative abnormal returns

This table reports the fixed effects regression of the variable of interest ‘board independency’ and control variables ‘method of

payment’ and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs. The variable of interest

‘Board independency’ is a percentage of the number of independent board members divided by the total amount of members sitting

on a board in the year of the M&A announcement. The control variable ‘Method of payment’ is a dummy variable that takes a

value of ‘1’ when the M&A was paid by cash only, and takes a value of ‘0’ when the M&A was paid by another method. At last,

the control variable ‘Firm size’ indicates how large a firm is by taking the logarithm of the total assets of each BHC in the year of

the M&A announcement. Firm FE indicates whether firm fixed effects were added in the regression. The standard errors are robust.

The regression is completed on four event windows, all with an estimation window of 100 days starting at -30 trading days of the

M&A announcement date (at t=0). The sample consisted of 138 domestic M&A deals done by BHCs within the US which took

place during the period 2005 until 2015.

Results of the regression on board independency and cumulative abnormal returns

Event window [-10,10] [-5,0] [-1,1] [0,5]

Board independency .403033*** )

(.162462)** *

.119636* **)

(.092091)** *

.077122** *)

(.061508)* **

.152187*** )

(.078719)** *

Method of payment -.003653*** )

(.025916)** *

.001687* **)

(.018282)* **

-.000857** *)

(.015437)** *

-.005658*** )

(.008128)** *

Firm size .073592**) *

(.033146)* * *

.032255)** *

(.026097)* **

.009576** *)

(.015952)** *

.025565*** )

(.011391)** *

Firm FE Yes Yes Yes Yes

R² 0.6349 0.4633 0.3764 0.5803

Adj. R² 0.6255 0.4113 0.2425 0.5396

*** p<0.01, ** p<0.05, * p<0.1



37

4.1.3 Regression 3: Blockholders

For testing the third hypothesis, I first perform a fixed effects regression of the second variable of

interest, blockholders, separately with the control variables on the CARs corresponding to the four event

windows used for this study. A blockholder is a large shareholder or an entity which holds at least 5% of

the shares of a firm. By having blockholders, managers who fail to create shareholder value might be

influenced by for instance a threat of the blockholders to take over the firm or to replace management. This

leads to managers acting in the interest of the shareholders, hence creating shareholder value (Bethel et al.,

1998; Denis & McConnell, 2003). For studying whether having more blockholders has a positive impact

on the firm a dummy variable is created which takes the value of ‘1’ if there are two or more blockholders,

and takes a value of ‘0’ when there is one or no blockholder present in the acquiring BHCs of the sample

at the year of the announcement. In table VIII the results of this regression are presented, where all event

windows report a negative impact on the BHCs financial performance. The only event window which shows

a statistically significant result, at a 5% significance level, is the event window closely surrounding the

M&A announcement. It reports that BHCs with two or more blockholders have about -2.81% lower returns

compared to BHCs which have zero or no blockholders present. The other event windows are not

statistically significant, however they economically show that if BHCs have two more blockholders they

will have lower returns than BHCs that have one or no blockholders present. Therefore, these results are in

conflict with previous literature (Bethel et al., 1998; Denis & McConnell 2003) stating that blockholders

have a positive effect on the firm’s financial performance measured by CARs. An explanation for the

negative impact on the BHCs returns might be that the presence of more blockholders can be a seen as a

threat of intervention and thus may erode managerial initiative, or their presence may lower liquidity

(Edmans, 2013). Another explanation might be that instead of maximizing shareholder value, blockholders

may extract private benefits, resulting in a conflict of interest between the blockholders and the smaller

shareholders (Edmans, 2013).


announcement and in both cases surrounding the M&A announcement whenever there was paid by cash

only for the M&A, whereas it reports a negative impact on BHCs M&A financial performance post-

announcement. However, these results are not statistically significant, thus it can only be assumed

economically that payment by cash only has a positive effect on the returns of the BHCs compared to the

market pre-announcement and surrounding the M&A announcement, but has a negative effect post-

announcement. On the other hand, control variable firm size shows positive results, for which the post-

announcement event window, and the event window widely surrounding the M&A announcement are

statistically significant at a 5% significance level. Thus, larger firms have better returns in case of an M&A

announcement.



38

To conclude on the effect of blockholders on M&A financial performance the full model will be

tested in paragraph 4.1.5.

Table VIII. Regression results on blockholders and its effect on BHCs cumulative abnormal returns

This table reports the fixed effects regression of the variable of interest ‘blockholders’ and control variables ‘method of payment’

and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs. The variable of interest is a

dummy that represents how many shareholders hold >5% of each BHC’s shares in the year of the M&A announcement, and takes

a value of ‘0’ when there is ≤ 1 blockholder, or takes a value of ‘1’ when there are ≥ 2 blockholders present. The control variable

‘Method of payment’ is a dummy variable that takes a value of ‘1’ when the M&A was paid by cash only, and takes a value of ‘0’

when the M&A was paid by another method. At last, the control variable ‘Firm size’ indicates how large a firm is by taking the

logarithm of the total assets of each BHC in the year of the M&A announcement. Firm FE indicates whether firm fixed effects

were added in the regression. The standard errors are robust. These regression is completed on four event windows, all with an

estimation window of 100 days starting at -30 trading days of the M&A announcement date (at t=0). The sample consisted of 138

domestic M&A deals done by BHCs within the US which took place during the period 2005 until 2015.

Results of the regression on blockholders and cumulative abnormal returns

Event window [-10,10] [-5,0] [-1,1] [0,5]

Blockholders -.030267*** )

(.027444)** *

-.018489*** )

(.017269)** *

-.028104*** )

(.014395)** *

-.008987** ) *

(.010135)** *

Method of payment .009539*** )

(.026876)** *

.008169*** )

(.015459)** *

.007685*** )

(.014349)** *

-.001336*** )

(.006740)** *

Firm size .083785*** )

(.041719)** *

.040765*** )

(.032574)** *

.023780*** )

(.018088)** *

.028050*** )

(.014059)** *


R² 0.6203 0.4664 0.4188 0.5677

Adj. R² 0.6105 0.4147 0.4188 0.5258

*** p<0.01, ** p<0.05, * p<0.1

4.1.4 Regression 4: CEO pay-for-performance

For testing the fourth hypothesis, I first perform a fixed effects regression of the third variable of

interest, CEO pay-for-performance, separately with the control variables on the CARs corresponding to the

four event windows used for this study. Previous studies have shown that linking CEO pay to firm

performance was key to optimization of shareholder’s wealth (Bruce et al., 2005). Making sure that a CEO

was paid by long-term incentives schemes makes this possible. CEO pay-for-performance is therefore

measured by looking at the percentage of equity-based compensation, which is known as long-term

incentive schemes, over the total compensation (Datta et al., 2001). The regression results are shown in

table IX, and report no statistically significant results on the effect of CEO pay-for-performance on the

M&A financial performance of the BHCs. However, pre-announcement it shows an economically negative

impact of CEO pay-for-performance on the BHCs returns compared to the market returns when there the

CEO gets paid more in equity. In addition the event window closely surrounding the M&A announcement



39

also reports an economically negative impact. These results are not in line with the previous literature by

Abowd (1990) and Bruce et al. (2005), but a possible explanation could be that CEOs became too optimistic

and overconfident and were therefore not acting in the best interest of the shareholders. However, the post-

announcement event window and the event window widely surrounding the M&A announcement show

economically positive impacts of CEO pay-for-performance. They suggest that the BHCs returns would be

higher pre-announcement and widely surrounding the M&A announcement compared to the market returns

when the CEO gets paid more in equity. These statistically significant results are in line with the previous

literature, and could be due to the fact that rewarding a CEO with stocks and options is a way to let them

act in the best interest of the firm’s shareholders as you connect the CEOs personal wealth with the

performance of the firm. Rationally speaking, the different results of the event windows can be caused due

to the fact that before the M&A announcement the impact is negatively and turns around positively after

the announcement, thus these effects had more recovery time in the wider event window surrounding the

M&A announcement than in the event window closely surrounding the M&A announcement, and therefore

showing a positive impact. Though, since there are no statistically significant results, no clear conclusion

can be drawn.


announcement and in both cases surrounding the M&A announcement whenever there was paid by cash

only for the M&A, whereas it reports a negative impact on BHCs M&A financial performance post-

announcement. However, these results are not statistically significant, thus it can only be assumed

economically that payment by cash only has a positive effect on the returns of the BHCs compared to the

market pre-announcement and surrounding the M&A announcement, but has a negative effect post-

announcement. On the other hand, control variable firm size shows positive results for all the event windows,

and the event window widely surrounding the M&A announcement are statistically significant at a 5%

significance level. Thus, larger firms have better returns in case of an M&A announcement.

