let's make a deal! how shareholder control impacts merger payoffs

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Journal of Financial Economics 76 (2005) 167–190

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Let’s make a deal! How shareholder controlimpacts merger payoffs$

Thomas Moeller�

Rawls College of Business Administration, Texas Tech University, Lubbock, TX 79409,USA

Received 6 June 2003; received in revised form 25 September 2003; accepted 15 June 2004

Available online 30 December 2004

Abstract

Mergers and acquisitions are well-suited events for a detailed study of the valuation effects

of corporate governance structures. Using a sample of 388 takeovers announced in the friendly

environment of the 1990s, I empirically show that target shareholder control, proxied by low

target chief executive officer share ownership, low fractions of inside directors, and the

presence of large outside blockholders, is positively correlated with takeover premiums. In

contrast, studies of takeovers in the hostile environment of the 1980s have shown a negative

relation between target shareholder control and takeover premiums.

r 2004 Elsevier B.V. All rights reserved.

JEL classification: G34

Keywords: Mergers; Acquisitions; Agency; Governance

- see front matter r 2004 Elsevier B.V. All rights reserved.

.jfineco.2004.11.001

Ty Callahan, Jay Hartzell, John Robinson, Laura Starks, Sheridan Titman, Kimberly

nda Wallace, James Weston, an anonymous referee, and seminar participants at the

f Texas at Austin, University of Cincinnati, College of William and Mary, Cornerstone

uisiana State University, Rice University, Santa Clara University, The Brattle Group,

Texas at Dallas, University of Toronto, Washington State University, and the 2002 Frank

g Scholars Conference at the College of William and Mary for helpful comments. Large parts

h were conducted while I was at the University of Texas at Austin, The Brattle Group, and

ity. All errors are my own.

nding author. Fax: 806 742 3197.

dress: [email protected] (T. Moeller).

www.elsevier.com/locate/econbase

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T. Moeller / Journal of Financial Economics 76 (2005) 167–190168

1. Introduction

How much control of a firm should rest in the hands of its managers, and howmuch should be retained by its shareholders? This question, and how to implementthe optimal balance of power, has long been central not only to the corporategovernance literature, but also to active investors and securities legislation. In thispaper, I empirically examine how the balance of power between target chiefexecutive officers (CEOs) and target shareholders affects takeover premiums inmergers and acquisitions in the 1990s.Mergers and acquisitions are in many ways ideal natural experiments to test the

valuation effects of corporate governance structures.1 First, a merger generallyrequires the active participation of all decision makers, namely, managers, directors,and shareholders. Managers usually negotiate the merger, directors have to endorseit and are sometimes involved in the negotiations, and shareholders have to eithervote on it or decide whether to tender their shares. Second, the effect of the corporategovernance structure on the value of the target, given adequate control for otherinfluences, is immediately observable in the takeover premium. Third, a mergerannouncement is a clearly defined and, in most cases, a surprising event.Intuitively, higher shareholder control should lead to higher shareholder value.

Therefore, we should only observe corporate governance structures with high levelsof shareholder control in the long run. However, maximum shareholder controlmight not be optimal in all situations. In an environment without takeover defenses,for example, the United States before the late 1980s, even if a target CEO is opposedto a takeover, large takeover premiums help hostile bids succeed by inducing targetshareholders to fight the CEO’s resistance. The more powerful the target CEO andthe weaker the target shareholders, the higher the takeover premium that is requiredto motivate shareholders to overturn the CEO’s opposition. Shleifer and Vishny(1986) and Stulz (1988) provide theoretical rationales for this result, and Song andWalkling (1993) have empirical evidence. Therefore, giving target CEOs power tomake decisions that are costly to overturn for shareholders can be valuable.However, a great change is evident in the characteristics of mergers and acquisitionsover the past two decades. Merger and acquisition activity in the 1980s wascharacterized by spectacular hostile transactions, while in the 1990s the vast majorityof transactions were done on friendly terms.2

In the 1990s, effective takeover defenses were widely available and hostile offershad only a small chance of success. With this shift in the balance of power towardtarget CEOs, bidders had to focus their efforts on convincing target CEOs to agreeto deals versus enticing target shareholders through large takeover premiums. Oneway to solicit a target CEO’s merger approval at a reduced takeover price is for the

1I use the terms ‘‘merger,’’ ‘‘acquisition,’’ and ‘‘takeover’’ synonymously.2The friendliness of the transactions is initially surprising, because, as Agrawal and Walkling (1994)

find, CEOs of target firms who lose their jobs generally fail to find another senior executive position in any

public corporation within three years after a bid. Schwert (2000) finds little economic difference between

friendly and hostile transactions.

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T. Moeller / Journal of Financial Economics 76 (2005) 167–190 169

bidder to offer private benefits to the target CEO, e.g., positions in the merged firmand improved retirement packages.3 Instead of negotiating the highest possibletakeover premium, target CEOs bargain over their private benefits with the bidder.Target shareholders can intervene and block these transactions, but intervention iscostly. The cost of target shareholder intervention is largely determined by thebalance of power between the target CEO and the target shareholders. The morepowerful the target CEO and the weaker the target shareholders, the higher the costof shareholder intervention and the larger the reduction in the takeover premiumthat the target CEO can allow in return for private benefits. Therefore, in the 1990sthe relationship between target shareholder control and takeover premium should bepositive, while it appears to have been negative in the 1980s.Given that the level of shareholder control is not directly observable, I must rely

on various proxies in my empirical analysis. I consider CEOs to be strong when theyown large fractions of their firms’ stock, there are small outside blockholdings, or alarge fraction of directors are insiders. I empirically show that these proxies for lowtarget shareholder control are related to lower takeover premiums in the 1990s.Combining several of the shareholder control variables to identify distinct cases, Idevelop a proxy for high shareholder control. I find that bidder returns are lower andtarget returns are higher when target shareholders have more control. These resultseliminate an important argument for high managerial power and discretion.4

Financial incentives, in particular the use of options, could substitute for directshareholder control. I use the target CEOs’ option holdings and the sensitivity oftheir value to the underlying stock price as proxies for financial incentives tomaximize shareholder wealth. I find little evidence that the CEOs’ stock optionsaffect takeover premiums.The results here are of substantial economic significance. The various proxies for

low shareholder control and strong CEOs reduce takeover premiums by 5 to 16percentage points. With an average target market value of $1.2 billion, this premiumreduction frees up significant amounts that can be distributed as rents to other parties.There are some related studies. Hartzell et al. (2004) examine target CEOs’ trade-

offs between financial gains, including augmented golden parachutes and merger-related bonuses, and executive positions in the merged firm. They find that financialgains are reduced when target CEOs receive executive positions. Generally, targetCEOs’ payoffs are comparable to the net present value of what they would havereceived without the merger. Takeover premiums, however, seem to be smaller incases in which target CEOs received extraordinary treatment.My study differs from Hartzell et al. (2004) in three ways. First, they focus on the

target CEOs’ trade-off between financial gains and executive positions in the merged

3The idea that strong target CEOs are susceptible to bidder-provided incentives also appears in Morck

et al. (1988a). They determine that targets in friendly transactions have higher share ownership by board

members and are more likely to be run by a founder.4Because shareholders in CEO-dominated target firms are in similar positions as minority shareholders,

this result is consistent with findings in international comparisons of corporate governance features by La

Porta et al. (2000, 2002). They, among others, have shown that better minority shareholder protection is

associated with higher valuations of corporate assets.

