Is offer premium affected by source of funds? : a comparison between European and North Asia target takeovers.

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MSc Business Economics, Finance track Master Thesis

Is offer premium affected by source of funds?

A comparison between European and North Asia target takeovers

Supervisor: dr Vladimir Vladimirov

Author: Yubo Li(10394079)

November 2013

Universiteit van Amsterdam Amsterdam business school

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Acknowledgements

I would like to express the deepest appreciation to my thesis supervisor Dr Vladimir Vladimirov, who has offered me greatest help for my thesis writing and given me best support to my internship. Without his supervision and constant help, this thesis would not have been possible.

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Is offer premium affected by source of funds?

A comparison between European and North Asia target takeovers

Abstract

This paper intends to explore the link between the sources of funds and offer premium in corporate takeovers. With a European sample of 1238 cases and a North Asia sample of 468 cases from 01 January 1985 to 31 August 2013, I regress offer premium on the sources of funds while control for other determinants of offer premium from previous researches. The results show that equity has less impact on the offer premium than internal funds for Europe, which is consistent with the pecking order theory; but debt financing has more impact on the offer premium than internal funds for North Asia. Debt financing is not significant for the European sample, and the results of the North Asia sample and Europe sample are different. In addition, I compare the effects of determinants of offer premium and try to include tobin’s q as a control variable.

Keywords: Coporate takeovers; Europe; North Asia; Offer premium; Source of funds; Source of financing; Tobin’s q

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According to the neoclassical model of the firm, mergers and acquisition are undertaken in order to increase the shareholder’s value. But for most of the cases ,the acquirer tend to overpay to realize the expected value increase, leading to gains for target shareholders but loss for acquiring shareholders (Sudarsanam, 2010, ch.4). The overpayment from the acquirer to the target is known as takeover premium, which is defined as the difference between the estimated real value of a company and the actual price paid to obtain it. Acquisition premium represents the increased cost of buying a target company during a merger and acquisition.

Many researches have showed the evidence of the takeover premium. But what are the determinants of the takeover premium? According to Betton, Eckbo and Thorhurn(2008a), the main determinants of the takeover premium can be categorized into three aspects: First, the target characteristics, including the size of the target, the target performance, the stock performance prior to the takeover announce and whether the target uses a poison pill; Second, the bidder characteristics , including toehold, acquirer public status, and whether the bidder and target are in the same industry. Third, deal characteristics, including the method of payment, whether it is a tender offer or a merger offer, the deal attitude, the number of bidders.

One of the most important determinants is the method of payment, method of payment can be cash payment, stock payment and a mix of both. When the payment is cash or has a cash portion, one question arises: what is the source of the cash or in other words, how the cash is financed. The cash can be financed by issuing debt,by issuing equity, or by internal funds. The payment method can be selected as part of a broader capital structure (Ross 1977), and attempts to link the payment method choice to financing sources for the cash portion of the bid are only starting to emerge. Furthermore, not a research has been done to study the questions such as: “How the takeover premium will be affected by the source of funds when control for the effect of all the other determinants?”, or “Do different sources of funds have different effects on the takeover premium?”, and this is where my thesis comes in. Therefore in this paper I will try to answer the question that “Is the offer premium affected by the source of funds?”. Seldom literature has focused on the link between the source of funds and offer premium, this is the contribution this paper will make.

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Based on the main determinants from Betton, Eckbo and Thorhurn(2008a), I will include the sources of funds into the regression, control for other determinants to study the link between the source of funds and the takeover premium. I also try to include Tobin’s q as a new control variable based on the existing control variables. Additionally, I will study how the determinants and the premium will change during the European debt crisis and give a further perspective of this issue. The regressions will be applied to a European takeover sample of 1238 cases and a North Asia sample of 468 cases. The results will be analyzed and the results of these two samples will be compared. No study in the topic of sources of funds has chosen the sample of both Europe and Asia, my paper is the first one to focus on the relation between source of funds and offer premium, doing a comparison for European and North Asia takeovers.

The structure of this paper is as follows: In section one, I give a brief introduction about this paper, discuss the topic, research question and the contribution. In section two, I will review the related literatures to give a general idea about this topic of prior literatures and form a theoretical framework for this paper; In section three, I will introduce the data sources, criterion of the data collection and the sample characteristics of the data. In section four, I will discuss how the methodology is designed and the hypothesis. And then I come to the results of the regressions, in section five I will analyze the results and compare the results of these two samples. Section six will be the conclusion of this paper.

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2. Literature review 2.1 Corporate takeovers

Corporate takeover is a corporate action where an acquiring company makes a bid for a target company. If the target company is publicly traded, the acquiring company will make an offer for the outstanding shares. Since takeovers are usually related to a lot of money and they can be one of the most important investments a company can have, a lot of researches have been done in this field.

Earlier Literatures mostly focus on the final bid in completed takeovers, for example, Jensen and Ruback (1983), Jarrell, Brickley and Netter(1988), Eckbo(1988)study the market for corporate control through final bid; recent studies gradually move the focus to the entire takeover process, that is , the process from the first biding to the final outcome. Betton and Eckbo(2000) initiate the approach of focusing on the entire process of takeover; Bhagat,Dong,Hirshleifer, and Noah(2005) re-estimate the takeover value improvements by focusing on the entire takeover process; Betton and Mulherin(2007b) provide novel data on the pre-public, private takeover process and compare two ways (auctions and negotiations)of selling a company.There can be a wide range of topics about corporate takeovers. From merger waves to the probability of takeover success; From choice of payment method to takeover defenses; From takeover premium to bidding behavior. Among all the topics in the field of corporate takeover, one attracts much public attention and empirical research is the question about offer premium.

2.2 Offer premium

Offer premium, or acquisition premium, is the difference in the amount offered by the acquirer and the pre-acquisition valuation of the firm being acquired ;and commonly defined as the acquirer’s bid minus the target’s pre announcement market value divided by the target’s pre-announcement market value. During a merger or acquisition, the acquirer will usually offer a premium that is above the target company’s closing stock price in order to make the deal attractive, or to deter other potential competitors.

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Many researches have showed the evidence of the takeover premium. Jensen and Ruback(1983) conclude that target shareholders get significant abnormal returns in the month or two around the takeover, with an average abnormal return of 29.1% in successful bids and substantial gain in unsuccessful takeovers as well. Dodd(1976),Walter(1984), and Bishop, Dodd and Officer(1987) find abnormal target returns of about 20% in both successful takeovers and unsuccessful takeovers in the takeover announcement period1.

