Are Bidders’ Gains Affected by
Family Control of the Target Firm?
An Empirical Investigation
Master Thesis University of Groningen
Faculty of Economics & Business
MSc Finance
Name
:
Erik van Sinderen
Student number :
1546120
Supervisor
:
Dr. H. Gonenc
Are Bidders’ Gains Affected by
Family Control of the Target Firm?
An Empirical Investigation
Abstract
This paper analyses if bidder gains are affected when its target firm is controlled by a family or not. The sample consists of 203 acquisitions of private owned targets in the Netherlands, Belgium and Germany in the period between January 1996 and January 2009. I find evidence that bidder’s cumulative announcement returns (CARs) are lower when they acquire family owned targets compared to non family owned targets. I also find that there is no difference in bidder CARs between acquiring a family owned target or non family owned target during the merger wave which lasted until the end of 2000, and that the difference is stronger after this merger wave. Furthermore, I find weak evidence for positive interaction effects between acquiring family owned targets and financing the deal with share payments.
JEL classification : G34
Table of Contents 1. Introduction... 4 2. Theoretical Background... 7 2.1 Family ownership... 8 2.2 Method of payment... 9 2.3 Control variables ... 10 3. Methodology... 15
3.1 Choice of announcement and event window... 15
3.2 Formulas... 15
3.3 Units of measurement... 17
4. Data... 20
5. Results... 24
5.1 Mean and median comparison... 26
5.2 Multivariate regression ... 31
6. Conclusion... 35
References... 37
List of figures... 41
1 Introduction
Studies regarding acquisitions often have a focus on deals with public targets. For the bidder’s interest, lots of studies have indicated that a public target takeover in general does not generate a positive announcement return (Andrade et al 2001, Sundarsanam and Mahate, 2003). But recently, there are a growing number of studies investigating the acquisition of private targets. Differences in private benefits to the managers, liquidity, corporate control, information asymmetry and bargaining power call for the need for separate research. And with a good reason, since the announcement returns on the acquisition of private targets seem to be significantly more positive compared to public ones (Chang, 1998; Fuller et al, 2002; Draper and Pauyal, 2006; Faccio et al, 2006; Capron and Shen, 2007). For instance, Fuller et al (2002) show that, by conducting research on a sample of 3.135 deals in the US, the bidder’s shareholders gain when they acquire a privately held company, and lose when they take over a publicly held company. Faccio et al (2006) find the same, by performing a similar study for non-U.S. acquirers.
Most of the firms in the world are controlled by its founders, or by the founder’s families and heirs. Among privately held firms, such family ownership is nearly universal (Burkart et
al, 2003). Furthermore, there are almost five times as many acquisitions of private targets
and subsidiaries as there are acquisitions of public firms. Therefore I believe the interaction between target family ownership and private firm acquisitions deserves a closer look in the financial academic research environment.
There are a few studies about the effects of family ownership in mergers and acquisitions research. There is a study by Baugess and Stegemoller (2008), who find that family firms destroy value when they acquire, consistent with an agency cost explanation for acquisitions. Sraer and Thesmar (2007) find that when the family firm hires and outsider as CEO, they make profitable acquisitions.
has a focus on target firm family ownership. They find that the propensity of being taken over is influenced by family ownership. If there is an heir or a family which owns more than 20% of the stake, the propensity of being acquired is lower. Furthermore, when a founder runs the firm as a CEO, it seems that they have superior skills in concluding profitable acquisitions. Caprio et al (2010) concluded that concentrated ownership and family control is desirable in those firms in which the potential of wasting money in wrong acquisition decisions is larger than the benefit of a higher probability to be acquired.
This study takes a different approach by focussing on the family ownership of the target firm, and looks at the acquirer announcement returns to find differences. My sample consists of 203 privately owned firms which have been acquired between January 1996 and January 2009. The targets are based in the Netherlands, Belgium and Germany, while the acquirers are from all over Europe. I will analyse abnormal announcement returns of the bidder firm when it acquires a private firm, and thereby I will look at who is the ultimate owner of the privately owned target firm.
The main research question of this thesis is:
“Are there different reactions in short term acquirer announcement returns, between buying a family owned private firm and a non-family owned private firm?”
I further find weak evidence that bidders who bought a family owned firm, were better off if they financed their deal with shares. This is consistent with the theory that the family owner is easier to convince to sell its firm through a stock-swap. The family prefers this payment method since it can gain control in the merged firm.
Furthermore, I find no evidence for the effect during the European merger wave which lasted from 1993 to 2000. It appears that the difference in bidder CARs is only present outside merger waves. I believe that during the merger wave, the bidder CARs of all acquisitions are lower, causing the differences between acquiring a family and a non family target to disappear.
2 Theoretical background
As mentioned earlier in the introduction, it matters if the target is publicly listed or privately owned. There are several explanations why an acquisition of a privately owned firm generates on average a positive CAR.
For instance, a common reason is market liquidity (Conn et al, 2005). When a privately owned firm becomes a takeover target, potential buyers have less information about their target, compared to if it was a publicly owned firm. An acquirer benefits from the private nature of the transaction, thereby gathering information about the target which others might not have. Furthermore, when market liquidity is high, good deals are often undone since the chance of interference from a bidding competitor is higher. Also, the process of making private bids is less exposed to public gaze. Bidders have the option to end negotiations without the loss of face that may occur in a public bid. Therefore poor acquisition outcomes due to hubris are less likely in private bids.
Others revealed that payment method matters, since it reveals information about the bidder and the target. Chang (1998) argues that acquirers benefit when the owners of private targets become blockholders in the newly merged firm through stock payment acquisitions. Officer et al (2008) find that the acquirer’s use of stock eliminates the negative effects of information asymmetry and results in positive acquirer CARs.
I argue that in current academic literature about announcement returns, an important argument is missing. I suggest that (non) family ownership of the target firm is also important in explaining the higher CARs for bidders acquiring private firms.
2.1 Family ownership
A fast growing strand of literature, mostly in the finance area, examines the claim that firms with a large family blockholder may perform better (Anderson and Reeb, 2003; Miller et al, 2007). In essence, large shareholders are expected to reduce agency costs and to enhance firm performance (Berle and Means, 1932; Jensen and Meckling, 1976), since they have a large stake in the firm. This gives them the incentives and the resources to monitor managers, as Morck et al (1988) called the convergence-of-interest hypothesis.
When the largest shareholder is a family, there are strong reasons to think this will reduce the probability of the company being acquired (Caprio et al, 2010). Families exhibit a well-known attachment to control and the private benefits they enjoy from controlling the firm. The family is also determined to see its company survive in the future.
