The potential influence of the Brexit referendum on cross-border M&A : testing for firm performance and international diversification

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The Potential Influence of the Brexit Referendum on

Cross-Border M&A

Testing for firm performance and international diversification

UNIVERSITY OF AMSTERDAM

MSc Finance

Specialisation Corporate Finance

Author: J.M.V. Kuijvenhoven

Student number: 10663940

Thesis supervisor: dr. Vladimir Vladimirov Finish date: July 2018

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STATEMENT OF ORIGINALITY

This document is written by student Jetse Kuijvenhoven who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have used in creating it.

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

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PREFACE AND ACKNOWLEDGEMENTS

Using this part, I want to thank all the professors and teachers at the University of Amsterdam for the past master year. I think that it was a year full of hard work and a big learning curve. It gave me lots of new insights and forced me to work in groups more than ever. Furthermore, I learned several techniques and theories which already proved its worth in several business courses, inhouse-days and job interviews.

Additional to this is that I would like to thank my supervisor Dr. Vladimirov for the pushes in the right direction and his critical way of thinking.

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ABSTRACT

In this thesis the impact of the Brexit referendum on cross-border Mergers & Acquisitions is tested. This is tested for the two-year period of 24 June 2015 up until 24 June 2017. In this period the declaration of the result on 24 June 2016 is used as to measure the impact. This thesis tries to use the referendum as an illustration as to what the impact is of leaving the European Union. Using panel data and fixed effects regression, this thesis finds a significant decrease in deal volume for inbound, outbound and domestic acquisitions. Using an event study for the event window (-5, +5) the Cumulative Abnormal Returns (CAR’s) are

calculated. The outcomes show an insignificant increase in CAR’s for outbound acquisitions after the referendum. Furthermore, following a difference in difference method, it is shown that there is a significant positive increase for firms increasing their foreign sales after the Brexit. Using the Brexit as example for further EU analysis, a possible leave from the European Union seems to have significant influence on cross-border M&A.

Keywords: Brexit, Political Uncertainty, Event Study, Announcement Returns, Panel Data, DiD

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LIST OF TABLES

[Continuous numbering throughout the thesis]

Table 1: Summary Statistics p. 24

Table 2: Summary Statistics Foreign Sales over Sales p. 24 Table 3: Amount of M&A Inbound, Outbound and domestic p. 28

Table 4: CAR statistics and significance p. 31

Table 5: Influence of Foreign Sales on CAR (-5,5) and CAR (-10,10) p. 34 Table 6: Treatment effect of after Brexit for Foreign Sales CAR (-5,5) p. 37 Table 7: Treatment effect of after Brexit for Foreign Sales CAR (-10, +10) p. 47 Table 8: Treatment effect of after Brexit for Foreign Sales CAR (-5, +5), Dec 2015-Dec 2017 p. 48

LIST OF FIGURES

[Continuous numbering throughout the thesis]

Figure 1: The Historical Spot Exchange Rates for GBP to EUR: Year 2016 p. 11

Figure 2: Inbound Acquisitions CAR (-5, +5) p. 29

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CHAPTER 1 Introduction

The objective of this thesis is to measure the impact is of political uncertainty surrounding the Brexit referendum of June 23 2016 on announcement returns of acquirers. Several points show why it is reasonable to perform this study. First of all, earlier research has shown that events of a political nature have led to market transaction interruptions in 25 countries, including Chile, France, Germany, Japan and Portugal. This proves that there could be an influence of political uncertainty on returns.

Secondly, because the UK market is a developed market, and all the companies that will be tested for are public, financial information is easily available for the market. This would mean that the market incorporates most of the information into announcement returns (Beaulieu et al., 2006). Furthermore, the market was not expecting the Brexit referendum to result in a vote to leave the European Union. Bookies placed about a 90% chance of rejection of the Brexit referendum (Bloomberg, 2016). So this would mean that the political uncertainty which arose from this referendum could hardly be resolved by the market beforehand.

Aforementioned is not quite common in election events, for which opinion polls can usually reveal the outcome within a reasonable range (Beaulieu et al., 2006). Because the outcome was not expected, the event is exogenous and gives an opportunity to test what unexpected political uncertainty does for announcement returns.

The third reason is that there has been few to no research about what the influence of such an unexpected event on cross-border M&A is. Most of the literature focusses on stock returns. On top of that, to the best of my knowledge no research has been done whether there is an additional impact for more internationally diversified companies. Current thesis will contribute in finding a continuous variable which will account for firms that are

internationally diversified. This will be tested using three different measures of international diversification. This testing is done because of the political uncertainty UK investors are likely to increase their share in the European Union and vice versa. There will be a focus on outbound UK acquirers and domestic UK acquirers in this thesis.

Lastly and of considerable importance, because it is an exogenous event and there is a high level of Mergers and Acquisitions (M&A) in the United Kingdom, we can test what the implications are for unexpected political uncertainty in the EU. More specifically, we can test what the implications are for a country which is about to step out of the European Union. How do investors react when it is expected that a country is about to leave EU? The impact of such a leave seems to be ever more relevant with the election of the conservative right parties

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in Italy. Resulting from this election Italy’s exit from the European Union is more likely to happen. At the moment more than half of the Italian voters turned against Europe. Additional to this is that Matteo Salvini, leader of one of the winning parties, called the European Union ‘the Titanic about to sink’ (The New York Times, 2018). Additional to this is the example of Greece. The Guardian (2017) reported that in February Greece was again on the verge of leaving the European Union. Greece was not able to meet bailout conditions, and pressure rose in Germany and US, which lead to more reasons to leave the EU. All three issues, the Brexit, the Italian election and the example of Greece show that the sentiment about the European Union has changed.

This study will make an attempt in testing what the market expects from firms based in countries that are about to leave. One of the advantages from the European Union and the Single Market as part of it, is the free movement of capital. If an exit actually would take place, this benefit amongst others will not be available anymore. Beaulieu et al. (2006) show that the political uncertainty caused by a referendum can disrupt the market. They prove this by testing for stock returns caused by the 1995 Quebec referendum. Again with the Brexit referendum, newspapers and reports seem to show the same implications for this case.

An article regarding the influence of the Brexit referendum follows the header: ‘Brexit effect shakes up London deal making’ (Financial Times, 2017). This shaking up is also to be seen in a study of PwC. This report states that the Brexit can cost up to USD 240 billion in lost M&A activity in the next five years, while M&A levels may fall with 8% in Europe in both 2017 and 2018 (PwC, 2016). Furthermore, another source reports an increase in domestic deal-making opposite to the falls in inbound and outbound UK M&A volumes. A decline of 12.9% inbound and a decline of 9.4% outbound (Business Insider, 2017).

The potential Brexit leads to financial market volatility, currency movements and increased uncertainty following the referendum. These factors have an influence on the valuation of the firm and therefore the return. A company located in the UK, with costs predominately nominated in pounds can benefit from the currently devaluated sterling. However, for companies located in the Eurozone and exporting much of their product to the UK, it could influence the return negatively (PwC, 2016).

