Value creation through cross-border mergers and acquisitions on acquirer’s shareholders in emerging and developed markets

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Value creation through cross-border mergers and acquisitions on acquirer’s

shareholders in emerging and developed markets

Amsterdam Business School

Name Maura van Werkhoven

Number 10243429

Bsc in Economics and Business Specialization Finance and Organization

Field Finance

Supervisor Ilko Naaborg Completion 20 February 2016

Abstract

This thesis analyses the effect of cross-border M&A on acquirer’s shareholder returns with targets from emerging or developed countries during the period 2001-2015. The empirical analysis contains 127 cross-border M&A deals by West-European firms. In order to measure the announcement effect, MacKinleys´ (1997) market model is used to gather the abnormal returns. Empirical evidence is found that cross-border M&As result in positive significant returns for the acquirer. On a 3-day event window, acquiring in developed countries lead to higher positive significant returns compared to emerging countries. The 41 day event window shows higher significant returns in emerging countries instead of developed countries. In that case, no conclusions could be made whether acquiring in emerging countries lead to higher abnormal returns than acquiring in developed countries. On the other hand, the OLS-regression shows that the explanatory variable results in a positive insignificant effect on CAR. Further, evidence is found that acquiring in emerging countries during the crisis period generates higher shareholder value than during the non-crisis period.

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Verklaring eigen werk

Hierbij verklaar ik, Maura van Werkhoven, dat ik deze scriptie zelf geschreven heb en dat ik de volledige verantwoordelijkheid op me neem voor de inhoud ervan. Ik bevestig dat de tekst en het werk dat in deze scriptie gepresenteerd wordt origineel is en dat ik geen gebruik heb gemaakt van andere bronnen dan die welke in de tekst en in de referenties worden genoemd. De Faculteit Economie en Bedrijfskunde is alleen verantwoordelijk voor de begeleiding tot het inleveren van de scriptie, niet voor de inhoud.

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1 Introduction

Over the past two decades M&A deals have grown explosively and so has research about M&A. In many studies research is done for M&A deals from the UK and the US, while less is done for European M&A activities and especially for Western Europe.

A reason why European takeovers are less discussed is that during the last four merger waves, there were no takeovers from European firms. European firms take part in M&A activities since 1992, called the fifth merger wave (Martynova and Renneboog, 2006). So far, six merger waves have taken place: in 1900, the 1920s, the 1960s, the 1980s, the 1990s and in 2000. Each merger wave is characterized by an increase in M&A activities followed by periods with less M&A activities. In addition, waves occur due to global economic,

regulatory, financial, political and technological changes (Martynova and Renneboog, 2008). When M&A are a response to such shocks, it can create or destroy wealth for shareholders. If managers take into account the shareholder´s interests when considering an acquisition, M&A activities lead to value creation for shareholders. However, synergies as managerial hubris and the principal-agent model, destroy wealth for shareholders (Martynova and Renneboog, 2008).

Of these waves, the fifth merger wave (1992-2002) was particularly interesting for European takeovers. This wave was characterized by a remarkable growth in the number of M&A and total value of European M&A. For the first time, European firms were as active as US firms regarding the number of M&A deals (Martynova and Renneboog, 2006). Martynova and Renneboog (2006) argue the introduction of the Euro, the globalization process and the financial markets boom as a reason for this. After that, in the middle of 2000, M&A deals collapsed and the amount of M&A deals remained significantly low till 2003. Subsequently, the number of M&A activities slightly increased but slowed down due to the global financial crisis in 2007. At this moment, some speculate about the so called seventh merger wave which would be triggered by the recovering economic conditions after this global financial crisis. From UNCTAD (2015), it seems that more emerging countries will operate as acquirers than before but on the other side, developed countries as the UK and the US will still dominate this position.

Previous empirical studies of M&A usually show positive abnormal returns around the announcement date for target shareholders (Bruner, 2002; Campa and Hernando, 2006). However, there is no clear evidence about the effect of M&A on abnormal return of the acquiring firm. Some papers argue a negative effect of abnormal returns (Walker, 2000; Healy

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et al, 1992) while Chari et al (2010) show that acquiring firms from developed markets earn a positive return from cross-border M&A with targets from emerging markets.

This study tests whether the acquirer’s announcement return of cross-border M&A with targets from emerging markets is different from the announcement return of cross-border M&A with targets from developed markets.

This thesis contributes to the literature of M&A by studying the announcement effect of cross-border M&A on shareholder value of the acquiring firm. It focuses on acquisitions by West-European firms with targets from emerging and developed countries over the period 2001-2015.

First of all, in many studies the announcement effect of cross-border M&A on target shareholders is discussed. Overall, they show a positive return for target shareholders.

Besides, as the UNCTAD World Investment Report (2015) announces the increase in foreign direct investment (FDI) through cross-border M&A, investigating the effect on shareholder value in emerging as well as developed targets have become more important. Moreover, in many studies research is done like Martynova and Renneboog (2008) with a time period during economic growth, before the financial crisis.

Contrary, this thesis only refers to the announcement effect of cross-border M&A on shareholder value of the acquiring firm. Results for acquiring shareholders are still

inconclusive. Besides, in this thesis, research is done for the period 2001-2015. This sample period is particularly interesting because it is a more recent time period and it includes the financial crisis of 2007 to 2009. In addition, it takes the sixth merger wave in consideration which is characterized by larger acquisitions that are more globally oriented (Cosh and Hughes, 1996). Moreover, these cross-border M&A account for more than 80% of all FDI by industrialized countries (Cosh and Hughes, 1996). Therefore it is interesting to do research on cross-border M&A instead of domestic M&A. Finally, due to the liberalization of markets, emerging targets are accessible and investigating the differences in announcement effect compared to developed targets is advised. These considerations bring us to the following question: ´´Does cross-border M&A lead to more shareholder value for the acquiring firm when the target is from an emerging market or a developed market?´´

Accordingly, an empirical research is done for the announcement effect of West-European firms taking over firms from targets from emerging or developed countries. From Haleblian et al (2009) these effects are measured by the abnormal returns which is are the most common indicator of M&A performance. The abnormal return is the return that shareholders earn in

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addition to what they should have earned without the event (Goergen and Renneboog, 2004). A comparison is made between the abnormal return when taking over firms from emerging countries and the abnormal return when taking over from developed countries. The abnormal returns are calculated by MacKinley’s market model (1997). Besides the announcement effect of cross-border M&A in emerging and developed countries, some control variables are tested as well. These control variables are acquirer related characteristics or deal related

characteristics and show an effect on shareholder return. The control variables tested, varies from firm size and return on equity to industry type and relative deal size. This research is done for the period 2001 till 2015 and includes two events, the sixth merger wave and the financial crisis.

This thesis describes the announcement effect of cross-border M&A on the acquirer firm´s abnormal returns with targets from emerging and developed countries. This thesis only contains West-European public acquirer firms. This paper proceeds as follows. Section 2 contains a literature review and provides the hypothesis tested in this thesis. In chapter 3 the methodology and the data set are described. In chapter 4 the results of the empirical analysis are given. This thesis ends with section 5 which provides the conclusion and

recommendations for further research.

2 Literature review

This section provides an overview of earlier research concerning the announcement effect of cross-border M&A on shareholder value with targets from emerging and developed countries. In the first and second paragraph the general motives behind M&A and cross-border M&A are described respectively. Besides, the advantages and disadvantages of emerging and developed countries as potential targets are provided. The third paragraph shows the effect of the financial crisis on the number of M&A. Finally, the last paragraph shows the effect on abnormal returns found in previous studies.

