Performance comparison of domestic mergers and acquisitions in the public sector, US evidence

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Performance comparison of domestic mergers and

acquisitions in the public sector, US evidence

Student: J.J.J.(Joost) Nijwening

Coach: Dr. W.Bessler

Co-reader: Dr. J.J. Bosma

Msc Finance

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1 Abstract

This thesis focuses on the evidence of the influence of industry factors, deal specific factors and firm specific factors on the performance of both the acquiring firm and the target firm. Most research focuses on either the bidder or the target, and this study includes both the effects of these factors on the acquirer and the target. This research a data sample of 282 mergers and acquisitions undertaken by publicly traded US-based firms between January 1st of 2012 and January 1st 2019. Evidence shows that for the acquirer M&A does not add to the shareholder value, however for the target firm M&A does add to the shareholder value. It is noted that the added value consist of largely the premium paid by the acquirer. Most important finding is that for both acquirer and target cash financed transaction ad to the shareholders value. Also I find evidence of the influence of the premium paid, corporate income tax, deal size and market capitalization of the acquirer show to influence the shareholder value of either the acquirer or target.

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List of Tables

1 Summary of variables analysed . . . 19

2 Distribution of transactions . . . 21

3 Time period distribution transactions . . . 22

4 Descriptive data . . . 22

5 Bidder event window cumulative abnormal returns . . . 25

6 Target event window cumulative abnormal returns . . . 25

7 Cross-sectional regression results: Bidder Part 1 . . . 29

8 Cross-sectional regression results: Bidder Part 2 . . . 31

9 Regression results: Bidder . . . 32

10 Cross-sectional regression results: Target Part 1 . . . 35

11 Cross-sectional regression results: Target Part 2 . . . 37

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2 Introduction

There are different reasons why firms engage in mergers and acquisitions (M&A). Reasons could be to increase sales and the market share, a diversification of the firm’s portfolio, synergies and vertical integration of the supply chain. The M&A market surged upwards during the period 2012-2015 with a increase of 81% in total transaction value. After these exceptional years the M&A market slowed down and only climbed up again in 2018. The total number of deals and deal value decreased in 2019 after an exceptional year in 2018 (Bureau van Dijk, 2020), see figure 1 and 2. Not every merger or acquisition results in a subsequent success, leading to the question, which factors influence and determine the success of a merger or acquisition? There has been significant research on the topic of determining the factors that influence the success of a deal. Most research analyzes the effects of deal type and company specific trends (Epstein, 2005). 2012 2013 2014 2015 2016 2017 2018 2019 4 5 6 ·10 6 Year D ea l V al u e (m il U S D )

Figure 1: Global deal Value (Aggregate)

Deal Value 2012 2013 2014 2015 2016 2017 2018 2019 90 100 110 120 Year D ea l V ol u m e (x 10 00 )

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The objective of this study is to investigate for the United States (U.S.) the effect of executed M&A transactions on the performance of the bidder and target. The sample used in this research consists of 299 transactions where both the bidder and target are U.S. based firms. In this research, the performance of bidder and target is measured as the abnormal return of the firm’s stock price during a certain period. Both cumulative abnormal return (CAR) and buy-and-hold abnormal returns (BHAR) are calculated, depending on the length of the time period used. There are several industry, deal and firm specific factors, which influence the performance of each transaction. Consequently, a number of factors are considered in this research, such as the payment method, industry and state diversification, premium paid, deal size, control and market value of the acquiring firm. The objective of this study is to determine the influence of each particular factor on the performance of both the acquiring (bidder) and acquired firm (target). In particular, the differentiation between the effects on the bidder’s and target’s shareholder value is analyzed in order to examine the different influence of these factors on the acquiring and acquired firm.

The empirical results shows that M&A do not create value for the acquirer, however do generate value for the target shareholders. Besides that, cash paid transactions significantly outperform stock financed transactions with respect to both the acquirer and target shareholder value.

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3 Literature review

In the next part, the literature is discussed to provide the basic ideas of this study. By discussing the literature, the mean research question and hypotheses are formulated that are examined in this study.

3.1 Value creation by merger and acquisitions

Why do firms engage in mergers or acquisitions? In a rational world, it can be expected that a manager will only engage in a M&A if it adds value to the firm. Maximizing shareholder value should in general be the most important target of a firm’s manager. The aim to maximize shareholder value should be one of the most important drivers behind the decision making of a manager. This idea is supported by Hansmann and Kraakman (2001). Therefore, if managers are assumed to act rational, they will not engage in a M&A if this transaction does not add value to the firm. However, it cannot be assumed that every man-ager acts in a rational way. Reasons are, the overestimation of success or other biases such as overestimation of control and overconfidence (Van den Steen, 2004). Hwanga et al. (2020) links power-led CEO overconfidence to undesirable outcomes of implemented investments also, acquirer shareholders react less fa-vorably to a takeover announcement when the target CEO is more narcissistic (Aktas et al., 2016). Other literature, which examines the drivers behind failed M&As link poor communication, valuation issues, payment issues, due diligence and post-integration phase issues like integration failure and cultural clashes to the phenomena of failing M&As (Kumar and Sharma, 2019). Besides, these factors are not the only factor behind failing or under performing M&As. The failure or under performance can also be attributed to factors which are outside the influence of a firm’s manager, such as financial recessions, natural disasters and other general risks such as currency risks and technological changes.

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firm. When comparing most relevant studies on target CAR it is found that the CAR is positive in most cases even despite variations in time period, type of the deal, industries involved and the observation period (Campa and Her-nando, 2004). These observations are in line with previous literature on this topic. Jensen and Ruback (1983); Datta et al. (1992); Bruner (2002) concluded that there is a significant positive CAR for target firms and furthermore that there is no significant positive CAR for the bidder firm. A study purely focused on the targets performance found a significant positive abnormal return, for a 11 days window around announcement date, of 10.55% (Zhou and Atallah, 2017). Other research found that bidders experience a significant short-term wealth destruction surrounding M&A announcement date, however they find positive and significant wealth effects in the long-run. One conclusion form this research is that target shareholders are demanding all (Boubaker and Hamza, 2014). From this literature, we can conclude that most studies find that value is created for the target’s shareholders but the effect of M&A on the bidders shareholder value is still ambiguous.

