Ownership concentration and premiums paid
_
Why do European listed acquirers pay more than unlisted acquirers?
Koen Dijkman
Master’s Thesis Finance University of Groningen Department of Finance
Author: Koen Dijkman
Programme: MSc BA Finance
Student number: 1531182
E-mail: k.dijkman.1@student.rug.nl
Address: Stateheide 36
Zip-code: 9257 MJ
City: Noordbergum, the Netherlands
Submission date: June 21th, 2013
Course name: Master’s Thesis Finance
Course code: EBM866B20
Ownership concentration and premiums paid
_
Why do European listed acquirers pay more than unlisted acquirers?
Koen Dijkman
Master’s Thesis Finance University of Groningen Department of Finance
ABSTRACT
This study shows that shareholders of listed firms receive significantly higher premiums from listed acquirers rather than unlisted acquires. The 5-day market and risk adjusted target return around the acquisition announcement is for acquisitions between listed acquirers almost twice as high than for deals with unlisted acquirers, respectively 20.10% against 10.11%. I investigate 110 complete cash acquisitions of listed targets within the European Union from January 1 of 2000 until 31 December of 2011. I try to answer why listed acquirers pay significantly more than unlisted acquirers.
Key-words: acquisition, agency costs, concentration of ownership, conflicts of interest, firm performance, target abnormal announcement returns
I. Introduction
The study compares the premium paid by listed and unlisted acquirers in European acquisitions. In particular, I devote especially attention to the impact of the ownership concentration and target characteristics on the premium paid by listed and unlisted firms.
Bargeron, Schlingemann, Stulz and Zutter (2008) find that shareholders of listed targets earn significantly more when the acquiring firm is listed on a stock exchange. The cause of these higher premiums paid by listed acquirers might be found in the separation of management and ownership within these firms. According to Jensen and Meckling (1976), the separation of ownership and decision making authority might lead to an agency problem whereby the interests of the management do not match with the interests of the shareholders. The bidder management might insist to make an offer successful because they will be better compensated by managing a larger firm. Also they can gain individual prestige from takeovers. Another reason to make an acquisition successful against any price is to protect own firm against hostile takeovers (Amihud & Lev, 1981; Ben-Amar & Andre, 2006; Cosh, Guest & Hughes, 2006)
The study of Bargeron et al. (2008), which focuses on acquisitions in the U.S., tries to explain the premium paid by target, deal and acquirer characteristics. They study, inter alia, the relationship between the concentration of ownership and the premiums paid by listed and unlisted acquirers. They find that the difference in premiums paid by listed and unlisted firms becomes smaller when the concentration of ownership of listed acquirers increases. So when the ownership structure of listed acquirers becomes more similar to ownership of unlisted firms, the premium difference decreases. This finding suggests that the ownership structure of the acquirer determines significantly the premiums paid to target shareholders. This is the reason why I give especially attention to the role of ownership structure in the premiums paid to target shareholders. The premium paid is measured by the abnormal returns in percentages of the target around the acquisition announcement. The study includes 49 acquisitions by listed acquirers and 61 by unlisted acquirers from the European Union.
In summary, the goal of the study is to examine the impact of ownership concentration and target firm performance characteristics on the premium paid by listed and unlisted acquirers. I hope that this research will contribute to a better understanding of the premiums paid by listed and unlisted firms. In contrast to the study of Bargeron et al. (2008), I focus on acquisitions within the European Union. Because of the international diversity and differences in ownership structure across the European countries, the outcomes may differ in comparison to the results of Bargeron et al. (2008). So this paper gives insight into whether one of their important findings also counts for other acquisition markets than the U.S. Furthermore, the outcomes of this research may have additional value for shareholders of potential targets or acquirers.
This paper is organized as follows. Section II reviews the existing literature on the coherence between concentration of ownership and agency costs. In addition, other variables which are considered to be important to explain the premium paid are discussed. Subsequently, hypotheses are formulated based on the discussed literature. Section III gives an outline of the sample construction procedure and it includes a sample description of the data. Also it presents the statistical methods of the event study and the regression analyses. Section IV provides the results of the study. Section V presents the final conclusions and limitations of the study. Finally the paper gives suggestions for future research on this topic.
II. Theoretical Background
Most of the studies in this field of research have focused on the market reaction of the acquirer during acquisition announcements (Alexandridis, Petmezas & Travlos, 2010; Chang, 1998; Faccio, McConnell & Stolin, 2006; Fuller, Netter & Stegemoller, 2002). In general, these studies show that takeovers of unlisted firms result in small positive abnormal returns for the listed acquirer during the acquisition announcement. Acquisitions of listed firms show a slightly negative or no abnormal return to the shareholders of the listed acquirer.
The next part of this theoretical background reviews the relationship between concentration of ownership, agency costs and the target premium paid. Also other possible determinants of the target premium paid will be reviewed. Finally, I outline why the focus on cash only acquisitions is chosen and how this may affect the results of the study.
2.1 Concentration of ownership and the agency problem
Bargeron et al. (2008) conclude that the ownership structure plays an important role in the acquisition premium paid to target shareholders in the United States. They put especially attention to the role of ownership concentration in the target premium paid. In their study the ownership concentration refers to the percentage of issued shares owned by the management. This variable focuses only on the concentration of ownership among managers. The ownership concentration in a broader scope expresses the percentage of issued shares which belongs to individual investors or large block holders. These strategically held shares amounts 5% or more of the issued shares. Often the strategically hold shares are held by pension or mutual funds. Other strategically investors might be companies, investment banks or government institutions. This broader definition of
concentration of ownership, which is also be used by Burkart, Gromb and Panunzi, (1997), is also
applied in this study.
The conclusions of Bargeron et al. (2008) are not automatically applicable to the European M&A markets. In particular, the ownership structure of European firms differs from Anglo-Saxon countries. Corporate control and ownership of Continental European listed firms tend to be highly concentrated in comparison to Anglo-Saxon listed firms. Most Continental European companies have relatively large shareholders such as families and banks, while widely held firms or diffused ownerships are more prevalent in Anglo-Saxon countries (Faccio & Lang, 2008). The concentration of shareholders also depends on the type of firm. Faccio and Lang (2008) show that financial and large firms are more likely to be widely held. Non-financial and small firms are more often family controlled.
of optimizing the shareholders’ value and firm performance. Moreover, in many cases the CEO have better and more information about the firm and the consequences of their actions than the shareholders. So divergent interests and asymmetric information between managers and shareholders may result in a loss of control experienced by the shareholders of the firm (Demsetz, 1983). Agency costs are the result of the ownership separation and defined by Jensen and Meckling (1976) as the sum of the expenditures to limit the agency problem and the reduction in welfare experienced by the shareholders.