To conclude on the effect of CEO pay-for-performance on M&A financial performance the full

model will be tested in paragraph 4.1.5.



40

Table IX. Regression results on CEO pay-for-performance and its effect on BHCs cumulative abnormal

returns

This table reports the fixed effects regression of the variable of interest ‘CEO pay-for-performance’ and control variables ‘method

of payment’ and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs. ‘CEO pay-for-

performance’ is the last variable of interest, which stands for the percentage of equity payment over the total compensation a CEO

got in the year of the M&A announcement. The control variable ‘Method of payment’ is a dummy variable that takes a value of ‘1’

when the M&A was paid by cash only, and takes a value of ‘0’ when the M&A was paid by another method. At last, the control

variable ‘Firm size’ indicates how large a firm is by taking the logarithm of the total assets of each BHC in the year of the M&A

announcement. Firm FE indicates whether firm fixed effects were added in the regression. The standard errors are robust. These

regressions are completed on four event windows, all with an estimation window of 100 days starting at -30 trading days of the


place during the period 2005 until 2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]

CEO pay-for-performance .037764** )

(.059600)* *

-.004839** )

(.022147)* *

-.013322***)

(.023692)***

.011307*** )

(.038083)** *

Method of payment -.006244** )

(.028315)* *

.004159** )

(.016955)* *

.002795***)

(.015927)***

-.006041*** )

(.009614)** *

Firm size .062758** )

(.032749)* *

.031281** )

(.026377)* *

.010165***)

(.016048)***

.021795*** )

(.010729)** *


R² 0.6180 0.4551 0.3748 0.5667

Adj. R² 0.6082 0.4024 0.2405 0.5247

*** p<0.01, ** p<0.05, * p<0.1

4.1.5 Regression 5: The full model

In order to test hypothesis 2 to 4 again, I perform a fixed effects regression of all the variables of

interest (board independency, blockholders, and CEO pay-for-performance) and the control variables

(method of payment, and firm size) on the CARs corresponding to the four event windows used for this

study in the so called ‘full model’. The results from the full model, which are shown in table X, are in line

with previous results of the previous regressions on the variables of interest.

For the pre-announcement window none of the results are statistically significant. However, a

higher level of board independency generates an economically positive impact on the returns of BHCs

compared to the market returns. While having two or more blockholders results in an economically negative

impact compared to having one or no blockholders, and a higher percentage of CEO pay-for-performance

leads to an economically negative impact compared to the market returns.

The post-announcement window shows that, higher board independency has a statistically positive

effect, at a 10% significance level. However, the results of the other two variables of interest are not

statistically significance. Still, having two or more blockholders has an economically negative effect on the



41

returns of the BHCs compared to BHCs that have zero or one blockholder. In addition, higher CEO pay-

for-performance has an economically positive effect on the returns of the BHCs compared to the market

returns. As the result on board independency is the only one statistically significant, it can be stated that

having a more independent board results in about 16.14% higher returns than the market.

When looking at the results of the event windows surrounding the M&A announcement, it shows

that in the event window widely surrounding the M&A announcement higher levels of board independency

have a statistically significant positive effect, at a 5% significance level, on the returns of the BHCs

compared to the market. Suggesting that, BHCs with higher levels of board independency have about 43.35%

higher returns than the market. In the event window closely surrounding the M&A announcement they are

not statistically significant, but do report an economically positive impact on the returns of the BHCs

compared to the market. On the other hand, in the event window closely surrounding the M&A

announcement, having two or more blockholders has a statistically significant negative effect, at a 5%

significance level, on the returns of the BHCs compared to the market. The event window widely

surrounding the M&A announcement reports no statistically significance, but does economically report that

BHCs with two or more blockholders have lower returns than BHCs with one or no blockholder. If BHCs

pay their CEO more in equity, and thus have higher levels of CEO pay-for-performance, this has an

economically negative effect on the returns of the BHCs in the event window closely surrounding the M&A

announcement. However, it has a positive effect on the returns of the BHCs in the event window widely

surrounding the M&A announcement. Still, as these results on CEO pay-for-performance are not

statistically significant, no empirical conclusion can be drawn from these results.


announcement and in the event window closely surrounding the M&A announcement whenever there was

paid by cash only for the M&A. On the other hand, it reports a negative impact on BHCs M&A financial

performance post-announcement and widely surrounding the M&A announcement. However, these results

are not statistically significant, thus it can only be assumed economically that payment by cash only has a

positive effect on the returns of the BHCs compared to the market pre-announcement, but has a negative

effect post-announcement. On the other hand, control variable firm size shows statistically significant

positive results, at a 5% significance level, for the event windows post-announcement and widely

surrounding the M&A announcement. In addition, even though they are not statistically significant, the

other event windows also show a positive impact. Thus, larger firms have better returns in case of an M&A

announcement.

In conclusion, the second hypothesis, stating that boards with greater oversight, measured by board

independency, will have a statistically significant positive impact on the M&A financial performance, is

confirmed. These results, from both the individual regression as well as from the ‘full model’, are in line



42

with previous literature by Rosenstein and Wyatt (1990), and Subrahmanyam et al. (1997). An explanation

for this could be that boards dominated by independent directors have a better position to monitor and

control managers and will therefore have better stock returns. On the other hand, having two or more

blockholders has a statistically significant negative impact on the M&A financial performance. The results

on the impact of blockholders are all statistically significant in both the individual regression and the ‘full

model’ regression. Therefore, these results are in conflict with previous literature (Bethel et al., 1998; Denis

& McConnell 2003) stating that blockholders have a positive effect on the firm’s financial performance

measured by CARs. An explanation for the negative impact on the BHCs returns might be the presence of

blockholders might be a seen as a threat of intervention and thus may erode managerial initiative, or their

presence may lower liquidity (Edmans, 2013). Another explanation might be that instead of maximizing

shareholder value, blockholders may extract private benefits, resulting in a conflict of interest between the

blockholders and the smaller shareholders (Edmans, 2013). Therefore, the third hypothesis, stating that

having more blockholders will have a positive impact on M&A financial performance, is rejected. With

regards to CEO pay-for-performance none of the results are statistically significant. These event windows

report an economically positive impact post-announcement and widely surrounding the M&A

announcement on stock returns compared to the market returns. However, the event windows pre-

announcement and closely surrounding the announcement show an economically negative impact if a CEO

get paid more in equity on the BHCs returns compared to the market. A possible explanation for this could

be that before the announcement CEO’s do not feel threatened and therefore do not care so much, but when

the M&A announcement is made and after this event they will be careful for their own sake as their wealth

is connected to the firm’s performance by their equity compensation. However, as the results are not

statistically significant, the fourth hypothesis of this study, which states that higher levels of CEO pay-for-

performance have a positive impact on BHCs M&A financial performance, cannot be confirmed as no

empirical evidence is found.