Adding to the literature examining the CAR for the bidder firm presented before, other literature show the difference relative to the target firm. In a study examining 281 transactions from US firms, a negative relation is found for the bidder’s CAR (Mulherin and Boone, 2000). This conclusion is supported by other studies which examine samples with transactions mainly done by US originating firms (Mitchell and Stafford, 2000; Walker, 2000). These studies find a negative value for the CAR related to the bidder, with CARs ranging between -0,84% and -0,07%. Other research shows a more positive valuation effect (CAR) around the announcement date of the acquisitions. Using data including US transactions for the period 1987–1996 and data including UK transactions during the period 1994-1998, there are positive CARs found for the bidder’s share value (Kohers and Kohers, 2000; Rai and Forsyth, 2002). On average, it can be concluded that the impact of mergers and acquisitions on the CAR for the acquiring company is basically zero. Bidder shareholders only benefit when the later on realized synergies are higher than the expected synergies. However this does not mean that they do not create value in the long run.

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the acquiring firm (Bessler and Schneck, 2015). This outcome is in line with the earlier mentioned fact that the target has, in general, a positive AR when engaging in M&A. In the long-run, the share price of the acquiring firm could still increase despite the fact that around announcement date the share price decreased or stabilized. This positive share price reaction could indicate that the management, which is undertaking the transactions, has information about synergies and other advantages which the market is not aware of.

To conclude this part, the review of the literature shows a positive AR for the target. However, for the acquiring firm the CAR is basically zero, this means that the market does not perceive the transaction as a positive net present value transaction. In general M&As do not create value for the bidder firm and are highly risky (Malmendier et al., 2018). There are two options when the market assesses the transaction as a negative present value action. The transaction is in fact a transaction, which will harm the shareholder value, or information asymmetry is present between management and the market. This last option is associated with an increase in share price in the long-run. In order to test this for our sample two hypotheses are formulated:

Research question: Do mergers and acquisitions have a negative effect on the performance of the bidder firm and a positive effect on the performance of the target firm?

In the upcoming parts of this paper, several hypotheses will be formulated in order to investigate the rationales behind the performance of M&A.

3.2 Determinants of value creation

3.2.1 Industry factor

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et al., 1997; Tanriverdi and Venkatraman, 2005). The ability of a company to generate a competitive advantage by diversifying M&A depends on the industry in which the company operates (Kotabe et al., 2017).

Despite all possible advantages there are also costs related to firm’s diversifi-cation strategy. There is significant amount of literature on this topic. However, not every argument is taken as fact. Research relates agency costs to the di-versification question (Denis et al., 1997), which is contracted by other research on this topic saying that agency costs cause a firm to diversify (Hyland, 1999). Further research relate inefficient allocation of capital among divisions to a di-versified firm (Stulz, 1990; Lamont, 1997; Rajan et al., 2000; Ng et al., 2019), difficulty of designing correct incentive compensation for managers also gener-ates costs of diversified operations (Aron, 1988; Rotemberg and Saloner, 1994) and information asymmetries arise between management and managers which increases costs (Harris et al., 1982; Vasilescu and Millo, 2016). However, there are several positive and negative sides on diversification, research shows a neg-ative relation between bidder’s returns and an increase in global diversification (Moeller and Schlingemann, 2005). This is supported by other research, which suggests that returns to the bidder’s shareholder are lower when their firm diver-sifies (Morck et al., 1990). Research that relates diversification with the long-run performance, three years post transaction, of a acquiring firm finds that in cer-tain sectors specialization transactions outperform diversification transactions. Giannopoulos et al. (2017) do find positive outcomes for bidder firms acting in the financial service sector when they engage in diversifying transactions.

As it shows, diversification of a particular firm has significant effect on the performance of that firm (shareholder value). More recent literature, Kotabe et al. (2017); Giannopoulos et al. (2017) find that for some specific industries diversification does add value, however the effects are industry specific. Due to this somewhat inconclusive outcome in the literature the following hypothesis is constructed in order to come up with a conclusive outcome for this research: Hypothesis I: If diversification is the bidder’s only objective for the merger and acquisition, the performance of the acquiring firm is usually negative or at least not positive.

3.2.2 Deal specific factors

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desired target. However, the ability of the target firms’ manager to predict the positive advantages and disadvantages correctly is not perfect. Thus, the premium paid in M&A could be to high relative to the real potential of the target company. The premium paid in M&As is linked to asymmetric infor-mation, possibility of value creation, principal-agent issues and overconfident managers (Zhang, 2019). More often than not acquirers pay enormous amounts to acquire a target. Betton et al. (2008) find that for transactions in the period from 1980 to 2002 the average premium paid was 48% of the market value of the target company with some transactions exceeding the 100%. Even though premiums tend to be substantial, Dionne et al. (2015) find that blockholders pay a substantial lower premium than other buyers do. They contribute this to the idea that blockbusters are better informed about the target than the other buyers. This would indicate that premiums will decrease when the information asymmetry decreases between the acquirer and target. Building on this idea the following hypothesis is formulated:

Hypothesis II: The premium paid in mergers and acquisitions is negatively related to the performance of the acquiring firm

Using a sample of 3,691 transactions during the period from 1990 until 2007 Alexandridis et al. (2013) found that large transactions result in more severe wealth destruction for acquiring shareholders as well as sharper increases in acquirer return uncertainty around the announcement date of the transaction. However, a new study using a sample of transactions from 1990 until 2015 from Alexandridis et al. (2016) found that large transaction are viewed more positively by the market during the period of 2010 until 2015. Other, more recent studies, which only take into account mega-deals, deals valued higher than $500 mil, found that mega-deals end up destroying shareholders value (Hua et al., 2020). The next hypothesis is constructed in order to test this factor in this study:

Hypothesis III: The deal size of a merger or acquisition and relative values is negatively related to the performance of the acquiring firm