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firm, while I relate the level of target shareholder control to bidder and targetannouncement returns. Second, they examine only the benefits of target CEOs anddo not consider bidder returns. Third, my proxies, covering various aspects of thetargets’ corporate governance structures, are much broader than their variables thatmeasure payments to the target CEO in great detail.The analysis here is also related to Wulf (2004), who shows that target managers

receive preferential treatment in mergers of equals compared with mergers ofnonequals. In a detailed analysis of 40 transactions, she finds higher bidder returnsand lower target returns in mergers of equals, which is consistent with my results.My sample, a broader selection of 388 mergers and acquisitions, allows morepowerful tests and more general and robust results. In addition, my study is lesssensitive to the accurate classification of bidders and targets, a difficult task inmergers of equals.The remainder of the paper is organized as follows. Section 2 presents my main

hypothesis. Section 3 develops the proxies for shareholder control. The sampledescription follows in Section 4. I discuss my takeover premium measures in Section5. Section 6 presents the empirical results, and Section 7 examines various robustnesschecks. Section 8 concludes.

2. Main hypothesis

Takeover defenses shift power from target shareholders to target managers. Iftarget managers trade takeover premiums in return for private benefits, targetshareholders lose part of the potential premium they could have received in asuccessful hostile transaction. Therefore, target shareholders could wish to forcetarget managers to maximize takeover premiums. Exerting influence on the targetmanagement’s decisions is easier, the more powerful the shareholders are relative tothe target management. For example, large outside blockholders with boardrepresentation can intervene at a low cost. Hence, strong target CEOs, or weaktarget shareholders, should be associated with reduced takeover premiums.5 I testthis hypothesis. It is the opposite of the prediction derived in the environment ofhostile transactions of the 1980s.

3. Description of proxies

The proxies represent the target firm’s ownership structure, board composition,and position of the CEO.

5An important assumption necessary to translate predictions of merger payoffs to announcement

returns is that the deals are not perfectly predictable. If investors already fully expected the merger,

abnormal announcement returns should be zero. However, I believe that merger and acquisition

announcements are, at least to a large degree, surprises. The relatively low frequency of these transactions

and the significant stock price movements associated with them support this assumption. In addition, I

control for pre-announcement period returns in my regressions.

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3.1. Target CEO share ownership

The most direct way for a CEO to control the firm and make shareholderintervention costly is to own a large fraction of the firm. For example, largeownership will allow the CEO to have a disproportionate impact on boardassignments. Therefore, I use target CEO share ownership, collected from Securitiesand Exchange Commission (SEC) filings, as a proxy for CEO power and expect it tobe negatively related to takeover premiums. An alternative view would be thatmanagerial shareholdings align CEOs’ and shareholders’ goals. In that case, higherownership would lead to higher takeover premiums. However, because compensat-ing target CEOs directly through bidder-provided incentives is always more efficientthan indirectly through increased takeover premiums, I expect the control aspect ofshare ownership to dominate.

3.2. Outside blockholders

As a result of the free-rider problem described in Grossman and Hart (1980),shareholder intervention is more feasible when firms have large blockholders. Idefine shareholders that are listed in the target’s SEC filings as beneficial owners of atleast 5% of the target’s stock as blockholders. (The 5% cutoff is commonly used.For example, the SEC requires firms to identify the owners of 5% or more of a firms’stock.) The larger the blockholdings, the smaller the potential value improvementsthat are required to trigger blockholder intervention. Because inside blockholderscan be expected to support the CEO, the outside blockholdings determine the degreeof shareholder control. Therefore, I expect higher outside blockholdings to lead tohigher takeover premiums.

3.3. Board composition

Blockholders’ influence can be significantly reduced when they lack boardrepresentation. The board of directors makes several critical decisions with respect totakeover offers. For example, it usually has to approve a deal. I define insiders asdirectors who, according to the target’s SEC filings, have an executive position in thefirm, had such a position in the past, or are related to an executive. Outsiders are allboard members without such a connection. I assume that insiders’ incentives arealigned with the CEO’s goals. Then, large fractions of insiders on the board makeshareholder intervention more costly, and the fraction of inside directors should benegatively related to takeover premiums.

3.4. Target CEOs’ financial incentives

Shareholders can control CEOs directly or use financial incentives that reduce theneed for shareholder intervention by aligning CEOs’ objectives with shareholders’goals. I use the number of the target CEOs’ stock options as a fraction of the firms’outstanding shares, the options’ Black and Scholes value, and their value sensitivity

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to changes in the target’s stock price as proxies. In most cases, all options vest oncethe deal closes, and restricted options become exercisable immediately. Conse-quently, large option holdings should motivate target CEOs to negotiate themaximum takeover premium. Age, however, might distort these incentives. Gibbonsand Murphy (1992), for example, show that implicit incentives from career concernsto maximize shareholder wealth are lower for CEOs who are close to retirement.6

3.5. High shareholder control proxy

Only dominant and established target CEOs should have sufficient clout toeffectively influence takeover premiums, e.g., in return for bidder-providedincentives. A CEO should be under less strict supervision when she has had herposition for several years because either she convinced shareholders of herworthiness or shareholders are unable to remove her. Therefore, a short tenure asCEO indicates higher shareholder control. Similarly, when the executive power isconcentrated in the CEO, the CEO presumably has more far-reaching decisionpower. Therefore, shareholder control should be higher when there is a separatechairman or president. The CEO’s control increases with her equity stake, andshareholder control is lower when insiders dominate the board. To identify distinctcases in which suboptimal takeover premiums are highly unlikely, I define my highshareholder control indicator variable to equal one when firms have a separatechairman or president, when CEOs are not large blockholders, when large fractionsof board members are outsiders, and when CEOs have had a short tenure.

4. Sample description

The sample consists of mergers and acquisitions with an announcement datebetween January 1, 1990 and December 31, 1999. The deals are identified in theSecurities Data Company (SDC) Mergers and Acquisitions database. I include onlycompleted transactions with a transaction value of at least $100 million, when boththe bidder and the target are US firms. Furthermore, the bidder must acquire at least25% of the target shares in the transaction and must own at least 50% of the target’sshares afterward. This initial screening gives 5,077 observations. In addition, Iexclude transactions when bidder and target were closely related before the mergerannouncement, e.g., firms with the same parent company, and when the SDCdescribes the bidder as ‘‘Shareholders,’’ ‘‘Investor Group,’’ ‘‘Investor,’’ or‘‘Creditors.’’ This reduces the sample to 2,039 observations. I exclude financialinstitutions and real estate trusts and require that both bidder and target are

6I examine the influence of the target CEOs’ age on takeover premiums in various specifications without

finding any significant relation (results not reported). Similarly, a CEO with a long tenure at the firm could

have built up more firm-specific human capital that she could lose in a takeover. She might seek

compensation, potentially through private benefits. Alternatively, longer tenure could indicate more CEO

control. I emphasize the latter interpretation in the remainder of the paper.