At last, one can thus say from the results of our analysis that having a good corporate governance

(in this study only measured according to three mechanisms) in a BHC has both positive and negative

impacts on the M&A announcement returns. Where higher levels of board independency create a positive

impact, and having two or more blockholders creates a negative impact. Regarding CEO pay-for-

performance no empirical evidence was found. Therefore, the results are partly in accordance with previous

literature saying that good corporate governance improves the M&A financial performance.



43

Table X. Regression results on the ‘full model’ and its effect on BHCs cumulative abnormal returns

This table reports the fixed effects regression of the ‘full model’ regressing all variables of interest ‘board independency’,

‘blockholders’, ‘CEO pay-for-performance’, and control variables ‘method of payment’ and ‘firm size’ on the dependent variable,

Cumulative Abnormal Returns of the acquiring BHCs. The variable of interest ‘Board independency’ is a percentage of the number

of independent board members divided by the total amount of members sitting on a board in the year of the M&A announcement.

The variable of interest ‘Blockholders’ describes how many shareholders hold >5% of each BHC’s shares in the year of the M&A

announcement, and is a dummy variable created that takes a value of ‘0’ when there is ≤ 1 blockholder, and takes a value of ‘1’

when there are ≥ 2 blockholders present. ‘CEO pay-for-performance’ is the last variable of interest, which stands for the percentage

of equity payment over the total compensation a CEO got in the year of the M&A announcement. The control variable ‘Method of

payment’ is a dummy variable that takes a value of ‘1’ when the M&A was paid by cash only, and takes a value of ‘0’ when the

M&A was paid by another method. At last, the control variable ‘Firm size’ indicates how large a firm is by taking the logarithm of

the total assets of each BHC in the year of the M&A announcement. Firm FE indicates whether firm fixed effects were added in

the regression. The standard errors are robust. These regressions are completed on four event windows, all with an estimation

window of 100 days starting at -30 trading days of the M&A announcement date (at t=0). The sample consisted of 138 domestic

M&A deals done by BHCs within the US which took place during the period 2005 until 2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]


(.186164)** *

.127679*** )

(.091983)** *

.086043***)

(.060035)***

.161493*** )

(.087455)** *


(.027124)** *

-.020261*** )

(.017625)** *

-.030438***)

(.014274)***

-.009403*** )

(.009576)** *

CEO Pay-for-performance .038377*** )

(.053983)** *

-.006798*** )

(.020957)** *

-.017941***)

(.021945)***

.011930*** )

(.036052)** *


(.028130)** *

.008422*** )

(.018566)** *

.010860***)

(.016556)***

-.005648*** )

(.011018)** *

Firm size .085682*** )

(.037659)** *

.044212***))

(.031872)** *

.018399***)

(.017372)***

.029197*** )

(.011503)** *


R² 0.6486 0.4771 0.4365 0.5869

Adj. R² 0.6393 0.4249 0.3114 0.5456

*** p<0.01, ** p<0.05, * p<0.1

4.2 Regression results – Before, during, and after the Global Financial Crisis

As the time period used for this study includes the Global Financial Crisis, we are interested its

impact on the previously gathered results. Therefore, it will be studied whether there are differences before,

during, and after the crisis from which we can gain new insights.

Looking at figure 2, it is clear that there were extremely less M&A announcements during the

Global Financial Crisis (which as previously written lasted from the 1st of July 2008 to the 31st of July 2009).

This is plausible as during the crisis BHCs had a rough time, and so the M&A wave which had built up

since 2002 went over, as the number of deals declined substantially since 2007 (Ravichandran, 2009).



44

Figure 2. M&A announcements per calendar year.

The figure illustrates the absolute number of M&A announcements made in each calendar year during the sample period. The

sample consisted of 138 domestic M&A deals done by BHCs within the US which took place during the period 2005 until 2015.

For testing the first hypothesis before, during, and after the crisis, and to see whether what sort of

impact an M&A announcement had on the returns of the BHCs, an event study was conducted for the whole

sample. Three separate regressions are conducted, as one regression only regressed the CARs of M&A

announcements before the crisis, one during the crisis, and one after the crisis, which lasted from the 1st of

July 2008 to the 31st of July 2009. The results from these regressions are shown in table XI. Before the

crisis, the CARs of BHCs were statistically significantly lower than the market, which is in accordance with

the Hubris Hypothesis of Roll (1986) and previous studies by Alexandridis et al. (2010), Hannah and

Wolken (1989), and Houston and Ryngaert (1994). Since there was a large M&A wave in this period, one

would expect firms only to conduct an M&A if it would result in better returns. On the other hand, even

though the results are not statistically significant, the results show that during the crisis BHCs announcing

an M&A did better than the market. This is in conflict with previous literature that shows negative stock

returns and price drops during the crisis (Ravichandran, 2009; Erkens et al., 2012). After the crisis, the

results are mixed. In the pre-announcement event window, BHCs are having worse CARs than the market,

and this result is highly statistically significantly showing that they perform about -1.2% worse. However,

the event window post-announcement shows that BHCs recover from this negative impact and indicate

economically higher CARs than the market. When looking at the time periods surrounding the M&A

announcement, the wider event window shows higher CARs for BHCs than the market, whereas the CARs

are lower than the market in the more narrow event window. Reasonably speaking, the different results of

the event windows can be caused due to the fact that before the M&A announcement the impact is

negatively and turns around positively after the announcement, thus these effects had more recovery time

in the wider event window surrounding the M&A announcement than in the event window closely

surrounding the M&A announcement, and therefore showing a positive impact.

10

2623

7

1

108

11

15 16

11

0

5

10

15

20

25

30

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Anno

untm

ents

(ab

solu

te n

um

ber

s)

Year

M&A Announcements



45

Table XI. Regression results of the event study on the dependent variable before, during, and after the Global

Financial Crisis

This table reports three simple OLS regressions of the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs,

on a constant; one regression before the crisis, one regression during the crisis, and one regression after the crisis. The Global

Financial Crisis lasted from the 1st of July 2008 to the 31st of July 2009. The standard errors are robust. These regressions are

completed on four event windows, all with an estimation window of 100 days starting at -30 trading days of the M&A

announcement date (at t=0). The sample consisted of 138 domestic M&A deals done by BHCs within the US which took place

during the period 2005 until 2015 of which 61 before the crisis, 6 during the crisis, and 71 after the crisis.


Event window [-10,10] [-5,0] [-1,1] [0,5]

Before crisis CAR -.016291** * -.012087*** * -.007311**** * -.003012*** *

During crisis CAR .069640* ** .057514*** * .042806*** * .058013*** *

After crisis CAR .006303 *** -.012107*** * -.004861*** * .004784*** *

*** p<0.01, ** p<0.05, * p<0.1

4.2.1 The impact of the variables of interest before the crisis

When looking at the individual regression on board independency (including the control variables

and firm fixed effects) before the crisis (Table XII), none of the results are statistically significant. However,

before the crisis, having more independent board members sitting on a BHC’s board seems to have an

economically positive impact on the BHCs returns compared to the market returns in the pre- and post-

announcement event windows and the event window closely surrounding the M&A announcement. In

contrast, the wider event window surrounding the M&A announcement presents an economically negative

impact, indicating that having higher levels of board independency leads to lower returns for the BHCs

compared to the market returns. In addition, the results of the ‘full model’ regression including firm fixed

effects before the crisis (Table XV), show no statistically significant impact. However, one could see that

the event window closely surrounding the M&A announcement now reports an economically negative

impact of higher levels of board independency on the returns of the BHCs compared to the market. The

other event windows keep reporting an economically positive impact pre- and post-announcement, and an

economically negative impact widely surrounding the M&A announcement. As none of the results are

statistically significant, there is no empirical evidence found that BHCs with higher levels of board

independency have a positive impact on M&A financial performance before the Global Financial Crisis.