A large shareholder can block some inefficient deals that managers would promote in its absence, and this may cause the profitability of acquisitions for targets to be higher. On the other hand, managers can also block some efficient deals because, as Morck and Yeung (2003) argue, family firms are less likely to undertake optimal investment decisions or creative destructionism as to maintain the benefits of concentrated ownership.
These findings are inconsistent with arguments made Anderson and Reeb (2003) who find that the large amount of wealth that families invest in their firms is a sufficient incentive to maximise firm value. It furthermore restrains them from extracting private benefits which would hurt them in establishing long term relationships with the investment community, raising additional capital to grow the firm and it would increase the cost of capital.
2.2 Method of payment
Since method of payment reveals some information to investors in mergers and acquisition activities, this plays an important role. In public firm acquisition research, it is shown that acquirers who use non cash methods of payment underperform in public acquisitions (Conn
et al, 2005; Moeller, 2010). Moeller (2010) argues that stock payments signal that the
acquirer management believes that the acquirer is overvalued or that the acquirer does not have sufficient funds to pay for an acquisition with cash. If the acquirer finances its deal with stock, the market considers the stock of the acquirer as worth more than its market value. But this is not the case in private firm acquisitions, as many studies have shown. As for instance, Chevalier and Redor (2010) find that private firm acquisitions paid for with stocks results in higher returns as those paid for with cash. This result is confirming the results of previous research of Chang (1998), Fuller et al (2002), Conn et al (2005) and Faccio et al (2006). Chang suggests that acquirer abnormal returns in stock-swap acquisitions of private firms are significantly positive because the payment of acquirer stock to the owners of the private target can give them the option to become a new blockholder in the acquiring firm. Also, according to Fuller et al (2002) acquirers obtain a better price for private targets than for public targets especially when they buy the target with stock, they believe that this is due to differences in the characteristics of the markets for public and private firms. They argue that when the private firm is acquired with cash, the private firm has to deal with immediate tax implications. This is not the case when the firm is acquired with stock in exchange for their ownership. Officer et al (2009) show that acquirer returns are significantly higher in stock-swap acquisitions when the target is hard to value, especially when the target is a private firm. When acquiring a private firm, information asymmetry between the negotiating parties and market participants is more likely to be one sided.
firm. Therefore I expect that there is a positive interaction effect between the family firm variable and the share payment method.
A positive effect of a cash payment method on acquirer CARs can be explained through the signal that a cash payment gives to the investors. A cash payment can signal that the acquirer has no liquidity problems. But I expect that family owners of target firms do not favour cash payments, since they lose complete control of their company, and can not participate in the newly merged firm as owners. Furthermore, they lose the benefits of cash flow rights. This in term could have a negative effect on acquirer CARs. I expect that for family firms which are acquired with cash, the results could go either way.
2.3 Control Variables
Andrade et al (2001) and Bruner (2002) document that for proper acquirer return studies, one has to include transaction characteristics, such as method of payment, location, diversification and relative size of the target. Since several studies, including Schleifer and Vishny (2003), argue that the tendency of the market also has an impact on acquirer returns, I decided to also include if the acquisition was announced during a merger wave or not as one of the characteristics. Furthermore, a study by Servaes (1991) documents that there is a relationship between bidders’ CARs and the Tobin’s q of both target and bidder. Theories about these transaction characteristics are included to this study as control variables.
Countries
For this research I have opted to choose for acquisition subsamples of countries with legal systems of different origin. Therefore I have chosen to retrieve data from the Netherlands and Belgium, which have a French civil law system, and Germany, with a legal system of German civil law origin. These countries I have chosen also since other factors like cultural influence and economic state of development are similar.
are lower for transactions involving countries with French civil law systems (Moeller and Schlingemann 2005), so I expect that this could be reflected in different announcement returns between the subsample of Germany and the other two countries.
Cross Border
Bidder firms which are to participate in cross-border acquisitions could be looking for benefits in taking advantage of imperfections in international capital, factor and product markets. They can benefit by internalising the R&D capacity of foreign market targets and by expanding their businesses into new markets. As these synergies are not available in domestic acquisitions, one could expect the shareholder wealth to be higher in cross-border deals (Martynova and Renneboog, 2009).
Conn et al (2005) studied announcement returns of UK acquisitions of domestic, cross-border, public and private targets. They find that domestic public acquisitions on average generate significantly negative announcement returns, whilst cross-border public acquisitions generate zero announcement returns. They also find evidence that both cross border and domestic private firm acquisitions experience positive announcement and zero post-acquisition returns.
Moeller and Schlingemann (2005) study domestic and cross-border acquisitions by US acquirers. They find that US firms who engage a cross-border acquisition compared to those who acquire domestic targets experience significant lower announcement stock returns. They find that the bidder’s returns are negatively associated with an increase in global and industrial diversification. Bidder returns are positively related to takeover activity in the target country and to a legal system which offers better shareholder rights.
discounting the expected takeover gains, as evidence provided by Conn et al (2005) and Moeller and Schlingemann (2005) indicate.
Georgen and Renneboog (2004) analyze short-term wealth effects of large European takeover bids. They found higher acquirer wealth effects for UK target firms than for Continental European targets, in countries like Germany (positive), Belgium and the Netherlands (negative). According to them this is due to institutional differences, such as higher shareholder rights protection and takeover regulation with higher transparency. I expect that firms which acquire domestic targets have better announcement returns than firms which acquire a cross border target.
Same industry
In general, it is believed that diversifying acquisitions create operational and financial synergies. However, mergers and acquisitions between companies who operate in different industries are expected to have lower bidder shareholders returns (Maquiera et al, 1998; Doukas et al, 2002). The creation of diversified firms comes with a number of problems such as rent-seeking behaviour by divisional managers (Scharfstein and Stein, 2000), bargaining problems within the firm (Rajan et al, 2000) or bureaucratic rigidity (Shin and Stulz, 1998). Martynova and Renneboog (2009) argue that these disadvantages of diversification outweigh the synergies and result in wealth destruction for the bidder’s shareholders. Furthermore, buying a firm outside the core business of the acquirer comes with an increased risk of overvaluing the target’s assets. Bidders will therefore face a higher likelihood of adverse selection in inter-industry transactions compared to intra-industry transactions (Balakrishna and Koza, 1993). Shen and Reuer (2005) find that private targets are less likely to be acquired by a bidder who comes from outside their core business.