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(Baker and Wurgler, 2002) and in the form of the “agency costs of overval-ued equity” hypothesis, which shows that managerial discipline may be eroded by the availability of cheap financing in the form of overvalued stock. These agency costs could imply that managers persue investments which are not op-timal (Jensen, 2005). More recent literature indicates that stock payment is used in order to decrease the possibility to overpay, however stock financed transactions are also associated with a lower possibility of completion (Huanga et al., 2016). Information asymmetries, signaling and agency effects cause all-cash M&A to outperform stock paid M&A according to more recent research (Bessler and Westerman, 2020) All together it is clear that the payment method has a significant influence on the performance of M&A, in order to test the in-fluence in this study the following hypothesis is formulated:

Hypothesis IV: All cash financed mergers and acquisitions have higher bid-der and target shareholbid-der return than stock-financed mergers and acquisitions

The percentage acquired by the bidder company is an other factor which should be incorporated in this study.Yilmaz and Tanyeri (2016) show that the transfer of control rights during an M&A, increase the CAR during the 3-day window around announcement day for both the bidder and target. Although more specific literature on this factor merely exists one could hypothesis that gaining the control over your target could incentives to pay a higher premium for that target. Gaining full control enables the acquiring firm to implement their way of work on to their acquiring target. When one acquires a significant smaller proportion of the targets shares the level of control decreases and so does the ability to influence specific outcomes. So in this research we assume that transactions which acquired 100%, or close to full control, of the targets shares will have a higher premium then transactions which have a significant smaller proportion.

Firms do not only diversify between sectors in which they are operating. Geographically diversified firms seem to have a higher degree of information asymmetry within the firm (Vasilescu and Millo, 2016). Global diversification has already been linked to lower bidders return (Moeller and Schlingemann, 2005) Due to the size of the U.S. itself and the states which make up the U.S. this study also includes a dummy variable for state diversification.

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manage-ment openly refuses the transaction. Therefore, hostile takeovers often include a higher premium then deals with a friendly attitude in order to pressure the target’s management to accept the offer. Due to previous mentioned points on control and deal attitude, this study only includes transactions in which the acquiring company has a post transaction share of more than fifty percent and transactions with a friendly deal attitude.

3.2.3 Firm specific factor

By examining 12,023 acquisitions by public firms during the period from 1980 until 2001, Moeller et al. (2004) find that shareholders return is two percent points higher for smaller acquirers regardless of the way of financing and whether the acquired firm is public or private. In this study, small (large) acquirers are defined as having a market capitalization equal to or less (greater) than the market capitalization of the 25th percentile of NYSE firms in the same year. They find a weighted AR on the announcement day of 1.1% in general. However, also find that the shareholders of the acquiring firm lose on average $25.2 million upon announcement of the transaction.

Hypothesis V: Firm size of the acquiring firm is negatively related to the performance of the acquiring firm

3.2.4 Investment climate

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firms have more resources to spend when the CIT decreases. This gives a firm more financial freedom, which could increase the amount spend on mergers and acquisitions. As already mentioned before, Alexandridis et al. (2013) showed that large transactions cause more severe wealth destruction for the acquiring firm than smaller transactions. This could implicate that lower CIT could not have a negative influence an the acquiring firm’s shareholders value.

Since the sample of this study only consists of transactions between US firms some of the factors which influence the investment climate do not differ per transactions. Since tax-related issues make up a significant part of the factors behind the investment climate, (Bastos and Nasir, 2004), this study takes into account the change in legislation in 2018. On January first, 2018 the Tax Cuts and Jobs Act come in place which, besides other changes, decreased the CIT from 35% to only 21%. In order to test the significance of this regulatory change the following hypothesis is formulated:

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4 Methodology

In this chapter, the methodology used to test to the previously stated hypothe-ses. First, I will conduct an event study to identify the abnormal return to the stock prices around the announcement date and a one-year time period post acquisition date of the transactions. Next, the model used for the ordinary-least-squares regression will be outlined and discussed.

4.1 Event study

In order to investigate the effect of the included variables on the shareholder value when engaging in domestic M&A I use the event study methodology de-scribed by Brown and Warner (1985). Event study methodology is a commonly used method to analyze stock prices around announcement dates of M&A. This event study methodology is used in various research such as in previous research from Dutta et al. (2013) and Moeller and Schlingemann (2005).

The event study methodology is a commonly used method for estimating shareholder return around announcement date of completed transactions. Some studies focus on a small window around the announcement date, on the share-holders value analysing the CAR (Moeller et al., 2004; Fuller et al., 2002; Mar-tynova and Renneboog, 2006) or CAAR (Adnan and Hossain, 2016; Shah and Arora, 2014). Other studies studies focus on the long term effect of value cre-ation by the buy-and-hold abnormal returns, BHAR, (Chakrabarti et al., 2008; Loughran and Vijh, 1997) or a combination of both CAR and BHAR (Savor and Lu, 2009; Bessler and Schneck, 2015).

4.1.1 Estimation window

In this research I use for the short run an event window of three and 10 trading days, respectively [t−1; t1] and [t−11; t−2], around announcement day. For these

shorter periods the CAR will be used in order to calculate the stock return, which I further explained in subsection 3.1.2. These two periods enables the opportunity to distinguish between the run-up and mark-up of each transaction. In order to check for robustness in the results I will also use a twenty trading day window around the announcement date of the transaction, [t−10; t10], for

the ten day period the BHAR will be used which will also be further explained in subsection 3.1.2.

Other periods used in this study are [t₋250; t

−2] and [t2; t250], in order to

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An important reason for using different windows is that information about the transaction, which would normally not be publicly known could be leaked and influence the stock prices around the announcement date.

