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The Quarterly Review of Economics and Finance 50 (2010) 471–484

Contents lists available at ScienceDirect

The Quarterly Review of Economics and Finance

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eterminants of the method of payment in mergers and acquisitions�

hmad Ismail a, Andreas Krauseb,∗

United Arab Emirates University, College of Business and Economics, P.O. Box 17555, Al Ain, United Arab EmiratesUniversity of Bath, School of Management, Claverton Down, Bath BA2 7AY, United Kingdom

r t i c l e i n f o

rticle history:eceived 21 September 2008eceived in revised form 4 June 2010ccepted 14 June 2010

a b s t r a c t

We empirically investigate the determinants of the payment form in mergers and acquisitions and intro-duce new variables on the target and acquirer investment characteristics to evaluate whether the concernsof target and acquirer shareholders are taken into account. Our sample encompasses mergers between

vailable online 23 June 2010

eywords:ergers

ayment formnvestment characteristics

publicly listed US companies from 1985 to 2004. Similarly we also consider the determinants of announce-ment returns using the same set of variables. We establish the relevance of a previously unreportedvariable for the determination of the payment form, the correlation of returns between target and acquirer,besides the more established determinants hostile takeovers, and defence mechanisms; weak evidenceis found for the significance of budget constraints and no evidence for asymmetric information or taxconsiderations being a relevant factor. We do not find that announcement returns are explained by the

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variables considered.© 2010 The Board of Tru

The choice of payment form in mergers and acquisitions – cash,hares, or a combination of these – can have a substantial impactn the successful completion of the transaction. It is generallyegarded to be preferable by shareholders of the target companyo receive a cash payment rather than shares of the bidding com-any. Empirical evidence furthermore shows a significantly highernnouncement return to the shares of the target company for cashffers than for share offers.

In this paper we provide an empirical investigation into the maineterminants of the payment form by introducing investment char-cteristics of the two companies involved as additional variables,hich have not been considered in previous studies. We include

nto our analysis the growth rate and return volatility of the twoompanies involved, their return correlation as well as the syn-rgies generated from the merger. We will not only focus on theecision whether payment is conducted in cash or shares, but will

ook in particular at mixed offers and how the mix between sharesnd cash is determined. Again, the determinants of the structure of

ixed offers have received very limited attention in the literature

hus far and we thereby extend the literature in this field.We find investment characteristics to be important for the pay-

ent form, the target growth rate and the correlation between the

� We would like to thank the referees for their careful suggestions on our paperhat helped us to improve its quality significantly.∗ Corresponding author. Tel.: +44 1225 383771; fax: +44 1225 386473.

E-mail addresses: ahmadismail@uaeu.ac.ae (A. Ismail), mnsak@bath.ac.ukA. Krause).

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062-9769/$ – see front matter © 2010 The Board of Trustees of the University of Illinoisoi:10.1016/j.qref.2010.06.003

of the University of Illinois. Published by Elsevier B.V. All rights reserved.

wo companies merging are statistically significant, the existencef defence mechanisms at the acquirer and the merger premiumaid are also statistically significant, as is the availability of cashith the acquirer. A range of other variables considered in the lit-

rature we do not find to have a significant impact on the paymentorm, most notably the valuation of the acquirer. The announce-

ent returns of the acquirer and the target we find to be quitenresponsive to any variables we investigate.

The first section of this paper provides a brief overview of theurrent evidence for the factors determining the payment formn mergers and acquisitions. Section two introduces the empiri-al technique used in our analysis and the third section describeshe dataset we used before in Section 4 we conduct our empiricalnalysis. Finally, Section 5 will conclude our findings.

. Determinants of the payment form in the literature

Beginning with Myers and Majluf (1984) it has been arguedhat asymmetric information between the bidder and the target onhe value of the bidder shares allows the bidder to offer shares ifhese are overvalued and to offer cash if they are undervalued. Thismpact of asymmetric information has been confirmed as beingelevant for the choice of the payment form in a number of empir-cal studies, see Travlos (1987), Hansen (1987), Fishman (1989),

erkovitch and Narayanan (1990), Eckbo, Giammarino, and Heinkel1990), Cornu and Isakov (2000), Linn and Switzer (2001), Shleifernd Vishny (2003), and Rhodes-Kropf and Viswanathan (2004),mongst others. In contrast, Cornett and De (1991) find evidenceontradicting the role of asymmetric information.

. Published by Elsevier B.V. All rights reserved.

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72 A. Ismail, A. Krause / The Quarterly Review

Another frequently cited aspect for choosing the payment forms the influence of taxation. In cash offers the target shareholdersften are liable to taxation on the profits they have made and thusould require a higher premium. The bidder will thus accumulatehigher goodwill whose depreciation will reduce future profits

nd thus tax burdens. Depending on the importance to show highrofits for the bidder and the amount of additional tax to be paidy target shareholders, cash or shares will be offered. A numberf empirical studies, e.g. Wansley, Lane, and Yang (1983), Harris,ranks, and Mayer (1987), and Huang and Walking (1987), supporthe role taxation plays in the determination of the payment form.

The third major factor commonly mentioned to determine theayment form is the aspect of managerial control. By using sharess payment, existing shareholders are diluting their stake in theidding company and hence losing control over the company.mpirical evidence in support of this aspect can be found in Harrisnd Raviv (1988), Stulz (1988), Eckbo et al. (1990), Amihud, Lev,nd Travlos (1990), Blackburn, Dark, and Hanson (1997), Yook,angopadhyay, and McCabe (1999), and Faccio and Masulis (2005).

A wide range of additional factors have been investigated andound to be relevant for the payment form in mergers and acqui-itions. The relative size of the two companies will be relevants the larger amount of cash required for a large target com-any might be difficult to obtain, see Grullon, Michaely, and Swary1997), Moeller, Schlingenmann, and Stulz (2004), and Swieringand Schauten (2008). Martin (1996) and Ghosh and Ruland (1998),owever, refute the importance of the size of the companies

nvolved. A bidder which has large growth opportunities will moreommonly seek to pay acquisitions by means of shares as thatay they can preserve their cash reserves to finance investments

equired for their growth, see Martin (1996), Zhang (2003), andwieringa and Schauten (2008). Schwert (2000) investigates thempact a hostile takeover has on the payment form.

While most of the determinants of the payment forms consid-red thus far are based on misvaluations, moral hazard, asymmetricnformation, tax effects and budget constraints, the main namedeason for conducting mergers, synergy effects, receives littlettention in the determination of the payment form, along withnvestment characteristics of the two companies involved. Thismission seems surprising given the importance synergy effectsre given in official statements on the merger rationale and alsohe impact investment characteristics, such as risk and return, haven investors’ decisions, apart from the market valuation of compa-ies. Our paper seeks to address these omissions by including thoseariables into our model.

. Empirical methodology

When investigating the payment form of mergers and acquisi-ions, we use the fraction of shares as part of the total price offeredy the acquirer to the target shareholders as the dependent vari-ble. This variable will be in the interval [0; 1], although the acquireright want to offer a fraction of shares above one, thus requiring

n additional cash payment by target shareholders, or a negativeraction of shares, requiring target shareholders to sell the acquirerheir own stock. With such an option not realistically available tocquirers, the observed variable can thus be interpreted as cen-ored such that the observed fraction of shares, s*, and the actuallyesired fraction of shares, s, are related as follows:

∗ ={

1 if s > 1s if 0 ≤ s ≤ 10 if s < 0

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onomics and Finance 50 (2010) 471–484

We thus have established that the fraction of shares offereds a censored variable and the appropriate econometric method-logy to analyze such censored dependent variables is the tobitodel. In order to account for the endogeneity of variables we

sed an instrumental-variable approach and found that using thearget firm’s average stock return in the pre-merger year as annstrument for the growth rate of the target company works best

ith our dataset. The target firm’s average stock return in the pre-erger period should be an exogenous measure of the target firm’s

xpected future returns; it will be correlated with the expectedeturn of the target firm but it is unlikely to have an impact on theethod of payment in the merger, other than through the effect on

he perception of the firm’s performance in the market. It is worthoting that in event studies, in addition to the market model andhe market-adjusted return model, one of the popular models usedo estimate expected returns is the mean adjusted return modelhich assumes that the expected return is the average return

arned by this security during a certain estimation period; studieshat used this model included Masulis (1980). Therefore, we believehere is a good reason to use the average stock return in the pre-

erger year as an instrumental variable. This view is confirmedhen we investigate the statistics of the instrumental-variable

egression; as detailed at the bottom of Table 4 we find valuesf the F-test commonly above a value of 10 suggesting the rele-ance and validity of our instruments. Also, given that the numberf instruments does not exceed the number of parameters esti-ated, overidentification is generally not a concern, as confirmed

y the Sargan test.The announcement returns are investigated in a linear regres-

ion using a range of dependent variables whose parameters arestimated using 2SLS, where the instrument used is the acquirerarket to Book ratio to account for the endogeneity of the payment

orm and the acquirer return. Our choice of the Market to Book ratios an instrument is justified by the fact that it is expected to be cor-elated with the stock return as consistently shown when usingama-French 3-factor models. The statistics of the instrumental-ariable regression shows values of the F-test indicating statisticalignificance although the values are well below 10, suggesting thathe instruments might be weak, see the bottom of Tables 5 and 6.s a further test for the validity of our instruments we conductedSargan test and were not able to reject the validity of the instru-ents given the very low values associated with this test. Thus we

an confirm with some confidence that the instruments used arealid and well chosen.