2.1 Motives behind domestic M&A

From literature it can be said that several motives for mergers and acquisitions exist. These motives could lead to value-destroying takeovers or value-enhancing takeovers. Value is destroyed when shareholder returns are less than required and value is created when the shareholder earns more than required (Bruner, 2002). Motives that destroy shareholders´ value are the agency problem and managerial hubris (Martynova and Renneboog, 2007). However, the synergy motive should contribute to shareholders´ value.

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The agency problem refers to managers that are not acting in the interest of shareholders. Instead, takeovers occur because the self-interested managers use the free cash flows for empire-building and only maximize their own utility (Jensen, 1986). In this case, excess cash leads to overbidding managers whereby poor acquisitions are made.

Managerial hubris should also lead to value-destroying mergers and acquisitions. The hubris theory suggests overconfident managers that make an offer while a synergy between the target and bidder is missing. Then, the premium paid is too high and results in a lower return for the acquiring shareholder value and a higher return for the target (Roll, 1986). Goergen and Renneboog (2004) amplify the hubris theory and reveal that European takeovers in the fifth merger wave (1990s) suffer from managerial hubris.

Unlike the former theories, the synergy motive should lead to higher shareholder returns. From Seth et al (2000), a takeover occurs because it results in a combined value that is greater than the sum of the values of the target and acquirer when there is no merger. The synergy motive is divided in an operating synergy and a financial synergy (Ghauri and Buckley, 2003).

Moreover, Ghauri and Buckley (2003) mention the operating synergies as achieved by economies of scale and scope. Economies of scale occur by merging the resources of the target and the acquirer, whereas economies of scope are achieved by allowing product and market diversification. Other operating synergies are the exchange of skills and knowledge. Next, financial synergies are achieved by better cash flow stability, a lower probability of bankruptcy and access to capital is cheaper (Martynova and Renneboog, 2006).

Both synergies are achieved by cutting costs or increased scope (Ghauri and Buckley, 2003).

2.2 Motives behind cross-border M&A

Moving from domestic M&A to cross-border M&A provides additional motives on top of the former general motives. These motives arise from strategic, cultural, geographic, economic and governance-related differences and should lead to cross-border M&As instead of domestic takeovers.

The first strategic determinant of cross-border M&A is access to new markets. Goergen and Renneboog (2004) mention that FDI theories predict that foreign bidders should be able to take advantage of imperfections in capital markets and therefore should generate more wealth compared to domestic M&A.

However, from an geographic view, according to Erel et al (2012) the likelihood of merging increases as the distance between two countries that are considering a merger shortens. In

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that case it is possible to see higher wealth effects for domestic M&A instead of cross-border M&A. Davis et al (1993) also state that domestic M&A are motivated by different reasons than cross-border M&A. The main motivation for cross-border mergers is to strengthen their market position when entering new markets. Moreover, a cross-border acquisition overcomes trade barriers to entry into foreign countries, as with an acquisition the acquirer gets

information on the target market as well as on local production conditions (Chesnais et al, 2000).

Further, considering a takeover depends on the cultural differences of the target and the acquirer. They may arise due to different languages and religions. The probability of M&A decreases when these languages and religions are too different because then the costs associated with contracting could be too high (Erel et al, 2012).

Another important economic determinant of cross-border M&A, is the difference in valuation. Following Erel et al (2012) it is given that markets in different countries are not perfectly integrated, and valuation differences across markets can help to motivate cross-border M&A.

Bris et al (2008) mention the corporate governance structure as an important driving force behind cross-border M&A. In a merger, the corporate governance structure of the acquirer is implemented in the target firm. They find a positive relationship between adopting the governance structure and increased market valuation for the target firm. As shareholder protection is an indicator for the corporate governance system, wealth is created due the suggestion that target firms often have less shareholder protection and so better protection is provided when the target is merged with the acquirer. Higher shareholder protection is associated with lower cost of capital. Volpin and Rossi (2004) are in line with these results and find less wealth creation if these differences exist in the governance structure.

2.2.1 Advantages and disadvantages of emerging and developed markets

As in this thesis the announcement effect on shareholder value with targets from emerging and developed markets is investigated, a difference between entering those two targets is provided. Especially, when comparing emerging targets with developed targets, some specific factors from literature lead to environmental differences.

Anand and Delios (2002), mention the resources and capabilities of the acquiring firm when determining cross-border M&A and Buckley and Casson (1976) further add the need to minimize transaction costs. However, recent studies show the importance of the

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Tsui, 2004).

Emerging economies are defined as low-income economies and have a rapid economic growth, whereas developed economies are of high income and have a low economic growth (Hoskisson et al 2000). Because of the fast economic development and a possible free-market system that emerging economies have, global acquirers are interested in these markets.

Hoskisson et al (2000) further state that liberalization is an explanation for emerging

economies with rapid economic growth and therefore their attractiveness as potential targets. Instinctively, developed economies with low economic potential growth are often seen as acquirers.

Meyer and Tran (2006) confirm this finding and argue that the sheer number of people with a low income makes even the less developed markets attractive to business because of their high growth potential and their market for consumer goods.

Other economic factors that determine entering an emerging or a developed market is the degree of natural sources a bidding firm has and the degree of using operational capabilities. Success in emerging markets requires operational capabilities to produce at low cost to

compete with local firms (Meyer and Tran, 2006). Moreover, firms in these emerging markets are more familiar with frequent changes in regulation and are flexible to adjust their strategy to a volatile economy (Meyer and Tran, 2006). In order to gain a competitive advantage, acquirers from developed countries should be able to change their strategies to the changing environment. In addition, some of these emerging markets have large reserves of raw materials and natural sources (Cavusgil et al, 2014). On the opposite, firms from emerging markets which consider an acquisition need to restructure their capabilities as well to succeed in an environment of developed markets (Wright et al, 2005).

Besides the advantages of investing in emerging targets, there are reasons why emerging markets might not be favorable in comparison to developed targets. Unless their high market development, emerging economies have more volatile business cycles and less liquid stock markets (Lin et al, 2003). As a consequence, acquiring firms face higher risks when entering an emerging market. Chari et al, (2010) mention incomplete contracting and bad protection as possible explanations. In order to benefit from these disadvantages, developed acquirers have to create different strategies and business models to serve not only the few wealthy customer regions but also the mass market (Meyer and Tran, 2006).

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2.3 The effect of the financial crisis on the number of M&As

In this thesis the announcement effect on shareholder value with targets from emerging and developed countries during the financial crisis is analyzed. From literature, the global financial crisis of 2007 had an enormous effect on the number of M&As that has been

exercised. However, it was only in September 2008 when the lending crisis reached enormous proportions and markets resulted in economic instability and an ailing credit market.

Ivashina and Scharfstein (2010) mention a rise of M&A deals until the financial crisis and then suddenly decrease about 47%. Different factors can function as a signal for this crisis. As for example the crisis was characterized by lending that slowed down and funding that dried up and therefore M&A deals began to decrease (Grave, 2012). In addition, Krugman(2000) mentions the mechanism of crisis where a circulation exists which explains the essence of financial crisis. As asset prices fall, the insolvency of banks become visible, forcing them to quit operations and as a result further asset deflation appears. The decrease of M&A deals mentioned by Ivashina and Scharfstein (2010) indicate that abnormal returns are expected to decrease as well. However, during the Asian financial crisis, Asian firms experienced an important increase in inflows of FDI. From the study of Krugman (2000), it is caused by an increase of cross-border M&A.