4.1.2 Abnormal returns

The abnormal return of a stock is calculated by subtracting the expected market return of stock i, (E[Ri,t]) from the actual stock return of stock i, (Ri,t). This

is shown in the following equation:

ARi,t= Ri,t− (E[Ri,t]) (1)

In order to capture to total gain in shareholder value for the acquiring firm around the announcement date we use the CAR. The CAR is calculated by adding up the ARs of the stock within the used period. This is defined as follows: CARP = ta X tb ARi,t (2)

To calculate the returns for longer periods than one day around the announce-ment date I estimate the BHAR:

BHARP = ta a tb 1 + Ri,t ! − ta a tb 1 + (E[Ri,t]) ! (3)

4.2 Regression model

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Before engaging in the build-up of the regression model, which used in this study, it is noted that only transactions are used in which the bidder acquired more than 50% of the total shares and there was a friendly deal attitude. First the base model, which will be expanded in the upcoming parts, is formulated:

CARP= α0+ β1Contr+ β2State+ εi

BHARP= α0+ β1Contr+ β2State+ εi

(Base model)

Contr shows the percentage of shares acquired by the bidder and State is a dummy variable, which takes on the value one when the acquirer and target have the main operation in the same state, and zero if they do not.

4.2.1 Industry factors

In order to test the first hypothesis the dummy variable Div is added to the base model, which results in the following first model:

CARP= α0+ β1Contr+ β2State+ β3Div+ εi

BHARP= α0+ β1Contr+ β2State+ β3Div+ εi

(Model 1)

The dummy variable Div takes on the value one when the acquirer and tar-get both operate in the same main industry, and zero if they do not operate in the same main industry. All companies are divided between ten main industries, Technology, Basic Materials, Telecommunications Services, Healthcare, Energy, Consumer Cyclicals, Industrials, Financials, Consumer Non-Cyclicals and Util-ities.

4.2.2 Deal specific factors

To investigate the hypotheses two, three, four and five we introduce the variables Prem, log(Size), Cash and Log(MC) to model 1:

CARP = α0+ β1Contr+ β2State+ β3Div

+β4P rem+ β5log(Size) + β6Cash+ β7Log(M C) + εi

BHARP = α0+ β1Contr+ β2State+ β3Div

+β4P rem+ β5log(Size) + β6Cash+ β7Log(M C) + εi

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Prem is the premium paid in by the acquirer, this number shows the premium paid as a percentage of the target stock price one day prior to the transaction. Log(Size) is the natural logarithm of the deal size, in millions, of the transaction. The variable Cash is a dummy variable showing whether a transaction is cash only or not, taking the value one when the transaction is cash only and zero if not. The variable Log(MC) shows the market capitalization, in millions, of the acquiring firm on the announcement date.

4.2.3 Investment climate factors

In order to test the sixth hypothesis the variable CIT is added to the previous model:

CARP= α0+ β1Contr+ β2State+ β3Div

+β4P rem+ β5log(Size) + β6Cash+ β7Log(M C) + β8CIT + εi

BHARP= α0+ β1Contr+ β2State+ β3Div

+β4P rem+ β5log(Size) + β6Cash+ β7Log(M C) + β8CIT + εi

(Model 3)

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Table 1: Summary of variables analysed

Variable Sign Explanation Source Stock return R 500 days around

an-nouncement date of bidder and acquirer

Thomson Reuters Eikon

Wilshire 5000 total stock market idex

E(R) 500 days around an-nouncement

Industry Diversifica-tion

Div Main operating indus-try

Premium Prem Premium paid as per-centage of stock price

Deal size Log(Size) Deal size of transaction Thomson Reuters Eikon

Payment method Cash Dummy variable for payment method, ei-ther cash or different

State diversification State Dummy variable for differences between op-erating state acquirer and bidder

Market Capitalization of bidder

Log(MC) Market capitalization of acquirer

Orbis by BvD Corporate income tax CIT Corporate income tax

at the moment of an-nouncement

www.cia.gov

5 Data

In this section, I will discuss the data used in this study. First, I will describe the construction of the data. Secondly, I will discuss the source of the data and the construction of certain variables.

5.1 Sample construction

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advanced economies (Chena et al., 2016). Also, financial constrains during the recession period caused firms to be in able to borrow externally and cause firms to bypass attractive investment opportunities (Campello et al., 2010). As a re-sult of these differences in financial opportunities post 2008 financial crisis, this study focuses on transactions announced post 1 January 2012. The end date is chosen due to the fact that a time period of 250 trading days post transaction is needed.

The sample is has several restrictions. Banks and financial services compa-nies are excluded in this sample. Also this study focuses on transactions which show a change of control, due to this only transactions are included in which the acquiring firms acquires more than 50%. Besides these two restrictions only transactions which shown to have a friendly deal attitude are included. After these first restrictions, the data is thoroughly cleaned by hand due to the fact that several key variables were not available for some transactions. In the end the sample consists of 282 deals.

In table 2 I provide a provide the geographical and industrial distribution of the sample size. As shown some states are significantly more represented in the sample with others having far less transactions. The industry distribution is more equally distributed with a slightly higher distribution towards health-care and technology. Technology includes companies active in the technology equipment, software and IT services. Table 2 also shows the distribution of diversification of state and industry. What can be noticed is that in the biggest parts of the transactions the acquirer and bidder do not originate from the same state, 74%, however do operate in the same main industry, 80%.

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Table 2: Distribution of transactions State # of ac-quirers # of targets Industry # of ac-quirers # of targets

Arizona 5 3 Basic Materials 13 13

California 51 68 Consumer

Cycli-cals

36 38

Colorado 3 7 Consumer

Non-Cyclicals 10 15 Connecticut 13 5 Energy 27 30 Florida 4 8 Healthcare 70 65 Georgia 7 8 Industrials 40 36 Illinois 18 10 Technology 66 66 Indiana 6 1 Telecom 10 9 Maryland 1 8 Utilities 10 10 Massachusetts 16 15 Total 282 282 Michigan 7 4

Minnesota 3 12 Diversification State Industry

Missouri 2 6 Yes 209 55

Nevada 6 4 No 73 227

New Jersey 19 10 Total 282 282

New York 21 19 North Carolina 6 8 Ohio 8 5 Oregon 0 5 Pennsylvania 10 9 Tennessee 8 3 Texas 29 33 Virginia 12 13 Washington 5 3 Other states1 22 15 Total 282 282 1

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Table 3: Time period distribution transactions Year # of transac-tions Year # of transac-tions 2012 37 2016 50 2013 26 2017 35 2014 34 2018 56 2015 44 Total 282

Table 4: Descriptive data

Variable Mean Std.Dev Min Max

Premium 35% 34% -37% 237%

Log deal size 7,13 1,71 2,92 11,33

Payment method 0,78 0,42 0 1

Log market cap. 8,11 2,13 1,44 12,83

CIT 32,22 5,59 21 35

Stake 98,41 7,02 52,94 100

Industry div. 0,80 0,40 0 1

State div. 0,26 0,44 0 1

Number of observations, N, for all variables is equal to 282.

