Is Broad Size an In Dependance Corporate Governace Machnisim

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Is Board Size an Independent CorporateGovernance Mechanism?

Stefan Beiner, Wolfgang Drobetz, Frank Schmid and Heinz Zimmermann*

I. INTRODUCTION

The board of directors plays a pivotal role in the governance of widely held corporations. It is generally acknowledged that the legal and contractual setting aswell as the structure and activities of the board of directors have a non-negligibleimpact on the agency costs to which rms are exposed. At least in theory, the board of directors is one of the most important corporate governance mecha-nisms ensuring that managers pursue the interests of shareholders. Its task is tomonitor, discipline, and remove ineffective management teams. One may suspect that several aspects and mechanisms are important in increasing the effec-tiveness of boards, such as board composition, board independence, and boardsize. While there is ample empirical evidence on board composition and boardindependence, there is only little international empirical evidence on the rela-tionship between board size and rm valuation. Most importantly, previous papers do not take into account that there are possibly complex interrelationships between different corporate governance mechanisms, i.e., they neglect that board size is only one mechanism out of a wide menu of choices a rm faces.

Yermack (1996) was the rst to report a negative relationship between board size and rm valuation. In general, an important issue in all empirical

* Sad Business School, University of Oxford, Park End Street, Oxford OX1 1HP, England, andDepartment of Finance, University of Basel, Holbeinstrasse 12, 4051 Basel, Switzerland, email:[email protected]; Department of Corporate Finance, University of Basel, Peters-graben 51, 4003 Basel, Switzerland, email: [email protected]; Department of Economics, University of Bern, Vereinsweg 23, 3012 Bern, Switzerland, email: [email protected]; Department of Finance, University of Basel, Holbeinstrasse 12, 4051 Basel, Swit-zerland, email: [email protected]. We thank two anonymous referees, Yakov Amihud, Wolf-gang Bessler, Stefan Duffner, Reiner Eichenberger, David Rey, and Markus Schmid for valuablecomments. Financial support from the National Center of Competence in Research FinancialValuation and Risk Management (NCCR FINRISK) is gratefully acknowledged. The NCCR FINRISK is a research program supported by the Swiss National Science Foundation. Beiner ac-knowledges nancial support from the Swiss National Science Foundation (SNF).


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work is the question whether board size is endogenous. Firm performance is both a result of the actions of previous directors and itself a factor that inu-

ences the choice of subsequent directors. While previous studies with mainlyUS evidence have been careful to control for endogeneity, they did not accountfor any interrelationships between different, and possibly alternative, corpo-rate governance mechanisms. Specically, these studies only looked at simul-taneous equations with board size and rm valuation as the dependent variables, thereby ignoring the possibility that different governance mechanisms aresubstitutes, at least to some extent. The underlying notion of the latter pre-sumption is that where one mechanism is used less, others could be used more,resulting in the same valuation effects. Accordingly, the relationship between board size and rm valuation could be driven by some other (so far unidenti-ed) governance mechanism correlated with both board size and rm valua-tion. Therefore, in this paper we explicitly model the interrelationships be-tween board size, board composition, leverage, and ownership structure inorder to reexamine the issue of causality between board size and rm valuationin a more realistic setting. For example, the number of board outsiders may be positively related with board size. Therefore, it may be the case that any board size effect actually relates to the composition of the board, and possiblyalso to other governance mechanisms. To explore these interrelationships isan important extension to the previous literature and specically addresses

the question whether board size is really an independent governance mecha-nism.Our second line of argument relates to previous work by Jensen (1993) and

Lipton and Lorsch (1992), who were the rst to express the notion of an opti-mum board size of around 7 or 8 directors. Intuitively, they suggest that smaller boards lack the necessary management capacity. In contrast, large boards can be less effective than small boards, presuming that the emphasis on politenessand courtesy in boardrooms is at the expense of truth and frankness. Speci-cally, when boards become too big, agency problems (e.g., director free-riding)increase and the board becomes more symbolic and neglects its monitoring andcontrol duties. Moreover, large boards may reect an inadequate perception of the true executive function, particularly in rms with public involvement. Un-fortunately, the ad-hoc claim of the existence of an optimal board size is incon-sistent with previous empirical evidence. For example, Yermacks (1996) USsample includes rms with very large boards (with a mean of 12.3 board members), and the Finnish sample in Eisenberg, Sundgren and Wells (1998) is dom-inated by small- and medium-sized companies (with a mean of 3.7 board members). Interestingly,both papers nd a negative relationship between board sizeand rm valuation, which is clearly inconsistent with a unique optimal board


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size. The specic characteristics of our sample, consisting of publicly listedSwiss rms, allow us to shed more light on these contradictory results.

As in the United States, in Switzerland the board of directors(Verwaltungs-rat) shares top executive responsibility. Note that this contrasts with, e.g., theGerman system, where the Aufsichtsrat has a purely supervisory function. In-terestingly, average board size in our sample is 6.6, which is just about the sizesuggested to be optimal by Jensen (1993) and Lipton and Lorsch (1992). Thisallows us to further explore the hypothesis of the existence of an optimal boardsize. Intuitively, in the optimum, the size of the board would be increased up tothe point where marginal benet just equals marginal cost. In this case, as wewill further discuss below, a carefully specied cross-sectional regressionshould nd no relationship between rm valuation and board size. This also ap- plies to other governance mechanisms, such as outside representation, debt,and ownership structure.