Reinhart and Rogoff (2011) clarify that the banking crisis of 2007 had about the same effect on developed markets as on emerging markets. First, the firms in the United States were hit by the crisis and then the financial breakdown was spread to emerging and developed

countries. In other words, both the acquirer and the target were affected and it should lead to a decrease in cross-border M&A deals in emerging countries. When combining Calderon and Didier´s (2009) findings with Aalber´s (2009a) findings, both argue that the financial crisis of 1980 have led to a M&A wave in which cross-border M&A raised. Besides, the current financial crisis should also lead to an increase in cross-border M&A´s because the credit crunch force banks to merge internationally. On the other hand, Calderon and Didier (2009) investigate the start of the present financial crisis and found a decrease in M&A deals in the last quarter of 2008.

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2.4 Empirical findings about abnormal returns and Hypothesis

2.4.1 Domestic and cross-border M&A

Over the years many research is done about the announcement effect of M&A. These studies investigate domestic and cross-border M&A and the effect on abnormal returns for target and acquirer shareholders. According to many different conclusions, a clear answer about value creation or value destroying is still missing. In this thesis the announcement effect on acquirer shareholders is investigated solely. This section provides empirical results about abnormal returns for acquirers from previous studies. Results regarding domestic and cross-border M&A and cross-border M&A with targets from emerging and developed countries.

In a recent study by Martynova and Renneboog (2011), research is done regarding cross-border M&A by European countries during the period 1993-2001. They argue that European takeovers are expected to generate synergy value of which an increase in share price is captured by the target firm. An announcement effect of 9.13% is found for the target and a statistically significant effect of 0.53% for the acquirer. Corhay and Rad (2000) research the effect of cross-border M&A by Dutch firms on the wealth effect of shareholders combined. They find weak evidence that cross-border M&A generate value for shareholders. A

percentage of 1.44 was found on an event window of 11 days (-5,5). When examining the differences between domestic and cross-border M&A, Goergen and Renneboog (2004) find significant positive results (2.38%) when European acquirers did a cross-border acquisition, but insignificant negative returns (-0.45%) when a domestic M&A occurs. Danbolt (2004) analyses the abnormal returns to target shareholders of the UK with a sample of 514 domestic M&A and 116 cross-border M&A. During the period 1986-1991, he found significant

positive abnormal returns for target shareholders for both domestic and cross-border M&A. During the month of the announcement it was a return of 20.29% when domestic M&A´s occurred and a return of 21.05% for cross-border M&A. Unlike the former studies, Mitchell et al (2004) find a significant negative return of 1.20% for shareholders of the acquiring firm. They examine cross-border M&A by UK firms during the period 1994-2000 and argue that half of the negative return is caused by arbitrage short selling.

2.4.2 Cross-border M&A with emerging and developed targets

When looking at cross-border M&A and examining the differences in abnormal returns for emerging and developed targets, nothing is straightforward. Chari et al (2010) find a

significant increase in abnormal returns when the acquisition occurred in an emerging country (1.16%). They examine the announcement effect of cross-border M&A by 9 developed

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countries into emerging and developed markets over a three-day event window. As taking over firms in an emerging target led to positive shareholder returns, there were no significant results when acquiring firms in developed countries. A reason why shareholders of emerging targets experienced positive returns is the better corporate government structure they

provided. Burns and Liebenberg (2010) are in line with these results and conclude that U.S. takeovers have on average a positive effect on shareholder return when the acquisitions takes place in an emerging country (0.575). Like Chari et al (2010), no significant results were found when taking over firms in developed countries. They argue that individual rival characteristics as rival size and growth opportunities matter more in developed markets than in emerging markets. In emerging markets characteristics as shareholder protection, target public status and economic development explain the returns.

2.4.3 Hypothesis

The focus in this paper is to test the announcement effect of cross-border M&A on

shareholders of the acquiring firm with targets from emerging and developed countries. Until now, theory and literature give no unanimous conclusion whether cross-border M&A create value for acquiring shareholders and assuredly for targets from emerging and developed economies. Therefore for the entire hypothesis, the tests are used only in relation to the acquiring firms.

The first hypothesis is created to test whether cross-border M&A have a positive effect on abnormal returns. My expectation is that the cumulative abnormal return (CAR) is positive during the announcement period because cross-border M&A are motivated by the creation of synergies which create value for the acquiring firm. This is based on theories offered by Goergen and Renneboog (2004) and Martynova and Renneboog (2006).

H1- Cross-border M&A result in positive abnormal returns for acquirer shareholders of West-European firms during the announcement period

The second hypothesis is created to examine when a cross-border M&A takes place in an emerging country, the abnormal returns are positively affected compared to developed countries.

When cross-border M&As occur in developed target countries, certain factors are

advantageous. From an economic point of view, acquirers face less risk when considering an acquisition as exchange rates are less volatile than in emerging markets. Besides, cultural

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barriers are less likely seen in developed countries compared to emerging countries, so they promote the process of integration of M&A. Finally, developed countries are characterized by more stable corporate government institutions.

On the other hand, emerging targets are characterized by rapid growth opportunities which create value for the West-European acquirer. Moreover, if the acquiring firm from a

developed country is able to bring better institutions and corporate governance to emerging markets, then this results in value creation for the acquiring shareholder (Chari et al, 2010). Coffee (1999) confirms this and states that the expected future cash flow rises if the target becomes bonded to better institutions. Finally, emerging markets have more imperfect financial and labor markets than developed markets and therefore, taking over firms from emerging markets is more favorable.

H2: There will be higher CARs for acquiring firms taking over targets from emerging countries than targets from developed countries

The third hypothesis is created to see whether M&A in emerging countries generate higher abnormal returns during the crisis period than in the non-crisis period. This is based on the findings by Campa and Hernando (2009) and Jensen´s theory (1986). From literature it becomes clear that a change in value creation arise for acquirers and targets during the crisis. Campa and Hernando (2009) test whether credit conditions create or destroy value in

European M&A. They conclude that less value is created in M&A when more relaxed credit conditions hold. But in this thesis, a crisis occurs and it should lead to value creation for shareholders, compared to a non-crisis period with relaxed credit conditions. This is where Jensen´s theory (1986) comes by. He argues that acquirers´ excess cash is positively related to poor acquisitions. However, during the crisis less cash is available instead of excess cash and acquirers need to be more careful when considering an acquisition. Because a failed

acquisition is harmful during the crisis. They only make an acquisition if the target is of great potential and therefore generates wealth for the acquiring firm. Both Campa and Hernando (2004) and Goergen and Renneboog (2004) are in line with these results and state that acquiring firms with excess cash destroy shareholder´s value by overbidding.

