1-s2.0-S0148619507000379-main

Journal of Economics and Business 59(2007)358–379

CEO overcon?dence,CEO dominance and

corporate acquisitions

Rayna Brown ?,Neal Sarma

Department of Finance,The University of Melbourne,Victoria 3010,Australia

Abstract

This study investigates the role of CEO overcon?dence (hubris)and CEO dominance in the ?rm’s decision

to undertake an acquisition.We argue that it is important to capture not only the extent of overcon?dence

but also the ability of the CEO to impose his or her views on the ?rm’s decisions.We test this approach

using logistic regression and Australian data.The results suggest that both CEO overcon?dence and CEO

dominance are important in explaining the decision to acquire another ?rm.When compared to existing US

studies,the evidence on CEO overcon?dence is robust across two different ?nancial and corporate governance

systems.Our results also indicate that CEO dominance is at least as signi?cant as CEO overcon?dence in

the decision to undertake an acquisition.

JEL classi?cation:G34;G38

Keywords:Overcon?dence;Dominance;Corporate acquisitions;Independent board

1.Introduction

The mergers and acquisitions literature suggests that there are three main motives for takeovers.

The ?rst motive is the creation of synergies so that the value of a new combined entity exceeds

the sum of its previously separate components.The second motive arises due to agency con?icts

between managers and shareholders.Jensen and Meckling (1976)suggest that managers may

rationally pursue their own objectives at the expense of shareholders’interests.Finally,the third

motive for takeovers is managerial hubris (Roll,1986).Roll’s hubris hypothesis suggests that

managers of acquiring ?rms make valuation errors because they are too optimistic about the

potential synergies in a proposed takeover.As a result,they overbid for target ?rms to the detriment

of their stockholders.

?Corresponding author.Tel.:+61383447661;fax:+61383446914.

E-mail address:rayna@https://www.360docs.net/doc/787461926.html,.au (R.Brown).

doi:10.1016/j.jeconbus.2007.04.002

R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379359 Thus,there are two main theories–rational responses to agency costs and non-rational managerial hubris–that have been suggested to explain why managers make value-destroying acquisitions.Although the hubris hypothesis has considerable intuitive appeal,and has been dis-cussed in the literature for two decades,it has only infrequently been subjected to direct empirical testing.Behavioral assumptions such as investor overcon?dence have become common in the asset pricing literature but the corporate?nance literature has largely neglected behavioral assumptions in models of managerial decision making(Barberis&Thaler,2003).1There has been only a limited amount of theoretical research and very few empirical studies.Moreover,such evidence as does exist concentrates on the United States(Hayward&Hambrick,1997;Malmendier& Tate,2005).The US evidence suggests that overcon?dent managers are more likely than other managers to destroy value.

We argue that it is important to capture not only the extent of CEO overcon?dence but also the effect of CEO dominance,which is the ability of the CEO to impose his or her overcon?dent views on the decisions of the?rm.Therefore,we test two hypotheses:(i)an overcon?dent CEO has a positive effect on the?rm conducting an acquisition and(ii)a dominant CEO has a positive effect on the probability of a?rm conducting an acquisition.We develop a measure of CEO dominance that is based on executive compensation and an empirical test of our approach is conducted using Australian data for the period1994–2003.

Our results suggest that CEO overcon?dence and CEO dominance affect corporate behavior as revealed in acquisition decisions.Overcon?dent CEOs are more likely to make acquisitions–especially diversifying acquisitions–than other CEOs.However,we also?nd that CEO dominance is at least as signi?cant as CEO overcon?dence.Evidence that CEOs may destroy?rm value also poses the question of how to rein in an overcon?dent CEO.Our results indicate that having an independent board of directors assists in achieving this goal.The evidence provided by this study should assist in attempts to mitigate the destructive effects of CEO behavior through stronger corporate governance regulation.

Although the US and Australian?nancial systems have much in common,two signi?cant differences may affect the in?uence of managerial overcon?dence.The?rst concerns corporate governance regulations.Anand(2005)classi?es countries into three groups depending upon their corporate governance compliance https://www.360docs.net/doc/787461926.html,ing this classi?cation,Australia,along with13 other countries including Germany,Italy and the United Kingdom,falls into the group of countries that has voluntary governance guidelines but mandatory disclosure of governance practices.The US is in a group of only two countries that have mandatory governance practices and mandatory disclosure of governance practices.The second important difference relates to the relative reliance on intermediary-based and capital market-based?nancing.Amongst large industrialized countries the US is at one extreme with less than30%of?nancing allocated through intermediaries,while Germany is at the other extreme with75%allocated through intermediaries.Like most developed countries,Australia falls between these extremes(Reserve Bank of Australia,2000).Hence,our results show that the evidence on CEO overcon?dence is robust across two different time periods and two different?nancial and corporate governance systems.

The structure of the paper is as follows:Section2provides a brief overview of the literature on the wealth effects of mergers and acquisitions.In Section3the theoretical background and measurement of our proxies for CEO overcon?dence and CEO dominance are discussed.The

1This pattern has emerged even though objections to behavioral?nance,such as arbitrage and learning,tend to be more persuasive in asset pricing than in corporate?nance(Heaton,2002).

360R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379 methodology is outlined in Section4,while Section5documents our data sources and provides descriptive statistics.Our results are presented in Section6.Some concluding comments are presented in Section7.

2.The wealth effects of mergers and acquisitions

There are two broad streams in the literature on mergers and acquisitions.2The?rst stream investigates the motives for undertaking acquisitions,which are traditionally considered to be either the maximization of shareholders’wealth or managerial hubris.The second stream inves-tigates the wealth effects of acquisitions.If managers act to maximize shareholders’wealth,then an acquisition can be seen as adding value to both target and acquirer through the creation of synergies that are expected to produce economic gains and hence increase wealth.

However,there is a consensus amongst empirical studies that acquisitions are value-enhancing for stockholders in target?rms but on average are at best value-neutral for stockholders in acquiring ?rms.In their survey of US evidence,Andrade,Mitchell,and Stafford(2001)?nd a positive abnormal return of16%to targets that is remarkably consistent over time,and a negative,but insigni?cant abnormal return to acquirers.Walter and da Silva Rosa(2004)survey the Australian evidence and report similar conclusions.In the case of targets,“the evidence is unequivocal... target?rm shareholders bene?t considerably”(p.iv),whereas“the share price performance of acquirers around the bid period is dif?cult to reconcile with the value-increasing hypothesis”(p.vi).

Several explanations have been offered for this disappointing outcome for acquirers.If the market for potential targets is suf?ciently competitive,then the bene?t of a proposed acquisition should be competed away,leading to a mean return of zero for acquirers.A negative return to stockholders in acquiring?rms could be explained by agency costs:that is,the manager(s) of acquiring?rms favor takeovers because their power,wealth and status are increased.Such managerial behavior is rational but not in the interests of the stockholders.Alternatively,a negative return to acquiring stockholders may be explained by hubris or overcon?dence on the part of the CEO of the acquiring?rm.This explanation suggests that the CEO may sincerely believe that a merger is in the best interests of the stockholders but that this belief is not rationally based.