To mitigate the conflict of interest, the principal can create incentives for managers in order to ensure an effective agency relationship. One way to resolve these conflicts of interest is monitoring management’s performance. Another way to deal with the agency problem is to design executive compensation schemes which create efficient incentives for managers to maximize shareholder value (Bebchuk & Fried, 2003). Equity based compensation linked to managerial performance, such as stock option plans, can provide incentives to managers that may be beneficial for their shareholders.
Applying the theory of agency costs to acquisition behavior of managers, several conflicts of interests between management and shareholders of bidding firm can be distinguished. Various studies find that the management of the bidding firm gain wealth at the cost of their shareholders (Cosh et al., 2006; Firth, 1991). Compensation and prestige of managers may increase as a result of an acquisition (Ben-Amar & Andre, 2006). In addition, managers may acquire other firms in order to be safer from hostile acquisitions and ensuring their own job (Amihud & Lev, 1981).
for listed acquirers with relatively low level of concentration of ownership. Also Cosh et al. (2006) find evidence for a strong relation between CEO ownership and takeover performance. They argue that ownership concentration mitigates agency problems.
Since unlisted firms do not disclose publicly financial information, assumptions are made on the level of ownership concentration of unlisted firms. Bargeron et al. (2008) state that the expected concentration of ownership of unlisted firms must be high because unlisted firms are not able to issue publicly traded equity. Based on the elaborated literature I assume that agency costs within the acquirer can be mitigated by a high level of ownership concentration. Large individual investors or block holders may have stronger monitoring power towards management decisions than individual investors. They will use their monitoring power to optimize the value of their investments. This will increase pressure on the management to perform in line with the interests of their shareholders. Therefore it will reduce the likelihood of self-interested managerial decisions (Burkart, Gromb & Panunzi, 1997).
The relationship between the concentration of ownership of the target and their premium received is another interesting aspect of the agency theory, though the link between the ownership concentration of the target firm and the target premium received is less clear. Hogfeldt and Hogholm (2000) state that the relationship is positive: the higher the concentration of ownership, the higher the target premium received. They argue that large target shareholders can use their voting power as bargaining power in deal negotiations, so if this bargaining power is severe, they can enforce a higher deal value. Grossman and Hart (2008) argue a positive relationship as well, but they use a different theory to explain the positive relationship. The authors state that when the target is widely held, the shareholders behave like free-riders. In this situation shareholders will believe that because of their limited voting control they do not have any influence on the share price paid. Therefore, a decision of an individual target shareholder does not affect the success of acquisition announcement. The authors reason that no target shareholder will accept an offer below the post-takeover value of the target company. So the acquirer can only be successful when they pay out all post take-over benefits to the widely held target company.
2.2 Other determinants of the target premium paid
According to Berkovitch and Narayanan (1993) synergy gains are the main reason for the majority of the acquisitions. Acquisitions can create economies of scale and scope. These operating synergies arise through for example the elimination of duplicate activities which exists with the target firm. However these operating synergies are of particular interest when the acquirer and the target firm are in the same industry. The combined entity after the acquisition may become more cost efficient. This will increase the post-acquisition profitability which creates an incremental cash flow to the shareholders. Also horizontal acquisitions may reduce competition which also contributes to higher profitability. In line with these acquisition reasons it can be stated that when a firm has strong synergy gains with the target firm, the acquirer is willing to pay higher premiums to the target shareholders than to target shareholders of firms which are not operating in the same industry. So a higher prevalence of horizontal acquisitions among listed acquirers may explain the higher premiums paid (Hayward & Hambrick, 1997).
Another important explanation of higher target premium paid by listed acquirers is a simple one. The target premium paid should be largely explained by the value of the target to the acquirer. Target shareholders of firms with a high growth or profitability potential must be rewarded with high target premiums. So determinants of future profitability and growth prospects of targets should have an important influence on the target premium paid. Sales growth before the acquisition announcement is often used as proxy of growth opportunities (Bargeron et al., 2008). At the same time it is important to realize that historical growth does not guarantee a flourishing future. The return on equity is a ratio to measure the profitability of the firm. It is a more useful measurement than a variable as earning per share since return on equity includes the balance sheet (Stern, Shiely & Ross, 2004)
2.3 Market of research
within the European Union over the period 1998-2000. So based on this study I expect lower target premiums paid to the target shareholders.
If one type of acquirer is more involved in cross-border deals than the other, it might affect the target premium difference. Therefore I examine to what extent the target premium differs due to a so-called 'cross-border effect' within the European Union. A European study on this subject is published by Goergen and Renneboog (2004). They analyses the short-term wealth effects of large intra-European takeover bids and compare those to domestic takeovers over the period 1993-2000. The announcement effects for domestic and cross-border targets are respectively 10.2% and 11.4%. However these differences are not statistically significant. In contrast to the conclusions of Goergen and Renneboog (2004), Campa and Hernando (2004) find evidence for lower target announcement returns for cross-border deals than domestic deals within the European Union. They attribute lower cross-border target returns to the existence of obstacles of cross-border deals such as cultural, legal or transaction barriers. These obstacles may be one of the explanations of the lower announcement returns because the barriers reduce the profitability of the acquisition.
2.4 Method of payment
Unlisted firms do not have the ability to finance acquisitions by publicly traded equity. This may have important consequences for the ability of unlisted firms to acquire listed targets. For example, unlisted firms cannot offer equity to the target firm during acquisitions. To avoid that the financing decision disturb the comparison of target premium paid by listed and unlisted acquirers, I focus on acquisitions which are only financed by cash. This is an important but unavoidable limitation of the study. Otherwise I cannot make a fair comparison of the target premium paid by the type of acquirer. Because of this limitation, it is interesting to examine in which way cash only acquisitions affects the outcome of this study.
Listed firms can finance cash transactions by internally generated funds, debt or pre-equity issues (Amihud, Lev & Travlos, 1990). The method of payment gives therefore no information how listed firms finance cash acquisition internally. However, if the restrictions of cash only acquisition would be dropped, some acquisitions by listed acquirers are compared with acquisitions which cannot be acquired by unlisted firms. In particularly, this counts for acquisitions which are financed by equity. This would make conclusions on premium differences paid by listed and unlisted firms unreliable. Therefore the focus on cash only acquisition is still necessarily.
acquisitions by cash through issuing debt depends on the debt capacity and existing leverage of the acquirer. An important bidder management incentive for cash financing is that it maintains the existing corporate governance structure. Equity financing, on the other hand, may lead to a dilution of the shareholder power of the existing shareholders. Acquirers prefer cash when a bidder's controlling shareholder has an intermediate level of voting power in the range of 20 up to 60%. In this case equity financed acquisitions threaten the voting power of existing shareholders of acquirer. If the concentration of shareholders is very low or very high, equity financing is unlikely to threaten the voting power of the existing shareholders.