H3 : There will be higher CARs for acquiring firms taking over targets from emerging countries during crisis period than in the non-crisis period

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3 Methodology and data

3.1 Methodology

To test the announcement effect of cross-border M&A on the acquirers´ shareholder value, an event study has to be done. It is a widely used method and it examines the abnormal return of the acquirer around the announcement date. With the announcement dates from Thomson One database and the daily stock prices from Datastream, an event study is performed. An event study consists of the following steps. First of all, the event of interest and the timing of the event have to be identified. Second, a benchmark model for the normal returns has to be chosen. Finally, the abnormal returns around the event date have to be calculated. In this thesis the event date is the announcement date of the takeover and is defined as t=0. An event window [t1, t2] is created because the period around the announcement date is also important (de Jong et al, 2007). The abnormal returns are calculated over two event windows: 3-day [-1,1] and 41 day [-20,20] event window. For example, [-[-1,1] meaning one day before the announcement date and one day after it. Moreover, to gather the normal returns, an estimation period before the event window has to be chosen. The same period as Martynova and

Renneboog (2006) is used; [-300,-60] meaning that the beginning of the estimation period is 300 days until 60 days before the announcement date. Further, the benchmark return has to be calculated to get the abnormal return. Here the benchmark return is the expected return of the West-European acquirer when no takeover is announced. MacKinley’s market model is used as the two other models, CAPM and the Fama French three factor model, give not sufficient data.

1)

𝐸(𝑅)

_𝑖𝑡

= 𝛼

_𝑖

+ 𝛽

_𝑖

∗ 𝑅

_𝑚𝑘𝑡

+ 𝜀

_𝑖𝑡

R

it= expected return of firm і, on event date t

R

mkt = daily market return, on event date t

α

i = intercept firm і

β

i = parameter firm і

ɛ

it = residual

The alpha was not significant in all of the deals so is left out in further calculations. The beta is estimated by OLS regression over the estimation period of 240 days (Martynova and Renneboog, 2006). The Stock ex 600 is used as the market return and is the European index.

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After that, the abnormal returns are calculated by subtracting the estimated beta times the daily market return of Stock ex 600 from the daily stock return of firm i on day t.

2)

𝐴𝑅

_𝑖𝑡

= 𝑅

_𝑖𝑡

− (𝛽

_𝑖

∗ 𝑅

_𝑚𝑘𝑡

)

AR

it = abnormal return of firm і, on event date t

R

it = actual ex-post return of firm і, on event date t

β

i

*R

mkt = estimated coefficient times the market return, on event date t

In order to calculate the t-statistic and capture the announcement effect, the cumulative abnormal return is calculated (CAR). This is in line with the study of Martynova and

Renneboog (2006) and it is done for the two event windows, the 3-day 1,1] and the 41 day [-20,20] window.

3)

𝐶𝐴𝑅

(𝑡1,𝑡2)

= ∑

𝑇2𝑇1

𝐴𝑅

𝑖𝑡

A positive CAR means that the market expects the announcement of the takeover creates value for the shareholders of the acquiring firm. A negative CAR means value destroying for the shareholder of the acquiring firm. In order to get the CARs that are not significantly different from zero, a t-test is performed by the following formula;

0)

𝑡𝐶𝐴𝑅

_{(𝑡1,𝑡2)}

=

𝐶𝐴𝑅(𝑡1,𝑡2)

𝜎𝐶𝐴𝑅_{(𝑡1,𝑡2)/√𝑁}

Thereafter, the CAR is taken as the dependent variable and an OLS regression is performed. A linear regression model generates beta´s which show the change in the dependent variable CAR, when an independent variable increases by one (Stock and Watson, 2012). According to Haleblian et al (2009), it is the most common indicator of M&A performance. With OLS regression, it is tested whether the abnormal return for the acquiring firm is higher when there is an announcement of a cross-border M&A in an emerging country than a cross-border M&A in a developed country. Besides, the regression will test whether a takeover in an emerging country during the financial crisis, will generate different abnormal returns than in the non-crisis period. Some important control variables will be added as well. Following (de Jong et al, 2007) the following model will be tested in this empirical analysis:

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𝐶𝐴𝑅𝑖𝑡 = 𝛽𝑜 + 𝛽1 ∗ 𝐸𝑚𝑒𝑟𝑔𝑖𝑛𝑔 + 𝛽2 ∗ 𝐶𝑟𝑖𝑠𝑖𝑠 + 𝛽3 ∗ (𝐸𝑚𝑒𝑟𝑔𝑖𝑛𝑔 ∗ 𝐶𝑟𝑖𝑠𝑖𝑠) + 𝛽4 ∗ 𝐹𝑖𝑟𝑚𝑠𝑖𝑧𝑒 + 𝛽5 ∗ 𝑅𝑂𝐸 + 𝛽6 ∗ 𝑆𝑒𝑐𝑡𝑜𝑟 + 𝛽7 ∗ 𝑅𝑆𝐼𝑍𝐸 + 𝛽8 ∗ 𝐷𝑒𝑎𝑙𝑣𝑎𝑙𝑢𝑒 + 𝛽9 ∗ 𝐶𝑎𝑠ℎ + 𝛽10 ∗ 𝑊𝑎𝑣𝑒 + 𝜀𝑖

Here, 𝐶𝐴𝑅𝑖𝑡 is the cumulative abnormal return which is used as the dependent variable. 𝛽𝑜 is a constant term. Continually, from de Jong et al (2007) it becomes clear that a lot of factors, acquirer related or deal related characteristics, have an effect on M&A performance. This research investigates the effect on acquirers´ shareholder return of takeovers in emerging or developed targets. 𝐸𝑚𝑒𝑟𝑔𝑖𝑛𝑔 is a dummy variable and equals 1 if the West-European takeover occurs in an emerging country and is used as the main explanatory variable. Moreover, some other independent variables, as control variables, influence these returns. Seen from the regression model and based on de Jong et al (2007), the following control variables are used: the financial crisis, firm size, ROE, industry sector, deal value, method of payment and the sixth merger wave.

The financial crisis: studies have shown different conclusions about the effect of the global crisis on abnormal returns. Jensen (1986) states that the acquirer’s excess cash is positively related to poor M&A. In that case it will be value destroying for the acquiring firm and the abnormal returns will be negative. During a financial crisis, there is no excess cash but less cash available and acquirers need to be more careful when considering an acquisition. 𝐶𝑟𝑖𝑠𝑖𝑠 is a dummy variable that equals 1 if the announcement lies in the period 2007-2009 and 0 otherwise. 𝐸𝑚𝑒𝑟𝑔𝑖𝑛𝑔 ∗ 𝐶𝑟𝑖𝑠𝑖𝑠 is a cross-variable of an acquisition in an emerging country and the crisis period.

Moreover, the size of the acquiring firm has an effect on the abnormal returns as well. 𝐹𝑖𝑟𝑚𝑠𝑖𝑧𝑒 is the natural logarithm of total assets of the acquiring firm. Small firms that are taking over will have higher abnormal returns than large firms that are taking over (Moeller et al, 2003). For small firms it is a percentage of 2,3% and for large firms a return of 0,1%. They argue that large firms that are taking over want to pay more. With regard to that, as firm size increases then acquirer´s shareholder returns are expected to decrease.

Besides, return on equity (ROE) of the acquiring firm influences the abnormal return. Sparta (2005) finds that ROE significantly influences the return of the shareholder when studying the effect of ROE, EPS and CFO on return of a manufacturing industry. But Kennedy (2003) is not in line with the conclusions made by Sparta (2005) and finds a negative effect of ROE on return. Overall, Martani et al (2009) argue that ROE is consistently significant on abnormal return. 𝑅𝑂𝐸 , the return on equity, is the net income divided by the acquirers’ equity.