Relative size
The success of an acquisition is also determined by the relative size of the target. As larger firms generally require a more complex management structure to operate effectively, the post-acquisition integration of a relatively large target may be a difficult process. Investors may fear that their firm will bear these additional integration costs and adjust their estimate of the takeover synergies downwards.
When Fuller et al (2002) explore on the relative size of private targets, they find that for private firms there is a positive relationship with the acquirer’s positive abnormal returns instead. Because the bidder can profit from the lack of market liquidity, the bidder receives a discount on the acquisition of a private firm. The relationship between the bidder’s returns and the relative size of private firms is positive, since the bigger the target, the larger the absolute value of the perceived discount.
Moeller et al (2004) conducted a study on the size effect on acquirer announcement returns with a large sample of 12.023 acquisitions by public firms from 1980 to 2001. They show that regardless of payment method and the target being publicly or privately owned, small acquirers fare significantly better than large firms when they make an acquisition announcement. They conclude that large firms offer larger acquisition premiums than small firms and enter acquisitions with negative dollar synergy gains. This evidence is consistent with managerial hubris playing more of a role in the decisions of larger firms.
Since other papers, as for instance Faccio et al (2006) and Cooney et al (2009) report similar results, and argue that returns are higher when the target is larger and the bidder is smaller. Therefore I expect to find a positive relation between relative firm size and CARs.
Period
Bouwman et al (2009) examined stock performance of acquisitions initiated during booming (high-valuation) and depressed (low-valuation) markets. They find CARs to be significantly better for acquisitions announced in high-valuation markets compared to those announced during low valuation markets. In the two years following the acquisition, acquirers buying in high-valuation markets significantly underperform relative to acquirers buying during low-valuation markets. They argue that during the period of equity market booms, high valuations increase managerial discretion and forces executives to make poor acquisitions. I expect that during waves CARs are higher due to overconfidence in the market.
Tobin’s q
Lang et al (1989) and Servaes (1991) document that CARs of bidders are affected by the Tobin’s q ratio of the targets and bidders. Bidders with high q ratios have significant positive abnormal returns when they engage in an acquisition, whereas bidders with low q ratios have significant negative abnormal returns. If Tobin’s q is interpreted as an indicator for management performance, these findings imply that better performing firms make better acquisitions and that more value can be created from taking over poorly performing companies. Authors of both papers concluded, and therefore I expect, that the returns of the bidder are highest when the bidders’ q ratio is high and the targets’ q ratio is low.
Table 1: Takeover characteristics and their expected effects on bidder CARs Deal characteristic Previous research Expected effect
Cash payment + +
Stock payment + +
Family ownership n.a. -
Family x Cash n.a. +/-
Family x Stock n.a. +
Countries + +
Cross border deal - -
Same industry + +
Relative size + +
Period (merger wave) + +
3 Methodology
To test the hypotheses daily prices are used, which are adjusted for stock splits and dividends to prevent the results from getting blurred. Since the data is from 1996 and onwards, prices are, if needed, converted to Euros.
3.1 Choice of announcement and event window
It has to be noted that measuring stock returns yields some limitations. For instance, in Grinblatt and Titman (2002, page 708) it is written that the stock return at the time of the bid, cannot be completely attributed to the expected effect of the acquisition on profitability. They argue that the stock returns of the bidder at the announcement date are a reflection of how the market is evaluating the bidder’s business. According to Hietala et al (2000), the announcement of a takeover reveals information about potential synergies in the combination, the stand-alone values of the bidder(s) and target(s), and the eventual overpayment by the bidder. They state that it is very hard to isolate these effects, making it difficult to know why the market reaction occurs after a takeover announcement.
Therefore, to isolate these effects, I intend to use a short event window of the stock returns of 1 day prior, the announcement day itself and 1 day after the announcement (MacKinlay, 1997). I chose 1 day prior, since the market may acquire information about the earnings prior to the actual announcement. Furthermore, I added the day after the announcement, since this captures the price effects of announcements which occur after the stock market closes on the announcement day.
3.2 Formulas
In order to calculate abnormal returns, I will apply two methods as MacKinlay (1997) and Brown and Warner (1985) described. The first method is that of the market adjusted
where Ri,t denotes the return of stock i at time t . Furthermore, Rm,t stands for the return on the local market index. These indexes are chosen above indexes such as the MSCI since they are closer to the acquirer, and daily MSCI returns are not available before 2002. The second method is the OLS market model, which calculates the market and risk adjusted abnormal returns.
Where
α
ˆ
iandβ
ˆ
i stand for the regression parameters estimated over the 250 days prior to the event (-255, -5). This method is useful to capture the correlation between the share price and market swings. A choice will be made between the market adjusted abnormal returns method and the OLS market model. It will become the model which is the closest to being normally distributed. Since daily announcement returns tend to be non-normally distributed, the Jarque-Bera test is added to detect normality. The significance of the abnormal returns is tested with the Wilcoxon signed rank test. Brown and Warner (1985) argue that even when abnormal returns do not follow a normal distribution, parametric tests are sufficient.Then I will breach the sample down into seven different groups, each group with a specific type of owner. I will investigate if there are differences between groups by an one-way ANOVA test and I will evaluate each groups’ CAR by testing if it is negative, zero or positive. Next, a comparison of means and medians will be established. There will be a comparison of means for family and non family firms in general. For each two means the student’s t-test will be added in order to check if there is a significant difference. The same will be done for the medians, by implementing the Wilcoxon Signed Rank test. This sequence will be repeated for differences between payment methods, countries, cross border acquisitions, periods and industry relatedness.
i j i j i i X CAR =α0 +
∑
(β, ⋅ , )+εWhere Xi,j stands for the takeover characteristics as stated in table 1. The student’s t-test is used to illustrate the significance of the coefficients of the variables.
3.3 Units of measurement
The multivariate model is estimated with variables as described in the theoretical section of this paper. The unit of measurement of each company or deal characteristic is described in the remainder of this section.
Family ownership
In order to determine if a target firm is family owned or not, I will add a dummy variable which has a value of one if the target firm is under family control before the acquisition. Payment method
A deal is defined as a cash payment deal when a deal has a cash component, but not a share component. A deal is defined as a share payment when it has a stock-component, but not a cash component. There is a dummy variable when the deal is made with cash, as well as a dummy variable when the deal is made with shares. This means that for all other types of payment method, both dummy variables need to have the value of zero.
Countries
Each country has its own dummy variable. For instance, for all acquisitions of targets located in Germany, there is a dummy which has the value 1 if the target is from Germany, and 0 if the target is from the Netherlands or Belgium. Likewise there is also a dummy for the Netherlands and Belgium.