Harford, Klasa and Walcott (2009) confirm the findings of Faccio and Masulis (2005) that most acquirers finance their cash deal by issuing debt. Namely, they find that the probability of a cash deal is negatively associated with an increase of leverage level before the acquisition announcement. Furthermore they show that when an acquirer’s leverage is over the level of the target, it is less likely that the acquisition is financed with cash instead of equity. But the target shareholders reaction depends on the method of payment as well. Moeller, Schlingemann and Stulz (2004) and Andrade, Mitchell and Stafford (2005) find significant higher target returns for all-cash offer than all-equity offers.
Based on the discussed studies, I assume that the limitation to cash deals influence the sample of selected acquisition in this study. In line with the findings of Faccio and Masulis (2005), I expect that the sample includes relatively many listed acquirers with intermediate level of concentration of ownership. Furthermore, I expect that the premiums paid are relatively high because of the focus on cash deals.
In order to examine the role of ownership concentration and target characteristics described in the literature review I formulate the following research question:
What is the impact of the concentration of ownership and target firm performance characteristics on the premiums paid by listed and unlisted acquirers?
2.5 Hypotheses
In order to answer the above research questions I formulate five hypotheses. These are summarized in table I. The formulated hypotheses are based on the literature. I expect that the premiums paid by listed acquirers are significantly higher than the premiums paid by unlisted acquirers. This is the
first hypothesis (H1) which is based on the findings of Bargeron et al (2008). The next hypothesis is
shareholders is strong. In this way, the interests of the shareholders are better represented by the management of the firm. This reduces the possibility that they overpay in acquisition deals at the cost of the shareholders. That is why I hypothesize that the concentration of ownership of acquirers
decreases the premiums paid (H2). To investigate the hypothesis it is assumed that the concentration
of ownership of unlisted firms is very high with respect to listed firms. In a similar way, I
hypothesize that the target’s concentration of ownership increases the premiums paid (H3).
Since I assume that the target premium paid is significantly higher for listed acquirers, I expect that targets of listed firms have more potential sales growth and better firm performance. I hypothesize that firm performance of the target firm is higher for listed acquirers than for unlisted
acquirers (H4). I distinguish several firm performance indicators. The historical three year annual
compounded sales growth is performance indicator which reflects the growth of the target firm. Other target firm’s performance indicators such as EV/EBITDA, Price-Earnings ratio and ROE are used to determine the effect of firm performance on the premiums paid. The Sales of the target is also used as a performance indicator. If there is no significant difference in those target indicators for listed and unlisted acquirers, it might the case that the positive relationship between firm performance and premiums paid for listed acquirers is stronger than for unlisted acquirers. This can also explain the difference in the premium paid by listed and unlisted acquirers. Either the performance target characteristics or the size of the coefficients may explain the target premium difference paid. Therefore I hypothesize that the relationship between target performance and
premiums paid is stronger for listed acquirers than for unlisted acquirers (H5).
***Insert table I about here***
The variables which measure the acquired stake, cross-border effect and synergy effects are used as control variables in this study. The relationships of those variables with the target premium paid are not captured in separate hypotheses. However I discuss shortly which relationship I predict between the control variables and the target premium paid.
For the stake acquired, I assume that for larger acquired stakes the premiums paid in percentages also increases. If more shares are demanded as a result of an acquisition announcement, it is logically that the stock market reacts stronger. Furthermore I assume that for horizontal acquisitions the potential synergy gains are higher for the acquiring firm. Thus, the target premium paid should be higher for horizontal acquisition than for diversifying acquisitions. In line with this reasoning I suppose that listed firms are more involved in horizontal acquisitions.
(2008). The existence of obstacles deals such as cultural, legal or transaction barrier within Eurozone makes cross-border acquisitions more costly.
III. Data and Methodology
3.1 Data selection
The starting point of the sample collection is to gather all possible acquisitions of listed firms within the European Union in which a listed or unlisted acquirer is involved. The collection of acquisitions and some of the deal, target and bidder characteristics of unlisted and listed firms are downloaded from the Zephyr database. In order to narrow down the number of acquisitions only acquisitions which are completed are selected. An acquisition announcement on the majority of the shares, at least 50%, will have a stronger impact on the targets’ stock return on the announcement date. The selection of only complete deals excludes bad bids which are not taken seriously by the target shareholders. All acquisitions included are announced and completed between January 1 of 2000 and 31 December of 2011. This restriction is put in place because of a high number of missing values before January 1 2000. All the acquisitions are financed by cash in order to prevent that the equity financing method disturbs the measurement of the effects for listed and unlisted acquirers. In this way the outcomes of this study are also comparable to the results of Bargeron et al. (2008). They also focus on cash only deals. Furthermore, I only examine targets which are listed at a stock exchange and headquartered within the European Union. The acquirer must also be headquartered within the European Union. If the acquirer is a subsidiary, I select the acquirer’s immediate parent’s status and nation to avoid that non-European acquisition are included. This procedure is in line with a study of Rustige and Grote (2011). Further, I require a minimum deal value of 5 million euro to exclude small acquisitions. The deal value is considered as the amount paid acquired actual stake. In addition, the shares of the included targets must at least once been traded during the estimation and event window.
3.2 Data description
unlisted and listed acquirers during the year 2005, 2006, 2007 and 2011. Further, the total deal value of acquisitions during those years is higher than the average yearly deal value. The average deal value of the total sample is 537.75 mln EUR. The average deal value for unlisted and listed firms is respectively 582.76 mln EUR and 479.63 mln EUR. The highest deal value from an unlisted acquirer in the final sample is 6583.20 mln EUR which is a bid from Schaeffler KG on Continental AG in 2006. The highest deal value of a listed firm equals 4300.00 mln EUR which a bid from UnitCredit Group on Bank BPH.
Appendix B depicts the distribution of the acquisitions by country for the acquirer and target firm. Compared to other studies (Rustige & Grote, 2011; Scherer & Ravenscraft, 1989) the number of acquisitions from Great-Britain is relatively low. The study of Rustige and Grote (2011) reflects a strong dominance of acquisitions from Great-Britain. Within their sample of European acquisition of public targets approximately 45 % of the deals involve targets from Great-Britain. In my sample 18% of all targets are from Great-Britain. One of the explanations of this lower percentage is that the authors have used different restrictions to determine their dataset. To make an apple to apple comparison, I restrict my sample to cash only acquisitions. While Rustige and Grote (2011) focus on all kind of deals and not only on cash deals. The study of Rustige and Grote (2011) shows for the distribution of acquirers by country also a high percentage of British acquirers respectively 48 % and 18% for our sample. Almost one third of all targets are headquartered in Germany.