It is also important to note that the mere fact that the average board size inour sample is similar in magnitude to what Jensen (1993) and Lipton andLorsch (1992) suggested, does not necessarily drive our results. Even thoughthe average board size in our sample is close to optimal, this may only be acoincidence, and any seemingly validating results are driven by some other governance mechanism, which itself is related to rm valuation. This againdemonstrates the importance of estimating a simultaneous system of equations

with a wide range of governance mechanisms.To test our argument, we proceed in two steps. In a rst step, we examinewhether board size is an independent governance mechanism. If this is not thecase, all previous papers lack from an important shortcoming, i.e., they look at board size as the only governance mechanism and neglect important interrela-tionships. Estimating a simultaneous system of equations, we nd that boardsize is indeed an independent governance mechanism out of several from whicha rm can deliberately choose. This implies that any relationship between board size and rm valuation could in fact be interpreted as causal. In a secondstep, we additionally include a measure of rm valuation to our simultaneoussystem of equations. In contrast to previous literature, we do not nd a signi-cant relationship between board size and rm valuation. Our results, therefore,support the Jensen (1993) and Lipton and Lorsch (1992) hypothesis.

The remainder of this paper is as follows. Section II gives an overview of therelated literature on board size and rm valuation. Section III explains the empirical approach. Section IV describes our sample of Swiss rms. Section V presents the empirical results, and section VI concludes.


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II. PRIOR RESEARCH ON BOARD SIZE

Probably the most widely discussed question in the literature on boards of di-rectors is whether having more outside directors increases corporate perform-ance. Unfortunately, there is numerous empirical evidence, which is mixed at best (e.g., Morck, Shleifer and Vishny 1988, Hermalin and Weisbach 1988, andBhagat and Black 1999). Interestingly, the maybe more obvious question aboutthe size of the board of directors has received much less attention. Therefore,our focus is on board size, or more specically, on the proposal for limiting thesize of boards in order to improve their effectiveness. One potential approachis to regard boards simply as a product of regulation. However, as Hermalin andWeisbach (2003) note, if boards simply satisfy regulatory requirements, theywould represent deadweight costs to rms, which subsequent lobbying pre-sumably would have eliminated, at least somewhere in the world. In any case,we should observe boards of minimum size. In practice, however, boards aregenerallylarger than required by law. Therefore, a more plausible hypothesisis that boards are part of the equilibrium solution (but still second-best) to thecontracting problem between dispersed shareholders and management (e.g.,Hart 1995). Viewed from this perspective, boards should be interpreted as anendogenously determined institution that helps to alleviate agency problems inlarge rms.

Jensen (1993) and Lipton and Lorsch (1992) were the rst to hypothesizethat board size affects corporate governance. The underlying notion is that atsome point the coordination problems outweigh the advantages from havingmore people to draw on. Jensen (1993) notes that when boards get beyondseven or eight people, they are less likely to function effectively and are easier for the CEO to control. Yermack (1996) presents empirical support for this proposition. Using a sample of large US public corporations, he reports an in-verse association between board size and rm valuation. This nding is notnecessarily clear ex ante ; an alternative hypothesis could be that larger boards bring together specialists from various functional areas and therefore contrib-ute to higher rm values. However, his results are robust to a variety of controlvariables, such as company size, growth opportunities and ownership structure.He carefully accounts for possible endogeneity problems. Causality runs from board size to rm valuation, and there is no evidence that companies change board size as a result of past performance. Specically, the results are incon-sistent with the conjecture that board size increases after poor performance inan attempt to increase management capacity. Yermack (1996) also reports thatsmaller boards are more likely to dismiss CEOs for poor performance, and thatCEO compensation is less dependent on performance if board size increases.


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Huther (1997) analyzes the relationship between board size and operatingcosts of US electricity companies. He also reports a negative board size effect.

Nevertheless, because the possible endogeneity of board size is not properlytaken into account, his results must be interpreted with due care. Conyon andPeck (1998) test the board size effect for a sample of rms from the UnitedKingdom, France, the Netherlands, Denmark, and Italy. Their results show anegative relationship between board size and rm valuation and the return onequity, respectively. However, the statistical signicance is rather mixed. In arelated study for a sample of Dutch rms, Postma, van Ees and Sterken (2003)report a negative relationship between board size and the market-to-book ratio, but again they do not properly account for the endogeneity problem.

Eisenberg, Sundgren and Wells (1998) nd a negative relationship between board size and rm valuation for a sample of small Finnish rms. The averagenumber of board members is 3.7 in their sample, as compared to 12.25 in Yer-mack (1996). This is interesting because average board size in their sample issignicantly below the critical number of board members of about 7 or 8,which has been put forth by Lipton and Lorsch (1992) and Jensen (1993).Taken together, the results are clearly inconsistent with the existence of an op-timal board size. To avoid biased estimates in ordinary least square regressionsin the presence of endogeneity, Eisenberg, Sundgren and Wells (1998) test a si-multaneous system of two equations, modeling board size and return on assets

as the dependent variables1. However, while this is an appropriate methodol-ogy, they do not account for possible relationships between different govern-ance mechanisms.

