1
Bachelor Thesis
The cross-border effect on target shareholders’
abnormal return of large and listed European
companies
Field: Finance
Supervisor: Shivesh Changoer
Date: 07-2014
Name: Nick van Toledo
Student number: 6079377
Abstract
This research studies the cross-border effect on shareholders’ abnormal return of large and listed European targets during the period 2009-2012. The global financial crisis could provide new evidence of a cross-border effect in M&A deals. This study focusses on target firms of listed European stock markets. The cumulative abnormal returns of domestic and cross-border acquisitions are calculated and these cumulative abnormal returns are put in a multiple linear regression model to estimate the cross-border effect. Due to the multiple linear regression, the abnormal returns are controlled for some variables to measure only the cross-border effect. The results show that shareholders from large and listed European target companies earn on average a higher abnormal return when there is a cross-border bid. These results are insignificant. The explanation for the cross-border effect can be that cross-border transactions are more valuable to bidders because of synergies and managerial factors.
2 Table of Contents
1. Introduction ... 3
2. Literature review ... 4
2.1 Characteristics of the M&A market ... 4
2.2 Possible factors for the existence of a cross-border effect on target shareholders’ abnormal return ………5
2.3 Factors that have influence on the targets’ abnormal return ... 7
2.4 Results from earlier studies ... 8
2.5 Summary ... 9
3. Data and Method ... 9
3.1 Data ... 9
3.2 Method ... 10
3.3 Descriptive statistics ... 13
4. Results ... 14
4.1 Cumulative abnormal return ... 15
4.2 Linear regression models ... 16
5. Conclusion ... 19
6. References ... 20
3 1. Introduction
There have been a lot of studies that have investigated mergers and acquisitions. Most of these studies focus on the short-term and long-term performance of the target companies and bidding companies. Most studies report positive wealth effects for target firm shareholders. The studies are searching for possible value drivers of this wealth effect to target firm shareholders. A small number of studies investigate the short-term wealth effect of cross-border mergers and
acquisitions to the target firm shareholders compared with domestic M&A’s. The short-term wealth effect of a cross-border merger and acquisition to a target firm shareholder could be systematically different than the short-term wealth effect of a domestic merger and acquisition.
The findings in the literature on the difference in short-term wealth effect to target firm shareholders are mixed and is mainly focused on companies from the United Kingdom and companies from the United States of America. Danbolt (2004) did research about target
companies in the UK and finds a cross-border effect of 0.84%, but this effect is not statistically significant. Studies focusing on the USA provide also some evidence for the existence of the cross-border wealth effect. Cheng and Chan (1995) finds a statistically significant higher
abnormal return in cross-border acquisitions. But they believe this difference in abnormal return is not due to overpayment but probably due to other value drivers. Also Harris and Ravenscraft (1991) find support for the cross-border effect. European evidence for a cross-border effect is limited. Goergen and Renneboog (2004) did a research about the wealth effects of European domestic and Cross-border takeover bids of large companies during the period 1993-2000. They conclude that there is an announcement effect, but this effect is not statistically significant.
The evidence of cross-border effects is limited and most studies conclude that the target company cross-border effect is driven by other factors. In this research some control variables are taken into account that are possible value drivers for the short-term wealth effect to the target firm shareholders. In this way we can determine the cross-border effect on target shareholders’ abnormal return.
Due to the economic downturn companies are seeking for cash and during this period new M&A deals are completed that can provide an answer to the following research question: What is the cross-border effect on target shareholders’ abnormal return of large and listed European companies?
4 In this paper is investigated what the short-term cross-border wealth effect of large
European mergers and acquisitions during the period 2009-2012. The paper gives new
information on this subject and provide evidence from 15 different European countries. When taken into account some control variables I find a positive influence of the cross-border effect on target shareholders’ abnormal return. However, this effect is not significant at the 5%
significance level.