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identifiable by the Center for Research in Security Prices (CRSP) and Compustat.These requirements leave 855 transactions. Checking if data items for bidder andtarget for the relevant dates are available on CRSP and Compustat reduces thesample to 704 observations. I am able to find proxy statements or 10-Ks for bidderand target for 609 deals. Because I measure the effect of the merger on the bidder, Irequire that the target’s market value of equity is at least 5% of the bidder marketvalue of equity. This requirement eliminates 152 transactions. To prevent miscodingof bidder and target from affecting my results, I exclude deals in which the target’smarket value of equity exceeds the bidder’s equity by more than 50% (nineobservations). To keep outliers or potential data errors from driving the results, Ieliminate observations in which the target’s excess announcement return exceeds100% (nine observations) or is lower than �50% (one observation). I also eliminate25 observations of highly leveraged targets with long-term debt more than threetimes as large as the market value of equity. Collectively, these restrictions reduce thesample size by 178, to 431 observations. Missing data items reduce the final samplesize to 388. I am able to calculate the takeover premium for 373 observations.Announcement dates are taken from the SDC Mergers and Acquisitions database.

The SDC database also provides data on the deal attitude, the acquisition mode, and thefraction of the takeover price that was paid in cash. Standard industrial classification(SIC) codes and some control variables are from Compustat. The focus of my analysis,however, is on the corporate governance variables that I collect from SEC filings.The proxy statements provide the data on the CEO, the board, and blockholders.

For the CEO, I record the tenure in her position, her share ownership, whether she isthe founder, her option holdings, and whether the firm has a separate chairman orpresident. I also calculate the Black and Scholes value of her options and thesensitivity of the value of her option holdings to a 1% price change in the underlyingstock price using the procedure described in Core and Guay (1999, 2002). Core andGuay’s method allows an estimation of the Black and Scholes value of executiveoption holdings using the data provided in a single proxy filing. I record the numberof insiders and outsiders on the board and blockholdings for each target firm.I also conduct a search for deal-related announcements in the Wall Street Journal

and Public Relations (PR) Newswire using the Dow Jones News Retrieval (DJNR). Iuse DJNR to verify the accuracy of the announcement dates. I record any deal-related rumors prior to the announcement date, mentioning of competitive bidders,changes to the offer after the announcement (offer increased, offer decreased),unexpected regulatory approval problems, and indications regarding the friendlinessof the transaction (clearly friendly). Furthermore, I record if the CEO is expected toassume, or is offered, an executive or board position in the merged firm.

5. Takeover premium measurement

I calculate the announcement return as the excess return over the CRSP equallyweighted index from five days before to five days after the announcement date. Thismeasure has several advantages. It takes expected movements in the bidder stock

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price into account, which is important when the bidder pays with stock. The shortevent window ensures that most of the return can be attributed to the merger event.However, the announcement return represents a combination of the takeover priceand the probabilities that the transaction closes, fails, or that another bidderemerges. (This problem is mitigated because the vast majority of the sample involveclearly friendly transactions and all deals eventually close.)Therefore, I eliminate the probability of the offer success by using

Takeover premium ¼price per share offered by bidder

target0s share price six days prior to announcement� 1:

In stock offers, I determine the offered price by multiplying the number of biddershares offered per target share by the bidder’s closing price on the announcementdate. When offers specify price ranges that depend on the bidder’s or target’s stockprice or both prior to the closing of the deal, I use the exchange ratios that wouldresult if current stock prices at the end of the announcement date prevailed.Unfortunately, some stock offers, through imbedded options, are so complicatedthat calculating an accurate takeover price is extremely difficult, or the exactexchange ratios are simply not available. My sample loses 15 observations that way.

6. Empirical results

Table 1 shows the majority of mergers in the sample occurred in the second half ofthe 1990s. Bidder announcement returns average �2.9%. Target announcementreturns and takeover premiums average 21.3% and 30.8%, respectively. Thecombined market value of bidder and target increases on average by about 2%.According to SDC classifications, only seven mergers of equals are in the sample, lessthan 4% of deals are hostile, and tender offers occur in roughly 19% of theobservations. Of all deals, about 93% have no indication of any hostility, only 6%face competitive bidders, and less than 2% involve financially distressed targets, i.e.,firms with total liabilities exceeding total assets. CEOs control on average 6.8% ofthe targets’ equity. The target market value of equity averages about 32% of thebidder’s market value. Table 2 shows the correlation between my proxies and thecontrol variables. The magnitudes of the correlations do not suggest any problemsstemming from multicollinearity.

6.1. Influence of control variables

Table 3 shows ordinary least squares (OLS) regressions of the takeover premiumon my proxies.7 The coefficients on the control variables are similar in all estimations.

7I check the takeover premium measures for non-normality and left-truncation. The distributions seem

close to normal, and little evidence emerges of truncation. Therefore, using OLS as the estimation method

is appropriate. I also conduct my analyses using a truncated regression model. The results are qualitatively

unchanged from those presented here.

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CEO is founder indicates the target CEO being the founder or a member of thefounder’s family or having been the CEO since the inception of the firm. The pointestimates appear to be positive but are generally insignificant.Hostile indicates that the SDC Mergers and Acquisitions database designates

a deal as hostile. Only 3.6% of all transactions are hostile, but the targetsin these hostile transactions receive about 10 percentage points highertakeover premiums than targets in friendly deals. Takeover premiums aresignificantly lower when the SDC database describes a deal as a tender offer(tender offer).The larger the target relative to the bidder, the lower is the takeover premium,

as indicated by the highly significant and negative coefficient on ratio oftarget to bidder market value of equity. The size of the target, measured by thelogarithm of total assets, is not significant. The target’s leverage seems to increase thetakeover premium, but long-term debt/market value of equity is marginallyinsignificant.Only 6% of the sample transactions involve a competitive bidder. The existence of

a competitive bidder does not affect takeover premiums in my sample. Consistentwith the prior literature, e.g., Travlos (1987), paying for the target with cash (fractionpaid with cash) is a positive signal that significantly increases takeover premiums.This effect could also be the result of the individual investors’ inability to defercapital gains taxes in cash offers.Prior rumors indicates evidence of rumors regarding the merger prior to the

announcement, but its coefficient is insignificant. A better proxy for the anticipationof a takeover seems to be the target’s excess return over the 200 trading days prior tothe announcement window. Excess return 200 days prior has a highly significant andnegative impact on takeover premiums. Not all of excess return 200 days prior’snegative influence can necessarily be attributed to rumors of a takeover. Forexample, it could also be driven by a target’s particularly poor performance prior tothe merger announcement. Regardless of what is the main contributor to excessreturn 200 days prior’s significance, it serves its purpose as a control for effects onthe takeover premium that are unrelated to my proxies for the level of targetshareholder control.Days to effective or delisting date records the number of days between the

announcement date and the earlier of the merger’s effective date and the target’sdelisting date. It serves to control for the influence on the takeover premium of anyremaining uncertainty regarding the successful completion of the transaction. Thetime to the completion of the deal appears to reduce takeover premiums but isinsignificant.In addition to the control variables reported in Table 3, I use industry

dummies, an indicator for bidder and target in the same industry (sameindustry), year dummies for 1995 through 1999, a dummy when DJNRarticles indicate problems with the regulatory approval of the transaction(regulatory problems), a financial distress dummy when total liabilities exceedtotal assets (distressed target), a proxy for the target’s profitability (netincome/total assets), and a proxy for the target’s efficiency (sales/total