. Data and descriptive statistics

.1. Sample selection

The sample for our investigation was determined by identify-ng all mergers and acquisitions announced by US publicly listedcquirers for publicly listed targets in the time period from 1anuary 1985 to 22 April 2004 using the Thomson Financial SDCatabase. From this sample we excluded all financial institutionss acquirers and any deals with a value below US$ 1 million. Weurthermore only considered those deals that were completed andesulted in the acquirer gaining an ownership stake of at least 50%.

From this sample we only considered those deals where both thecquirer and the target have share price data available in the CRSP

atabase and accounting information on COMPUSTAT. With theseestrictions we identified 1670 deals. In order to identify the syn-rgy effects we searched the SEC filings and media for estimatedost savings and revenue enhancements from the proposed dealnd were able to identify 337 completed deals with all available

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A. Ismail, A. Krause / The Quarterly Review

nformation. Our final sample was further reduced due to the avail-bility of certain variables we included in our regressions. While thenal sample size seems to be small compared to the total numberf deals in the market, our sample size is well in line with similarmpirical investigations.

.2. Determination of explanatory variables and predicted signs

We use a range of potential explanatory variables for the pay-ent form that are related to the various theories proposed in the

iterature and briefly outlined above. The first group of variables arehose characterizing the investment characteristics of the companiesnvolved in the merger that are most commonly used in portfo-io selection of investors. The variables considered are the growthates of the stock prices of the target and acquirer, their respec-ive volatilities and the correlation between the two firms’ stocketurns. We determine the mean growth rate of the stock pricef the target and acquirer, TARG GROW and ACQ GROW, as wells the target and acquirer volatility, TARG VOL and ACQ VOL, andhe correlation between returns, CORR, from daily data in the timeindow from 210 to 20 trading days prior to the merger announce-ent. We annualize our daily estimate to annual data over 252

rading days. We would expect a higher growth rate of the targeto lead to more shares being offered as payment in the merger,ecause the high-growth rate would make it attractive to maintainhe resources with a view to make further investments into theigh-growth business. The opposite is true for an acquirer, wherehigher growth rate in a share offer would mean that the good

rospects of the company are diluted to the target shareholdersuch that we would expect a negative relationship. The volatili-ies of the target and acquirer should both be positively related tohe fraction of shares used. To see this consider that when offer-ng cash, the target shareholders do give up any potential futureains from holding the shares; these potential gains are larger theigher the volatility of the shares is and therefore share offers areore attractive. Companies which have a high correlation will be

ery much alike and therefore offering shares will result in a like-or-like exchange between companies, such that shareholders gethe additional benefit of the synergies without a change in theharacteristics of their shareholdings.

A commonly used explanation for the choice of payment forms the taxation of any potential capital gains. As in Fuller (2003) wepproximate the size of capital gains and proxy for the subsequentax burden by the cumulative performance of the target over theyears prior to the merger announcement, denoted PERFORM. If

he tax liability is a major concern for investors, high capital gainshould result in more share offers; we would therefore expect aositive sign in a regression of this variable.

The third group of variables is related to the asymmetric infor-ation hypothesis, which states that an acquirer with overvalued

hares will tend to offer more shares as payment. Using Tobin’s Qo measure the valuation of companies, we determine ACQ TOBINs the ratio of book and market value of the company. Similarlye determine TARG TOBIN and also expect a positive relationship

etween this variable and the fraction of shares used. If the targetompany is highly valued, the acquirer will be reluctant to use casho pay shareholders but use shares as in that case the overvaluations shared with target shareholders.

An obvious limitation to the free choice of the payment formould be any budget constraints on the cash available or, equiva-

ently, the ability to raise sufficient debt to finance cash payments.he leverages of the target and acquirer, TARG LEV and ACQ LEV,re obtained as the ratio of the debt and the book value of assets athe end of the fiscal year prior to the merger announcement. A higheverage of the target or acquirer will obviously limit the ability to

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onomics and Finance 50 (2010) 471–484 473

aise sufficient debt and we should expect to find a positive rela-ionship between these variables and the fraction of shares offered.he amount of cash available to the acquirer, ACQ CASH, is deter-ined as the ratio of cash plus marketable securities to the book

alue of assets as taken from the accounts at the end of the fiscalear prior to the merger announcement. The free cash flow of thecquirer is similarly determined as the sales minus cost of goodsold, selling and general administrative expenses, taxes, change inet operating working capital and change in capital expenditures.e then divide this number by the book value of assets to obtain the

ariable ACQ FCF. Having cash available and a strong free cash flowill obviously make the offering of cash easier and we would expectnegative relationship between these variables and the amount of

hares offered. The size of the companies involved will also affecthether a budget constraint becomes binding. We determine the

elative size of the target to the acquirer, REL SIZE, defined as theatio of the market capitalization of the target to that of the acquirermonths prior to the merger announcement. Two companies of a

imilar size or even a company taking over a larger target will faceore problems financing a cash offer than a company taking overmuch smaller target; we would thus expect a negative relation-

hip between those variables. The market value of the acquirer,CQ MV, determined as the market capitalization of the acquirer 2onths prior to the merger announcement, should have a positive

mpact; a larger acquirer is more easily able to offer cash as accesso debt markets is easier and targets are relatively small. Finally welso include the risk-free rate, RATE, in form of the yield of 10-yearS government bonds, with the aim to control for times of high

nterest rates that might increase the costs of using debt to financecquisitions.

Another hypothesis put forward is that of managerial entrench-ent. In order to assess this hypothesis we include a number

f defence mechanisms as well as a corporate governance indexnto our regression. In particular we consider a staggered board,CQ BOARD and TARG BOARD, the existence of poison pills,CQ PILL and TARG PILL, limited directors’ liability, ACQ DIRLIABnd TARG DIRLIAB as well as a compensation plan for the direc-ors in case of a change of control, ACQ PLAN and TARG PLAN. Allhese variables are dummy variables which are 1 if the defence

echanism is present and 0 otherwise. We also use a corpo-ate governance index for the target and acquirer, TARG GOV andCQ GOV. This index is based on the IRRC database and measures

he number of anti-takeover provisions with a higher score imply-ng more anti-takeover measures. The maximum score is 24 andor more details on the construction of this index see Gompers,shii, and Metrick (2003). With the management of acquirers being

ore entrenched, we would expect them to offer more shares as theilution of their own holdings or that of other friendly shareholdersecomes less relevant, thus a positive relationship is expected. Thepposite is true for the target; here the acquirer has to overcomehe entrenchment of the existing shareholders which is more easilychieved when offering cash to shareholders. For targets we wouldhus expect to find a negative relationship between the variablesonsidered and the fraction of shares offered.

In addition to the variables introduced above, we also includesmall number of control variables. The premium paid by the

cquirer, PREMIUM, is determined as the ratio of the deal valuend the market capitalization of the target. The deal value is theotal value of the transaction as paid by the acquirer and the mar-et capitalization is the value of the target 2 months prior to the

erger announcement. A merger with a high premium will gener-

lly be associated with a larger fraction of cash being offered in lineith the established literature. Another variable we control for is

he amount of synergies generated by the merger, SYNERGY, a vari-ble most often claimed to be the main motivator for the merger.

474 A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484

Table 1Overview of variables.

Variable Description Expected sign Hypothesis

TARG GROW Growth rate of target Positive

Investmentcharacteristics

ACQ GROW Growth rate of acquirer NegativeTARG VOL Volatility of target PositiveACQ VOL Volatility of acquirer PositiveCORR Correlation between target and acquirer Positive

PERFORM Capital gains prior to merger Positive Taxation

TARG TOBIN Tobin’s Q of target Positive AsymmetricinformationACQ TOBIN Tobin’s Q of acquirer Positive

TARG LEV Leverage of target Negative

Budget constraints

ACQ LEV Leverage of acquirer NegativeACQ FCF Free cash flow of acquirer NegativeACQ CASH Cash holdings of acquirer NegativeREL SIZE Relative size of target and acquirer NegativeACQ MV Market value of acquirer PositiveRATE Risk-free interest rate Negative

ACQ BOARD Existence of a staggered board at the acquirer Positive

Managerialentrenchment

ACQ PILL Existence of a poison pill at the acquirer PositiveACQ DIRLIAB Existence of limited director’s liability at the acquirer PositiveACQ PLAN Existence of a compensation plan at the acquirer PositiveACQ GOV Corporate governance index of the acquirer PositiveTARG BOARD Existence of a staggered board at the target NegativeTARG PILL Existence of a poison pill at the target NegativeTARG DIRLIAB Existence of limited director’s liability at the target NegativeTARG PLAN Existence of a compensation plan at the target NegativeTARG GOV Corporate governance index of the target Negative

PREMIUM Premium paid by acquirer NegativeControl variablesSYNERGY Synergies claimed through merger Positive

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HOSTILE Dummy variable for hostile takeovers

his table shows an overview of the explanatory variables, their brief description, the hypothesis to which they belong. Those variables which in the empirical analys

e define this variable as the ratio of the synergy expected fromhe merger and the market capitalization of the target. Followingouston, James, and Ryngaert (2001) we collect information from

he SEC filings (8-k filings and proxy statements) as well as presseleases in the immediate aftermath of the merger announcementrom Lexis-Nexis as in Bernile (2005). We attempt to obtain infor-

ation on estimated cost savings, revenue enhancements and anyosts of the merger, such as fees paid to advisors. We use as muchetailed information as possible from these sources and in caseshere a target date for the realization of synergy effects is given,e assume that in each year prior to this the gains were half of

hat the following year. The final projected gains are then assumedo be perpetual and throughout we assume a tax rate of 36%. This

ethodology is identical to that used in Houston et al. (2001) and

ernile (2005).