The structure of the paper is as follows: in section 2 of this paper is discussed which information the literature provide on mergers and acquisitions and which factors are identified as possible factors for the existence of a cross-border effect on target shareholders’ abnormal return and some results of earlier studies. Section 3 describes the data set, some control variables and the used method to answer the research question. Some descriptive statistics about the data set are also given in section 3. In section 4, the results of the research are provided and analyzed. Paragraph 6 concludes our findings.
2. Literature review
This section describes the existing literature on M&A deals. First of all the M&A market is described. In addition, possible factors for the existence of a cross-border effect on target shareholders’ abnormal return are described. Thirdly, some variables are discussed that have influence on the target abnormal return as described by the literature. The section ends with results from earlier studies about the cross-border effect on short-term target abnormal returns.
2.1 Characteristics of the M&A market
Mergers and acquisitions (M&A’s) is the term used to refer to the integration of companies. It is called a merger when two companies combine to form a new company and when one company purchases another company it is called an acquisition. The term mergers and acquisitions also refer to joint ventures, licensing, spin-offs, restructuring activities and other corporate structure changes (Berk and Demarzo, 2007).
5 Berk and Demarzo (2007) describe that the M&A market can be subdivided in waves. Martynova and Renneboog (2008) also find evidence of these waves and describe five M&A waves during the following periods: 1980-1903, 1910-1929, 1950-1973, 1981-1989 and 1993-2001. Berk and Demarzo conclude that during economic expansion there is a high activity M&A market and during economic downturn there is low activity on the M&A market. In this research the period 2009-2012 is analysed. During this period there was an economic downturn because of the global financial crisis and according to Berk and Demarzo (2007) and Martynova and Renneboog (2008) this economic downturn lead to a low-activity M&A market and a lower success. But maybe it gives new insights on the cross-border effect on target shareholders’ wealth effect.
2.2 Possible factors for the existence of a cross-border effect on target shareholders’ abnormal return
Previous M&A literature has discovered that several factors could explain a difference in shareholders return between cross-border and domestic mergers and acquisitions. One of these factors is international risk diversification. Several studies shown that shareholders benefit from a well-diversified portfolio because of less-risk relative to return. In a well-diversified portfolio there will be less systematic risk than in a non-diversified portfolio (Davis, 1991). But this is the case for shareholders in international diversified portfolios. There is less agreement when looking if such benefits also count when there is corporate diversification (Danbolt, 2004). Markides and Ittner (1994) did a research about the shareholders benefits from corporate
international diversification. They investigated 276 U.S. international acquisitions and conclude that these acquisitions could create value for the acquiring firm under certain conditions. They say that due to information asymmetry “a multinational corporation is a valuable service to investors because it can diversify their portfolios indirectly” (Markides and Ittner, 1994 p. 346). So cross-border diversification via mergers can bring benefits to firms that might not be fully realized by their shareholders through international diversified portfolios. Therefore, corporate cross-border diversification might add value. But more recent studies show opposite results. Danbolt (2004) concludes that the support for the international risk diversification on corporate level is limited. So it is doubtful if international risk diversification lead to a higher abnormal return of the target in cross-border acquisitions relative to domestic acquisitions. To be sure, the
6 used sample has a restriction that the bidder is also a listed European Union company. In this case the international diversification effect is negligible.
Another factor that Danbolt (2004) mentioned is market access. Trade and investment barriers make it valuable for investors to acquire or merge with a cross-border company. Root (1987) did research on the effect of trade and investment barriers on M&A deals. Root concludes that cross-border acquisitions may be valuable to foreign bidders to get market access and thus are willing to pay higher premiums than domestic bidders. Danbolt (2004) concludes that there is no evidence of a positively relation between the level of target company returns and the trade and investment barriers. Hijzen (2005) concludes that these barriers have a negative effect on cross-border M&A’s. In this research only European Union companies are investigated where trade and investment barriers don’t exist.