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Morck et al (1990) find that the industry sector also has an effect on the return of the

acquiring firm. 𝑆𝑒𝑐𝑡𝑜𝑟 is a dummy variable that equals 1 if the target is in the same industry as the acquirer and 0 otherwise. Acquiring firms can make a decision between M&A with targets from related or non-related industries. In their study they show that takeovers with targets from related industries, causes higher abnormal returns for the acquiring firm. Maquieria et al (1998) are consistent with this finding and find negative but insignificant returns when the target is from a non-related industry. A reason could be that taking over targets from non-related industries destroys shareholder value.

According to Fuller et al (2002), a large relative deal value will lead to higher abnormal returns for the acquiring firm. Also, from Chari et al (2004) it becomes clear that deal value has a positive but insignificant effect on shareholder return when US acquirer is taking over a target from an emerging market. 𝑅𝑆𝐼𝑍𝐸, relative deal size, is measured as the deal value divided by the enterprise value of the acquirer. 𝐷𝑒𝑎𝑙𝑣𝑎𝑙𝑢𝑒 is the natural logarithm of deal value.

Method of payment: transactions of takeovers could be financed through cash, stock or a mix of cash and stocks. 𝐶𝑎𝑠ℎ is a dummy variable that equals 1 if the deal is paid by cash only and 0 is the deal is paid by stock only. From literature, it seems that the payment method influences the shareholder returns. Faccio and Masulis (2005) study the effect of the payment method of European M&A on announcement returns. They find that a transaction involving stocks is chosen if the firm has a weak financial position. Further, Loughran and Vij (1997) find that payment of stocks leads to negative returns of 25% and cash financing leads to positive returns of 62%. The reason could be that stock financing may give a signal that the acquirers believe that the firm´s shares are overvalued. The results of Myers and Majluf (1984) are in line with Loughran and Vij´s findings and they add that the share price goes downward due to the overvalued acquirer´s shares. These studies clarify that there is a relationship between the method of payment and the return of shareholders.

Finally, the sixth merger wave took place between 2003-2007 and has an effect on shareholder value as well. It was a period characterized by less acquisitions and a reason could be due to managerial hubris (Alexandridis et al, 2012). Also, a relationship between more cash financing and less overvalued acquirers is shown in the studies. When the acquirer is taking over during the merger wave, shareholder´s value decreases by 0.45%. 𝑊𝑎𝑣𝑒 is a dummy variable that equals 1 if the announcement lies in the period 2003-2007 and 0 otherwise

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acquisition in an emerging country instead of a developed country on the CAR during the period 2001-2015. According hypothesis 2, the CAR is expected to be positive. Further, by looking at the coefficient 𝛽3, hypothesis 3 is tested. The difference in CAR show acquisitions in an emerging country during the crisis period instead of acquisitions in an emerging country during the non-crisis period. Also according to hypothesis 3, the CAR is expected to be positive.

3.2 Data and descriptive statistics

In this thesis empirical research is done for West-European acquirers with targets from

emerging and developed countries for the period 1 January 2001 – 31 August 2015. To define the emerging and developed targets, the lists by FTSE (Financial times stock exchange) Group are used. The list of emerging countries consists the following: Brazil, Czech Republic, Hungary, Malaysia, Mexico, Poland, South Africa, Taiwan, Thailand, Turkey, Chile, China, Colombia, Egypt, India, Indonesia, Pakistan, Peru, Philippines, Russia and United Arab Emirates. Moreover, the list of developed countries consists of: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Hong Kong, Ireland, Israel, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, South Korea, Spain, Sweden, Switzerland, UK and the US (FTSE, 2015). The M&A deals by West-European countries are collected from the Mergers & Acquisitions Database of Thomson One. Then two samples are extracted, the first consists of West-European takeovers in emerging countries and the second consists of West-European takeovers in developed countries. The initial sample of cross-border M&A by West-European firms was 282139, but using the following criteria there were less deals left.

The acquiring firm has to be a listed company which has a Datastream code otherwise the stock price cannot be obtained from Datastream. This criterion is essential because then some variables, like firm size, about the acquiring firm can be gathered from Datastream. From Lowinski et al (2004) it becomes clear that the deal value has a minimum of $100 million, since with low deal values the effect of the announcement will be too small to capture. For developed targets the deal value has a maximum of $795 million in order to compare with the emerging sample where the average deal value is $775 million. Furthermore, the acquirer had to make a merger or acquisition at most once a year during the time period because otherwise it is not clear whether the abnormal return can be devoted to that particular takeover or has other causes than the announcement date. Finally, only completed confirmed M&A are

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included to prevent other bids on the same target. Accordingly, after these corrections, only 157 deals in emerging targets and 520 deals in developed targets were left.

For these two samples, also additional information about the SIC codes and method of payment is gathered from Thomson One. The SIC codes are numbers and reveal the industry sectors of the acquirer and the target. Comparing the four digits of the SIC codes, results in industry related or unrelated M&A where the control variable ‘industry sector’ is based on. The method of payment contains transactions that could be financed through cash, stocks or a mix between cash and stocks. Again, not for all deals the payment method was known so less deals remained. Thomson One did not have all the information about the control variables and additional information is gathered from Datastream Worldscope database. The control

variable firm size is based on the market capitalization of the acquiring firm and is obtained from Datastream using the code ‘WC08001’. The variable return on equity is (ROE) is gathered from Datastream and both variables are taken a year before the announcement date. The stock prices are obtained from Datastream as well and after calculating the abnormal returns in Stata, a sample is left of 46 deals in emerging countries and 81 deals in developed countries.

Figure 1 shows the number of deals over a time period of 2001 till 2015. During this research period two important events took place, the sixth merger wave (2003-2007) and the global financial crisis (2007-2009). During the sixth merger wave, an increase of M&A deals is expected. This trend is seen for emerging targets as the number of deals raised from 2 bids in 2002 to 6 bids in 2007, with a total sample of 49 deals in emerging countries. When looking at developed targets, the number of cross-border M&A increased during the period 2003-2005 and then the frequency declined in 2006. This is in accordance with literature in which a merger wave is characterized as a period with many M&A activities followed by fewer acquisitions. When looking at the financial crisis, Krugman (2000)would have expected an increase in FDI inflows. He did research to Asian deals and found an increase of 91% acquisitions during the period 1996-1998. Looking at the figure, there can be seen that as soon as the crisis arrives, the number of deals decreases for both developed and emerging targets in 2008. This is in line with Calderon an Didier’s (2010) results who found a decrease in M&A deals as well in the last quarter of 2008. A reason could be the economic instability of both markets and an ailing credit market in 2008.