Finally, Loderer and Peyer (2002) analyze the effects of board overlap andseat accumulation on share prices for a panel of Swiss rms. They report thatseat accumulation is negatively related to rm value. Board size is used as acontrol variable in pooled regressions. Their results document that larger boardsize is associated with lower rm valuation. Given that we also apply Swissdata but obtain contradicting results, it is important to note that their data setdiffers from that in this paper. Loderer and Peyer (2002) use a panel of all rmstraded on the Swiss stock exchange in 1980, 1985, 1990 and 1995. In contrast,we use data as of end 2001. This is an important distinction because Loderer and Peyer (2002) report that average board size declined from 10.5 in 1980 to8.5 in 1995. The corresponding number in our sample is 6.6. Hence, average board size has decreased even further (see Section IV). This number is close tothe optimal board size put forth by Lipton and Lorsch (1992) and Jensen

1. They also report that while bad performance implies larger board changes, there is no signicantrelation between the lagged return on assets and the net change in board size.


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(1993). Most important, in contrast to the interpretations in previous studies,Loderer and Peyer (2002) are hesitant to draw nal conclusions. They argue

that the problem with the traditional argument is that it cannot explain whymarginally larger boards should impair performance even if boards are small to begin with, which is the case in the Eisenberg, Sundgren and Wells (1998)study for Finnish rms. In addition, one could generally expect that executivecommittees are an effective way to increase board effectiveness and conceiva- bly correct the drawbacks of large boards. However, Loderer and Peyer (2002)nd that the delegation of activities and responsibilities in companies withlarge boards to executive committees does not impact rm value. Therefore,they come up with an alternative explanation, suggesting that it is not so muchthat large boards make it harder to run rms properly, but rather that rms,whose governance systems are not working properly, are also characterized bylarger boards. If this is the case, large board sizes simply identify rms that arerun inefciently, but they are not the main reason for those inefciencies. Their considerations build an optimal starting point for our empirical analysis, sincethey seem to suggest that board size isnot an independent corporate govern-ance mechanism.Table 1 provides an overview of the related literature andsummarizes the discussion.

III. EMPIRICAL APPROACH1. Theoretical Considerations

Although striking, we think that the results in the previous literature raise animportant question. If boards are detrimental to rm value, why do we still seelarge boards? Or as Hermalin and Weisbach (2003) put it, why hasnt eco-nomic Darwinism eliminated this unt organizational form?2 To address thisquestion, it is important to understand two problems, which plague virtually allempirical work on boards of directors. First, most of the variables are endo-genous, i.e., the econometrician faces the problem of joint endogeneity. A plausible alternative to the Jensen (1993) and Lipton and Lorsch (1992) hypothesis is that troubled rms expand their board in response to poor past per-formance in order to increase managerial capacity3. Therefore, rm perform-ance is both a result of the actions of previous directors and itself a factor that

2. See Hermalin and Weisbach (2003), p. 13.3. However, an alternative hypothesis would be that rms attempt to wash out responsibilities over

a larger number of directors.


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Table 1

Overview of previous literature on board size

inuences the choice of subsequent directors. Second, as forcefully argued inHermalin and Weisbach (2003), many empirical results can be interpreted aseither equilibrium or out-of-equilibrium phenomena. Viewed as an out-of-equi-librium phenomenon, a negative relationship between board size and rm per-

Sample Board Size PerformanceMeasure

Findings

Yermack (1996)

Panel of 452large US rms(19841991)

4 to 34Mean: 12.25Median: 12

Tobins Q Signicant negative board size effect

Smaller boards re CEOsmore frequently

CEO compensation less per-formance dependent if boardsize is large

Large changes in board size(> 3) have signicant price

impactHuther (1997) US electricity

companies3 to 16Mean: 9

Total variablecosts

Signicant cost increasingimpact of board size

Eisenberg,Sundgren andWells (1998)

785 smallFinnish rms(19921994)

Mean: 3.7 ROA Signicant negative board size effect

Bad performance implieslarger board changes

Conyon andPeck (1998)

2886 rmsfrom UK, 360from France,186 from Netherlands,132 fromDenmark,126 from Italy(19901995)

Means:UK: 8.5France: 10.5 Netherlands:10.3Denmark: 10.7Italy: 11.8

ROE,Tobins Q

Negative board size effectin all countries

ROE: signicant negative board size effect in 3 countries

Tobins Q: signicant negative board size effect in 2 countries

Postma,van Ees andSterken (2003)

94 Dutchrms (1996)

Mean 4.95Median: 5

Market-to- book ratio

Negative board size effect

Loderer andPeyer (2002)

Panel of 169Swiss rms

Means: bet-ween 8.5 and10.5 (depend-ing on year)Medians: bet-ween 7 and 9(depending onyear)

Tobins Q Signicant negative board size effect

Committee work has no impact of rm value; thus newinterpretation large board isa sign of bad overall govern-ance system


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formance implies that limits on board size should be encouraged4. In contrast,the equilibrium interpretation of this result is that some other factor is causing

both board size and rm performance. In this case, any correlation between thetwo variables is purely spurious. An important policy implication, for example,is that regulation would be at best useless and possibly counterproductive. Or put differently, does board size really constitute an independent governancemechanism that is directly responsible for rms inefciencies and malfunc-tions? Alternatively, do larger board sizes simply identify rms that are not runas effectively as other rms? And in the latter case, what is the other factor driv-ing the results?

Sorting out the appropriate interpretation is an important task, which previ-ous studies could not answer due to their limited focus on board size as the sin-gle governance mechanism. Specically, these studies only looked at simulta-neous equations with board size and some measure of rm performance as thedependent variables (e.g., Eisenberg, Sundgren and Wells 1998). While this isan appropriate way to control for the possible endogeneity of board size andrm valuation, it does not account for the possibility that a rm can choosefrom a wide menu of different governance mechanisms. However, one may suspect that there exist important substitution effects between the different govern-ance mechanisms. Given a menu of alternative governance mechanisms, thegreater use of one mechanism needs not be positively related to rm valuation;

where one mechanism is used more, others may be used less, resulting in thesame valuation effects. Accordingly, the relationship between board size andrm valuation may possibly be driven by some other (so far unidentied) gov-ernance mechanism correlated with both board size and rm performance. Inthe terminology of Hermalin and Weisbach (2003), this would indicate an equi-librium situation.