3.3 Event study methodology
To measure the acquisition premium paid by listed and unlisted firms the event study methodology of Brown and Warner (1980, 1985) is used. Therefore the stock prices of the listed targets and the market index prices must be first extracted from the Thomson Reuters DataStream database. I use adjusted daily prices from June 1 1998 to April 1 2012. The adjusted daily prices are the closing prices at the end of the day adjusted for capital gains. Therefore I must first transform the observed stock prices into stock returns. The observed stock returns are calculated as follows:
Rit = ln(Pit) – ln(Pit-1) (i)
where
Rit = the daily return on security i over day t. Pit = the price of stock i at time t.
a trading day I choose the first following trading day as the announcement day. I make use of an event window of 3 days and 5 days around the announcement day. To include the leakage of information before the acquisition announcement I include one or two day before the announcement day. To capture the price effects of announcements which occur after the stock market closes and to capture price effects in less efficient markets I also include one or two days after the announcement date (Brown & Warner, 1980; MacKinlay, 1997).
To estimate the normal returns during the event window, I calculate the average return over a period of 250 trading days (t = -260 to t = -11) or I make use of returns on the market index of the specific stocks. The normal returns are used as a benchmark to determine the abnormal returns during the event window. Brown and Warner (1980, 1985) present three models to measure abnormal returns: Mean Adjusted Returns model, Market Adjusted Returns model and Market and Risk Adjusted Returns model.
3.3.1 Mean Adjusted Returns model
The first model assumes that the expected return for a given stock is equal to the average return over the estimation period for stock i. It is named the Mean Adjusted Returns or the Constant Mean Adjusted Return model (ii). The model is consistent with the Capital Asset Pricing model. It assumes that a stock has a constant systematic risk and furthermore it assumes that the expected
return is a constant. So the abnormal returns ARit calculated by difference between the observed
return of the stock Rit and the expected return Eμi.. The t is the t th day of the analysis period or the
event window:
ARit = Rit - Eμi (ii)
3.3.2 Market Adjusted Returns model
The Market Adjusted Returns model corrects the observed return Rit the by the expected return Eμi..
The expected return is the observed return in the local market index of the specific stock over the
estimation window which is defined as Rmt. The model removes the portion of the stock return that
is related to the variation in the market. Hereby it reduces the variance of the abnormal returns. Formula (iii) shows the formula of the Market Adjusted Returns model:
ARit = Rit - Rmt (iii)
The last model I make use of in this event study is the Market and Risk adjusted Returns model. It relates the return of any given stock to the return of the market portfolio, in this case the market index of the specific stock. The model estimates by performing OLS regression the expected return on the α and the β of the specific stock and the market return. The α represents the non-market related risk of stock i or the relative riskiness of stock i. The β indicates the degree to which the volatility of the stock returns is correlated to the volatility of the market return. Mathematically the Market and Risk Adjusted Returns model is expressed as follows:
ARit = Rit – αi – βi Rmt (iv)
where denotes the abnormal return of target company i on day t, is the return of the target company
i on day t and is the average return of target company i over the estimation period. Rmt captures the
specific market return of the local index of the target company i.
3.3.4 Cumulative average Abnormal Returns
I must compute the average abnormal return for all target firms of the sample. It is obtained by summing up all abnormal returns for every stock i on day t and dividing by the number of target
firms represented by Jt (Hogfeldt & Hogholm, 2000; Huang & Walkling, 1987):
AARt= (AR1t +AR2t + ... + ARjt) / Jt (v)
The next step is to aggregate the average abnormal return (AAR) during the chosen event windows. The first cumulative abnormal return (CAR) over the announcement period gives the percentage changes over the three-day period:
CARi(-1,1) = (AARi-1 + AARi0 + AARi1) (vi)
The cumulative average abnormal returns for the 5 days event window are defined as follows:
CARi(-2,2) = (AAR-i2 + AAR-i1 + …+ AARi2) (vii)
3.3.5 Parametric and Non Parametric tests
Since the parametric t-test assumes normal distribution, the distribution of the CARs is tested by the Kolmogorov-Smirnov test. These tests point out that the distributions among all subgroups are not normally distributed. For this reason I use besides parametric test also non-parametric test such as the Wilcoxon Signed Rank test to check the significance of the returns. Non-parametric tests do not, in contrast to parametric tests, require normal distributed data.
Despite of a strong expectation of positive abnormal returns around the acquisition announcement for all estimation methods I will test the abnormal returns if they are significantly different from zero. Namely, these tests will give insight into the influence of the event window and the estimation method on the target premium paid. Since positive abnormal returns are expected as a result of an acquisition announcement a one-tailed t-test is used. The null hypothesis assumes that the cumulative abnormal return is equal or lower than zero.
3.4 Regression analysis methodology
To address the question of how ownership concentration and target firm performance characteristics impact the premium paid by listed and unlisted acquirers set of multiple regressions is conducted. The selection of the ownership concentration, target firm performance and control variables is based on the existing literature. The Ordinary Least Squares (OLS) regression is used to explain the
variance of the target premium paid where β0 is the intercept. β1 is the parameter associated with the
first independent variable. k is the number of independent variables and u is the error term or
residual. This residual ei will not be equal to zero when the chosen independent variables do not
explain all variance of yi.
yi = αi + β0 + β1x1 +β2x2 + βkxk + ei (viii)
To check whether our independent variables are relevant the following hypothesis is tested (ix). In case the null hypothesis is rejected, at least one of the independent variables must not be equal to zero and therefore it should be included in the model.
H0 : β1 = 0. β2 = 0. …. βk = 0 (ix)
H1 : At least one of the βk is non-zero
One of the assumptions is that for each value of x, the values come from probability density with the same variance also called homoscedasticity. If this assumption is violated, the standard errors are no longer correct and heteroscedasticity exists. Hereby the confidence intervals and hypothesis tests may be misleading. In order to deal with potential problems of heteroscedasticity White’s heteroscedasticity-consistent standard errors or robust standard errors are used (Hill, Griffiths & Lim, 2008).
Since OLS regression analysis further assumes that none of the independent variables are an exact linear function of the other, it is important to check whether there is a relationship between the independent variables. If independent variables are correlated to each other, adding or removing the variable will cause changes in the coefficients of the other variables. Correlated independent
variables cause a high ‘explanatory power’ or R-squaredof the model. However, at the same time
present the Variance Inflation Factors for independent variables within the regressions. When the Variance Inflation Factor of the independent variable is greater than 10, the independent is excluded from the regression analysis.
Regression equation (1) is used to test the H2 and H3 for listed acquirers. It checks whether the
ownership concentration of the acquirer is negatively and the target’s ownership concentration is positively related to the premium paid. The dependent variable is the 5-day cumulative market and
risk adjusted return around the acquisition announcement. H2 is accepted for (1) when the
coefficient of ownership concentration acquirer is negative and significant at the 5% level. H3 for
(2) is accepted when the coefficient of the ownership concentration of the target is positive and
significant at the 5% level. Furthermore (1) is controlled for the dummy variable horizontal acquisition, domestic acquisition and the acquired stake after completion of the acquisition. All signs of the control variables are expected to be positive. This also applies for the coming regression equations.