Agency costs and/or managerial hubris may be more likely in the case of diversifying acquisi-tions.Morck,Shleifer,and Vishny(1990)?nd that a signi?cant negative abnormal return accrues to bidding?rms upon the announcement of a diversifying acquisition.Maquiera,Megginson, and Nail(1998)and Bhagat,Dong,Hirshleifer,and Noah(2004)provide further empirical evidence that acquiring?rm stockholders gain less from diversifying acquisitions than from non-diversifying acquisitions.In addition,there is evidence that diversi?ed?rms trade at a dis-count to stand-alone entities in the same line of business(Berger&Ofek,1995;Lang&Stulz, 1994;Servaes,1996).The existence of a diversi?cation discount has often been interpreted as evidence that diversi?cation destroys value.Scharfstein and Stein(2000)suggest that there may be increased agency costs in diversi?ed?rms.3Diversifying acquisitions have,therefore,been linked to the existence of agency costs as diversi?cation may bene?t managers(Morck et al., 1990),and to the existence of managerial overcon?dence(Malmendier&Tate,2005).

2For simplicity,in the remainder of the paper we use the term‘acquisition’to include merger.

3Findings on the diversi?cation discount have recently been the subject of a debate that has been well summarized in Martin and Sayrak(2003).

R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379361 3.CEO overcon?dence and CEO dominance:theory and measurement

3.1.CEO overcon?dence

‘Overcon?dence’is de?ned as an overestimation of one’s own abilities and of outcomes relating to one’s own personal situation(the‘better-than-average’effect)(Langer,1975).4The hypothesis of overcon?dence in?nance is based upon an extensive literature in psychology which?nds that people are generally overcon?dent(Frank,1935;Weinstein,1980).For example,people tend to overestimate their abilities relative to the average when assessing their relative skill(Larwood& Whittaker,1977).Roll(1986)was the?rst study in the corporate?nance literature to investigate the effects of managerial overcon?dence.Gervais,Heaton,and Odean(2003)argue that managers may be more overcon?dent than the general population because of selection bias.That is,people who seek managerial positions are more likely to be those who are overcon?dent about their ability as a future manager.

There are two main objections to the proposition that managers are overcon?dent.The?rst objection is that irrational managers will be“arbitraged”away through takeovers or other mech-anisms.However,corporate takeovers involve extremely high transaction costs and arbitrageurs will need to bear large idiosyncratic risks,thus severely limiting the power of arbitrage(Heaton, 2002).Moreover,if managerial irrationality is a widespread phenomenon,then there is no guar-antee that the replacement manager will be rational(Paredes,2004).Further,a?rm’s internal incentive mechanisms may not eliminate managerial irrationality(Goel&Thakor,2000;Heaton, 2002).The second objection is that irrational managers will learn from experience to become rational.However,the feedback from corporate?nancial decisions is typically infrequent,slow and noisy.Under these circumstances,it is less likely that agents will learn from experience (Brehmer,1980;Heaton,2002).Importantly,both objections are weaker in a corporate?nance setting than in the setting of?nancial markets(Gervais et al.,2003;Heaton,2002).

The empirical evidence on the role of overcon?dence in acquisition decisions is limited.Lys and Vincent(1995)adopt a case study approach to analyze AT&T’s acquisition of NCR.They suggest that the massive value destruction that resulted from that acquisition could be attributed to managerial hubris.Hayward and Hambrick(1997)test Roll’s hubris hypothesis.They argue that the psychological effects of strong recent?rm performance,media praise for the CEO,and high relative CEO compensation will result in hubris.They?nd strong evidence that the hubris of CEOs leads them to overbid for targets.

Malmendier and Tate(2005)study the relationship between managerial overcon?dence and acquisitions.5They assume that there exist only two types of CEOs:rational(non-overcon?dent) CEOs and overcon?dent CEOs.6They argue that the behavior of overcon?dent CEOs differs from the behavior of rational CEOs in two ways.First,overcon?dent CEOs overestimate the potential synergies of a proposed acquisition because they believe that their leadership skills are“better

4The term‘optimism’is sometimes used to describe the‘better-than-average’effect.Following Malmendier and Tate (2005),we use the term‘overcon?dence’to refer to both the‘better-than-average’and‘narrow-con?dence-intervals’effects.‘Optimism’is de?ned as a general overestimation of exogenous outcomes,such as may occur at the outbreak of a war.

5Heaton(2002)had previously analyzed the effect of managerial overcon?dence on corporate investment and manage-rial resistance in takeovers.

6It is also assumed that managers invest in all projects that they believe have a positive net present value and never invest in projects that they believe have a negative net present value.

362R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379

Table1

The?ve factor model

Openness Conscientiousness Extroversion Agreeableness Neuroticism Imagination Competence Friendliness Trust Anxiety

Artistic Interests Orderliness Gregariousness Straightforwardness Hostility Emotionality Dutifulness Assertiveness Altruism Depression Adventurousness Achievement-striving Activity level Compliance Self-consciousness Intellect Self-discipline Excitement seeking Modesty Impulsiveness Liberalism Cautiousness Cheerfulness Tender-mindedness Vulnerability

The?rst row identi?es the?ve factors.The next?ve rows contain the?ve lower-order traits(“sub-factors”)for each factor.Within each factor,traits are highly correlated;across factors,they are not.Source:MIT Laboratory for Financial Engineering(2004).

than average”.They may also overestimate potential synergies because they fail to perceive some of the risks involved in an acquisition due to the“illusion of control”over its outcome. Second,overcon?dent CEOs mistakenly believe that their company’s equity is undervalued by the market.This belief arises because overcon?dent CEOs overestimate the future returns that could be generated under their leadership.

A rational CEO will decide to acquire another?rm if the value of the synergies that will accrue to the acquiring?rm’s stockholders is greater than zero.The rational CEO is also indifferent between?nancing the merger with cash,equity or a combination of cash and equity.In contrast, the acquisition decision of an overcon?dent CEO depends on the means of?nancing,due to the perceived cost of external?nance.An overcon?dent CEO will decide to acquire whenever perceived merger synergies exceed the perceived loss from issuing undervalued equity.Therefore, Malmendier and Tate do not predict an unambiguous relationship between CEO overcon?dence and corporate acquisitiveness.However,in their empirical work,Malmendier and Tate?nd strong evidence of higher average acquisitiveness among overcon?dent CEOs.This?nding is consistent with Roll’s(1986)hubris hypothesis,which unambiguously predicts that overcon?dent CEOs will make more acquisitions than rational CEOs.7

Our proxy for CEO overcon?dence relies on trait theory,which is regularly used by psycholo-gists to measure and explain personality.Traits constitute underlying personality dimensions on which individuals vary.Allport and Odbert(1936)compiled a list of18,000words from Webster’s dictionary that could be described as traits.Over the years,researchers reduced the number of traits in the list using factor analysis.Most trait theorists agree that the original list can be reduced to just?ve traits,known as the Big Five Factors or the Five Factor Model(FFM)(Goldberg,1981, 1993;John,1990;McCrae&Costa,1990,1997).