The referendum resulted in a lot of uncertainty about what the implication of an actual Brexit will be for firms, from both the EU and the UK. The idea of leaving the Single Market and the European Union is no longer only an idea by the UK. With the election in Italy, another country might be heading for an exit. To see whether the market perceives the European Union as something positive, the acquisitions before and after the referendum will

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be compared. In this thesis the Brexit referendum serves as an example for countries that are willing to exit as well. If, for example, the announcement returns of UK outbound

acquisitions increase, the market perceives it as something positive that the firm wants to remain part of the Single Market. This without knowing the exact consequences resulting from an actual leave by Britain. This leads to the following research question which will be answered in this thesis.

‘How does political uncertainty, regarding the leave of the European Union, influence cross-border M&A?’

This thesis is laid out as follows: section 1 is an introduction about the issue of the Brexit, section 2 is the literature review on cross-border M&A, the European Union and

diversification. The method to test what the impact is of the referendum is discussed in section 3. In data 4 the sources of the data and summary statistics are described. Section 5 shows the empirical analysis, followed by the robustness checks in section 6. The last section shows a discussion and conclusion.

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CHAPTER 2 Theory and Literature Review

2.1 Cross-border M&A

To measure the impact of political uncertainty following the referendum, this thesis will be testing for cross-border M&A. Testing will be done based on the amount of cross-border acquisitions and announcement returns following cross-border acquisitions. Literature implicates different aspects as to why cross-border M&A has different outcomes than domestic acquisitions.

Shimizu et al. (2004) display three theoretical perspectives on why investors should engage in cross-border M&A. First of all, the argument whereby M&A is used as a mode of entry into a foreign market is stated. In general, entry mode choices can vary from equity-based (e.g. greenfield, acquisition, joint ventures) to non-equity-equity-based (e.g. export alliance). The equity based provide the highest form of control over internal resources. The second argument is the use of cross-border M&A as a dynamic learning process. Given the risks involved in these M&A’s it is important that each step, pre and post, involves learning. In every step of the process, the acquirer should improve its knowledge considering future acquisitions. The last argument Shimizu et al. (2004) mention is the value creating strategy. They state that cross-border M&A provide integrating benefits of internalization, synergy and risk diversification and thereby create wealth for both acquirer and target-firm shareholders.

The literature displays four categories as to why cross-border rather than domestic acquisitions create more value for shareholders, and are therefore more interesting to engage in. The first of those is international risk diversification in which, under certain market inefficiencies, investors could benefit from international corporate diversification through cross-border acquisitions. Secondly, the market increases in its accessibility. International takeover may be motivated by the need to operate in a certain country to avoid trade barriers. An example of this was the cross-border takeover activity following the passing of the Single European Act in 1985. At the time, non-EU firms actively acquired EU companies to join in the efficiencies of the Act (Danbolt, 2004). Following the referendum, it could be the case that acquirers from the United Kingdom are more willing to acquire into the European Union. This arises due to the fact that they will not be part of the efficient market anymore.

Another category could be the exchange rate effects. Earlier studies indicate that the level of cross-border M&A into the USA was higher whenever the U.S. dollar was relatively weak. Figure 1 shows the historical spot rate for EUR to GBP in the year 2016. This shows

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that after the notification of the outcome, the market responded with a loss of trust in the Pound Sterling. Danbolt (2004) argues that if there is a decline in the exchange rate, the country with the weaker currency is more attractive for foreign acquirers. In this case this would mean that there would be an increase of cross-border M&A whereby the UK would be the target country. This because of the fact that acquirers can buy the same company for a lower cost. A vote for a leave out of the European Union leads to more uncertainty. Following this uncertainty, the market perceives the currency as riskier which leads to a decline in exchange rate.

Figure 1: Spot Exchange Rates

This figure shows the exchange rate for the year 2016. On the x-axis the months are given from January 2016 to January 2017. The y-axis displays the exchange rate. The exchange rate is given as Euro to Sterling (€/£).

Lastly, managerial factors seem to be a driver of cross-border acquisitions rather than

domestic acquisitions. Danbolt (2004) and other literature find that, also in acquisitions, there is a case of agency conflict, with bidding company management aiming to maximize their own utility. Through these acquisitions, the managers then can increase their power, status and salary. Roll (1986) states that bidding companies tend to overestimate the value of economic benefits of the merger. Assuming that international companies are more difficult to value than domestic firms, there could be a bigger valuation error in the bid. This would mean that the acquirer’ returns would be lower and the target’s returns higher. A leave from the European Union will also lead to less information available for investors from the United Kingdom. Hence, it could be the case that the valuation errors increase.

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Historical Spot Ex change Rates for GBP to EUR: Year 2016

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Jan Feb M ar Ap r M ay Jun Jul Aug Sep Oct N ov Dec Jan

1 .1 1 .1 5 1 .2 1 .2 5 1 .3 1 .3 5 1 .4

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2.2 The EU and the Policy Uncertainty 2.2.1 Policy Uncertainty

The Brexit referendum causes uncertainty about what kind of a Brexit there will be. A hard Brexit would result in no further ties with the EU. On the other hand, negotiations could also result in a Brexit in which it is still connected to the European Union to some extent. This uncertainty is likely to affect cross-border M&A and this section explains the implications of uncertainty for investors.

In the literature, policy uncertainty arises when policy changes cause a deviation in the economic environment. Pastor & Veronesi (2012) lay out two different sorts of uncertainty. The first type, which is called political uncertainty, relates to whether changes are made in current government policies. The other one, impact uncertainty, looks into the uncertainty about the impact which will arise due to a new government policy. This will look into what the effect is for the profitability of the private sector after the new government policy. This thesis will look into the case of impact uncertainty, in which I will test for the impact of the potential Brexit on announcement returns and amount of cross-border M&A.

Uncertainty can arise from different political events. Whether it is an election outcome or referendum, the event is likely to affect the private sector. Political uncertainty is relevant for investors performing corporate investments in the sense that they have implications for industry regulations, monetary and trade policy, and taxation (Julio & Yook, 2012). The same goes for the impact of a public vote as the Brexit referendum. So the intuition of the Brexit influence on the level of corporate investments domestically as well as cross-border is easily made. If an election, in this case the referendum, can potentially result in a bad outcome from a firm’s perspective, the option of waiting out the uncertainty is more rewarding for a

company. Aforementioned is the case because firms become more cautious and will delay their initial planned investment. Subsequently, the amount of M&A should decrease after the announcement of the referendum outcome.

2.2.2 The European Union

To be able to understand what the influence is of a potential Brexit for investors, it is important to understand what the benefits of being part of the EU are. One part of the

European Union, of which the United Kingdom is a member, is the Single Market. One of the objectives of this Market is to lower or eliminate the trade barriers within the European member states. This then would result in an increase in competition and would therefore

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reduce the price-cost margins. Because the competition was higher and the trade barriers were removed, cost of products decreased and overall welfare increased (Allen et al., 1998). If the Brexit continues, British firms will be excluded from this market and higher tariffs are likely to arise. Since importing UK products would be more expensive for a European customer, the chance that revenue for UK firms decline exists. More broadly, a country leaving the

European Union is likely to see a decrease in revenues.

The European Commission (1996) indeed shows an important increase in trade and in the EU’s amount of foreign direct investment after formation of the Single Market. They also show that lifting trade barriers resulted in an increase of trade volumes of 20-30% in

manufacturing products for the member states. The same report indicates that a large part of the increase in foreign direct investments is associated with mergers and acquisitions within member states, which were multiplied as soon as the Single Market was implemented.