2. Benets of Estimating a Simultaneous System of Equations

Our empirical approach accounts for the endogeneity problem in a simultane-ous system of equations and carefully chooses appropriate controlling variablesto distinguish between the two types of interpretation. Specically, we analyzefour corporate governance mechanisms: board size, outside representation onthe board, ownership structure, and debt. In a rst step, we are interested in

4. This is particularly interesting in light of the result of Wu (2000), who reports that board sizesover the 19901995 period decreased in the US, among other things, due to pressure from activeinvestors such as CalPERS.


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whether there are any interdependencies among these mechanisms. We include board size to examine whether it constitutes an independent governance mech-

anism, or whether it is simply related to the other mechanisms, but with no in-dependent impact on other rm characteristics. With the exception of owner-ship structure, these are all mechanisms chosen internally by the rmsdecision makers. Therefore, as argued by Agrawal and Knoeber (1996), all of the costs and benets should be considered. Optimal choice requires that theuse of a mechanism is increased until marginal benet just offsets marginalcost. In this case, a carefully specied cross-sectional regression should nd norelation between rm performance and the use of internally chosen mecha-nisms (i.e., board size, outside representation, and debt). This, in turn, doesnot imply that these mechanisms are ineffective. Conversely, for a governancemechanism chosen byoutside parties, such as ownership structure, part of thecosts or benets may be borne by parties other than those choosing the use of the particular mechanism. As a consequence, these choices need not maximizerm value.

If a rm altered the use of one of its internally chosen mechanisms, thiswould likely lead to a change in managerial behavior and a change in the rms performance. If these governance mechanisms are chosen optimally, any cross-sectional variation in their use should primarily reect differences in rms un-derlying environments, butnot mistaken choices. If these differences are con-

trolled for, then there should be no cross-sectional relation between the extentto which these mechanisms are used and rm valuation. In contrast, variationacross rms in the use of external mechanisms may reect both differences inrms environment and non-value maximizing choices. Hence, regressionanalysis may reveal a cross-sectional relation between rm performance andthe extent to which an external mechanism is used.

Overall, therefore, our empirical analysis addresses three main questions.First, is board size an independent governance mechanism, or is it merely dependent on the three other mechanisms? In other words, one goal is to shed lighton the possibly complex interrelationships between a set of governance mecha-nisms. We implicitly assume that different combinations of governance mecha-nisms can result in similar valuation effects. Second, do rms with smaller boards exhibit higher valuations? Taken together, the rst two questions are di-rectly related to an interpretation of the results in previous empirical studies asequilibrium or out-of-equilibrium situations. Third, are the four governancemechanisms selected optimally? If this is indeed the case, any cross-sectionalvariation in their use reects differences in rms underlying environment, butnot inefcient choices. In contrast, if these mechanisms are not selected opti-mally, changes in their use alleviate governance malfunctions and increase rm


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value. With respect to our particular interest in board size, the results from esti-mating a simultaneous system of equations can shed light on the hypothesis of

the existence of an optimal board size, as put forth by Jensen (1993) and Liptonand Lorsch (1992).

3. Setting up a Simultaneous System of Equations

To account for the problem of joint endogeneity, we test several equations sep-arately as well as in a system of simultaneous equations5. The four corporategovernance mechanisms we explore empirically are board size(BOARDSIZE) ,outsider representation on the board(OUTSIDER) , ownership structure(OWN-

ERSHIP) and leverage(LEV) (seeTable 2 for a description). Each governancemechanism appears on the left-hand side of one equation and the right-handside of each of the others.

Our rst regression equation contains BOARDSIZE as the dependent variable, where BOARDSIZE refers to the number of directors on the board of thecompany. Assuming that all relations are linear, we have6:

BOARDSIZE i = 0 + 1 OUTSIDER i + 2 LEV i + 3 OWNERSHIP i+ 4 SIZE i + 5 GOV i + 6 ROAi + 7 IND i + i (1)

Large rms will naturally have larger boards. Hence, we expect a positive rela-tionship between BOARDSIZE andSIZE , whereSIZE is measured as the natu-ral logarithm of total sales. The dummy variableGOV is one if the state ownsmore than 5% of the rms equity, and zero otherwise. This variable accountsfor the possibility that political inuences lead to presumably larger boardswith a disproportionate number of government representatives. As hypothe-sized by Hermalin and Weisbach (1991) and Yermack (1996), small boardscould contribute to better performance, or companies might adjust board sizein response to past performance in order to increase managerial capacity. Whilecausation is not clear ex ante , Yermacks (1996) results provide no evidence that boards either expand or contract in response to past performance. Nevertheless,to capture possible relationships between operating performance and boardsize, we also include current-year ROA. This variable is dened as operating in-

5. See Hermalin and Weisbach (2003) and Agrawal and Knoeber (1996) for a generalized descrip-tion of this approach.

6. We assume linear relations to avoid econometric problems, which may occur in simultaneousequation systems with nonlinear (endogenous) variables (see Davidson and MacKinnon 1993,chapter 18).