Cross border deal
Period
In order to measure the announcements of acquisitions during the last part of a merger wave, I will use a dummy variable for all the announcements that have been made between 01/01/1996 to 31/12/2000, since Georgen and Renneboog (2004) define the years 1993-2000 as the fifth European merger wave. During the fifth wave, a sustained economic boom occurred, new European stock exchanges were developed and the internet- and telecommunication industries were rapidly growing. In 2001, the collapse of consumer confidence in these industries as well as the overcapacity in the traditional sectors caused an abrupt reduction in merger activity.
Same industry
There is also a dummy variable which is influenced by the fact that the target firm is active in the same industry or not. The bidder and its target are matched by their SIC code.
Relative Size
Since the targets market value of equity was unavailable for a large portion of the sample, the relative size of the target is based on Travlos’ (1987) calculation. It is measured as the logarithm of the value of a transaction divided by the market value of equity of the acquiring firm. The transaction value is corrected, if less than 100% of the target’s equity is acquired. Tobin’s q
My computation of Tobin’s q is based on Chung and Pruitt (1994) their approximation, which is conservative with respect to both data requirements and computational effort. It is defined as follows: TA DEBT PS MVE q= + +
Table 2: Takeover characteristics and their units of measurement
Deal or company characteristic Unit of measurement Description
Family ownership Dummy variable
This dummy has a value 1 if the target firm is owned by a family and 0 otherwise
Cash payment Dummy variable
This dummy has a value 1 if a cash only payment has been made and 0 otherwise
Cross border deal Dummy variable
This dummy has a value 1 if the deal is between two companies from two different countries
Countries Dummy variables
For each country there is a specific dummy variable added which has the value 1 for that specific country and 0 otherwise
Period Dummy variable
This dummy has a value 1 if the deal is announced between 01/01/1996 and 31/12/2000 and 0 otherwise
Same industry Dummy variable
Dummy variable which is 1 if the acquirer is active in the same industry as the target, by SIC code and 0 otherwise
Stock payment Dummy variable
Dummy variable which is 1 if the deal contains a stock only payment and 0 otherwise
Relative Size Ratio
The natural log of the value of the transaction divided by the market value of equity of the acquiring firm.
Tobin’s q Ratio
4 Data
I used the Orbis of Bureau van Dijk Publishing database to trace 203 privately owned target firms which have been taken over between 1996 and 2008 in the Netherlands, Belgium and Germany. Within this sample, 90 target firms were under family control and 113 were not. Next, I used the Orbis database of Bureau van Dijk Publishing to identify the acquirers of these firms and Thomson Datastream for their corresponding stock returns. The acquirers are located within the European Union.
For the purpose of this study, I define family businesses as companies in which the (founding) family still has a stake of 20% or more. If the founding family holds a minority stake, the influence of the family could be so small, that the firm loses the characteristics which are typical for family owned firms. Even more, it is typical in academic research that a family firm is defined as a family firm when the family owners together have a large stake (La Porta et al, 1999; Claessens et al, 2000; Isakov and Weisskopf, 2010).
Table 3: Sample selection criteria
Selection criteria Specification
Time period 01/01/1996 to 31/12/2008
Target location The Netherlands, Belgium and Germany
Acquirer location Europe
Deal status Completed
Type of companies Unlisted and delisted targets Old percentage of stake < 50%
New percentage of stake > 50%
Deal type Mergers and acquisitions
To make sure that a change of control is established, and that a significant part of the target is sold in the deal, I excluded deals where the bidders buy less than 50% of the targets equity. Furthermore, I do not include deals where the bidders have 50% or more of the targets equity before the acquisition or deals where the bidder has got less than 50% of the targets equity after the acquisition.
shareholders wealth. My study has its focus on family ownership of the target firm. In order to determine whether one is family held or not, I used the Orbis database of Bureau van Dijk
Publishing to locate each target firms Global Ultimate owner. In some cases, when Orbis did
not provide ownership data, I contacted the firm itself in order to retrieve it.
I shall distinguish between firms which are owned by either a single (family) owner, multiple family owners, a family with a minority stake, a family with a majority stake, other firms (subsidiaries), divisions of other firms or if they had a widely dispersed ownership. Table 4 presents the results of the ownership distribution of the target firms.
Table 4: Ownership data
Single Family Owner stands for all target family firms in which a single family member owns the firm for 100%. Multiple Family Owners represents all target family firms in which 100% of the firm is owned by multiple family members, for instance father and son, brothers and sisters, spouses etc. Family Owns Majority Stake represents all target family held firms in which the family had over 50% of the stake in the firm. Family Owns Minority Stake represents all target family held firms in which the family held a stake in the firm between 20% and 50%.
Netherlands Belgium Germany Total %
Family owned 23 5 62 90 44,33
Single Family Owner 5 1 15 21 10,34
Multiple Family Owners 14 3 39 56 27,59
Family Owns Majority Stake 3 1 3 7 3,45
Family Owns Minority Stake 1 0 5 6 2,96
Non family owned 44 11 58 113 55,67
Subsidiary 26 3 40 69 33,99
Division 5 1 9 15 7,39
More than 1 owner 13 7 9 29 14,29
Total sample 67 16 120 203 100
Table 5: Descriptive statistics of the acquirers
The first five statistics are displayed in millions of Euros (€). Leverage stands for the acquirers accounting leverage, and is calculated as total liabilities divided by total assets plus total liabilities. Debt to equity is the total liabilities divided by total equity. Relative size is calculated as the deal value divided by the total marketvalue of equity of the acquiring firm.
Mean Median Std. Dev Minimum Maximum
Marketvalue of Equity (mln) 8.603,55 1.062,61 32.273,11 4,76 355.419,59 Total Liabilities (mln) 4.152,59 733,53 11.461,37 0,40 91.860,00 Common Stock (mln) 3.490,89 384,77 17.957,11 0,11 234.175,27 Preferred Stock (mln) 9,13 0,00 49,27 0,00 597,00 Deal value (mln) 1.333,42 35,00 14.385,48 3,60 204.730,00 Leverage 0,38 0,38 0,19 0,00 0,95 Debt to equity 0,94 0,61 1,82 0,00 17,99 Relative size 0,19 0,05 0,47 0,01 4,26
Table 5 shows the descriptive statistics of the acquirers. The mean market value of equity is €8.6 billion, the median is €1.0 billion. The low median indicates that there are some heavy outliers, as for instance British Petroleum with €195 billion and Vodafone Airtouch with €355 billion. Similar is the case for the averages of total liabilities, common stock, preferred stock, deal value, debt to equity and relative size. Here, also high outliers are responsible for the low median and relatively high standard deviation compared to the mean. The fifth column also illustrates this by showing high maximum values. The relative size statistic shows that on average (median) the target was approximately 5 (20) times smaller then its acquirer.