Additional to this is that regional trade agreements, like the Single Market, can trigger cross-border merger waves. When competition is fostered, trade liberation can favour an environment whereby low-cost firms find it profitable to acquire or merge with high cost firms. The European Union enhances this competition through a reduction in trade costs, eliminations of exchange rate risk and improved price transparency. This could trigger cross-border merger waves (Neary, 2007). A leave from the European Union, and therefore the assumed leave of the Single Market, is likely to result in a decrease in cross-border Mergers & Acquisitions.

One of the characteristics of the Single Market is the free movement of capital. Resulting from this free movement, financial integration within this area is increasing. This integration can partly be explained by the reduction in the cost of capital and partly because of the elimination of risk. The Single Market is an agreement within Europe consisting of 28 member states. Such an agreement can impact cross-border M&A through higher

profitability, as the Single Market increases market size and competition. Furthermore, the financial integration will be followed by a decrease in transaction costs (Coeurdacier et al., 2009).

Bhagwat et al. (2016) provide evidence that higher uncertainty will decrease deal activity. They also show that the rise in expected costs during the interim period should imply that higher uncertainty would make the deal value less appealing. Therefore, political

uncertainty is assumed to have a decreasing effect on the number of announced mergers. Following this theory, it is likely that after a country voted to leave the European Union, investors are less likely to engage in cross-border M&A.

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2.3 International diversification and its benefits

Theory about international diversification and the benefits surrounding this diversification are needed to answer the question as to which firms are more affected by the referendum. Are firms that are diversified in the European Union more or less affected. Positively or negatively?

The increased integration of world product markets over time has made global diversification more feasible (Denis et al., 2002). Following this argument, an integrated market like the European Union is likely to have international diversification. International acquisitions allow firms to diversify abroad and literature have shown three different types of benefits which arise from this: operational, strategic and financial benefits.

The possible leave of the United Kingdom from the EU could lead to a loss for UK companies which are planning to invest in Europe. This loss is caused by the decline in potential operational benefits. International diversification presents these benefits through industrial organization and transaction-cost economies. A leave from the European Union by one of the member states will lead to more rules and regulations for the free movement of capital. The European Commission (1996) showed an increase in cross-border M&A

following the formation of the Single Market. A leave from this market will therefore lead to a decline in cross-border acquisitions. Because of this, firms undergoing a leave of this market are less likely to exploit intangible firm-specific assets and imperfections on the market (Markides & Ittner, 1994). Companies that acquire into the European Union, or already have subsidiaries in the EU, will be affected positively by the referendum compared to firms which are not internationally diversified. Stated benefit aligns with the internationalization theory. This states that direct foreign investment occurs when a firm can increase its value by internationalizing markets for certain of its intangible assets. These assets might include superior production skills, patents, marketing abilities, managerial skills or consumer goodwill (Morck & Yeung, 1991).

Another rationale of the leave of the Single Market is strategic. If there will be an actual leave, UK firms will have a disadvantage compared to their competitors. Competitors, active in a different member state, will still be able to seize all opportunities which arise within the Single Market. The reasoning behind this is that as external conditions face an industry change, new transaction opportunities emerge. If the new opportunity is seized by a competitor, their profitability will improve while the profitability of the rival declines. By acquiring foreign competitors, a firm will bring a more diverse portfolio of assets and is therefore more likely to seize new opportunities. It improves their own position while

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excluding the competition. Therefore, firms UK firms that acquire subsidiaries in the Single Market will have positive announcement returns. This leads to the conclusion that firms either undertake cross-border acquisitions to improve their own performance or limit that of their competitors (Markides & Ittner, 1994).

Again, leaving the Single Market could also have an influence for investors which is of a financial nature. Because economic activity per country is not much correlated,

diversification across international boundaries should improve shareholders’ risk-return opportunities (Markides & Ittner, 1994). Additional to this is that literature also sees value increase because firms that are multinational, have more opportunities for tax avoidance and/ or access to relatively low-cost inputs (Morck & Yeung, 1991). Denis and colleagues’ study (2002) show that a multinational firm has the opportunity and ability to lower the firm’s tax liability by exploiting differences in tax systems across countries. This would mean that firms that are diversifying right after the declaration of the result, should be perceived as positive. This while the capital flow is not regulated yet and it is therefore easier to acquire cross-border for UK investors.

Comparing EU competitors with UK companies, the European companies will be less restricted and have the right to move goods and people freely. After a possible leave of the European Union, the United Kingdom doesn’t yet know what the consequences will be for their international investments. Denis et al. (2002) their paper classifies a firm as globally diversified if it reports any sales by foreign subsidiaries. Following this measure, I am also assuming that a company is diversified when one or more foreign subsidiaries make revenue for the company.

Because it is likely that there will be more rules and regulations after the final Brexit, companies that are already active in Europe will be less influenced or even positively

influenced. Furthermore, following the argument of Allen et al. (1998) and the European Commission (1996) the market is likely to react positively to a firm which increases its share by acquiring in the European Union. Partly because there is still the option to make use of opportunities, there is high competition and there is more trade.

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2.4 Formulation of Hypotheses

Based on the above stated literature, the referendum is likely to show an increase in inbound acquisitions. Literature showed that the formation of the Single Market lead to an increase in cross-border acquisitions. A possible leave of this market will therefore result in a lower amount of acquisitions. Also investors are more likely to wait out the uncertainty. This leads to a decrease in inbound acquisitions after the referendum (1a). Furthermore, based on the exchange rate argument, there will be less money available for UK acquirers to make outbound cross-border acquisitions into EU countries (1b).

Hypothesis 1a: The Brexit referendum has a decreasing effect on the number of cross-border acquisitions in which the UK is the target company.

Hypothesis 1b: The Brexit referendum has a decreasing effect on the number cross-border acquisitions in which the UK is the acquiring company.

Following earlier research, the uncertainty about the policy changes have a negative effect on acquisitions in which the UK company is the acquirer (2a). Because what will happen next is

unknown, the market will perceive the acquisition as riskier. Because acquisitions inbound could have been done at a lower cost, due to the low exchange rate, announcement returns should be higher for the cases in which the UK company is the target (2b).

Hypothesis 2a: The Brexit referendum has a negative effect on the announcement returns of cross-border acquisitions in which the UK-company is the acquirer.

Hypothesis 2b: The Brexit referendum has a positive effect on the announcement returns of cross-border acquisitions in which the UK-company is the target.

Previous literature of Markides & Ittner (1994), Morck & Yeung (1991) and Denis et al. (2002) show different aspects of diversifying internationally. A possible leave of the Single Market, in which there is free movement of capital, will lead to more constraints regarding cross-border acquisitions.

Following the Brexit, it is likely that UK firms experience more difficulties to acquire cross-border into the European Union. The firms that are already internationally diversified, measured by the amount of revenues generated by subsidiaries, will be able to continue to exploit these benefits. This is caused by the fact that they have European subsidiaries and are less likely to be affected by the leave from the Single Market. Enlarging their share in the European Union, and therefore enlarging the option to the benefits, will lead to higher announcement returns. The comparative advantage of these internationally diversified companies to firms that are not diversified, leads to higher firm performance surrounding an acquisition. Firms that acquire subsidiaries internationally at this moment, without restrictions on movement of capital, will be less influenced by a Brexit in the future.