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come over total assets, where the latter is a simple average of the year 2001starting and ending values. Finally, to control for industry effects, we use an in-

dustry dummy, labeled as IND, as an exogenous variable. The industry classi-cation is from Swiss Exchange (SWX).We measure the extent of outsider membership on the board asOUTSIDER ,

i.e., the percentage of board seats held by non-ofcers and members without re-lationship to the founding family (if any). This is the dependent variable in our second equation:

OUTSIDER i = 0 + 1 BOARDSIZE i + 2 LEV i + 3 OWNERSHIP i+ 4 CEOCOB i + 5 ROAi + 6 GOV i + 7 IND i + i (2)

In addition to ROA and IND, we use a dummy variable calledCEOCOB as acontrol variable that is one if the CEO is also Chairman of the Board (COB),and zero otherwise. Being CEO and COB at the same time alleviates coordina-tion and communication problems. On the other hand, a major conictwithinthe boardroom is between the CEO and the directors. The CEO has the incen-tive to capture the board, so as to ensure that he can keep his job and increasethe other benets he derives from being CEO. Directors have the incentives tomaintain their independence and monitor the CEO. Shivdasani and Yermack (1999) suggest that a situation where the CEO is also the COB leads to a con-

centration of power and the election of less independent board members. Ac-cordingly, we expect a negative relationship betweenOUTSIDER and CEO-COB . Finally, to control for government ownership, we again includeGOV asan exogenous explanatory variable. Ex ante , one would suspect that rms withlarge government stakes have fewer outsiders on the board.

Our third internal governance mechanism, rm leverage, denoted as LEV , isthe ratio of total (non-equity) liabilities to total assets. We use this governancemechanism as the dependent variable in our third regression equation:

LEV i=

0+

1 BOARDSIZE

i+

2 OWNERSHIP

i+

3 OUTSIDER

i+ 4 SIZE i + 5 AGE i + 6 GROWTH i + 7 IND i + i (3)

The control variables are chosen following previous results. Recently, Drobetzand Fix (2003) report that Swiss rms with more growth opportunities haveless leverage. Hence, we expect a negative relationship between LEV andGROWTH , where the latter is the average annual sales growth over the pastthree years. In contrast, their results indicate that larger and more mature rmsexhibit higher leverage ratios, implying a positive relationship between LEV and bothSIZE and AGE , where AGE is the number of years since inception as


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a private limited company. This is also consistent with Jensens (1986) freecash-ow hypothesis, where mature rms with substantial cash-ows use more

debt to discipline managers. To control for industry effects, we again includethe industry dummies, labeled as IND.Our only external governance mechanism is ownership structure. Speci-

cally, the variableOWNERSHIP denotes the percentage of cumulated votingrights exercised by large investors with > 5% of voting rights7. For rms withunitary shares, this is equivalent to the percentage of actual stockholdings. Thefourth regression specication is:

OWNERSHIP i = 0 + 1 BOARDSIZE i + 2 LEV i + 3 OUTSIDER i+ 4 SIZE i + 5 RESTR i + 6 GROWTH i + 7 IND i + i (4)

We includeSIZE as an exogenous variable, because one might suspect thatlarger rms have less ownership concentration. Voting restrictions could allowsome shareholder groups (e.g., founding families) to practically dominate therm even if they own less than 50% of the rms stock. This allows them to pur-sue their own interest at the expense of other shareholders with less board in-uence. One may therefore suspect a positive relationship betweenOWNER-SHIP and RESTR, where the latter variable is a dummy variable that is one if the rm has different share categories with different voting rights and, hence,

deviates from the one-share-one-vote principle. Finally, Zeckhauser und Pound(1990) argue that the higher the R&D intensity, the more closed is the informa-tion structure, and the more difcult is outside monitoring. Large investors willrecognize the problems associated with asymmetric information and, hence,ownership concentration should be lower for rms with a more diffuse infor-mation structure. We therefore useGROWTH as a proxy for asymmetric infor-mation (i.e., the difculty to monitor) and expect a negative relationship withOWNERSHIP .

To summarize, each governance mechanism depends on all the others asspecied in equations (1)(4). To estimate these relationships empirically, weadopt a simultaneous equations framework and apply the weighted two-stageleast squares (W2SLS) procedure. This procedure also accounts for het-eroscedasticity. There are eight exogenous variables in the four equations.Therefore, at least three of the exogenous variables must be excluded from any

7. Unfortunately, the Aktienfhrer Schweiz 2002/2003 (Swiss Stock Guide) by Finanz und Wirt- schaft only includes voting rights. Therefore, we also use the variable RESTR (i.e., a dummy var-iable that is 1 if the rm has different share categories with different voting rights attached, and0 otherwise) as a controlling variable for OWNERSHIP . In our sample, 24% of the rms havethis form of voting restrictions.


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Table 2

Summary of variables

single equation to identify the system. The development of equations (1)(4)is motivated partially by the need for these exclusion restrictions to be met, butmost of them seem non-controversial. For example, AGE is likely to be relatedto leverage, but it is unlikely to be related to all other governance mechanisms.Similarly,CEOCOB should only be important for theOUTSIDER equation.Excluding ROA from the LEV equation seems somewhat more problematic.The ndings in Drobetz and Fix (2003) indicate that ROA is an important var-iable to explain cross-sectional differences in leverage of Swiss rms. How-ever, this exclusion is driven by the requirement that any single equation of thesystem must be identied8.