Table 6: Descriptive statistics of the cumulative abnormal returns With significance levels of 1%,5% and 10% denoted as ***,** and * respectively
Market adjusted OLS Market model
Mean 1,228% 1,219% Median 0,821% 0,709% Standard deviation 0,040 0,039 Skewness 0,275 0,385 Kurtosis 3,058 3,171 Jarque-Bera test 2,592 5,270*
5 Results
Table 7 shows descriptive statistics divided by the presented types of ownership. It can be seen that only two out of seven groups have significant positive returns. These are in line with well known studies as for instance Chang (1998) and Capron and Shen (2007), who expect positive acquirer CARs for bidders acquiring privately owned firms. However, I argue that the groups which contain non family owned divisions, as well as family targets which own a minority and majority stake are too small for each one-sample T-test to detect return significant from zero. Therefore I can not say that bidder CARs for acquiring those targets is different from zero. For acquiring fully family owned firms, returns are not statistically different from zero. This is in line my expectations, namely that the acquisition of family owned firms gives bidders lower CARs compared to bidders acquiring non family owned targets. Further, returns of acquisitions of firms owned by a single owner appear to be less volatile than the other groups. This is reflected by a lower standard deviation.
It appears that for acquisitions of targets which are completely owned by a family, the bidder CARs are lowest, and when the family ownership stake decreases, the bidder CARs increase. This suggests a negative relation between the percentage of family ownership and bidder CARs.
Table 7: Mean and median comparison per type of ownership
Single Family Owner stands for all target family firms in which a single family member owns the firm for 100%. Multiple Family Owners represents all target family firms in which 100% of the firm is owned by multiple family members, for instance father and son, brothers and sisters, spouses etc. Family Owns Majority Stake represents all target family held firms in which the family had over 50% of the stake in the firm. Family Owns Minority Stake represents all target family held firms in which the family held a stake in the firm between 20% and 50%. Subsidiary, Division and More than 1 owner stand for non family held targets. The T-statistic stands for the one-sample t-test to check if the mean CAR is different from zero. With significance levels of 1%, 5% and 10% denoted as *, ** and *** respectively.
Target ownership status Total Mean T-statistic Std. Dev Median Lowest Highest
Single Family Owner 21 0,29% 0,512 2,59% -0,20% -4,06% 5,96%
Multiple Family Owners 56 0,51% 0,958 3,95% 0,09% -7,47% 11,39%
Family Owns Majority Stake 6 2,35% 1,785 3,22% 2,30% -3,10% 6,42%
Family Owns Minority Stake 7 1,66% 1,037 4,23% 1,72% -5,33% 8,03%
Subsidiary 69 1,50% 2,866*** 4,36% 1,19% -8,17% 12,93%
Division 15 1,74% 1,604 4,21% 1,25% -4,58% 10,93%
More than 1 owner 29 2,05% 2,561** 4,30% 1,78% -7,03% 10,13%
By dividing the sample into acquisitions of fully family owned targets and the rest of the acquisitions, it becomes clear that there is a significant difference between them. In Table 8 it is illustrated that an acquirer who buys a fully family owned target has on average a 0,45% abnormal announcement return, whereas acquirers of all other targets have on average a 1,64% abnormal announcement return. An one-sample t-test shows that for acquiring fully family owned targets the bidders CARs is not significantly different from zero, whereas the rest of the sample there is on average a significantly positive bidder CAR.
A t-test for mean differences and a Wilcoxon Rank test for median differences confirm that bidders acquiring fully owned family firms were worse off compared to bidders acquiring partly family owned or non family owned targets.
Table 8: Mean and median comparison in two groups
Fully family owned represents all target firms which were 100% owned by a family (member). Partly Or Non Family represents all target firms of which less than 100% of the stake was owned by families. The T-statistic stands for the one-sample t-test to check if the mean CAR is different from zero. For the analysis of differences between means and medians, the t-test for mean differences (in parentheses) and the Wilcoxon Rank test for median differences [in square brackets] are used. With significance levels of 1%,5% and 10% denoted as ***,** and * respectively.
Fully family owned Partly or non family Difference
Mean Median Mean Median Mean Median
CAR 0,45% 0,07% 1,71 1,57 -1,26 -1,50
T-statistic 1,085 4,400*** (-2,076*) [-2,521**]
5.1 Mean and median comparison
Bidder CARs where on average positive, with a mean of 1,23% and a median of 0,82%. As later results will also point out, the median is always lower than the mean, which points out that the announcement return distribution is slightly positively skewed. Table 9 shows the results of the comparison of means and medians.
For family owned targets, on average (median) there is a positive acquirer announcement return of 0,67% (0,16%). This is significantly lower than the average (median) of the bidder announcement returns who acquired non family owned targets, which was 1,67% (1,20%). Table 12 (appendix) shows that only the acquisitions of non family owned targets gave bidders CARs significantly higher than zero. This is consistent with my expectations, namely that the family owners require a large premium for giving up the benefits of control. Since the differences are significant, I conclude that deals with family owned targets generates lower, close to zero, bidder announcement returns compared to deals with non family owned targets.
Method of payment
Then it is compared whether results were influenced by payment methods. In order make a simplified comparison between payment methods, results are classified in payments with cash, shares and other methods of payment. A deal is classified as a cash deal when it involves a cash payment and no stock payment. Vice versa, a deal is classified as a share deal when it involves a stock payment but does not have a cash component. All deals which have either a mixed form of cash and stock payment, or have another type of payment method is classified as ‘other’ method of payment.
considers the stock of the bidder as not overvalued. They also reported positive announcement returns for deals paid for with shares.
When comparing results with respect to ownership influences, there are not many significant differences to be observed. Regarding to cash payments, the picture of abnormal returns are relatively similar to the returns of the total sample. The mean (median) of a cash payment generated a positive return of 1,20% (0,69%). For acquiring family owned targets this is 0,71% (0,15%), and non family owned targets this is 1,57% (1,17%), which in this case is not proven to be significantly different.
There is no significant difference between share payment for family owned targets and non family owned targets. However, regardless the fact that there is no statistically significant difference, it is striking that for family owned targets acquired by shares, there is a relatively high average bidder abnormal return of 2,14%. For non family targets, bidders reported on average a 0,09% return. It seems likely that there is an interaction effect between share payments and family ownership. Nevertheless, I think this is not a strong conclusion since there were not a lot of observations of deals paid for with shares, namely 22.