We use these annual incremental gains from the merger to cal-ulate its present value and after deducting the merger costs webtain the size of the synergies. The discount factor to determinehe present value is given by the cost of capital as determined from

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able 2erger characteristics.

Median Stan

Merger partnersNumber of deals 337Market value of acquirer ($m) 2489 29,2Market value of target ($m) 622 847Deal value ($m) 987 13,1Synergy claimed ($m) 181 684

Payment formFraction of all-share offers 42.4%Fraction of all-cash offers 16.9%Fraction of mixed offers 40.7%

Negative

ected sign of the influence on the fraction of shares offered in a merger as well asfind to be statistically significant are shown in bold for the expected sign.

he CAPM. The beta used is the weighted average of the beta of thecquirer and the target, where the weights are the relative marketapitalizations of the two companies 2 months prior to the mergernnouncement. The betas are estimated from daily data in the timeindow from 210 to 21 trading days prior to the merger announce-ent. As the market we use the CRSP value-weighted index and setfixed risk premium of 7.5% p.a., in line with other similar inves-

igations such as Devos, Kadapakkam, and Krishnamurthy (2009)nd Houston et al. (2001) who use 7%, Bernile (2005) use 8% andilson, Hotchkiss, and Ruback (2000) 7.4%. As the risk-free ratee use the 10-year US government bond yield. In cases where we

btain a negative beta, we set the beta equal to the average beta inur sample which is 0.86 for acquirers and 0.71 for targets. Mergersith large synergies would be expected to have a larger fraction of

hares in the offer.A final control variable is whether the merger is hostile or

riendly. HOSTILE is a dummy variable that is set to 1 for a hostileerger and 0 otherwise. A hostile merger is generally associ-

ted with a cash offer in order to overcome the opposition of the

dard deviation Maximum Minimum

31 296,257 61 72,897 365 164,767 32 118,960 −258

A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484 475

Table 3Descriptive statistics.

Observations Mean Median Standard deviation Maximum Minimum Winsorized mean

Dependentvariables

SHARES 337 0.6739 0.8308 0.3821 1.0000 0.0000 0.6739TARG CAR 337 0.1626 0.1573 0.2113 0.9936 −0.8460 0.1634ACQ CAR 337 −0.0419 −0.0183 0.1472 0.2773 −0.9703 −0.0353

Targetcharacteristics

TARG GROW 337 0.0598 −0.1148 1.5849 20.4660 −0.9897 −0.0838TARG VOL 337 0.6012 0.5048 0.3336 2.9579 0.1594 0.5909TARG TOBIN 302 1.9042 1.4381 1.6633 15.1966 0.3034 1.6729TARG PE 300 18.6633 14.7361 46.9225 286.2664 −256.2500 14.5559PREMIUM 280 0.7239 0.6397 0.4730 1.9292 0.0088 0.7239PERFORM 337 −0.0433 −0.0182 0.9277 3.6075 −3.9085 −0.0599TARG LEV 304 0.5529 0.5829 0.2461 1.9006 0.0342 0.5051TARG BOARD 153 0.6275 1 0.4851 1 0 0.6275TARG PILL 153 0.6209 1 0.4868 1 0 0.6209TARG DIRLIAB 153 0.5033 1 0.5016 1 0 0.5033TARG PLAN 153 0.7190 1 0.4510 1 0 0.7190TARG GOV 153 9.4314 10 2.7602 15 3 7.0045

Acquirercharacteristics

ACQ GROW 337 0.1286 −0.0454 1.7859 27.6041 −0.9977 −0.0301ACQ VOL 337 0.5723 0.4483 0.4055 3.5311 0.1427 0.5461ACQ TOBIN 318 2.4551 1.6750 4.0820 58.0409 0.5810 1.9612ACQ PE 285 50.1758 17.2753 413.2405 6364.5833 −840.6667 14.4416ACQ MV 337 10660.33 2488.78 29231.26 296257.3 6.0175 7714.11ACQ CASH 327 0.1213 0.0349 0.1840 0.8569 0.0000 0.1111ACQ FCF 294 0.0735 0.0759 0.0811 0.4424 −0.4452 0.0600ACQ LEV 294 0.5520 0.5911 0.2093 1.2361 0.0428 0.4975ACQ BOARD 207 0.5700 1 0.4963 1 0 0.5700ACQ PILL 207 0.5652 1 0.4969 1 0 0.5652ACQ DIRLIAB 207 0.5459 1 0.4991 1 0 0.5459ACQ PLAN 207 0.7198 1 0.4502 1 0 0.7198ACQ GOV 153 9.6242 10 2.7056 15 1 7.1172

Dealcharacteristics

REL SIZE 337 0.7619 0.5496 0.7607 4.0700 0.0015 0.7318SYNERGY 337 0.1588 0.0677 0.2997 3.2148 −0.0157 0.1296HOSTILE 337 0.0475 0 0.2130 1 0 0.0475CORR 337 0.2004 0.1538 0.2061 1.0000 −0.1058 0.1963RATE 337 0.0565 0.0557 0.0107 0.1129 0.0401 0.0565

This table provides information on the descriptive statistics of the dependent and independent variables used in the empirical investigations. The winsorized mean refers tothe 90% winsorized data. SHARES denotes the fraction of shares used to pay the target shareholders, TARG CAR are the cumulative abnormal returns of the target surroundingthe merger announcement, ACQ CAR are the cumulative abnormal returns of the acquirer surrounding the merger announcement, TARG GROW denotes the growth rate ofthe stock price of the target, TARG VOL the volatility of this growth rate, TARG TOBIN Tobin’s Q of the target, PREMIUM the premium paid by the acquirer in the merger,PERFORM the cumulative performance of the target in the 2 years prior to the merger, TARG LEV the leverage of the target, TARG BOARD is a dummy variable for the existenceof a staggered board of the target, TARG PILL is a dummy variable for the existence of a poison pill of the target, TARG DIRLIAB is a dummy variable for the existence oflimited liability of the directors of the target, TARG PLAN is a dummy variable for the existence of a compensation plan of the target, TARG GOV the quality of the corporategovernance of the target, ACQ GROW the growth rate of the stock price of the acquirer, ACQ VOL the volatility of this growth rate, ACQ TOBIN Tobin’s Q of the acquirer,ACQ MV the market capitalization of the acquirer, ACQ CASH the amount of cash available to the acquirer, ACQ FCF the free cash flow of the acquirer, ACQ LEV the leverageof the acquirer, ACQ BOARD is a dummy variable for the existence of a staggered board of the acquirer, TARG PILL is a dummy variable for the existence of a poison pill ofthe acquirer, TARG DIRLIAB is a dummy variable for the existence of limited liability of the directors of the acquirer, TARG PLAN is a dummy variable for the existence of ac ce of to e corrr

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ompensation plan of the acquirer, ACQ GOV the quality of the corporate governanf the synergy effects, HOSTILE is a dummy variable for a hostile takeover, CORR thate at the time of the offer.

anagement and sometimes also of large shareholders, we wouldhus expect a negative relationship between this variable and theraction of shares offered.

We summarize these variables, their expected signs in a regres-ion and their association with different explanations of theayment form in Table 1 for convenience.

.3. Determination of independent variables

We determine the fraction of shares as the ratio of the value ofhe shares offered on the day the merger is announced and the totalalue of the transaction.

it

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he acquirer, REL SIZE the relative size of the target and acquirer, SYNERGY the sizeelation in the growth rate between the target and acquirer and RATE the risk-free

In order to assess the market reaction to a merger, we determinehe announcement returns as the cumulative abnormal returns intime window from 5 days prior to the merger announcement todays after. As the benchmark returns we use the market model

alibrated in the time period of 210 to 21 days prior to the merger.e also use different time periods in order to check the robustness

f our results and the effect of an early run-up of prices as reported

n Schwert (1996). In addition we also consider the returns of thearget and acquirer as a weighted average.

We show the descriptive statistics for the explanatory andependent variables in Tables 2 and 3, providing some basic

nsights into the nature of the dataset we investigate.

476 A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484

Table 4IV-TOBIT regression of payment form.