Hypothesis 3: Outbound acquisitions by UK companies, which are internationally diversified, will result in an increasing effect on the firm performance after the referendum.

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CHAPTER 3 Method

3.1 Amount of M&A’s

In this thesis, I will be testing whether there is an influence of the Brexit on cross-border M&A. Testing this will be done over-time ranging from June 2015 to June 2017. In this sample the 24th_{of June 2016 (the day that the results were announced) will be used as the}

event date and the influential dummies will be used from this date onwards.

Because I will be interested in what the impact of the uncertainty will be on inbound and outbound cross-border M&A, this thesis will test whether the volume decreased after the results of the referendum. This is in comparison to the year before the public vote. Using the method of Cao et al. (2009) the following regression will be used:

Ln(𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑟𝑜𝑠𝑠 − 𝑏𝑜𝑟𝑑𝑒𝑟 𝑎𝑐𝑞𝑢𝑖𝑠𝑖𝑡𝑖𝑜𝑛)𝑖,𝑡= 𝛽0+ 𝛽1𝑃𝑜𝑠𝑡 − 𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑑𝑢𝑚 𝑦𝑒𝑎𝑟𝑖,𝑡+ 𝛽2𝑋𝑖,𝑡+ 𝜖𝑖,𝑡 (1)

This regression is used to analyse whether the uncertainty from the outcome affect the inbound and outbound mergers and acquisitions of the United Kingdom. The dependent variable is the natural logarithm of 1 plus the number of cross-border acquisition deals with country i in year t. The acquisitions post-referendum are denoted by a dummy-variable, which equals one if year t is the year after the 24th_{of June 2016.}

In this analysis X denotes the control variables. Both Cao et al. (2017) and Coerdacier et al. (2009) use the same control variables. These include the economic development (GDP per capita), GDP annual growth rate and trade-to-GDP ratio (sum of imports and exports as a percentage of GDP). Furthermore, the size of the acquiring firm is measured by the natural logarithm of assets, the natural logarithm of deal value is included and the exchange rate. Only assets bigger than 0.5 million were included (Danbolt, 2004). Lastly there is controlled for whether the bid was competing and whether the acquiring firm and the target firm are active in the same industry. The bid was competing when there was more than one bidder. Therefore, this is a dummy variable equal to one if the bid is competing and zero otherwise. Same industry is a dummy variable which equals one if the acquisition is related. Based on the methodology of (Markides & Ittner, 1994), the largest two-digit SIC industry were first identified. If the acquired company was from the same two-digit SIC industry, the acquisition was related.

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3.2 Influence on Firm Performance

The regression will give a relation whether the amount of M&A’s increased or decreased. However, it will not give a causal relationship between the amount and the influence of the referendum. Because of this, two additional tests, based on announcement returns and influence of international diversification, will be done. This will be tested using deal-level data, the outcomes of cross-border acquisitions in the period around the referendum. I presume that there will be a negative influence of the public vote on returns of companies which acquire out of the United Kingdom. Cross-border acquisitions in which a UK firm is the target are hypothesized to be influenced positively.

Testing for this will be done by first testing for significance on the Cumulative Abnormal Returns (CAR) which will compare the year before and after the referendum. To calculate the abnormal returns around the event date, the following formula will be used:

𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 −∝̂− 𝛽𝑖 ̂ 𝑅𝑖 𝑀,𝑡 (2)

Normal returns (𝑁𝑅_𝑖𝑡) will be calculated using the OLS Market Model. This model calculates the predicted return by regressing the actual return over the market return. This is done by the estimation window of -250 to -30 trading days prior to the event. Hereby having 𝛽_𝑖 as a predictor for the normal return. By subtracting this return from the actual stock return, which is given by the Datastream database, the abnormal return return (𝐴𝑅𝑖𝑡) can be calculated.

The CAR’s will be focused on the acquirers, because of the fact that the additional expected uncertainty will be incorporated in the stock price of the acquirer. This works both ways, so either for an inbound as well as an outbound investor. This results in the following formula based on Tielmann & Schiereck (2017) and Brown & Warner (1987):

𝐶𝐴𝑅𝑖,[𝜏1,𝜏2]= ∑𝜏1𝑡=𝜏2(𝑅𝑖,𝑡−∝̂− 𝛽𝑖 ̂ 𝑅𝑖 𝑀,𝑡) (3)

Bruner (2002) gives an overview of research done on announcement returns and the used event windows. The majority of the studies use an event window of (-5, +5).

Furthermore, a lot of literature is taking into account the event window (-10,+10). Also Dissanaike et al. (2016) use the event window of (-5, +5). Based on this information my primary focus will be on this event window, and will do robustness checks for the window

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from (-10,+10). By doing a two-sided regression there will be checked whether the announcement return was significant in the period surrounding the referendum.

𝐻0: 𝐶𝐴𝑅 = 0 (4)

𝐻1: 𝐶𝐴𝑅  0 (5)

Hypothesis is that the CAR’s for inbound transactions, so other European countries acquiring in the UK, will increase after the referendum. For outbound transactions, in which a UK company acquires a firm from one of the 28 member states, this is hypothesized to be negative after the referendum. This effect will be tested separately for inbound and outbound.

3.3 Influence on UK acquirers which are foreign oriented. 3.3.1 Influence of foreign sales on UK announcement returns

To test what the impact of internationally diversification, classified by Denis et al. (2002) as reporting any sales by foreign sales, is on the announcement returns, domestic and outbound transactions will be analysed. This thesis will not look into the the influence of transactions in which the acquiring nation is one of the European Union member states. This is because there is assumed that there will be no influence on these companies because they will stay part of the Single Market, no matter what the outcome of the Brexit is. This assumption lies in the fact that acquirers from one of the member states are still able to acquire with the free movement of capital. For the market there is not an extra incentive to appreciate these acquisitions into the United Kingdom as higher. Acquirers which are part of the Single Market will still have the opportunity to profit from the cross-border benefits, even if the UK continues to leave the European Union. So the impact of their foreign sales on their

announcement returns will not be looked into.

To see whether the foreign sales has any impact on the announcement returns, the CAR(-5, +5) and CAR(-10, +10) will be regressed on three different measures of foreign sales. The first measure, as defined by Denis et al. (2002), is foreign sales over total sales. To check for robustness, the five-year average foreign sales over total sales will be included, as well as the percentage change foreign sales over sales from 2016 to 2017. This results in the following regression:

CAR(−5, +5)𝑖,𝑡= 𝛽0+ 𝛽1𝐴𝑓𝑡𝑒𝑟 𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑑𝑢𝑚𝑖,𝑡+ 𝛽2𝐹𝑜𝑟𝑒𝑖𝑔𝑛 𝑆𝑎𝑙𝑒𝑠𝑖,𝑡+ 𝛽3𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐹𝑜𝑟𝑒𝑖𝑔𝑛 𝑆𝑎𝑙𝑒𝑠𝑖,𝑡+

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The same specification holds for CAR(-10, +10). Also there will be accounted for industry and acquiring nation fixed effects and the standard errors will be clustered for acquiring company CUSIP.