The FFM has been arrived at by many independent studies using different data sets and has been found to be universal across cultures.This conclusion has prompted some psychologists to claim that they have uncovered general laws of personality structure.The?ve factors are openness, conscientiousness,extroversion,agreeableness and neuroticism.Each of the factors represents several highly correlated sub-factors or traits.Each factor is measured on a continuous,normally distributed scale.The factors and traits are listed in Table1.

Quantifying overcon?dence is problematic as there is no instrument to directly measure a personality trait.Hayward and Hambrick(1997)use three proxies:recent stockholder returns to

7In Roll(1986),the hubris of managers does not result in managers believing that their?rm’s equity is undervalued by the market.

R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379363 measure recent organizational success;content analyses of major newspapers and magazines about CEOs to measure media praise for the CEO;and CEO compensation relative to the second-highest paid of?cer to measure CEO self-importance.Malmendier and Tate(2005)use two measures; the?rst is based on how long a CEO holds company options and the second is a press coverage proxy.

The proxy we use for CEO overcon?dence is based on media coverage.8To classify CEOs as overcon?dent or rational,data were collected on how the leading business press in Australia portrayed each individual CEO during the sample period.For each individual CEO,?ve separate searches were conducted of the Factiva database.9The searches were for speci?c personality traits based on the Five Factor Model of Personality outlined in Table1.For each CEO in the sample, a record was made of the number of articles during the sample period that portray the CEO as(a)“con?dent”(b)“optimistic”and(c)“reliable”,“cautious”,“conservative”,“practical”,“frugal”,“disciplined”,“conscientious”,“not con?dent”or“not optimistic”.Also recorded was the total number of articles which mention the CEO during the sample period.

Like Hayward and Hambrick(1997),we have chosen to construct a continuous variable and,because some CEOs are mentioned in the press more often than others,our measure of overcon?dence(oc)is expressed in relative terms:

oc=(a)+(b)

(c)

(1)

A potential limitation of this measure of overcon?dence is that managers may attempt to project an aura of false con?dence to the press in order to mislead investors and keep their stock price high(Malmendier&Tate,2005).However,Malmendier and Tate suggest that it would seem unlikely that managers would pursue this strategy in the long term because even-tually the manager’s credibility would be questioned.A second potential limitation is that managers may try to“hype”major corporate events such as acquisitions to improve their chances of success.Malmendier and Tate(2005)contend that for managerial hyping to be success-ful,the CEO would need to be mentioned as con?dent or optimistic in the press a relatively large number of times.To control for managerial hyping,we include in the regression a con-trol variable(total),which is the number of articles that mention the CEO during the sample period.

3.2.CEO dominance

Following Haleblian and Finkelstein(1993),we de?ne‘dominance’(or‘power’)as the capacity of an individual to exert their will.CEO dominance may be an important factor in acquisition behavior since the CEO is typically the most powerful member of the corporate elite(Jensen& Zajac,2004).

Dominance differs from overcon?dence.Overcon?dence is an aspect of personality and there-fore is intrinsic to the individual.Dominance is in principle an objective fact of behavior.It is the demonstrated ability of one person to impose their will on others.Hence,dominance has meaning 8Data limitations prevent the use of a proxy based on the length of time a CEO holds company options.

9The Factiva search was conducted via the Westlaw database which has a subscription to Factiva.The publications searched were The Age(Melbourne),Australian Financial Review,Sydney Morning Herald and Business Review Weekly.

A more detailed description of the press search is given in Appendix A.

364R.Brown,N.Sarma /Journal of Economics and Business 59(2007)358–379

only in a social or organizational context.10Dominance may follow from overcon?dence,but not

all overcon?dent CEOs will be dominant.In a corporate context,a decision in which an individual

is very likely to wish to exert dominance is in the determination of their personal compensation.

In their analysis of the relationship between governance structures and acquisition behav-

ior,Jensen and Zajac (2004)include a control variable for CEO power.They argue that this is

necessary to prevent differences in effects across governance positions being confounded by

differences in CEO power.In similar vein,we argue that a variable for CEO dominance is

needed to prevent the effects of different levels of CEO overcon?dence being confounded by

different levels of CEO power.Thus,we argue that both CEO overcon?dence and CEO domi-

nance must be included when testing for the signi?cance of CEO hubris in corporate acquisition

behavior.

The annual compensation of the CEO may be considered an estimate agreed to by the board

of the value of that person’s contribution to the ?rm for the year.Paredes (2004)argues that

large executive compensation packages are paid against the backdrop of a corporate governance

system which is characterized by deference to the CEO.As noted in his summary of the normative

executive compensation debate,Paredes (2004,p.32)observes that according to one stream of

the literature,“huge”CEO pay re?ects a board that is shirking its responsibility by not exercising

due care in overseeing and negotiating executive pay.

Our main proxy for CEO dominance (dom1)is the natural logarithm of the ratio of CEO total

annual remuneration to the ?rm’s total assets:dom1=log CEO remuneration total assets

(2)CEO remuneration is the most signi?cant validation and form of recognition a chief executive

receives,and high compensation is more salient than other possible measures of a CEO’s success

and value to the ?rm (Paredes,2004).CEO remuneration is calculated as base salary +directors

fees +performance bonuses +allowances and non-cash bene?ts.Total assets is a measure of the

size of the ?rm.A high ratio of CEO compensation to total assets indicates that the ?rm expects

a very large contribution from that person compared to the size of the ?rm and/or that the CEO

has considerable in?uence over the decisions of the board.

A possible limitation of this measure is that it is based on the assumption that CEOs who exert

their power in one area (determination of their compensation)will exert their power in another area

(acquisition decisions).While CEOs are usually concerned about their personal compensation,it

is of course possible that a CEO might care little about personal compensation but be enthusiastic

about acquisitions:megalomaniacs do not necessarily want to be rich.Whether this possibility

arises frequently enough to be a problem is an empirical question.

Although dom1is our preferred proxy for CEO dominance,as a robustness test we also proxy

CEO dominance with a non-continuous (ordinal)variable:

dom2=observations of dom1ranked in ascending order (3)

Results using dom2will test whether our main results are driven by outliers or other discontinuities

in the data.

To illustrate,Robinson Crusoe could have been overcon?dent before the arrival of Man Friday but he could not have

been dominant.