1 2 3 4 5 6 7

CONSTANT 0.1291 0.4117 0.3108 0.4049 0.5703 −0.4434 0.2754(0.33) (0.71) (0.51) (0.68) (0.96) (−0.78) (0.46)

Target characteristicsTARG GROW −0.0092 0.2435** 0.2599** 0.2707** 0.2749** 0.1703 0.2169*

(−0.20) (1.95) (1.96) (2.07) (2.10) (1.50) (1.74)TARG VOL −0.0737 0.2919 0.2092 0.2963 0.3251 0.3501 0.2480

(−0.42) (1.00) (0.73) (1.02) (1.09) (1.32) (0.85)LOG(TARG TOBIN) 0.0649 0.2511 0.2035 0.2932* 0.3220** 0.1561 0.1530

(0.71) (1.49) (1.15) (1.67) (1.78) (1.13) (0.89)PREMIUM −0.1115 −0.2871** −0.2646** −0.2947*** −0.3018*** −0.3350*** −0.2540**

(−1.52) (−2.55) (−2.39) (−2.62) (−2.66) (−3.13) (−2.32)PERFORM −0.0002 0.0667 0.0622 0.0485 0.0254 0.0628 0.0732

(−0.00) (0.50) (0.47) (0.36) (0.18) (0.58) (0.56)TARG LEV 0.3235** −0.0147 −0.1758 −0.0172 −0.0593 0.0102 −0.2174

(2.07) (−0.05) (−0.56) (−0.05) (−0.18) (0.03) (−0.74)TARG BOARD −0.0353 −0.0219

(−0.37) (−0.23)TARG PILL −0.0827 −0.0686

(−0.86) (−0.74)TARG DIRLIAB 0.0079 0.1215

(0.09) (1.37)TARG PLAN 0.0900 0.1080

(0.69) (0.84)TARG GOV 0.0008

(0.05)

Acquirer characteristicsACQ GROW 0.0609 −0.0365 −0.0447 −0.0470 −0.0424 −0.0253 −0.0288

(1.08) (−1.16) (−1.49) (−1.43) (−1.34) (−0.67) (−0.90)ACQ VOL 0.2254 0.2045 0.2312 0.1970 0.1863 0.2515 0.2069

(1.46) (1.26) (1.43) (1.18) (1.10) (1.49) (1.29)LOG(ACQ TOBIN) 0.0981 −0.0428 −0.0215 −0.1049 −0.0819 0.0352 0.0563

(0.96) (−0.23) (−0.12) (−0.53) (−0.40) (0.27) (0.29)LOG(ACQ MV) −0.0233 −0.0575 −0.0330 −0.0446 −0.0734 0.0006 −0.0469

(−0.78) (−1.10) (−0.63) (−0.79) (−1.28) (0.01) (−0.82)LOG(ACQ CASH) −0.0331 −0.0697 −0.0884** −0.0933** −0.0887** −0.0849** −0.0818**

(−1.11) (−1.55) (−2.15) (−2.11) (−2.00) (−2.19) (−1.98)LOG(ACQ FCF) −0.0225 0.0413 0.0069 0.0539 0.0504 −0.0060 0.0003

(−0.45) (0.67) (0.11) (0.86) (0.78) (−0.11) (0.01)ACQ LEV −0.3533 −0.1467 −0.2448 −0.1727 −0.1431 −0.2674 −0.1977

(−1.56) (−0.43) (−0.73) (−0.50) (−0.41) (−1.00) (−0.61)ACQ BOARD 0.1653** 0.1503*

(1.96) (1.65)ACQ PILL 0.2057** 0.2123**

(2.39) (2.38)ACQ DIRLIAB −0.0629 −0.0706

(−0.60) (−0.71)ACQ PLAN −0.0290 −0.1154

(−0.24) (−0.97)ACQ GOV 0.0341**

(1.98)

Deal characteristicsREL SIZE −0.0092 −0.0918 −0.1114 −0.1246* −0.1215* 0.0268 −0.1041

(−0.18) (−1.28) (−1.46) (−1.66) (−1.65) (0.43) (−1.39)SYNERGY 0.4956 0.3841 0.8174 0.5385 0.3995 0.1425 0.3129

(1.63) (0.66) (1.34) (0.90) (0.63) (0.35) (0.48)HOSTILE −0.4355*** −0.2501* −0.2257 −0.1775 −0.2033 −0.2921* −0.2728**

(−3.30) (−1.68) (−1.54) (−1.19) (−1.37) (−1.89) (−1.87)CORR 0.6307*** 0.4882** 0.5780** 0.4652* 0.4417* 0.5315** 0.4765**

(3.48) (1.96) (2.30) (1.79) (1.70) (2.10) (1.90)RATE 1.7654 5.0864 2.6250 5.2130 5.2438 2.6748 4.2392

(0.56) (0.88) (0.46) (0.88) (0.83) (0.52) (0.75)

Observations 219 98 98 98 98 120 98�2 34.08** 31.45** 34.40** 29.32* 29.83* 33.49** 42.31**Wald-test of exogeneity 0.02 0.62 0.46 1.32 1.68 0.48 0.29

A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484 477

Table 4 (Continued )

1 2 3 4 5 6 7

F-test instruments 6.07*** 12.21*** 11.94*** 12.01*** 12.38*** 14.95*** 9.55***R2 instruments 0.3534 0.7602 0.7562 0.7572 0.7628 0.7512 0.7777Sargan test 0.00 0.21 0.07 0.00 0.13 0.63 1.04

This table shows the parameter estimates of an instrumental-variable tobit regression of the fraction of shares used for payment in a merger on various explanatory variables.It is assumed that censoring occurs at 0 and 1. As an instrument we used the target firm’s average stock return in the pre-merger year as an instrument for the growth rateof the target company. Numbers in parenthesis denote the t-values and ***, **, and * denote statistical significance at 1%, 5%, and 10% level, respectively. CONSTANT denotesthe constant of the regression, TARG GROW denotes the growth rate of the stock price of the target, TARG VOL the volatility of this growth rate, TARG TOBIN Tobin’s Q ofthe target, PREMIUM the premium paid by the acquirer in the merger, PERFORM the cumulative performance of the target in the 2 years prior to the merger, TARG LEV theleverage of the target, TARG BOARD is a dummy variable for the existence of a staggered board of the target, TARG PILL is a dummy variable for the existence of a poisonpill of the target, TARG DIRLIAB is a dummy variable for the existence of limited liability of the directors of the target, TARG PLAN is a dummy variable for the existence of acompensation plan of the target, TARG GOV the quality of the corporate governance of the target, ACQ GROW the growth rate of the stock price of the acquirer, ACQ VOL thevolatility of this growth rate, ACQ TOBIN Tobin’s Q of the acquirer, ACQ MV the market capitalization of the acquirer, ACQ CASH the amount of cash available to the acquirer,ACQ FCF the free cash flow of the acquirer, ACQ LEV the leverage of the acquirer, ACQ BOARD is a dummy variable for the existence of a staggered board of the acquirer,TARG PILL is a dummy variable for the existence of a poison pill of the acquirer, TARG DIRLIAB is a dummy variable for the existence of limited liability of the directors ofthe acquirer, TARG PLAN is a dummy variable for the existence of a compensation plan of the acquirer, ACQ GOV the quality of the corporate governance of the acquirer,REL SIZE the relative size of the target and acquirer, SYNERGY the size of the synergy effects, HOSTILE is a dummy variable for a hostile takeover, CORR the correlation in thegrowth rate between the target and acquirer and RATE the risk-free rate at the time of the offer.

Table 52SLS regression of announcement returns of acquirers.

1 2 3 4 5 6 7

CONSTANT 0.0318 0.0792 −0.0406 −0.0452 0.0857 −0.0708 −0.1349(0.04) (0.10) (−0.04) (−0.07) (0.12) (−0.08) (−0.04)

Target characteristicsTARG GROW 0.0055 −0.0243 −0.0487 −0.0385 −0.0353 −0.0628 −0.0698

(0.56) (−0.21) (−0.27) (−0.46) (−0.43) (−0.46) (−0.13)TARG VOL −0.0408 0.0053 −0.0507 −0.0300 −0.0041 −0.2405 −0.0977

(−0.48) (0.02) (−0.09) (−0.11) (−0.01) (−0.33) (−0.07)LOG(TARG TOBIN) 0.0417 0.0415 0.0104 0.0210 0.0352 −0.0446 −0.0160

(0.33) (0.21) (0.03) (0.12) (0.21) (−0.18) (−0.02)PREMIUM −0.0291 −0.0196 0.0439 0.0304 0.0088 0.1957 0.0990

(−0.13) (−0.50) (0.09) (0.11) (0.03) (0.26) (0.07)PERFORM 0.0107 0.0642 0.0578 0.0566 0.0555 −0.0027 0.0406

(0.45) (1.13) (0.64) (0.97) (1.12) (−0.03) (0.43)TARG LEV −0.0452 −0.0171 −0.0619 −0.0623 −0.0467 −0.1728 −0.0990

(−0.16) (−0.07) (−0.23) (−0.35) (−0.27) (−0.27) (−0.11)TARG BOARD −0.0344 0.0080

(−0.28) (0.01)TARG PILL 0.0208 0.0428

(0.15) (0.11)TARG DIRLIAB −0.0305 −0.0497

(−0.97) (−0.20)TARG PLAN 0.0341 0.0197

(0.62) (0.05)TARG GOV 0.0072

(0.30)

Acquirer characteristicsACQ GROW −0.0060 −0.0025 −0.0037 −0.0042 −0.0025 −0.0045 −0.0033