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Figure 1

M&A in emerging and developed countries (2001-2015)

Source: Thomson One database

From table 1 it becomes clear how the sample of this research is composed. The sample contains the amount of cross-border M&A per country. The sample exists out of 25 targets from developed countries and 21 targets from emerging countries. As already argued in the literature, developed countries still dominate the position as acquirers these days. Inflows from these countries to emerging markets are expected to remain at historically high levels (UNCTAD, 2015). Ranjan and Agrawal (2011) mention that the BRICS (Brazil, Russia, India, China and South-Africa) play an important role as producers of goods and services in the world economy. The number of cross-border M&A in emerging economies and mainly into the BRICS countries is expected to be high. Results show that Brazil has a quite large proportion of acquisitions, 17.39%. Then Russia, China and South-Africa are all in the top 5 with percentages of 15.22, 8.70 and 8.70 respectively. India follows with 6.52% which lead to a total of 56.5% deals in BRICS countries. An explanation for this result is that they all have attractive low labor costs, a large market size and a high growth potential (Ranjan and Agrawal, 2011) 0 2 4 6 8 10 12 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Num ber o f dea ls Years Emerging Developed

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Table 1

Number of cross-border M&A deals per country Developed targets # % Emerging targets # % UK 23 28.40 Brazil 8 17.39 US 16 19.75 Russia 7 15.22 Germany 10 12.35 Poland 6 13.04 Italy 7 8.64 China 4 8.70 France 5 6.17 South-Africa 4 8.70 Spain 5 6.17 India 3 6.52 Switzerland 3 3.70 Turkey 3 6.52 Belgium 3 3.70 Malaysia 2 4.35 Netherlands 2 2.47 Mexico 2 4.35 Austria 1 1.23 Czech Republic 2 4.35 Canada 1 1.23 Egypt 2 4.35 Ireland 1 1.23 Chile 1 2.17 Norway 1 1.23 Colombia 1 2.17 Japan 1 1.123 UAE 1 2.17 South-Korea 1 1.23 Hungary 0 0 Australia 0 0 Taiwan 0 0 Denmark 0 0 Thailand 0 0 Finland 0 0 Indonesia 0 0 Greece 0 0 Pakistan 0 0 Hong-kong 0 0 Peru 0 0 New-Zealand 0 0 Philippines 0 0 Portugal 0 0 Singapore 0 0 Sweden 0 0 Israel 0 0 Total 81 100 46 100

Source: Thomson One database

Table 2 provides the descriptive statistics of the total sample. It includes all the control variables which are of interest as determinants for cross-border M&A. The second column shows the number of observations per characteristic. From the 3rd and 4th column the smallest and largest observations per characteristic is shown. Cash takes the value 0 if the transaction was paid by stock only and 1 if the transaction involved cash. The same holds for the dummy variable stock, which is the reverse. The 5th column shows that on average the most cross-border M&A transactions are paid by cash instead of stocks. Also, when looking at the variable EM-crisis, 0.102362 means that on average cross-border M&A with targets from emerging countries took place during the non-crisis period. Moreover, the mean of all determinants varies between 0.102362 and 15.44874 and the variation of the different determinants varies between 0.303245 and 22.45218, as can be seen from the 6th column.

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Table 2 Descriptive statistics

Variables Obs Min Max Mean

Standard deviation Variance Cash 127 0 1 0.834646 0.3729713 0.139107591 Stock 127 0 1 0.165354 0.3729713 0.139107591 Firm size (Ln) 127 2.205302 6.386455 4.097246 1.002512 1.00503031 Crisis (2007-2009) 127 0 1 0.283465 0.4524648 0.204724395 EM-crisis 127 0 1 0.102362 0.303245 0.09195753 Wave (2003-2007) 127 0 1 0.472441 0.5012171 0.251218581 Industry sector 127 0 1 0.385827 0.4887179 0.238845186 Deal value (Ln) 127 2 4.176602 2.497778 0.4215652 0.177717218 ROE % 127 -114.4 102.95 15.44874 22.45218 504.1003868 Rsize % 127 0.0000834 1.037896 0.11454 0.2035835 0.041446241 Notes: ROE refers to return on equity. Rsize refers to relative deal size measured as deal value divided by the acquirers’ total assets. EM-crisis refers to deals in emerging targets during the financial crisis.

Table 3 shows the correlations between the several variables, tested on a 1% significance level. The variables crisis and wave have the smallest correlation, -0.0003, which is negative. It suggests that a negative relation exists. On the other hand, the largest correlation is between the variables firm size and rsize, -0.6314. It indicates a strong negative relation as well. With this table the variables are tested on multicollinearity. Multicollinearity appears if some variables have the same variance that is if a linear relationship exists. Perfect correlation between variables is a problem as it indicates that the OLS regression is violated. Mason et al (1991) argue that collinearity is a problem if correlation values of 0.8 and higher are found. They have to be omitted from the regression model. Table 3 shows no correlation above 0.8, as -0.6314 is the largest correlation found. This correlation between the variables firm size and rsize is significant at a 1% level. It is expected as rsize is measured as deal value divided by acquirer´s total assets and so firm size is part of the equation. The same holds for the positive significant correlations found between crisis and crisis (0.5369) and target_EM and EM-crisis (0.4481), as an interaction dummy is added to the regression model which both includes

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emerging targets and the crisis period.

A positive significant correlation is found between the variables firm size and deal value. 0.4119 indicates a strong positive relation. This is not a surprise as larger firms are able to make higher transaction deals than smaller firms. A significant positive correlation of 0.2928 between equity and ROE makes sense as the ROE equation consists of equity. The positive correlation between emerging targets and deal value (0.3361) is found due to the deal value assumption of developed targets. In general, developed targets are related to higher

transaction deals than emerging targets but because of the maximum deal value restriction, transaction deals turn out to be higher in emerging targets. UNCTAD (2015), argues that emerging countries attract more than half of global FDI flows from particularly developed economies. Developed acquirers are related to large firm sizes and established in emerging countries and therefore a positive significant correlation of 0.3269 is found between firm size and target_em. Finally, positive correlations are found between deal value and EM-crisis (0.2468) and firm size and EM-crisis (0.3058) at a 1% level as well. An explanation could be that during the crisis, larger firms have more possibilities to get (more) credit than smaller firms and therefore are less affected by the crisis than smaller firms (Campello et al, 2009).

Table 3 Cross-correlations

Target_EM Stock Firm size Crisis EM-crisis Wave

Industry sector

Deal

value ROE Rsize

Target_EM 1.0000 Stock 0.1149 1.0000 Firm size 0.3269*** 0.1572 1.0000 Crisis -0.0014 -0.0022 0.1893 1.0000 EM-crisis 0.4481*** 0.0105 0.3058*** 0.5369*** 1.0000 Wave -0.024 -0.1307 0.0463 -0.0003 -0.0074 1.0000 Industry sector 0.1094 0.0915 -0.005 -0.0319 0.0525 0.1572 1.0000 Deal value 0.3361*** 0.0241 0.4119*** 0.1679 0.2468*** 0.1036 -0.0262 1.0000 ROE 0.0127 0.2928*** 0.0151 0.0231 0.0148 -0.1411 -0.1411 -0.0787 1.0000 Rsize -0.1182 -0.1693 -0.6314*** -0.0156 -0.0802 0.0491 0.0491 -0.0321 -0.0708 1.0000 Notes: ROE refers to return on equity. Rsize refers to relative deal size measured as deal value divided

by the acquirers’ total assets. EM-crisis refers to deals in emerging targets during the financial crisis. *** indicate significant at 1% level.

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4 Empirical analysis

4.1 Analysis

This chapter shows the results of the empirical research. First, the descriptive statistics of the abnormal returns (CARs) are explained. Then the OLS regression with the dependent variable CAR and the several determinants are discussed. Finally, the robustness checks are explained.

Analyzing the CARs show answers for this thesis´ hypothesis. Two different event windows are discussed: 3-day (-1,1) and 41 day (-20, 20) window. From the methodology the t-test is used to calculate the effect of the total sample, 127 M&A activities, as well as for the two different subsamples, 46 deals in emerging countries and 81 deals in developed countries. Table 4 and 5 show the descriptive statistics of the CARS for the two event windows.