There are two methods of measuring the offer premium according to related literatures. One is to use the target cumulative abnormal stock returns(CAR), the other is to use the premium of the target share price on the deal announcement date over the target share price prior to the deal announcement date.

the CAR estimation used the market model. For example, one way Sandra(2013) chose to estimate markups and runups was to use the target’s cumulative abnormal stock return. CAR was estimated using the market model, where the runup was CAR(-41, 2) and the markup was CAR(-1, 1). CAR rather than offer price was used as a proxy of offer premium to compare the results of the main empirical analysis. Some early literature study the CAR itself , for example Yen-Sheng and Ralph A.(1987) studied how the target cumulative abnormal returns would react with different acquisition announcements Tomi(2007) also used the cumulative abnormal return as the measurement of the offer premium. Tomi used the standard procedure used by Capron and Pistre(2002) to determined Eckbo and Thorburn(2008b) used the target abnormal stock returns as an alternative measurement, where value-weighted market return was used as normal returns.Officer(2003) indicates that the first measure, the one using CAR, in spite of frequent use in many literatures, could make the nominal premium more complex due to the variation of market’s anticipation. Therefore, officer(2003)study offer prices directly. Bradley(1980), Walkling(1985), Betton,Eckbo and Thorburn(2008b) all employ the offer prices directly and support the use of offer prices with data analysis in order to calculate the offer premium. The method using CAR as a proxy for the actual offer premium have many restrictions, for the target cumulative abnormal returns can incorporate the possibility of bid

1_{Martin and Terry, An empirical analysis of some determinants of the target shareholder premium in takeovers}

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failure and competition at the initial offer date, which will induce noisy estimates of offer premiums. Therefore the direct use of offer prices should be a better way of calculating and measuring the offer premium according to the literature shown so far. As for the target’s pre-announcement market value, prior literature use different length of the runup window. Tomi(2007) used a market model which was created for each acquiring firm's stock by regressing 200 daily dividend-corrected returns from day-240 to -40 against the index. Bradley (1980) calculates the offer premium using 40 days pre-announcement offer price. Betton and Eckno(2000) use the target share price 60 days prior to the offer date. Comment and Schwert(1995) begin their periods 20 trading days before the initial takeover announcements in order to ensure they capture any runup. Andrade, Mitchell, and Stafford (2001) compare several windows and find that the longer the windows is, the less precision the result will be. Betton, Eckbo,and Thorburn(2007) use 42 days prior to the announcement. Billet and Ryngaert(1997) use 20 days prior to the first corporate control event announcement and 5 days after the final offer announcement window to estimate the target’s abnormal equity return. Brigida and Madurab(2012) estimate the runup over alternative 60 days and 30 days prior to the announcement. Fua,Lin,and Officer (2013) use 42 trading days before the announcement as measurement.

Table 1 summarized the different runup period used. Schwert (1996) uses 42 days relative to the first bid and suggests that, because of information leakage and market anticipation, stock prices of the ﬁrms merged could partially reﬂect the value implications of the merger in the two months prior to announcement.The longer the runup window is, the less effect will be produced from the market’s pre-acquisition anticipation, but at the same time, there will be more noise. So there is a tradeoff between the length of the window we use and the accuracy of the offer premium we would like to measure. Having compared many of the analysis results in the prior literature, I found that the 42 days prior to the announcement period would be a good choice, for the period is neither too short nor too long, which not only reduced the market’s pre-acquisition anticipation to a good extent, but also excluded most noise that may be introduced.

Eckbo and Thorburn(2008b) decomposed the offer premium into initial offer premium and the final offer premium. The initial offer premium was calculated using

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the initial offer price and the target stock closing price with the adjustment of splits and dividends. Similarly, the final offer premium was calculated using the final offer price in the contest. I will follow the method employed by Eckbo and Thorburn(2008b) to use both intial offer premium and final offer premium as the dependent variables.

2.3 Determinants of offer premium

Numerous factors can account for the determination of offer premium. According to Betton, Eckbo and Thorburn (2008a), the determinants of offer premium can be categories into three parts: target characteristics, bidder characteristics and deal characteristics: target characteristics, bidder characteristics and deal characteristics. 2.3.1 Target characteristics

Size: ln of target market capitalization on day−42. Previous literature has shown that

the size of the target company can have a significant influence on the acquisition premium (Rossi and Volpin, 2004).Transaction size is used as a proxy of target size. The argument indicates that the larger the target size is, the fewer the potential bidders and therefore less premium due to less competition and negotiation. Officer (2003) shows there is evidence that target shareholder gain less when the target size is larger. Target book-to-market > industry median. Target book to market value is book value divided by market value of the target company. Book value is calculated from the historical cost while market value is calculated from the stock price and shares of the target. Book to market value is an indicator of whether the target securities is overvalued or undervalued.

Target runup: ln(p−1/p−42). Schwert(1996) find a strong evidence of markup pricing by regressing a measure of the final takeover premium on the runup. Based on the study of Schwert(1996) Betton, Eckbo and Thorburn (2008b) are the first to estimate the effect of target runups on markups in initial and final offer prices. And they further the research by extending the question using initial offer price as well and they find that a dollar increase in the runup raises the intial offer by$0.80 in their sample, a sample of seven thousand initial takeover bids for publicly traded U.S. targets 1980-2002

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Amihud liquidity .Amihud(2002) argues that expected stock excess return is related to stock illiquidity and illiquidity reflects the impact of order flow on price, that is , the premium the the acquirer has to pay in order to execute a market order. Amihud liquidity is a measure of the liquidity of target stock and is calculated as Amihud liquidity is the average value of |Ri|/(pi/Si) over days i ∈{−250, −42}, where Ri is the % holding period return, pi is the closing price and Si is the number of shares traded on day i(Amihud,2002; Betton, Eckbo and Thorburn 2008a). Marshall et al. (2012) demonstrate the Amihud liquidity measure is a good liquidity proxy. Kamara et al. (2008) and Korajczyk and Sadka (2008) use the Amihud liquidity measure in their stock market liquidity commonality studies.

Poison pill dummy. There is substantial empirical evidence about the adoption of poison pills by the targets and the relation between poison pills and takeover premiums. Comment and Schwert (1995) provide large sample evidence related to poison pills issues and show that poison pills are reliably associated with higher takeover premiums for target company shareholders. Zingales (1995) and Mello and Parsons (1998) suggest that takeover defenses can be used to facilitate the future sale of the firm and increase its expected takeover premium.

2.3.2 Bidder characteristics

Positive toehold (vs. zero toehold). Acquiring firms sometimes will own some shares

in the target firm prior to the takeover, which is called toehold. Large toehold means fewer outside shareholders need to accept the offer for the takeover to succeed, which improve the probability of the success of the takeover and give the acquirer more negotiation power in the deal. Stulz(1988) indicates that the takeover premium will be lower at higher levels of toehold. Stulz, Walkling and Song(1990) found target cumulative abnormal returns(CARs) in the five days before the initial offer to the five days after the final offer are significantly negatively related to the toehold. Bugeja and Walter(1995) also hypothesize and testify this negative relation between the toehold and the takeover premium.

Acquirer public (vs. private). Schwert(1996) compares the premium for cash offers by

private acquirers and by public acquirers and finds a big difference in premiums between the two types of acquisitions. The premium paid by the public acquirers is

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higher the premium paid by the private acquirers. Bargeron, Schlingemann Stulz and Zutter (2008) find evidence that public acquirers pays 63% higher premium to the public target shareholders than private acquirers, which is consistent with the findings by Schwert(1996), indicating that the public status of the acquirer has an influence on the takeover premium.