(−0.32) (−0.29) (−0.41) (−0.44) (−0.29) (−0.24) (−0.10)ACQ VOL 0.0413 −0.0370 −0.0476 −0.0434 −0.0472 −0.0503 −0.0598

(0.96) (−0.54) (−0.52) (−0.64) (−0.77) (−0.44) (−0.31)LOG(ACQ TOBIN) −0.0269 −0.0211 −0.0361 −0.0306 −0.0274 −0.0690 −0.0347

(−0.22) (−0.35) (−0.59) (−0.54) (−0.53) (−0.42) (−0.10)LOG(ACQ MV) −0.0201 −0.0060 0.0027 0.0001 −0.0080 −0.0172 0.0006

(−0.46) (−0.11) (0.05) (0.00) (−0.17) (−0.08) (0.00)LOG(ACQ FCF) −0.0247 −0.0060 −0.0092 −0.0127 −0.0048 −0.0393 −0.0149

(−1.19) (−0.10) (−0.14) (−0.22) (−0.08) (−0.42) (−0.11)ACQ LEV 0.0992 0.0222 0.0443 0.0454 0.0367 0.1637 0.0731

(0.31) (0.14) (0.19) (0.31) (0.27) (0.43) (0.22)ACQ BOARD 0.0251 0.0090

(0.31) (0.03)ACQ PILL −0.0185 −0.0662

(−0.09) (−0.10)ACQ DIRLIAB 0.0301 0.0533

(0.67) (0.14)ACQ PLAN −0.0257 0.0075

(−0.42) (0.01)ACQ GOV −0.0081

(−0.37)

478 A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484

Table 5 (Continued )

1 2 3 4 5 6 7

Deal characteristicsREL SIZE −0.0567 −0.0615 −0.0420 −0.0415 −0.0585 −0.0491 −0.0119

(−1.26) (−0.62) (−0.27) (−0.51) (−0.73) (−1.20) (−0.02)SYNERGY −0.0119 0.3049 0.2051 0.2664 0.2447 −0.0448 0.1027

(−0.05) (0.75) (−0.25) (0.78) (0.88) (−0.11) (0.06)HOSTILE −0.0417 −0.0543 −0.0210 −0.0298 −0.0405 0.0757 −0.0049

(−0.12) (−0.32) (−0.10) (−0.27) (−0.35) (0.17) (−0.01)CORR 0.1150 0.0752 −0.0017 0.0162 0.0249 −0.1380 −0.0604

(0.27) (0.23) (0.00) (0.09) (0.14) (−0.21) (−0.04)RATE 1.2139 −0.7676 −2.1071 −1.7829 −1.5183 −3.6878 −3.1999

(0.34) (−0.10) (−0.22) (−0.34) (−0.30) (−0.36) (−0.10)FRAC SHARE −0.0550 −0.0121 0.1981 0.1672 0.0795 0.6410 0.4109

(−0.05) (−0.01) (0.13) (0.22) (0.11) (0.29) (0.08)

Observations 219 98 98 98 98 120 98F-test 1.71** 1.18 0.91 1.03 1.13 0.37 0.54R2 0.1332 0.2368 0.1930 0.2136 0.2294 0.0706 0.1672Adjusted R2 0.0552 0.0359 −0.0193 0.0066 0.0266 −0.1191 −0.1422

F-test instruments 3.05*** 2.92*** 3.07*** 2.69*** 2.75*** 3.20*** 2.54***R2 instruments 0.2156 0.4343 0.4467 0.4145 0.4194 0.3950 0.4852Sargan test 0.00 0.00 0.00 0.00 0.00 0.00 0.00

This table shows the parameter estimates of two-stage least squares regressions of the acquirer announcement returns on various sets of explanatory variables. As aninstrument we use the acquirer market-to-book ratio to account for the endogeneity of the payment form and the acquirer return. Numbers in parenthesis denote thet-values and ***, **, and * denote statistical significance at 1%, 5%, and 10% level, respectively. CONSTANT denotes the constant of the regression, TARG GROW denotes thegrowth rate of the stock price of the target, TARG VOL the volatility of this growth rate, TARG TOBIN Tobin’s Q of the target, PREMIUM the premium paid by the acquirer inthe merger, PERFORM the cumulative performance of the target in the 2 years prior to the merger, TARG LEV the leverage of the target, TARG BOARD is a dummy variablefor the existence of a staggered board of the target, TARG PILL is a dummy variable for the existence of a poison pill of the target, TARG DIRLIAB is a dummy variable for theexistence of limited liability of the directors of the target, TARG PLAN is a dummy variable for the existence of a compensation plan of the target, TARG GOV the quality ofthe corporate governance of the target, ACQ GROW the growth rate of the stock price of the acquirer, ACQ VOL the volatility of this growth rate, ACQ TOBIN Tobin’s Q of theacquirer, ACQ MV the market capitalization of the acquirer, ACQ CASH the amount of cash available to the acquirer, ACQ FCF the free cash flow of the acquirer, ACQ LEV theleverage of the acquirer, ACQ BOARD is a dummy variable for the existence of a staggered board of the acquirer, TARG PILL is a dummy variable for the existence of a poisonp iabilito nances R ther paym

4

4

ieaacgainwgalc

tvficfioaodtb

s4osis

vtogi0m2hi5woifsoasi

ill of the acquirer, TARG DIRLIAB is a dummy variable for the existence of limited lf a compensation plan of the acquirer, ACQ GOV the quality of the corporate goverize of the synergy effects, HOSTILE is a dummy variable for a hostile takeover, CORate at the time of the offer and FRAC SHARE denotes the fraction of shares used as

. Empirical investigation

.1. Investigation of the payment form

Using the parameters introduced above we run a number ofnstrumental-variable tobit regressions. Table 4 shows the param-ter estimates of these regressions whose results are very stable,lso for other parameter constellations not shown here. The vari-bles not considered in the literature before are the investmentharacteristics of the target and acquirer; we therefore investi-ate the stability of results when determining these variables indifferent way and in Section 4.3 we will see that results are

ndeed stable. From our regressions we observe that only a smallumber of parameters are statistically significant; in particulare find that more shares are offered in a merger if the target

rowth rate is higher, the premium paid in the merger is lower, thecquirer has less cash available, has defence mechanisms estab-ished against being taken over, the takeover is friendly and theorrelation between the two companies is higher.

We see that statistically significant variables are associated withhe investment characteristics, managerial entrenchment, controlariables and to a small degree also budget constraints. We do notnd evidence for the relevance of asymmetric information or taxonsiderations in the choice of the payment form, a result con-rmed when conducting robustness checks in Section 4.3. Fromur results we can confirm that managerial entrenchment in thecquiring firm is the only traditionally found factor for the choice

f payment form for which we have convincing empirical evi-ence. The evidence for budget constraints is very weak as onlyhe amount of cash available to the target is statistically significantut other constraints like the leverage or sizes of the companies are

wf

a

y of the directors of the acquirer, TARG PLAN is a dummy variable for the existenceof the acquirer, REL SIZE the relative size of the target and acquirer, SYNERGY the

correlation in the growth rate between the target and acquirer, RATE the risk-freeent to the target shareholders.

tatistically insignificant. When winsorizing our data, see Section.3 and Table 8, we find some additional evidence for the relevancef budget constraints with the size of the acquirer and the relativeize of the two companies becoming statistically significant. Whennvestigating the �2 value of our regressions we observe high valuesuggesting that overall the system is well identified.

Focussing on the marginal impact of the statistically significantariables (the marginal effects have been found to be identical tohe coefficients of the tobit regression), we observe that the impactf the growth rate of the target is low; an increase of the annualrowth rate by 5% will only affect the fraction of shares by approx-mately 1%. On the other hand an increase of the correlation by.2 increases the fraction of shares offered by nearly 10%, a muchore significant impact. A hostile takeover sees an approximately

7% reduction in the fraction of shares. The impact the premiumas on the fraction of shares offered is also relatively small, a 20%

ncrease in the premium reduces the fraction of shares by only%. The impact of the defence mechanisms are more significanthere the introduction of a staggered board increases the fraction

f shares by 15% and a poison pill by 21%. On the other hand a 20%ncrease in the cash holding of an acquirer would only reduce theraction of shares offered by 1.6%. In addition, from Table 8 we alsoee that the relative and absolute size of the companies involvednly have a small impact on the payment form, even though theyre statistically significant for winsorized variables. Thus we canummarize that the main factors having an economically signif-cant impact on the choice of payment form are the correlation,

hether the takeover is hostile, and whether defence mechanismsor the acquirer exist.

Our results confirm only the existence of defence mechanismsnd whether the merger is hostile as the traditionally mentioned

A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484 479

Table 62SLS regression of announcement returns of targets.

