The impact of cross-border mergers and acquisitions on shareholder wealth of Dutch acquiring companies

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The impact of cross-border mergers and acquisitions on

shareholder wealth of Dutch acquiring companies

Daniël Robert Coene

Author: D.R . Coene

Student Number: 10640363

Specialization: Economics and Finance

Thesis Supervisor: Dr. J.J.G. Lemmen

Bachelor Thesis Finance

University of Amsterdam

Faculty Economics and Business

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Statement of Originality

This document is written by Student Daniël Coene who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text

and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

COPYRIGHT STATEMENT

The author has copyright of this thesis, but also acknowledges the intellectual copyright of contributions made by the thesis supervisor, which may include important research ideas and data. Author and thesis supervisor will have made

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ABSTRACT

This paper investigates transactions in cross-border mergers and acquisitions involving Dutch acquiring firms in the period between 2001 and 2016. To see whether and how these

transactions affect the stock return of the acquiring firm, the abnormal returns are examined in three event windows, (-1,1), (-3,3) and (-5,5). Data is collected from 147 mergers and

acquisitions of Dutch-based bidding firms on non-Dutch target companies. Both private and public firms are included for both target and acquiring companies. The results show that cross-border mergers and acquisitions of Dutch-based bidding firms on non-Dutch target firms have a positive but insignificant effect on the stock return of the acquiring company. Cross-border mergers and acquisitions announced in the period of the economic crisis of 2007-2008 resulted in lower CARs than mergers and acquisition in the rest of the period 2001-2017 with a

significant effect on a 10% level.

JEL-classification : G14, G34

Key-words: Mergers; acquisitions; event study; cross-border; Dutch; shareholder value

Write direct, en sober. Het is te wollig.

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CHAPTER 1. Introduction

During the last 15 years there has been an enormous growth of mergers and acquisition (M&A) activity around the world. The globalizing economic trend of the 21st_{century stimulates} this even more. Deregulation and increased globalisation resulted in substantial increases in the amount of cross-border mergers and acquisitions around the world. This international

accessibility makes it possible for firms to not only take part in domestic mergers and

acquisitions, but also focus on taking over firms outside of their base country. On a global scale, cross-border M&As accounted for 26% of the value of total acquisitions around the world. Evidently, cross-border M&As are more prevalent than ever, and now account for 80% of all foreign direct investment by industrialised countries (Conn et al., 2005; UNCTAD, 2000).

When investigating the history of mergers and acquisitions, remarkable are the cyclical waves in which M&A transactions occur. Goergen and Renneboog (2004) argue that five different waves took place in the period from 1880 – 2000. Europe experienced its first substantial increase in M&A transactions during the second industrial revolution which led to the first wave of 1880 - 1904. The main reason for this increase was the development of creating monopolies in European countries. After this, the twentieth century contained four more waves: in the 1920’s, around the 1960’s, in the 1980’s and the last one in the period from 1993 – 2000. The latter was triggered by the development of new European stock exchanges and the

expansion of the telecommunications and internet industries. Reasons for this development were the globalization process, technological innovation and the deregulation and privatisation trend in this period. Thereafter, in 2001, these industries faced a crash in consumer confidence and caused a substantial decrease in merger transactions around the world (Goergen and Renneboog, 2004; Martynova and Renneboog , 2006).

As Martynova and Renneboog (2007) found, this decrease recovered and since mid-2003 M&A activity expanded due to global expansion and increasing cross-border M&A. The

transactions became global orientated and significantly higher in value, compared to previous years. This expansion lasted 5 years until 2008, when the global and financial economic crisis took place. With a remarkable decrease in M&A activity during the crisis, the world economy now is recovering together with the amount of mergers and acquisitions. As UNCTAD (2016) reports, global Foreign Direct Investments (FDI) increased with 38% in 2015 to $1.76 trillion and reached its peak since the crisis in 2008. The principal factor behind this global rebound was the increase in cross-border M&A from $432 billion in 2014 to $721 billion in 2015. With the recovery of the world economy, the increase in corporate profit and the associated stock prices boosted the value of cross-border M&A even more in 2017 (UNCTAD, 2017). Today’s surge in cross-border M&A transactions is an indication of a potential seventh merger wave and

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gives great incentives to investigate impact on shareholder perspective.