Endogenous variables

Tobins Q Ratio of market value to book value of assets. Market value of assets is computed as market value of equity plus book value of assets minus book value of equity

BOARDSIZE Number of directors on the board of the company

OUTSIDER Outsider membership on the board, measured by the percentage of board seatsheld by non-ofcers without relationship to the founding family (if any)

LEV Leverage, measured as the ratio of total (non-equity) liabilities to total assets

OWNERSHIP Percentage of cumulated voting rights exercised by large investors with > 5%

of voting rightsExogenous variables

SIZE Firm size, measured by the natural logarithm of sales

GOV Dummy variable = 1 if state owns > 5% of the rms equity, = 0 if otherwise

ROA Ratio of operating income and total assets (return on assets)

CAR Cumulated risk-adjusted abnormal return over the last 24 months (using weeklydata)

AGE Number of years since inception as private limited company

RESTR Dummy variable = 1 if the rm has different share categories with different vot-

ing rights attached, = 0 if otherwiseCEOCOB Dummy variable = 1 if the CEO is also COB, = 0 if otherwise

GROWTH Average annual growth of sales over the past three years (19992001)

IND Dummy variable = 1 if rm belongs to a particular industry (15 sectors as clas-sied by SWX), = 0 if otherwise

8. Note that in the system of equations (1)(4) we could add ROA as an additional variable, stillleaving the system identied. However, when we expand the system and add the Tobins Q re-


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In our nal regression equation, in addition to the interrelations among thegovernance mechanisms, we also examine the cross-sectional relationship be-

tween these mechanisms and rm valuation, measured by Tobins Q9. TobinsQ is dened as the ratio of market value to replacement value. As an approxi-

mation, the market value of assets is usually computed as market value of equity plus book value of assets minus book value of equity. The replacementvalue is taken as the book value of assets. A Tobins Q ratio greater than 1 indi-cates that the rm has done well with its investment decisions, i.e., it has in-vested in positive net present value projects. In contrast, a value of Tobins Qlower than 1 indicates that the company did not even earn its rm-wide cost of capital. The empirical specication is as follows:

Q i = 0 + 1 BOARDSIZE i + 2 LEV i + 3 OUTSIDER i + 4 OWNERSHIP i+ 5 SIZE i + 6 GROWTH i + 7 ROAi + 8 IND i + i (5)

In addition to the four governance mechanisms, we include controls for other variables that might affect Tobins Q directly. Following Morck, Shleifer andVishny (1988), we control for growth opportunities and expect a positive rela-tionship between Tobins Q andGROWTH . We also control for SIZE , sincegrowth opportunities should be lower for larger rms. On the basis of simplevaluation models, ROA seems a purely analytical control variable; one expects

a positive relationship.We rst estimate equation (5) using ordinary least square. This allows us toexamine the effect of all governance mechanisms together, but treats each of them as exogenous. If the previous analysis showed that all four governancemechanisms were independent, this would be an adequate and sufcient proce-dure. Nevertheless, in a second step we include equation (5) along with (1)(4)in a simultaneous system of equations, adding Tobins Q as an independent var-iable, and again apply weighted two-stage least square (W2SLS) to estimate thesystem. This treats Tobins Q as endogenous along with the governance mech-anisms, allowing each of the mechanisms to affect Tobins Q but also allowingTobins Q to affect the choice of each mechanism. Finally, note that this systemis just identied equation-by-equation.

gression in equation (5), we must exclude at least four exogenous variables from each equationto identify the system. In untabulated tests we nd that using ROA in equation (3) instead of AGE (which we think could most easily be replaced) does not qualitatively change our results.

9. Alternatively, Eisenberg, Sundgren and Wells (1998) and Conyon and Peck (1998) use return of assets (ROA) and return on equity (ROE), respectively.


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IV. DATA DESCRIPTION

We potentially target all 267 rms contained in the Swiss Performance Index.We exclude all banks, insurances, and other nancial services rms. This isstandard in the empirical corporate nance literature due to problems in com- puting appropriate valuation measures. After inspecting the collected data, wedrop another six rms, which we regard as obvious outliers10. This leaves uswith a nal sample of 165 publicly listed rms. Our primary sources of data areDatastream and Worldscope. Several data had to be collected manually from

Aktienfhrer Schweiz 2002/2003 and the website of Finanz und Wirtschaft .Most of the data are as of end 2001, i.e., they refer to the reporting period fromJanuary 2001 to December 2001.

Table 3 shows descriptive statistics of Tobins Q and the four governancemechanisms. Following Loderer and Peyer (2002), we dene Tobins Q as theratio of market value to book value of assets. Market value of assets is computed as market value of equity plus book value of assets minus book value of equity. To avoid that daily uctuations inuence our results, we compute themarket value of equity as the mean of daily observations during 2001. The av-erage value of Tobins Q is 1.50, the median is 1.24. This indicates that Swissrms, on average, invest in positive NPV projects.

The average board size in our Swiss sample is 6.59. This is only half of the

size of boards studied in Yermack (1996) for the US, but signicantly larger than those in Eisenberg, Sundgren and Wells (1998) for a Finnish sample. It isalso important to note that the average board size of Swiss rms has decreasedover time. Using data from all rms traded on the Swiss stock exchange in1980, 1985, 1990 and 1995, Loderer and Peyer (2002) report that average boardsize declined from 10.5 in 1980 to 8.5 in 1995. Since then, board size further decreased to an average of 6.6, which is just the board size hypothesized to beoptimal by Lipton and Lorsch (1992) and Jensen (1993).

However, as one could have expected, there are pronounced differences be-tween rms with and without government inuence. Specically, there areseven rms in our sample where some state authority owns more than 5% of the rms equity. On average, board size for these rms is 11.71. The differencein board size is statistically signicant on the basis of a simplet -test (with at -value of 6.69).