1 2 3 4 5 6 7

CONSTANT −0.4238 1.1346 1.2483 0.9763 1.1153 0.0095 3.4518(−0.19) (0.49) (0.40) (0.74) (0.71) (0.01) (0.14)

Target characteristicsTARG GROW −0.0175 0.0046 0.0662 −0.0236 −0.0254 −0.1856 0.3366

(−0.62) (0.01) (0.11) (−0.13) (−0.14) (−0.96) (0.09)TARG VOL −0.1641 0.2638 0.4417 0.2138 0.2359 −0.4404 1.0917

(−0.67) (0.27) (0.24) (0.35) (0.35) (−0.43) (0.12)LOG(TARG TOBIN) −0.1292 0.2057 0.3030 0.1814 0.1887 −0.1578 0.6139

(−0.36) (0.37) (0.29) (0.50) (0.49) (−0.44) (0.12)PREMIUM 0.2700 −0.2879 −0.4219 −0.2102 −0.2124 0.4441 −1.1106

(0.55) (−0.28) (−0.25) (−0.37) (−0.36) (0.41) (−0.12)PERFORM 0.0139 0.0407 0.0744 0.0410 0.0217 −0.0521 0.0590

(0.20) (0.26) (0.25) (0.33) (0.19) (−0.35) (0.09)TARG LEV −0.3195 0.1585 0.1722 0.0884 0.0769 −0.3724 0.6828

(−0.40) (0.22) (0.19) (0.23) (0.20) (−0.41) (0.11)TARG BOARD −0.0998 −0.4946

(−0.29) (−0.12)TARG PILL −0.1292 −0.3336

(−0.28) (−0.12)TARG DIRLIAB 0.0123 0.2149

(0.18) (0.13)TARG PLAN 0.0793 0.3857

(0.64) (0.13)TARG GOV 0.0220

(0.64)

Acquirer characteristicsACQ GROW −0.0140 0.0066 0.0031 0.0027 0.0061 0.0053 0.0320

(−0.26) (0.27) (0.10) (0.13) (0.31) (0.20) (0.14)ACQ VOL −0.0308 −0.0260 0.0001 −0.0375 −0.0513 −0.1154 0.0750

(−0.35) (−0.14) (0.00) (−0.26) (−0.37) (−0.70) (0.06)LOG(ACQ TOBIN) −0.0810 0.0846 0.0763 0.0440 0.0637 −0.0422 0.3359

(−0.23) (0.50) (0.38) (0.36) (0.55) (−0.18) (0.15)LOG(ACQ MV) 0.0352 −0.0473 −0.0458 −0.0296 −0.0485 0.0029 −0.2148

(0.28) (−0.31) (−0.26) (−0.40) (−0.47) (0.09) (−0.12)LOG(ACQ FCF) 0.0235 0.0699 0.0734 0.0703 0.0725 −0.0383 0.1297

(0.39) (0.43) (0.34) (0.56) (0.55) (−0.29) (0.14)ACQ LEV 0.3035 −0.2011 −0.2730 −0.1882 −0.1692 0.0669 −0.3453

(0.33) (−0.45) (−0.36) (−0.59) (−0.55) (0.12) (−0.15)ACQ BOARD 0.0675 0.2358

(0.30) (0.12)ACQ PILL 0.1716 0.5435

(0.26) (0.12)ACQ DIRLIAB −0.0196 −0.3107

(−0.20) (−0.12)ACQ PLAN −0.0515 −0.5142

(−0.38) (−0.12)ACQ GOV −0.0179

(−0.58)

Deal characteristicsREL SIZE −0.0057 −0.1701 −0.2228 −0.1550 −0.1597 −0.0297 −0.5645

(−0.04) (−0.61) (−0.43) (−0.90) (−0.89) (−0.51) (−0.14)SYNERGY −0.2257 0.8422 1.2354 0.7666 0.6972 −0.0796 1.8153

(−0.35) (0.73) (0.45) (1.05) (1.11) (−0.13) (0.16)HOSTILE 0.3781 −0.1575 −0.2014 −0.1050 −0.1187 0.2172 −0.5962

(0.38) (−0.33) (−0.28) (−0.44) (−0.46) (0.34) (−0.12)CORR −0.3341 0.3425 0.4219 0.2181 0.2051 −0.3356 1.3232

(−0.27) (0.38) (0.31) (0.55) (0.52) (−0.35) (0.12)RATE −2.7388 8.9389 10.7427 6.9679 6.8536 −4.0800 27.1885

(−0.27) (0.44) (0.34) (0.62) (0.60) (−0.28) (0.13)FRAC SHARE 0.9078 −1.3591 −1.7735 −1.1004 −1.1078 0.8433 −4.4066

(0.27) (−0.45) (−0.34) (−0.67) (−0.66) (0.27) (−0.13)

Observations 219 98 98 98 98 120 98F-test 0.69 0.50 0.29 0.74 0.74 0.82 0.03R2 0.0587 0.1165 0.0719 0.1633 0.1637 0.1437 0.0127Adjusted R2 −0.0260 −0.1160 −0.1723 −0.0568 −0.0564 −0.0311 −0.3540

F-test instruments 3.05*** 2.92*** 3.07*** 2.69*** 2.75*** 3.20*** 2.54***R2 instruments 0.2156 0.4343 0.4467 0.4145 0.4194 0.3950 0.4852

480 A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484

Table 6 (Continued)

1 2 3 4 5 6 7

Sargan test 0.00 1.22 0.10 0.00 0.00 0.00 0.00

This table shows the parameter estimates of two-stage least squares regressions of the acquirer announcement returns on various sets of explanatory variables. As aninstrument we use the acquirer market-to-book ratio to account for the endogeneity of the payment form and the acquirer return. Numbers in parenthesis denote thet-values and ***, **, and * denote statistical significance at 1%, 5%, and 10% level, respectively. CONSTANT denotes the constant of the regression, TARG GROW denotes thegrowth rate of the stock price of the target, TARG VOL the volatility of this growth rate, TARG TOBIN Tobin’s Q of the target, PREMIUM the premium paid by the acquirer inthe merger, PERFORM the cumulative performance of the target in the 2 years prior to the merger, TARG LEV the leverage of the target, TARG BOARD is a dummy variablefor the existence of a staggered board of the target, TARG PILL is a dummy variable for the existence of a poison pill of the target, TARG DIRLIAB is a dummy variable for theexistence of limited liability of the directors of the target, TARG PLAN is a dummy variable for the existence of a compensation plan of the target, TARG GOV the quality ofthe corporate governance of the target, ACQ GROW the growth rate of the stock price of the acquirer, ACQ VOL the volatility of this growth rate, ACQ TOBIN Tobin’s Q of theacquirer, ACQ MV the market capitalization of the acquirer, ACQ CASH the amount of cash available to the acquirer, ACQ FCF the free cash flow of the acquirer, ACQ LEV theleverage of the acquirer, ACQ BOARD is a dummy variable for the existence of a staggered board of the acquirer, TARG PILL is a dummy variable for the existence of a poisonp iabilito nances R ther paym

drtotbatescwfatthf

4

tteataOltebraata

tbrdofrsa

mrtetrsertsawSTtaf

4

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ill of the acquirer, TARG DIRLIAB is a dummy variable for the existence of limited lf a compensation plan of the acquirer, ACQ GOV the quality of the corporate goverize of the synergy effects, HOSTILE is a dummy variable for a hostile takeover, CORate at the time of the offer and FRAC SHARE denotes the fraction of shares used as

river of the payment form; at the same time we establish theeturn correlation between the two companies involved as an addi-ional factor that has not been previously reported. The relevancef the correlation suggests that companies also take into accounthe considerations of investors, who are first and foremost affectedy this management decision and often have to approve the trans-ction. In cases where the acquirer differs significantly from thearget, i.e. we find a low correlation, more cash is offered, whichnables investors to reinvest their proceeds freely in a way thatuits their preferences rather than having to go through the pro-esses of selling the received shares in the first instance. It would beorth to consider in future research whether evidence can be found

or the extent of portfolio rebalancing by investors into the targetfter a merger. Based on our argument above, we would expecto find a larger extent of rebalancing for smaller return correla-ions and larger fraction of shares offered. Such an investigation is,owever, beyond the scope of this investigation and we leave it for

uture research.

.2. Announcement returns

We also investigate the announcement returns of acquirers andargets. It is commonly found that all benefits of mergers go tohe target shareholders and the announcement returns to acquir-rs are either negligible or slightly negative, a result confirmed heregain in our sample as we see from Table 3. When we investigatehe determinants of these returns, however, we find that all vari-bles considered are statistically insignificant, see Tables 5 and 6.ne common result from the literature is that cash offers result in

arger announcement returns for targets, a result we are not ableo reproduce. Furthermore, it is commonly assumed that merg-rs between companies of a similar size are less well receivedy investors, which should be reflected in lower announcementeturns for acquirers. We also find no evidence to suggest thathigher premium paid by the acquirer actually results in higher

nnouncement returns as would be expected. The low values ofhe F-tests suggest that the variables considered are indeed notdequate explanatory variables for the announcement returns.