5.2 Descriptive data

In previous tables the data used in this study is described. In this part the de-scriptive data will be more thoroughly explained. In order to better understand the sample used the descriptive data is being discussed.

2012 2013 2014 2015 2016 2017 2018 2 4 ·10 5 Year D ea l V al u e (m il U S D )

Figure 3: Deal Value (Aggregate)

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2012 2013 2014 2015 2016 2017 2018 20 40 60 Year D ea l V ol u m e

Figure 4: Deal Volume (Aggregate) Deal Volume

Figure 3 and 4 show the development of M&A in the sample used, the aggregate value in millions per year in figure 3 and the M&A volume per year in figure 4, which is the number of transactions per year. The data shows resemblance with the report published by Bureau van Dijk (2020), data showed a decline in deal value in the years 2016 and 2017 compared to previous years. This is also shown in the data used for this study. Total deal volume per year of the data used shows a different trend compared with the Bureau van Dijk (2020) report. From 2015 to 2016 the data used in this study shows an increase in volume and a decrease from 2017 relative to 2016. This compared to the decrease in volume from 2015 to 2016 and another decrease in volume from 2016 to 2017, which is reported by Bureau van Dijk (2020). As shown in figure 3 and 4, and table 4 previously, the range of deal size is significantly large, that it makes more sense to use the natural logarithm of deal size, which value is shown in table 4.

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2012 2013 2014 2015 2016 2017 2018 2 4 ·10 4 Year M ar ke t C ap . (m )

Figure 5: Market Capitalization (Average) Market Cap.

In figure 5 the average market capitalization of the acquiring firm is shown for each of the years included in the study. Comparing figure 1 and figure 3 is shows that in the years 2016 and 2017, when total deal value per month was significant lower than in the year 2015 the average market capitalization from acquiring firms increased with a peak in the year 2016. This indicates that in this sample the total deal value decreases. however larger companies where relatively more active in M&A. Combining these two observations it can be concluded that the average deal size drops significantly in 2016 compared to preceding years. This shows that larger companies were acquiring ,relative to previous years, smaller targets. Adding to that, the increase in total deal value and volume is accompanied with a decrease in market capitalization of the acquiring firm. In contrast to the year 2016, in 2018 relatively smaller acquirers were doing more deals in both value and total numbers.

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excludes in some extend control differences and potentially agency problems. The last variable is the CIT which changed in the US at the start of 2018, only transactions from 2018 onward have a CIT of 21%, the average CIT in the study is 32,2%, which are 56 of the 282 transactions.

Table 5: Bidder event window cumulative abnormal returns

Variable N Mean Std.Dev Min Max

CAR_{(−1, +1)} 282 -0.67% 0,49% -36,01% 23,12% CAR(−11, −1) 282 -0,36% 0,32% -18,80% 22,15% BHAR(−10, +10) 282 -1.52%** 0,10% -47,44% 41,56% BHAR_{(−250, −2)} 282 4.76%** 0,26% -83,14% 165,84% BHAR(+2, +250) 282 -5.43%*** 0,28% -95,56% 170,96% Number of observations N ∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1

Table 6: Target event window cumulative abnormal returns

Variable N Mean Std.Dev Min Max

CAR(−1, +1) 282 27,11%*** 1,64% -24,89% 175,15% CAR_{(−11, −1)} 282 3,25%*** 0,91% -39,08% 171,53% BHAR_{(−10, +10)} 157 29,19%*** 3,85% -16,66% 530,73% BHAR(−250, −2) 282 3,62% 3,42 -97,86% 446,94% BHAR(+2, +250) 29 -7,98% 5,43% -68,65% 44,63% Number of observations N ∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1

5.3 Abnormal returns

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−30 −20 −10 0 10 20 30 −2

−1 0 1

Days around announcement date

C u m u la ti ve A b n or m al R et u rn (% )

Figure 6: Cumulative Abnormal Return Bidder CAR

A negative abnormal return is found during the periods [t₋1; t1] , [t

−11; t−2],

[t−10; t10] and [t2; t250] for the acquiring firm, which is shown in table 5, this is

also observable in figure 6, showing a decrease in the CAR during these periods. This is in line with recent research by Malmendier et al. (2018) who found that M&As do not in general generate value, post transaction, for the acquiring firm. In contrast to the previous mentioned periods the [t−250; t−2] period shows a

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−30 −20 −10 0 10 20 30 0 10 20 30 40

Days around announcement date

C u m u la ti ve A b n or m al R et u rn (% )

Figure 7: Cumulative Abnormal Return Target CAR

For the target firm all period except the [t2; t250] period, shows a positive

abnormal return, shown in table 6. For the target it is interesting to have a look at the difference between the run-up and mark-up, respectively [t₋11; t

−2] and

[t−1; t1]. For both periods the abnormal return is positive, however the mark-up

is significantly higher than the run-up, respectively 27,11% and 3,25%. As noted before, there might be a case of information spillage prior to the announcement of the transaction. This positive abnormal return might be the reason of the positive abnormal return during the period [t−11; t−2], another reason might be

that acquirers are more interested in good performing targets. These values are in line with previous literature which suggests that M&A increases shareholder value for the target firm (Kohers and Kohers, 2000; Rai and Forsyth, 2002). The negative return during the [t2; t250] period is not hold against previous

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6 Empirical results

In this part, the results of the analysis are shown and discussed and hypotheses are being discussed. First, the regression results will be shown and discussed. This section ends with discussing the limitations of this study.