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Table 1

Summary statistics, indicator variables, and number of observations. Panel A shows selected summary statistics. The announcement returns are in excess of the

equally weighted Center for Research in Security Prices index. The announcement return period spans 11 trading days starting five days before the

announcement. Target realized return covers the period from five days before the announcement to the earlier of the effective or the target’s delisting date.

Takeover premium is calculated as the price per share offered by the bidder, using the closing prices at the announcement date for stock offers, divided by the

target’s closing price six days prior to the announcement date minus one. Combined announcement return is the total percentage change in the market value of

equity of bidder and target. The market values of equity and option values are calculated as of six days before the announcement date. The data on chief

executive officer (CEO) share ownership, board composition, and blockholdings are from the latest available proxy filing or 10-K before the announcement

date. Governance index is calculated from Investor Responsibility Research Center (IRRC) data as in Gompers et al. (2003). Panel B shows the fractions of the

observations in which the indicator variables are equal to one. Hostile, clearly friendly, tender offer, competitive bidder, and merger of equals are from the

Securities Data Company Mergers and Acquisitions database. Offer increased, offer decreased, and prior rumors are hand-collected from Wall Street Journal

and Public Relations Newswire articles. Poison pill is from IRRC data. Delaware corporation and staggered board are from proxy and 10-K filings. Distressed

target equals one when the target’s total liabilities exceed total assets. Same industry equals one when the bidder and the target share the same primary industry.

Panel C shows the distribution of observations over time. About 83% of the observations are in the second half of the sample period.

Panel A: selected summary statistics

Variable Mean Median Standard deviation Number of observations

Target announcement return 0.2131 0.1848 0.2017 388

Takeover premium 0.3081 0.2766 0.2240 373

Target realized return 0.2097 0.1893 0.3271 388

Bidder announcement return �0.0291 �0.0303 0.0989 388

Combined announcement return 0.0173 0.0164 0.0963 388

Target market value equity (millions of dollars) 1,166 291 4,349 388

Bidder market value equity (millions of dollars) 4,732 1,472 13,200 388

Ratio of target to bidder market value of equity 0.3167 0.2234 0.2695 388

Percent CEO share ownership 0.0677 0.0200 0.1188 387

Amount CEO share ownership (thousands of dollars) 31,640 7,882 108,952 387

Percent inside directors 0.3112 0.2857 0.1612 388

Percent outside blockholdings 0.2442 0.2356 0.1757 387

Option value (thousands of dollars) 9,273 2,923 24,583 305

Option price sensitivity (thousands of dollars/1% price change) 122 40 331 305

Governance index 9.08 9.00 2.93 173

Fraction paid with cash 0.2740 0.0000 0.3861 388

Excess return 200 days prior �0.0745 �0.1056 0.3019 388

Days to effective or delisting date 148 112 130 388

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Panel B: statistics on indicator variables

Indicator variable Number of observations in which indicator variable equals 1 Percent of sample Number of observations

Hostile 14 3.6 388

Clearly friendly 358 92.7 386

Tender offer 73 18.8 388

Competitive bidder 23 6.0 386

Merger of equals 7 1.8 388

Offer increased 24 6.2 386

Offer decreased 11 2.8 386

Prior rumors 34 8.8 386

Poison pill 89 51.4 173

Delaware corporation 223 57.8 386

Distressed target 7 1.8 388

Same industry 276 71.1 388

CEO is founder 77 19.9 387

Percent CEO share ownership X5% 119 30.7 387

Percent inside directors X40% 123 31.7 388

Outside blockholdings p10% 94 24.3 387

CEO options o1% 160 48.6 329

Option price sensitivity o$20,000 107 35.1 305

Separate chairman or president 207 53.4 388

Tenure X5 years 199 53.8 370

Staggered board 190 49.4 385

Percent inside director o40%and percent CEO share ownership o20% 62 16.8 369

and separate chairman or president

and tenure o5 years

Panel C: observations by year

Year 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Total

Number of observations 12 12 8 11 24 49 39 80 87 66 388

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Table 2

Correlation matrix. The table shows the pairwise correlation coefficients among the target shareholder control proxies and between the target shareholder

control proxies and control variables. Bold coefficients indicate significance at the 0.05 level or higher. CEO ¼ chief executive officer. MV ¼ market value.

Variable Percent

CEO share

ownership

X5%

Log (percent

CEO share

ownership)

Log (amount

CEO share

ownership+1)

Percent inside

directors

X40%

Log (percent

inside directors)

Outside

blockholdings

p10%

CEO

options

o1%

High

shareholder

control

proxy

Percent CEO share ownership X5% 1.000

Log (percent CEO share ownership) 0.732 1.000

Log (amount CEO share ownership+1) 0.511 0.720 1.000

Percent inside directors X40% 0.351 0.341 0.196 1.000

Log (% inside directors) 0.420 0.439 0.216 0.755 1.000

Outside blockholdings p10% �0.025 �0.096 0.107 �0.050 �0.091 1.000

CEO options o1% 0.039 �0.193 �0.003 �0.105 �0.083 0.155 1.000

High shareholder control proxy �0.251 �0.241 �0.225 �0.310 �0.158 �0.152 0.100 1.000

Log (amount CEO option value+1) �0.267 �0.181 0.095 �0.137 �0.190 �0.070 �0.460 0.078

Option price sensitivity o$20,000 0.213 0.117 �0.170 0.025 0.094 0.025 0.440 �0.047

CEO is founder 0.467 0.489 0.383 0.271 0.313 �0.011 �0.002 �0.172

Hostile �0.129 �0.090 0.002 �0.072 �0.021 0.116 0.038 0.025

Tender offer �0.107 �0.024 �0.174 �0.045 �0.008 �0.073 �0.034 0.112

Ratio of target to bidder MV equity �0.048 �0.120 0.068 0.010 �0.028 0.040 0.029 0.015

Log (target total assets) �0.365 �0.504 0.057 �0.271 �0.375 0.277 0.197 0.105

Long-term debt/MV equity �0.023 �0.026 �0.047 �0.041 �0.058 0.076 �0.097 �0.061

Competitive bidder �0.047 �0.059 0.005 �0.008 0.017 0.010 �0.034 0.052

Fraction paid with cash �0.054 0.024 �0.127 0.001 0.011 �0.053 0.016 0.078

Prior rumors 0.013 �0.039 �0.021 0.023 0.009 0.036 �0.005 0.046

Excess return 200 days prior 0.072 0.064 0.179 0.057 0.057 0.073 0.017 0.006

Days to effective or delisting date �0.128 �0.334 �0.190 �0.113 �0.194 0.331 0.143 �0.021

