The Effect of the Brexit on cross-border M&A in the UK

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The Effect of the Brexit on cross-border M&A in the UK

Gerike van Deelen (s1014463) Master Thesis in Financial Economics

Radboud University

Nijmegen School of Management Master Thesis (MAN-MTHECFE) Nijmegen, August 2020

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Abstract

This study aims to research the influence of Brexit on the cross-border M&A activity in the UK. The existing literature of the determinants that affect cross-border M&A activity is used to make a connection with the Brexit announcement. The macro-economic variables that are influenced by Brexit and influence cross-border M&A activity are: stock market, exchange rate, GDP, interest rate and inflation. The data that is used for this study is monthly data from 2000 up to and including 2019. The three-step mediation analysis measure the relationships of the variables. The relationship between Brexit and the macro-economic variables is measured in the first step. In the second step the relationship is measured of Brexit on cross-border M&A activity. In the third step the relationship is measured of Brexit and the macro-economic variables on cross-border M&A activity. The results showed that Brexit leads to an increase in cross-border M&A, and that this effect is mediated by a higher value of the stock market.

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1. Introduction

The Brexit started with the referendum on 23 June 2016. Just over half of the United Kingdom (UK) voted to leave the European Union. For most countries, this outcome came as a surprise and had negative effects on their stock markets (Amewu, et al., 2016). Since then there has been great uncertainty while the referendum did not have direct consequences (Kierzenkowski et al., 2016). Until the real exit date 31 December 2020, the UK is a member of the EU single market, which means that the UK is part of the regulations and the trade agreements of the EU (Breinlich et al., 2017). The referendum has not had any economic consequences yet, but it has changed the economic expectations of the UK. Investors’ behaviour depends on the future economic expectations of these investors. Therefore, we find it interesting to check if and how cross-border M&A activity is influenced by the Brexit.

Research has shown that cross-border M&A activity is influenced by several macroeconomic variables (Di Giovanni, 2003; Erel et al., 2012; Uddin & Boateng, 2011; Vorachen, 2016). There are specific cases available of cross-border M&A in the United Stated (US) and in the UK. Vorachen (2016) mentioned that the majority of the cross-border M&A deals is between the US and the UK. All the data that is used was before the referendum date of the Brexit. That makes it interesting to research the period after the referendum announcement, because the Brexit had influence on the whole economy (OECD, 2016; Amewu, et al., 2016; Tabeshian, 2018).

The existing body of literature mainly focuses on national presidential or parliamentary elections, like a pre-scheduled political event as a cause of changes in foreign direct investment (Dadurkevicius & Jansonaite, 2017). Therefore, the Brexit makes a unique case in the existing body of literature. Brexit makes an even more interesting case because the outcome of the referendum was unexpected and lead to macroeconomic interesting research by looking into the aggregated consequences and the change in expectations of the future (Born, et al., 2017). Brexit goes beyond typical political elections, but cannot be seen as a onetime event because of the upcoming euro scepticism in the EU.

The purpose of this study is to explore to what extent the Brexit leads to an increase or decrease in cross-border M&A activity in the UK. The main objectives of the research include:

1. To determine the relationship between the Brexit and cross-border M&A activity in the UK.

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2. To determine the relationship between the Brexit and the stock market, exchange rate, GDP, interest rate and the inflation rate.

3. To determine the relationship between the stock market, exchange rate, GDP, interest rate, the inflation rate and cross-border M&A activity in the UK

The question that will be answered by determining the relationships is: ‘’How does the Brexit affect the cross-border M&A activity in the UK’’? The literature review forms the basis for the hypotheses, which is elaborated in chapter 2. In chapter 3 we will discuss the data and methodology that is being used to test the hypotheses. Chapter 4 gives an overview of the results and in addition the results will be discussed.

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2. Literature Review

In the literature overview, we distinguish between the effect of the Brexit on macroeconomic variables and the effect of macroeconomic variables on cross-border M&A. The variables that are used are in line with Boateng, et al. (2014). The variables that are used in previous literature are based on subjectivity. This is unavoidable. We based the selection of our variables on the fact that the variables not only affect cross-border M&A but are also affected by the announcement of the Brexit, or the Brexit consequences. The macroeconomic variables that we will use are stock market, exchange rate, GDP, interest rate and the inflation rate.

2.1 Effects of Brexit on stock market and effects of stock market on M&A

On 23 June 2016, the referendum of the Brexit was announced. Several studies researched the abnormal returns of the stock market as a consequence of the announcement. Amewu, et al. (2016) found that the US stock market showed a negative effect on the day of the announcement. Except for China and Japan every other stock market had a negative response on the event day and the day after. However, all markets also recovered after the Brexit announcement. Tabeshian (2018) found that the announcement of the Brexit referendum had a negative effect on the British and European stock markets. The cumulative abnormal returns showed that the overall effect of the Brexit is positive for the UK. This is in line with the research of Amewu, et al. (2016). Due to the depreciation of the Pound the stock markets could recover relatively fast. One of the conclusions from these papers is that the Brexit announcement came totally unexpected. The time after the announcement was really uncertain and political uncertainty can cause higher volatility in the stock market (Bittlingmayer, 1998). Li and Born (2006) concluded that stock markets are affected by uncertainty about the future president and the uncertainty during this election process. This is in line with Niederhoffer, at al. (1970), Peel and Pope (1983) and Gemmill (1992), who concluded that a shift in national policy and uncertainty by political events influence the valuation of the stock market. Changes that are made in the future have a significant influence on the stock price. This can also be seen in the case of the Brexit. We know the final exit date, which is 31 December 2020, but they are still negotiating about terms. This can also influence the investors to consider the market as uncertain and to fear about the Brexit consequences. Kierzenkowski et al. (2016) concluded that uncertainty about the economic policy influences bond yield and price volatility.

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Most of the papers distinguish between the acquired country and the target country. In this paper, we will look at the UK as an acquired country and as a target country. Di Giovanni (2005) researched the macroeconomic variables that affect the foreign direct investment. He concluded that multiple financial variables have an effect on M&A. The size of the financial markets does have a strong relationship on cross-border M&A for the acquired country. An increase in the stock market would lead to an increase in cross-border M&A activity (Di Giovanni, 2005). If investors have positive prospects of the future economy this will result in positive cross-border M&A (Wilson & Desire, 2013). They stated that if the domestic stock market improves financing, costs of investors will be lower and that will stimulate cross-border M&A for the acquired country. Shleifer & Vishny (2003) used overvaluation to explain the relationship between stock prices and M&A activities. When the stock market is at a higher level, share prices of companies might be overvalued. In order to protect the shareholders from decreasing share prices, the overvalued share prices will be used to acquire assets by acquisitions. This can be used in firms of foreign countries. Boateng, et al. (2014) stated that stock prices are positively correlated with cross-border M&A as the UK as acquire country. Firms with overvalued stock will minimize their valuation risk and, therefore, engage in acquisition.