The global increase in mergers and acquisitions influences the Dutch market. Dutch companies are increasingly involved in international takeovers. In 2016 there has been a 12% increase of M&As on the Dutch market. The amount of transactions increased from 578 in 2015 to 647 in 2015. Compared to the rest of the world (+1%) and Europe (+6%), the Dutch market distinguishes from and exceeds the global trend (KPMG DAU) . The globalizing trend in the Dutch economy is affected by multiple factors. First, The Netherlands belongs to the top economic stable countries in the world. Next to high quality infrastructure and technological innovation, the openness of the Dutch economy for cross-border trade plays an important role in its growth (KPMG GPI). In addition, the taxation of cross-border mergers and acquisitions have been revised by the Dutch government in favour of global expanding Dutch companies (KPMG Taxation). The stability of the Dutch economy and the growth-stimulating governmental policy makes the market attractive for foreign target firms to merge with Dutch acquiring firms. Second, the recent appreciation of the euro stimulates the Dutch globalization trend. In 2017, the euro-dollar exchange rate increased with 15.9% to 1.24 and reached its peak since 2014 (Yahoo! Finance). The rise in the value of the euro gives Dutch companies more purchasing power when taking over dollar-based companies and gives incentives for international

expansion. Lastly, with 32% of Dutch citizens from 25-64 years old holding a university degree, the education rate of The Netherlands belongs to the highest of the world. In comparison, the Dutch education rate exceeds the average of the OECD countries of 24%. (OECD 2014). This makes The Netherlands a great source for high-graded expat employees and gives even more reason for foreign firms to merge with Dutch companies.

The recent 64 billion euro takeover from Royal Dutch Shell of UK-based company BG group, the NXP takeover of Freescale and the Ahold/Delhaize merger are interesting cases of international expansion from Dutch-based companies. Together with the growth-stimulating governmental policy, this gives great incentive to investigate the actual effect of these mergers and acquisitions. Subsequently, this raises a variation of interesting questions; Should the Dutch government stimulate domestic companies to expand internationally? What effect does these cross-border mergers and acquisitions have on shareholder value? What variables influence M&A performance? Hence, the research question in this thesis: “Do the effects of cross-border mergers and acquisitions of Dutch acquiring companies have a positive effect on the acquiring companies’ stock prices, when investigating the period of 2001 – 2016?”

To investigate if international expanding policy by the Dutch government is desirable, this paper studies the impact of cross-border mergers and acquisition with Dutch-based acquiring companies. To do research on this matter, M&A performance is measured by evaluating stock return of the acquiring company around the acquisition announcement date.

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The impact on stock return is estimated in the form of Cumulative Abnormal Returns (CARs) to analyse the short-term effect of M&A around the announcement date in three different event windows: (-1,+1), (-2,+2) and (-5,+5). This is achieved by using the methodology of an event study. The model used in this paper is based on the market-model event study described in Mackinlay (1997). As previous research has shown, the market-model is a valid method to determine the short-term effect on stock-return of the acquiring firm.

Empirical evidence on the short-term effect of M&A around the announcement date can be found in several previous studies. The focus of these studies varies from domestic to cross-border transactions, public and/or private companies, and examined the effect on stock return of both target and acquiring companies. Multiple studies focussed on countries like the UK and US (Andrade et al., 2001; Fuller et al., 2002; Moeller et al., 2004) Most studies are related to periods before the global economic and financial crisis. As UNCTAD (2016) reports, Foreign Direct Investment in Europe together with the amount of cross-border M&A, is on the rise again. Accordingly, this study distinguishes itself by focusing on cross-border transactions in the period of 2001 – 2017, including the period during and after the financial crisis. As there is no empirical literature about the effect on Dutch acquiring companies yet, this paper will contribute new evidence even more by focusing merely on acquirers in the Dutch market.

For this study, data is collected from 147 mergers and acquisitions of Dutch-based bidding firms on non-Dutch target companies. Both private and public firms are included for both target and acquiring companies. To be able to evaluate the effect on the stock return of the bidding firm, only public acquiring companies will be included. To eliminate biasedness financial organizations and utilities are excluded for both the acquirers and targets

The remainder of this thesis continues in chapter 2 with a review of related literature on M&A performance, together with the formation of the hypotheses relevant in this study.

Thereafter, a description of the data used in this paper is described in chapter 3. The

corresponding methodology used to set up the model is explained in chapter 4. Subsequently, chapter 5 displays and discusses the results of this study. Finally, chapter 6 concludes on the main thesis findings and discusses limitations and suggestions for future research.

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CHAPTER 2. Related literature and hypotheses development

2.1 General M&A concepts

Before going into detail with the descriptive analyses, it is necessary to define the importance of mergers and acquisitions and explain the incentives behind this phenomenon. Schoenberg (2006) defines an acquisition as the purchase by a ‘bidder’ company of another ‘target’ company. In exchange for the shares of the target company, an acquiring company can either offer cash or its own shares. After this transaction the acquirer controls all the assets of the target company. As an acquisition can be referred to as a takeover, a merger on the other hand is a combination of two separate firms. In a merger, shareholders jointly become the owners of the new combined firm. While the terms ‘mergers’ and ‘acquisitions’ do have narrow differences, for example in legal structures, both share many common motives and criteria in their success (Schoenberg, 2006). This paper, therefore, does not distinguish mergers from acquisitions and both concepts will be used interchangeably

Buckley & Ghauri (2002) categorize three different sorts of M&A: horizontal, vertical and conglomerate. Horizontal mergers and acquisitions are between two firms competing in the same industry, while conglomerate M&As are between companies in unrelated businesses. Contrary, vertical mergers are between firms which are in the same industry but are operating at different levels in the industry’s supply chain. M&As can either be ‘friendly’ or ‘hostile’. A takeover is called friendly if the board of the target firm agrees to be taken over by the bidding firm. When the board of the target firm does not agree on the acquisition, and the bidding company goes directly to the shareholders or try to replace the management, it is called hostile. Previous research on shareholder performance of both friendly and hostile takeovers has been done by Goergen and Renneboog (2004). Their study reports positive announcement returns for friendly mergers, while the negative short-term is statistically significantly negative.