Horizontal takeover (same industry).According to Anna Dodonova(2013), Prior

literatures study the effect of horizontal mergers and acquisitions on the market value of rival companies indicates both positive and negative effects. There might be two reason , firstly ,the horizontal acquisition can lead higher concentration ,which can produce higher prices and profits due to economic scale;secondly, the merger may lead to an innovation. Kedia, Ravid, Abraham and Pons(2011) study the market reaction to vertical mergers and acquisitions. They find that Abnormal returns for vertical merger announcements are positive until the late 1990s, and turn negative afterward, where the acquirers bear most of the loss.Huyghebaert and Luypaert(2013) use a sample of horizontal acquisitions in Europe during the period 1997-2008 and compute the combined abnormal return around announcement as a proxy of acquisition value creation. The results show that industry sales concentration and the ratio of the combined target and bidder size are significantly negatively related to the acquisition value creation, but the data reveal that division of M&A gains between target and acquirer is determined by firm and deal characteristics rather than by industry conditions.

2.3.3 Deal characteristics

Tender offer (vs. merger). Michael Jensen and Richard Ruback(1983) shows that the abnormal percentage stock price changes more when the offer is tender offer rather than a merger announcement. Betton,Eckbo and Thorburn(2008b) find the premium is related to the choice between tender offer and merger offer.The study of the choice of tender and merger offer has just began to emerge. Kohers,Kohers and Kohers(2007) study the distinction between tender offers and mergers, and their results show that tender offers are not just a function of method of payment, tender offers are more likely when the form of payment is all-cash, when the institutional ownership is high, when the target is defensive and when there are more than one bidders, which

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indicates that the choice between tender and merger offer can affect the premium through other factors, making it important to include it as a control variable. Betton Eckbo and Tohrburn(2008a) focus on the choice between tender and merger offer from the bidders’ perspective, they also separate public bidders from private bidders to test for the differences.

All cash consideration (vs. stock or mixed). According to Jing Zhang and Yong’an Zhang(2011), Method of payment in merger and acquisition refer to the resources and financial tools through which the purchasing companies acquire the ownership and controlling right of the target companies. Initial tender offers and merger offers can use all-cash, all-stock, and mixed cash-stock as method of payment. Numerous economic hypotheses and related empirical evidence are concerning the choice of payment method. The reasons for different method of payment choices can be taxes related effect, asymmetric information, capital structure and corporate control motives and behavioral motives. Eckbo and Langohr(1989) show that if the method of payment is all cash in tender offers ,the target premiums will be higher in France. Eckbo and Thorburn(2000) find that the average announcement-induced abnormal stock returns to bidders are highest when the deal is transected all in cash, lowest when the deal is all in stock, with mixed cash-stock deals in between. Burcha, Nandab, Silveric(2012) study the association of target shareholders’ investment preference on the method of payment and the acquisition premiums. They find that different method of choice can lead to different premium, which can be explained by tax-related effects for stock offers allow target shareholders to defer capital gains taxes.

Hostile target response (vs. friendly or neutral).In a process of takeover, the reaction of the target company can be either friendly of hostile. The attitude of the target can also have an impact on the success of a takeover as well as the premium that the acquirers have to pay. Walking (1985) find a positive relationship between the bid premium and the probability of a successful tender offer. However, Zissu and Stone(1989) study the relationship between the bid premium and the outcome of tender offers, and their results show that bid premiums have opposite relationship with the probability of successful outcome , depending on whether the offer is friendly or hostile. Holmén, Nivorozhkin and Rana (2012) use a prior model,the

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Heckman selection model to study the relation between the possibility that a firm becomes a takeover target, takeover premium and the use of anti-takeover devices. They document a negative relation between the anti-takeover devices and the possibility that the firm will be taken over; and a non-significant relation bwtween the takeover premium and the anti-takeover devices.

Multiple bidders (vs. single-bidder contest). In the sense that the more bidders bid for

a target company, the more competition there will be, which will lead a decrease in bidder gains, since the bidder has to pay more to take over the target under competition. The bidders tend to pay more premiums to get the deal done ,therefore the number of bidders should has an impact on the takeover premium. Flanagan and O'Shaughnessy(2003) employ the data of 285 tender offers for US-based manufacturing firms to study the impacts of core-relatedness and multiple bidders on takeover premiums. They found that the existence of multiple bidders has a greater impact on the premium when the final acquirer is not core-related to the target, the acquirers tend to pay very high premiums when there are multiple bidders competing for the target.

2.3.4 Other characteristics

Schlingemann use (2004) Tobin’s q to measure investment opportunities, and find that the bidder gains are more positively and significantly related to the equity financing for high q firms than for low q firms. Tobin’s q might be a variable that can make a difference when study the relation between the source of financing and takeover premium. Buguja(2011) studies if there exists a positive relation between takeover premiums and the auditor’s reputation and independence of the target company and find a significant relation for reputation under some circumstances, but no significant relation for independence. Chatterjee, John, and Yan(2008) study the effect of divergence of opinion on bid prices and they find that the takeover premium increases when investors have higher divergence of opinion. Levi, Li, and Zhang(2008) study the relation between CEO and director gender and takeover premium and find that the bid premium over the pre-announcement target share price is statistically and economically smaller if the CEO of the bidding company is a woman.

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2.4 Summary of the determinants and the determinants’ effects of offer premium

Betton S., B.E. Eckbo, K.S. Thorburn,(2008a) summarize the determinants of the offer premium in 4889 control contests for U.S. public targets from 1980 to 2002. According to Betton S., B.E. Eckbo, K.S. Thorburn,(2008a),they use the initial and final offer premium as dependent variables, which are defined as ln(pintial/p-42) and

ln(pfinal/p-42) respectively .pintial is the initial offer price, pfinal is the final offer price.

p-42 is the stock price on day -42 adjusted for splits and dividends.

They regress the initial and final offer premium on all the determinants summarized, and find the following:

1. When the bidder is a public company, the premiums are significantly higher; 2. When the initial bid is a tender offer, the premiums are significantly lower; 3. When the method of payment is all cash, the premiums are significantly higher;

4. When the bidder has a positive toehold, the premiums are significantly higher.;

5. When the target runnup prior to the initial bid is greater, the premiums were significantly greater; and

6. Premiums are found unaffected by the presence of poison pill. 2.5 Sources of funds

Among all the determinants of the premium, method of payment is one of the most important. Many literatures focus on the method of payment(Chen, Chou, and Lee(2011), Raymond , Robin and David (2004); Eckbo and Langohr(2004) ). The choice of the payment method can be affected by taxes, asymmetric information , capital structure and control motives and so on. For the capital structure and control motives, Ross(1977) and Jensen(1986) state that the payment method is selected as part of a broader capital structure choice. Moreover, some bidder managements select cash over stock as payment in order to avoid diluting their private benefits of control in the merged firm.

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However, most of the cases, the term” method of payment” is always considered the same as “source of funding”. But these two concepts are different. The method of payment is about “how you pay in order to acquire a company”, while the sources of funding is about ”where the money you paid comes from”. The payment method in takeovers includes all-stock payment, all cash payment, and mixes of securities and cash. the sources of funding focus on “where the cash come from”, or “how the fund is financed”. Therefore using method of payment to present the sources of funding might lead to some inaccuracy.