Same industry �0.097 �0.123 �0.075 �0.067 �0.104 0.079 �0.058 0.000

Distressed target �0.006 0.028 0.048 0.074 0.028 0.014 �0.059 �0.009

Sales/total assets 0.144 0.178 0.093 0.165 0.212 �0.035 �0.015 �0.028

Net income/total assets 0.045 0.024 0.072 0.099 0.076 0.065 �0.004 �0.139

Regulatory problems �0.048 �0.038 �0.012 �0.010 �0.053 0.058 �0.022 �0.010

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assets).8 These control variables are either insignificant or have no relevantinterpretation in the context of this study (e.g., the industry and year dummyvariables). However, they control for characteristics that have been shown to affectstock returns.

6.2. Impact of target characteristics on takeover premiums

The influence of CEO share ownership is likely nonlinear. A change in ownershipfrom 1% to 6% is arguably more relevant than a change from 35% to 40%. Toreduce the potential impact of the nonlinearities, I use indicator variables. PercentCEO share ownershipX5% equals one when the target CEO controls at least 5% ofthe target’s shares.9 The CEO is a blockholder in about 31% of the sample firms.Table 3 shows that the coefficient on this indicator variable is significantly negative.The point estimate indicates that high target CEO share ownership reduces takeoverpremiums by almost 7 percentage points.When at least 40% of board members are classified as insiders, the takeover

premium is significantly reduced by almost 7 percentage points. I choose the 40%cutoff because it identifies about one-third of the sample. The negative impact ofhigh fractions of inside directors is consistent with the result for the CEO shareownership. The more control the target CEO has, the lower is the takeover premium.I measure outside blockholdings as total percentage holdings of blockholders, i.e.,

holders of at least 5% of the firm’s stock, minus the CEO’s percentage holdings. Thisvariable faces the same nonlinearity issues as CEO share ownership and boardcomposition. Therefore, I only report the impact of an indicator variable that equalsone when outside blockholdings do not exceed 10%, a condition satisfied by about24% of the sample. As expected, low outside blockholdings significantly decreasetakeover premiums by almost 5 percentage points.Next, I jointly estimate the effect of the indicator variables for high CEO share

ownership, a high fraction of inside directors, and low outside blockholdings ontakeover premiums. Column 4 of Table 3 shows that all three proxies retain theirsigns, but their statistical significance is somewhat lower with the proxy for lowoutside blockholdings becoming marginally insignificant. However, an F-test showsthe joint significance of the three proxies at the 1% level.Why is CEO share ownership still an important determinant of entrenchment

when the presence of takeover defenses indicates that most managers are entrenched?

8The industry classification I use is based on Table 1 in Teoh et al. (1998) that distinguishes 17 industries

and allocates firms based on two-digit SIC codes.9The cutoff level for the indicator variables are determined to accomplish two goals. First, the resulting

indicator variable should equal one for a sufficiently large portion of the sample to have statistical power.

Second, the resulting indicator variable should be restricted to equal one for a sufficiently small portion of

the sample to represent distinct cases. While the 5% cutoff is arbitrary, Morck et al. (1988b) use the same

level and the SEC defines blockholders as owners of 5% or more of a firm’s equity. More important,

small changes in the cutoff of this and all other proxies in my paper do not affect my results qualitatively.

Table 1 shows the proportions of observations in which the various indicator variables are equal to one.

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Table 3

Impact of target characteristics on takeover premiums. Takeover premium is the dependent variable. All equations are estimated using ordinary least squares

regressions with the heteroskedasticity adjustment by Davidson and MacKinnon (1993). In addition to the reported control variables, the coefficients of the

following control variables, which either are insignificant or have no relevant interpretation in the context of this study, are not reported: industry dummies, an

indicator for bidder and target in the same industry, year dummies for 1995 through 1999, a dummy when Dow Jones News Retrieval articles indicate problems

with the regulatory approval of the transaction, a financial distress dummy (total liabilities exceed total assets), a proxy for the target’s profitability (net income

as a fraction of total assets), and a proxy for the target’s efficiency (sales as a fraction of total assets). The last row shows the result of an F-test of the three

target shareholder control proxies being jointly equal to zero. This hypothesis is rejected at the 0.01 level for the larger sample that does not require option data

and at the 0.10 level for the sample with option data. High target chief executive officer (CEO) share ownership, large fractions of inside directors, and low

outside blockholdings are associated with lower takeover premiums. Target CEO option holdings do not affect takeover premiums. T-statistics are in

parentheses. ��, ��, and � denote significance at the 0.01, 0.05, and 0.10 level, respectively. MV ¼ market value.

Takeover premium (1) (2) (3) (4) (5) (6)

Percent CEO share ownership X5% �0.0662�� 0.0546� �0.0362

(�2.37) (�1.90) (�1.23)

Percent inside directors X40% �0.0687�� 0.0614�� 0.0572�

(�2.44) (�2.15) (�1.91)

Outside blockholdings p10% �0.0499� �0.0452 �0.0275

(�1.78) (�1.62) (�0.87)

CEO optionso1% �0.0157 �0.0118

(�0.54) (�0.41)

CEO is founder 0.0326 0.0178 0.0074 0.0441 �0.0148 0.0184

(0.97) (0.54) (0.23) (1.33) (�0.44) (0.54)

Hostile 0.0968� 0.0969� 0.1130� 0.1102� 0.0962� 0.1043�

(1.68) (1.70) (1.93) (1.87) (1.72) (1.77)

Tender offer �0.1066�� 0.1005�� 0.0986�� 0.1099�� 0.0794 �0.0894�

(�2.25) (�2.12) (�2.04) (�2.36) (�1.54) (�1.76)

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Ratio of target to bidder �0.2007�� 0.1938�� 0.2096�� 0.1951�� 0.1786�� 0.1708��

market value of equity (�4.69) (�4.60) (�4.98) (�4.74) (�4.16) (�3.97)

Log (target total assets) �0.0055 �0.0046 0.0043 �0.0062 0.0045 �0.0016

(�0.50) (�0.43) (0.39) (�0.54) (0.41) (�0.13)

Long-term debt/MV of equity 0.0462 0.0361 0.0360 0.0432 0.0340 0.0366

(1.50) (1.19) (1.16) (1.42) (0.98) (1.07)

Competitive bidder �0.0493 �0.0472 �0.0521 �0.0509 �0.0797 �0.0836

(�0.74) (�0.73) (�0.77) (�0.78) (�1.26) (�1.38)

Fraction paid with cash 0.1276�� 0.1288�� 0.1204�� 0.1293�� 0.1340�� 0.1401��

(2.61) (2.59) (2.40) (2.71) (2.66) (2.84)