2.2 Motives behind M&A

Individual firms can have different motives for acquiring another company. Goergen and

Renneboog (2004) state that a motive for both domestic and cross-border M&A is the creation of value by synergies. They classify two types of synergies: operating and informational synergies. The first relates to creation of value by economies of scope or scale and the second is of interest when the value of the combination of two firms is higher than their separate value summed up. Seth et al. (2000) define the latter as the ‘synergy hypothesis’ and specify two additional motives for both types of acquisitions: the ‘managerialism’ and ‘hubris’ hypothesis. The

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maximize their own utility without taking account for the company’s shareholders. The hubris hypothesis suggests that managers of the bidding firm wrongly evaluate the value of the target company and pursue the acquisition in the assumption of a correct evaluation of the target value. Seth et al. (2000) state that domestic takeovers in the U.S. are mostly explained by the synergy motive. From their empirical results, it can be concluded that much of cross-border acquisitions can also be explained by the synergy hypothesis. On the other hand, the hubris hypothesis explains part of the value creation in the majority of cross-border M&A, whereas value destruction is more driven by managerialism (Seth et al., 2000).

In addition, Schoenberg (2006) classifies motives in three different categories: strategic, managerial and financial motives. Firstly, firms can undertake an acquisition out of strategic purposes. By taking over another company, the acquiring firm is able to either increase its power in an existing product market or enter new markets and/or geographical territories. Secondly, acquisitions can contribute to the managerial self-interest of the acquiring firm. Managers can increase their power by increasing the size of the acquiring company via an acquisition. Maximizing shareholder value is unlikely when M&As are merely motivated by managerial self-interest. This is due to two reasons. First, managers who take over other

companies for their own purpose are less focussed on prior economic analyses to investigate the actual effect on stock return. Second, self-interested managers are willing to pay a higher price premium than economically is desired. As Hayward and Hambrick (1997) find, companies with a high proportion of executives in the board of directors (BoD) are likely to exhibit a higher bid premium. Meanwhile, companies with a strong independent BoD can reduce managerial self-interest motives of executives. Lastly, companies can be motivated for mergers and acquisitions because of financial benefits. As Schoenberg (2006) states, this motive is especially attractive for public acquirers with a high price/earnings ratio compared to the target firm. Such companies are able to increase their earnings per share on the short term through M&A activity.

Furthermore, acquiring firms can exploit financial benefits due to accumulated tax revenue. As KPMG TAX reports, the tax regulation in the Netherlands are since 2013 revised and in favour of acquiring companies.

Although managerial and strategic motives do exist, maximization of shareholder value is the prevalent incentive for firms to participate in an acquisition. Hence, this paper evaluates the outcome of financial motives of the acquiring firm and examines what effect M&A has on its shareholder value. (Schoenberg, 2006)

2.3 Domestic vs. Cross-Border

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announcement returns for the US in the period of 1985 – 1995. To reflect on the differences between these two they point out the cross-border effect. Although both cross-border and domestic M&As are influenced by multiple similar factors, acquisitions in other countries do have advantages and disadvantages. For example, acquisition of foreign assets can exploit benefits for the bidder firm in the form of advanced technology, favourable governmental policies, and risk management.

As Harris and Ravenscraft (1991) state, cross-border M&A can create value by exploiting economies of scale and scope in different areas such as Research and Development (R&D), production or marketing. For instance, firms can spread their R&D fixed costs over multiple international markets. Whilst cross-border M&As bring more costs than domestic ones, international diversification and the access in new markets can create additional benefits (Danbolt and Maciver, 2012). There are multiple incentives for a firm to choose cross-border acquisitions as their strategy for foreign direct investment. The availability of new markets and specific specialized resources, the possibility of achieving product efficiencies and seeking for a reduction in policy risk are examples of those (Cooke, 1988).

2.4 Empirical findings

Empirical evidence on the short-term effect of M&A around the announcement effect can be found in several previous studies. The focus of these studies varies from domestic to cross-border transactions, short- and long-term effects, public and/or private companies, and examine the effect on stock return of both target and acquiring companies. Multiple studies mainly focus on countries like the UK and US.