Hypothesis 1: Brexit leads to an increase in cross-border M&A, mediated by higher value of the stock market.

2.2 Effects of Brexit on exchange rate and effects of exchange rate on M&A

Tabeshian (2018) examined the effects of the Brexit on the currency and the stock markets. He found that the announcement of the Brexit referendum had a negative effect on the pound sterling relative to the UD dollar and the EURO. On the other hand, he also finds a small negative effect of the EURO relative to the US dollar. However, he also stated that after the event the Brexit still had a negative effect on the Pound. The higher risk in the pound caused the exchange rate depreciation. Caporale et al. (2018) expect that the pound will depreciate further. On the other hand the UK was one of the few countries within the EU with their own currency. They always used their exchange rate for creating trade barriers to foreign counties (Georgiadis & Gräb 2016).

Valuation differences can be a reason for firms to have cross-border M&A activity. If markets in different countries are not fully integrated, the exchange rate and changes in the

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currency value can be a motivation for cross-border M&A (Erel et al., 2012). If the currency of the UK appreciates relative to the currency of other countries, the foreign country will be cheaper for the UK and this will encourage cross-border M&A. This is also confirmed by the research of Wilson & Desire (2013), who stated that an appreciation or a depreciation of the currency would have consequences for foreign investors, because the exchange rate determines the price of the transaction, the cost of managing, its financing and its profits (Weston & Jawien, 1999). On the other hand, if the currency of the UK depreciates, they will be more attractive to foreign countries to invest in. Than there will be an inflow of cross border M&A (Erel et al., 2012). This is also confirmed by Froot & Stein (1991), who said that in terms of depreciation foreign countries are wealthier and invest in countries with a depreciated currency. Another study shows that a country with an appreciating currency should be an acquired country and countries with a depreciating currency should be the target country (Dewenter, 1995; Goergen & Renneboog, 2004). When the Pound was stronger against the US dollar, UK firms acquired more firms in the US (Nisbet, et al., 2003).

Hypothesis 2: Brexit leads to more cross-border M&A in the target country, mediated by a decrease of the exchange rate.

Hypothesis 3: Brexit leads to less cross-border M&A in the acquired country, mediated by a decrease of the exchange rate.

2.3 Effects of Brexit on GDP and effects of GDP on M&A

During the past years the GDP of UK has increased with 2.25% due to the fact that the UK was part of the European Union. The positive effects of economic integration can get lost for the UK due to the Brexit (Pain and Young, 2004). The OECD has made several predictions relative to the Brexit. What would happen with the economy of Great-Britain when they leave the European Union? One of the predictions is a decrease in GDP of 3 % over 2020. This is relative to when the UK would still be in the EU (OECD, 2016). They expect a loss of foreign direct investment and, therefore, a loss in GDP on long term.

Vorachen (2016) found a positive relationship between GDP per capita and cross-border M&A activity. This positive relationship can be explained by different theories. One theory is if the domestic market saturates due to economic growth and high GDP investors invest in foreign countries (Neto & Brandao, 2010). A high GDP means a wealthy country. If a country

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is also more attractive to invest in. Countries with a high GDP that invest abroad will not only invest in wealthy countries but also invest in countries that are not wealthy because of the lower cost of capital (Erel et al., 2012). Another study shows that in a country with high GDP, firms have a higher reserve which they can invest in foreign countries and engage international expansion (Vasconcellos & Kish, 1996).

Hypothesis 4: Brexit leads to less cross-border M&A, mediated by a decrease in GDP.

2.4 Effects of Brexit on interest rates and effects of interest rates on M&A

Most of the times interest rates can be adjusted by the government or the country bank. In the UK, this is the Bank of England. When the economy is affected by a big event, in this case the Brexit, the Bank of England can raise or lower the interest rates to help the economy recover (Trading economics, 2020). At the time of the referendum the interest rates dropped for more than a year before they started to raise again. Stimulating the market by adjusting the interest rates when a big event occurs is very important for the consumers and investors in the country (Tsai & Chen, 2010).

The interest rate plays a role in cross-border M&A. The investors are influenced by the cost of capital of a domestic country. If there is a low interest rate this will stimulate investments and also cross-border M&A activity (Moeller & Schlingemann, 2005). Low interest rates may occur when there is enough money within the country, so investors invest abroad (Tolentino, 2010). Firms will undertake cross-border activities when the costs of investing are lower (Forssbaeck & Oxelheim, 2008). There is an expected relationship between cross-border M&A activity and interest rates because we expect, when there are low interest rates, domestic countries have capital abundance and will invest in foreign countries.

Hypothesis 5: Brexit leads to an increase in cross-border M&A, mediated by lower interest rates.

2.5 Effects of Brexit on inflation and effects of inflation on M&A

As mentioned in the part about the exchange rate, after the referendum the value of the pound depreciated, and still is not on their value they were before the referendum (Novy, 2019). This paper also expects that the depreciation of the pound results in higher inflation. Higher inflation rates have negative consequences for the activity of consumers and investors. The

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literature of exchange rates stated that in case of a sudden depreciation leads to an increase in inflation (Novy, 2019; Breinlich et al., 2017). After the referendum, the UK also experienced a larger import, that also indicates higher inflation in the domestic country.

Also, inflation can be an important variable for explaining cross-border M&A activity. In 1990, the low inflation rate was an important determinant for the growth of the cross-border M&A (Uddin & Boateng, 2011). Gugler et al. (2012) stated that return on investment and costs of capital are both affected by inflation and therefore, influence the acquisitions. When the inflation is high, the net return on the investment is lower. When the inflation in a foreign country is lower firms invest abroad.

Hypothesis 6: Brexit leads to less cross-border M&A, mediated by higher inflation.