3.3.2 Influence of foreign sales on UK announcement returns after Brexit

To test whether there is additional influence for an acquiring company which has foreign sales, a treatment effect needs to be calculated. The most common measures for testing treatment effects are the Difference-in-Difference (DiD) method and 2-Staged Least Squared (2SLS) method. This thesis will use the DiD method.

The data used is panel data. Because this is the case, it allows me to consistently estimate treatment effects without having the assumption of ignorability of treatment and without an instrumental variable. The ignorability of treatment assumption states that the choice to be assigned to the control group or the treatment group can be assumed to be effectively random. Because of this, the effects of unobserved factors can be ignored

(Woolridge, 2002). It is plausible that acquirers delay their acquisition till after the declaration of the result because of the political uncertainty which arises (Julio & Yook, 2012). This then will lead to a sample which is not random. The acquirer chooses whether they will be in the control group (acquisitions before referendum) or in the treatment group (acquisitions after referendum). The advantage of using panel data is that this will not be an issue and the ignorability of treatment assumption does not need to hold.

Another benefit of having panel data is the fact that there is no instrument needed to measure the impact of the event. The 2SLS method is the other measurement to test for a treatment effect. For this method an instrument is needed. Because the outcome of the Referendum was unexpected there are not much variables which can explain the result. The instrument is needed in the first stage to test for in the second stage. Because there is no clear exogenous instrument which is also correlated with the choice to leave the European Union, 2SLS can not be used.

Additional to this is the fact that Tielmann and Schiereck (2016) also use a DiD method to see what the impact of the referendum is. They test this for stock returns. Adopting this information, the DiD method is the method which will be used to measure the treatment effect of the referendum. Using panel data, this method will lead to the lowest endogeneity. For this thesis this means that all acquisitions and announcement returns from the 24th_{of June}

2015 up to the 24th_{of June 2016 will act as the control group. The year after the referendum,}

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will be done by creating an interaction variable between the dummy variable ‘After

Referendum’ and each of the internationally diversification measures. These measures are all

continuous variables which lead to an interaction term of a binary times a continuous variable. For example:

𝐴𝑓𝑡𝑒𝑟 𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑑𝑢𝑚𝑖,𝑡∗ 𝐹𝑜𝑟𝑒𝑖𝑔𝑛 𝑆𝑎𝑙𝑒𝑠𝑖,𝑡 (7)

𝐴𝑓𝑡𝑒𝑟 𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑑𝑢𝑚𝑖,𝑡∗ 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐹𝑜𝑟𝑒𝑖𝑔𝑛 𝑆𝑎𝑙𝑒𝑠𝑖,𝑡 (8)

𝐴𝑓𝑡𝑒𝑟 𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑑𝑢𝑚𝑖,𝑡∗ 𝐶ℎ𝑎𝑛𝑔𝑒 𝐹𝑜𝑟𝑒𝑖𝑔𝑛 𝑆𝑎𝑙𝑒𝑠𝑖,𝑡 (9)

This interaction term will be created for all three measures of international diversification. The measure used by Denis et al. (2002) is the ‘Foreign Sales over Total Sales’. To check for robustness, I will also include a 5-year average of ‘Foreign Sales over Total Sales’ and I will calculate the percentage change in ‘Foreign Sales over Total Sales’ from 2016 to 2017. Moeller and Schlingemann (2005) also use a percentage change of foreign sales as

measurement. Their focus is before and after the acquisition. Because I would like to know the effect of foreign sales before and after the referendum, the focus will be on the years 2016-2017. This will lead to three different interaction terms and three different regressions.

These regressions will look into the effect of being internationally diversified on announcement returns. Therefore, they are specified the same as in (6) but also include the interaction term. ‘After Referendum’ is specified as a dummy variable equal to 1 when the acquisition was done after the declaration of the result on the 24th_{of June 2016. The}

internationally diversification measure is a continuous variable. This thus means that the coefficient of the interaction term accounts for acquisitions after the referendum, for firms that have foreign sales. As explained in section 2.4, I will be expecting an increase of announcement returns for firms that acquire into the European Union which already have foreign sales. This reasoning follows the theory of Markides & Ittner (1994), Morck & Yeung (1991) and Denis et al. (2002). Internationally diversified firms that enlarge their European Union share, and therefore enlarge their potential benefits, will positively influence the announcement returns. This will result in positive coefficients for interaction terms (7)-(9) which is also stated by the hypotheses.

Again the same control variables as in (1) are used and there is accounted for industry and acquiring nation fixed effects. Standard errors are clustered for acquiring company. In the appendix the exact specifications are given.

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CHAPTER 4 Data

4.1 Data Sources

As mentioned before, I will use the dataset from June 2015 until June 2017. For testing the hypotheses, I will need information on all acquisition deals in which the United Kingdom is involved. This means European Union firms acquiring into the United Kingdom, UK firms acquiring into the EU, and domestic deals. Further on stated as inbound, outbound and domestic acquisitions respectively. The focus of the analysis will be on the day after the EU referendum in the United Kingdom. This following the declaration of the result as of the 24th

of June 2016 (Tielmann & Schiereck, 2017). Therefore, I will look into all acquisitions announced and completed in the two years from the 24th_{of June 2015 up until the 24}th_{of June}

2017. Multiple acquisitions done by the same company, announced on the same date, will be excluded from the sample. The announcement effect will otherwise be interpreted double or even triple wise.

The data is available at Thomson One. In this sample, LBOs, spin-offs

recapitalizations, self-tender offers, exchange offers repurchases and privatizations are excluded. I also will focus on acquisitions in which the acquirer will receive the majority interest (Cao et al., 2017). After constructing the sample based on Thomson One, the

increasing number of acquisitions before and after the referendum can be estimated. Based on Cao et al. (2017) I also will use GDP, GDP growth and Trade over GDP as control variables. This data is downloaded from ‘The World Bank’. Data like size, measured by amount of assets, deal value and whether the bid was competing was downloaded from Thomson One as well. The last control variable, the exchange rate, comes from ‘Pound Sterling Live’.

To test for the second and third hypotheses I will be calculating the abnormal returns as shown in the method part. Campa and Hernando (2004) state that to see a change in abnormal returns due to the uncertainty of an event each merger has to satisfy selection criteria. Both the target and acquiring companies are from EU countries, the acquirer is a public company and the returns are available for the acquirer. The stock returns, the actual returns, of all public acquirers are available at Thomson Reuters Datastream.

To calculate the abnormal returns, a normal return is needed as well. Based on

Dissanaike et al. (2016), who use a European market index as benchmark index, I will use the Europe STOXX Europe 600 index. They find that there is no significance difference between a market index for the European region compared to individual indices. This index has a fixed number of 600 stocks, representing large, mid and small capitalization companies across

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seventeen European countries (Stoxx.com, 2018). Therefore, this will give an insight in a diversified market, controlled for different countries. This market index is also available at Thomson Reuters Datastream.