R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379365 4.Methodology

We have two main hypotheses:(i)an overcon?dent CEO has a positive effect on the probability of the?rm conducting an acquisition and(ii)a dominant CEO has a positive effect on the prob-ability of the?rm conducting an acquisition.We test these hypotheses using logistic regression and pooled cross-sectional time series data.The main dependent variable is acq,which equals1if the CEO made at least one successful acquisition in a particular?rm-year.In subsequent tests we also employ two other dependent variables:(i)dacq,which equals1if the?rm made at least one successful diversifying(unrelated)acquisition during a particular?rm-year and(ii)racq,which equals1if the?rm made at least one successful related(non-diversifying)acquisition during a particular?rm-year.11

In order to isolate the effects of CEO overcon?dence and CEO dominance,it is necessary to control for the confounding effects of?rm characteristics and other potentially important fac-tors in the decision to acquire.We therefore include the proportion of independent directors as a control(gov)for effective corporate governance,managers’stock and option ownership as a control(owner)for its incentive effect on managers and Tobin’s Q as a control(q)for growth and investment opportunities.A proxy for cash?ow(cf)is included as a control for different levels of internal resources.The variable size(natural logarithm of the book value of assets)is included to control for?rm size.12To control for the possibility of merger waves in particular years we include year dummies.13The logistic identity(random effects)to be estimated is

I=β0+β1oc+β2dom+β3gov+β4owner+β5q+β6cf+β7size+β8total +β9D1994+β10D1995+β11D1996+β12D1997+β13D1998+β14D1999

+β15D2000+β16D2001+β17D2002+ε(4) where I is the acq,dacq or racq,oc the proxy for CEO overcon?dence(Eq.(1)),dom the dom1 or dom2,which are proxies for CEO dominance(Eqs.(2)and(3)),gov the proxy for effective corporate governance,de?ned as the proportion of non-executive directors on the board,owner the control for ownership incentive effects,de?ned as the number of ordinary shares of the company in which the CEO has a bene?cial interest,whether through partly paid shares,fully paid shares, or stock options,divided by the total number of shares outstanding,cf the cash?ow,which is a proxy for corporate resources,and is de?ned as net pro?t after tax before abnormal items plus depreciation,all divided by the book value of assets,size the natural logarithm of the book value of assets,total the total number of articles that mention the CEO during the sample period and D(year)and dummy variables which equal1if an acquisition occurred in the year speci?ed,where year equals1994,1995, (2002)

A series of robustness tests are undertaken.We test the robustness of our control variable for internal resources(cf)by estimating Eq.(4)with two alternative proxies(cf2and cashnorm).These variables are de?ned in Table2.To test for possible industry effects we use dummy variables.

11An acquisition is de?ned as diversifying if the acquiring and target?rms do not share a primary2-digit Standard Industry Classi?cation(SIC)code.The results for racq are not reported as the results are not signi?cant.

12Moeller,Schlingemann,and Stulz(2004)argue that agency problems and hubris may be more prevalent in larger ?rms.

13It is widely accepted that mergers tend to occur in waves.Gorton,Kahl,and Rosen(2005)provide a review of this literature.

366R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379

Table2

Variable de?nitions

Variable name De?nition

Panel A:dependent variable

acq Binary variable equal to1if the?rm made at least one eventually successful acquisition during a particular year

dacq Binary variable equal to1if the?rm made at least one eventually successful diversifying

acquisition during a particular year.An acquisition is de?ned as diversifying if the acquiring and

target?rms do not share a primary2-digit SIC code

racq Binary variable equal to1if the?rm made at least one eventually successful related acquisition

during a particular year.An acquisition is de?ned as related if the acquiring and target?rms share a

primary2-digit SIC code

Panel B:measures of overcon?dence and dominance

oc The ratio of the number of“con?dent”plus“optimistic”mentions divided by the number of

“reliable,”“conservative,”“practical,”“frugal,”“disciplined,”“conscientious,”“not con?dent,”and

“not optimistic”mentions

dom1natural logarithm of CEO compensation(ceo pay)divided by book value of assets

dom2dom2=observations of dom1ranked in ascending order

Panel C:control variables

cashnorm Cash divided by book value of assets

cf Net pro?t after tax before abnormal items plus depreciation,normalized by book value of assets cf2Net pro?t after tax before abnormal items plus depreciation,normalized by capital

q Market value of assets divided by book value of assets

size Natural logarithm of book value of assets

gov The number of non-executive directors on the board divided by the total number of directors on the board

owner The number of ordinary shares of the company in which the CEO has a bene?cial interest,whether through partly paid shares,fully paid shares,or stock options,divided by the total number of shares

outstanding

total Total number of articles that mention the CEO during the sample period

Panel D:press variables

con?dent Number of articles that portray the CEO as“con?dent”

optimistic Number of articles that portray the CEO as“optimistic”

cautious Number of articles that portray the CEO as“reliable,”“cautious,”“conservative,”“practical,”

“frugal,”“disciplined,”“conscientious,”“not con?dent,”“not optimistic”

Panel E:other variables used to construct independent variables

market value of assets Market value of equity plus book value of assets minus book value of equity

market value of equity Fiscal year closing price multiplied by total number of shares outstanding

CEO compensaton Total compensation of the CEO in a particular year calculated as base salary+directors

fees+performance bonuses+allowances and non-cash bene?ts

capital Book value of property,plant and equipment

Panel A contains the variable de?nitions for the three dependent variables used when estimating Eq.(4).Panel B contains the de?nitions of the proxies for CEO overcon?dence and CEO dominance.In Panel C all control variables are de?ned. Panel D contains the de?nitions of the search terms used to construct the proxy for overcon?dence.Panel E contains the de?nitions of subsidiary variables used in the analysis.

We classify all?rms into one of four major industry groups:?nancial services(industry group1), construction and manufacturing(industry group2),transport and retail services(industry group 3)and mining(industry group4).14Finally,an alternate measure of CEO dominance(dom2)is tested.

14Originally,the industry classi?cations were based on the seven SIC categories.These results were not signi?cant.We then combined categories to reduce the number of industry groups to4and reran all regressions.The results remained insigni?cant but are reported in Tables6and8.The reference industry for the dummy variables is?nancial services.

R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379367 The sample period is1January1994to31December2003.The regression is estimated on unbalanced panel data for65?rms.The initial sample consisted of all?rms that were included in the S&P/ASX50Index at the start of the sample period.Firms which did not have annual report data in the Connect4database for at least2years were removed.Firms that were subsequently included in the S&P/ASX50Index during the sample period were added to the sample in the year that they were included in the index.Firms that were excluded at any time from the S&P/ASX 50Index were not removed from the sample unless they were delisted.If a?rm was delisted it was removed from the sample in the year in which it was delisted.For each?rm in the sample, acquisitions data were collected on an annual basis using Thomson Financial Securities Data Corporation(SDC)database.

5.Data sources and descriptive statistics

5.1.Data sources

The following data were collected from annual reports accessed through the Connect4 database.

The name of the CEO.The CEO for each?rm during each year of the sample period was identi?ed.If a?rm temporarily did not have a CEO at the time of publishing its annual report, the previous year’s CEO was assumed to still be the CEO.15

Remuneration data.Data were collected on the total compensation of each CEO for each year of the sample period.Contractual termination payouts were excluded from the measure of total com-pensation.If it was unclear whether there had been a termination payout,or if there was uncertainty about the amount of a payout,no data were recorded for that observation.Before1998,CEO and executive of?cer compensation were reported in bands of$10,000,beginning at$100,000for most ?rms.Following De?na,Harris,and Ramsay(1994),the mid-point of the relevant compensation band was recorded and it was assumed that the highest paid company director was the CEO.