Conn et al. (2005) examine the short- and long-term announcement effect on stock returns of UK acquirers, of public and private targets in both domestic and cross-border

acquisitions. They significantly find zero and negative (-0.99%) announcement effects on public targets, of cross-border and domestic transactions, respectively. In contrast, they find a positive announcement effect on private targets on both types of acquisitions. Overall, results show that cross-border M&A result in lower announcement returns compared to domestic transactions. Fuller et al. (2002) find a positive effect (2.08%) of acquiring shareholder on private target firms in domestic transactions, and a negative effect (-1%) when taking over a public firm. Similarly, Moeller et al. (2004) report positive and negative CAR effects of private and public target firms, respectively. They find a significant negative effect on public targets of -1%, and positive effect of 2.08% for private targets.

To find empirical evidence on the effect of cross-border M&A on the shareholder value of the acquiring firm, multiple studies can be examined. On the long-term, the majority of studies

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found significant negative long-term effects on the acquiring stock return and focused on the US and UK. Papers from Conn and Connell (1990), Danbolt (1995) and Aw and Chatterjee (2004), used the marketmodel and find significant negative longterm CARs for private targets of -11.5%*, -9.8%**, -3.7 and -24.4%**, respectively.

To examine previous results on the short-term, various papers can be found to see what effect mergers and acquisitions have on the acquiring shareholder value. The previous reported findings of Fuller et al. (2002) combined, result in an overall significant positive effect on the acquirer CAR of +1.77%. This corresponds with the findings of Ma et al. (2009), with a

cumulative abnormal return of +1.28%. Goergen and Renneboog (2004) analyze the short-term effect of large European mergers and acquisitions on both target and bidding firms. They find an insignificant announcement effect of +9% for target shareholders and a significant

announcement effect of +0.7% for bidders. Furthermore, results show the short-term abnormal return for the shareholders of the bidding firm for friendly mergers to be positive of +2.2%. Contrary, for hostile takeovers the abnormal return at the announcement date is significantly negative with an abnormal return of -2.5%. This shows that the characteristic of a takeover, either friendly or hostile, does influence shareholder value for the bidding firm.

2.5 Hypotheses

The focus of this thesis is to test the short-term effect of cross-border mergers and acquisitions on shareholder value of Dutch-based acquiring firms, with non-Dutch target firms around the announcement date. Previous literature have shown various effects on both target and acquiring firms and differ in either domestic or cross-border acquisitions. As noted above, Goergen and Renneboog (2004) and Fuller et al. (2002) both show positive announcement date returns for acquiring shareholders. There is no strong evidence about M&A effect on shareholder revenue with Dutch acquiring firms. Hence, the first hypothesis for this paper is the wealth hypothesis:

H1: Cross-border mergers and acquisitions of Dutch-based bidding firms on non-Dutch target firm have significant effect on the stock return of the acquiring company.

Because the recent appreciating trend of the euro/dollar exchange rate, it is interesting to investigate whether U.S. based targets are preferred for mergers and acquisition by Dutch acquiring firms. As table 1 shows, the amount of targets are largely based in the United States. Because of relative narrow relationship in M&A activity between The Netherlands and the U.S., the companies are expected to merge more easily. Therefore, the expectation is that M&As on

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U.S. target is higher than the rest of the world. Hence, the second hypothesis in this study is the geographical hypothesis:

H2: Cross-border mergers and acquisitions create higher CARs for the bidder when the target firm is based in the U.S. compared to the rest of the world.

To further distinct the aim of this paper from previous empirical studies, a third hypotheses is constructed regarding the recent financial and economic crisis. With a remarkable decrease in M&A activity during the crisis, M&A activity in the years 2007 and 2008 tend to be affected. This raises the interesting question if there is a significant difference in the mergers and acquisitions announced in the period of 2007-2008? The circumstances of the financial crisis are expected to negatively affect the abnormal returns. Hence the third hypotheses is the time hypothesis:

H3: Cross-border mergers and acquisitions announced in the period of 2007-2008 result in lower CARs than mergers and acquisition in the rest of the period of 2001-2017.

As Goergen and Renneboog (2004) reports, the method of payment in which the bidding firm pays for the takeover is an important factor in explaining the effect on stock return. If the managers of the bidding company thinks their stocks are undervalued, they prefer to pay with cash. Vice versa, a company with overvalued stocks the preferred method of payment tend to be with stocks. Several studies contribute evidence on the effect of method of payment on

shareholder value. Empirical results show that method of payment affects target firms in contrast to acquiring firms. Goergen and Renneboog (2004) find a negative effect of transaction paid with cash for the bidding firm and large positive effect for the target. Transactions paid with cash are therefore expected to negatively affect the abnormal returns of the bidding firm. Hence the fourth and last hypotheses in this study is the financial hypothesis:

H4: The transaction payed in cash have a higher cumulative abnormal return than the ones financed by other method of payments

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CHAPTER 3. Data description and methodology

3.1 Methodology

To test the effect of cross-border M&A on the acquirers’ shareholder value around the

announcement date, the methodology of an event study has been used (MacKinlay, 1997). With an event study it is possible to determine how an event affects the value of a firm. As Mackinlay (1997) states, the initial task of an event study is to identify the event and determine the event window over which the stock returns will be examined. In perfect conditions the effect of an event is displayed in one day and the stock price can fully adjust on the announcement date. On the other hand, because of delayed information and the leakage of data and rumours, this is not always the case. To get a complete overview of the effect of the event, days prior and after the announcement date should be included. Therefore, for this paper an event window is

constructed of one day prior and after the announcement date (-1,1). This makes it possible for the stock prices to fully adjust and reflect the change caused by the transaction.