46

Table XII. Regression results on board independency and its effect on BHCs Cumulative Abnormal Returns

before the Global Financial Crisis


payment’ and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs before the Global

Financial Crisis. The Global Financial Crisis lasted from the 1st of July 2008 to the 31st of July 2009. The variable of interest





the M&A announcement. Firm FE indicates whether firm fixed effects were added in the regression. The standard errors are robust.

The regression is completed on four event windows, all with an estimation window of 100 days starting at -30 trading days of the


place before the Global Financial Crisis during the period of the 1st of 2005 until 30th of June 2008.


Event window [-10,10] [-5,0] [-1,1] [0,5]

Board independency -.131312*** )

(.546979)** *

.112968*** )

(.286046)** *

.140176*** )

(.308183)** *

.241020*** )

(.072727)** *


(.054013)** *

.017900*** )

(.019489)** *

.012782*** )

(.01849)** *

.022045*** )

(.013458)** *

Firm size .022375** )*

(.134622)** *

.016075*** )

(.087877)** *

-.063482*** )

(.097744)** *

.014360*** )

(.072814)** *


R² 0.7971 0.7627 0.7605 0.6580

Adj. R² 0.7895 0.7284 0.6795 0.6086

*** p<0.01, ** p<0.05, * p<0.1

When observing the individual regression on blockholders (including the control variables and firm

fixed effects) (Table XIII) and the ‘full model’ regression including firm fixed effects (Table XV) before

the crisis, the pre- and post-announcement event windows show that having two or more blockholders had

a statistically significant negative impact on the returns of the BHCs compared to having zero or no

blockholders present. The event window pre-announcement reports a statistically significant negative

impact of about -1.46% in both regressions at a 10% significance level, and the event window post-

announcement reports a statistically significant negative impact of about -3% in both regressions at a 1%

significance level. In addition, in the ‘full model’ regression the event window closely surrounding the

M&A announcement shows a statically significant negative impact of about -1.37% at a 5% significance

level. Moreover, the event windows that do not show statistically significant results, do report an

economically negative impact when there are two or more blockholders present in the BHCs compared to

zero or no blockholders.

All the results indicate that having two or more blockholders before the crisis have a negative

impact on its returns compared to having one or zero blockholders. As some of these results are statistically



47

significant, it can be empirically stated that having two or more blockholders within BHCs before the crisis

lead to worse returns than when there are one or zero blockholders present within the BHCs. These results

are in conflict with previous literature (Bethel et al., 1998; Denis & McConnell 2003) stating that

blockholders have a positive effect on the firm’s financial performance measured by CARs. An explanation

for the negative impact on the BHCs returns might be the presence of blockholders might be a seen as a

threat of intervention and thus may erode managerial initiative, or their presence may lower liquidity

(Edmans, 2013). Another explanation might be that instead of maximizing shareholder value, blockholders

may extract private benefits, resulting in a conflict of interest between the blockholders and the smaller

shareholders (Edmans, 2013).

Table XIII. Regression results on blockholders and its effect on BHCs Cumulative Abnormal Returns before

the Global Financial Crisis


and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs before the Global Financial Crisis.

The Global Financial Crisis lasted from the 1st of July 2008 to the 31st of July 2009. The variable of interest is a dummy that

represents how many shareholders hold >5% of each BHC’s shares in the year of the M&A announcement, and takes a value of ‘0’

when there is ≤ 1 blockholders, or takes a value of ‘1’ when there are ≥ 2 blockholders present. The control variable ‘Method of




the regression. The standard errors are robust. The regression is completed on four event windows, all with an estimation window

of 100 days starting at -30 trading days of the M&A announcement date (at t=0). The sample consisted of 61 domestic M&A deals

done by BHCs within the US which took place before the Global Financial Crisis during the period of the 1st of 2005 until 30th of

June 2008.


Event window [-10,10] [-5,0] [-1,1] [0,5]

Blockholders -.006519** )*

(.012570)** *

-.014698*** )

(.008116)** *

-.010082*** )

(.008867)** *

-.027414*** )

(.008485)** *


(.039161)** *

.011419*** )

(.013055)** *

.004680*** )

(.007930)** *

.008188*** )

(.006599)** *

Firm size .041310*** )

(.108489)** *

-.073344*** )

(.070043)** *

-.087489*** )

(.076529)** *

-.029162*** )

(.073232)** *


R² 0.7962 0.7630 0.7580 0.6566

Adj. R² 0.7886 0.7288 0.6762 0.6071

*** p<0.01, ** p<0.05, * p<0.1

When looking at the individual regression on CEO pay-for-performance (including the control

variables) (Table XIV), and the ‘full model’ regression including firm fixed effects (Table XV) before the

crisis, all the event windows show that higher levels of CEO paid in equity have a negative impact on the



48

BHCs returns compared to the market. In both regressions, the post-announcement event window even

reports a statistically significant negative impact of about -5% at a 1% significance level, and the event

window closely surrounding the M&A announcement reports a statistically negative impact of about -4.3%

at a 5% and 10% significance level. The other event windows do not show statistically significant results,

however they do report an economically negative impact on the returns of the BHCs compared to the market.

Therefore, it can be empirically stated that before the crisis, paying a CEO more in equity has a negative

impact on a BHCs returns compared to the market returns. These results are in contrast with the previous

literature, stating that due to rewarding a CEO with stocks and options is a way to let them act in the best

interest of the firm’s shareholders as you connect the CEOs personal wealth with the performance of the

firm (Abowd, 1990; Bruce et al., 2005). A possible explanation could be that before the crisis, CEOs who

got paid in more equity based compensation became too optimistic and overconfident as they wanted to

increase their own wealth, which resulted in negative returns compared to the market.

Table XIV. Regression results on CEO pay-for-performance and its effect on BHCs Cumulative Abnormal

Returns before the Global Financial Crisis


of payment’ and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs before the Global

Financial Crisis. The Global Financial Crisis lasted from the 1st of July 2008 to the 31st of July 2009. ‘CEO pay-for-performance’

is the last variable of interest, which stands for the percentage of equity payment over the total compensation a CEO got in the year

of the M&A announcement. The control variable ‘Method of payment’ is a dummy variable that takes a value of ‘1’ when the

M&A was paid by cash only, and takes a value of ‘0’ when the M&A was paid by another method. At last, the control variable

‘Firm size’ indicates how large a firm is by taking the logarithm of the total assets of each BHC in the year of the M&A

announcement. Firm FE indicates whether firm fixed effects were added in the regression. The standard errors are robust. The

regression is completed on four event windows, all with an estimation window of 100 days starting at -30 trading days of the M&A

announcement date (at t=0). The sample consisted of 61 domestic M&A deals done by BHCs within the US which took place

before the Global Financial Crisis during the period of the 1st of 2005 until 30th of June 2008.


Event window [-10,10] [-5,0] [-1,1] [0,5]

CEO pay-for-performance -.045111*)

(.035963)*

-.013102*** )

(.028901)** *

-.043297***)

(.021747)***

-.050499*** )

(.015123)** *

Method of payment -.011742*)

(.050819)*

.016399*** )

(.016918)** *

.021418***)

(.016041)***

.027596*** )

(.010905)** *

Firm size .136936*)

(.086535)*

-.042720*** )

(.109849)** *

.005143***)

(.071939)***

.082365*** )

(.038277)** *


R² 0.8170 0.7649 0.8157 0.7310

Adj. R² 0.8101 0.7310 0.7533 0.6922

*** p<0.01, ** p<0.05, * p<0.1



49

Before the crisis, M&As being paid in cash only have in all regression results (Table XII – Table

XV) a, in most cases, positive impact on the BHCs returns compared to the market returns. The event

windows post-announcement even shows some statistically significant results, reporting about 3% higher

returns of the BHCs compared to the market, at a 5% significance level. Firm size has, in most event

windows, a positive impact on the returns of the BHCs compared to the market returns (Table XII – Table

XV). The event windows post-announcement even shows some statistically significant results, reporting

about 8.3% higher returns for larger BHCs compared to the market, at a 5% significance level.