Managerial factors can also explain a cross-border effect. A bidding company’s management has sometimes an incentive to acquire. By doing a M&A deal, the management increases her salary or power. Cross-border acquisitions may give more status to managers than domestic ones. Roll (1986) argues that companies overestimate the benefits of a merger.
Especially cross-border companies may be overestimating the value of a company. Bliss and Rosen (2001) did a research about bank mergers in the United States of America. They conclude that cross-border acquisitions are more likely to happen when managers want more status and power.
Finally a possible factor for the existence of a cross-border effect is synergies (Goergen and Renneboog, 2004). Synergies create value and can distinguished in two types: operating synergies and informational synergies. Operating synergies lead to economies of scope and economies of scale and therefore the firm can take a cost advantage relative to their competitors. Parts of the company can form together such as Research and Development, production division and marketing division to save costs and get an advantage to other companies (Harris and Ravenscraft, 1991). In the case of informational synergies the total value of the merged firms is higher than the value if the firms are not merged. Due to cultural differences and skill differences the value of the synergies may be different in cross-border mergers and acquisitions than in domestic mergers and acquisitions.
7 2.3 Factors that have influence on the targets’ abnormal return
In this research some control variables are included in the return model. These variables help to overcome possible differences in the bid characteristics and help to calculate the cross-border effect.
Studies by Gregory (1997) and Jensen and Ruback (1983) find tender offers and hostile acquisitions generate higher target returns than friendly mergers of acquisitions. Goergen and Renneboog (2004) also conclude that the returns for hostile bids are significantly higher than friendly mergers and acquisitions. They report an abnormal return of 13% on the announcement date for hostile bids and the bids of friendly mergers and acquisitions generate significantly lower abnormal returns.
Cash bids generate higher target returns than equity bids (Yook, 2000). An equity bid can be a signal to shareholders that the bidding company believes that their share prices are too high and therefore want to pay with equity. Another argument why cash bids generate higher
abnormal returns to target shareholders, is the influence of capital gains tax (CGT). Davidson and Cheng (1997) conclude that the tax effect has to be compensated to target shareholders in case of a cash bid and therefore target shareholders will demand a higher premium than in case of an equity bid. Goergen and Renneboog (2004) find strong evidence that the abnormal return to the target is significantly higher when there is a cash offer. The return of cash bids is 10% and the abnormal return of equity bids is 6.7% and cash-equity bids 5.6%. The event window does not matter, all cash bids generate higher abnormal returns at the 1% significance level.
Size is also a factor that influence the level of abnormal return to target shareholders. In case of acquisitions, the bidding companies are bigger companies and thus can afford to pay a higher premium to shareholders from smaller target firms than to shareholders from larger target firms (Danbolt, 2004). The abnormal return can partly be a function of the targets enterprise value.
8 2.4 Results from earlier studies
The M&A literature on target abnormal returns discovered significant abnormal returns prior and around the M&A announcement. Jensen and Ruback (1983) did a research about the abnormal return to shareholders of the target company and found evidence of a 30% abnormal return. Datta, Pinches and Narayanan (1992) found evidence of an abnormal return to target companies of 21.8% by using a meta-analysis. This means that several researches has been combined to get stronger and better results. All studies are unanimous in their conclusion: target company
shareholders receive a significantly high abnormal return.
The M&A literature is not that unanimous in their conclusion about the influence of the cross-border effect on the short-term abnormal return to target firm shareholders. The literature is largely limited to the United States of America and The United Kingdom.
Studies from the United States provide some evidence for the existence of the cross-border effect. Sinan Cebonoyan, George Papaioannnou and Nickolaos Travlos (1992) did a research about the wealth effects for target firm shareholders in the United States when there is a cross-border takeover. Similar to domestic acquisitions they found a large abnormal return for the target shareholders in cross-border acquisitions but not statistically higher. Cheng and Chan (1995) conclude in their research about target companies in the United States that there are statistically higher abnormal returns in cross-border acquisitions. Harris and Ravenscraft (1991) also find support for the cross-border effect. Dewenter (1995) does not find significantly higher abnormal returns in the USA market for cross-border acquisitions when including control variables.