6.1 Regression analysis

In this section, the regression analyses regarding the effects of M&A on share-holder value are presented. In the first hypothesis I suggest that: ”If diversifica-tion is the bidder’s only objective for the merger or acquisidiversifica-tion, the performance of the acquiring firm is usually negative or at least not positive”. After this first hypothesis the effect of the premium paid is investigated, this is tested by hypothesis II that: ”The premium paid in mergers and acquisitions is negatively related to the performance of the acquiring firm”. Then the idea that ”The deal size of a merger or acquisition and relative values is negatively related to the performance of the acquiring firm” is tested by hypothesis III. Firms engaged in a cash paid transactions are expected to perform better firms engaged in a stock paid transaction (Bessler and Westerman, 2020). This is tested by hy-pothesising that: ”All cash financed mergers and acquisitions have higher bidder and target shareholder return than stock-financed mergers and acquisitions”. On firm level the effect of market size of the acquiring firm is negatively related to the capability of engaging in a successful M&A. To test this hypothesis V is formulated: ”Firm size of the acquiring firm is negatively related to the perfor-mance of the acquiring firm”. The final hypothesis formulated in this research addresses the investment climate of the firms included in the transaction. Due to the fact that this study only involves public firms originating from the US the investment climate does not differ in a significant way, as discussed in part 2.2.4. One important aspect of the investment climate has changed in the US, the CIT. To test the effect of this change in CIT I hypothesise that: ”Corporate income tax is positively related to the performance of the acquiring firm”. These relationship are examined by applying several cross-sectional regressions

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6.1.1 Bidder regression analysis

First, I start with the analysis of the effects on the performance of the acquiring firm. This will be done by examining the effects of the independent variables in a cross-sectional regression for the periods [-1,1] and [-10,10]. After that an attempt to understand the relative effects of the independent variables on the shareholder value is presented and discussed.

Table 7: Cross-sectional regression results: Bidder Part 1

Variable (1) CAR [-1,1] (2) CAR [-1,1] (3) CAR [-1,1] (4) CAR [-1,1] (5) CAR [-1,1] (6) CAR [-1,1] (7) CAR [-1,1] Percentage acquired 0,02 (0,07) 0,02 (0,07) 0,03 (0,07) 0,02 (0,07) 0,02 (0,07) 0,02 (0,07) -0,02 (0,07) State Div. -0,79 (1,14) -0,76 (1,15) -0,84 (1,14) -0,79 (1,14) -0,59 (1,17) -0,76 (1,15) -0.66 (1,11) Industry Div. 0,44 (1,26) Premium -1,89 (1,47) Deal size -0,08 (0,29) Payment method 0,91 (1,24) Market Cap. 0,09 (0,23) CIT 0,34 (0,09) Observations 282 282 282 282 282 282 282 R2 _0,0023 _0,0027 _0,0083 _0,0026 _0,0042 _0,0028 _0,0531

Standard errors are in parenthesis ∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1

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acquired which indicated that gaining more control through the acquisition of a higher percentage of shares positively influences shareholder value during the 3-day period. For the state diversification variable a negative sign is presented which is not in line with prior literature (Moeller and Schlingemann, 2005). This indicates that state diversifying results in a higher shareholder return in the 3-day period.

Compared to specification (1). Specification (2) introduces the dummy vari-able for industry diversification. (2) shows that industry diversifying acquirers have a -0,44% 3-day cumulative abnormal return compared to non-diversifying acquirers. This indicates that acquisitions which cause diversification across in-dustries add less value to the acquiring firm compared to non-diversifying M&A. Although the result is insignificant it is in line with Morck et al. (1990). However my result contradicts the findings of Chandler (1977); Stulz (1990); Tanriverdi and Venkatraman (2005). Even tough, diversification might lead to synergies it does not add value during the 3-day period surrounding the announcement. Despite the fact that the result is insignificant it is in line with my hypothesis II which states that: ”If diversification is the bidder’s only objective for the merger and acquisition, the performance of the acquiring firm is usually negative or at least not positive”.

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Table 8: Cross-sectional regression results: Bidder Part 2 Variable (1) BHAR [-10 ,10] (2) BHAR [-10 ,10] (3) BHAR [-10 ,10] (4) BHAR [-10 ,10] (5) BHAR [-10 ,10] (6) BHAR [-10 ,10] (7) BHAR [-10 ,10] Percentage acquired 0,09 (0,09) 0,10 (0,09) 0,12 (0,10) 0,09 (0,09) 0,07 (0,09) 0,08 (0,10) 0,05 (0,09) State Div. -1,93 (1,57) -1,88 (1,58) -2,02 (1,56) -1,94 (1,57) -0,87 (1,59) -1,73 (1,57) -1,79 (1,55) Industry Div. 0,70 (1,73) Premium -3,30 (2,01) Deal size 0,08 (0,40) Payment method 4,77*** (1,67) Market Cap. 0,49 (0,32) CIT 0,37*** (0,12) Observations 282 282 282 282 282 282 282 R2 _0,0102 _0,0108 _0,0197 _0,0103 _0,0383 _0,0183 _0,0420

Also in table 8, in line with the results from table 7, the control variables, percentage acquired and state diversification are despite being insignificant in line with prior literature. Furthermore, the sign does not change across specifi-cation (2)-(7).

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stock-financed mergers and acquisitions” and ”Corporate income tax is positively related to the performance of the acquiring firm”.

The other variables included in (2)-(3)-(4)-(6),respectively industry diversifi-cation, premium paid, deal size and the market capitalization of the acquirer do not have any significant influence on the shareholder value during the 10-period surrounding the announcement date for the acquiring firm.