Table XV. Regression results on the ‘full model’ and its effect on BHCs Cumulative Abnormal Returns

before the Global Financial Crisis

This table reports the fixed effects regression of the ‘full model’ before the crisis. The Global Financial Crisis lasted from the 1st

of July 2008 to the 31st of July 2009. All variables of interest ‘board independency’, ‘blockholders’, ‘CEO pay-for-performance’,

and control variables ‘method of payment’ and ‘firm size’ are regressed on the dependent variable, Cumulative Abnormal Returns

of the acquiring BHCs. The variable of interest ‘Board independency’ is a percentage of the number of independent board members

divided by the total amount of members sitting on a board in the year of the M&A announcement. The variable of interest

‘Blockholders’ describes how many shareholders hold >5% of each BHC’s shares in the year of the M&A announcement, and is a

dummy variable created that takes a value of ‘0’ when there is ≤ 1 blockholders, and takes a value of ‘1’ when there are ≥ 2

blockholders present. ‘CEO pay-for-performance’ is the last variable of interest, which stands for the percentage of equity payment

over the total compensation a CEO got in the year of the M&A announcement. The control variable ‘Method of payment’ is a

dummy variable that takes a value of ‘1’ when the M&A was paid by cash only, and takes a value of ‘0’ when the M&A was paid

by another method. At last, the control variable ‘Firm size’ indicates how large a firm is by taking the logarithm of the total assets

of each BHC in the year of the M&A announcement. Firm FE indicates whether firm fixed effects were added in the regression.

The standard errors are robust. The regression is completed on four event windows, all with an estimation window of 100 days

starting at -30 trading days of the M&A announcement date (at t=0). The sample consisted of 61 domestic M&A deals done by

BHCs within the US that took place before the Global Financial Crisis during the period of the 1st of 2005 until 30th of June 2008.


Event window [-10,10] [-5,0] [-1,1] [0,5]


(.649085)** *

.057512*** )

(.273478)** *

-.006032***)

(.179209)***

.053919*** )

(.196544)** *


(.014859)** *

-.014644*** )

(.008286)** *

-.013711***)

(.006747)***

-.030472*** )

(.005159)** *

CEO Pay-for-performance -.051055*** )

(.038924)** *

-.012564*** )

(.027993)** *

-.043865***)

(.020312)***

-.050556*** )

(.015879)** *


(.059834)** *

.019651*** )

(.021420)** *

.021386***)

(.017771)***

.030985*** )

(.012067)** *

Firm size .098890*** )

(.112012)** *

-.038175*** )

(.117896)** *

.002339***)

(.085990)***

.084071*** )

(.033226)** *


R² 0.8227 0.7679 0.8181 0.7454

Adj. R² 0.8158 0.7328 0.7529 0.7068

*** p<0.01, ** p<0.05, * p<0.1



50

4.2.2 The impact of the variables of interest during the crisis

Looking at figure 2, it is clear that there were extremely less M&A announcements during the

Global Financial Crisis (which as previously written lasted from the 1st of July 2008 to the 31st of July 2009).

The data set used for this study only contains 6 observations During the Global Financial Crisis. This little

amount of observations causes the variables of interest to be omitted due to collinearity when doing a

regression including firm fixed effects. Therefore, no conclusion can be drawn on the impact of the variables

of interest on M&A financial performance during the Global Financial Crisis.

4.2.3 The impact of the variables of interest after the crisis

When looking at the results from the individual regression on board independency (including the

control variables and firm fixed effects) (Table XVI) and the ‘full model’ regression including firm fixed

effects (Table XIX) after the crisis, the results are mixed. In addition, none of the results are statistically

significant. However, the pre-announcement event window and the event window closely surrounding the

M&A announcement report an economically positive impact on the returns of the BHCs compared to the

market returns when there are more independent board members. On the other hand, the post-announcement

event window reports an economically negative impact, and in the individual regression the event window

widely surrounding the M&A announcement also reports an economically negative impact. As none of the

results are statistically significant, there is no empirical evidence found that BHCs with higher levels of

board independency have a positive impact on M&A financial performance after the Global Financial Crisis.



51

Table XVI. Regression results on board independency and its effect on BHCs Cumulative Abnormal Returns

after the Global Financial Crisis


payment’ and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs after the Global Financial

Crisis. The Global Financial Crisis lasted from the 1st of July 2008 to the 31st of July 2009. The variable of interest ‘Board

independency’ is a percentage of the number of independent board members divided by the total amount of members sitting on a

board in the year of the M&A announcement. The control variable ‘Method of payment’ is a dummy variable that takes a value of

‘1’ when the M&A was paid by cash only, and takes a value of ‘0’ when the M&A was paid by another method. At last, the control




announcement date (at t=0). The sample consisted of 71 domestic M&A deals done by BHCs within the US which took place after

the Global Financial Crisis during the period 1st of August 2009 until 31st of December 2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]


(.402031)** *

.234401*** )

(.177232)** *

.189368*** )

(.166845)** *

-.012215*** )

(.253561)** *


(.045463)** *

.008079*** )

(.051569)** *

.020438*** )

(.046649)** *

-.012889** *

(.017914)** *

Firm size -.020648*** )

(.055049)** *

-.010383*** )

(.024989)** *

.007803*** )

(.025686)** *

.005347*** )

(.028246)** *


R² 0.8847 0.7848 0.7144 0.7820

Adj. R² 0.8809 0.7574 0.6308 0.7543

*** p<0.01, ** p<0.05, * p<0.1

When observing the individual regression on blockholders (including the control variables and firm

fixed effects) (Table XVII) and the ‘full model’ regression including firm fixed effects (Table XIX) after

the crisis, the pre-announcement event windows and the event windows widely surrounding the M&A

announcement show that having two or more blockholders had a statistically significant positive impact on

the returns of the BHCs compared to having zero or no blockholders present. The event windows pre-

announcement reports a statistically significant positive impact of about 4.4% in both regressions at a 5%

and 1% significance level, and the event windows widely surrounding the M&A announcement reports a

statistically significant positive impact of about 4% to 6% in both regressions at a 10% and 1% significance

level. Moreover, the event windows that do not show statistically significant results, do report an

economically positive impact when there are two or more blockholders present in the BHCs compared to

zero or no blockholders. All the results indicate that having two or more blockholders after the crisis have

a positive impact on its returns compared to having one or zero blockholders. As some of these results are

statistically significant, it can be empirically stated that having two or more blockholders within BHCs



52

before the crisis lead to better returns than when there are one or zero blockholders present within the BHCs.

These results are in accordance with previous literature (Bethel et al., 1998; Denis & McConnell 2003)

stating that blockholders have a positive effect on the firm’s financial performance measured by CARs.

Table XVII. Regression results on blockholders and its effect on BHCs Cumulative Abnormal Returns after



and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs after the Global Financial Crisis.