MAR5i = αi + β1OCAi + β2OCTi + β3HORi + β4DOMi + β5STAi + ei (1)
Regression equation (2) checks whether the coefficient results of regression (1) are robust for adding the target firm performance variables into the regression. If, for example, the ownership concentration variables are no longer significant by this addition, it may be concluded that target firm performance variables are more influential to the premium paid than the ownership concentration variables for listed acquirers. Therefore the coefficients of the target firm performance variables are also tested at the significance level of 5%. I expect positive coefficients between the target firm performance and the premium paid. The control variables are also included in (2).
MAR5i = αi + β1OCAi + β2OCTi + β3LNSi + β4ROEi + β5GRSi + β5HORi + β6DOMi + β7STAi + ei (2)
Regression equations (3) and (4) includes the same variables as (1) and (2) except for the ownership concentration of the acquirer. The ownership concentration of unlisted firms is generally not disclosed publicly. Regression equation (3) shows the relationship between ownership concentration of the target with the premium paid. I expect a positive sign for this coefficient. Also
(3) is controlled for the control variables.
MAR5i = αi + β1OCTi + β2HORi + β3DOMi + β4STAi + ei (3)
MAR5i = αi + β1OCTi + β2LNSi + β3ROEi + β4GRSi + β5HORi + β6DOMi + β7STAi + ei (4)
Regression equation (5) examines the relationship between type of acquirer and the premium paid. The dummy variable unlisted is equal to 1 for unlisted acquirers and equal to zero for listed acquirers. I expect that the coefficient of this variable is negative and significant.
MAR5i = αi + β1UNLi + β8HORi + β9DOMi + β10STAi + ei (5)
Regression equation (6) tests hypothesis H5. It shows whether the relationship between target firm
performance variables and the premium paid is stronger for listed acquirers than for unlisted
acquirers. When H5 is accepted I conclude that for listed firms the relationship is stronger. Therefore
I expect negative signs for the interaction term between unlisted acquirers and the target firm performance variables.
MAR5i = αi + β1UNLi + β2LNSi + β3DLNSi + β4ROE + β6DROEi + β6GRS + β7DGRSi (6)
IV. Results
4.1 Event study Results
Panel A of table II reports the characteristics of the CARs for all targets in the sample. The mean of the CARs is around 15% for all six calculations and they are all highly different from zero. The median is around 10% for all calculations and also significantly differed from zero. Panels B and C show that the acquisition announcements by listed acquirers result in higher target CARs. Additionally, it shows that target stocks react almost twice as strong to acquisition announcements by listed firms rather than unlisted firms. For acquisitions by listed acquirers the CAR is around 20%, against 10% for unlisted acquirers. These findings are consistent with the findings of previous studies on this subject (Bargeron et al., 2008; Martynova and Renneboog, 2006b).
The last panel of table II shows whether the differences between the means of both types are
significant. The null hypothesis (H0) states that the premiums paid by listed acquirers are equal or
lower than the premiums paid by unlisted acquirers. The alternative hypothesis (H1) states that
listed acquirers pay higher premiums than unlisted acquirers. Panel D shows that the means of CARs for both types and for all 6 calculations clearly differ. The p-values are all lower than 0.01
and this favors the alternative hypothesis (H1). The non-parametric tests come up with the same
results. Again, the medians of the CARs of all three models and both event windows are significantly different from zero with a significance level below 1%. Also these results show that target shareholders receive higher premiums from listed acquirers than from unlisted acquirers. This in line with the conclusions of Bargeron et al. (2008). The results report a higher relative difference in mean and median CARs between both types of acquirers than reported in the study of Bargeron et al. (2008). However, the absolute premiums paid by European acquirers are significantly lower than the premiums paid by their U.S. counterpart. In the sample of Bargeron et al. (2008) the 3-days target CAR is for listed and unlisted acquirers respectively 29.48% and 22.06%.
***Insert table II about here***
4.2 Comparison of the explanatory variables
The second part of Table III shows the target firm performance characteristics for listed and unlisted acquirers. In contrary to the study of Bargeron et al. (2008) which finds that listed firms generally acquire larger firms than unlisted firms, I must conclude from table III that the differences in net sales, measured by Natural log (LNS), between both groups is insignificant. Bargeron et al. (2008) also find that firms acquired by unlisted firms have significant lower growth opportunities. The fact that unlisted firms acquire firms with lower growth opportunities may explain the lower target premium paid. I check whether this statement is true. I assume that growth rate of sales (GRS) before the acquisition announcement is an indicator of the future growth, though we know that past results do not guarantee future performance. Table III compares the mean and the mean of this variable for both types of acquirers. The average sales growth of a public firm’s target is 33.59% against 18.35% for private firm targets. So it seems that also on the European market unlisted firms are more interested in firms which are less flourishing in the past. However, the growth rates of sales do not differ significantly amongst the two groups of acquirers. All other firm performance target characteristics are also not significantly different across the organizational forms
of the bidder. Therefore H4 must be rejected. The pre-deal firm performance of targets of listed
acquirers is not higher than for targets of unlisted acquirers.
The last part of table III examines whether the deal characteristics of listed acquirers are significantly different from the deal characteristics of unlisted acquirers. These variables are used as control variables in the regression analysis. It is observed that listed acquirers on average are less involved in domestic acquisitions (DOM) and more often involved in horizontal acquisitions (HOR) than unlisted acquirers, though the difference is not significant. The average acquired stake (STA) hardly differs across the type of acquirer. So, none of the deal characteristics are significantly different across listed and unlisted acquirers.
*** Insert table III about here***
4.3 Regression analyses results
dependent variable. The ownership concentration and target firm performance are used as the explanatory variables in the regressions. The deal characteristics which are not significantly different for listed and unlisted acquirers are used as control variables. Even though many of these variables are not significantly different for listed and unlisted acquirers, the relationship between deal and target characteristics may differ for listed and unlisted acquirers.
Table IV presents the regression analyses on the premiums paid by listed acquirers. The target premium paid is measured by the 5-day cumulative abnormal market and risk adjusted return around the acquisition announcement. The first regression (1) shows strong statistical evidence for the negative relationship between the concentration of ownership of the acquirer and the premium paid. Furthermore the concentration of the target does not influence the premiums paid by listed
acquirers. So the first regression confirms H2 for listed acquirers: the concentration of ownership of
the acquirer decreases the premium paid. H3 must be rejected for target of listed acquirers: the
ownership concentration of the target does not increase the premiums paid significantly. Remarkably, the coefficient sign of the ownership concentration of the target is negative.
The other firm performance variables do not change the sign or significance of the acquirer concentration of ownership on the premium paid in regression (2). Strikingly, the variable Acquired stake has no significant positive influence on the bid premium. None of the coefficients of the target
firm performance indicators are significant. This is in contrast to H5 and the theoretical background.