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3. Data and Methodology

3.1 Dependent variables

In this paper, the dependent variable is the cross-border M&A activity in the UK. Two different indicators measure the cross-border M&A activity. The first indicator is the value of the cross-border M&A deals (Choi & Jeon, 2011) and the second indicator is the number of completed cross-border M&A deals (Uddin & Boateng, 2011). We do not only use the number of cross-border M&A deals but also the value of the cross-border M&A deals because they provide us with more information (Di Giovanni, 2005). The cross-border M&A activity will also be split in the inflow M&A activity in the UK and the outflow M&A activity in the UK. This split is necessary because we expect that the variables can have a positive influence on the M&A inflow but a negative effect on the M&A outflow through the Brexit (Erel et al., 2012). The Brexit referendum took place on 23 June 2016, so we will use data from 2016 till 2019 to correct for the Brexit. In order to research the cross-border M&A activity before the Brexit announcement we will use data from 2000. We will use monthly data, so that the effect of the Brexit is visible. The M&A data before the year 2000 is less than the period after 2000. Therefore, we started on the year 2000 (Choi & Jeon, 2011). The M&A deals are collected from the Zephyr database. To build the dataset we used the following criteria:

All listed acquired companies in the United Kingdom. All listed target companies in the United Kingdom. Acquired or target company all stock exchange.

The cross-border deals with United Kingdom as acquirer and as target country. All deals with a known value.

All deals on and after 01/01/2000 and up to and including 31/12/2019. All deals with deal type an acquisition or a merger.

3.2 Independent variables

The independent variable used for the research is the Brexit. The referendum of 23 June 2016 is the tipping point of the Brexit. Every data before 23 June 2016 is not affected by the Brexit and every data point after 23 June 2016 could be affected by the Brexit. In order to measure this, we add a dummy variable in the equation to find out whether the data can be

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affected by the Brexit or not (Hill, et al., 2018). When not affected by the Brexit the dummy adds a zero, when the data is affected by the Brexit the dummy adds a one.

3.3 Mediator variables

The mediator variables that are being used are stock market, exchange rate, GDP, inflation and interest rate. In line with Uddin & Boateng (2011), Choi & Jeon, (2011) these variables will be in the equation. For the mediator variables, the database of Eikon is used. Stock market is measured by the FTSE all-share market value. Exchange rate is the real exchange rate between United Kingdom and the United States (Tabeshian, 2018). The GDP is the real gross domestic product at basic prices monthly adjusted. The inflation is measured by consumer price index. The interest rate is measured by the interest rate on the three-month treasury bill of the United Kingdom.

3.4 Methodology

The data that is used for this research is time series data, all variables are measured at monthly time series (Choi & Jeon, 2011). This research focusses on the macroeconomic variables that affect M&A activity within the UK. We use time series and not panel data because we are only measuring the M&A activity in the UK, so we have one entity. We want to explain the dependent variable by the independent variable mediated by the mediator variables. Therefore, we will use the mediation analysis. We make use of the basic step method of Baron and Kenny (1986) (Zhao, et al., 2010).

Figure 1: direct effect of mediation analysis

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The first step is taking the regression analysis where the independent variable, X, predicts the mediator variables, M. This is the first path is path a, which is illustrated in figure 2, where the independent variable significantly accounts for the mediator variable (Zhao, et al., 2010). This will be tested by the following regression:

𝑀 = 𝑖1 + 𝑎𝑋 + 𝑒1

The independent variable must affect the mediator variable in this equation. In this research the relationship between the Brexit and the stock market, the exchange rate, GDP, the inflation and the interest rate is measured. The second step is making a regression analysis where the independent variable, X, predicts the dependent variable, Y. The second path, c is illustrated in figure 1, where the mediator variable significantly accounts for the dependent variable (Zhao, et al., 2010). Path c is called the direct effect between X and Y. This will be tested by the following equation:

𝑌 = 𝑖2 + 𝑐,_{𝑋 + 𝑒2}

The independent variable must affect the dependent variable in this equation. This measures the direct relationship between the Brexit and the cross-border M&A activity in the UK. The third step is regressing a multiple regression analysis where the independent variables and the mediation variables predicts the dependent variable. This is path c’ or path a*b and this is illustrated in figure 2 and is called the indirect effect. The previous significant relation between the dependent variable and independent variable is no longer significant. This will be tested by the following equation:

𝑌 = 𝑖3 + 𝑐𝑋 + 𝑏𝑀 + 𝑒3

The mediator variable must affect the dependent variable in this equation. In this research the relationship between the Brexit, the stock market, the exchange rate, GDP, the inflation and the interest rate and the cross-border M&A activity in the UK is measured. When there is only an indirect effect in the third step and no direct effect, the mediation is the strongest. When only an indirect effect exists, there is full mediation. When there is also a small direct effect there exists partly mediation (Baron and Kenny, 1986).

This research assumes a relationship between stock market, exchange rate, GDP, inflation and interest and the Brexit. This is the first step and will be tested in the following equations:

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𝐸𝑋𝐶𝐻𝐴𝑁𝐺𝐸₄ = 𝛽₇+ 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝑒₄ 𝐺𝐷𝑃4 = 𝛽7 + 𝛽8𝐷𝐵𝑅𝐸𝑋𝐼𝑇4+ 𝑒4

𝐼𝑁𝐹𝐿𝐴𝑇𝐼𝑂𝑁₄= 𝛽₇+ 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝑒₄ 𝐼𝑁𝑇𝐸𝑅𝐸𝑆𝑇₄ = 𝛽₇+ 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝑒₄

The second equitation is where the Brexit predicts the cross-border M&A activity in the UK: 𝐶𝐵𝑀&𝐴 𝑣𝑎𝑙𝑢𝑒4 = 𝛽7+ 𝛽8𝐷𝐵𝑅𝐸𝑋𝐼𝑇4+ 𝑒4 𝐶𝐵𝑀&𝐴 𝑛𝑢𝑚𝑏𝑒𝑟₄ = 𝛽₇+ 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝑒₄ 𝐶𝐵𝑀&𝐴 𝑖𝑛𝑓𝑙𝑜𝑤 𝑣𝑎𝑙𝑢𝑒₄ = 𝛽₇+ 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝑒₄ 𝐶𝐵𝑀&𝐴 𝑖𝑛𝑓𝑙𝑜𝑤 𝑛𝑢𝑚𝑏𝑒𝑟4 = 𝛽7+ 𝛽8𝐷𝐵𝑅𝐸𝑋𝐼𝑇4+ 𝑒4 𝐶𝐵𝑀&𝐴 𝑜𝑢𝑡𝑓𝑙𝑜𝑤 𝑣𝑎𝑙𝑢𝑒₄ = 𝛽₇+ 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝑒₄ 𝐶𝐵𝑀&𝐴 𝑜𝑢𝑡𝑓𝑙𝑜𝑤 𝑛𝑢𝑚𝑏𝑒𝑟₄ = 𝛽₇+ 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝑒₄

The third step of the mediation analysis is where the independent and the mediator variables predict the cross-border M&A activity. This is elaborated in the following equation:

𝐶𝐵𝑀&𝐴 𝑣𝑎𝑙𝑢𝑒4 = 𝛽₇ + 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝛽_P𝑆𝑇𝑂𝐶𝐾₄+ 𝛽_Q𝐸𝑋𝐶𝐻𝐴𝑁𝐺𝐸₄+ 𝛽_R𝐺𝐷𝑃₄ + 𝛽_S𝐼𝑁𝑇𝐸𝑅𝐸𝑆𝑇₄+ 𝛽_T𝐼𝑁𝐹𝐿𝐴𝑇𝐼𝑂𝑁₄+ 𝑒₄ 𝐶𝐵𝑀&𝐴 𝑛𝑢𝑚𝑏𝑒𝑟4 = 𝛽₇ + 𝛽₈𝐷𝐵𝑅𝐸𝑋𝐼𝑇₄+ 𝛽_P𝑆𝑇𝑂𝐶𝐾₄+ 𝛽_Q𝐸𝑋𝐶𝐻𝐴𝑁𝐺𝐸₄+ 𝛽_R𝐺𝐷𝑃₄ + 𝛽_S𝐼𝑁𝑇𝐸𝑅𝐸𝑆𝑇₄+ 𝛽_T𝐼𝑁𝐹𝐿𝐴𝑇𝐼𝑂𝑁₄+ 𝑒₄

Because we might experience differences in the inflow and outflow of M&A activity in the UK there will be also a separate relationship between inflow M&A activity and the outflow M&A activity in the UK.

𝐶𝐵𝑀&𝐴 𝐼𝑛𝑓𝑙𝑜𝑤 𝑣𝑎𝑙𝑢𝑒₄

= 𝛽7 + 𝛽8𝐷𝐵𝑅𝐸𝑋𝐼𝑇4+ 𝛽P𝑆𝑇𝑂𝐶𝐾4+ 𝛽Q𝐸𝑋𝐶𝐻𝐴𝑁𝐺𝐸4+ 𝛽R𝐺𝐷𝑃4

+ 𝛽_S𝐼𝑁𝑇𝐸𝑅𝐸𝑆𝑇₄+ 𝛽_T𝐼𝑁𝐹𝐿𝐴𝑇𝐼𝑂𝑁₄+ 𝑒₄ 𝐶𝐵𝑀&𝐴 𝐼𝑛𝑓𝑙𝑜𝑤 𝑛𝑢𝑚𝑏𝑒𝑟₄

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𝐶𝐵𝑀&𝐴 𝑜𝑢𝑡𝑓𝑙𝑜𝑤 𝑣𝑎𝑙𝑢𝑒₄ = 𝛽7 + 𝛽8𝐷𝐵𝑅𝐸𝑋𝐼𝑇4+ 𝛽P𝑆𝑇𝑂𝐶𝐾4+ 𝛽Q𝐸𝑋𝐶𝐻𝐴𝑁𝐺𝐸4+ 𝛽R𝐺𝐷𝑃4 + 𝛽_S𝐼𝑁𝑇𝐸𝑅𝐸𝑆𝑇₄+ 𝛽_T𝐼𝑁𝐹𝐿𝐴𝑇𝐼𝑂𝑁₄+ 𝑒₄ 𝐶𝐵𝑀&𝐴 𝑜𝑢𝑡𝑓𝑙𝑜𝑤 𝑛𝑢𝑚𝑏𝑒𝑟₄ = 𝛽7 + 𝛽8𝐷𝐵𝑅𝐸𝑋𝐼𝑇4+ 𝛽P𝑆𝑇𝑂𝐶𝐾4+ 𝛽Q𝐸𝑋𝐶𝐻𝐴𝑁𝐺𝐸4+ 𝛽R𝐺𝐷𝑃4 + 𝛽_S𝐼𝑁𝑇𝐸𝑅𝐸𝑆𝑇₄+ 𝛽_T𝐼𝑁𝐹𝐿𝐴𝑇𝐼𝑂𝑁₄+ 𝑒₄

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4. Results and Discussion

4.1 Augmented Dickey-Fuller test

When you have time-series data it is necessary to test for stationarity. A variable is stationary when the mean and variance of the variable is constant over time. The variable returns to a certain mean. A non-stationary variable is an exploding variable and can be unpredictable in a regression analysis. Non-stationary variables can lead to misleading results, because it shows a significant relationship that does not exist (Hill, et al. 2018). Also, the T-value by non-stationary data are not reliable. The Augmented Dickey-Fuller (ADF) test is used to check whether the data is stationary or not. The ADF-test rejects the null hypothesis when the test statistic is negative and below the critical value. Table 1 provides the test statistics of the ADF test.

Table 1

Unit root dickey fuller test

Variable Test statistic Rejection of H0

CBMA value -14.210*** Reject H0

CBMA number of deals -11.640*** Reject H0

CBMA inflow deal value -15.587*** Reject H0

CBMA inflow number of deals -15.648*** Reject H0

CBMA outflow deal value -14.471*** Reject H0

CBMA outflow number of deals -11.838*** Reject H0

Exchange rate -1.200 Failed to reject H0

d. Exchange rate -15.141*** Reject H0

Stock market -1.042 Failed to reject H0

d. Stock market -15.997*** Reject H0

GDP -20.141*** Reject H0

Interest rate -1.297 Failed to reject H0

d.interest -7.738*** Reject H0

Inflation -2.134 Failed to reject H0

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Note. Variable with d. is first difference. *Significant at 10% level. **Significant at 5% level. ***Significant at

1% level

Table 1 shows that the dependent variables of cross-border M&A activity are stationary. On the other hand, all mediator variables are non-stationary, except for GDP. GDP is already measured as monthly growth rates. The non-stationary variables are stationary with first differences. When co-integration between the variables exists, the non-stationary variables can be used in the regression. To test whether the variables are co-integrated, the augmented Dickey-Fuller test is used for testing the residuals of the equation (Hill, et al. 2018). When there is co-integration the residuals of the equation are stationary. In the first step of the mediation analysis this study performs five equations with unit roots so, five equations are tested for co-integration. In the third step this study performs six equations with unit roots so these six equations are also tested on co-integration.

Table 2

Co-integration test first step

Variable Test statistics

Stock market -2.144

Exchange rate -2.477

Interest rate -1.458

Inflation -2.756

Table two shows the test statistics of the residuals in the first step equation. None of the residuals of the equations are stationary so there is no co-integration between those variables. Therefore, an OLS regression with first difference is used for the first step in the mediation analysis.