10. Excluded rms have values of Tobins Q above 6.


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Table 3

Descriptive statistics

Lipton and Lorsch (1992) and Jensen (1993) argue that for board sizes beyondseven or eight the benets of increasing monitoring capacities are outweighed

by costs such as slower decision-making, less-candid discussions of managerial performance, and biases against risk-taking. Roughly 85% of all rms in thefull sample have a board size equal to or less than eight. Figure 1 shows themean and median values of Tobins Q for companies sorted by board size. In-terestingly, there is no obvious relationship between the two variables, i.e., in aunivariate analysis larger board sizes are not associated with lower valuations.This is in sharp contrast to the results in Yermack (1996) for US data. Plotting board size against average Tobins Q as in Figure 1 , he nds that Tobins Q val-ues decline almost monotonically over the range of board size11. For boardsizes below six, however, he also reports no consistent association between board size and rm value. In contrast, Eisenberg, Sundgren and Wells (1998) present a gure with a negative relationship between the two variables for their sample of Finnish rms, even though average board size is only 3.7. Neverthe-less, as argued above, the relationship depicted in Figure 1 does not drive our empirical results; it is necessary to account for possible interrelationships bet-ween different governance mechanisms.

Variable Mean Median S. D. Maximum/Minimum

Tobins Q 1.50 1.24 0.86 5.70/0.40

BOARDSIZE 6.59 6.00 2.33 19/3

BOARDSIZE if GOV = 1 11.71 11.00 3.64 19/8

OUTSIDER 0.87 0.89 0.15 1/0.2

LEV 0.55 0.57 0.18 0.99/0.043

OWNERSHIP 0.47 0.50 0.26 1/0

Notes: The table contains the descriptive statistics of 165 Swiss rms listed on Swiss Exchange

(SWX), excluding banks, insurance and nancial services companies. Tobins Q is the ratio of mar-ket value to book value of assets. Market value of assets is computed as market value of equity plus book value of assets minus book value of equity. BOARDSIZE is the number of directors on the board of the company. GOV is a dummy variable that is one if the state owns > 5% of a rms equity,and zero otherwise. OUTSIDER is measured by the percentage of board seats held by non-ofcerswithout relationship to the founding family (if any). LEV is computed as the ratio of total (non-eq-uity) liabilities to total assets. OWNERSHIP is the percentage of cumulated voting rights exercised by large investors with > 5% of voting rights. S. D. is the abbreviation for standard deviation.

11. See Yermack (1996), Figure 1 , p. 193.


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Figure 1

Tobins Q and board size

Table 3 further shows that the average value of OUTSIDER is 0.87, which isalso in contrast to the results in Yermack (1996). He reports a much lower valueof 0.54 for US rms. This is a surprising result for two reasons. First, similar tothe United States (but in contrast to Germany), Switzerland has a one-tier boardsystem. And second, founding families are still regarded as a non-negligiblefactor in corporate Switzerland. The data for the variableOUTSIDER is takenfrom the website of Finanz und Wirtschaft 12.

The average leverage ratio ( LEV ) is 55%, which closely corresponds to thegures recently reported in Drobetz and Fix (2003). The average of OWNER-SHIP is 0.47. The maximum of 1 for this variable is due to Hilti, where all reg-istered shares with voting rights are in the hands of the founding family, whileall publicly traded participation notes have no voting rights.

Finally,Table 4 shows the correlation coefcients between Tobins Q and thefour governance mechanisms. All correlations are relatively small. The onlynoteworthy correlation is that between BOARDSIZE and OUTSIDER . The re-

12. See http://www.nanzinfo.ch.


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spective value is 0.275, which is slightly higher than in Yermack (1996). This isan important result, because it indicates that part of the board size effect reported

in earlier studies may relate to the composition of the board. Note that we accountfor this possibility in our empirical setup, having bothOUTSIDER and BOARD-SIZE as explanatory variables in equations (1) and (2), respectively.

Table 4

Correlation matrix between governance mechanisms

Our controlling variables are gathered from different sources.SIZE is measuredas the natural logarithm of sales in 200113. We deneGROWTH as the averageannual sales growth over the past three years (19992001). For rms whichwent public after 1999, we use average sales growth since IPO14. ROA is de-ned as the ratio of operating income to total assets, where operating income ismeasured as of end 2001, but total assets are a simple average of the respectivestarting and ending values. The corresponding list of rms with voting restric-tions for the variable RESTR can directly be found in the Aktienfhrer Schweiz2002/2003 15. The data for the dummy variableCEOCOB is from the website of

Finanz und Wirtschaft . Finally, we apply the industry classication, as provided

BOARDSIZE LEV OWNERSHIP OUTSIDER Tobins Q 0.018 0.261 0.207 0.072

BOARDSIZE 0.075 0.012 0.275LEV 0.020 0.005OWNERSHIP 0.100 Notes: The table shows the correlation coefcients between Tobins Q and the four governancemechanisms: BOARDSIZE, LEV, OWNERSHIP, and OUTSIDER. Tobins Q is the ratio of marketvalue to book value of assets. Market value of assets is computed as market value of equity plus book value of assets minus book value of equity. BOARDSIZE is the number of directors on the board of the company. OUTSIDER is measured by the percentage of board seats held by non-ofc-ers without relationship to the founding family (if any). LEV is computed as the ratio of total (non-equity) liabilities to total assets. OWNERSHIP is the percentage of cumulated voting rights exer-cised by large investors with > 5% of voting rights. The sample contains 165 Swiss rms listed onSwiss Exchange (SWX), excluding banks, insurance and nancial services companies.