Prior rumors �0.0097 �0.0150 �0.0136 �0.0125 �0.0582 �0.0538

(�0.19) (�0.29) (�0.26) (�0.25) (�0.92) (�0.88)

Excess return 200 days prior �0.1564�� 0.1582�� 0.1546�� 0.1500�� 0.1827�� 0.1729��

(�3.71) (�3.65) (�3.63) (�3.49) (�4.13) (�3.83)

Days to effective or delisting date �0.0002 �0.0002 �0.0002 �0.0001 �0.0003 �0.0002

(�1.36) (�1.34) (�1.26) (�1.02) (�1.52) (�1.16)

Intercept 0.2903�� 0.2774�� 0.2387�� 0.2953�� 0.2086�� 0.2360��

(3.16) (3.14) (2.65) (3.21) (2.36) (2.54)

Adjusted R2 0.18 0.17 0.17 0.19 0.19 0.20

Number of observations 372 373 372 372 315 315

Pr (F-test) 0.0042�� 0.0753�

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Here, CEO share ownership is a measure of managerial power, not entrenchment.Because large equity stakes convey power, they measure aspects of the CEO’s powerthat are not necessarily picked up by other proxies, such as insiders on the board.More target CEO power makes target shareholder intervention more costly andtherefore increases the magnitude by which takeover premiums can be reducedwithout triggering shareholder actions.One proxy for financial incentives is the target CEO’s total option holdings as a

fraction of shares outstanding. Again, I create an indicator variable that equals onewhen the CEO option holdings are less than 1%. Opposing effects might confoundthe impact on the takeover premium. If options serve their purpose of motivatingmanagers to maximize shareholder wealth, they would increase the takeoverpremium. However, large holdings of exercisable options can be converted intocommon stock. As shown above, high levels of CEO share ownership reducetakeover premiums because they give the CEO control.10 Column 5 shows no effectof the target CEOs’ low option holdings indicator on the takeover premium. Whenthe other proxies for target shareholder control are included with the low optionholdings indicator, the low option holdings indicator remains insignificant and thesignificance of the other proxies is reduced, likely as a result of the lower number ofobservations caused by missing option data. Still, an F-test shows that high targetCEO share ownership, high fractions of inside directors, and low outsideblockholdings remain jointly significant.Overall, Table 3 provides strong support that the three proxies for lower target

shareholder control (percent CEO share ownership X5%, percent inside directorsX40%, and outside blockholdings p10%) are associated with lower takeoverpremiums. The target CEOs’ option holdings do not seem to affect takeoverpremiums.

6.3. Bidder effects

My high shareholder control indicator variable for targets with very high levels ofshareholder control equals one when the fraction of inside directors is smaller than40%, the target CEO’s share ownership is less than 20%, the target CEO’s tenure inher position has been less than five years, and the target has a chairman or presidentseparate from the CEO. This variable selects the 17% of the sample firms with thehighest levels of target shareholder control. Table 4 shows that the high shareholdercontrol indicator variable has a significantly positive effect on the takeover premiumand a significantly negative effect on bidder announcement returns. This resultsuggests that target CEOs who lack such high shareholder control are susceptible toagree to merger terms that are more favorable to bidders.

10In addition, large numbers of options might have been granted in the special case when a merger or

takeover could have been anticipated. For example, occasionally CEOs are hired specifically to sell a target

firm that is in a crisis. While it could be efficient to compensate the CEO with highly sensitive options, the

takeover premium should be low in these cases because financial distress weakens the target’s negotiating

power.

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Table 4

Impact of high shareholder control on takeover premiums, bidder returns, and target chief executive

officer (CEO) benefits. Takeover premium is the dependent variable in Column 1 and bidder

announcement return in Column 2. Columns 1 and 2 are estimated using ordinary least squares

regressions with the heteroskedasticity adjustment by Davidson and MacKinnon (1993). High target

shareholder control is associated with higher takeover premiums and lower bidder announcement returns.

The dependent variable in the probit estimation in Column 3 equals one when the bidder offers an

executive or board position to the target CEO, and zero otherwise. This information is available only for a

subset of the sample. The reported coefficients represent marginal effects (dF/dX). High target shareholder

control reduces the probability of the target CEO’s receiving a job offer in the merged firm by almost 21%.

In addition to the reported control variables, the coefficients of the following control variables, which

either are insignificant or have no relevant interpretation in the context of this study, are not reported:

long-term debt as a fraction of the market value of equity, indicator for the existence of a competitive

bidder, indicator for merger rumors prior to the announcement date, time between the announcement date

and the earlier of the effective or the target’s delisting date, industry dummies, an indicator for bidder and

target in the same industry, year dummies for 1995–1999, a dummy when Dow Jones News Retrieval

articles indicate problems with the regulatory approval of the transaction, a financial distress dummy

(total liabilities exceed total assets), a proxy for the target’s profitability (net income as a fraction of total

assets), and a proxy for the target’s efficiency (sales as a fraction of total assets). T- and Z-statistics are in

parentheses. ��, ��, and � denote significance at the 0.01, 0.05, and 0.10 level, respectively.

(1) Takeover

premium

(2) Bidder

return

(3) Target CEO

position

Percent inside directorso40%and percent CEO share ownershipo20% 0.0780�� 0.0361�� 0.2075��

and separate chairman or president (2.25) (�2.60) (�2.02)

and tenureo5 yearsHostile 0.1090� �0.0163 �0.5685�

(1.81) (�0.55) (�1.91)

Tender offer �0.1031�� 0.0181 �0.0348

(�2.08) (0.82) (�0.21)

Ratio of target to bidder �0.2043�� 0.0071 �0.2303

market value of equity (�4.46) (�0.29) (�1.55)

Log (target total assets) �0.0009 0.0031 �0.0034

(�0.08) (0.73) (�0.10)

Fraction paid with cash 0.1158�� 0.0292 �0.2072

(2.26) (1.35) (�1.29)

Excess return 200 days prior �0.1624�� 0.0338

(�3.47) (0.24)

Intercept 0.2484�� 0.0571�

(2.68) (�1.71)

Adjusted R2/log likelihood 0.17 0.03 �109.67

Number of observations 354 354 200


Why would target CEOs agree to lower takeover premiums? One explanationcould be bidder-provided incentives for the target CEO. My only proxy here is anindicator variable that equals one when the target CEO is offered an executive orboard position in the merged firm.11 I am able to collect this information for 200

11Matsusaka (1993) finds higher bidder returns when the target management is retained. He explains his

result as investors putting positive value on the target management’s expertise remaining with the merged

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deals. High target shareholder control significantly reduces the probability of atarget CEO receiving the benefit of a job offer by about 20%. Arguably, this is aweak and incomplete proxy for bidder-provided private benefits for the target CEO.However, while clearly no proof, the results are at least consistent with the intuitionthat some target CEOs trade takeover premium for private benefits.

7. Robustness

I conduct several tests to verify the robustness of the results.