However, I cannot yet reject the H5 because I must first examine the influence of these variables for
targets of unlisted acquirers.
Table IV also presents the adjusted R2 of the regression equations (1) and (2). It adjusts the
R2 for the number of explanatory variables in the model. In this case, the adjusted R2 is used as a
measure to compare the suitability of the explanatory variables in the regressions. It can be seen that
the addition of the of target performance variables into the regression (2) decreases the adjusted R2.
The target firm performance variables do not contribute to the explanatory power of the model. So I can conclude that regression (1) have more appropriate and efficient set of explanatory variables than regression (2). Since the F-statistic is significant for regression (1) and (2), I state that the regression models do partly explain the variance of the premium paid by listed acquirers. For both models at least one of the independent variables should be in the regression equation. The average variance inflation factors show that there is no multicollinearity in the model, all values are lower than 10.
Table IV has shown that the selected target variables do not explain the target premium paid by listed acquirers. To address the question whether target firm performance characteristics of unlisted acquirers explain the target premium paid another regressions are conducted. The same variables as in table IV are used in the regressions in table V except from the ownership concentration of the acquirer. It can be seen that none of the variables in regression (1) influences the premium paid
significantly. So for the target firm performance characteristics of unlisted acquirers, H2 can also be
rejected. The target concentration of ownership does not have a linear relationship with the premium paid. In the second regression (2) the firm performance variables are included. The return on equity (ROE) is significant on a level of 5%. The relationship between the historical Return On Equity and the premium paid by unlisted acquirers is positive. This is in line with my expectations. I assume that firms are prepared to pay higher premiums for targets with better historical firm performance. By adding the firm performance variables, the adjusted R squared of the regression model (1) increases by 2.4% to 8.3%. In contrast to Table IV the addition of the firm performance
variables leads to a more efficient model. These findings are remarkable. In hypothesis H5 I assume
that the relationship between the target performance variables and the premium paid is stronger for listed acquirers than for unlisted acquirers. Based on table IV and V the contrary seems to be true. The addition of the firm performance in the regression equation leads only for unlisted acquirers to a better model. The F-statistic of Table V shows that regression (3) is not a viable explanatory variable. None of the independent variables should be in the regression model. F-statistic of regression (4) is, however, significant. The addition of the firm performance variables increases the explanatory power of the model. The average variance inflation factor indicator of regression (3) and (4) gives no indication of multicollinearity between the independent variables.
The robustness of the outcomes of table IV is also checked by using different event windows and a different estimation method of the abnormal returns. In the appendix .., .. , it can be seen that for each table the ownership concentration of the acquirer is negatively related to the premium paid. This is also found by Bargeron et al. (2008).
*** Insert table V about here***
Based on the results of table III, I conclude that the firm performance of targets of listed acquirer is not significantly different from the firm performance of unlisted acquirers. To explain the
level. The stake acquired by the acquirer (STA) is significant at the 5% level. If more shares are demanded as a result of an acquisition announcement, it is logically that the stock market reacts stronger. From regression (5) it can be concluded that the dummy variable of unlisted firms is negatively related to the premiums paid. The acquirerd stake is positively related to the premium paid. These findings are in line with the findings of Bargeron et al. (2008). Table VI shows that none of the target performance characteristics are significant positively related to the target premiums paid. The only variable which is almost significant is the Return on Equity of the target firm. The control variable acquired stake (STA) is also significant in table VI. However, the
adjusted R2 points out that the addition of the firm performance variables in regression (6) leads to
a more efficient model. This can be caused by the possibility of multicollinearity in the regression equation (6). The average variance inflation factor is relatively high.
V. Conclusions
I investigate complete cash acquisitions of listed targets by listed and unlisted acquirers within the European Union from January 1 of 2000 until 31 December of 2011. This study shows that shareholders of listed firms receive significantly higher target premiums from listed acquirers rather than from unlisted acquires. The 5-day market and risk adjusted target return around the acquisition announcement is for acquisitions between listed acquirers almost twice as high than for deals with unlisted acquirers, respectively 20.10% against 10.11%.
Subsequently I examine why listed firms pay significantly more than unlisted firms by comparing the target firm performance characteristics and deal characteristics for both types of acquirers. I find that listed firms are interested in firms with a lower concentration of ownership than unlisted acquirers. This finding can be combined with the theory of Grossman and Hart (2008), who reason that when the ownership is dispersed no target shareholder accepts an acquisition offer below the post-takeover value of the target company. So the acquiring firm must pay the maximum target premium. This corresponds to the higher target premium paid by listed acquirers. The ownership concentration of the unlisted firms cannot be compared. These firms do not disclose information about their ownership structure. Even though this information is not available it is likely that the ownership of unlisted firms is very concentrated compared to the concentration of ownership of listed firms, because unlisted firms are unable to issue publicly traded shares.
Moreover, it cannot simply be concluded that listed firms pay higher premiums because they are interested in different kind of firms which are more valuable. The concentration of ownership of listed acquirers is significant for different sets of regression models. I find a negative relationship between acquirer ownership concentration and the premiums paid. The regression results show furthermore no relationship between the concentration of the ownership of the target and the target premium paid.
The regressions results on the firm performance variables of the target of listed acquirers show no relationship between the premiums paid. We find a negative relationship between the concentration of ownership of the acquirer and the target premium paid. So if the structure of ownership of listed firms becomes more similar to the ownership of unlisted firms, the target premium differences decrease. This finding is in line with the hypothesis based on the agency theory. I assume based on the agency theory that when the concentration of ownership is high, monitoring ability strength of the shareholders is stronger. In this way, the interest of the shareholders will be better represented by the management of the firm. This will lower the possibility that they overpay in an acquisition deal at the cost of the shareholders.
provide empirical support that the concentration of ownership mainly determines the premium paid since it is hypothesized that the concentration of ownership of unlisted firms is high.
Furthermore I do not find evidence that listed acquirers are prepared to pay more for firms with better target performance characteristics than unlisted acquirers. So the question why listed firms pay significantly more than unlisted firms is still unanswered. However, I can conclude that the concentration of ownership of acquirer is negatively related to the premium paid. The deal and firm performance characteristics seem to be less important.
This study has also some drawbacks. One of them is that the number of acquisitions used in the research restricts the robustness of the findings. However, I find that one can only make valid conclusions if the comparison of acquisitions is fair and the restriction to focus only on cash acquisition in this study is essential but it limits the amount of acquisitions heavily. In addition, this study considers the cumulative abnormal returns around the acquisition announcement as an indicator of the final target premium paid. The acquisition announcement premium may differ from the final premium paid at the date of completion. Also it includes an expectation element of the stock market which presents whether the acquisition announcement should be taken seriously or not. Other methods using a premium measure over a long period of time are, however, sensitive to misspecification of the benchmark return (Brown & Warner, 1985).