Attempts to link the payment method choice to financing sources for the cash portion of the bid are only starting to emerge. Yook (2003) tries to explain higher returns for bidders offering cash rather than stock, and the result suggests that cash acquisition and stock acquisitions have different sources of value creation; although most unsuccessful acquisitions use stock, but no convincing evidence that cash is used for good acquisitions is found. Schlingemann (2004) analyzes the relation between bidder gains and source of financing. He finds a positive relation between bidder gains and equity financing, a negative relation between bidder gains and free cash flow, or internal funds, but not a significant relation between bidder gains and debt financing. And these findings are consistent with pecking order theory and free cash flow hypothesis. Martynova and Renneboog(2009) first clearly bring about the distinction of the two concepts of sources of financing and method of payment. They reveal that the external sources of financing (debt and equity) are frequently employed in takeovers involving cash payments, which is one of the methods of payment. They also find that the acquisitions with the same method of payment but different sources of funds can be quite different.

Therefore, referring to all the prior literature and base on the model used by Betton,Eckbo, and Thorburn(2008b), I will focus on the source of funds, to study the relationship between the source of funds and the offer premium, that is , how the source of funds can affect the premium, controlling for the effect of the method of payment for how the cash bids are financed and all the other determinant of the offer premium.

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3. Data

3.1 Data sources and sample selection

In this paper, in order to study the effect of sources of funds on the takeover premium, I use the samples of takeover cases both from Europe2 and North Asia3. The two main databases I use are Thomson one and Datastream. The location of the takeover is defined according to the location of the target company. In order to cover most of the takeovers cases of Europe and North Asia, I set the period of the searching criteria as the announcement days between January 1st 1985 and August 31th, 2013. And then I drop the deals with Initial offer price per share less than 0.0001 to eliminate the deals without the record of initial offer prices, since the initial offer price is one of the most important elements of calculating Initial offer premium, which is the dependent variable of this study. The other key element of the study is the sources of funds, which includes 12 different specified sources : Bridge Loan, Rights Offering, Mezzanine Financing, Staple Financing, Debt Offering, Junk Bond Offering, Common Stock Offering, Preferred Stock Offering, Corporate Funds, Borrowing, Line of Credit, Foreign Lender. I created 12 dummies for these 12 sources of fund and separate them into three categories : Internal fund , debt source and stock source. The definition of the independent variables are summarized in Table 2

The sources of fund are displayed as dummy variables in the Thomson One database, where the flag was set to “Y” if the transaction is done by the source of fund, otherwise “N”. To avoid the all the 12 dummies are “N”, in which case it means the source of funds is unknown, I set the criteria that the sources of fund contains at least one of the 12 sources of fund, although the criteria limits the sample to a much smaller size.

2_{Europe includes: Albania, Andorra , Austria, Bosnia and Herzegovina, Belgium, Bulgaria, Belarus, Czech Republic,}

Croatia, Cyprus, Czechoslovakia, Denmark, Estonia, Faroe Islands, Finland, France, East Germany, Georgia, Guernsey, Gibraltar, Greenland, Greece, Hungary, Iceland, Isle of Man, Republic of Ireland, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Slovenia, Luxembourg, Moldova, San Marino, Montenegro, Macedonia, Monaco, Malta, Norway, Netherlands, Poland, Portugal, Serbia, Romania, Russian Federation, Spain, Serbia & Montenegro, Svalbard/Jan Mayer Islands(Norway),Soviet Union, Slovak Republic, Sweden, Switzerland, Turkey, Ukraine, United Kingdom, Holy See(Vatican City), Germany, Yugoslavia, according to the Thomson One database.

3_{North Asia includes : China, Hong Kong, Macau, Mongolia, North Korea, South Korea, Taiwan according to}

Thomson One database. Hong Kong(from 1997) and Macau(from 1999) are special administrative regions in China, Taiwan is an arguable region of China due history reasons.

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After using the criteria mentioned above I got the sample size of 1645 for the European countries and 840 for the North Asian countries. And then I collect target market information from the Datastream database based on the target datastream code provided in the Thomson One database, which include stock prices, number of shares, book to market ratio, target total assets, target common stock, market value, total return index.

Due to the missing of Datastream codes and data processing, I drop more cases that are not suitable for the study, for example I drop the cases in which the company’s consideration ratio is “UNKNOWN”, the deal attitude with “Not Appl” and some other cases like initial offer premium, book to market when there are missing values or the missing values are created from calculation. The two sample sizes were decreased to 1238 cases for the European target takeovers and 468 cases for the North Asian target takeovers respectively. Search criteria and Sample size are summarized in Table 3.

3.2 Sample Characteristics

Table 4 and Figure 1 show the takeover deals sample distribution from year 1985 to 20134 for both Europe and North Asia. We can see that during the first decade, there are few takeover deals. Europe has a greater number of takeovers than North Asia does. European takeovers reach a peak around 1999, which is the time when more takeover deals in North Asia just begin to come about. North Asia takeovers deals have a high speed of growing after 2009, while the Europe has a decrease. Therefore, the takeover deals sample distribution of Europe and North Asia are quite different, as to number and tendency.

Since I would like to study the relation between the source of funds and the offer premium, no doubt these two are the most important variables. With all the other control variables, I make source of funds the key independent variables and the offer premium the dependent variable. (refers to Table 7) For the independent variables, i.e. the sources of funds, there are totally twelve sources of funds and I separate them into three categories: first, the internal fund which only includes the corporate fund;

4_{Due to the time of writing the paper, the data collected was constrained to August 31, 2013.}

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Second, the debt source, which includes debt offering, borrowing, bridge loan, line of credit, foreign lender mezzanine financing, junk bond offering and staple financing; third, the stock source, which includes common stock offering, preferred stock offering and rights offering, refer to Table 2. Since these three categories are not mutually exclusive, in many cases a company tends to use more than one source of funds, I add one item “Mixed financing” to illustrate this situation. Table 5 summarizes the distribution of the sources of funds for both samples. Panel A shows distribution of the 12 different sources of funds. Panel B shows the distribution among three categories. Panel C is the European sample sources of funds distribution through years. Panel D is North Asia target sample sources of funds distribution through years. Figure 2 to Figure 8 show the comparison of the sources of funds for both samples in different angels as well.

And then I come to the key dependent variables—offer premium. To illustrate more properly, I used the initial offer premium and final offer premium as the dependent variable s for each regression. As discussed above, based on the prior literature (Bradley 1980, Betton, Eckbo,and Thorburn 2007), I choose 42 days as event window to calculate the initial offer premium and final offer premium. Initial offer premium are defined as ln(P_inital/P-42) , final offer premium are defined as ln(P_final/P-42), where P_initial is the initial offer price per share, P_final is the final offer price in the contest, P-42 is the stock price on day 42 days prior to the announcement date. Information about the offer premium is summarized in Table 6. 3.2.1 Deal distribution though years

Table 4 and Figure 1 show the tendency of European sample and North Asia Sample of takeover deals though years. According to the sample, the tendency for European takeovers remained at steady low level for about a decade before 1996. However, there are several significant changes afterwards :from 1996 on, the number of takeover deals began to increase sharply and reached the peak at 1999 and 2000, 12.2% and 9.53% respectively, after which there is a decrease, which last for several years before next increase, probably due to the growth and break of the “dot-com bubble” during the period from 1997 to 2001; the first though occurred at 2002, the year after the break of internet bubble; after 2002, the graph shows a tendency of

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recovery , it began to rise again steeply and reach a high point of 130 in 2006 and the peak of 138 in 2007,with a percentage of 10.5% and 11.15% respectively. A sharp decrease followed 2007, in 2008 the number was reduced to 89 from 138, and further to 52 in 2009. After 2009 the number remained at a comparably steady level around 60. This period of tendency can be due to the European debt crisis which happened in late 2009, as well as the post- crisis influence.