7.1. Cutoff levels of indicator variables

Several of my proxies are indicator variables that rely on somewhat arbitrarycutoff levels. One concern could be that the results obtain only for a very narrowrange of cutoffs. I examine the robustness of my results by varying the cutoff levels.12

For example, I vary the high CEO share ownership indicator (5% cutoff in thepaper) between 2.5% and 20%, the high inside director indicator (40% cutoff in thepaper) between 30% and 50%, and the large outside blockholdings indicator (10%cutoff in the paper) between 5% and 15%. The point estimates and significancelevels depend on the cutoff levels, but signs never reverse. Qualitatively, the resultsstay the same and are robust to small changes in the cutoff levels. Furthermore,Table 5 shows that the logarithm of the target CEOs’ share ownership is negativelycorrelated with the takeover premium and significant at the 5% level. The logarithmof the fraction of inside directors seems to be negatively correlated with the takeoverpremium, but in contrast to the corresponding indicator variable it is marginallyinsignificant. Firms that have both a low fraction of inside directors and largeoutside blockholdings achieve about 8 percentage points higher takeover premiums,an effect that is statistically significant at the 1% level.

7.2. Effect of CEO share ownership and option holdings

Table 3 shows a strong negative effect of the target CEOs’ percentage shareownership on takeover premiums, but no effect of the percentage CEOs optionholdings. Column 4 of Table 5 presents a horse race between the logarithm of thevalue of target CEOs’ stock and the logarithm of the Black and Scholes value of thetarget CEOs’ options. Again, CEO share ownership is significantly associated withlower takeover premiums, while options have no effect. Column 5 repeats theanalysis with the indicators for high CEO share ownership and low sensitivity of

(footnote continued)

firm. His sample period coincides with the conglomerate merger wave of the late 1960s and has a large

portion of diversifying acquisitions. Because diversifying mergers were rare in the 1990s and retaining

target managers’ expertise was arguably less important, viewing executive positions in the merged firm as

perks instead of retained expertise seems more plausible during my sample period.12Results and tables are available upon request from the author.

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Table 5

Robustness of share ownership, board composition, and chief executive officer (CEO) options. Takeover

premium is the dependent variable. All equations are estimated using ordinary least squares regressions

with the heteroskedasticity adjustment by Davidson and MacKinnon (1993). In addition to the reported

control variables, the coefficients of the following control variables, which either are insignificant or have

no relevant interpretation in the context of this study, are not reported: long-term debt as a fraction of the

market value of equity, indicator for the existence of a competitive bidder, indicator for merger rumors

prior to the announcement date, time between the announcement date and the earlier of the effective or the

target’s delisting date, industry dummies, an indicator for bidder and target in the same industry, year

dummies for 1995–1999, a dummy when Dow Jones News Retrieval articles indicate problems with the

regulatory approval of the transaction, a financial distress dummy (total liabilities exceed total assets), a

proxy for the target’s profitability (net income as a fraction of total assets), and a proxy for the target’s

efficiency (sales as a fraction of total assets). Columns 1–3 show that the results for CEO share ownership

and board composition do not depend on the specific definition of indicator variables. Columns 4 and 5

test whether target CEO stock or option holdings have a stronger affect on takeover premiums. T-statistics

are in parentheses. ��, ��, and � denote significance at the 0.01, 0.05, and 0.10 level, respectively.

Takeover premium (1) (2) (3) (4) (5)

Log (percent CEO share

ownership)

�0.0195��

(�2.46)

Log (percent inside directors) �0.0358

(�1.50)

Percent inside directorso40% 0.0790��

and outside blockholdings

410%(3.39)

Log (amount CEO share

ownership +1)

�0.0148�

(�1.76)

Log (amount CEO option value

+1)

0.0001

(0.02)

Percent CEO share ownership

X5%

�0.0555�

(�1.87)

Option price sensitivityo$20,000 �0.0450

(�1.44)

Hostile 0.1034� 0.1033� 0.1169�� 0.0693 0.0701

(1.74) (1.74) (2.03) (1.30) (1.37)

Tender offer �0.1059�� 0.0976�� 0.1041�� 0.0892� �0.0869�

(�2.09) (�2.03) (�2.21) (�1.74) (�1.79)

Ratio of target to bidder �0.1994�� 0.1991�� 0.1980�� 0.1862�� 0.1904��

market value of equity (�4.47) (�4.63) (�4.87) (�4.11) (�4.26)

Log (target total assets) �0.0111 �0.0038 0.0000 0.0136 �0.0048

(�0.97) (�0.35) (0.00) (1.14) (�0.42)

Fraction paid with cash 0.1309�� 0.1252�� 0.1242�� 0.1258�� 0.1367��

(2.58) (2.48) (2.54) (2.50) (2.82)

Excess return 200 days prior �0.1590�� 0.1573�� 0.1526�� 0.1798�� 0.1956��

(�3.69) (�3.66) (�3.53) (�3.82) (�4.24)

Intercept 0.2388�� 0.2173�� 0.1913�� 0.2696�� 0.2609��

(2.62) (2.35) (2.19) (2.32) (2.56)

Adjusted R2 0.17 0.16 0.19 0.21 0.22

Number of observations 364 373 372 294 294


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option prices to underlying stock price (change in option value o$20,000 per 1%change in stock price). Again, the high share ownership indicator is significantlynegative, while the effect of the options’ sensitivity is insignificant. One explanationfor the stronger effect of CEO share ownership is that in my sample the averagevalue of the CEOs’ stock is about three times higher than the value of their options.

7.3. Takeover defenses

Takeover defenses could affect takeover premiums. However, they appear to havelittle impact in my sample.

7.3.1. Staggered boards

Bebchuk et al. (2002) point out that staggered boards are effective antitakeovertools, often to the detriment of target shareholders when bids fail. They find that‘‘effective’’ staggered boards, i.e., boards that cannot be dismantled without havingcontrol of the board, have the strongest antitakeover effects. Cotter et al. (1997) findthat independent boards and poison pills increase takeover premiums. Comment andSchwert (1995) determine not only that poison pills and share control laws areassociated with higher takeover premiums, but also that these antitakeover measuresdo not seem to prevent takeovers.My sample does not allow any inferences on the effect of antitakeover measures

on the probability of receiving a bid or the probability of deal success. Columns 1and 2 of Table 6 show that staggered boards by themselves do not seem to affecttakeover premiums and that the fraction of insiders on the board appears to be amore important influence. However, when an indictor for insider-controlledstaggered boards is added, staggered boards seem to increase takeover premiumsas long as they are independent. Insider-controlled staggered boards are associatedwith lower takeover premiums. It appears that the antitakeover effect of a staggeredboard can be used for and against target shareholders’ interests, depending on whothe directors are. This result provides some insight as to why some studies findpositive and others find harmful effects of antitakeover measures. It also relates toBlack and Kraakman’s (2002) ‘‘hidden value’’ model. If a target’s true value is onlyvisible to directors and hidden to target shareholders and potential bidders, then astaggered board might prevent target shareholders from selling their shares at toolow a price.