Danbolt (2004) did a research about the difference in wealth-effect for UK targets of domestic M&A and border M&A. His research analyses the abnormal return in 116 cross-border and 515 domestic acquisitions during the period 1986-1991. Danbolt (2004) finds no statistical evidence of a difference in wealth-effect, but the abnormal return for UK targets of domestic M&A is some smaller than those of the cross-border M&A. The difference in return is 1.22% but this effect is not significant.
European evidence for a cross-border effect is limited. Marc Goergen and Luc Renneboog (2004) did a research about the wealth effects for European domestic and cross-border takeover bids. They investigated large acquisitions of at least 100 million in dollars in
9 deal value. They conclude that there is an announcement effect for domestic targets of 10.2% and for cross-border targets of 11.3%. But the difference in return is not significant.
2.5 Summary
This section described the M&A market, the possible factors for the existence of a cross-border effect on target shareholders’ abnormal return, the factors that have influence on the targets’ abnormal return and the results from earlier studies. Due to the global financial crisis there is low activity on the M&A market. This period can provide new insights on the cross-border effect in abnormal return to target shareholders. A cross-border effect may exist because of a difference in managerial factors or a difference in synergies. Most studies are confined to the United States of America or the United Kingdom. This research is focusing on the European market. The earlier studies have shown a cross-border effect, but most studies find insignificant results.
3. Data and Method
In this section the research design is provided. First the sample is described and the restrictions are described which are used. Second the method to calculate the cumulative abnormal returns and the method to answer the research question: What is the cross-border effect on shareholders’ abnormal return of large and listed European companies?
3.1 Data
This study is based on large European Union acquisitions which were undertaken by European Union companies listed on the stock exchange during the 2009-2012 period. By using Thomson Reuters One Banker I got the information needed. The program reports the name of the firms involved in the M&A deal, the type of the deal, the payment method, targets firm value and the deal value. We eliminate all transactions that does not met the following restrictions:
- Deal value has to be above 50 million dollar
10 - The acquiring corporation was listed on a stock exchange at least 365 days prior to the
announcement date and 2 trading days after the announcement date. - Announcement date has to be available
- Transaction has be completed during the period 2009-2012
This leads to a total of 206 transactions. By using Thomson Reuters Datastream we get the share prices of all companies involved in the merger or acquisition during the period. The method of payment, the type of the deal (hostile or friendly), the deal value and the enterprise value of the target are retrieved from Thomson Reuters One Banker. Because of a lack of share price or other missing accounting information the sample reduced to 156 acquisitions. These acquisitions are distributed over 15 European Union countries.
3.2 Method
In this paper is examined if the wealth effect for listed EU targets involved in cross-border acquisitions is significantly different than the wealth effect for listed EU targets involved in domestic acquisitions. I apply a standard event study methodology to estimate the difference in abnormal return by using daily data (Brown and Warner, 1985). To measure the short-term wealth effects for the target firms I have to calculate the cumulative abnormal returns. The event window starts 3 months before the announcement date. This is to avoid the effects of insider trading or rumors and to detect slow information processing. The literature does not provide a best start in event window to measure short-term wealth effects. To minimize the measurement error, a balance has to be found between the error caused by a too narrow event window and the error caused by insider trading. A too small event window may cause a substantial measurement error because of leakage of information just before the announcement date, but a too large event window may also cause a substantial measurement error.
The market model is used to calculate the expected returns. The market model will be running over a 9 month period ending 3 months prior to the event date. The event date is defined as the announcement date of the transaction according to the Thomson Reuters Datastream database. The most used index of the targets country is used as the relevant market index. In table 3 in the appendix is shown which index is used as market index depending on location of
11 the listed target. A standard OLS-regression in Microsoft Excel is used to estimate the alpha parameter and beta parameter for each firm.