Secondly, to be able to determine the abnormal returns around the announcement date, a benchmark model must be chosen. As the previous section showed, most of previous papers used the market model (MM) to calculate the abnormal returns (Franks et al., 1991; Schwert, 1996; Chang, 1998; Datta et al., 2001). The market model relates the return of a stock to the return of the market portfolio, and therefore eliminates market biasedness in the results. While the market model is the most used event study model for identifying the abnormal returns, there are some critiques on it. As Danbolt (2012) states, missing variables and other measurement errors can cause for some trouble in the market model. On the other hand, Kothari and Warner (2007) report that the impact of the chosen benchmark has a negligible effect on the estimated returns. Therefore, the market model is the appropriate model to use in this study. To calculate the Abnormal Return the following equation is used:

𝐴𝑅_𝑖𝑡 = 𝑅_𝑖𝑡− 𝑁𝑅_𝑖𝑡

Where 𝐴𝑅_𝑖𝑡 is the Abnormal Return, 𝑅_𝑖𝑡 is the actual Return and 𝑁𝑅_𝑖𝑡 the normal return for a given firm 𝑖 at time 𝑡 . To calculate the return of a stock at a given time, the market model is as follows:

𝑅_𝑖𝑡 = 𝛼_𝑖+ 𝛽_𝑖𝑅_𝑚𝑘𝑡+ 𝜀_𝑖𝑡

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Here, 𝑅_𝑖𝑡 is the return of a specific security 𝑖 at time period 𝑡. Furthermore, 𝛼_𝑖, 𝛽_𝑖 and 𝜀_𝑖𝑡 are parameters determined by the model. 𝛼_𝑖 is the intercept estimated by the model for a certain security 𝑖. 𝛽_𝑖 is a parameter for a specific firm 𝑖 of the relationship between the market return and the return of the security. Lastly, 𝜀_𝑖𝑡 is the residual determined by the model and is assumed to be normally distributed with mean zero. To analyse the relationship of the stock return with a benchmark return, the Market Return is calculated with the following equation (𝑅_𝑚𝑘𝑡):

𝑁𝑅_𝑖𝑡 = 𝛼̂ + 𝛽̂𝑅_𝑚𝑘𝑡

Where 𝛼̂ and 𝛽̂ are the predicted parameters of the model. To be able to estimate the normal return, an estimation window is set based on previous studies. Based on Mackinlay (1997) and Brown and Warner (1985), the estimation window in this study is set to 250 days. To exclude biasedness in the estimate of the normal return, a gap of 10 days prior to the announcement date is included. Hence, the estimation window in this study is denoted as (-260,-10). To calculate the abnormal return (AR), we have to subtract the market return from the observed return for a certain security 𝑖. Accordingly, the formula for the abnormal return can be rewritten as:

𝐴𝑅_𝑖𝑡 = 𝑅_𝑖𝑡− (𝛼̂ + 𝛽̂𝑅_𝑚𝑘𝑡 )

To calculate the abnormal return on the stock of an individual firm for each event period, the average of the summation of the abnormal returns in the chosen event window is taken. This is calculated by the formula denoted as the Abnormal Average Returns (AARs):

𝐴𝐴𝑅_𝑖𝑡 = 1

𝑁∑ 𝐴𝑅𝑖𝑡 𝑁 𝑖=1

In this paper, an event window is constructed of one day prior and after the announcement date (-1,1). This makes it possible for the stock prices to fully adjust and reflect the change caused by the transaction. As Andrade et al. (2001) states, the impact on stock return can significantly differ in various event windows. To compare different event windows and check for robustness, two extra event windows are added: (-2,2) and (-5,5). To calculate the abnormal return inside these windows we use the Cumulative Abnormal Return (CAR):

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𝐶𝐴𝑅_𝑖(𝑡₁𝑡₂) = ∑ 𝐴𝑅_𝑖𝑡 𝑡2 𝑡1

Finally, the mean of the sum of the CARs for the different firms is taken, to be able to calculate the effect over the period of the event window rather than on a specific event date. The formula for the Cumulative Average Abnormal Returns (CAARs) for each stock 𝑖 is:

𝐶𝐴𝐴𝑅_𝑖 = 1

N∑ 𝐶𝐴𝑅𝑖(𝑡1𝑡2) 𝑁

𝑖=1

3.2 Data and descriptive statistics

For this paper, data is collected from ZEPHYR. The sample contains cross-border mergers and acquisitions on Dutch-based target companies with non-Dutch as the acquirers, in the period of 2001 - 2017. Included are the names of both the acquirer and target companies, the acquirer country code, the type of deal and the International Securities Identification Number (ISIN) of the acquirer. The initial dataset consists of 308 observations of different cross-border

transactions.