Table 4 shows that the CARs for the two different event windows are both positive. It

indicates a positive abnormal return for acquirers who did a cross-border M&A. For the 3-day window, a positive return of 1.49% is found which is significant at a 1% level. Despite the positive return of 0.60% for the longer event window, it is not significantly different from zero. It seems that after the announcement there was no information leakage to the acquirers. Goergen and Renneboog (2004) show the same results and find positive significant returns of 2.38% for European acquirers who did a cross-border merger of acquisition. Moreover, these findings are in line with Martynova and Renneboogs´ (2008) results who find positive returns of 0.80%. They investigate cross-border M&A in Europe as well. Combining these findings, it can be concluded that cross-border M&A lead to an increase in shareholder value of the acquiring firm. Hypothesis 1 is accepted.

Table 5 shows the CARs for cross-border M&A in emerging countries and developed

countries for the two different event windows as well. For both subsamples the CARs turn out to be positive, in a 3-day event window as well as for the 41 day window. Takeovers in emerging countries result in a significant positive return of 1.28% for the acquirer on a 3-day window. Extending the event window to 41 days, it results in a higher positive return of 3.05% which is significant at a 5% level as well. It seems that as the announcement date approaches, returns decrease by approximately 50% due to more information that reaches the market. This result is in line with Leeth and Borg (2000) who find a positive return of 3.12% for the acquiring firm, which was significant on a 5% level on a 41 day event window. These findings are also in accordance with Chari et al (2010) who investigate acquisitions by developed countries into emerging countries between 1986-2006. They find a positive and

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significant return of 1.16% for the US acquirer on a 3-day window. When looking at the subsample of developed countries, takeovers result in a positive significant return of 1.61% on a 1% level on a 3-day window. Extending the event window to 41 days, results in a slightly increase in returns of 0.79%, but which is not significant at all levels. This is not in accordance with Chari et al (2010) who find that acquiring in developed countries lead to insignificant results at all levels. An explanation could be that they investigate cross-border M&A between 1986-2006 which does not include the whole sixth merger wave and the financial crisis of 2007-2009. As already mentioned, the sixth merger wave was characterized by an increase in M&A deals. Therefore a positive significant return of 1.61% on a 3-day event window is expected. There can be concluded that cross-border M&A, by West-European acquirers, result in an increase of shareholder value for the acquiring firm.

Moreover, acquiring firms in developed countries lead to a higher significant positive return than acquiring firms in emerging countries. This is only true for the 3-day window, as for the 41 day window the CAR is positive and significant higher for emerging targets. Taken

together, no conclusions could be made whether acquiring firms in emerging countries lead to higher abnormal returns for the acquiring firm than acquiring firms in developed countries.

Table 4

Descriptive statistics CARS total sample

Event window Mean Std. Error Std. Dev T-test p-value CAR [-1,1] 1.493625 0.376250429 4.240127 3.97 0.000*** CAR [-20,20] 0.5997647 1.434108322 16.16158 0.677 0.677

Notes: robust standard errors in parentheses. ***, **, * indicate significant at 1%, 5% and 10% level respectively.

Table 5

Descriptive statistics CARS two subsamples

Emerging target

Event window Mean Std. Error Std. Dev T-test p-value CAR [-1,1] 1.284964 0.634219 4.301483 2.03 0.049** CAR [-20,20] 3.049737 1.316772 8.930783 2.32 0.025**

Developed target

Event window Mean Std. Error Std. Dev T-test p-value CAR [-1,1] 1.612124 0.469691 4.227217 3.43 0.001*** CAR [-20,20] 0.791578 2.11143 1.900287 0.37 0.709

Notes: robust standard errors in parentheses. ***, **, * indicate significant at 1%, 5% and 10% level respectively.

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This section shows the results of all OLS regressions performed, which uses the CAR as the dependent variable. The main explanatory variable emerging target and the control variables are taken into account as well. The abnormal returns (CARs) for the acquiring firm are estimated over two event windows around the announcement date, 3-day 1,1] and 41 day [-20,20] window. From literature, testing the abnormal returns on a short and longer event window could lead to other significant results compared to testing around the announcement date [-1,1] only. First, the results of the regression model for the total sample are provided, seen in table 6. Then the OLS regression tests the control variables on the emerging and developed sample, seen in table 7.

Table 6 shows the estimated beta coefficients for the explanatory variable and the control variables. It shows the effect of the variable on the abnormal return of the acquirer (CAR). Robust standard errors are used in parentheses as another robustness check. As the cross-correlations in table 3 already showed that multicollinearity is not present within the

regression model. As table 6 shows, most of the variables do not have a significant effect on the cumulative abnormal returns. It indicates that these variables do not explain the found cumulative abnormal returns (CAR). This is also read by the low r-squared percentages of 10.41 and 9.8 and the F-values which indicate if the control variables are jointly significant or not. However, a few variables do show significant results on a 5 and 10% level.

When looking at the main explanatory variable target_em, shareholders of the acquiring firm earn a 0.40% higher abnormal return when the acquisition takes place in an emerging country. This positive result is found on a 3-day event window and is in line with the hypothesis. It is not significantly different from zero for all levels. On the longer event window [-20,20] acquirer shareholders seem to earn a 6.98% higher abnormal return when the acquisition happens in an emerging country. This value is significant on a 10% level. The result of the 3-day window is in accordance with Chari et al (2010) who find that acquirers of a developed firm earn a positive significant abnormal return of 1.16% when a firm in an emerging country is acquired. Moreover, the positive results are in line with Leeth and Borg (2000) who find a positive significant return of 3.12%. The difference with the found CAR in table 6, is that they estimated the CAR over a longer event window [-41, 0].

Examining the control variables, two variables show a significant result on a 3-day window. The variable crisis seems to have a positive effect of 1.83% on the cumulative abnormal return. The variable is significant at a 5% level and therefore, takeover announcements during

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the financial crisis create value for the acquiring shareholder on a 3-day event window. This finding is in line with Anema’s (2010) results who finds a positive effect of 1,04% for the acquiring firm. It was estimated on a 3-day event window and significant at a 5% level as well. Campa and Hernando (2004) argue that an excess of cash holdings lead to value

destroying transactions. During the financial crisis, less cash is available and acquirers should be more careful when considering a merger or acquisition. They only want to merge if the target is of great potential and creates value for the acquiring shareholders. Aguair and Gita (2005) agree and mention that a financial crisis should indicate an increase in M&A. The control variable ROE, return on equity, is also significant at a 5% level. 0.0311748 indicates that ROE has a slightly positive effect of 0.03% on the cumulative abnormal return on a 3-day event window. The positive return is related to the ROE equation. This slightly positive return is in accordance with Sparta (2010) who finds that return on equity influences the abnormal return as well. An effect of 0.14% on abnormal return was found. The value is found significant at a 5% level. Looking at the longer event window [-20,20], no control variable seems to have an effect on cumulative abnormal return as no significant results are found. The main explanatory variable target_em is the only one which is significant at a 10% level. It could be explained looking at the F-value and R-squared.

Examining the R-squared of both event windows, it appears that the R2 is 0.1041 and 0.098 respectively. R-squared tests the explanatory power of the regression models. For the 3-day window, 10.41% is explained by the model and for the 41 day window; less is explained by the model, namely 9.8%. Following Stock and Watson (2012), the model tested on a 3-day window with the same control variables, has a higher explanatory power than the model provided for the 41 day window with the same control variables. This implies that in need to answer the hypothesis, only the model by the 3-day window [-1,1] is valid. Andrade et al (2001), already argued that the 3-day window is one of the most commonly used event windows when examining cross-border M&A. In addition, looking at the F-value from both event windows, only the F-value for the 3-day window is significant at a 5% level (0.0392). This indicates that the simultaneously tested control variables are jointly significant at a 5% level. They show a combined significant effect on the cumulative abnormal return.