The market model is calculated as: E(Rit)= α + β*Rmi
where
E(Rit) is defined as the expected return of the target company’s stock i at time t,
α is the intercept term,
β is the slope of the regression of the Firms i’s returns against returns on the corresponding market index at time t,
Rm is the return on the market index at time t.
The abnormal return is calculated as the difference between the actual return and the expected return in the event window:
ARit = Rit – E(Rit),
where
ARit is the abnormal return of the target company’s stock i for event day t,
Rit is the actual return of the target company’s stock i for event day t,
E(Rit) is the expected return of the target company’s stock i at the event date t.
Then the cumulative abnormal return of each firm will be calculated over the event periods [-1 ; 1] and [-1 ; 2]. This means that we use the period from one trading day before the announcement date to one or two trading day(s) after. The cumulative abnormal return is the short-term shareholders’ wealth effect in a particular time window.
CARit = ∑ARit
After the CAR is calculated for all the target companies of the sample, the CAR of each firm will regressed on the method of payment, the type of deal (Friendly or hostile acquisition), the size of the target and the cross-border effect. By using Stata, simple and multiple linear regressions will be executed. Simple linear regressions will test the influence of each variable on the cumulative
12 abnormal return. The multiple linear regression model regress all variables on the CAR and will test in what the influence is of each variable on the CAR. The following regression is tested:
CARit = α0 + β1* Cash + β2*Hostile + β3*log (Size) + β4*Cross-border + εt
where
CAR is the cumulative abnormal return for each firm, α0 is the intercept term,
β1 is the slope of the regression of the Firms i’s CAR against the method of payment,
Cash is the dummy variable for the method of payment,
β2 is the slope of the regression of the Firms i’s CAR against the type of deal (friendly/hostile),
Hostile is the dummy variable for the consideration,
β3 is the slope of the regression of the Firms i’s CAR against the size of the target,
Size is the variable for the size of the target,
β4 is the slope of the regression of the Firms i’s CAR against the cross-border effect,
Cross-border is the dummy variable for the cross-border effect (cross-border/domestic), εt is the error term of the regression.
In this section all the variables of the multiple linear regression model will be explained. The first variable in the regression is a dummy variable for the method of payment. When the dummy variable has a value of ‘1’ the β1 coefficient indicates the relationship between the CAR and if
the deal is paid in cash. The expected value of this coefficient will be positive because in the literature is described that the CAR has an higher value when the deal is paid in cash (Yook, 2000). The second variable is also a dummy variable. The dummy variable Hostile has a value of ‘1’ if the M&A deal was hostile and 0 otherwise. The β2 coefficient is expected to be positive
because hostile bids generates higher abnormal returns (Goergen and Renneboog, 2004). The third variable that is included in the multiple linear regression model is Size. Smaller target firms get larger returns than bigger target firms (Danbolt, 2004). Thus the β3 coefficient is expected to
be negative. The targets enterprise value at the announcement date is taken as size-variable. The log is taken from this variable because otherwise the values are too high and the relationship is close to exponential. And the last variable included in the regression is the most important one in this research. The Crossborder dummy variable has a value of ‘1’ if it was a cross-border
13 3.3 Descriptive statistics
The database Thomson One Banker is used to find M&A announcements during the period 2009-2012. When the above described restrictions are met and some announcements have been eliminated because of missing information, the sample consists 156 deals. In this section some descriptive statistics are described to understand the sample.
Table 1 shows the geographical distribution of the sample. The most M&A deals have taken place in the United Kingdom: 20.51% of the targets involved in a M&A deal have taken place in the United Kingdom. But as seen from the table, none of the 32 M&A deals are cross-border transactions. With 17.31% of the total M&A deals, France has the second rank. There are 31 out of 156 border transactions, thus 19.87% of the targets was involved in a cross-border transaction. Germany has the greatest share in cross-cross-border transactions (6 out of 31 cross-border transactions).