Table I: Summary of hypotheses
Number Hypothesis
H1 Listed acquirers pay higher premiums than unlisted firms.
H2 The ownership concentration of the acquirer decreases the premium paid.
H3 The ownership concentration of the target increases the premium paid.
H4 The firm performance of targets of listed acquirers is higher than for unlisted acquirers
H5 The relationship between target firm performance and the premium paid is stronger for listed acquirers than for unlisted
Table II:
The table presents mean and median cumulative abnormal returns during the event windows (-1,+1) and (-2,+2) for three estimations methods for all acquisitions and for listed and unlisted acquirers. ‘MEAN3’ and MEAN5’ are the 3-day and 5-day cumulative mean adjusted returns around the acquisition announcement day. ‘MA3’ and ‘MA5’ are the 3-day and 5-day cumulative market adjusted returns around the acquisition announcement day. ‘MAR3’ and ‘MAR5’ are the 3-day and 5-day market and risk adjusted returns around the acquisition announcement day. Panel A, B and C shows the cumulative abnormal returns for all deals, listed acquirers and unlisted acquirers, respectively. The p-value tests one-sided whether cumulative abnormal returns are larger than 0. The p-value is for each difference in the cumulative abnormal returns between listed and unlisted acquirers is shown. The p-value for each mean difference is based on a t-test. The p-value for each median difference is based on a Wilcoxon Signed Rank Test. ‘Obs.’ is the number of observations.
MEAN3 MEAN5 MA3 MA5 MAR3 MAR5
Panel A: all deals (Obs.=110)
Mean 0.1460 0.1540 0.1460 0.1550 0.1460 0.1560
Median 0.1008 0.1127 0.1144 0.1208 0.1059 0.1165
P-value for t-test on larger listed
cumulative abnormal returns. 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
Wilcoxon Signed Rank Test 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
Panel B: listed acquirer (Obs.=48)
Mean 0.2036 0.2195 0.2044 0.2195 0.2010 0.2206
Median 0.1790 0.1924 0.1802 0.1877 0.1825 0.1901
p-value of t-test on positive
CARs 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
Wilcoxon Signed Rank Test 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
Panel C: unlisted acquirer (Obs.=62)
Mean 0.1012 0.1035 0.1010 0.1062 0.1011 0.1034
Median 0.0638 0.0673 0.0609 0.0611 0.0658 0.0673
P-value for t-test on larger listed
cumulative abnormal returns. 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
Wilcoxon Signed Rank Test 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
Panel D: Difference between listed and unlisted acquirer
Mean Difference 0.1024 0.1160 0.1034 0.1133 0.0999 0.1172
Median Difference 0.1152 0.1251 0.1192 0.1266 0.1167 0.1228
P-value for t-test on larger listed
cumulative abnormal returns. 0.0011 0.0005 0.0009 0.0007 0.0010 0.0004
Table III
Summary statistics on ownership concentration, target firm performance and the control variables for listed and unlisted acquirers. The sample includes all completed cash acquisitions of listed targets by listed and unlisted acquirers announced between 01/01/2000 and 12/31/2011. It includes only acquisitions in which at least 50% of the ownership is acquired. The table reports mean and median values for the ownership concentration, target firm performance and control variables. The mean and median differences for the variables between both types of acquirers are tested by the t-test and the Mann-Whitney test, respectively. Prob. indicates the significance of the difference. ‘OCA’ is the ownership concentration of the acquirer; ‘OCT’ is the concentration of ownership of target firm; ’LNS’ is the natural log of the target net sales; ‘ROE’ is the target return on equity; ‘GRS’ is the 3-year annually compounded growth in net sales; ‘HOR’ is a dummy variable equal to 1 if the target and the acquirer are in the same industry, and else 0; ‘DOM ’is a dummy variable equal to 1 for domestic deals and 0 for cross-border deals; ‘STA’ is the stake acquired by the acquirer after completion of the acquisition. ‘NA’ presents value is not available. Differences denoted by * are significant at the 5% level.
Listed acquirer Unlisted acquirer
Mean Median Mean Median Mean dif. Prob. Median dif. Prob.
Table IV:
Regression results of ownership concentration, target firm performance and the control variables on the premium paid by listed acquirers. The sample includes all completed cash acquisitions of listed targets by listed acquirers between 01/01/2000 and 12/31/2011. It includes only acquisitions in which at least 50% of the ownership is acquired. This table presents estimations of the following two regression equations:
MAR5i = αi + β1OCAi + β2OCTi + β3HORi + β4DOMi + β5STAi + ei (1)
MAR5i = αi + β1OCAi + β2OCTi + β3LNSi + β4ROEi + β5GRSi + β5HORi + β6DOMi + β7STAi + ei (2)
In which ‘MAR5’ is the 5-day cumulative market and risk adjusted return; ‘OCA’ is the ownership concentration of the acquirer; ‘OCT’ is the concentration of ownership of target firm; ‘LNS’ is the natural log of the target net sales; ‘ROE’ is the target return on equity; ‘GRS’ is the 3-year annually compounded growth in net sales; ‘HOR’ is a dummy variable equal to 1 if the target and the acquirer are in the same industry, and else 0; ‘DOM’ is a dummy variable equal to 1 for domestic deals and 0 for cross-border deals; ‘STA’ is the stake acquired by the acquirer after completion of the acquisition; Constant is the intercept of the regression equation; Obs. is the number of observations for which all information is available; Adj. R2is the adjusted coefficient of determination;
F-statistic is the test F-statistic from the F-test; Prob. indicates the significance of the model;’ VIF’ is the average variance inflation factor of the independent variables of the regression. The expected sign is the coefficient expected sign of the independent variable. (1) and (2) indicate the coefficient of the variable in the regression equation. (SE) indicates the White hetereoskedasticity-consistent standard errors. Coefficients denoted by * are significant at the 5% level.
Variable Expected Sign (1) (SE) (2) (SE)
Ownership concentration
OCA - -0.277* (0.078) -0.316* (0.094)
OCT + -0.018 (0.095) -0.054 (0.109
Target firm performance
Table V:
Regression results of ownership concentration, target firm performance and the control variables on the premium paid by unlisted acquirers. The sample includes all completed cash acquisitions of listed targets by unlisted acquirers between 01/01/2000 and 12/31/2011. It includes only acquisitions in which at least 50% of the ownership is acquired. This table presents estimations of the following two regression equations:
MAR5i = αi + β1OCTi + β2HORi + β3DOMi + β4STAi + ei (3)
MAR5i = αi + β1OCTi + β2LNSi + β3ROEi + β4GRSi + β5HORi + β6DOMi + β7STAi + ei (4)
In which ‘MAR5’ is the 5-day cumulative market and risk adjusted return; Since unlisted firms do not disclose publicly financial information ‘OCA’ is not presented; ‘OCT’ is the concentration of ownership of target firm; ‘LNS’ is the natural log of the target net sales; ‘ROE’ is the target return on equity; ‘GRS’ is the 3-year annually compounded growth in net sales; ‘HOR’ is a dummy variable equal to 1 if the target and the acquirer are in the same industry, and else 0; ‘DOM’ is a dummy variable equal to 1 for domestic deals and 0 for cross-border deals; ‘STA’ is the stake acquired by the acquirer after completion of the acquisition; Constant is the intercept of the regression equation; Obs. is the number of observations for which all information is available; Adj. R2is the
adjusted coefficient of determination; F-statistic is the test statistic from the F-test; Prob. indicates the significance of the model; ‘VIF’ is the average variance inflation factor of the independent variables of the regression. The expected sign is the coefficient expected sign of the independent variable. (3) and (4) indicate the coefficient of the variable in the regression equation. (SE) indicates the White hetereoskedasticity-consistent standard errors. Coefficients denoted by * are significant at the 5% level.