Table 9: Comparisons of means and medians between family and non family owned targets
For the analysis of differences between means and medians, the t-test for mean differences (in parentheses) and the Wilcoxon Rank test for median differences [in square brackets] are used. With significance levels of 1%, 5% and 10% denoted as ***, ** and * respectively.
Total sample Family Non Family Difference
Mean Median Mean Median Mean Median Mean Median
Control variables
Table 10 presents the results of the mean and median analysis of the bidder CARs through the control variables. For the entire sample, it appears that, every type of control variable still enables the bidder to generate a positive CAR.
When I looked for differences between countries, I did not find any significant differences in bidder CARs between acquiring family and non family owned targets. However, I believe that each countries sample is too small, since the analysis of the entire sample produces a significant difference as discussed previously.
The analysis which looks at merger waves gives an interesting result. The t-test for mean differences and Wilcoxon Rank for median differences both accept that the mean and median of the bidder CARs for the period of 1996-2000 are the same for acquiring family and non family owned targets. But the period 2001-2008 shows a different result. Here, the differences between CARs for acquiring a family or non family owned firm become more pronounced.
These results indicate that it matters in which period the firm is acquired. It seems that when the market is booming, there is no difference to be observed in bidder abnormal returns between acquiring family owned or non family owned firms. Differences in returns seem to come from outside merger waves.
Table 10: Comparisons of means and medians by control variables
For the analysis of differences between means and medians, the t-test for mean differences (in parentheses) and the Wilcoxon Rank test for median differences [in square brackets] are used. With the T-test values between brackets and significance levels of 1%, 5% and 10% denoted as ***, ** and * respectively.
Total sample Family Non Family Difference
Mean Median Mean Median Mean Median Mean Median
5.2 Multivariate regression
Table 11 presents the results of the multivariate regression analysis. Regression (1) shows an analysis which only looks at the research variables, namely family ownership and both payment methods. Regression (2) and (3) are conducted to test if the results are robust to control variables. In regression (2) dummy variables are added and regression (3) includes ratios. Regression (4) and (5) are added to investigate interactions between the research variables, with family control and cash payments and family control and share payments respectively.
The first regression shows weak evidence that bidder CARs are negatively influenced when the target firm is family owned. This is consistent with the theory that bidder CARs are lower when buying a family owned firm, since the owning family requires a premium for selling the firm. The regression further shows that cash and share payments both do not have a significant influence on bidder CARs.
Regression (2) shows that the family ownership effect is still valid when I expand the analysis with control variables. The coefficient of -0,010 is significant at the 10% level. This second regression shows that none of the dummy control variables have a significant impact on bidder CARs. It shows that bidder CARs are insensitive to target location (cross-border or domestic), the period in which the deal has been made (during a merger wave or not) and industry relatedness (focused or diversified acquisition). This regression also includes country dummies, which seem to have no impact on bidder CARs as well as on results from the previous regression.
Table 11: Coefficients of the multivariate model
With the T-test values between brackets and significance levels of 1%, 5% and 10% denoted as ***, ** and * respectively. With White heteroskedasticity-consistent standard errors & covariance.
(1) (2) (3) (4) (5)
Constant (2,637***)0,020 (2,386**)0,030 (3,070***)0,041 (2,787***)0,041 (3,113***)0,045 Family ownership (-1,812*)-0,010 (-1,718*)-0,010 (-1,185)-0,007 (-0,771)-0,009 (1,705*)-0,011 Cash payment (-0,441)-0,003 (-0,521) -0,004 (-0,018)0,000 (-0,146)-0,002 (-0,046)-0,000 Share payment (-0,308)-0,004 (-0,303) -0,004 (-0,371)-0,005 (-0,444)-0,005 (-1,546)-0,022
Family * Cash payment (0,213)0,003
Family * Share payment (2,022**)0,037
Cross border acquisition (-1,463) -0,015 (-1,581)-0,014 (-1,407)-0,014 (-1,540)-0,015 Period (-0,608) -0,004 (-0,737)-0,006 (-0,817)-0,005 (-0,839)-0,006 Same industry (1,222) 0,007 (0,920)0,005 (0,901)0,005 (0,946)0,006 Relative size (2,831***)0,011 (2,686***)0,011 (2,823***)0,012 Tobin’s Q (1,246)0,002 (1,487)0,002 (1,635)0,002
Country dummies No Yes Yes Yes Yes
R squared 0,016 0,038 0,076 0,077 0,096
Adjusted R squared 0,002 -0,001 0,028 0,023 0,044
In regression (4) the first interaction variable is included, namely the interaction between family control and bidders using cash as payment for the acquisition. This regression shows that there is no significant interaction between cash payments and family control. This is no surprise, since I provided arguments that cash payments can have a negative as well as a positive impact on bidder CARs. I expected that family owners do not prefer cash payments which could hurt bidder CARs. However it seems that the signal that the acquirer has no liquidity problems neutralizes this negative effect. Furthermore, the inclusion of this interaction variable has very little impact on results from the previous regression.
Regression (5) is the final regression, and this contains the interaction between family control and bidders using shares as payment method. In this regression there are two important changes that are worth mentioning. Firstly, family control is now significant with a coefficient of -0,011. Secondly, family firm acquisitions which have been financed with shares also are better of compared to the rest of the sample. This means that the negative effect of family control is apparent when I take the positive effect of equity deals into account. A coefficient of 0,037 is consistent with my expectations that a family owner benefits from a stock-swap deal since they keep a certain amount of control over their sold firm. In this case, family owners require a lower or no premium on selling their firm.
Heteroskedasticity and normality
Multicollinearity
To be sure there is no multicollinearity between variables in this regression, I constructed a correlation matrix between all 8 variables, as table 15 (appendix) shows. A correlation is too high when it is larger than 0,3. There is a high correlation between cash payments and share payments, however this is expected since those two variables are dummies and account for roughly 85% of all acquisitions (table 10 appendix). The correlation between period and
Tobin’s Q is relatively high with 0,3.
6 Conclusions
This paper has examined whether bidder announcement returns are influenced by target firm family ownership. One theory about the influence of family ownership is about the impact of the family owner(s) during negotiations of the acquisition. The family owner is more reluctant to sell his firm, for two reasons. Firstly, a family owner wants to make sure that their firm survives in the long run, either with or without their involvement. Since they want to make this sure, they could block some efficient deals if they for instance have less confidence in the acquisition compared to the manager (if the manager is not the owner). The second reason is that a family owner is enjoying the benefits of concentrated ownership, and has no reason to give it up. In this case the owner also might block efficient deals. To overcome the resistance of large family shareholders one might be willing to pay a large premium towards to the targets shareholders, which in turn should be reflected in the acquirer’s cumulative abnormal announcement returns.