Table 1: The geographical distribution of the sample
Target nation
No. of transactions Percentage of transactions
Domestic
Cross-border Total Domestic
Cross-border Total United Kingdom 32 0 32 20.51 0.00 20.51 France 23 4 27 14.74 2.56 17.31 Spain 14 4 18 8.97 2.56 11.54 Sweden 10 2 12 6.41 1.28 7.69 Germany 9 6 15 5.77 3.85 9.62 Italy 7 3 10 4.49 1.92 6.41 The Netherlands 6 2 8 3.85 1.28 5.13 Finland 5 0 5 3.21 0.00 3.21 Belgium 3 0 3 1.92 0.00 1.92 Austria 3 1 4 1.92 0.64 2.56 Denmark 3 1 4 1.92 0.64 2.56 Portugal 0 2 2 0.00 1.28 1.28 Greece 5 3 8 3.21 1.92 5.13 Poland 5 2 7 3.21 1.28 4.49 Lithuania 0 1 1 0.00 0.64 0.64 Total 125 31 156 80.13 19.87 100.00
14 Table 2 illustrates the mean, standard deviation, median, 1st quartile, 3rd quartile, the minimum and the maximum of the cumulative abnormal return and some control variables which are used in the research. The table shows that the average cumulative return with a time window [-1;1] has a value of 13%. The means of the CAR’s are some higher than the medians. This is as a result of a few large CAR’s. This is confirmed by the high values of the maximum CAR. The payment method is a dummy variable and denotes 1 if it’s paid in cash. The mean of this variable is 0.43589. This value means that (43.59% of 156) 68 bids are cash bids. The dummy variable ‘Hostile’ has a mean of 0.00641. In the sample is just 1 deal that was a hostile bid. The average size of a company was 7742.05. But the median is much lower as a result of some relative very large target companies. This is also expressed by the value of the 3rd quartile (6275) which is lower than the average size of a target.
Table 2: Some statistical properties of the sample
4. Results
In this section the results are presented and analysed. Firstly the difference in short-term wealth effect is presented by means of the CAR. Secondly, the single and multiple linear regression models are presented. The method of payment effect, the consideration effect, the size effect and the cross-border effect on the CAR’s are discussed.
Mean St. dev. Median 1st
quartile 3rd quartile Minimum Maximum CAR[-1;1] 0.13055 0.28878 0.047285 -0.0012 0.167854 -0.3597 1.980776 CAR[-1;2] 0.14859 0.35272 0.058405 -0.00466 0.1799 -0.49079 2.631556 Payment method 0.43589 0.49747 0 0 1 0 1 Hostile 0.00641 0.08006 0 0 0 0 1 Size (in million USD) 7742.05 16656.2 1175.67 308 6,275 48.328 95474.99 Cross-border 0.19871 0.40032 0 0 0 0 1
15 4.1 Cumulative abnormal return
Table 4 shows the means of abnormal returns of domestic and cross-border transaction on the day before the announcement, the day of the announcement and the 2 days after the
announcement and the table also shows the means of cumulative abnormal return for the event windows [-1;1] and [-1;2]. As seen in the table, the target shareholders get on average an higher abnormal return on the announcement date for a cross-border transaction. The abnormal return in case of a domestic transaction is 8.14% and the abnormal return in case of a cross-border
transaction is 10.69%. The means of the abnormal return on the event day (announcement date) are in both cases significantly different than zero at the 1%-significance level. The average abnormal returns on the day after the announcement date are significantly different than zero at the 5%-significance level. But the average abnormal return for domestic transactions is 1.57% higher than the average abnormal return for cross-border transactions.
The cumulative abnormal returns for the event windows [-1;1] and [-1;2] are significantly different than zero at the 1%-significance level. In case of a cross-border transaction, the average cumulative abnormal returns for the event windows [-1;1] and [-1;2] have a value of 13.30% and 17.68%. In case of a domestic transaction, the average cumulative returns are respectively 12.99% and 14.16%. The differences are shown in the fourth column of the table.