The Global Financial Crisis lasted from the 1st of July 2008 to the 31st of July 2009. The variable of interest is a dummy that

represents how many shareholders hold >5% of each BHC’s shares in the year of the M&A announcement, and takes a value of ‘0’

when there is ≤ 1 blockholders, or takes a value of ‘1’ when there are ≥ 2 blockholders present. The control variable ‘Method of




the regression. The standard errors are robust. The regression is completed on four event windows, all with an estimation window

of 100 days starting at -30 trading days of the M&A announcement date (at t=0). The sample consisted of 71 domestic M&A deals

done by BHCs within the US which took place after the Global Financial Crisis during the period 1st of August 2009 until 31st of

December 2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]

Blockholders .040734*** )

(.023619)** *

.043611*** )

(.017073)** *

.022295*** )

(.017894)** *

.022156*** )

(.015122)** *


(.034759)** *

.014750*** )

(.040093)** *

.026126*** )

(.038045)** *

-.013862*** )

(.012287)** *

Firm size -.034707*** )

(.024279)** *

-.041022*** )

(.016829)** *

-.014233*** )

(.013583)** *

.001272*** )

(.009892)** *


R² 0.8914 0.8237 0.7228 0.7912

Adj. R² 0.8878 0.8012 0.6417 0.7646

*** p<0.01, ** p<0.05, * p<0.1

When looking at the individual regression on CEO pay-for-performance (including the control

variables and firm fixed effects) (Table XVIII) and the ‘full model’ regression including firm fixed effects

(Table XIX) after the crisis, the results only report one statistically significant result in the ‘full model’

regression. There the event window widely surrounding the M&A announcement shows that BHCs in

which the CEO gets paid more in equity have about -23.16% lower returns than the market returns. The

other results are not statistically significant, however they almost all do report an economically negative

impact of CEO pay-for-performance on the BHCs returns. Therefore, it can be concluded that after the

Global Financial Crisis paying a CEO with more equity has a negative impact on the returns of the BHCs.

This result is not in line with previous literature, stating that linking CEO pay to firm performance is key



53

to optimizing shareholder’s wealth (Bruce et al., 2005). A possible explanation for the negative impact of

CEO pay-for-performance on M&A financial performance could be that CEOs became too optimistic and

overconfident and therefore not act in the best interest of the shareholders.

Table XVIII. Regression results on CEO pay-for-performance and its effect on BHCs Cumulative Abnormal

Returns after the Global Financial Crisis


of payment’ and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs after the Global

Financial Crisis. The Global Financial Crisis lasted from the 1st of July 2008 to the 31st of July 2009. ‘CEO pay-for-performance’

is the last variable of interest, which stands for the percentage of equity payment over the total compensation a CEO got in the year

of the M&A announcement. The control variable ‘Method of payment’ is a dummy variable that takes a value of ‘1’ when the

M&A was paid by cash only, and takes a value of ‘0’ when the M&A was paid by another method. At last, the control variable

‘Firm size’ indicates how large a firm is by taking the logarithm of the total assets of each BHC in the year of the M&A



announcement date (at t=0). The sample consisted of 71 domestic M&A deals done by BHCs within the US which took place after

the Global Financial Crisis during the period 1st of August 2009 until 31st of December 2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]

CEO pay-for-performance -.150164* )

(.107239) *

-.030585*** )

(.044487)** *

.023518*** )

(.035659)** *

-.022419*** )

(.033045)** *

Method of payment .036833* )

(.037852) *

.017520*** )

(.041592)** *

.027979*** )

(.038989)** *

-.014516*** )

(.013513)** *

Firm size -.020114* )

(.026469) *

-.032140*** )

(.020411)** *

-.009915*** )

(.015281)** *

.007258*** )

(.013277)** *


R² 0.8909 0.7748 0.7047 0.7826

Adj. R² 0.8872 0.7461 0.6182 0.7550

*** p<0.01, ** p<0.05, * p<0.1

With regards to the method of payment, after the crisis, no statistically significant results are found

in all regressions (Table XVI – Table XIX). However, paying for an M&A by cash only has an economically

positive effect on returns compared to the market in both event windows surrounding the M&A

announcement, and in the pre-announcement event window. On the other hand, the event window post-

announcement reports an economically negative impact on the returns. When looking at the impact of large

firms after the crisis, only one statistically significant results is found. It reports in table XVI that larger

firms have statistically significant lower returns of about -4.1% than the market returns (at a 5% significance

level). An explanation for this negative impact comes from Masulis et al. (2007) who argue that a large

firm its size may serve as a quite effective takeover defense as it takes more resources to acquire a large



54

firm, leading to managers of larger firms being more entrenched and more likely to make value-decreasing

acquisitions.

Table XIX. Regression results on the ‘full model’ and its effect on BHCs Cumulative Abnormal Returns after


This table reports the fixed effects regression of the ‘full model’ after the crisis. The Global Financial Crisis lasted from the 1st of

July 2008 to the 31st of July 2009. All variables of interest ‘board independency’, ‘blockholders’, ‘CEO pay-for-performance’, and

control variables ‘method of payment’ and ‘firm size’ are regressed on the dependent variable, Cumulative Abnormal Returns of

the acquiring BHCs. The variable of interest ‘Board independency’ is a percentage of the number of independent board members

divided by the total amount of members sitting on a board in the year of the M&A announcement. The variable of interest

‘Blockholders’ describes how many shareholders hold >5% of each BHC’s shares in the year of the M&A announcement, and is a

dummy variable created that takes a value of ‘0’ when there is ≤ 1 blockholders, and takes a value of ‘1’ when there are ≥ 2

blockholders present. ‘CEO pay-for-performance’ is the last variable of interest, which stands for the percentage of equity payment

over the total compensation a CEO got in the year of the M&A announcement. The control variable ‘Method of payment’ is a

dummy variable that takes a value of ‘1’ when the M&A was paid by cash only, and takes a value of ‘0’ when the M&A was paid

by another method. At last, the control variable ‘Firm size’ indicates how large a firm is by taking the logarithm of the total assets

of each BHC in the year of the M&A announcement. Firm FE indicates whether firm fixed effects were added in the regression.

The standard errors are robust. The regression is completed on four event windows, all with an estimation window of 100 days

starting at -30 trading days of the M&A announcement date (at t=0). The sample consisted of 71 domestic M&A deals done by

BHCs within the US which took place after the Global Financial Crisis during the period 1st of August 2009 until 31st of December

2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]


(.336545)** *

.219788*** )

(.143525)** *

.190173*** )

(.154337)** *

-.058038*** )

(.232885)** *


(.019844)** *

.043960*** )

(.015489)** *

.021066*** )

(.016089)** *

.027285*** )

(.016248)** *

CEO Pay-for-performance -.231602*** )

(.085634)** *

-.008797*** )

(.024636)** *

.010351*** )

(.019531)** *

-.059818*** )

(.037003)** *


(.040863)** *

.006984*** )

(.050834)** *

.020452*** )

(.046664)** *

-.015388*** )

(.016285)** *

Firm size -.041609*** )

(.042344)** *

-.021334*** )

(.018073)** *

.002746*** )

(.022892)** *

-.003359*** )

(.025063)** *


R² 0.9041 0.8346 0.7336 0.7951

Adj. R² 0.9008 0.8125 0.6514 0.7678

*** p<0.01, ** p<0.05, * p<0.1



55

5. Conclusion

This thesis started by explaining that according to the literature there were mixed findings on the fact

whether M&As increased shareholder value or not. For example, Bruner (2002) states that M&As do create

an increase in shareholder value, and discusses whether M&A in general pays off. Whereas, Mulherin and

Boone (2000) and Bruner (2005) show, when studying US-based acquirers, firms tend to have negative

statistically significant abnormal returns. However, the Hubris Hypothesis of Roll (1986) however states

that bidding firms tend to overpay for their targets, leading to negative returns for the acquiring firm. Most

of the previous studies related to the banking industry, and in addition previous literature for all M&As,

confirm this Hubris Hypothesis for the bidding firms in the banking industry (Alexandridis et al., 2010;

Hannah & Wolken, 1989; Houston & Ryngaert, 1994). In addition, the results from this study are in line

with those of the previous literature, confirming the fact that M&As have a significant negative effect on

the stock returns of the acquiring BHCs.