Table 9: Regression results: Bidder

Variable (1) CAR [-1,1] (2) CAR [-11,-2] (3) BHAR [-10,10] (4) BHAR [-250,-2] (5) BHAR [2,250] Percentage acquired -0,01 (0,07) 0,08* (0,05) 0,04 (0,10) 0,54* (0,30) -0,047** (0,234) State Div. -0,45 (1,16) 0,66 (0,75) -0,64 (1,58) -9,73** (4,89) -6,30 (4,54) Industry Div. 0,56 (1,24) 0,35 (0,81) 0,92 (1,70) -5,07 (5,27) -0,15 (4,88) Premium -2,61* (1,48) -0,25 (0,96) -4,94** (2,02) 6,67 (6,28) 0,29 (5,82) Deal size -0,14 (0,33) 0,13 (0,22) -0,22 (0,45) 0,64 (1,41) 1,10 (1,31) Payment method 0,74 (1,29) 1,601* (0,84) 4,64*** (1,75) -10,91* (5,44) 17,11*** (5,04) Market Cap, 0,11 (0,27) 0,04 (0,18) 0,34 (0,37) 0,23 (1,16) 1,10 (1,08) CIT 0,34*** (0,09) -0,08 (0,06) 0,36*** (0,12) 0,14 (0,38) 0,53 (0,35) Observations 282 282 282 282 282 R2 _0,0653 _0,0367 _0,0886 _0,0432 _0,0979

In table 9, I introduce specifications (1)-(5), in an attempt to get a better understanding of the relative effect of the independent variables on the share-holders value in different periods. Besides the previous discussed periods in table 7 and 8 I introduce the time period [-11,-2], [-250,-2] and [2,250].

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negative sign for premium paid, (-2,61), shows that an increase in the premium paid by 1% causes the shareholder value during the 3-day period to change by -2,61%. As discussed this is in line with previous stated hypothesis II. Also the positive sign for the variable corporate income tax is according prior stated hypothesis, the implication of the coefficient is that when corporate income tax increase by 1% the shareholders return in the 3-day period increases by 0,34%. All other introduced variables in (1) do not have significant influence on the shareholders value during this period.

Now examining the [-11,-2] period, also called the run-up period. There are two variables which show a significant effect on the shareholder value during this period. First, is the percentage acquired, (0,08), indicating that an increase in 1% of the total shares acquired the shareholder value increases with 0,08%, is significant at a 10% level. This positive sign is in line with prior literature. The other variable which has a significant influence in the method of payment for the transactions. The coefficient indicates that cash paid transactions perform 1,6% better than stock financed transaction during this period. In line with previous literature and hypothesis IV, an increase pre announcement date might indicate that information about the transaction is spilled in public and that a cash-paid transaction is seen as positive.

Specification (3) from table 9 adds to table 8, the change in significance for the premium paid in the 10-day period. It shows a negative sign, which is in line with previous findings and literature. Next to the premium variable, both payment method and corporate income tax show a significant influence, which is also observed in table 8.

For both the periods [-250,-2] and [2,250] a significant value is presented in table 9 for the variables, percentage acquired and payment method. With the extra significant value for the [-250,-2] for the state diversification dummy variable. The signs of the variables do contradict each other. For the 250-day window prior to the announcement the percentage acquired has a positive influ-ence on the shareholder value during the period. It is difficult to come up with a practical reasoning behind this phenomena, however it might indicate that firms which outperform the market are able to acquire a larger part of their target. This reasoning can also directly link to the negative sign for the per-centage acquired for the 250-day post announcement date, firms which perform better prior to the announcement have a higher change of under-performing after announcement.

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re-turn than stock-financed mergers and acquisitions”. A positive sign, (17,11), indicate that cash paid transactions perform 17,33% better than stock financed transaction during that same period, [2,250]. This is according to previous lit-erature (Bessler and Westerman, 2020). On the other hand a negative sign for payment method is shown for the 250-day period pre announcement, this might be contributed to the fact that when a firm pays for a transaction in cash this amount needs to be extracted from the day-to-day operations of the firm which might decreases the efficiency and profitability.

Concluding the part on the bidder shareholder value, strong evidence is found that in both the short-run and future long-run cash paid transactions outperform stock financed transactions. Further, in the short-run the premium paid significantly decreases shareholders value of the acquiring firm. Finally, the amount of corporate income tax influences the shareholder value positively in the short-run. These three results confirm three of the hypotheses formulated in this study, hypothesis II, IV and VI.

6.1.2 Bidder regression analysis

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Table 10: Cross-sectional regression results: Target Part 1 Variable (1) CAR [-1,1] (2) CAR [-1,1] (3) CAR [-1,1] (4) CAR [-1,1] (5) CAR [-1,1] (6) CAR [-1,1] (7) CAR [-1,1] Percentage acquired 0,50** (0,23) 0,49** (0,24) 0,15 (0,15) 0,52* (0,23) 0,45* (0,23) 0,51** (0,24) 0,51** (0,24) State Div. 0,36 (3,75) 0,06 (3,77) 1,99 (2,40) 0,77 (3,73) 2,35 (3,83) 0,27 (3,77) 0,34 (3,76) Industry Div. -3,96 (4,13) Premium 62,00*** (3,10) Deal size -2,27** (0,95) Payment method 8,97** (4,03) Market Cap. -0,22 (0,78) CIT -0,05 (0,30) Observations 282 282 282 282 282 282 282 R2 _0,0163 _0,0195 _0,5971 _0,0360 _0,0335 _0,0165 _0,0163

In table 10, specification (1), the control variables are shown. In line with the effect of the percentage acquired for the acquiring firm, also the target benefits from a higher percentage acquired by the bidder. In all specifications (1)-(7) the variable is positive and except from (3) the value is significant. However, in contrast to the negative effect of state diversification for the acquiring firm the bidder shows a positive sign for state diversification over all specification. This indicates that targets which originate from the same state as their acquirer show a higher shareholder return than targets which differentiate from their acquirer in geographical location. This outcome is in line with Moeller and Schlingemann (2005).