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Table 3

Co-integration third step

Variables Test statistics

Cross border M&A value -15.145***

Cross border M&A number -14.205***

Cross border M&A inflow value -16.003***

Cross border M&A inflow number -16.803***

Cross border M&A outflow value -15.401***

Cross border M&A outflow number -14.251*** ***Significant at 1% level

Table 3 shows that residuals in the equation of the third step of the mediation analysis are stationary. So, the variables of these equations have unit roots and are co-integrated. These equations will be estimated in the original form (Studentmund, 2017).

4.2 Regression results

The first step in the mediation analysis is the regression of the independent variable on the mediator variable. Because the mediator variables are non-stationary the first differences are used in the regression analysis. The regressions are tested for serial correlation. When serial correlation exists, it means that the observations of the error term are correlated. This is tested by the Durbin-Watson test. The Durbin-Watson statistic is included in the tables of the regressions. A Durbin-Watson statistic around value two means that there is no autocorrelation. Is the value near 0, below a critical value of 1.69, near 4, or above a critical value of 2.31 (4-1.69) it indicates positive, or negative autocorrelation. Then, the Prais-Winsten method is used as treatment for autocorrelation. In elaboration of the first step in the mediation analysis can be found in table 4.

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Table 4

First step of the mediation analysis

Variables Stock market Exchange rate GDP Interest Inflation

Brexit 0.1049* 0.0594*** -0.1534 -0.1254 0.0983 Cons 0.0019 0.0004 0.1477*** -0.0181 0.0017 F value 2.51 12.38*** 0.07 0.95 0.12 Adj R-sqrt 0.0063 0.0456 -0.0039 -0.0002 -0.0037 T value 1.58 3.52 0.34 -1.08 0.35 Dw-stat 2.05 1.997 (2.54) 1.99 (0.78)1.99 1.69 rho -0.27 0.6014

*Significant at 10% level. **Significant at 5% level. ***Significant at 1% level

The first step of the mediation analysis wants Brexit to affect the mediator variables. When Brexit does not affect the mediator variable, then the mediator is just a variable that may have an effect on the dependent variable. But mediation analysis only exists when Brexit effects the mediator variables. Table 4 shows the effect of Brexit and the mediator macroeconomic variables. It shows a significant relationship between Brexit and stock market, and the exchange rate. The Durbin-Watson statistic of GDP and interest showed signs of autocorrelation and those equations are adjusted for autocorrelation with the Prais-Winsten method. Because the treatment of first differences the adjusted R squared, the T-value and the F-value became lower. For the second step of the mediation analysis there will be an estimation between the independent variable and the dependent variable. In the regression analysis Brexit will be the independent variable and all cross-border mergers and acquisitions will be the independent variable. The estimation of six regressions analysis is shown in Table 5.

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Table 5

Second step of the mediation analysis

Variables CBMA value CBMA number CBMA inflow value CBMA inflow number CBMA outflow value CBMA outflow number Brexit 2.3573*** 2.0080*** 0.0272 0.1732** 2.3301*** 1.8285*** Cons 2.1481*** 8.2158*** 0.1087* 0.1363*** 2.0394*** 8.0808*** T value 2.71 2.80 0.18 2.54 2.74 2.60 Adj R-sqrt 0.0259 0.0258 -0.0041 0.0223 0.0265 0.0216 F value 7.34*** 7.33*** 0.03 6.46** 7.52*** 6.29** N 240 240 240 240 240 240 Dw-stat 1.90 (1.54)2.02 2.03 2.08 1.94 (1.56) 2.01 Rho 0.23 0.22

*Significant at 10% level. **Significant at 5% level. ***Significant at 1% level

Table 5 shows that except for CBMA inflow value every regression is significant. The Durbin-Watson statistic of CBMA number and CBMA outflow number were too low, so they have been adjusted for autocorrelation. The new Durbin-Watson statistic is shown next to the old one. For mediation analysis, we want Brexit to affect the cross-border M&A activity, so this regression must be significant because otherwise there is nothing to mediate. That means that apart from CBMA inflow value this paper can make statements about mediation. There exists a direct effect from Brexit to cross-border M&A activity. So, path c is significant.

In the third step, the independent variable, Brexit and the mediator variables in the equation affects the dependent variable cross-border M&A activity. For a mediation effect Brexit should be insignificant or show a smaller effect, because the mediator variables should take over the effect on cross-border M&A activity.

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Table 6

Third step total CBMA

Variable CBMA value CBMA Number

Brexit -0.4105 (-0.26) 0.1944 (0.20) Stock market 2.7870** (2.09) 3.9853*** (4.85) Exchange rate 13.1492** (1.86) -7.9279 **(-1.82) GDP 0.4503 (0.64) 0.2961 (0.69) Interest rate 0.4893** (2.35) -0.2042 (-1.59) Inflation rate 0.2212 (0.67) 0.0646 (0.32) Cons -12.4158 **(-1.08) 6.8594* (1.87) Adjusted R-squared 0.0388 0.1731 F-value 2.61** 9.34*** Dw-stat 1.96 1.83 N 240 240

Note. In parentheses are the t-values. *Significant at 10% level. **Significant at 5% level. ***Significant at 1%

level

Table 6 summarizes the regression results of the total inflow and outflow of the cross-border M&A activity in the United Kingdom. The table makes a difference between the total deal value and the total number of the cross-border M&A activity. Table 6 shows that stock market, exchange rate and interest rate have a positive significant effect on the total value of the cross-border M&A activity. Stock market also has a positive significant effect on the total number cross-border M&A activity. Exchange rate shows a negative significant effect on the total number cross-border M&A activity.

Furthermore, the goodness of fit of the regression model is measured by adjusted R-squared and the F-value. The F-value is relatively low in comparison with the research of Uddin & Boateng (2011), but it is higher than its critical value so the test is statistically significant. In the paper of Uddin & Boateng (2011) only the number of deals is used while this paper also uses the total value of deals. The adjusted R-squared is relatively low relative to the studies of Nakamura (2004) and Pablo (2009). The low adjusted R-squared corresponds to regression models of Choi and Jeon (2011). A reason for a low adjusted R-squared might be that there are

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other variables explaining the variance of cross-border M&A activity. This could be not only variables at macro-economic level but also at firm level or industry level. In addition to that, there is more data before the Brexit announcement than after the Brexit announcement in the regression analysis. The data before the Brexit announcement is also affected by the economic crisis of 2008. This can cause a low goodness of fit for the regression models. The Durbin-Watson statistic shows that there is no evidence of autocorrelation.