North Asia sample shows a tendency of increase in general. From 1985 to 2001, there is hardly any takeover deal. The deals only began to emerge from 2002 and experience a period of fluctuation until 2009. After 2009, there is a significant increase, and it reached the peak at 2011 of 111 deals, but shows a tendency of gradual decrease afterwards. The increase after 2009 maybe also come from the Europe debt crisis, because of the bad performance of European market, investors tend to seek for new market, which makes Asia a best choice.The number of deals of North Asia is lower compared with that of the Europe in general, and shows different tendency, which can be attributed to the market maturity of the two region.

3.2.2 Tendency of source of funds

Table 5 shows the sample characteristics of source of funds

Panel A. For European targets sample, among all the 12 kinds of source of funds, 34.89% of all the cases are financed by more than one source, 29.48% of all the cases are financed by corporate funds and 19.31% are financed by borrowing. These three sources of financing are the top three sources of financing as to the percentage and account for more than 80% of all the financing sources. For North Asia Target sample, 20.51% deals are financed by more than one source, 63.89% deals are financed by corporate funds, and 12.18% are financed by borrowing. These three sources of funds account for approximately 95 percent of all the cases.

Due to the total number of takeovers in Europe target sample is higher than that in North Asia, in general the number of North Asia sample is lower than that of Europe. The top three sources of funds used in both the European target sample and North Aisa Target sample are the same----mixed financing, corporate funds and

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borrowing. All the other kinds of sources are not used alone so frequently. North Asia has a much higher percentage of takeovers financed by corporate funds.

Panel B. I separate the 12 sources of funds into three categories (fully internal financed, debt financed and stock financed). For the Europe target sample, besides the mixed financing, fully internal financed and debt financed deals account for approximately 30% respectively while stock financed only account for about 4%. However, for the North Asia target sample, fully internal financed deals accounts for 63.89%, the largest percentage, debt financed 14.53% and stock financed only 1.07%. Therefor we can see that: stock financing is the least frequently used source of funds in both Europe and North Asia takeovers; North Asia depends more heavily on fully internal financed than Europe does; mixed financing has a big percentage of all the cases for both Europe and North Asia.

Panel C and Panel D. Shows the sources of funds of European sample and North Asia sample change over years. Stock financed deals are few in the European sample, the tendency remain steady at a low level, not above 10 deals for each year while even fewer in the North Asia sample only 5 deals in total for the whole period from 1995 to 2013 were financed by stock.

We can see from the Figure 7 and 8: for European sample, internal funds financed, debt financed and mixed financing have almost the same tendency as the tendency of the whole sample, all of them experienced big fluctuation from 1996 to 2013, there are two peaks around 1999 and 2007 respectively. For North Asia sample, debt financed and stock financed deals remain almost at a same level with a little rise after 2009, fully internal funds financed has almost the same trend as the whole tendency, which experience a fluctuation before 2009, increase sharply afterwards and reach a peak in 2011 and fall sharply after 2011.

3.2.3 Offer premium

For both samples, the initial and final premium has almost the same trend. For the European target sample, the initial and final offer premium had a higher premium for the first several years from 1986 to 1988, but the takeovers deals are few during those years. Then the premium came to a steady level of around 3% with a little

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fluctuation. With an average of around 2, the standard deviation ranged from 1.5 to 2.5 for the past decade, which also indicated that the premium stays at a comparable steady level. For the sample of North Asia, the premium is a bit different from that of Europe, the initial and final premium in North Asia sample shows a more fluctuated tendency and a lower average. Many years the initial and offer premium were negative, the tendency of the lines of the premium is around 0 and the average initial and final premium are all about -0.01%. the standard deviation is much more than that of Europe, which is about 0.77 for both initial and final offer premium. We can see from the takeover premium that the market of Europe and North Asia has some differences, the European market is more mature than North Asia market, which makes the comparison study meaningful. The sample characteristics for the offer premium are summarized in Table 6 and Figure 9, Figure 10.

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4. Methodology and hypothesis 4.1 Methodology

The general idea of the methodology used in my study is to regress the offer premium(the dependent variable) on the source of funds(the independent variable). To make the result more accurate and reliable, control variables are also used in the regression. And some adjustment will also be added to the variables and the regression.In order to find the relationship between the source of funds and the offer premium, there are several regressions that I run, using both the European sample and North Asia sample. .And for each sample, the regression is run used by both initial offer premium and final offer premium.

The basic methodology I employed is as follows:

Initial offer premium𝑖𝑖 = 𝛼𝛼0+ 𝛽𝛽0𝑋𝑋𝑖𝑖 + 𝛽𝛽1𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖+ 𝛽𝛽2𝑆𝑆𝐷𝐷𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖 + 𝜇𝜇𝑖𝑖 (1)

Final offer premium𝑖𝑖 = 𝛼𝛼0+ 𝛽𝛽0𝑋𝑋𝑖𝑖 + 𝛽𝛽1𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖+ 𝛽𝛽2𝑆𝑆𝐷𝐷𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖 + 𝜇𝜇𝑖𝑖 (2)

Xi represents for all the control variables , which includes

Sizei MTBi TargetRunupi Amihudi Poisonpilli , Toeholdi Pub.Statusi

Industryi Tenderi Paymethodi Attitudei MutiBidderi

All the definitions of the variables are displayed in Table 7.

There are totally three categories of source of funding: cash ,debt ,stock. In order to avoid the dummy variable trap, only two dummies are created, that is: Debti and

Stocki, if the deal is financed by debt, Debt=1, otherwise 0; if the deal is financed by

stock , Stock=1,otherwise 0. In the regression, if Debt=1, Stock=0, it means the deal is financed by debt; if Debt=0, Stock=1, it means the deal is financed by stock; if both of the Debt and Stock are 0 , it means the deal is financed by cash. Therefore the cash here is like a reference, 𝛽𝛽₁represents the difference of influence between debt financing and cash financing on the offer premium, rather than the influence of debt financing alone; similarly, 𝛽𝛽₂ represents for the difference of influence between stock financing and cash financing on the offer premium, rather than the influence of stock financing alone. All the control variables used in the regression can have an influence

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on the offer premium and they are included as control variables to make the effect of the independent variables ( 𝛽𝛽₁ and 𝛽𝛽₂) more accurate and pure.

First I re-run the regression in Betton, Eckbo and Thorhurn(2008a),using the European sample, the result is displayed in Table 8

Second, to explore the relationship between the offer premium and sources of funds based on the first step,I add the Debt dummy and Stock dummy as the independent variables into the regression， the regression was run on both the European sample and the North Asia sample5, the results of the regressions refer to Table 9-1 and Table 10-1.