This effect is examined for a sample of 203 acquisition announcements between January 1996 and January 2009. I find evidence that bidder CARs are significantly lower when they acquire a family owned firm, compared to acquiring a non family owned firm. This provides evidence for the view that bidders are expected to pay a premium in case the target firm is family owned. A non family owned target is has less negotiation power and is therefore less successful in negotiations to a premium. Furthermore, I find no evidence for the effect during the European merger wave which lasted from 1993 to 2000. It appears that the difference in bidder CARs is only present outside merger waves. I believe that during the merger wave, the bidder CARs of all acquisitions are lower, causing the differences between acquiring a family and a non family target to disappear. I further find that there is a potential negative relation between the degree of family ownership and bidder CARs.
This research adds to the existing literature since it has evaluated family target firm ownership on acquisitions in the context of the acquirer’s short term earnings. This contributes in understanding the effect of target firm characteristics on bidder shareholder wealth. However, future research still needs to point out if my findings are still valid when improvements have been made. Firstly, a more extensive dataset would increase the quality and reliability of the outcome of this investigation. It can also shed light to a more extensive analysis, for instance by analyzing differences between acquisitions of fully family owned firms and partly family owned firms.
References
Andrade, Gregor, Mark L. Mitchell and Erik Stafford (2001). New evidence and perspectives on mergers. Journal of Economic Perspectives 15, 103-120.
Anderson, Ronald C., and David M. Reeb, (2003). Founding-family ownership and firm performance: evidence from the S&P 500, Journal of Finance 58, 1301-1328.
Balakrishna, Srinivasan and Mitchell P. Koza (1993). Information asymmetry, adverse selection and joint ventures: Theory and evidence. Journal of Economic Behavior and
Organization 20 (1), 99-117.
Baugess, Scott and Thomas Stegemoller (2008). Protective governance choices and the value of acquisition activity. Journal of Corporate Finance, 14 (5), 550-566.
Berle, Adolf A., and Means, Gardiner C. (1932). The modern corporation and private property. New York: Macmillan Publishing Co.
Bhaumik, Sumon Kumar, and Ekta Selarka (2008). Impact of M&A on firm performance in India: Implications for concentration of ownership and insider entrenchment. SSRN
Working paper.
Bouwman, Christa H.S., Kathleen Fuller and Amrita S. Nain (2009). Market valuation and acquisition quality: empirical evidence. Review of Financial Studies 22 (2), 633-679. Brown, Stephen J. and Jerold B. Warner (1985). Using daily stock returns: the case of event
studies. Journal of Financial Economics, 14 (1), 3-31.
Bruner, Robert F. (2002) Does M&A pay? A survey of evidence for the decision maker.
Journal of Apllied Finance 12 (1), 48-68.
Burkart, Mike, Fausto Panunzi and Andrei Schleifer (2003). Family firms. Journal of Finance 58 (5), 2167-2202.
Caprio, Lorenzo, Ettore Croci and Alfonse Del Guidice (2010). Ownership structure, family control and acquisition decisions. SSRN Working paper.
Capron, Laurence and Jung-Chin Shen (2007). Acquisitions of private vs. public firms: Private information, target selection, and acquirer returns. Strategic Management Journal 28 (9), 891-911.
Chang, Saeyoung (1998). Takeovers of privately held targets, methods of payment, and bidder returns. Journal of Finance 53, 773-784.
Chung, Kee H. and Stephen W. Pruitt (1994). A simple approximation of Tobin’s q. Financial
Management 23 (3), 70-74.
Claessens, Stijn, Simeon Djankov and Larry H. P. Lang (2000). Separation of ownership from control of East Asian firms. Journal of Financial Economics 58, 81-112.
Conn, Robert L., Andy Cosh, Paul M. Guest and Alan Hughes (2005). The impact on UK acquirers of domestic, cross-border, public and private acquisitions. Journal of Business
Finance and Accounting 32 (5) & (6), 815-870.
Cooney, John W. Jr., Thomas Moeller and Mike Stegemoller (2009). The underpricing of private targets. Journal of Financial Economics 93 (1), 51-66.
Denis, Diane K. and John J. McConnell (2003). International corporate governance. Journal
of Financial and Quantitative Analysis 38 (1), 1-36.
Draper, Paul and Krishna Pauyal (2006). Acquisitions: private versus public. European
Financial Management 12 (1), 57-80.
Doukas, John A., Martin Holmen and Nickolaos G. Travlos (2002). Diversification, ownership and control of swedish acquisitions, European Financial Management 8, 281-314. Dyck, Alexander and Luigi Zingales (2004). Private benefits of control: An international
comparison. Journal of Finance 59, 537-600.
Faccio, Mara, John J. McConnell and David Stolin (2006). Returns to acquirers of listed and unlisted targets. Journal of Financial and Quantitative Analysis 41, 197-220.
Fuller, Kathleen, Jeffry Netter and Mike Stegemoller (2002). What do returns to acquiring firms tell us? Evidence from firms that make many acquisitions. Journal of Finance 57, 1763-1793.
Georgen, Marc and Luc Renneboog (2004). Shareholder wealth effects of European domestic and cross-border takeover bids, European Financial Management 10 (1), 9-45.
Grinblatt, Mark, and Sheridan Titman (2002). Financial Markets and Corporate Strategy, 2nd
Edition (Irwin McGraw-Hill, Boston, MA).
Hietala, Pekka, Steven Kaplan, and David Robinson (2003). What is the price of hubris? Using takeover battles to infer overpayments and synergies. Financial Management, 32 (3), 2003.
Jensen, Michael C. and W.H. Meckling (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics 3, 305-360.
La Porta, Rafael, Florencio López De Silanes and Andrei Schleifer (1999). Corporate ownership around the world. Journal of Finance 54, 417-517.
Lang, Larry H.P., René M. Stulz and Ralph A. Walkling (1989). Managerial performance, Tobin’s q and the gains from succesful tender offers. Journal of Financial Economics 24, 137-154.
MacKinlay, A. Craig (1997). Event studies in economics and finance. Journal of Economic
Literature, 35, 13-39.
Martynova, Marina and Luc Renneboog (2009). The performance of the european market for corporate control: Evidence from the 5th takeover wave. European Financial
Management, Forthcoming.
Maquiera, Carlos P., William L. Megginson and Lance Nail (1998). Wealth creation versus wealth redistributions in pure stock-for-stock mergers. Journal of Financial Economics 48 (1), 3-33.