Using these market returns and the individual stock returns, the abnormal returns can be calculated. This will be done by the OLS Market Model which compute the abnormal returns as the actual return in the event window minus the expected return whenever the transaction would not have happened. Using the method of Cao et al. (2017), my estimation period for the expected return will (-252, -30) days before the event. Means and medians of the different Cumulative Abnormal Returns are given in the results section.

4.2 Summary Statistics

Table 1 provides an overview of the summary statistics of both the control variables as well as the dependent variable in the first regression. Each sort of acquisition is again separated in whether it was an inbound, outbound or domestic acquisition. Mostly because an inbound acquisition will have different means, for example for GDP growth, then it does for outbound acquisitions. This is also to be seen in the table, for which the average GDP growth is 4.006% for inbound and 2.068% for outbound. This is probably largely due to the high divergence between the maximum and minimum value of GDP growth inbound. Of the 142 inbound acquisitions, eight have the GDP growth of 25.557%. Also, for inbound ‘Trade over GDP’ compared to outbound and domestic there seems to be a difference in the mean. To account for the outliers, both ‘Trade over GDP’ and ‘GDP growth’ will be winsorized at the 1% and 99% level.

In the control variables of ‘Size’, ‘Deal Value’, and ‘Exchange Rate’ there doesn’t seem to be much difference. This, apart from the fact that domestic acquirers seem to be smaller than cross-border acquirers size wise. Furthermore, on average there seems to be a smaller number of acquisitions inbound than outbound or domestically. But there is not much to say about this without testing.

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Table 1: Summary Statistics

Summary Statistics on various control variables and the dependent variable Number of Acquisitions. Shown here are the average, standard deviation, maximum, minimum and the amount of observations in the sample. All

statistics in this table are not winsorized yet. The observations are done in the period from the 24th_{of June 2015}

up to the 24th_{of June 2017. The sample is portioned into three different groups on the basis whether the}

acquisition was inbound, outbound or domestic.

Variable Type Average

Standard

Deviation Maximum Minimum Observations

Number of acquisitions (in Ln) Inbound 1.713 0.691 2.833 0.693 142

Outbound 4.879 1.016 5.976 0.693 136 Domestic 4.900 0.924 5.979 0.693 566 GDP Growth (%) Inbound 4.006 5.482 25.557 0.858 142 Outbound 2.068 0.193 2.346 1.936 136 Domestic 2.056 0.187 2.345 1.936 566 GDP (in Ln) Inbound 10.712 0.319 11.520 9.427 142 Outbound 10.636 0.043 10.699 10.607 136 Domestic 10.634 0.042 10.699 10.607 566 Trade/GDP (%) Inbound 66.334 27.831 169.609 43.569 142 Outbound 39.468 0.156 39.468 37.653 136 Domestic 39.468 0.000 39.468 39.468 566

Size (in Ln) Inbound 7.426 2.667 14.182 1.027 142

Outbound 7.094 2.394 12.292 0.503 136

Domestic 5.679 2.346 14.758 0.263 566

Deal Value (in Ln) Inbound 5.334 0.646 6.159 3.829 142

Outbound 5.349 0.867 6.215 1.097 136

Domestic 5.205 0.975 6.211 0.693 566

Exchange Rate (€/£) Inbound 1.254 0.103 1.440 1.097 142

Outbound 1.268 0.101 1.439 1.107 136

Domestic 1.266 0.010 1.435 1.107 566

Table 2: Summary Statistics Foreign Sales over Sales

Summary Statistics on the three different variables to measure the international diversification. All three will be used in an interaction variable to show the impact of the diversified companies after the Brexit. Average Foreign Sales is the 5-year average and the Change Foreign Sales is the change from 2016-2017 in Foreign Sales. Shown here are the average, standard deviation, maximum, minimum and the amount of observations in the sample. All

statistics in this table are not winsorized yet. The observations are done in the period from the 24th_{of June 2015}

up to the 24th_{of June 2017. The sample is portioned into two different groups on the basis whether the}

acquisition was outbound or domestic.

Variable Type Average

Standard

Deviation Maximum Minimum Observations

Foreign Sales over Sales (%) Outbound 48.969 37.710 143.45 0.000 136

Domestic 16.669 27.800 134.50 0.000 566

Average Foreign Sales over Sales (%) Outbound 42.081 35.857 111.61 0.000 136

Domestic 14.204 26.128 100 0.000 566

Change Foreign Sales 2016-2017 (%) Outbound 2.636 9.830 59.259 -37.973 136

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4.2.1 Influence Variables International Diversification

To test what the impact is for internationally diversified companies from the referendum, interaction variables are made to show how these firms are influenced after the results were announced. As said in the method part, the measure for international diversification is

‘Foreign Sales over Sales’ (Denis et al., 2002). Onwards called as ‘Foreign Sales’. In this case the foreign sales include all sales created by foreign subsidiaries. So this does not take into account the sales by export. It purely focuses on sales generated in a foreign country. This data is available at Thomson Reuters Datastream for all public companies. The same goes for the ‘5-year average Foreign Sales over Sales’. From now on stated as ‘Average Foreign Sales’. To calculate the percentage change in ‘Foreign Sales over Sales’, the following formula was used:

𝐹𝑆_∆16−17 =𝐹𝑆2017−𝐹𝑆2016

𝐹𝑆2016 (9)

By calculating the difference in foreign sales between the year 2016 and the year 2017, I hope to have included the firms’ perceptions about the leave from the European Union. So whether they, for example, increased or decreased their amount of foreign sales.

Table two, the summary statistics, show all the three variables as given by a percentage. As is to be seen there does not seems to be a large difference in averages and standard deviations between ‘Foreign Sales’ and ‘Average Foreign Sales’. As expected, summary statistics seem to show that firms that acquire outbound have more foreign sales than firms that acquire domestically. In both the variables there seems to be a big difference between the maximum and minimum and there should be controlled for outliers. Therefore, they will be winsorized at the 1% and 99% level for the further analysis. The same accounts for the ‘Percentage change in Foreign Sales’.

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CHAPTER 5 Empirical Analysis

5.1 The Impact of the Referendum on the Amount of M&A

The first specification given in the method part is used to analyse what the influence is on the amount of M&A after the declaration of the result on June 24 2016. The dependent variable, for analysing this influence, is the natural logarithm of 1 plus the number of (cross-border) acquisitions. In table 3 the first column represents inbound acquisitions, the second column domestic acquisitions and the third outbound acquisitions. The ‘After Referendum’ variable is a dummy variable equalling 1 if the announced date is after the declaration of the results and zero otherwise.

Hypothesis states that amount of M&A decreases for both inbound and outbound acquisitions. This would mean that the ‘After Referendum’ variable should be negative. This thesis strives to explain what the influence is of a leave from the European Union for cross-border Mergers & Acquisitions. Using the Brexit referendum as an example, we can see what the impact is for a country which is also on the verge of exiting the EU. Relevance lies in the fact that, as mentioned in the introduction, Italy also seems to be heading onto an exit from the EU.

Table 3 indicates a result which is in line with the hypothesized impact of the referendum for inbound acquisitions. The ‘After Referendum’ variable denotes a negative statistical significance at 5% for the amount of inbound acquisitions. So, acquisitions done by one of the 28 member states into the United Kingdom. The economic significance of this is that the year after the referendum the number of cross-border acquisitions 87.9% lower than the year prior. The decrease in acquisitions was mostly backed by the arguments of the Julio & Yook (2012) and Bhagwat et al. (2016). They find that uncertainty lowers the deal volume, because investors prefer to wait out what is going to happen.