Share ownership.Annual data relating to each CEO’s bene?cial interest in the?rm’s ordinary share capital were collected from the annual reports.

Board structure.The proportion of independent directors on each?rm’s board of directors was recorded.An independent director is de?ned as a non-executive director(i.e.not a current employee of the?rm).

Other data were obtained from a variety of sources,as follows.

Market data.Market data were obtained from IRESS.

Press coverage variables.A CEO is classi?ed as overcon?dent depending upon his/her press coverage throughout the sample period and hence his/her classi?cation does not change.However, if a?rm changes its CEO,then its classi?cation may change from one managed by an overcon?dent CEO to one not managed by an overcon?dent CEO or vice versa.

All?nancial variables are constructed from annual observations for each?rm and each CEO during the sample period.Detailed de?nitions of all variables are provided in Table2.

5.2.Descriptive statistics

Table3presents the correlation matrix of all variables.

15If remuneration and ownership data regarding that CEO were unavailable in the annual report for that year,then that observation was dropped.

368R.Brown,N.Sarma /Journal of Economics and Business 59(2007)

358–379

Table 3

Correlation coef?cients

acq dacq racq oc dom1gov owner q size total cf cf2

dacq 0.75941

racq 0.60970.04631

oc 0.10170.04910.06391

dom1?0.0422?0.0899?0.00100.24301

gov ?0.0669?0.0635?0.02780.0792?0.23371

owner 0.13350.14430.08100.05410.1555?0.38621

q 0.0012?0.06790.04750.06040.5512?0.20960.21761

size 0.17370.24250.0410?0.1607?0.86470.3011?0.0370?0.52121

total 0.17930.24160.1217?0.1411?0.33660.02220.3670?0.09230.54471

cf ?0.1732?0.2193?0.04680.05890.5797?0.0460?0.03940.5742?0.5474?0.17761

cf20.14250.2459?0.09270.0306?0.1836?0.00250.0320?0.08490.20350.0364?0.23101

cashnorm 0.12230.09320.08050.00470.2116?0.07990.05610.1562?0.1822?0.03320.1473?0.0230All variables are de?ned in Table 2.

R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379369

Table4

Descriptive statistics

Panel A:dependent variables and main independent variables

Dependent variables Main independent variables

acq dacq oc dom1

Mean0.27450.1791 2.7927?3.6530

Median002?3.5353 Maximum1118?1.9009 Minimum000?5.2363 Standard deviation0.44670.3839 2.78220.5815

Panel B:?rm variables

gov owner q cf cf2cashnorm size Mean0.76040.01700.95550.07710.53020.041122.6587 Median0.80000.00140.79600.07580.16800.027322.4463 Maximum0.92860.44878.44010.446511.09300.397726.6565 Minimum0.12500.00000.0308?0.0187?3.11310.000119.1028 Standard deviation0.14130.06190.88050.0520 1.09190.0502 1.4812

Panel C:summary statistics of press data

Cautious Optimistic Con?dent Total Mean 5.80 2.498.45508.84 Median316278 Maximum5120383978 Minimum0003 Standard deviation0.370.140.3627.52

Panel D:summary statistics of acquisitions data

Number of acquisitions312 Number of diversifying acquisitions78 Mean deal value(US$m)380 Median deal value(US$m)132 Standard deviation105 Stock offers(%)13

All variables are de?ned in Table2.Financial variables are reported in AUD in Panels A and B and USD in Panel D.

The measure of CEO overcon?dence(oc)has a correlation with the measure for CEO domi-nance(dom1)of only0.2430.This?nding indicates that the proxy for CEO dominance captures different attributes to the proxy for CEO overcon?dence and therefore is not merely an alter-native proxy for CEO overcon?dence.The data in Table3also suggest that larger?rms have a higher proportion of independent directors,while CEOs with higher levels of stock ownership are associated with a less independent board of directors.

Descriptive statistics of the data used to construct all variables are presented in Table4.

Panel A of Table4provides descriptive statistics for the main dependent and independent variables.In Panel B an overview of the press data is presented.The mean number of articles which mention the CEO is509and the median304,which indicates that we have an adequate number of articles from which to make a classi?cation regarding overcon?dence for the vast majority of CEOs.Summary statistics of the acquisitions data are presented in Panel C.

370R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379

6.Results

For each regression,parameter estimates,p-values and the exponential ofβare reported.In Section6.1results for all acquisitions are discussed and in Section6.2results for diversifying acquisitions are discussed.

6.1.All acquisitions

The results presented in Table5are based on the total sample of acquisitions.They provide direct empirical evidence on the extent and importance of CEO overcon?dence and CEO dom-inance in?rm acquisition behavior.The results of robustness tests using industry dummies and an alternative proxy for CEO dominance(dom2)are presented in Table6.

Our central results are shown in Table5under speci?cation1,which includes both the over-con?dence proxy(oc)and the dominance proxy(dom1).The likelihood ratio statistic is highly signi?cant(1%level),while the overcon?dence proxy(oc)is signi?cant at the5%level and the dominance proxy(dom1)is signi?cant at the1%level.In the robustness test reported in Table6 (Panel A)industry dummies are included.The rationale for this test is that some industries might attract overcon?dent and/or dominant CEOs more often than others,in which case it could be argued that our proxies for overcon?dence and dominance are merely picking up an industry effect.In speci?cation1A the signi?cance of the overcon?dence proxy(oc)decreases to10%and the signi?cance of the dominance proxy(dom1)remains at1%.None of the industry dummies is signi?cant.In the other robustness test reported in Table6the alternative proxy for CEO domi-nance(dom2)is used.The signi?cance of the overcon?dence proxy(oc)is5%and the signi?cance of the dominance proxy(dom2)is also5%.

The importance of including proxies for both CEO overcon?dence and CEO dominance is demonstrated by examining the results for speci?cations2A and3A in Table5.In speci?cation 2A,CEO dominance(dom1)is excluded and CEO overcon?dence(oc)is found to be signi?cant at the1%level.In speci?cation3A,CEO overcon?dence(oc)is excluded and CEO dominance (dom1)is found to be signi?cant at the1%level.The addition of industry dummies(speci?cations 2A and3A in Table6)reduces the signi?cance of CEO overcon?dence to5%but the signi?cance of dominance remains at1%.Again,none of the industry dummies is signi?cant.

The relative importance of CEO overcon?dence and CEO dominance in acquisition behavior is best demonstrated through the effect that a change in each variable has on the odds and probability of an acquisition.Considering speci?cation1,for overcon?dence(oc),the effect is to increase the odds by a factor of1.09.A1-unit change in dominance(dom1)increases the odds by a factor of4.5.The probability of a?rm undertaking an acquisition is calculated at23.23%.16If a?rm acquires an overcon?dent CEO,the effect is to increase the probability of it making an acquisition by1.6percentage points(from23.23%to24.83%).For a10%increase in the variable to proxy CEO dominance(dom1),the probability of a?rm making an acquisition increases by more than 2.5percentage points from23.23%to25.89%.17

When the in?uence of CEO overcon?dence is considered without a proxy for CEO dominance (speci?cation2)the acquisition of an overcon?dent manager increases the odds by a factor of 16All probabilities are calculated at the means of the variables as reported in Table4.