Miller, Danny, Isabelle Le Breton-Miller, Richard H. Lester, and Albert A. Cannella Jr., (2007). Are family firms really superior performers? Journal of Corporate Finance 13, 829-858. Moeller, Sara B., Frederik P. Schlingemann and René M. Stulz (2004). Firm size and gain from
acquisitions. Journal of Financial Economics 73, 201-228.
Moeller, Sara B., Frederik P. Schlingemann and René M. Stulz (2005). Wealth destruction on a massive scale? A study of acquiring-firm returns in the recent merger wave. Journal
of Finance 55, 757-782.
Moeller, Sara B. and Frederik P. Schlingemann (2005). Global diversification and bidder gains: A comparison between cross-border and domestic acquisitions. Journal of
Banking and Finance 29, 533-564.
Moeller, Thomas (2010). Prior target valuations and acquirer returns: risk or perception?
SSRN Working Paper.
Morck, Randall, Andrei Shleifer and Robert W. Vishny (1988). Management ownership and market valuation: An empirical analysis. Journal of Financial Economics 20, 293-315. Morck, Randall and B. Yeung (2003). Agency problems in large family business groups.
Officer, Micah S., Annette B. Poulsen and Mike Stegemoller (2009). Target-firm information asymmetry and acquirer returns. Review of Finance 13, 467-493.
Rajan, Raghuram, Henri Servaes and Luigi Zingales (2000). The cost of diversity: The diversification discount and inefficient investment. Journal of Finance 55 (1), 35-80. Scharfstein, David S. and Jeremy C. Stein (2000). The dark side of internal capital markets:
Divisional rent-seeking and inefficient investment. Journal of Finance 55 (6), 2537-2564.
Schoenberg, Richard (1999). Cultural Compatibility in International Acquisitions in F. Burton, M. Chapman, and A. Cross (eds.) International business organization: Subsidiary
management, entry strategies and emerging markets, Academy of International
Business series. New York: St. Martin's Press; London: Macmillan Press, 294-306. Servaes, Henri (1991). Tobin’s Q and gains from takeovers. Journal of Finance, 66 (1),
409-419.
Shen, Jung-Chin and Jeffrey J. Reuer (2005). Adverse selection in acquisitions of small manufacturing firms: a comparison of public with private targets. Small Business
Economics 24 (4), 392-407.
Shleifer, Andrei and Robert W. Vishny (2003). Stock market driven acquisitions. Journal of
Financial Economics 70 (3), 295-311.
Shin, Hyan-Han and Réne M. Stulz (1998). Are internal capital markets efficient? Quarterly
Journal of Economics 113 (2), 531-552.
Sraer, David and David Thesmar (2007). Performance and behavior of family firms: Evidence from the French stock market. Journal of the European Economic Association 5, 709-751.
Sundarsanam, Sudi and Ashraf A. Mahate (2003). Glamour acquirers, method of payment and post-acquisition performance: The U.K. evidence. Journal of Business Finance and
Accounting 30, 299-341.
Travlos, Nickolaos G. (1987). Corporate takeover bids, methods of payment and bidding firms’ stock returns. Journal of Finance 42 (4), 943-963.
Villalonga, Belen and Raphael H. Amit (2009). How are U.S. family firms controlled? The
List of figures Tables
Table 1: Takeover characteristics and their expected effects on bidder CARs Table 2: Takeover characteristics and their units of measurement
Table 3: Sample selection criteria Table 4: Ownership data
Table 5: Descriptive statistics of the acquirers
Table 6: Descriptive statistics of the cumulative abnormal returns Table 7: Mean and median comparison per type of ownership Table 8: Mean and median comparison of two groups
Table 9: Comparison of means and medians between family and non family owned targets Table 10: Comparison of means and medians by control variables
Table 11: Coefficients of the multivariate model
Table 12: Bidder CARs comparison by takeover characteristics Table 13: Heteroskedasticity and normality per regression Table 14: Acquisitions per year
Appendix
Table 12: Bidder CARs comparison by takeover characteristics With significance levels of 1%,5% and 10% denoted as *,** and *** respectively
Total Perc. t-statistic Mean Std. Dev Median
Family owned 90 44,33 1,740 0,67% 3,64% 0,16%
Non family owned 113 55,67 4,147*** 1,67% 4,34% 1,20% Cash payment 151 74,38 3,862*** 1,20% 3,53% 0,69% Stock payment 22 10,84 0,785 0,93% 5,57% -0,10%
Other 30 14,78 2,210** 1,58% 3,91% 1,38%
Cross border deal 181 89,16 3,596*** 1,07% 3,61% 0,82% Domestic deal 22 10,84 2,843*** 2,52% 4,16% 0,92% Same industry 125 61,58 4,142*** 1,44% 3,69% 1,17% Different industry 78 38,42 1,831* 1,17% 4,26% 0,45% 1996-2001 71 34,98 1,314 0,82% 4,77% 0,48% 2002-2008 132 65,02 4,528*** 1,40% 3,46% 0,85% the Netherlands 67 33,00 2,633** 1,14% 3,55% 0,83% Belgium 16 7,88 1,475 1,18% 3,20% 0,00% Germany 120 59,11 3,191*** 1,28% 4,64% 0,71% No. of deals 203 100,00 4,333*** 1,23% 4,04% 0,82%
Table 13: Heteroskedasticity and normality per regression With significance levels of 1%,5% and 10% denoted as *,** and *** respectively
(1) (2) (3) (4) (5)
White's 2,921** 1,649 1,408 1,512 1,506
Table 14: Acquisitions per year
Table 15: Correlation matrix
Table 16: Multicollinearity check
Year Number of Acquisitions Percentage
1996 1 0,49 1997 8 3,94 1998 9 4,43 1999 11 5,42 2000 30 14,78 2001 12 5,91 2002 28 13,79 2003 18 8,87 2004 20 9,85 2005 21 10,34 2006 15 7,39 2007 22 10,84 2008 8 3,94 Total 203 100,00
Family Cash Share Cross Period Same Relsize Q Family 1 -0,054 0,006 0,122 -0,006 0,006 -0,129 0,052 Cash payment 1 -0,586 0,044 -0,112 0,018 -0,015 0,017 Share payment 1 0,020 0,230 0,144 0,063 0,032 Cross border 1 0,085 0,086 -0,113 -0,039 Period 1 -0,034 -0,048 0,304 Same industry 1 -0,045 0,048 Relative size 1 -0,135 Tobin’s Q 1
Variables Variance Inflation Factors