7.3.2. State of incorporation

State laws differ substantially in the degree of takeover defenses they provide orallow. Most firms are able to choose their state of incorporation based on tax andlegal considerations. Delaware law, e.g., allows a host of takeover defenses andabout 58% of my sample firms are incorporated in that state. Incorporation inDelaware could be a takeover defense, but Column 3 of Table 6 shows that beingincorporated in Delaware does not affect takeover premiums. (Daines, 2001, findsthat being incorporated in Delaware increases firms’ Tobin’s Q and their probabilityof receiving a takeover bid and being acquired.)

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Table 6

Impact of takeover defenses on takeover premiums. Takeover premium is the dependent variable. All

equations are estimated using ordinary least squares regressions with the heteroskedasticity adjustment by

Davidson and MacKinnon (1993). In addition to the reported control variables, the coefficients of the

following control variables, which either are insignificant or have no relevant interpretation in the context

of this study, are not reported: long-term debt as a fraction of the market value of equity, indicator for the

existence of a competitive bidder, indicator for merger rumors prior to the announcement date, time

between the announcement date and the earlier of the effective or the target’s delisting date, industry

dummies, an indicator for bidder and target in the same industry, year dummies for 1995–1999, a dummy

when Dow Jones News Retrieval articles indicate problems with the regulatory approval of the

transaction, a financial distress dummy (total liabilities exceed total assets), a proxy for the target’s

profitability (net income as a fraction of total assets), and a proxy for the target’s efficiency (sales as a

fraction of total assets). The results show that staggered boards with high fractions of inside directors

decrease takeover premiums while Delaware incorporation, poison pills, and the governance index seem to

have no effect. T-statistics are in parentheses. ��, ��, and � denote significance at the 0.01, 0.05, and 0.10level, respectively.

Takeover premium (1) (2) (3) (4) (5)

Percent inside directors X40% �0.0654�� 0.0247

(�2.29) (�0.69)

Staggered board 0.0295 0.0576��

(1.20) (2.09)

Staggered board �0.0907�

and inside directors X40% (�1.72)

Delaware corporation 0.0079

(0.32)

Governance index �0.0005

(�0.07)

Poison pill �0.0319

(�0.77)

Hostile 0.0978� 0.1005� 0.0975� 0.1055 0.1036

(1.73) (1.85) (1.69) (1.30) (1.25)

Tender offer �0.1050�� 0.1051�� 0.0984�� 0.2035�� 0.2125��

(�2.21) (�2.19) (�1.99) (�2.86) (�2.95)

Ratio of target to bidder �0.1948�� 0.1875�� 0.2052�� 0.3069�� 0.3089��

market value of equity (�4.60) (�4.48) (�4.77) (�3.45) (�3.44)

Log (target total assets) �0.0065 �0.0068 0.0008 0.0322�� 0.0341��

(�0.60) (�0.63) (0.07) (1.99) (2.19)

Fraction paid with cash 0.1296�� 0.1305�� 0.1272�� 0.2533�� 0.2613��

(2.60) (2.59) (2.44) (3.56) (3.56)

Excess return 200 days prior �0.1493�� 0.1494�� 0.1594�� 0.0991 �0.1023

(�3.48) (�3.51) (�3.70) (�1.17) (�1.18)

Intercept 0.2726�� 0.2603�� 0.2444�� 0.1313 0.1359

(3.09) (2.94) (2.71) (0.86) (1.08)

Adjusted R2 0.17 0.18 0.16 0.25 0.25

Number of observations 370 370 371 169 169


7.3.3. Governance index

Gompers et al. (2003) find that firms with a lower governance index (constructedfrom the Investor Responsibility Research Center, IRRC, dataset), i.e.,stronger shareholder rights, outperformed firms with weaker shareholder rights in

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the 1990s. The governance index does not affect takeover premiums (Column 4 ofTable 6), probably because my sample includes only firms that were taken oversuccessfully.

7.3.4. Poison pills

Given that Comment and Schwert (1995) cover a different time period than mysample, it is instructive to examine if the impact of poison pills has changed. I collectpoison pill data from the IRRC database. Unfortunately, the database covers lessthan half of my sample. Of the target firms covered by IRRC, about 52% havepoison pills in place. However, Column 5 of Table 6 shows that the presence ofpoison pills has no effect on takeover premiums in my sample. The reduced samplesize might be one reason for the insignificance, another might be that the IRRC datahave been updated only every two to three years. Moreover, poison pills can usuallybe deployed on short notice as need arises, reducing the importance of having poisonpills in place.

7.4. Long-run returns

I calculate the excess return from five days before the announcement date tothe earlier of the deal’s effective or the target’s delisting date (target realizedreturn). It eliminates all uncertainty but has long event windows that varysubstantially from deal to deal. The length of the event window, the longestextends for almost two and a half years, introduces large variances and noisethat are unrelated to the merger event. Furthermore, if target shareholderstendered their shares before the delisting date, this measure perhaps is notrepresentative of shareholders’ payoffs.13 I repeat the analyses of Table 3 usingthis measure, and significance levels are reduced.14 The signs of the coefficientsappear unchanged, but all individual target shareholder control proxies areinsignificant. Still, F-tests of the joint significance of my proxy variables reject thatthey equal zero.

7.5. Friendly and hostile deals

I also test the robustness of my results with two subsamples. The first containsonly clearly friendly deals that the SDC database does not classify as hostile and inwhich the Wall Street Journal announcements do not indicate any hostility. Thesecond contains only clearly friendly deals without revisions of the original offersthat closed within 180 days of the announcement. The results using both subsamplesare qualitatively similar to those presented here.

13I thank the referee for pointing this out.14Results are available from the author upon request.

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8. Conclusion

In the 1980s, target shareholder control and takeover premiums were negativelyrelated. I show, however, that this relation is positive in the 1990s. Shareholdercontrol is beneficial in the important market for corporate control.My results suggest that direct shareholder control through outside blockholders

and outside directors is most effective, while large share ownership of the target CEOcan be harmful to target shareholders. Indirect financial incentives, such as executivestock options, do not seem to mitigate the principal-agent problem. Targets that arehighly controlled by shareholders are associated with lower abnormal bidder returns,and CEOs of these targets are less likely to receive executive positions in the mergedfirm. This evidence suggests that powerful entrenched target CEOs reduce takeoverpremiums, possibly in return for bidder-provided incentives. Large equity ownershipappears to be an inappropriate incentive for CEOs, in particular when the firmbecomes a target.The results here and in the related studies have important implications for the

potential rent extraction by managers. Clearly, targets with powerful CEOs receivelower takeover premiums. However, premiums are generally positive and averagemore than 20%, while target CEOs generally lose large amounts of their humancapital in takeovers. Given the current abundance of takeover defenses, allowingsome rent extraction by managers might be beneficial for shareholders when itincreases the probability of receiving profitable takeover offers. The morefundamental question becomes: Why are CEOs allowed to extract large rents whenshareholders on their own, e.g., through blockholders, could presumably extractthose rents for themselves? Additional research is needed to answer this question.

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let's make a deal! how shareholder control impacts merger payoffs

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