Offer premium𝑖𝑖 = 𝛼𝛼0+ 𝛽𝛽0𝑋𝑋𝑖𝑖 + 𝛽𝛽1𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖+ 𝛽𝛽2𝑆𝑆𝐷𝐷𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖 + 𝛽𝛽3𝑇𝑇𝑆𝑆𝐷𝐷𝑇𝑇𝑛𝑛′𝑠𝑠 𝑞𝑞 + 𝜇𝜇𝑖𝑖 (3)

Third, to make the results more accurate, I put one more control variable, Tobin’s q of the target companies. , into the regression , to control for the replacement value for different companies, the results are shown in Table 9-2 and Table 10-2. Offer premium𝑖𝑖

= 𝛼𝛼0 + 𝛽𝛽0𝑋𝑋𝑖𝑖+ 𝛽𝛽1𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖 ∗ 𝐶𝐶𝐶𝐶𝑠𝑠ℎ𝑃𝑃𝐶𝐶𝑃𝑃𝑃𝑃𝐷𝐷𝐷𝐷ℎ𝑆𝑆𝑜𝑜𝑖𝑖 + 𝛽𝛽2𝑆𝑆𝐷𝐷𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖 ∗ 𝐶𝐶𝐶𝐶𝑠𝑠ℎ𝑃𝑃𝐶𝐶𝑃𝑃𝑃𝑃𝐷𝐷𝐷𝐷ℎ𝑆𝑆𝑜𝑜𝑖𝑖

+ 𝜇𝜇𝑖𝑖 (4)

Fourth, I make some adjustment about the independent variable. Since the method of payment for a takeover deal can be cash, stock or the mix of these two, the data of the takeover deals I collected includes all these three method of payment. But what I would like to study in this paper is whether the sources of funds have an effect on the offer premium, which means in theory I need to focus on the cash bids, or the takeover deals which are paid by cash. In order to solve this problem, I made an adjustment on the independent variables, instead of using Debt dummy, I adjusted the variable by multiplied the Debt dummy by the payment method dummy variable , since the definition of the payment method dummy is “equal to 1 when it is paid by cash, equal to 0 otherwise”, Debt dummy*paymethod of cash will make the regression only focus on the cash bids, to give a more accurate result. For the Stock

5_{For the next four steps, the regression are all employed using both the European sample and the North Asia}

sample

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dummy, I did the same adjustment . In short, instead of regress the offer premium on the Debt dummy and Stock dummy, I regress the offer premium on.

Finally, I regress the offer premium on Debt dummy * paymethod of cash and Stock dummy*paymethod of cash and added Tobin’s q as one more control variable as well.

Offer premium𝑖𝑖

= 𝛼𝛼0+ 𝛽𝛽0𝑋𝑋𝑖𝑖+ 𝛽𝛽1𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖 ∗ 𝐶𝐶𝐶𝐶𝑠𝑠ℎ𝑃𝑃𝐶𝐶𝑃𝑃𝑃𝑃𝐷𝐷𝐷𝐷ℎ𝑆𝑆𝑜𝑜𝑖𝑖 + 𝛽𝛽2𝑆𝑆𝐷𝐷𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖 ∗ 𝐶𝐶𝐶𝐶𝑠𝑠ℎ𝑃𝑃𝐶𝐶𝑃𝑃𝑃𝑃𝐷𝐷𝐷𝐷ℎ𝑆𝑆𝑜𝑜𝑖𝑖

+ 𝛽𝛽3𝑇𝑇𝑆𝑆𝐷𝐷𝑇𝑇𝑛𝑛′𝑠𝑠 𝑞𝑞 + 𝜇𝜇𝑖𝑖 (5)

4.2 Hypothesis

According to the pecking order theory, due to asymmetric information, the cost of financing differs. Firms have different priorities for different sources of financing. Normally, they put internal funds in the first order, and then debt, finally the equity. Therefore investors would like to pay a lower premium for equity or debt compared with internal funds. Hence I hypothesize that the equity and debt source of financing will lead to a lower premium compared with the internal funds, for which in equation (1) and (2) 𝛽𝛽₁𝐶𝐶𝑛𝑛𝑜𝑜 𝛽𝛽₂ should have a significant negative value.

However, since North Asia is still a growing market, the takeover market is not as mature as the Europe, the results of the North Asia may be inconsistent with the hypothesis mentioned above.

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5. Empirical results, analysis and discussion

In this section, I display the results of the study, analyze the regression results, and present the main findings on the effect of source of funds on the offer premium. A comparison between the results of European sample and the North Asia sample will also be presented.

Before regression, I winsorize the initial offer premium and the final offer premium of the European sample as well as the North Asia sample, which means that I cut off the outliers of the data, and only focus on the main part of the data (above 10 percentile and under 90 percentile), the Figure 11 and Figure12 shows the before and after winsorizing situation of the data for the European sample and the North Asia sample respectively. First I re-run the regression of the handbook of Betton,Eckbo, and Thorhurn(2008a) using the European sample that I collected, in order to test the correctness of the data and the model design. Since the results of my own sample and the results are comparable, we can conclude that the model can be relied on for a further study.And then I regress initial offer premium and final offer premium on the Debt dummy and Stock dummy, as well as the control variables, using the methodology discussed in the last section, for both samples. There are totally four regressions that I run for each sample. The first regression is the basic regression, others are meant to improve and perfect the first regression. The results are shown in Table 9 and Table 10.Table 9 shows the results of the OLS regression analysis on European sample of 1238 cases. The results of each regression are displayed in Table9-1, Table 9-2, Table 9-3 and Table 9-4. Table9-1shows the basic regression that I use in the paper ,which regress offer premium on Debt dummy and Stock dummy, with all the control variables; Table9-2 add one more control variable, Tobin’s q of the target company, based on the regression of Table9-1; Table 9-3 make an adjustment on the independent variables(Debt dummy and Stock dummy),based on the regression of Table 9-1; Table 9-4 add Tobin’s q and make the adjustment of the independent variables, the combination of Table9-3 and Table 9-4.

Similarly, Table 10 shows the results of the OLS regression analysis on North Asia sample of 468 cases. There are totally four regressions, and the results of each regression are displayed in Table10-1,Table 10-2,Table10-3 and Table 10-4. The first regression is the basic regression, others are meant to improve and perfect the first

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regression. Table10-1 shows the basic regression that I use in the paper ,which regress offer premium on Debt dummy and Stock dummy, with all the control variables; Table10-2 add one more control variable, Tobin’s q of the target company, based on the regression of Table10-1; Table 10-3 make an adjustment on the independent variables(Debt dummy and Stock dummy),based on the regression of Table 10-1; Table 10-4 add Tobin’s q and make the adjustment of the independent variables, the combination of Table10-3 and Table 10-4. A summary of the coefficients of the independent variables of the four regressions for both samples are shown in Table 11-1 and Table 11-2.

5.1 The determinants of offer premium

In this paper ,Initial offer premium is defined as ln (𝑃𝑃_{𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖}/𝑃𝑃₋₄₂), and final offer premium is defined as ln (𝑃𝑃_{𝑓𝑓𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖}/𝑃𝑃₋₄₂), where 𝑃𝑃_{𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖} is the initial offer price per share of the target company, 𝑃𝑃_{𝑓𝑓𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖} is the final offer price per share of the target company, 𝑃𝑃₋₄₂ is the stock price 42 trading days prior to the announcement date. The announcement date of sample ranged from 01-01-1985 to 31-08-2013

For the European sample, as shown in the first two rows in the Table 9(same for four tables), the mean value of initial offer premium is 29% and increases to 31% by the time of final bid, with a standard deviation of approximately 20%.For each table, there are four columns. Columns(1) and (2) run regressions of initial offer premium; Columns (3) and (4) run regressions of final offer premium. Columns (2) and (4) are the regressions with year fixed effects, (1) and (3) are the regressions without year fixed effects.