A counter argument for the increase in inbound acquisitions would be that of the exchange rate. Countries in which the currencies are devaluated show an increase in acquisitions. With the exchange rate specified as (€/£), an increase in exchange rate would mean that more euros are needed for the same amount of pounds. Column 1 shows that the exchange rate is significant at the 10% level. This indicates that when the exchange rate declines with 1, for example from 1.22 to 0.22, the amount of inbound acquisitions increases by 365%. A decrease of 1 of the exchange rate is not realistic, but it does show the impact of a change in the variable.

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Based on this, hypothesis 1a seems to be confirmed. One of the reasons for this could be that investors find the risk of investing in an uncertain business climate too large and are currently less incentivized to engage in cross-border acquisitions. Research show that investors like to wait out the uncertainty before they continue to invest in a market (Julio & Yook 2012).

For the acquisitions done outbound the ‘After Referendum’ variable is significantly negative at the 5% level. This is line with hypothesis 1b. The coefficient implicates that after the referendum the amount of cross-border acquisitions declines with 184% compared to the year before. So this would mean that there is a large impact due to the referendum for UK investors willing to invest in one of the member states. Hypothesis 1b is largely based on the exchange rate argument. Even though the sign is correct, the variable is not significant. Looking into the control variables, only ‘Same Industry’ is significant. Because the rest is insignificant, it is likely that there are other predicator variables needed.

Domestic acquisitions also seem to decline after the referendum. The variable shows a 125% decrease in number of acquisitions when the dummy equals one. Important to state here is that the outcomes for inbound, outbound and domestic acquisitions are not per se causal. The number of acquisitions is depending on much more than whether the referendum took place. But it does give a sign to whether the declaration of the result had a negative or positive impact on the number of (cross-border) M&A.

Table 3 implicates an influence on amount of cross-border M&A following uncertainty about a EU exit. With inbound, outbound and domestic acquisitions declining after the referendum, it seems that investors are more willingly to wait out the actual results, and therefore the uncertainty. Using the Brexit as an example for the rest of the EU, this then would mean that a vote to leave the EU, and therefore the Single Market, will result in a decrease in deal level.

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Table 3: Amount of M&A Inbound, Outbound and domestic

This table shows the outcome of the panel regressions for either inbound, domestic and outbound acquisitions. Sample is from June 24 2015 up to June 24 2017. The dependent variable is the natural logarithm of 1 plus the total number of acquisitions done. The after Referendum variable is a dummy variable which takes the value of one after the 24th of June 2016 and zero otherwise. GDP, Trade/GDP, Foreign Sales, Average Foreign Sales and Change Foreign Sales are winsorized at the 1% and 99% level. In the regression there is accounted for Industry Fixed Effects. Standard errors are clustered at the acquiring firm level based on acquirer’s CUSIP, and these are reported in the parentheses below. *, **, and *** denote statistical significance at the 10%, 5%, and 1% level respectively.

Ln(Number of (cross-border) acquisitions) (1) Inbound (2) Domestic (3) Outbound

VARIABLES Acquisitions Acquisitions Acquisitions

After Referendum -0.879** -1.256*** -1.840** (0.361) (0.215) (0.932) GDP Growth -0.0207 -2.614*** -2.062 (0.0132) (0.421) (1.578) Competing -0.727*** -0.0284 -0.126 (0.208) (0.214) (0.350) Same Industry 0.0178 -0.0860 0.847** (0.196) (0.0954) (0.346) Size -0.00303 6.16e-05 -0.0137 (0.0640) (0.0210) (0.0353) Deal Value -0.0586 0.00508 0.0182 (0.0411) (0.0205) (0.0306) Exchange Rate -3.650* -2.198 -4.909 (1.998) (1.526) (6.973) Foreign Sales 0.276 -0.0138 (0.542) (0.383)

Average Foreign Sales -0.158 0.423

(0.502) (0.423)

Change Foreign Sales 0.320 -0.200

(0.275) (0.853) GDP 1.096* (0.597) Trade/GDP -0.695 (0.453) Observations 93 496 102 R-squared 0.526 0.401 0.660

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5.2 Results Event Study 5.2.1 Univariate Analysis

Figure 2 and 3 show a plot of the Cumulative Abnormal Returns (CAR’s) against the announcement dates of acquisitions done. The figures show the evolvement of the CAR’s before and after the declaration of the result of the EU referendum on June 24 2016. For inbound acquisitions there are 129 announced acquisitions and consequently 129

announcement returns. Regarding outbound acquisitions there are 122 announcement returns. Based on these returns, the abnormal return is calculated and using that the Cumulative Abnormal Returns can be estimated. The figures show the CAR’s for the event window (-5, +5).

Both figures seem to show an increase in CAR’s after the referendum, leading to a discontinuity from before to after the referendum in CAR’s. This would mean that the market sees the acquisitions after the referendum as something positive, resulting in positive

announcement returns. This implies that the referendum has a positive effect on both inbound and outbound acquisitions. Contrary to the hypothesis in which was hypothesized that the referendum would have a negative impact for outbound acquirers. It does seem to be in line with the hypothesis that acquisitions done into the United Kingdom have higher

announcement returns after the referendum.

Figure 2: Inbound Acquisitions CAR (-5, +5)

This figure shows all announcement returns of acquisitions prior and after the declaration of the result of the EU referendum on June 24 2016. These are the acquisitions done by a firm from one of the 28 member states into the United Kingdom, inbound acquisitions. On the left hand, in blue, are all the acquisitions prior to the

referendum. On the right hand side, in green, are all the acquisitions announced after the referendum. These dots show the Cumulative Abnormal Returns (CAR) for the event period (-5, +5). For both scatter plots, there is also a fitted line included. Red prior to the referendum, orange afterwards. The x-axis shows the announcement date for when the acquisition was announced. The y-axis shows the CAR (-5, +5). The vertical line is the the day of the declaration of the result, June 24 2016.

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Figure 3: Outbound Acquisitions CAR (-5,+5)

This figure shows all announcement returns of acquisitions prior and after the declaration of the result of the EU referendum on June 24 2016. These are the acquisitions done by a firm from the United Kingdom into a country from one of the 28 member states, outbound acquisitions. On the left hand, in blue, are all the acquisitions prior to the referendum. On the right hand side, in green, are all the acquisitions announced after the referendum. These dots show the Cumulative Abnormal Returns (CAR) for the event period (-5, +5). For both scatter plots, there is also a fitted line included. Red prior to the referendum, orange afterwards. The x-axis shows the announcement date for when the acquisition was announced. The y-axis shows the CAR(-5, +5). The vertical line is the the day of the declaration of the result, June 24 2016.