The literature has tried to find explanations and solutions to these negative returns for acquiring

firms. The corporate governance structure of firms might be one of the solutions to this problem. As a result,

this study has tried to investigate several corporate governance mechanisms, namely: board independency,

blockholders, and CEO pay-for-performance. To the best of our knowledge, there are however very few

studies analyzing the impact of those three corporate governance mechanisms on BHCs M&A financial

performance over the time period 2005-2015 including the effects of the Global Financial Crisis. Since the

results of this study are clearly described in the previous chapter (4), the main research question of this

study can be answered:

‘Is there a positive relationship between corporate governance mechanisms and M&A financial

performance for BHCs?’

First of all, regarding board independency, boards dominated by independent outsiders are arguably

in a better position to monitor and control managers, and will face better stock returns and operating

performance. This study confirms previous studies Dunn (1987), Rosenstein and Wyatt (1990), and

Subrahmanyam et al. (1997), showing that boards with greater oversight, measured by board independency,

will have a statistically significant positive impact on the M&A financial performance measured by CARs.

Secondly, according to the literature, blockholders would discipline and influence managers, who fail to

create shareholder value, by for instance threatening to take over the firm or replacing management.

Therefore, one might expect that having more blockholders on a firm is a good corporate governance

mechanism, and will lead to improved M&A financial performance of BHCs measured by CARs. However,



56

the results show, in the individual regression and the ‘full model’, a statistically significant and an

economically negative impact on the BHCs financial performance. Thus, the results from this study are in

conflict with previous literature by, amongst others, Bethel et al. (1998), and Denis and McConnell (2003).

An explanation for the negative impact on the BHCs returns might be the presence of blockholders might

be a seen as a threat of intervention and thus may erode managerial initiative, or their presence may lower

liquidity (Edmans, 2013). Another explanation might be that instead of maximizing shareholder value,

blockholders may extract private benefits, resulting in a conflict of interest between the blockholders and

the smaller shareholders (Edmans, 2013). At last, regarding CEO pay-for-performance, previous literature

states that in order to encourage CEO’s to maximize shareholders wealth, boards should create

compensation contracts that are performance or stock price oriented. Thus, one would expect higher levels

of CEO pay-for-performance, measured by the percentage of equity based compensation of a CEO, to have

a positive effect on M&A financial performance of BHCs measured by CARs. However, no statistically

significant results are found on the impact of CEO pay-for-performance. Therefore, no conclusion can be

drawn as there is no empirical evidence on this matter.

As the Global Financial Crisis, which lasted from the 1st of July 2008 to the 31st of July 2009,

occurred within the time period of our sample, we are interested its impact on the previously gathered

results. It is clear that during the Global Financial crisis BHCs had a rough time that resulted in an enormous

decline of M&As announced during that period. With regards to board independency, no empirical evidence

is found that before or after the crisis this corporate governance mechanism had a positive or negative

impact on M&A financial performance of BHCs surrounding the M&A announcement. When looking at

the second corporate governance mechanism, blockholders, the results indicate that having two or more

blockholders before the crisis have a statistically significant negative impact on its returns compared to

having one or zero blockholders. However, this is in contrast with previous literature as having more

blockholders present arguably leads to managers acting in the interest of the shareholders, hence creating

shareholder value. An explanation for the negative impact on the BHCs returns could be that the presence

of blockholders might cause an erosion of managerial initiative, or lower liquidity, or they may extract

private benefits, resulting in a conflict of interest between the blockholders and the smaller shareholders.

On the other hand, the results after the crisis show that having two or more blockholders has a statistically

significant positive impact on the returns of the BHCs, which is in line with previous literature. With respect

to CEO pay-for-performance, empirical evidence has been found on the fact that before the crisis, when

BHCs were paying a CEO more in equity, this resulted in a statistically negative impact on BHCs returns.

However, this is in contrast with previous literature that shows when rewarding a CEO with more equity is

a way to let them act in the best interest of the firm’s shareholders. A conceivable explanation could be that



57

before the crisis, CEOs who got paid in more equity based compensation became too optimistic and

overconfident as they wanted to increase their own wealth, which resulted in negative returns compared to

the market. In addition to the results before the crisis, the results from after the crisis indicate that CEO pay-

for-performance will have a negative impact on the returns of the BHCs.

The data set used for this study only contains 6 observations during the Global Financial Crisis.

This little amount of observations causes the variables of interest to be omitted due to collinearity when

doing a regression including firm fixed effects. Therefore, no conclusion can be drawn on the impact of the

variables of interest on M&A financial performance during the Global Financial Crisis.

As The National Commission on the Causes of the Financial and Economic Crisis in the US

declared in their report ‘Final Report of the National Commission on the Causes of the Financial and

Economic Crisis in the United States, 2011’ that the key cause of the crisis were the dramatic failures of

corporate governance at many important financial institutions (Beltratti & Stulz, 2012), one would expect

that BHCs with better governance performed better during and after the crisis. In addition, one would expect

that the corporate governance mechanisms that were having a negative influence on M&A financial

performance, and thus were lacking their function before the crisis, would have improved after the crisis

causing a positive relationship instead. However, there is only one corporate governance mechanism that

had a negative impact before the crisis, but improved the M&A financial returns after the crisis, namely:

blockholders. It can therefore be assumed that after the crisis, having two or more blockholders lead to

more intensively influenced managers who fail to create shareholder value by for instance a threat of the

blockholders to take over the firm or to replace management. This leads to managers acting in the interest

of the shareholders, hence creating shareholder value.

In result, these findings might have general implications for both the academic as well as the

corporate world. BHCs for example might design or redesign their corporate governance structures in line

with the findings of this study with the intention of increasing their M&A financial performance. As the

results over the entire time period show, board independency is important mechanism to increase M&A

financial performance. Therefore, BHCs for instance might want to rethink the way their board of directors

are build up. On the other hand, as having two or more blockholders is shown to have a negative impact on

M&A financial performance for BHCs, BHCs might want to readjust the allocations of their assets to make

sure they have zero or one blockholder present. From the academic point of view, the results of this study

add new value since new knowledge has been added in both the research field of corporate governance

along with M&A. Furthermore, it adds value to the research on the possible explanations of and the finding

of solutions for the high failure rate of acquisitions.



58

One major drawback from this study is the limited availability of data and the sample size of the

data sample. For conducting this study, several choices had to be made with regards to the selection criteria

of the data. There was limited availability of data on the corporate governance mechanisms, influencing

these choices. For some corporate governance mechanisms the data was only available between the years

2005 up to 2015, thus only this data could be used. In addition, this study had to use data that was collected

from several databases, and was merged in order to generate the variables. The process of merging

generated a relative large amount of missing data. As a result, a large body of observations was dropped

out. Thus from starting with 747 observations, after merging, we only had 138 complete observations

available. As one can state, the smaller the sample size, the further away the data gets from the entire

population, and thus the accuracy of the results will decrease. In addition, due to the small amount of

observations, the data set used for this study only contains 6 observations During the Global Financial Crisis.

This little amount of observations causes the variables of interest to be omitted due to collinearity when

doing a regression including firm fixed effects. Therefore, no conclusion can be drawn on the impact of the

variables of interest on M&A financial performance during the Global Financial Crisis.

Although previous studies have been based on a different time period, I do not believe this would

be a central explanation to the different impact shown in some results compared to the previous literature.

One explanation could be that corporate governance structures are industry specific, thus previous studies

on other industries could produce other outcomes (Adams & Mehran, 2003). This however is a speculation

and not based on actual data.

For this study only the effect of three corporate governance mechanisms are tested, however some

other corporate governance mechanisms which have not been tested could relate to the M&A financial

performance. In addition corporate governance consists of more than just the three components which have

been addressed for this study. Therefore, for further research I would suggest other corporate governance

mechanisms to be tested on BHCs during the time period 2005 up to 2015 using the same dependent variable.