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Table 11: Cross-sectional regression results: Target Part 2 Variable (1) CAR [-11,-2] (2) CAR [-11,-2] (3) CAR [-11,-2] (4) CAR [-11,-2] (5) CAR [-11,-2] (6) CAR [-11,-2] (7) CAR [-11,-2] Percentage acquired 0,03 (0,13) 0,04 (0,13) 0,04 (0,13) 0,03 (0,13) 0,00 (0,13) -0,01 (0,13) 0,03 (0,13) State Div. -0,81 (2,10) -0,57 (2,11) -0,83 (2,11) -0,91 (2,10) 0,18 (2,15) -0,32 (2,08) -0,80 (2,11) Industry Div. 3,19 (2,31) Premium -0,68 (2,71) Deal size 0,54 (0,53) Payment method 4,47** (2,26) Market Cap. 1,22*** (0,43) CIT 0,04 (0,17) Observations 282 282 282 282 282 282 282 R2 _0,0008 _0,0077 _0,0011 _0,0045 _0,0147 _0,0289 _0,0010

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the rumours of the transaction by a relative large firm as positive. Table 12: Regression results: Target

Variable (1) CAR [-1,1] (2) CAR [-11,-1] (3) BHAR [-10,10] (4) BHAR [-250,-2] (5) BHAR [2,250] Percentage acquired 0,20 (0,15) -0,01 (0,13) -0,19 (0,44) -0,58 (0,49) -1,81 (0,86) State Div 1,68 (2,49) 0,64 (2,15) -3,59 (8,55) -11,02 (7,90) -4,93 (13,67) Industry Div -2,41 (2,68) 3,53 (2,32) 8,05 (8,65) 8,77 (8,50) 11,53 (17,85) Premium 62,16*** (3,20) -1,55 (2,76) 51,69*** (10,89) -11,55 (10,14) 4,97 (21,72) Deal size -0,30 (0,72) -0,31 (0,62) -6,29*** (2,36) 2,12 (2,278) 5,91 (6,48) Payment method 0,10 (2,77) 3,11 (2,40) 12,56 (8,44) 15,38* (8,78) -20,52 (16,10) Market Cap -0,17 (0,59) 1,19** (0,51) 6,60*** (2,04) 4,56 (1,87) 2,62 (3,03) CIT -0,37* (0,19) 0,019 (0,17) 0,56 (0,57) 0,60 (0,61) -0,51 (1,32) Observations 282 282 157 282 29 R2 _0,6043 _0,0439 _0,2834 _0,0896 _0,2404

In table 12 specifications (1)-(5) are introduced in order to further under-stand the relative effect of the independent variables. Important to note that restrictions are found in the sample size due to the fact that acquired firms tend to be delisted in the period after the announcement date.

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significance however they do hold on to the same sign as in the cross-sectional regression analysis.

For the run-up period, only the market capitalization remains significant, this might suggest that the information which is spilled to the public is con-strained to the name of the potential acquirer and that larger firms earn more trust, relative to smaller firms, of investors prior to the transaction. This posi-tive sign for the market capitalization of the acquirer contradicts previous liter-ature,(Moeller et al., 2004), and hypothesis V: ”Firm size of the acquiring firm is negatively related to the performance of the acquiring firm”.

For the [-10,10], besides the premium paid, both deal size and market capi-talization significantly influence the shareholder value during this period. Both variables being significant at a 1% level. The negative sign for deal size is in to prior literature Alexandridis et al. (2013); Hua et al. (2020), however contradicts the findings of Alexandridis et al. (2016) which found that large transaction are viewed more positively by the market. Furthermore it confirms my hypothesis III that states: ”The deal size of a merger or acquisition and relative values is negatively related to the performance of the acquiring firm”.

For the last two periods, the variable payment method for the period [-250,-2] is the only significant variable. Common rationing suggests that the correlation might be the other way around. Companies which outperform the market are seen as interesting targets and bidders want to maximize the possibility to com-plete the transaction (Huanga et al., 2016).

To conclude this part, strong evidence is found for the influence of the pre-mium paid(+), deal size(-) and the payment method(+) on the targets share-holder value during the mark-up period. Evidence is also found on factors influencing the run-up period to a transactions, both the payment method(+) and market capitalization(-) show great significance in influencing the share-holder value during the run-up period. These outcomes confirm the hypotheses III, IV

6.2 Study limitations and further research

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6.2.1 Sample limitations

For this study only completed deals are used and transactions which are canceled prior to completion are excluded in the sample. Managers can always decide to cancel the transaction before completion. Building further on the idea that managers should act rational, only transactions which are seen as positive prior to transaction are completed. By excluding the failed transactions it might be that improper conclusions are drawn between the factors influencing the shareholder value and the true shareholder value prior and post transaction.

Besides previous mentioned sample limitation this research focuses on do-mestic transaction between listed companies originating from the U.S. This is done in order to narrow the study and to exclude several factors which can influence the performance of M&As, such as cross-border transactions and the acquisition of private targets. Due to the fact that the sample is limited in this way the outcomes of the study can not be assumed to hold for every country and its domestic transactions.

6.2.2 Further research

As discussed in the part of ”Sample limitations” this study focuses on domestic transaction between listed companies originating from the U.S. This research can be broadened to include these order transactions in order to include variables as cross-border transactions and private target. This further expansion of bidder and target firms broadens the scope of the research and generate outcomes which could be used as standard around the world.

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7 Conclusion

We currently witness a M&A market which is not going as smoothly as it once did. This gives the opportunity to look back and analyse what the factors are behind successful transactions. In this study I try to examine the factors behind the performance of transaction, by looking at the stock price changes of both the acquirer and target. In contrast to most prior literature this study does not concentrate on only the bidder or target performance. This gives a clear image on which factors are of much importance to the acquirer and the target.

The base question of this study: Do mergers and acquisitions have a negative effect on the performance of the bidder firm and a positive effect on the perfor-mance of the target firm? Which is formulated in the introduction is answered in this study. As shown in this study the positive effect on the shareholder value of the target is overwhelming, showing on average increase of around 25% post announcement of the transaction. However, for the acquiring firm the outcome is not that bright in this study. Despite the fact that prior literature does not generate a conclusive answer, the outcome from this study is straightforward. M&A destroys value for the acquiring firm, in both the short run and in the long run. Behold of the limitations of this study which are previously mentioned. By incorporating one or more suggested additions to the study more even more conclusive outcomes can be generated.

The true reason of this research is to find the drivers behind these loses and gains in shareholder value. Strong evidence is found that in both the short-run and future long-run cash paid transactions outperform stock financed transac-tions for both the acquirer and the target. This confirms the hypothesis IV: All cash financed mergers and acquisitions have higher bidder and target share-holder return than stock-financed mergers and acquisitions.

Further, in the short-run the premium paid significantly decreases share-holders value of the acquiring firm. Finally,the amount of corporate income tax influences the shareholder value positively in the short-run. These three results confirm three of the hypotheses formulated in this study, hypothesis II and VI

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