For the North Asia sample, as shown in the first two rown in the Table 10(same for four tables ), the mean value of initial offer premium is -9.5% and increases to -8.7% by the time of final bid, with a standard deviation of proximately 77%.For each table, there are four columns. Columns(1) and (2) run regressions of initial offer premium; Columns (3) and (4) run regressions of final offer premium. Columns (2) and (4) are the regressions with year fixed effects, (1) and (3) are the regressions without year fixed effects.

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Comparing the two samples, the offer premium of the European sample is much higher than that of the North Asia sample, which suggests European bidders pay more premium than the North Asia bidder to take a target company. And the standard deviation of the European sample is much lower than that of the North Asia sample, which indicates that the premium of North Aisa sample experience more fluctuation than the European sample.

5.2 Effect of control variables and comparison of European and North Asia sample

The control variables I use are based on the model of Betton,Eckbo, and Thorhurn(2008a), which are grouped into three categories, that is , target characteristics, bidder characteristics and deal characteristics. In the second and forth regression, I included Tobin’s q as control variable as well. All the definitions of the control variables are summarized in Table 7. The effect of each control variables are discussed as follows:

5.2.1 Target characteristics

Sizei is the natural logarithm of the target market capitalization on 42 trading

days prior to the initial bid, which is used to control for the impact that different sizes of the target companies can induce on the offer premium. Sizei shows a negative

relationship with offer premium and the result is statistically significant at 1% level. The coefficient experiences a slight decrease from initial bid to the final bid, and not a big difference between the four regressions. For instance for the first column of the first regression in Table 9-1, 1% increase of the Size will lead to 0.015% decrease of the initial offer premium. For the North Asia sample, the results are also significant at 1% significant level, and represents a negative relation with the offer premium. The results for both sample are consistent with the results from Betton,Eckbo, and Thorhurn(2008a) , which proves again that the size of the target company is an important factor explaining the offer premium.

BTMi is the book to market value of the target companies, which is calculated as

the target company's book value divided by market capitalization from its balance sheet on the announcement day. The data I collected from Datastream is market to book value, the data I use here is the reciprocal, that is book to market value, which is

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consistent with the variable used in Betton,Eckbo, and Thorhurn(2008a). The influence of BTM on the offer premium is around 0.006% to 0.007% for the four regressions, and they are all significant at 1% significant level. But for the North Asia sample, the results are not significant and the coefficient are very small, which indicates a weak relation. This can be due to the different situation of the two markets.

TargetRunupi is Natural logarithm of the target stock price on day -42 relative to

day -1. It represents for how the stock of the target company performed before the announcement date, which is a very important factor that bidders will take into account when offer the price. In my regression, 1% increase of TargetRunny can lead to more than 0.5% increase of the offer premium, which in the regression of Betton,Eckbo, and Thorhurn(2008a) is 0.8%. The result is also significant at 1% significant level. For the North Asia sample, 1% increase of the target runup can induce 0.7% increase for the offer premium. The results are also significant at 1% significant level. Both of my samples suggest a strong and significant relation between the target runup and the offer premium ,which is consistent with prior literature.

Amihudi is a variable brought about by Amihud (2002) used to measure

illiquidity of the stock of the target, which reflects the impact of order flow on price. It is calculated as the average of |Ri|/(piSi). Ri is the holding period return, pi is the closing price and Si is the number of shares traded. i ranges from -250 to -42. The result is not significant, all though the coefficient is very large for this control variable for both samples.

Poisonpilli also known as shareholder rights plan, It is a type of defensive tactic

used by the target company. The use of Poison pill will increase the difficulty of the takeover process, which might force the bidders to pay a higher premium. For the European sample, the effect of the poison pill on offer premium seems to be affected by the year fixed effects, for example in Table9-1, column (2) and column (4), which are the results with a year fixed effects, are about 0.04% higher than column(1) and column (3), which are the results without the year fixed effects. Only the column (3) is significant at 5% significant level, others are all not significant. But for the North Asia sample, the poison pill doesn’t show an effect on the premium, the results are all omitted, probably due to the not mature market in Asia, few Poison pill was used.

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Tobin's q is calculated by dividing the market value of a company by the replacement value of the book equity. Always used to measure the value of a company (McConnell and Servaes ,1990). Servaes (1991) finds that the magnitude of the target firm’s Tobin’s q ratio is an important determinant of takeover gains, but the results of the bidder’s q ratio are not significant. Therefore, target’s Tobin’s q was also added in the regression as a control variable. The results of the regression with Tobin’s q are shown in the Table 9-2 and Table 9-4 for European sample. The coefficient is around 0.001% to 0.002%, which does not make a big difference; and the results for European sample are not significant. The R square only increases 0.001 for the first column if we compare Table 9-1 and Table9-2.

But as for the North Asia sample, the results of the coefficients of the Tobin’s q are significant at 1% significance level, for example in the first column of Table 10-2, 1% increase of the q ratio will induce 6% decrease in the offer premium. The R-square increases from 0.202 to 0.265 after adding Tobin’s q as a control variable, which means the Tobin’s q gives more explanation power to the results of the North Asia sample.

5.2.2 Bidder Characteristics

Toeholdi is the fraction target shares owned by the initial control bidder prior to

announcing the bid. Whether a bidder owns a percentage of the shares of the target company will also have an influence on the offer premium. For the European sample, the results are mostly statistically significant at 1% level. The deals with the bidder having a toehold will have around 0.038% difference compared with the deals without a toehold according to the first column of Table 9-1. Compared with final offer premium, the influence of the Toehold is stronger for the influence of initial offer premium. the value of results in column (2) and (4) are higher than the value in column (1) and (3) respectively, which indicates that the regression with the year fixed effects are stronger. For the North Asia sample, the results are not significant, which shows maybe the Toehold is not an decisive factor for North Asia takeover market.

Pub.Statusi is a dummy variable which refer to whether the bidder is publicly

trade. For the European sample, publicly traded company has to pay around 0.035%

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higher premium to the target company than the non-publicly traded company, which is about the same amount four the regressions and the regressions in the four table. This result is significant at a 1% significant level. But for the North Asia sample, the result the more fluctuated between different regressions across the four tables, which ranged from0.05% to 0.12 %, and the results are not significant.

Industryi is a dummy variable created to indicate whether the target company and

the bidder company are in the same industry. The industry was represented by the four-digit primary SIC 6code. For the European sample, if the target and the bidder are in the same industry, the offer premium will increase for around 1.7% compared with if they are not in the same industry. The results are not significant. For the North Asia sample, there is a difference occurring between the regressions with year fixed effects and the regressions without year fixed effects. For example, in Table 10-1, the results of column (1) and (3) are from the regression without year fixed effects, are 0.11% and 0.0998% respectively; The results of (2)and(4) , which are from the regressions with year fixed effects, and the results are 0.059% and 0.048% respectively. The results are not significant, either.