17The10%increase was calculated as a10%increase in the ratio of CEO compensation to total assets and then converted to the natural logarithm.

R.Brown,N.Sarma /Journal of Economics and Business 59(2007)358–379

371

Table 5

CEO overcon?dence and acquisitiveness

Variable Speci?cation 1Exp(β)Speci?cation 2Exp(β)Speci?cation 3Exp(β)constant ?11.0528(0.0091)***0.0000?3.5609(0.2571)0.0284?11.7795(0.0004)***0.0000oc 0.0878(0.0402)** 1.09180.1150(0.0059)*** 1.1218––

dom1 1.5067(0.0057)*** 4.5116–– 1.7623(0.0005)*** 5.8258gov ?2.1033(0.0446)**0.1221?1.9418(0.0522)*0.1435?1.8219(0.0745)*0.1617owner ?1.0397(0.6404)0.3536?0.2172(0.9188)0.8048?0.2896(0.8870)0.7485q 0.3602(0.0489)** 1.43360.3714(0.0357)** 1.44980.3359(0.0608)* 1.3991cf ?11.0652(0.0031)***0.0000?10.1510(0.0060)***0.0000?10.9748(0.0024)***0.0000size 0.7567(0.0026)*** 2.13120.1797(0.1895) 1.19680.8315(0.0000)*** 2.2968total 0.0001(0.5791) 1.00010.0004(0.1093) 1.0004––LR statistic 73.9857(0.0000)***65.8078(0.0000)***69.8392(0.0000)***

Observations with acq =1312312312

Observations with acq =0118118118

Results for the estimation of Eq.(4)using logistic regression (random effects).The dependent variable is binary where 1indicates that the ?rm completed an acquisition in a particular ?rm-year.All variables are de?ned in Table 2.The results for year dummies are not reported because nearly all coef?cients are insigni?cant.Sample size is 430.*Signi?cant at 10%;**Signi?cant at 5%;***Signi?cant at 1%;p -values in parentheses.acq =β0+β1oc +β2dom +β3gov +β4owner +β5q +β6cf +β7size +β8total +β9D 1994+β10D 1995+β11D 1996+β12D 1997+β13D 1998+β14D 1999+β15D 2000+β16D 2001+β17D 2002+ε.

372R.Brown,N.Sarma /Journal of Economics and Business 59(2007)358–379

Table 6

Robustness tests:industry effects and CEO dominance in acquisitions

Variable Panel A:robustness test using industry dummies Panel B:robustness test using alternative proxy (dom2)

Speci?cation 1A Exp (β)Speci?cation 2A Exp (β)Speci?cation 3A Exp (β)Speci?cation 1B Exp (β)Speci?cation 3B Exp (β)

constant ?11.4997(0.0113)**0.0000?4.4557(0.2116)0.0116?12.4716(0.0002)***0.0000?11.5207(0.0116)**0.0000?13.7225(0.0004)***0.0000oc 0.0796(0.0728)* 1.08280.1043(0.0165)** 1.11000.0940(0.0268)** 1.0986––dom1 1.4780(0.0070)*** 4.3842–– 1.6923(0.0011)*** 5.4322––––dom2––––––0.0045(0.0146)** 1.00450.0055(0.0021)*** 1.0055gov ?2.2130(0.0373)**0.1094?2.1186(0.0379)**0.1202?2.0317(0.0516)*0.1311?2.2988(0.0251)**0.1004?2.0484(0.0392)**0.1289owner ?0.9003(0.6953)0.40650.0151(0.9945) 1.0152?0.1825(0.9293)0.8332?0.9922(0.6508)0.37080.3520(0.8577) 1.4219q 0.3664(0.0471)** 1.44250.3837(0.0316)** 1.46770.3475(0.0542)* 1.41550.3819(0.0308)** 1.46510.3630(0.0376)** 1.4376cf ?10.7944(0.0110)**0.0000?10.2520(0.0143)**0.0000?10.4135(0.0122)**0.0000?11.0271(0.0033)***0.0000?10.4494(0.0038)***0.0000size 0.7732(0.0030)*** 2.16670.2214(0.1549) 1.24780.8530(0.0000)*** 2.34660.4994(0.0088)*** 1.64770.5911(0.0002)*** 1.8060total 0.0001(0.6452) 1.00010.0004(0.1946) 1.0004–0.0003(0.2686) 1.0003––LR statistic 74.4995(0.0000)***66.7549(0.0000)***75.2115(0.0000)***71.9797(0.0000)***65.4568(0.0000)***Observations with acq =1

312312312312312

Observations with acq =0

118118118118118

Panel A provides the results when industry dummies are included in Eq.(4).Panel B provides the results when the alternative proxy for CEO dominance (dom2)is included Eq.(4)in place of dom1.In both panels,the dependent variable is binary where 1indicates that the ?rm completed an acquisition in a particular ?rm-year.All independent variables are de?ned in Table 2.All estimations are made using logistic regression (random effects).The results for year dummies are not reported because nearly all coef?cients are insigni?cant.Sample size is 430.*Signi?cant at 10%;**Signi?cant at 5%;***Signi?cant at 1%;p -values in parentheses.acq =β0+β1oc +β2dom +β3gov +β4owner +β5q +β6cf +β7size +β8total +β9D 1994+β10D 1995+β11D 1996+β12D 1997+β13D 1998+β14D 1999+β15D 2000+β16D 2001+β17D 2002+β17Dind 2+β18Dind 3+β19Dind 4+ε.

R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379373 1.12.However,when CEO dominance is considered without a proxy for CEO overcon?dence (speci?cation3)a1-unit change increases the odds by a factor of5.8.Thus,for a10%increase in the variable(dom1)the probability of an acquisition increases by3.2percentage points from 23.5%to26.7%.

Several of the control variables in speci?cation1A are also signi?https://www.360docs.net/doc/787461926.html,rger?rms and?rms with higher values of Tobin’s Q are more likely to make acquisitions.This result is expected as larger?rms should be less?nancially constrained and should have a greater capacity than smaller?rms to make an acquisition.Cash?ow is found to have a signi?cantly negative effect on acquisitiveness.18This result is unexpected as cash?ow should be an indicator of internal resources.However,further robustness tests show that this result is sensitive to the de?nition of cash?ow.19If cash?ow is normalized by capital instead of assets,the effect becomes marginally positive but is not signi?https://www.360docs.net/doc/787461926.html,ing cash balances instead of cash?ow as an indicator of internal resources results in a highly signi?cant positive effect on acquisitiveness.Overcon?dence and dominance remain highly signi?cant under both speci?cations.