These results are very much at odds with the previous litera-ure investigating announcement returns. One reason for our resulteing different might be that most other studies use a standard OLSegression while we employ a 2SLS regression with appropriatelyetermined instruments. When conducting an OLS regression on

ur dataset, the results are more in line with those traditionallyound, see Table 7. For the acquirer we find that the announcementeturns are decreasing if the two companies are of a more equalize, in line with the common perception that “mergers of equals”re not well received; the same result is obtained for the announce-

gsit

y of the directors of the acquirer, TARG PLAN is a dummy variable for the existenceof the acquirer, REL SIZE the relative size of the target and acquirer, SYNERGY the

correlation in the growth rate between the target and acquirer, RATE the risk-freeent to the target shareholders.

ent returns of the target. We also observe that the announcementeturns are decreasing the more shares are offered, in line withhe established literature. Not surprisingly higher estimated syn-rgies and premium paid increase the announcement returns ofhe target and we finally can observe that a high target growth rateeduces the announcement returns, which is not surprising as thehareholders have to give up shares in a well-performing stock inxchange for a stock performing less well or cash that might not beeinvested at the same rate. While these OLS results are in line withhose in the literature, although support from the F-test is not verytrong, they do not remain valid using an instrumental-variablepproach taken in our investigation, even though our instrumentsere found to be valid as can be seen from the low value of the

argan test as well as the F-test of the regression of instruments.he discrepancies in our approach and that more widely used inhe literature merits some further investigation, but given that thisspect falls beyond the scope of this investigation, we leave it foruture research.

.3. Robustness of results

We conducted a range of robustness checks to establish thealidity of our results; these are summarized in Table 8. Firstlye checked for the sensitivity of the model to the time lengthuring which we estimate the investment characteristics of thewo merging companies. We compare the window of 210 to 20ays prior to the merger announcement comprised of daily dataith monthly data for the time period of 5 years prior to theerger announcement; results using daily data for 2 years prior

o the merger announcements are similar to those for 5 years.e clearly observe that apart from the results on the investment

haracteristics the outcomes are very similar and we can concludehat they are robust. The results on the investment characteristicshange, however marginally. Rather than the target growth ratend correlation being statistically significant, the target volatilitynd correlation becomes significant. It is not surprising that therowth rates become insignificant with the long time frames usednd the changes that occur in investors’ perceptions during thisong time period. The emergence of the target volatility which hasn economically significant impact – a 10% increase in the volatilityf the target stock would increase the fraction of shares offered bybout 10% – underlines the relevance of the investment character-stics for the determination of the payment form.

We further investigated our result that the valuation of the tar-et and acquirer, as measured by Tobin’s Q, are statistically notignificant. Including the difference in their respective valuationsnto the regression (TOBIN DIFF), confirms our results that this fac-or is statistically not significant.

A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484 481

Table 7OLS regressions of announcement returns and portfolio returns.

Acquirer Target Portfolio

CONSTANT 0.1603 0.3383 0.2168(0.77) (1.58) (1.32)

Target characteristicsTARG GROW −0.0254 −0.1159*** −0.0584**

(−0.77) (−3.41) (−2.24)TARG VOL 0.0248 −0.0915 0.0012

(0.27) (−0.96) (0.02)LOG(TARG TOBIN) 0.0401 0.0041 0.0201

(0.85) (0.09) (0.54)PREMIUM −0.0209 0.0886** 0.0027

(−0.52) (2.13) (0.09)PERFORM 0.0499 −0.0066 0.0538

(1.19) (−1.50) (1.64)TARG LEV −0.0253 −0.1011 −0.0325

(−0.30) (−1.17) (−0.49)TARG BOARD −0.0439 0.0244 −0.0345

(−1.25) (0.68) (−1.25)TARG PILL 0.0070 0.0060 −0.0038

(0.22) (0.18) (−0.15)TARG DIRLIAB −0.0299 0.0040 −0.0098

(−0.94) (0.12) (−0.39)TARG PLAN 0.0584 0.0304 0.0446

(1.28) (0.65) (1.25)

Acquirer characteristicsACQ GROW −0.0007 0.0063 0.0035

(−0.07) (0.69) (0.49)ACQ VOL −0.0455 −0.0720 −0.0627

(−0.77) (−1.18) (−1.34)LOG(ACQ TOBIN) −0.0020 0.0577 0.0321

(−0.04) (1.04) (0.75)LOG(ACQ MV) −0.0199 0.0009 −0.0199

(−1.06) (0.05) (1.34)LOG(ACQ FCF) −0.0034 0.0134 −0.0029

(−0.15) (0.56) (−0.16)ACQ LEV 0.0693 −0.0991 0.0223

(0.64) (−0.89) (0.26)ACQ BOARD 0.0331 −0.0024 0.0249

(1.03) (−0.07) (0.98)ACQ PILL −0.0071 −0.0203 −0.0100

(−0.21) (−0.59) (−0.38)ACQ DIRLIAB 0.0163 0.0142 0.0140

(0.44) (0.37) (0.48)ACQ PLAN −0.0453 0.0172 −0.0412

(−1.21) (0.45) (−1.41)

Deal characteristicsREL SIZE −0.0619** −0.0666** −0.0157

(−2.16) (−2.26) (−0.70)SYNERGY 0.2432 0.4235** 0.2981**

(1.34) (2.27) (2.09)HOSTILE −0.0654 0.0033 −0.0002

(−1.19) (0.06) (−0.00)CORR 0.0734 −0.0050 0.0925

(1.02) (−0.07) (1.63)RATE −0.6276 1.1261 0.2981**

(−0.30) (0.53) (2.09)FRAC SHARE −0.0130 −0.2086*** −0.0518

(−0.25) (−3.83) (−1.24)

Observations 98 98 98F-test 1.04 3.48*** 1.19R2 0.2750 0.5605 0.3039Adjusted R2 0.0096 0.3996 0.0489

This table shows the parameter estimates of OLS regressions of the acquirer and target announcement returns. The last column shows the portfolio returns consisting ofa value-weighted average of the acquirer and target announcement returns. Numbers in parenthesis denote the t-values and ***, **, and * denote statistical significanceat 1%, 5%, and 10% level, respectively. CONSTANT denotes the constant of the regression, TARG GROW denotes the growth rate of the stock price of the target, TARG VOLthe volatility of this growth rate, TARG TOBIN Tobin’s Q of the target, PREMIUM the premium paid by the acquirer in the merger, PERFORM the cumulative performanceof the target in the 2 years prior to the merger, TARG LEV the leverage of the target, TARG BOARD is a dummy variable for the existence of a staggered board of the target,TARG PILL is a dummy variable for the existence of a poison pill of the target, TARG DIRLIAB is a dummy variable for the existence of limited liability of the directors of thetarget, TARG PLAN is a dummy variable for the existence of a compensation plan of the target, ACQ GROW the growth rate of the stock price of the acquirer, ACQ VOL thevolatility of this growth rate, ACQ TOBIN Tobin’s Q of the acquirer, ACQ MV the market capitalization of the acquirer, ACQ CASH the amount of cash available to the acquirer,ACQ FCF the free cash flow of the acquirer, ACQ LEV the leverage of the acquirer, ACQ BOARD is a dummy variable for the existence of a staggered board of the acquirer,TARG PILL is a dummy variable for the existence of a poison pill of the acquirer, TARG DIRLIAB is a dummy variable for the existence of limited liability of the directors ofthe acquirer, TARG PLAN is a dummy variable for the existence of a compensation plan of the acquirer, REL SIZE the relative size of the target and acquirer, SYNERGY thesize of the synergy effects, HOSTILE is a dummy variable for a hostile takeover, CORR the correlation in the growth rate between the target and acquirer, RATE the risk-freerate at the time of the offer and FRAC SHARE denotes the fraction of shares used as payment to the target shareholders.

482 A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484

Table 8Robustness of the IV-TOBIT regression of the payment form.

Base case 5 years Tobin Industry Winsorize

CONSTANT 0.2754 −0.4288 0.2754 0.3665 0.2452(0.46) (−0.82) (0.46) (0.61) (0.42)

Target characteristicsTARG GROW 0.2169* 0.3557 0.2169* 0.2595** 0.3291*

(1.74) (0.17) (1.74) (1.96) (1.81)TARG VOL 0.2480 1.2030** 0.2480 0.4253 0.3355

(0.85) (2.37) (0.85) (1.50) (1.10)LOG(TARG TOBIN) 0.1530 0.1645 0.2094 0.2294 0.2368

(0.89) (0.85) (1.32) (1.30) (1.42)PREMIUM −0.2540** −0.3062*** −0.2540** −0.2335** −0.2991***

(−2.32) (−2.85) (−2.32) (−2.14) (−2.80)PERFORM 0.0732 0.07847 0.0732 0.0849 0.2526

(0.56) (0.46) (0.56) (0.65) (0.19)TARG LEV −0.2174 −0.1250 −0.2174 −0.2335 0.0160

(−0.74) (−0.31) (−0.74) (−0.77) (0.05)TARG BOARD −0.0219 0.06245 −0.0219 −0.0002 −0.0323

(−0.23) (0.60) (−0.23) (−0.00) (−0.35)TARG PILL −0.0686 −0.07362 −0.0686 −0.0565 −0.0575

(−0.74) (−0.90) (−0.74) (−0.60) (−0.63)TARG DIRLIAB 0.1215 0.0891 0.1215 0.1356 0.1283

(1.37) (1.08) (1.37) (1.51) (1.38)TARG PLAN 0.1080 0.0813 0.1080 0.1279 0.1628

(0.84) (0.66) (0.84) (1.00) (1.27)