Furthermore, required for analysing the short-term effect on shareholder value, the date of announcement and the final date of completion are added in the dataset. Only completed-confirmed deals are included in the time period, whereas rumours and uncompleted-confirmed deals are excluded. To make sure the transaction is big enough, the minimum deal value is set to 1 million euro’s. To eliminate incomplete mergers and acquisitions, the data is restricted to transactions that exclusively take over 100% of the target firm. This eliminates biasedness caused by different acquired portions of the target by the same acquirer, and ensures the analyses to fully analyse the effect on complete mergers and acquisitions.

As previous stated, the acquiring company is set to be listed, to be able to analyse the effect on the stock return of the bidding firm. While the acquiring companies are merely based in the Netherlands, the target companies have a wide spread of different nationalities and come from different regions of the world. The majority of the acquirers come from the United States. Furthermore, neighbouring countries like the UK, Germany and Belgium also have a significant share in the total cross-border transaction. The international mergers and acquisitions are ordered per target country and can be found in table 1.

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To prevent biasedness, overlapping acquisitions of the same acquirer must be

eliminated. When multiple announcement dates fall into the ±1, ±3 or ±5day event window by the same acquirer, the observations are removed. Furthermore, financial organizations, utilities and public administrative institutions are eliminated to prevent biasedness of these exceptional industries. This is done by collecting the Standard Industrial Classification (SIC) codes and remove all the companies with SIC codes from 40-49, 60-67 and 90-91. The dataset contained two Dutch based targets and US acquiring firms, which have been manually been removed. To obtain information about companies’ daily stock prices and the corresponding market return, Thomson Reuters DataStream is used. After eliminating the undesirable observations, DataStream provided the stock prices for the acquiring companies related to the estimation windows. The companies that did not have sufficient information about the stock price for the complete estimation and event windows were excluded. To be able to calculate the market return, the closing price of the market is obtained from the period 2000-2017. Because the remaining Dutch acquiring companies are all listed on the Amsterdam Exchange index, the AEX closing prices are used as the benchmark return. After successfully eliminating all the unwanted observations, the final sample dataset contains of 147 observations.

3.3 Cross-sectional regression model

To analyse the effect on the cumulative abnormal return, the dependent variable will be

regressed on various control variables. The model contains four different explanatory variables and is constructed as follows:

0 10 20 30 40 50 60 US G re at Britain G erm an y Ot h er Ru ss ia Be lgi u m It aly Fran ce Can ad a Sw itze rlan d Au stra lia De n m ar k Sp ain N o rw ay Au stria Bu lgari a Braz il C h ina

M&As per target country

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𝐶𝐴𝑅𝑖 = 𝛽₀+ 𝛽₁∗ 𝑈𝑆 + 𝛽₂∗ 𝐶𝐴𝑆𝐻 + 𝛽₃∗ 𝐶𝑅𝐼𝑆𝐼𝑆 + 𝛽₄∗ 𝐷𝑒𝑎𝑙𝑣𝑎𝑙𝑢𝑒

Here, the dependent variable 𝐶𝐴𝑅𝑖 is the Cumulative Abnormal Return relating to the three different event windows: (-1,1), (-2,2) and (-5,5). The independent variable US is constructed as a dummy that equals 1 when the target firm is based in the United States and 0 if otherwise. Observing the results of the regression with respect to US makes it possible to analyse effect of US-based countries in comparison to the rest of the world. Hence, the second hypothesis can be explained. The second controlled dummy variable is CASH. M&As can be financed with various method of payments. The acquiring firms in this sample are paying with either cash, stock or a mix of both. Because previous studies have shown that the method of payment is an important factor in explaining the CAR, the CASH variable is added. This variable equals 1 if the transaction is completed by payment in cash and 0 when a different method of payment is used. To be able to analyse the effect of mergers and acquisition taking place in the economic and financial crisis in the period 2007-2008, the dummy variable CRISIS is included. For the transactions falling in the period 2007-2008 the variable is equal to 1. For the remaining the CRISIS variable is set to 1. According to various studies, the deal value of the transaction influences the effect on

shareholder value of the acquiring firm. As Fuller et al. (2002) find, relative high deal values will positively affect the abnormal return. Finally the independent control variable Dealvalue is added. To reduce the error of large outliers, the natural logarithm of the size of the deal is taken.