In addition, I would advise to use a sample with more observations to get more accurate and reliable results

and which makes it able to test the impact of the variables of interest on the dependent variable during the

Global Financial Crisis. Also, it might be interesting perform a similar study on European BHCs and the

effect of corporate governance on its M&A financial performance. While there is a lack in data on corporate

governance for European based BHCs, it might become possible in the future to perform such a study.

However, as the crisis had no clear starting and ending point within Europe, this would be very hard to

study.



59

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Appendices

Appendix A. Multicollinearity

Table XX. Multicollinearity test on the variables of interest and the control variables

This table reports the multicollinearity test conducted on the variables of interest and the control variables. The test is conducted to

show that none of the variables are highly correlated, and so that no variables may be linearly predicted form the others. The sample

consisted of variables corresponding to 138 domestic M&A deals done by BHCs within the US which took place during the period

2005 until 2015.

Results of the multicollinearity test

Board

independency

Blockholders CEO Pay-for-

performance

Method of

payment

Firm size

Board independency 1

Blockholders -0.1132 1

CEO Pay-for-performance -0.2080 -0.0084 1

Method of payment -0.0392 -0.0478 0.0494 1

Firm size -0.0677 -0.3701 0.3205 -0.0498 1



65

Appendix B. Regression results from the OLS regressions

Table XXI. OLS Regression results on board independency and its effect on BHCs

cumulative abnormal returns

This table reports the simple OLS regression of the variable of interest ‘board independency’ and control variables ‘method of

payment’ and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs. The variable of interest





the M&A announcement. The regression is completed on four event windows, all with an estimation window of 100 days starting

at -30 trading days of the M&A announcement date (at t=0). The sample consisted of 138 domestic M&A deals done by BHCs

within the US which took place during the period 2005 until 2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]


(.014362)** *

.002263*** )

(.015590)** *

-.018682*** )

(.015201)** *

.009315*** )

(.012683)** *


(.004902)** *

-.005111*** )

(.004339)** *

-.001013*** )

(.003407)** *

.002364*** )

(.004492)** *

Firm size .009130*** )

(.001910)** *

.005048*** )

(.001806)** *

.000388*** )

(.001469)** *

.004004*** )

(.001716)** *

R² 0.0221 0.0275 0.0027 0.0196

*** p<0.01, ** p<0.05, * p<0.1



66

Table XXII. OLS Regression results on blockholders and its effect on BHCs cumulative abnormal returns

This table reports the simple OLS regression of the variable of interest ‘blockholders’ and control variables ‘method of payment’

and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs. The variable of interest is a

dummy that represents how many shareholders hold >5% of each BHC’s shares in the year of the M&A announcement, and takes

a value of ‘0’ when there is ≤ 1 blockholder, or takes a value of ‘1’ when there are ≥ 2 blockholders present. The control variable

‘Method of payment’ is a dummy variable that takes a value of ‘1’ when the M&A was paid by cash only, and takes a value of ‘0’

when the M&A was paid by another method. At last, the control variable ‘Firm size’ indicates how large a firm is by taking the

logarithm of the total assets of each BHC in the year of the M&A announcement. These regression is completed on four event

windows, all with an estimation window of 100 days starting at -30 trading days of the M&A announcement date (at t=0). The

sample consisted of 138 domestic M&A deals done by BHCs within the US which took place during the period 2005 until 2015.

Results of the regression on blockholders and cumulative abnormal returns

Event window [-10,10] [-5,0] [-1,1] [0,5]


(.003447)** *

-.006312*** )

(.002795)** *

-.011292*** )

(.003611)** *

.005295*** )

(.002697)** *


(.004957)** *

-.004781*** )

(.004290)** *

-.000136*** )

(.003328)** *

.001946*** )

(.004563)** *

Firm size .010870*** )

(.001984)** *

.004271*** )

(.001849)** *

-.001094*** )

(.001570)** *

.004701*** )

(.001768)** *

R² 0.0248 0.0315 0.0235 0.0225

*** p<0.01, ** p<0.05, * p<0.1



67

Table XXIII. OLS Regression results on CEO pay-for-performance and its effect on BHCs

cumulative abnormal returns

This table reports the simple OLS regression of the variable of interest ‘CEO pay-for-performance’ and control variables ‘method

of payment’ and ‘firm size’ on the dependent variable, Cumulative Abnormal Returns of the acquiring BHCs. ‘CEO pay-for-

performance’ is the last variable of interest, which stands for the percentage of equity payment over the total compensation a CEO

got in the year of the M&A announcement. The control variable ‘Method of payment’ is a dummy variable that takes a value of ‘1’

when the M&A was paid by cash only, and takes a value of ‘0’ when the M&A was paid by another method. At last, the control


announcement. These regressions are completed on four event windows, all with an estimation window of 100 days starting at -30

trading days of the M&A announcement date (at t=0). The sample consisted of 138 domestic M&A deals done by BHCs within the

US which took place during the period 2005 until 2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]

CEO pay-for-performance .005474*** )

(.005080)** *

-.002565*** )

(.005275)** *

-.006162*** )

(.006511)** *

.003979*** )

(.003639)** *


(.004808)** *

-.004917*** )

(.004317)** *

-.000243*** )

(.003739)** *

.001902*** )

(.004537)** *

Firm size .008863*** )

(.001880)** *

.005249*** )

(.001687)** *

.000774*** )

(.001423)** *

.003744*** )

(.001708)** *

R² 0.0214 0.0278 0.0036 0.0201

*** p<0.01, ** p<0.05, * p<0.1



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Table XXIV. OLS Regression results on the ‘full model’ and its effect on BHCs cumulative abnormal returns

This table reports the simple OLS regression of the ‘full model’ regressing all variables of interest ‘board independency’,

‘blockholders’, ‘CEO pay-for-performance’, and control variables ‘method of payment’ and ‘firm size’ on the dependent variable,

Cumulative Abnormal Returns of the acquiring BHCs. The variable of interest ‘Board independency’ is a percentage of the number

of independent board members divided by the total amount of members sitting on a board in the year of the M&A announcement.

The variable of interest ‘Blockholders’ describes how many shareholders hold >5% of each BHC’s shares in the year of the M&A

announcement, and is a dummy variable created that takes a value of ‘0’ when there is ≤ 1 blockholder, and takes a value of ‘1’

when there are ≥ 2 blockholders present. ‘CEO pay-for-performance’ is the last variable of interest, which stands for the percentage

of equity payment over the total compensation a CEO got in the year of the M&A announcement. The control variable ‘Method of



the total assets of each BHC in the year of the M&A announcement. These regressions are completed on four event windows, all

with an estimation window of 100 days starting at -30 trading days of the M&A announcement date (at t=0). The sample consisted

of 138 domestic M&A deals done by BHCs within the US which took place during the period 2005 until 2015.


Event window [-10,10] [-5,0] [-1,1] [0,5]


(.015096)** *

.008382*** )

(.016576)** *

-.007987***)

(.016748)***

.003587*** )

(.012681)** *


(.003853)** *

-.006388*** )

(.003082)** *

-.010705***)

(.003750)***

.004913*** )

(.002681)** *

CEO Pay-for-performance .001635*** )

(.005209)** *

-.001732*** )

(.005285)** *

-.003522***)

(.006399)***

.002772*** )

(.003704)** *


(.004878)** *

-.004521*** )

(.004291)** *

.000035***)

(.003451)***

.001773*** )

(.004675)** *

Firm size .010535*** )

(.001979)** *

.004357*** )

(.001679)** *

-.000725***)

(.001516)***

.004431*** )

(.001733)** *

R² 0.0254 0.0318 0.0253 0.0230

*** p<0.01, ** p<0.05, * p<0.1

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