Hypothesis 1 states that a positive exists relationship between stock market and cross-border M&A activity which is shown in table 6. This outcome is in line with the conclusions of Shleifer & Vishny (2003), Evenett (2004) and Uddin & Boateng (2011). The outcome of the positive significant relationship between stock market and cross-border M&A activity was expected from the theory, because an increase in the value of the stock market leads to an increase in cross-border M&A activity in the acquired country. Since there is more outflow of cross-border M&A activity than inflow, the total cross-border M&A activity should show a positive effect.

The outcome of exchange rate differs in the relationship with the total value of cross-border M&A and the total number of cross-cross-border M&A. In the relationship with exchange rate and the total value of cross-border M&A, it shows a positive significant effect. On the other hand, the relationship with exchange rate and the total number of cross-border M&A shows a negative significant effect. This negative relationship between exchange rate and the number of cross-border M&A activity is not in line with the research of Uddin & Boateng (2011). According to Froot & Stein (1991) a country with a depreciating currency is more attractive to invest in, which means that when the exchange rate goes down, there will be more inflow of cross-border M&A activity but less outflow of cross-border M&A activity (Nisbet, et al., 2003). Since there is more outflow of cross-border M&A activity than inflow, the exchange rate should show a positive effect that is shown in relationship with the total value of cross-border M&A activity. The difference in the positive and negative relationship may be due to the fact that there is less cross-border M&A activity, but the M&A has a bigger value.

GDP shows an insignificant positive relationship in table 6. Therefore, we cannot confirm hypothesis 4, which implies a positive relationship between GDP and cross-border M&A activity. Pablo (2009) and Boateng et al. (2014) however, found a positive significant relationship between GDP and cross-border M&A activity

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M&A activity. Hypothesis 5 states that a negative relationship exists between interest rate and cross-border M&A activity. When there is a low interest rate in a country, this will stimulate investments and there is more outflow of cross-border M&A activity (Moeller & Schlingemann, 2005; Tolentino, 2010). So, this is in contrast to the prediction of hypothesis 5, but in line with the findings of Uddin & Boateng (2011). The expectation was that when the interest rates goes down because of the Brexit, the cross-border M&A go up, because low interest rates causes more money in a country. However, a negative relationship with interest rates is found by Boateng, et al. (2014). One reason that a positive relationship exists between interest rates and cross-border M&A activity is that when interest rates are high, it will be cheaper for companies to invest in a country abroad with lower cost of capital.

Inflation shows an insignificant relationship in table 6. In contrast to this paper, Boateng et al. (2011) found a significant negative relationship between inflation and cross-border M&A activity.

Table 6 shows that there is no significant effect of Brexit anymore. When you expect an effect to be mediated the effect of Brexit should be smaller than table 5 or insignificant. This indicates that the effect of Brexit is mediated.

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Table 7

Third step inflow CBMA

Variable CBMA inflow value CBMA inflow Number

Brexit -0.2662 (-0.94) 0.0586 (0.47) Stock market -0.0179 (-0.08) 0.0946 (0.91) Exchange rate 2.8514** (2.26) -0.1920(-0.35) GDP 0.1073 (0.86) -0.0076 (-0.14) Interest rate 0.0642* (1.73) -0.0369** (-2.27) Inflation rate 0.0333 (0.56) -0.0245 (-0.95) Cons -1.8714 (-0.76) 0.2515 (0.54) Adjusted R-squared 0.0047 0.0434 F-value 1.19 2.81** Dw-stat 2.07 2.17 N 240 240

level

The results are split in inflow and outflow cross-border M&A activity because of the second and third hypothesis. Those hypotheses are about the exchange rate. Table 7 shows a significant effect by exchange rate and interest rate with the inflow value of cross-border M&A activity and between interest rate and the inflow number of cross-border M&A activity. The F-value of the inflow F-value is not significant, which means that the overall results are not significant. An explanation for this is the way the data is collected for the cross-border M&A results. In the years from 2000 till 2019, the UK was overall more an acquired country than a target country. So, there are much less cross-border M&A inflows than cross-border M&A outflows. However, the significant relationships are all positively related to the inflow of cross-border M&A. According to the literature of Dewenter (1995), Goergen & Renneboog (2004) and Froot & Stein (1991), when the currency depreciates, the exchange rate decreases and the inflow of cross-border M&A activity should be higher. So, this research expects a negative relationship between the exchange rate and the inflow of cross-border M&A activity.

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A negative significant relationship between the interest rate and the number of inflow cross-border M&A activity corresponds with the research of Uddin & Boateng (2011). This also confirms a part of hypotheses 5 and the theoretical approach that when the interest rate is lower, the net return on investments is higher which results in more cross-border M&A activity (Gugler et al, 2012). Low interest rates attract firms from abroad (Vasconcellos, G. M., & Kish, R. J., 1996; Forssbaeck & Oxelheim, 2008).

Table 8

Third step outflow CBMA

Variable CBMA outflow value CBMA outflow Number

Brexit -0.1444 (-0.09) 0.1358 (0.14) Stock market 2.8051** (2.15) 3.8907*** (4.74) Exchange rate 10.2978* (1.49) -7.7359* (-1.78) GDP 0.3429 (0.58) 0.3037 (0.71) Interest rate 0.4250** (2.08) -0.1673 (-1.30) Inflation rate 0.1879 (0.58) 0.0892 (-0.44) Cons -10.5444* (-1.80) 6.6078* (1.80) Adjusted R-squared 0.0345 0.1568 F-value 2.43** 8.41*** Dw-stat 1.99 1.83 N 240 240

level

Table 8 shows the regression results of the outflow of the cross-border M&A activity. Stock market, exchange rate and interest rate have a significant relationship with the value of the outflow. The number of cross-border outflow shows a significant effect with stock market and exchange rate.

The positive effect of stock market and cross-border M&A activity was expected from theory and confirms hypothesis 1. Boateng, et al. (2014) stated that a positive relationship exists

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between stock market and cross-border M&A outflow. This is also confirmed in the results of the paper.