Returns Domestic (t) Cross-border (t) Cross-border effect(t)
AR: -1 .0144365 (1.7997) .007736 (0.9986) -.0067005 AR: 0 .0814259 (5.6416)** .1069307 (3.1741)** 0.0255048 AR: 1 .0340749(2.2937)* .0183699 (2.2087)* -.015705 AR: 2 .0116678 (1.5121) .0437527 (1.1359) .0320849 CAR[-1;1] .1299373 (4.7042)** .1330366 (3.8677)** 0.0030993 CAR[-1;2] .1416051 (4.2686)** .1767893 (3.6382)** 0.0351842
Table 4: Means of abnormal returns and cumulative abnormal returns during the period 2009-2012 *Statistical significance at 95% level of significance using two tailed t-tests
16 4.2 Linear regression models
In this section the single and multiple linear regression models will be discussed. First the simple linear regression models are provided to see if the different variables have an influence on the estimated CAR’s for each target firm. Thereafter the multiple linear regression is provided to see if the cross-border effect has a significantly influence on the CAR when taken other variable in to account.
Table 5 shows the results obtained from the simple linear regression model with the dummy variable ‘Cash’. This is a dummy variable for the method of payment and denotes ‘1’ if the bid was a cash bid. The cumulative abnormal return for the different time windows are regressed on the dummy variable ‘Cash’ and a constant term. The coefficient for the dummy variable is .0230363, which indicates that cash bids create a higher cumulative abnormal return of 2.30% compared to equity bids. This value is not statistically significant at the 5%- level of significance. The coefficient for the dummy variable on the CAR with a time window of [-1;2] is also not statistically significant at the 5%-level. The positive values for the coefficient does provide limited support for the findings of Yook (2000). Cash bids generate higher target returns than stock swap acquisitions.
Table 5: Simple linear regression: Dependent variable CAR regressed on dummy variable ‘Cash’ and a constant. * Statistical significance at 99% level of significance using two tailed t-tests
Table 6 shows the results obtained from the simple linear regression model with the dummy variable ‘Hostile’. In the used sample only 1 bid out of 156 bids is a hostile bid. The coefficients are insignificant and are also negative. This does not support the findings of previous studies which find positive relationship between a hostile bid and the return to target
shareholders. But the result of the simple linear regression is based on 1 hostile bid and therefore unreliable.
CAR[-1;1] CAR[-1;2]
Coefficient t-value Coefficient t-value
Α .1205117 3.91* .1262361 3.36*
17
Table 6: Simple linear regression: Dependent variable CAR regressed on dummy variable ‘Hostile’ and a constant. * Statistical significance at 99% level of significance using two tailed t-tests
In table 7, the dependent variable CAR with time windows [-1;1] and [-1;2] are regressed on the logarithm of variable ‘Size’ and a constant. The coefficient of the variable is in both time windows negative. This indicates that a higher size of the target firm has a negative influence on the shareholders cumulative abnormal return. When a firm is 1% bigger, the cumulative
abnormal return in the time window [-1;1] will be 7.85% lower. The returns are significantly lower at the 1% significance level. This is in line with the findings of Danbolt (2004). He also finds a negative relationship between the Size and the target cumulative abnormal return.
Table 7: Simple linear regression: Dependent variable CAR regressed on the log of variable ‘Size’ and a constant. * Statistical significance at 99% level of significance using two tailed t-tests
Table 8 shows the cross-border effect on the abnormal return to target shareholders in a simple linear regression model. The positive coefficients indicates that the cumulative abnormal return will be higher if the target was involved in a cross-border transaction. But as seen from the table, the t-values have a low value and therefore the coefficients are insignificant.