Variable Expected Sign (3) (SE) (4) (SE)
Ownership concentration OCA
OCT + -0.115 (0.082) -0.043 (0.057)
Target firm performance
Table VI:
Regression results of type of acquirer, target firm performance and the control variables on the premium paid.
The sample includes all completed cash acquisitions of listed targets by listed and unlisted acquirers between 01/01/2000 and 12/31/2011. It includes only acquisitions in which at least 50% of the ownership is acquired. This table presents the estimation of the following regression equation:
MAR5i = αi + β1UNLi + β8HORi + β9DOMi + β10STAi + ei (5)
MAR5i = αi + β1UNLi + β2LNSi + β3DLNSi + β4ROE + β6DROEi + β6GRS + β7DGRSi +β8HORi + β9DOMi + β10STAi + ei (6)
In which ‘MAR5’ is the 5-day cumulative market and risk adjusted return; ‘UNL’ is a dummy variable equal to 1 for unlisted acquirers and 0 for listed acquirers; LNS is the natural log of the target net sales; ‘DLNS’ is the dummy ‘UNL’ multiplied by the natural log of net sales; ‘ROE’ is the target return on equity; ‘DROE’ is the dummy variable ‘UNL’ multiplied by ‘ROE’. ‘GRS’ is the 3-year annually compounded growth in net sales; ‘DGRS’ is the dummy ‘UNL’ multiplied by ‘GRS’; ‘HOR’ is a dummy variable equal to 1 if the target and the acquirer are in the same industry, and else 0; ‘DOM’ is a dummy variable equal to 1 for domestic deals and 0 for cross-border deals; ‘STA’ is the stake acquired by the acquirer after completion of the acquisition; Constant is the intercept of the regression equation; Obs. is the number of observations for which all information is available; Adj. R2is the adjusted coefficient of determination; F-statistic is the test statistic from the F-test; Prob. indicates the significance of the model; VIF is the average variance inflation factor of the independent variables of the regression. The expected sign is the coefficient expected sign of the independent variable. (5) and (6) indicate the coefficient of the variable in the regression equation. (SE) indicates the White hetereoskedasticity-consistent standard errors. Coefficients denoted by * are significant at the 5% level.
Variable Expected Sign (5) (SE) (6) (SE)
Type of acquirer
UNL - -9.440* (3.415) -28.532 (20.730)
Target firm performance
References
Alexandridis, G., Petmezas, D., & Travlos, N. G. (2010). Gains from mergers and acquisitions around the world: New evidence. Financial Management, 39(4), 1671-1695.
Amihud, Y., & Lev, B. (1981). Risk reduction as a managerial motive for conglomerate mergers,
Bell Journal of Economics, 12, 605-617.
Amihud, Y., Lev, B., & Travlos, N. G. (1990), Corporate control and the choice of investment financing: The case of corporate acquisition. Journal of Finance, 45, 603-617.
Andrade, G., Mitchell, M., & Stafford, E. (2005). New evidence and perspectives on mergers.
Journal of Economic Perspectives, 15(2), 103-120.
Bargeron, L. L., Schlingemann, F. P., Stulz, R. M., & Zutter, C. J. (2008). Why do private acquirers pay so little compared to public acquirers? Journal of Financial Economics, 89(3), 375-390. Bebchuk, L. A., & Fried J. M. (2003). Executive Compensation as an Agency Problem. Journal of
Economic Perspectives, 17: 71–92
Ben-Amar, W., & André, P. (2006). Separation of Ownership from Control and Acquiring Firm Performance: The Case of Family Ownership in Canada. Journal of Business Finance and
Accounting, 33(3), 517-43.
Berkovitch, E., & Narayanan, M. P. (1993). Motives for takeovers: An empirical investigation.
Journal of Financial & Quantitative Analysis, 28(3), 347-362.
Brown, S. J., & Warner, J. B. (1980). Measuring security price performance. Journal of Financial
Economics, 8(3), 205-258.
Brown, S. J., & Warner, J. B. (1985). Using daily stock returns: The case of event studies. Journal
of Financial Economics, 14(1), 3-31.
Campa, J. M., & Hernando, I. (2004). Shareholder value creation in European M&As. European
Financial Management, 10(1), 47-81.
Chang, S. (1998). Takeovers of privately held targets, methods of payment, and bidder returns.
Journal of Finance, 53(2), 773-784.
Chrisman, J. J., Chua J. H., & Litz, R.A., (2004). Comparing the agency cost of family and non-family firms. Entrepreneurship Theory and Practice, 28(4), 335-354
Cosh, A., Guest, P.M., & Hughes, A., (2006). Board share ownership and takeover performance. Journal
of Business Finance & Accounting, 33, 459-510.
Demsetz, H. (1983), The structure of ownership and the theory of the firm, Journal of Law
and Economics, 26, 375-390.
Faccio, M., & Lang, L. H. P. (2008). The ultimate ownership of western European corporations. In R. A. I. van Frederikslust, J. S. Ang & P. S. Sudarsanam (Eds.), Corporate governance and
corporate finance: A European perspective, 163-190. London and New York: Taylor and Francis,
Routledge.
Faccio, M., & Masulis, R. W. (2005). The choice of payment method in European mergers and acquisitions. Journal of Finance, 60(3), 1345-1388.
Faccio, M., McConnell, J. J., & Stolin, D. (2006). Returns to acquirers of listed and unlisted targets.
Journal of Financial & Quantitative Analysis, 41(1), 197-220.
Fatemi, A. M., & Furtado, E. P. H. (1988). An empirical investigation of the wealth effects of foreign acquisitions. In S. J. Khoury, & A. Ghosh (Eds.), Recent developments in international
banking and finance, volume 2, (pp. 363-379) Lexington, Mass. and Toronto:; Heath,
Lexington Books.
Firth, M. (1991). Corporate takeovers, stockholder returns and executive rewards. Managerial and