The CEO’s stock and option ownership levels(owner)are not found to have a signi?cant effect on acquisitiveness.This?nding may indicate the ineffectiveness of stock and option holdings as an incentive mechanism,but this interpretation is subject to two caveats.First,we are unable to differentiate between value-creating and value-destroying acquisitions.Second,as discussed by Sanders(2001),the risk-return characteristics of stock ownership and stock option ownership are fundamentally different.Sanders acknowledges that a common theme in the literature is to view CEO stock option ownership as a substitute for CEO stock ownership.However,Sanders argues that the different risk-return characteristics may have different effects on acquisition activity and his results indicate a negative(positive)association between CEO stock(stock option)ownership and?rm acquisition activity respectively.

An important?nding is that effective corporate governance,as measured by a higher proportion of independent directors on the board(gov),signi?cantly mitigates acquisitiveness.Previous research(Heaton,2002),has suggested that an independent board of directors may be an effective way to mitigate CEO overcon?dence.The?ndings provide empirical support for that proposition.

In order to assess whether an interaction effect exists between overcon?dence(oc)and dom-inance(dom1)Eq.(4)was also estimated with an additional multiplicative variable.The results were insigni?cant.20

6.2.Diversifying acquisitions

As discussed in Section2,the theoretical expectation is that agency costs and/or managerial hubris are likely to be more important in the case of diversifying takeovers.Our empirical analysis con?rms this expectation.The main results for diversifying acquisitions are presented in Table7 and the robustness tests in Table8.Following the format used in the previous subsection,results are presented for three speci?cations in Table7and for speci?cations1and3in Table8.Eq.

(4)is estimated with the dependent variable(dacq)taking the value1if the CEO completed a diversifying acquisition in a particular?rm-year.

The likelihood ratio statistics reported in Table7are highly signi?cant for all three speci?-cations.In speci?cation l,the proxy for overcon?dence(oc)is no longer signi?cant(p=0.15), 18As the coef?cient of cash?ow(cf)is very large,its signi?cance may be biased upwards.

19Detailed results of these robustness tests are available upon request from the authors.

20These results are available from the authors upon request.

374R.Brown,N.Sarma /Journal of Economics and Business 59(2007)358–379

Table 7

Diversifying acquisitions

Variable Speci?cation 1Exp (β)Speci?cation 2Exp (β)Speci?cation 3Exp (β)constant ?19.5014(0.0006)***0.0000?5.3914(0.1453)0.0046?18.9121(0.0000)***0.0000oc 0.0748(0.1423) 1.07770.1113(0.0199)** 1.1177––

dom1 2.5935(0.0003)***13.3759–– 2.7020(0.0000)***14.9096gov ?2.2681(0.0941)*0.1035?2.4879(0.0407)**0.0831?2.0643(0.1183)0.1269owner ?1.0922(0.6661)0.3355?0.1209(0.9598)0.8861?0.6506(0.7787)0.5217q 0.2969(0.1526) 1.34570.3382(0.1141) 1.40240.2780(0.1812) 1.3205cf ?13.8624(0.0032)***0.0000?12.8999(0.0062)***0.0000?13.9400(0.0023)0.0000size 1.2895(0.0001)*** 3.63110.2650(0.1032) 1.3034 1.2845(0.0000)*** 3.6130total 0.0000(0.8784) 1.00000.0005(0.0676)* 1.0005––LR statistic 84.0839(0.0000)–68.8144(0.0000)–82.0954(0.0000)–Observations with dacq =0353–353–353–Observations with dacq =177–77–77–

This table presents results for the estimation of Eq.(4)using logistic regression (random effects).The dependent variable is binary where 1indicates that the ?rm completed a diversifying acquisition in a particular ?rm-year.Acquisitions are classi?ed as diversifying if the acquirer and target did not share a primary 2-digit SIC code.All variables are de?ned in Table 2.The results for year dummies are not reported because nearly all coef?cients are insigni?cant.Sample size is 430.*Signi?cant at 10%;**Signi?-cant at 5%;***Signi?cant at 1%;p -values in parentheses.dacq =β0+β1oc +β2dom2+β3gov +β4owner +β5q +β6cf +β7size +β8total +β9D 1994+β10D 1995+β11D 1996+β12D 1997+β13D 1998+β14D 1999+β15D 2000+β16D 2001+β17D 2002+ε.

R.Brown,N.Sarma /Journal of Economics and Business 59(2007)358–379

375

Table 8

Robustness tests:industry effects and CEO dominance in diversifying acquisitions

Variable Panel A:robustness test using industry dummies Panel B:robustness test using alternative proxy (dom2)

Speci?cation 1A Exp (β)Speci?cation 2A Exp (β)Speci?cation 3A Exp (β)Speci?cation 1B Exp (β)Speci?cation 3B Exp (β)

constant ?22.1754(0.0006)***0.0000?7.2639(0.1054)0.0007?21.3623(0.0000)***0.0000?17.8486(0.0016)***0.0000?20.4544(0.0000)***0.0000oc 0.0435(0.4189) 1.04450.0789(0.1164) 1.0821––0.0814(0.0960)* 1.0848––dom1 2.6948(0.0003)***14.8028–– 2.7346(0.0001)***15.4041––––dom2––––––0.0070(0.0024)*** 1.00700.0079(0.0004)*** 1.0080gov ?2.6969(0.0622)*0.0674?2.8543(0.0277)**0.0576?2.5675(0.0685)*0.0767?2.8706(0.0238)**0.0567?2.7880(0.0222)**0.0615owner ?1.3830(0.6047)0.2508?0.1077(0.9651)0.8979?1.2877(0.5873)0.2759?1.1704(0.6366)0.31020.3762(0.8616) 1.4567q 0.2340(0.2713) 1.26360.2867(0.1960) 1.33200.2233(0.2921) 1.25020.3388(0.1256) 1.40330.3025(0.1819) 1.3532cf ?7.5341(0.1633)0.0005?8.8505(0.1092)0.0001?7.3336(0.1653)0.0007?13.9246(0.0041)***0.0000?12.8321(0.0056)***0.0000size 1.4340(0.0001)*** 4.19560.3559(0.0775)* 1.4275 1.4066(0.0000)*** 4.08210.7583(0.0012)*** 2.13460.8720(0.0000)*** 2.3917total 0.0000(0.9445) 1.00000.0004(0.2141) 1.0004––0.0003(0.2400) 1.0003––Dind20.0134(0.9787)11.01340.2455(0.6063) 1.27830.0159(0.9728) 1.0161––––Dind3?0.1752(0.7530)0.8393?0.0252(0.9615)0.9751?0.2641(0.5674)0.7679––––Dind4?19.5832(0.9969)0.0000?19.2940(0.9970)0.0000?19.6710(0.9969)0.0000––––LR statistic 99.8923(0.0000)***83.7040(0.0000)***99.2481(0.0000)***78.7356(0.0000)***75.2442(0.0000)***Observations with acq =1

353353353353353

Observations with acq =0

7777777777

Panel A provides the results when industry dummies are included in Eq.(4).Panel B provides the results when the alternative proxy for CEO dominance (dom2)is included Eq.(4)in place of dom1.In both panels,the dependent variable is binary where 1indicates that the ?rm completed a diversifying acquisition in a particular ?rm-year.All independent variables are de?ned in Table 2.All estimations are made using logistic regression (random effects).The results for year dummies are not reported because nearly all coef?cients are insigni?cant.Sample size is 430.*Signi?cant at 10%;**Signi?cant at 5%;***Signi?cant at 1%;p -values in parentheses.dacq =β0+β1oc +β2dom +β3gov +β4q +β5cf +β6owner +β7size +β8total +β9D 1994+β10D 1995+β11D 1996+β12D 1997+β13D 1998+β14D 1999+β15D 2000+β16D 2001+β17D 2002+β17Dind 2+β18Dind 3+β19Dind 4+ε.