5.2.3 Deal Characteristics

Tenderi is a dummy variable which indicates that whether the deal is a tender

offer or merger offer. For the European sample, the results are significant for the final offer premium regression, with 0.0241% and 0.0189% respectively for the results without and with the year fixed effects in Table 9-1. For the North Asia sample, the results are not significant. This result are different from the results from Betton,Eckbo, and Thorhurn(2008a), which is significant with a negative relationship. The difference may come from the sample difference or the process of handling data.

Paymethodi is a variable represents for the method of payment, the method can

be cash, and stock or mixed. For the European sample, the results are significant for

6 _The_{Standard Industrial Classification}_{(SIC) system is a hierarchical coding structure developed by the U.S.}

government and used widely in govemment and private-sector data. It attempts to classify all forms of economic activity—including government and nonprofit entities—in order to provide a common statistical and conceptual framework for data collection and analysis

Readmore: http://www.referenceforbusiness.com/encyclopedia/Sel-Str/Standard-Industrial-Classification-System-S IC.html#ixzz2jyTWiiWD

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the Table 9-1 and Table 9-2 when there are no year fixed effects. Probably because the adjustment on the control variable is to use the method of payment of cash, to multiply the debt dummy and stock dummy. The coefficient is around 0.02%, which is similar to the result that Betton,Eckbo, and Thorhurn(2008a) found. The number for the North Asia sample is ,for example in Table 10-1,0.034%,0.1%,0.027%,0.1% for column (1)(2)(3)(4).The result is also not significant, this can be due to the different sample from Europe.

Attitudei represents whether the target is friendly or not against the takeover. For

the European sample, the results are significant for the final offer premium regressions, around 0.08% without year fixed effects and 0.05% with year fixed effects. For the North Asia sample, the results are not significant.

MutiBidderi is a variable indicate whether the bidder has a rival bidder. Since for

the initial offer ,there cannot be more than one bidder, so the regression for the initial offer premium don’s include this control variable; This variable is included in the last two regressions, the results of which are represented in the column (3) and (4) in each table, the regression for the final offer premium. For the European sample, the results are around 0.026% and 0.037% for the regressions without and with year fixed effects, the results are significant, which indicates that the offer premium tend to be higher when there are more bidders competing for the same target company. For the North Asia sample, the numbers are around0.65% and 0.8% , which are also significant.

Announced during 2009-2013 after European debt. Since the European debt crisis can have an big influence on the takeover activities, not only for Europe but also Asia, for the business of the world now connect with each other very closely, and the Asia economy rely on the European economy to a very big extent, I add one control variable to study how the debt crisis can influence the takeover deals and offer premium. In order to avoid the multi-collinearity, this variable cannot be included with the year fixed effects. So the regressions with this variable are only the one of column(1) and (3). The results are significant at 1% level for European sample, 0.034% for initial offer premium regression and 0.0427% for final offer premium regression in Table 9-1. But the results are not significant for the Asia sample, which suggests that the Europe suffers more than Asia during the debt crisis.

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5.3 Effect of sources of funds and comparison of European and North Asia sample

As for the source of funds, there are totally 12 different kinds that I got from the Thomson one database, I group them into three categories, which are internal fund, debt source and stock source. The detailed information and definition refer to Table 2. And in order to study the influence of the source of funds on the offer premium, I create two dummy variables to represent these three categories of sources of funds: Debtdummy and Stock dummy. Debt dummy equals to 1 when the source of funds are debt, meaning the money that the bidder takeover the target comes from debt, which can be borrowing, loan and so on, and equals to 0 otherwise; Stock dummy are created in the similar way, equals to 1 when the source of funds are stock, that is the money comes from common stock offering, preferred stock offering and so on., and equals to 0 otherwise. With these two dummy variables, the three different categories of sources of funds can be represented: “debt dummy = 1, stock dummy = 0” represents for the debt source of funds; “debt dummy = 0, stock dummy =1” represents for the stock source of funds; “debt dummy = 0, stock dummy = 0” represents for the internal fund source. 7Therefore, the coefficient of the Debt dummy should be explained as the difference of the impact on the offer premium that debt source has and the internal fund has, in other words, the coefficient of the Debt dummy represents for the impact difference between the debt source and the internal fund on the offer premium. Similarly, the coefficient of the Stock dummy represents for the impact difference between the stock source and the internal fund on the offer premium. therefore, the influence that the internal fund can have on the offer premium is a reference.

For the European sample, Table 9-1 gives the basic regression result of how the source of funds can affect the offer premium; Table 9-2 is the results base on the previous regression, but with one more control variable—target’s tobin’s q; Table 9-3 also base on the basic regression of Table 9-1, with adjustment of the independent variables (debt dummy and stock dummy), I multiply the debt dummy and stock dummy with the dummy variable Paymethod, which equals to 1 when the method of payment is cash, and equals to 0 otherwise. This gives the economic meaning that this

7 _{For detail information, refer to the methodology section of this paper}

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(34)

regression only focus on the deals that are paid by cash. Table 9-4 is kind of combination of the first three regressions, which base on the first basic regression , with the tobin’s q as control variable and the adjustment of the independent variables. The coefficients of the independent variables of the four tables are summarized in Table 11-1.

Only the results of Stock dummy are significant, when there are year fixed effects, the results of Debt dummy are not significant. For the row ”EU”, the results are all negative, meaning that compared with internal fund source, the stock source has less influence on the offer premium. Including tobin’s q doesn’t make a big difference, adjustment of the independent variables make the difference on the offer premium larger, but the impact difference on the final offer premium with year fixed effects, column (4), stays almost the same, around -0.0305, and significant for all the situation. The coefficient of the debt dummy in Table 9-1 are negative, which mean the debt source also has less influence on the offer premium than the internal funds do, although the results are not significant. To interpret the results, for example, in column (2), row EU, stock dummy: compared with 1% increase of internal funds, 1% increase of stock source of funds will lead to -0.0241% change of the offer premium. This is for the initial offer premium with year fixed effects.

Similarly, for the North Asia sample, Table 10-1 gives the basic regression result of how the source of funds can affect the offer premium; Table 10-2 is the results base on the previous regression, but with one more control variable—target’s tobin’s q; Table 10-3 also base on the basic regression of Table 10-1, with adjustment of the independent variables (debt dummy and stock dummy), I multiply the debt dummy and stock dummy with the dummy variable Paymethod, which equals to 1 when the method of payment is cash, and equals to 0 otherwise. This gives the economic meaning that this regression only focuses on the deals that are paid by cash. Table 10-4 is kind of combination of the first three regressions, which base on the first basic regression , with the tobin’s q as control variable and the adjustment of the independent variables. The coefficients of the independent variables of the four tables are summarized in Table 11-2.

The results of the debt dummy are statistically significant at 1% level, for all the regressions. The results are positive, which means for the North Asia sample, debt

Is offer premium affected by source of funds? : a comparison between European and North Asia target takeovers.

Is offer premium affected by source of funds?

A comparison between European and North Asia target takeovers

Acknowledgements

Is offer premium affected by source of funds?

A comparison between European and North Asia target takeovers

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