For the outflow of cross-border M&A activity we expected a positive relationship with exchange rate (Wilson & Desire, 2013; Nisbet, et al., 2003). A negative effect was found in the relationship between the number of cross-border M&A outflow and the exchange rate. However, the value of the cross-border M&A outflow shows a positive relationship. This could mean that the number of M&A activities has increased because of a lower exchange rate, but the value of each merger or acquisition has become smaller. Another possibility is that a higher exchange rate decreased the number of M&A activities and the value of each merger or acquisition become larger. A positive relationship between exchange rate and cross-border M&A activity was also found by Uddin & Boateng (2011) and Boateng, et al (2011). Hypothesis 3 stated that when exchange rate goes down by Brexit the ouflow of M&A activity also must be lower. So, it indicates a positive relationship, which is shown in table 8 with the outflow value of cross-border M&A activity.

The interest rate in table 8 is positive, which means that at a higher interest rate the cross-border M&A will be higher or a lower interest rate causes lower cross-border M&A activity. This goes against the findings of Tolentino (2010) and against hypothesis 5 that is formulated from theory. An explanation can be that there would have been more outflow of cross-border M&A if the interest rate in the United Kingdom had been high. Since there is more outflow cross-border M&A activity than inflow cross-border M&A activity this is also the case in the total M&A activity.

The effect of Brexit is smaller than in table 5, the second step of the mediation analysis. The Durbin-Watson statistic shows that there is no evidence of autocorrelation.

4.3 Hypothesis testing

As discussed in chapter 3 there are three steps when using mediation analysis. These steps are necessary when judging the hypotheses. The first step in the mediation analysis is the regression between Brexit and the macro-economic variables. The second step in the mediation analysis is the regression between Brexit and cross-border M&A activity. Lastly, the third step in the mediation analysis is the regression between Brexit, the macro-economic variables and cross-border M&A activity.

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Hypothesis 1: Brexit leads to an increase in cross-border M&A, mediated by higher value of the stock market.

The first step of the mediation analysis, elaborated in table 4, shows that the regression between Brexit and stock market is significant. This means that Brexit can be mediated and the second step can be carried out. The second step of the mediation analysis, elaborated in table 5, shows that the regression between Brexit and cross-border M&A activity is significant. If the second step is also significant, the third step can be carried out. The third step of the mediation analysis, elaborated in table 6, shows an insignificant effect between Brexit and cross-border M&A activity and a significant effect between stock market and cross-border M&A activity. For Brexit to have an effect on cross-border M&A activity, mediated by stock market, the effect of Brexit must be lower than table 5 or insignificant. The effect of the mediator, stock marker, must be significant to be a mediator variable because the mediator must take over the effect on cross-border M&A activity. Based on the results we can assume that mediation exists. Hypothesis 1 indicates a positive effect of Brexit on stock market. This positive effect is confirmed by table 4. Hypothesis 1 also indicates a positive effect of stock market on cross-border M&A activity. This positive effect is shown in table 6. Based on the results we do not reject hypothesis 1.

Hypothesis 2: Brexit leads to more cross-border M&A in the target country, mediated by a decrease of the exchange rate.

The first step of the mediation analysis, elaborated in table 4, shows that the regression between Brexit and exchange rate is significant. This means that Brexit can be mediated and the second step can be carried out. The second step of the mediation analysis, elaborated in table 5, shows that the regression between Brexit and the inflow number of cross-border M&A activity is significant. Nevertheless, the effect of Brexit on the inflow value of cross-border M&A activity is insignificant. When there is no relationship between Brexit and cross-border M&A activity, there is nothing to be mediated. Because there is a significant relationship between Brexit and the inflow number of cross-border M&A activity we will continue to the third step. The third step of the mediation analysis, elaborated in table 7, shows an insignificant effect between Brexit and inflow number of cross-border M&A activity and an insignificant effect between exchange rate and inflow number of cross-border M&A activity. For Brexit to have an effect on cross-border M&A activity, mediated by stock market, the effect of Brexit must be lower than table 5 or insignificant. The effect of the mediator, exchange rate, must be significant. However, exchange rate is not significant. This means that the effect of Brexit on

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the inflow number of cross-border M&A activity is not mediated by the exchange rate. Hypotheses 2 indicates a negative effect of Brexit on exchange rate, while the results in table 4 show a positive effect. Hypothesis 2 also indicates a negative effect of exchange rate on inflow number of cross-border M&A activity. This effect is not significant. Based on the results we reject hypothesis 2.

Hypothesis 3: Brexit leads to less cross-border M&A in the acquired country, mediated by a decrease of the exchange rate.

The first step of the mediation analysis, elaborated in table 4, shows that the regression between Brexit and exchange rate is significant. This means that Brexit can be mediated and the second step can be carried out. The second step of the mediation analysis, elaborated in table 5, shows that the regression between Brexit and outflow of cross-border M&A activity is significant. If the second step is also significant, the third step can be carried out. The third step of the mediation analysis, elaborated in table 6, shows an insignificant effect between Brexit and the outflow of cross-border M&A activity and a significant effect between exchange and the outflow of cross-border M&A activity. For Brexit to have an effect on cross-border M&A activity, mediated by exchange rate, the effect of Brexit must be lower than table 5 or insignificant. The effect of the mediator, exchange rate, must be significant to be a mediator variable because the mediator must take over the effect on the outflow of cross-border M&A activity. Based on the results we can assume that mediation exists. Hypothesis 3 indicates a negative effect of Brexit on exchange rate, but table 4 shows a positive effect of Brexit on exchange rate. Hypothesis 3 indicates a positive effect of exchange rate on the outflow of border M&A activity. This positive effect is shown in table 6 with the outflow value of cross-border M&A activity. The effect of exchange rate on the outflow number of cross-cross-border M&A activity shows a negative effect. Based on the results we reject hypothesis 3.

Hypothesis 4: Brexit leads to less cross-border M&A, mediated by a decrease in GDP. The first step of the mediation analysis, elaborated in table 4, shows that the regression between Brexit and GDP is insignificant. This means that Brexit cannot be mediated by the macroeconomic variable GDP. Now GDP can be just a variable who has an effect on cross-border M&A activity. Therefore, we skip the second step and we proceed to the third step. The third step of the mediation analysis, elaborated in table 6, shows an insignificant effect between Brexit and border M&A activity and an insignificant effect between GDP and cross-border M&A activity. GDP cannot be seen as a mediator variable nor a variable that affects

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cross-border M&A activity. Based on the results we cannot assume that mediation exists, and we reject hypothesis 4.

Hypothesis 5: Brexit leads to an increase in cross-border M&A, mediated by lower interest rates.