To further analyse what the impact is of the referendum on the announcement returns, t-tests for significance are done. Table 4 shows the outcomes of these tests. Averages, medians an t-values are given for both before as well as after June 24 2015. As implied by figure 2 and 3, the averages, for both the event windows (-5, +5) and (-10, +10), seem to show an increase in announcement returns after the referendum. For inbound acquisitions the average for CAR (-5, +5) increases from 0.195% to 1.456%. As for outbound acquisitions, the averages were negative prior to the referendum with a value of -0.792% for CAR (-5,+5) which is in line with figure 3. After the referendum the average and median for outbound acquisitions are 1.849% and 1.295% respectively. This implies that the market sees an acquisition by a UK acquirer into the European Union, and therefore increasing their share in the Single Market, as something positive.

The Brexit referendum can be used to illustrate the impact of a vote to leave the EU. Taken into broader perspective, if for example Italy would vote to leave the EU, their cross-border acquisitions are likely to have higher announcement returns after their vote. A firm increasing its share of the market which it is about to leave, is something that is perceived as positive by the market.

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Unfortunately, inbound and outbound CAR’s have a t-value of 1.52 and 1.56

respectively for the event window (-5, +5). With a critic value of 1.64, the CAR’s are almost significant at the 10% level. This implicates, again, a positive influence on the announcement of cross-border acquisitions. But, with the small sample available, 63 inbound acquisitions and 58 outbound acquisitions, they are not significant. Another explanation of the

insignificance could be the overvaluation theory by Roll (1986). This states that international companies are harder to value for the acquiring firm. Because of this, errors in valuating are likely to happen which leads to acquiring firms overestimating the target firm. This

consequently leads to lower announcement returns for the acquiring firm. Because of the insignificance nothing can be stated about the impact of the referendum on the announcement returns at the moment. Using this information, nothing can be concluded about the hypotheses 2a and 2b.

Domestic announced acquisitions do seem to be positively impacted at the 1% level for CAR (-5, +5) and 5% level for CAR (-10, +10). This would mean that there is a chance that the referendum has a positive influence on the announced acquisitions done in the United Kingdom. On the other hand, the Cumulative Abnormal Returns for the acquirers are also significantly positive for the acquisitions prior to the referendum. Potentially this outcome is also influenced by other factors or the referendum doesn’t have an influence on the domestic acquisitions.

Table 4: CAR statistics and significance

This table shows the Cumulative Abnormal Returns (CAR) from all acquisitions announced and completed after the declaration of the result from the referendum on 24 June 2016. These abnormal returns are resulting from the announcement of an acquisition, from now on announcement returns. These are the announcement returns of the acquirer. All CAR’s used in this thesis focus on announcement returns of acquirer. The returns are calculated for two different event windows namely CAR (-5, +5) and CAR (-10, +10). The daily abnormal returns are

calculated using the methodology of the market model with the estimation period as (-252, -30). As the

benchmark index I use the STOXX Europe 600. The CAR’s are given for either Inbound, Outbound or Domestic Acquirers. The t-value is the value resulting from the two-sided t-test. *, **, and *** denote statistical

significance at the 10%, 5%, and 1% level respectively.

Event Window Cumulative Abnormal Return

Before Referendum After Referendum

Mean (%) Median (%) t-value Mean (%) Median (%) t-value

Inbound Acquisitions (-5,+5) 0.195 -0.123 0.24 1.456 0.058 1.52 (-10,+10) -0.350 -0.526 -0.34 1.238 -0.622 0.81 Outbound Acquisitions (-5,+5) -0.792 0.008 -0.77 1.849 1.295 1.56 (-10,+10) -1.910 -0.658 -1.29 0.858 0.121 0.58 Domestic Acquisitions (-5,+5) 1.573 0.938 3.38*** 2.187 0.844 3.38*** (-10,+10) 1.476 0.787 2.40** 1.971 0.084 2.37**

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5.2.2 Multivariate Analysis

Table 5 shows the implications for acquiring firms that are also internationally oriented. As said in the method part, the focus will be on the domestic and outbound acquisitions. Again, outbound acquisitions are UK firms that acquire into the European Union. The expected impact of a possible leave of the Single Market is the highest for these firms. Firms from one of the 28 member states will remain in the Single Market and are assumed to be not affected by the Brexit. This table looks into the impact of three different measures of international diversification on announcement returns. ‘Foreign Sales’ is the amount of international diversification for a firm in the year the acquisition was announced. ‘Average Foreign Sales’ is the 5-year average for a firm in the year the acquisition was announced. Lastly, the ‘Change in Foreign Sales’ shows the percentage change from 2016-2017 in foreign sales. All three are continuous estimators.

Table 5 indicates that for outbound acquisitions, so where a firm from one of the EU member states is the target, the CAR is impacted by international diversification. For the CAR in which the event window is (-5, +5), ‘Average Foreign Sales’ and ‘Change Foreign Sales’ are significantly negative at the 1% and 5% level significantly. This is line with the findings of Moeller and Schlingemann (2005) who also find that an increase in international

diversification is negatively and significantly associated with acquirer returns. My

implications are that a 1% percentage increase in foreign sales leads to a loss of 12.7% in announcement returns. Opposite to the theory is the outcome for the variable ‘Foreign Sales’ which is positive at the 1% level. But, this estimator does not take into account the difference in foreign sales over multiple years. This could mean that there is difference in foreign sales after the acquisition or that the amount of foreign sales was an outlier. The exchange rate seems to be functioning as theorized. An increase in exchange rate would make the Pound more expensive and the Euro cheaper. Firms, from the UK, acquiring at a lower Euro price will have higher announcement returns.

In the domestic acquisitions the foreign sales measures do not seem to be of any influence on the CAR’s. This is likely to be correct because firms that are acquiring

domestically are less internationally diversified. Because of this reason, further analysis of the effect of international diversification after the Referendum will be focused on outbound acquirers. Inbound acquisitions are influenced by the variables as the theory predicts. For example, Markides & Ittner (1994) also find that related acquisitions are associated with higher benefits and lower integration costs than unrelated acquisitions. In this regression, the

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‘Same Industry’ variable is a dummy variable equalling 1 if the acquisitions are related. This variable is significantly positive at the 1% level.

Apart from the variable ‘Foreign Sales’, the other two estimators seem to be functioning as hypothesized by the theory. This would mean that acquirers which increase their international diversification by cross-border acquisitions, are negatively influenced if they are already international diversified. Increasing their share of foreign sales lowers the announcement returns. This is probably caused by the costs that arise because of the expansion. The results here show the impact of foreign sales over the entire period. So this would mean from June 2015 up until June 2017.

The CAR’s for the event window (-10, +10) have the same signs and impact as the variables in the event window (-5, +5). This indicates that the impact of the international diversification variables is the same for the two different event windows. Even though the impact seems the same, the significance for the foreign sales variables declines or even disappears for CAR (10, +10). But overall the results seem robust for the extended event window.

For outbound acquisitions the ‘After Referendum’ dummy has a t-value of 1.61. Just like table 4 it seems to be the case that after the referendum the announcement returns

increase. Again with this this t-value the coefficient is almost significant at the 10% level. So controlled for firms that are internationally diversified, there seems to be a positive influence on announcement returns after the referendum. Using this sample as an example for a leave from the EU, it would mean that cross-border acquisitions, after a vote to leave the EU, are perceived as something positive by the market. Staying part of the Single Market, by acquiring European subsidiaries, seems to positively influence firm performance.

The potential influence of the Brexit referendum on cross-border M&A : testing for firm performance and international diversification