Acquirer characteristicsACQ GROW −0.0288 1.0852 −0.0288 −0.3014 −0.0999

(−0.90) (1.32) (−0.90) (−0.93) (−0.76)ACQ VOL 0.2069 −0.5628 0.2069 0.1765 0.0996

(1.29) (−0.51) (1.29) (1.08) (0.49)LOG(ACQ TOBIN) 0.0563 −0.1880 −0.8797 0.2374

(0.29) (−0.98) (−0.44) (1.24)LOG(ACQ TOBIN/TARG TOBIN) 0.5634

(0.29)LOG(ACQ MV) −0.0469 −0.0396 −0.0469 −0.0147 −0.1009**

(−0.82) (−0.73) (−0.82) (−0.26) (−1.85)LOG(ACQ CASH) −0.0818** −0.1179*** −0.0818** −0.0657 0.1002**

(−1.98) (−3.01) (−1.98) (−1.62) (−2.37)LOG(ACQ FCF) 0.0003 −0.0721 0.0003 0.0212 0.0028

(0.01) (−1.08) (0.01) (0.35) (0.03)ACQ LEV −0.1977 −0.3306 −0.1977 −0.3186 −0.0901

(−0.61) (−0.99) (−0.61) (−0.94) (−0.24)ACQ BOARD 0.1503* 0.0012 0.1503* 0.1369 0.1771*

(1.65) (0.01) (1.65) (1.41) (1.94)ACQ PILL 0.2123** 0.3144** 0.2123** 0.2173** 0.1972**

(2.38) (2.29) (2.38) (2.33) (2.17)ACQ DIRLIAB −0.0706 −0.0666 −0.0706 −0.0733 −0.0677

(−0.71) (−0.54) (−0.71) (−0.72) (−68)ACQ PLAN −0.1154 −0.0582 −0.1154 −0.0862 −0.1538

(−0.97) (−0.57) (−0.97) (−0.73) (−1.34)

Deal characteristicsREL SIZE −0.1041 −0.0781 −0.1041 −0.1008 −0.1630**

(−1.39) (0.74) (−1.39) (−1.33) (−1.82)SYNERGY 0.3129 1.0856 0.3129 0.2547 0.3171

(0.48) (1.54) (0.48) (0.39) (0.48)HOSTILE −0.2728** −0.2380* −0.2728** −0.2756* −0.2250

(−1.87) (−1.74) (−1.87) (−1.84) (−1.50)CORR 0.4765** 0.9070*** 0.4765** 0.2648**

(1.90) (3.36) (1.90) (2.34)INDUSTRY −0.902

(−0.87)RATE 4.2392 2.5385 4.2392 3.3451 6.2025

(0.75) (0.51) (0.75) (0.58) (1.16)

Observations 98 98 98 98 98�2 42.31** 69.30*** 42.31** 40.33** 50.94***

A. Ismail, A. Krause / The Quarterly Review of Economics and Finance 50 (2010) 471–484 483

Table 8 (Continued)

Base case 5 years Tobin Industry Winsorize

Wald-test of exogeneity 0.29 0.00 0.23 0.24 0.00

This table shows the parameter estimates of an instrumental-variable tobit regression of the fraction of shares used for payment in a merger on various explanatory variables.We use different variantion from the “base case” reported in Table 4 and repeated here for convenience, “5 years” uses monthly data for the 5 years prior to the mergerannouncement to determine the investment characteristics of the stocks, “Tobin” introduces the differences between Tobin’s Q of the target and acquirer, “Industry” replacesthe correlation of returns with a dummy if both companies are in the same industry and “Winsorize” used winsorized data for the regression at the 90% level. It is assumedthat censoring occurs at 0 and 1. As an instrument we used the target firm’s average stock return in the pre-merger year as an instrument for the growth rate of the targetcompany. Numbers in parenthesis denote the t-values and ***, **, and * denote statistical significance at 1%, 5%, and 10% level, respectively. CONSTANT denotes the constantof the regression, TARG GROW denotes the growth rate of the stock price of the target, TARG VOL the volatility of this growth rate, TARG TOBIN Tobin’s Q of the target,PREMIUM the premium paid by the acquirer in the merger, PERFORM the cumulative performance of the target in the 2 years prior to the merger, TARG LEV the leverage ofthe target, TARG BOARD is a dummy variable for the existence of a staggered board of the target, TARG PILL is a dummy variable for the existence of a poison pill of the target,TARG DIRLIAB is a dummy variable for the existence of limited liability of the directors of the target, TARG PLAN is a dummy variable for the existence of a compensation planof the target, TARG GOV the quality of the corporate governance of the target, ACQ GROW the growth rate of the stock price of the acquirer, ACQ VOL the volatility of thisgrowth rate, ACQ TOBIN Tobin’s Q of the acquirer, ACQ MV the market capitalization of the acquirer, ACQ CASH the amount of cash available to the acquirer, ACQ FCF the freecash flow of the acquirer, ACQ LEV the leverage of the acquirer, ACQ BOARD is a dummy variable for the existence of a staggered board of the acquirer, TARG PILL is a dummyv ariaba V the qt ariablea he sam

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mt5atrtoehcao

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ariable for the existence of a poison pill of the acquirer, TARG DIRLIAB is a dummy vdummy variable for the existence of a compensation plan of the acquirer, ACQ GO

arget and acquirer, SYNERGY the size of the synergy effects, HOSTILE is a dummy vnd acquirer, INDUSTRY a dummy variable which is 1 of the two companies are in t

One of our results was that the correlation between the targetnd acquirer are statistically significant for the determination of theayment form. We replaced this variable with an industry dummyINDUSTRY) that we set equal to 1 if the two companies are in theame industry as identified by their 2-digit SIC code and 0 other-ise. This allows us to investigate whether our result is actuallyriven by the two companies being in the same industry and wend this variable not to be statistically significant, thus the corre-

ation between the companies is not a substitute for the industryhey are operating in and therefore captures additional aspects.

Finally, we recognize from Table 3 that some variables havearge outliers that might drive some of the results. To establish thatur results are not driven by such outliers we winsorized our data athe 90% level and used the resulting data for a regression. As we canee in Table 8, using winsorized data does not change the resultsbtained in any meaningful way. The only difference we observe ishat the size of the merging companies becomes statistically sig-ificant, with larger companies using fewer shares, in accordanceith budget constraints for raising cash of the required amount.s discussed above, the marginal effects of these variables are verymall such that the economic significance is negligible. All otherariables remain unchanged.

We conducted a similar sensitivity analysis for the announce-ent returns of targets and acquirers. As above we changed the

ime horizon for the estimation of investment characteristics toyears, included the difference in Tobin’s Q between the target

nd acquirer, used an industry dummy to replace the correla-ion, winsorized the data at the 90% level and used these data toun regressions, as well as extended the event window up to 20rading days around the merger announcement. In all cases webserve either no change in the significance of variables or theconomic significance is so small that the variables in questionave no meaningful impact on the announcement returns. We alsoonsidered the portfolio returns of the target and acquirer usingweighted average of the respective announcement returns and

btained results entirely consistent with those reported above.Our sample only included mergers that had published estimated

ost savings and/or revenue enhancement as a basis for the cal-ulation of synergies. It has been noted in Houston et al. (2001)hat such estimations are only published in cases where they areufficiently large, thus potentially imposing a bias into our sample.

owever, we do observe relatively small announcement returns for

he acquirer as well as the target, suggesting that our sample doesot only include mergers that have very large projected synergies.his view is also confirmed when looking at the descriptive statis-ics in Table 3 where the median synergies were found to be only

A

B

le for the existence of limited liability of the directors of the acquirer, TARG PLAN isuality of the corporate governance of the acquirer, REL SIZE the relative size of thefor a hostile takeover, CORR the correlation in the growth rate between the targete industry and 0 otherwise, and RATE the risk-free rate at the time of the offer.

.0677. Nevertheless our restriction of the sample only to thoseergers that have projected synergies published deserves some

urther research with a larger sample of companies.Having conducted these robustness checks we can confidently

onclude that the results discussed above are robust to any changesn measurement or exact model specification.

. Conclusions

We have investigated the determinants of the payment form inergers and acquisitions using US mergers of publicly listed com-

anies between 1985 and 2004. We have introduced a new set ofariables that have previously not commonly been used in empiri-al investigations, the investment characteristics of the companieserging. Employing an instrumental-variable tobit regression we

ound that the economically important determinants were theeturn correlation between the stocks of the merging companies,hether the merger is hostile and the existence of defence mecha-isms for the acquirer. There was no evidence in our investigationupporting an economically and statistically significant role ofsymmetric information, budget constraints or tax considerations,ome of the most commonly cited determinants of the paymentorm in mergers and acquisitions.

We also analyzed the announcement returns of acquirers andargets. After carefully adjusting for the endogeneity between theayment form and the return by using the acquirer Market to Bookatio as an instrument in a 2SLS we found that none of the vari-bles investigated was able to explain the announcement returnsbserved.

Despite these new findings, we find that there is still a signifi-ant gap in our understanding of the determinants of the paymentorm. In future research it might be of interest to include additionalactors that are not directly related to the target, acquirer or theeal itself, but the environment in which they are announced in,.g. the general conditions of the stock market, any herding effectrising from the conditions in other mergers. We might also wanto consider new variables not investigated in this paper, such ashe ownership structure of the companies involved or the biddingrocess of the merger.

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