376R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379

whereas the proxy for dominance(dom1)is signi?cant at the1%level.In speci?cation2,the proxy for CEO overcon?dence(oc)is signi?cant at the5%level.In speci?cation3,the proxy for CEO dominance(dom1)is signi?cant at the1%level.

In Table7,speci?cation1,a1-unit change in CEO dominance(dom1)increases the odds by a factor of13.4,a much larger factor than that estimated for CEO overcon?dence(1.08). From the coef?cients reported in speci?cation1,the probability of a?rm undertaking a diver-sifying acquisition is11.5%.If a?rm acquires an overcon?dent CEO the effect is to increase the probability of a diversifying acquisition by0.8of a percentage point(from11.5%to 12.3%).For a10%increase in the variable to proxy CEO dominance(dom1),the proba-bility increases by2.8percentage points from11.5%to14.3%.However,the in?uence of CEO dominance in a diversifying acquisition is most clearly demonstrated in speci?cation 3.For a10%increase in the variable to proxy CEO dominance(dom1),the probability of a?rm completing a diversifying acquisition increases by7.8percentage points(from12.9% to20.7%).21

Our results support the proposition that the dominance variable captures the ability of the CEO to impose his/her views on?rm decisions.The less justi?able the acquisition(as is arguably the case for diversifying relative to related acquisitions),the more important is dominance rel-ative to overcon?dence.The results suggest that studies attempting to measure the effects of CEO overcon?dence should control for CEO dominance,especially in the case of diversifying acquisitions.

7.Implications and conclusion

This study investigates the roles of CEO overcon?dence and CEO dominance in the decision to undertake an acquisition in the Australian market place.We argue that it is important to cap-ture not only the extent of overcon?dence but also the likelihood that the CEO will be able to impose his or her overcon?dent views on the?rm’s decisions.The results suggest that both CEO overcon?dence and CEO dominance are important in explaining the decision to acquire another ?rm.CEO dominance is particularly important in the case of diversifying acquisitions,with the probability of a diversifying acquisition almost doubling with a10%increase in CEO dominance. When compared to existing US studies,the evidence on CEO overcon?dence is robust across two different countries,two different time periods and two different?nancial and corporate gov-ernance systems.Our results also indicate that CEO dominance is at least as signi?cant as CEO overcon?dence in the explanation of the acquisition decision.

A higher proportion of independent directors on the board mitigates the effect of CEO over-con?dence and CEO dominance and reduces the probability of the?rm deciding to make an acquisition.If the effect of CEO overcon?dence in making potentially value-destroying acqui-sitions is a concern to stockholders and corporate regulators,then the?ndings suggest that a possible solution may be to ensure that there is an independent board of directors.

Quantifying CEO overcon?dence and dominance are dif?cult tasks and hence all our conclu-sions are contingent upon the ability of our proxies to capture these characteristics.Nevertheless, we suggest that future researchers may?nd it bene?cial to supplement measures of CEO over-con?dence with measures of CEO dominance.

21As a robustness test an estimation of Eq.(4)was also conducted for related acquisitions.The results were not signi?cant and are not reported.Acquisitions are classi?ed as related if the acquirer and target share a primary2-digit SIC code.

R.Brown,N.Sarma/Journal of Economics and Business59(2007)358–379377 Acknowledgments

We thank Rob Brown,Bonnie Buchanan,Edward Lee,David Reeb,Kim Sawyer,Ian Sharpe and an anonymous referee for helpful comments on earlier drafts.We are also indebted to seminar participants at the Annual AIBF Banking and Finance Conference(2005,Melbourne),Bangor Business School at the University of Wales,the University of Manchester and the2006annual meeting of the Financial Management Association(Salt Lake City).For technical assistance we are grateful to Philip G.Brown and Kim Sawyer.All remaining errors are ours.Rayna Brown also wishes to thank the Manchester Accounting and Finance Group,the University of Manchester, for support during a sabbatical leave.

Appendix A.Description of press search

To classify CEOs as overcon?dent,data was collected on how the leading business press in Australia portrays each individual CEO during the sample period.The publications searched were The Age,Australian Financial Review,Sydney Morning Herald,and Business Review Weekly.

For each individual CEO?ve separate searches were conducted in the Factiva database.The search was conducted via the Westlaw database which has a subscription to Factiva.Factiva on Westlaw is fully searchable using Westlaw search commands.The total number of articles that referred to the CEO during the sample period was found using the following search command:“CEO’s Full Name”&“Company’s Name”&DA(AFT01/01/1994&BEF31/12/2003) This gave the total number of articles that had both the CEO’s name and the name of the CEO’s company in the same article,while restricting the search to articles published during the sample period.For each CEO,the search initially used the full name of the CEO that was reported in the annual report.However,the results of each search were then checked to ensure that the CEO in question was not commonly being referred to by another name.For example, Foster’s CEO Edward Kunkel is invariably mentioned as Ted Kunkel.Similarly,Gerald Harvey of Harvey Norman,is often referred to as Gerry Harvey.For these CEOs,the number of articles that mentioned the CEO’s nick-name far exceeded the number of articles that mentioned the CEO’s actual name.Therefore,for these CEOs,the number of total articles mentioning the CEO was found by searching for their commonly used full name.

The number of articles that referred to the CEO as being“con?dent”was found using the following search command:

“CEO surname”/s“con?dent”&“CEO’s Full Name”&“company name”&DA(AFT 01/01/1994&BEF31/12/2003)%“not con?dent”

This gave the number of articles which had the CEO’s surname in the same sentence as the word“con?dent”in any article which contained both the full name of the CEO and the name of the CEO’s company.Articles in which the CEO was described as“not con?dent”were?ltered out of the results of this search.Similar searches were conducted for each of the personality traits used to construct the variable(oc);“optimistic”,“reliable”,“cautious”,“conservative”,“practical”,“frugal”,“disciplined”and“conscientious”.A review of over one hundred articles suggested that the results obtained were highly accurate.

References

Allport,G.W.,&Odbert,H.S.(1936).Trait names:A psycho-lexical study.Psychological Monographs,47,211.