CAR[-1;1] CAR[-1;2]
Coefficient t-value Coefficient t-value
Α .1309525 5.63* .1490653 5.25*
Hostile -.0622884 -0.21 -.0730672 -0.21
CAR[-1;1] CAR[-1;2]
Coefficient t-value Coefficient t-value
Α .3765251* 4.31* .4444116 4.16*
18
Table 8: Simple linear regression: Dependent variable CAR regressed on dummy variable ‘Cross-border’ and a constant.
* Statistical significance at 99% level of significance using two tailed t-tests
Finally, table 9 shows the multiple linear regression model. When controlling for the method of payment (Cash/equity), the type of the bid (hostile/other) and the size of the target, the cross-border effect has a positive influence on the cumulative abnormal return of target
shareholders. The coefficient of the cross-border effect in time window [-1;1] has a value of .0191422, which indicates a higher cumulative abnormal return to target shareholders of 1.91% when there is a cross-border bid. When the time window is [-1;2], the cross-border effect is 5.49%. But the cross-border effects are insignificant at the 5% significance level. This result is similar to the findings of Danbolt (2004) and Goergen and Renneboog (2004). They also found a positive coefficient for the cross-border effects when controlling for some other variables, but their findings are also insignificant. Only the size effect has a significant influence on the target shareholders’ CAR. The R-squared of these estimated models have a value of respectively 0.0560 and 0.0450. This value indicates that the CAR is only for a small part explained by these variables.
Table 9: Multiple linear regression model: Dependent variable CAR regressed on dummy variables ‘Cash’, ‘Hostile’ and ‘Cross-border, the logarithm of variable ‘Size’ and a constant.
* Statistical significance at 99% level of significance using two tailed t-tests
CAR[-1;1] CAR[-1;2]
Coefficient t-value Coefficient t-value
Α .1299373 5.01* .1416051 4.48*
Cross-border .0030993 0.05 .0351842 0.50
CAR[-1;1] CAR[-1;2]
Coefficient t-value Coefficient t-value
α .3654101 4.09 .4217718 3.88
Cash .0314558 0.68 .06113 1.09
Hostile -.0082173 -0.03 -.0219289 -0.06
Log(size) -.0805097 -2.94* -.0991009 -2.98*
19 5. Conclusion
In this research, the cross-border effect on target shareholders’ abnormal return is analysed during the period 2009-2012. The research focuses on large and listed European Union targets. Earlier studies on this cross-border effect are mainly confined to targets from the United Kingdom or United States of America. They found a positive cross-border effect on the abnormal returns to target shareholders, but most of the times this effect is insignificant. But there could be new evidence for the cross-border effect from the European stock market during the period 2009-2012. The central research question in this paper was: What is the cross-border effect on target shareholders’ abnormal return of large and listed European companies?
To answer the research question, an event study has been done. Using 156 M&A deals, the cumulative abnormal return to target shareholders is calculated for each target firm for 2 different time windows. These returns are regressed on some control variables and the border variable. The results obtained from the multiple linear regression show a positive cross-border effect on the return to target shareholders. Synergies or managerial factors can be the reason for this effect. However the cross-border effect is insignificant. These findings were the same as the findings of earlier studies. Only the size of a target has a significant influence on the CAR to shareholders.
Further research on this subject should be done with a larger sample. A significant cross-border effect might be found when a larger sample is used. The used data sample consists of only one hostile deal and consists of a large share of UK targets which all are involved in domestic transactions. This provide a skewed data sample and as result the findings are less reliable. When using a larger sample, the findings are more reliable than the findings in this research.
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22 7. Appendix
Table 3
Target’s location Market index used
United Kingdom FTSE100
France CAC40
Spain IBEX 35
Sweden OMXS30
Germany DAX30
Italy MIB
The Netherlands AEX
Finland OMXH25
Belgium BEL20
Austria ATX
Denmark OMXC20
Portugal PSI-20
Greece ASE general
Poland WIG20
Lithuania OMX RGI