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CHAPTER 4. Empirical Results

In this section the main empirical findings of this study are presented. First, the descriptive statistics concerning the Cumulative Abnormal Return are displayed. Subsequently, a conclusion can be drawn on the first wealth hypothesis for this study. Secondly, the results of the cross-sectional analyses are shown. The tests for significance is done by a cross-cross-sectional t-test based on the three significance levels: 1%***, 5%** and 10%*. Afterwards, a conclusion is drawn on the remaining three hypotheses: geographical(H2), time(H3) and financial(H4) hypotheses.

4.1 Cumulative Abnormal Returns (CARs)

To analyse the CARs around the different event windows the descriptive statistics are

summarized. After collecting all the needed information, a t-test is used to see whether the CARs significantly differ from zero or not. Subsequently, the first wealth hypothesis can be concluded. Analyses will show whether cross-border mergers and acquisitions of Dutch bidding firms on non-Dutch targets have an effect on the stock return of the acquirer. Table 3 summarizes the statistics for the CARs of the three different event windows: (-1,1), (-2,2) and (-5,5).

As shown in table 2, a positive CAR of +0.17% is found for the (-1,1) event window. This indicates a positive abnormal return for Dutch acquiring companies operating in cross-border M&A. With a t-value of 0.4036, it can be concluded that the abnormal returns are positive but insignificant. It is not possible to conclude the CARs to be significantly differ from zero. On the other hand, the short-term positive abnormal return seems to be similar to multiple previous empirical findings. To make up for the insignificance, the results are compared with significant findings on the 3-day event window CARs in previous literature. The results are in line with the findings by Goergen and Renneboog (2004). They find a significant positive announcement effect of +0.7%. In addition, Moeller et al. (2009) report a +1.10% CAR significant at 1%. Despite the insignificant findings, taking into account previous empirical findings indicates the CAR to be positive.

Furthermore, the effect of the (-2,2) event window are positive with a CAR of +0.5%. The corresponding t-value of 1.1877 indicates that the null hypotheses cannot be rejected at a 1%, 5% or 10% significance level. Nevertheless, the 5-day window results in a higher rejection window increases, the CAR shows to be negative. The CAR for the (-5,5) event window is negative of -0.006%. With a low t-value of -0.1023 the negative result is highly insignificant and it cannot be concluded that it is different from zero. The (-2,2) window seems to be the best choice to evaluate the short-term effect on the cumulative abnormal returns.

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Table 2. Descriptive statistics of dependent variable

Analysing the descriptive statistics of the CARs around the different event windows makes it possible to make a conclusion on the first wealth hypothesis. As the CARs are not significantly different from zero, the first hypothesis is rejected. Hence, cross-border mergers and acquisitions of Dutch-based bidding firms on non-Dutch target firms do not have a significant effect on the stock return of the acquiring company.

4.2 Regression Analyses

In this section the cross-sectional regression analyses are presented. In addition to the findings of the abnormal returns for the three different event windows, a further investigation is done to see which variables explain the cumulative abnormal returns. This is done by a multiple

Ordinary Least Square (OLS) regression on the four different explanatory variables. To be able to make a conclusion on the second geographical hypotheses , the dummy variable US is regressed to see what effect it has on the CARs. Furthermore, to investigate if the transaction completed during the financial crisis in the period of 2007-2008 affects the CAR, the same is done for the dummy variable CRISIS. Lastly, the effect of the method of payment is analysed by regressing the dummy variable CASH on the CARs. Hence, a conclusion for the fourth and last hypothesis can be given.

Table 3, 4 and 5 summarize the regression analyses of the ±1, ±2 and ±5 day event window respectively. As shown, all of the four explanatory variables are negatively affecting the CAR in the different windows. The negative effect of the US variable of -0.0057 is not in line with the predictions previously made. The high US-based target ratio was expected to indicate narrow relationships in M&A activity between the two countries, causing a positive effect on the CARs. A possible reason for this can be that the cultural differences between the Dutch and U.S. companies are still higher than Europe countries geographically close to The Netherlands. However, the p-values show that the effect is not significant. Therefore, the second geographical hypotheses is rejected. Hence, cross-border mergers and acquisitions do not create higher CARs for the bidder when the target firm is based in the U.S. compared to the rest of the world. The

Variable Obs. CAAR Std. Dev. t-statistic Min. Max.

CAR (-1,1) 147 0.17% .04974 0.4036 -.0065 .0098

CAR (-2,2) 147 0.52% .0531 1.1877 -.0035 .01386

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insignificant results indicate that the CARs are not affected by the fact that the target firm is US-based.