The first step of the mediation analysis, elaborated in table 4, shows that the regression between Brexit and interest rate is insignificant. This means that Brexit cannot be mediated by the macroeconomic variable interest rate. Now interest rate can be just a variable who has an effect on cross-border M&A activity. Therefore, we skip the second step and we proceed to the third step. The third step of the mediation analysis, elaborated in table 6, shows an insignificant effect between Brexit and cross-border M&A activity but a significant effect between interest rate and the total value of cross-border M&A activity. Therefore, interest rate cannot be seen as a mediator variable. Although interest rate shows a significant effect on the total value of cross-border M&A activity, it is a variable that has an effect on the total value of cross-border M&A activity. Based on these results we reject hypothesis 5. In addition to this, hypothesis 5 expects a negative relationship between interest rates and cross-border M&A activity. And table 6 shows a positive relationship between interest rates and the total value of cross-border M&A activity.

Hypothesis 6: Brexit leads to less cross-border M&A, mediated by higher inflation The first step of the mediation analysis, elaborated in table 4, shows that the regression between Brexit and inflation is insignificant. This means that Brexit cannot be mediated by the macroeconomic variable inflation. Now inflation can be just a variable who has an effect on cross-border M&A activity. Therefore, we skip the second step and we proceed to the third step. The third step of the mediation analysis, elaborated in table 6, shows an insignificant effect between Brexit and cross-border M&A activity and an insignificant effect between inflation and cross-border M&A activity. Inflation cannot be seen as a mediator variable nor a variable that affects cross-border M&A activity. Based on the results we cannot assume that mediation exists, and we reject hypothesis 6.

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5. Conclusion

The purpose of this study is to examine the relationship between Brexit and cross-border M&A activity in the UK. This study uses monthly cross-border M&A data from January 2000 till December 2019. In order to answer the research question: “How does the Brexit affect the cross-border M&A activity in the UK”? This study determines the relationship between the Brexit and cross-border M&A activity in the UK, determines the relationship between the Brexit and the stock market, exchange rate, GDP, interest rate and the inflation rate and determines the relationship between the stock market, exchange rate, GDP, interest rate, the inflation rate and cross-border M&A activity in the UK. The macro-economic variables that are used in explaining cross-border M&A activity are used in previous studies. The cross-border M&A activity is measured by the value of the deals and the number of the deals. The cross-border M&A activity is also split in the inflow and the outflow cross-cross-border M&A activity. The method mediation analysis is used for measuring the relationship between Brexit and the mediator variables and between the mediator variables and the cross-border M&A activity.

The main finding, which is in line with the hypothesis is that Brexit leads to an increase in cross-border M&A, mediated by higher value of the stock market. In addition, this study finds a positive relationship between Brexit and the macro-economic variables, stock market and exchange rate. While a negative relationship between Brexit and exchange rate was expected (Tabeshian, 2018; Caporale et al., 2018). The direct effect from Brexit to cross-border M&A activity shows a significant effect. This is an important finding in order to perform the mediation analysis. Stock market has a positive significant effect on cross-border M&A activity. This corresponds to the theory of Di Giovanni (2005) and research of Shleifer & Vishny (2003) and Evenett (2004). Exchange rate has a positive significant effect on the value of cross-border M&A and a negative significant effect on the number of cross-border M&A. These findings are the same as the findings of the outflow cross-border M&A activity. The positive effect that is found is in line with the results of Uddin & Boateng (2011). And the negative effect is found in the literature of Erel et al. (2012) and Froot & Stein (1991). This study founds a positive significant effect from interest rate to the total value of cross-border M&A activity and to the outflow value of cross-border M&A activity. The positive relationship is in line with the findings of Uddin & Boateng (2011) but in contrast to the theory of Moeller & Schlingemann (2005) and Tolentino (2010), that expected a negative relationship. Interest rate shows a negative relationship with the inflow number of cross-border M&A activity, which

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is also found by Uddin & Boateng (2011) and corresponds to the literature (Vasconcellos, G. M., & Kish, R. J., 1996).

Previous literature examined the effect of the economic crisis of 2008 and the cross-border M&A activity (Reddy, et al., 2014) or mainly focused on national presidential or parliamentary elections, as a cause of changes in foreign direct investment. Many studies show the short term negative results for the stock market. The Brexit changed the economic expectations of the UK. Brexit is a new effect that is examined in combination with macro-economic factors and cross-border M&A activity.

Because of the Brexit announcement in 2016, there is only cross-border M&A data available of three years. This might be a limitation of the research. The actual Brexit effective date is 2021. This study measured only the period prior to the official Brexit date. The cross-border M&A data before 2016 is a lot more. Within a few years there would be access to a lot more information, than at this time. The influence of Brexit on cross-border M&A can be significantly larger in five years. Another limitation is that this study only used factors on macro-economic level and stock market level to investigate the influence of the Brexit on mergers & acquisitions, because the existing literature mainly focuses on these levels. There was not found any theoretical link between the Brexit and factors on firm level or industry level. Nevertheless, previous research shows that factors on firm level and industry level can influence cross-border M&A activity (Mitchell & Mulherin, 1996; Harford, 2005). Passing the factors on firm level and industry level means that the fit of the model is less appropriate. This is showed by a relatively low adjusted R2.

An additional suggestion for further research is investigating the long-tern influence of Brexit on cross-border M&A activity. The effect of Brexit on cross-border M&A activity, mediated by macro-economic variables can be significantly larger in a few years. This study measures a mediation effect by macro-economic variables, but research shows that firm level and industry level also can be important variables. A following study that investigates more determinants that can explain the mediated effect of Brexit and cross-border M&A activity can be interesting. Those determinants can focus more on micro-economic data and industry level and make a combination with the macro-economic data. Another suggestion for future research is investigating the effect of Brexit on the cross-border M&A activity in Europe. This study focusses only on the effects in the UK, but the Brexit also has major consequences for Europe. It would be interesting to compare the results of UK and Europe.

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7. Appendix

Appendix 1 Table 9

Summary statistics

Variable Mean Std. dev. Min Max

CBMA value 2.5606 5.1878 0.0044 42.8471 CBMA number 8.5667 3.4453 2 18 Inflow value 0.1135 0.9084 0 11.1824 Inflow number 0.1667 0.4056 0 2 Ouflow value 2.4472 5.0701 0.0018 42.8471 Outflow number 8.4 3.4091 1 18 Stock market 1.7718 0.3656 1.0138 2.4804 Exchange rate 0.6399 0.0828 0.4804 0.8290 GDP 0.1508 0.4764 -2.2 1.9 Interest rate 2.4025 2.1907 0.15 6.1 Inflation 2.0408 1.1139 -0.1 5.2

The Effect of the Brexit on cross-border M&A in the UK