Hypothesis 2, referring to higher shareholder value for the acquirer when the M&A takes place in an emerging country compared to an acquisition in a developed country, is rejected at a 1%, 5% and 10% significance level. Finally, looking at the interaction term emerging crisis, an insignificant negative effect of 0.38% is found on a 3-day window. It implies that when a

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cross-border M&A happens in an emerging country during the financial crisis, shareholder value for the acquiring firm is destroyed.

Table 6

Regression results CAR total sample

Notes: robust standard errors in parentheses. ***, **, * indicate significant at 1%, 5% and 10% level respectively

Dependent variable: CAR

Event window [-1,1] Event window [-20,20] (1) p-value (2) p-value Target_EM 0.3994651 0.651 6.981238* 0.054 (-0.881849) (-3.597607) Cash 0.3968556 0.714 0.9562985 0.731 (-1.079644) (-2.77024) Firm size -0.712949 0.194 -5.714469 0.11 (-0.545793) (-3.543986) Crisis 1.830287** 0.044 1.133797 0.711 (-0.8972) (-3.052799) EM-Crisis -0.37557 0.839 8.176702 0.255 (-1.849391) (-7.150858) Wave 0.0911389 0.907 -2.461694 0.436 (-0.77673) (-3.148152) Sector 0.0771857 0.925 0.2092609 0.935 (-0.813538) (-2.556934) Deal value 1.785934 0.114 1.896805 0.463 (-1.12283) (-2.576865) ROE 0.0311748** 0.013 -0.0354104 0.406 (-0.012382) (-0.0424182) Rsize 0.5100425 0.881 -0.7371003 0.947 (-3.413045) (-11.15256) Constant -1.364352 0.645 1.734109 0.129 (-2.956768) (-11.35277) N 127 127 R-squared 0.1041 0.098 F-test 0.0392** 0.1051

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In excel the mean cumulative abnormal returns (CARs) for the acquiring firm over the two event windows are calculated. Two lists are created: one list including the announcements of M&A during the crisis period and one list including the announcements of M&A during the non-crisis period. Besides, a difference is made between the mean CAR for the total sample and the mean CAR for acquisitions in emerging countries only.

There can be concluded that the mean CAR for the total sample is higher during the financial crisis compared to the non-crisis period on a 3-day event window. In the crisis period the mean CAR for the total sample is 2.81 and in the non-crisis period the mean CAR for the total sample is 0.97. As already mentioned, the crisis has a positive influence on the cumulative abnormal return of the acquiring firm. Dividing the sample in emerging targets only, the mean CAR during the crisis period is 2.30 and the mean CAR during the non-crisis period is 0.89. This means that acquiring firms in emerging countries during the financial crisis generate higher abnormal returns than acquiring firms in emerging countries during the non-crisis period. In that case, hypothesis 3 is not rejected. Em-crisis in table 2 in the appendix shows a negative relation between emerging targets during the financial crisis and value creation for shareholders on a 3-day window. An explanation for these contrary results, is that in table 2 in the appendix other factors affect the variable target_em. Seen from table 3, for example firm size is highly correlated with target_em

Table 7 shows the results of the different OLS regressions performed when dividing the total sample in an emerging sample and a developed sample. When examining emerging countries on a 3-day window, the control variable firm size shows up as the only variable which has a significant effect. An effect of -1.9923 means that as the acquiring firm increases its assets with 1 million, then the abnormal return for the acquiring firm decreases with 1.99%. This negative effect is significant at a 10% level. This finding is in accordance with Moeller et al (2003) who find that the acquiring shareholders of large firms lose 1.69% when an acquisition is announced. In that case, smaller firms who are announcing an acquisition earn higher abnormal returns than larger firms. This negative relation between firm size and cumulative abnormal return is caused by management hubris (Moeller et al, 2003). This negative relation still exists when looking at the 41 day window. Firm size decreases shareholder returns by 2.26%, however this value is not significantly different from zero for all levels. On the other hand, the 41 day event window shows that the variable ROE is the only variable which is significant. On a 10% significance level, return on equity has a slightly negative effect of 0.17% on shareholders’ abnormal returns. The R2 _{for the longer event window is 25.29% and}

(30)

indicates that more is explained by the model than for the 3-day event window, as the R2 _is 18.27%.

Looking at the developed target, table 7 shows that the control variable deal value is the only control variable which has a significant effect on cumulative abnormal returns, for a 3-day window. 4.574128 shows that deal value increases shareholder return of the acquiring firm by 4.57% on a 5% significance level. Fuller et al (2002) argue that when relative deal size, measured as deal value divided by acquirers’ total assets, is large, then the cumulative abnormal return will be positive on a 3-day event window. In that case, a large relative deal size explained by a high transaction value makes sense. Lastly, the R2 of the short 3-day event window [-1,1] is higher than the R2 of the 41 day event window. An R2 of 20.01% and 12.98% is found respectively.

Table 7 Regression results CAR Emerging and Developed target

Emerging target

Developed target

Dependent variable: CAR

Window [-1,1] Window [-20,20] Window [-1,1] Window [-20,20] (1) p-value (2) p-value (3) p-value (4) p-value Cash 0.0935267 0.965 3.645716 0.351 0.8497291 0.517 1.66424 0.682 (-2.130954) (-3.858155) (-1.304133) (-4.047293) Firm size -1.992337* 0.074 -2.260652 0.228 -0.3850583 0.537 -8.331652 0.147 (-1.083624) (-1.844901) (0.6212872) (-5.680033) Crisis 2.118965 0.213 4.264 0.268 1.389737 0.194 -1.353223 0.768 (-1.671581) (-3.793975) (-1.060217) (-4.57505) Wave 1.257179 0.327 -2.66692 0.304 -0.4613921 0.610 -3.560772 0.397 (-1.265744) (-2.555904) (0.8999306) (-4.181979) Sector 0.9330715 0.506 0.6765297 0.773 -0.7902152 0.429 -0.0647863 0.986 (-1.388003) (-2.323417) (0.9927516) (-3.70396) Deal value 1.937151 0.257 -0.502272 0.857 4.574128** 0.017 3.69.441 0.531 (-1.683456) (-2.773588) (-1.864197) (-5.875559) ROE 0.0402734 0.331 -0.165579* 0.072 0.0191683 0.169 -0.019506 0.719 (0.0408642) (0.0892507) (0.0137925) (0.0540589) Rsize -9.928784 0.117 1.19583 0.937 4.55362 0.102 -5.419249 0.730 (-6.190952) (-1.49679) (-2.751444) (-1.564277) Constant 3.778271 0.480 2.011457** 0.029 -9.320649* 0.056 2.425748 0.302 (-5.298877) (-8.841755) (-4.789108) (-2.335693) N 46 46 81 81 R2 _0.1827 _0.2529 _0.2001 _0.1298

Notes: robust standard errors in parentheses. ***, **, * indicate significant at 1%, 5% and 10% level respectively

Value creation through cross-border mergers and acquisitions on acquirer’s shareholders in emerging and developed markets