Table 3. Regression analyses on (-1,1) event window

*10% significance level;**5% significance level; ***1% significance level

*10% significance level;**5% significance level; ***1% significance level Variable Coefficient Std. Err. t-statistic p-value 95 % Conf. Interval

US -.0057 .0090 -0.63 0.527 -.0236 .0121

CASH -.0001 .0083 -0.01 0.993 -.0165 .0164

CRISIS -.0095 .0103 -0.93 0.355 -.0298 .0108

LogDealSize -.0014 .0020 -0.71 0.481 -.0055 .0026

Constant .0215 .0228 0.94 0.346 -.0235 .0666

Variable Coefficient Std. Err. t-statistic p-value 95 % Conf. Interval

US -.0079 .0096 -0.82 0.413 -.0268 .0111

CASH -.0025 .0088 -0.28 0.779 -.0199 .0150

CRISIS -.0167 .0109 -1.53 0.128 -.0382 .0048

LogDealSize -.0015 .0022 -0.71 0.480 -.0058 .0027

Constant .0296 .0242 1.22 0.223 -.01812 .0774

Variable Coefficient Std. Err. t-statistic p-value 95 % Conf. Interval

US -.0098 .0124 -0.79 0.431 -.0343 .0147

CASH -.0038 .0114 -0.33 0.741 -.0263 .0188

CRISIS -.0235 .0141 -1.67 0.097* -.0513 .0043

LogDealSize -.0016 .0028 -0.56 0.577 -.0071 .0039

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To analyse the effect of transactions happened in the financial crisis, the dummy variable CRISIS is examined. The CARs are negatively affected in all of the three event windows. Although the effects in the (-1,1) and (-2,2) are insignificant, the significance tend to grow together with the size of the event window. As table 5 shows, the CRISIS variable affects the CAR in the ±5 day event window with -0.025. With a p-value of 0.09 the effect is significant on a 10% level. This corresponds with the previous stated expectations. The third time hypothesis can therefore be concluded for the (-5,5) window. Cross-border mergers and acquisitions announced in the period of 2007-2008 result in lower CARs than mergers and acquisition in the rest of the period of 2001-2017. With a remarkable decrease in M&A activity during the crisis, M&A activity in the years 2007 and 2008 tend to be affected.

The variable CASH negatively affects the CAR on the three different windows. The effect is the highest in the (-2,2) event window. The negative effects of the cash method of payment is in line with expectations and corresponds with the weakly negative results of Goergen and Renneboog (2004). Even though the negative coefficient was expected, the high p-values indicate to not significantly affect the CARs. Thus, the last financing hypotheses is rejected. The transaction payed in cash do not have a higher cumulative abnormal return than the ones financed with other method of payments. Looking at previous empirical findings, the

insignificant negative can be explained. As Faccio et al. (2005) states, bidding firms are likely to choose payment with equity instead of cash if the firm is financially constrained with high leverage and have relatively low total assets. Further research can be done on the financial stability and the total assets of the Dutch bidding firms to explain the effect of method of payment.

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CHAPTER 5. Conclusion

This study investigates the impact of cross-border mergers and acquisitions on shareholder wealth of Dutch acquiring companies. The research question central in this study is: “Do the effects of cross-border mergers and acquisitions of Dutch acquiring companies have a positive effect on the acquiring companies’ stock prices, when investigating the period of 2001 – 2016? . The research consists four different hypotheses: wealth, geographical, time and financing hypotheses. The results are found by using the methodology of an event study on 147

observations of cross-border mergers and acquisitions. To investigate the wealth hypothesis about the effect on the abnormal return of the bidding firm, analyses of the CARs are executed on three different event windows: (-1,1), (-2,2) and (-5,5). Finally, a multiple OLS regression is used to investigate the effect of the explanatory variables and a conclusion is drawn on the remaining three hypothesis.

Analysing the descriptive statistics of the CARs around the different event window gives a conclusion on the first wealth hypothesis. The results show that the CAR in the (-1,1) event window is positive of +0.17%. For the (-2,2) event window, the CAR resulted in a positive +0.52% effect. The higher CAR compared to the shorter event window, can indicate that the stock prices did not fully adjust in the ±1 day event window. For the (-5,5) event window the CAR is small and negative. Conducting a t-test on the different CARs shows that they do not significantly differ from zero. Therefore, the wealth hypothesis is rejected. Hence, cross-border mergers and acquisitions of Dutch-based bidding firms on non-Dutch target firms do not have a significant effect on the stock return of the acquiring company.

Furthermore, analyses of the multiple regression gives result on the remaining three hypotheses. The negative findings of the US variable is in line with the expectation set in the paper. Results show that the variables are not significantly differ from zero. Therefore, the second geographical hypotheses is rejected. Hence, cross-border mergers and acquisitions do not affect the CARs for the bidder when the target firm is based in the U.S. compared to the rest of the world. The time hypothesis is rejected for the first two windows, but results in a 10% significant negative effect in the (-5,5) window. Finally, the last financing hypotheses is rejected. The method of payment with cash does not affect the cumulative abnormal return in the different event windows.

Further research is suggested to also focus on the target shareholder value on the Dutch market. The shareholder value tend to be largely different affected for target firms in

comparison with bidding firms. Also further research can be done by merely focusing on transactions during the financial crisis to investigate the cause of the negative returns.

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The impact of cross-border mergers and acquisitions on shareholder wealth of Dutch acquiring companies