13. We also experimented with the logarithm of total (book) assets as of end 2001, but the resultsare qualitatively similar.

14. We also excluded particular rm-years for Allreal, Bon Apptit, Sulzer und Zblin due to rm-specic events, such as acquisitions and spin-offs.

15. See Aktienfhrer Schweiz 2002/2003, p. 468.


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by Swiss Exchange (SWX)16. For each of the 15 industries we construct adummy variable, denoted as IND.

V. EMPIRICAL RESULTS

This section describes our empirical results. In section V.1 we examine the in-terdependencies among the four governance mechanisms. In section V.2 we ex-tend the simultaneous system of equations and analyze the relationship bet-ween rm valuation and the different governance mechanisms. Section V.3contains several robustness tests.

1. Relationships Between the Governance Mechanisms

To examine the relationship between the four governance mechanisms, we es-timate (1)(4) as a system of linear equations using weighted two-stage leastsquare (2SLS). Each governance mechanism appears on the left-hand side of one equation and the right-hand side of each of the others. We are primarily in-terested in the null hypothesis that board size is not an independent governancemechanism. If this is true, any ndings that board size is negatively related to

rm valuation may be spurious, and some other factor determines both boardsize and rm valuation. The null hypothesis must be rejected if the coefcientson the other three governance mechanisms in the BOARDSIZE equation are in-signicant. The results of the weighted 2SLS estimation are displayed inTable 5 .

The coefcients of the exogenous variables in the lower part of Table 5 gen-erally have the predicted sign, but they are often statistically insignicant. Ashypothesized, looking at board size (equation (1)), rms with government own-ership have larger boards. On average, a rm where the state owns a signicant portion of stock has four additional board members, all else equal. The coef-cient onGOV is signicant at the 1% level. The coefcients onSIZE and ROAare positive and negative, respectively, but both are insignicant. With respectto board composition (equation (2)), we nd evidence for a potential conictwithin the boardroom. There is a negative relationship betweenOUTSIDERandCEOCOB , indicating that outsiders seek independence from the CEO and prohibit the CEO to take the role as COB at the same time. Looking at leverage(equation (3)), the signs of the coefcients onSIZE and AGE are as predicted

16. See http://www.swx.com.


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ex ante. Large rms carry higher debt levels, and the coefcient onSIZE is sig-nicant at the 1% level. Older rms (measured by the variable AGE ) are also

more levered, but the relationship is not signicant. Surprisingly, rms withmore growth opportunities exhibit higher leverage, but the coefcient onGROWTH is again insignicant. Finally, with respect to ownership structure(equation (4)), the only signicant exogenous variable is RESTR, indicatingthat a rm has different share categories with different voting rights attached.As hypothesized, larger rms have less ownership concentration, although therelationship is insignicant.

We now look at the coefcients for the endogenous variables in the upper partof Table 5 . Evidently, there are no interdependencies between any of the four governance mechanisms; the respective coefcients are all insignicant. There-fore, we conclude that the null hypothesis must be rejected. Board size should be regarded as an independent governance mechanism, and potential correla-tions with rm valuation are not merely spurious. Most important, any potential board size effect is not (solely) related to board composition. Of course, with nointerdependencies at all, the other three mechanisms board composition, own-ership structure, and leverage also constitute independent governance mech-anisms. However, given the results from previous studies, this should come asno surprise.

Finally, a Wald test for the simultaneous signicance of all the coefcients

(except the constant and the industry dummies) always rejects the null hypoth-esis that they are jointly zero, except for theOUTSIDER equation.

2. Firm Valuation and Governance Mechanisms

In this section we examine the null hypothesis that board size has no inuenceon rm performance against the alternative hypothesis that reductions in boardsize increase rm performance. For this purpose, we estimate the extended sys-tem of simultaneous equations (1)(5). The null hypothesis must be rejected if the coefcient on BOARDSIZE in the regression containing Tobins Q as the dependent variable (in equation (5)) is signicant. A nal (and closely related)question is whether the four governance mechanisms are selected optimally. Ashypothesized, this is the case if the marginal benet of a mechanism just offsetsmarginal cost. This hypothesis can be tested in the same system of equations(1)(5). Specically, it must be rejected if a signicant relationship betweenrm valuation and the use of internally chosen mechanisms is uncovered. Incontrast, insignicant coefcients on the respective variables in the regressioninvolving Tobins Q as the dependent variable (in equation (5)) are a sign of op-


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Table 5

Results from weighted 2SLS regressions of governance mechanisms

Dependent variable (N = 165)Independent variable BOARDSIZE OUTSIDER LEV OWNERSHIPConstant 0.151

0.96630.627**0.0361

0.1310.6601

0.3290.5897

BOARDSIZE 0.0920.4851

0.0160.3113

0.0200.5885

OUTSIDER 0.7940.8187

0.0500.8734

0.6980.3253

LEV 5.1700.4529

0.6410.6468

1.3430.1006

OWNERSHIP 0.0750.9557

0.0530.7176

0.1210.2043

SIZE 0.2160.4307

0.027***0.0089

0.00050.9879

GOV 4.284***0.0000

0.3480.5316

AGE 0.00030.1419

GROWTH 0.0330.6582

0.0530.7331

RESTR 0.309***0.0000CEOCOB 0.109**

0.0215ROA 0.116

0.9596 0.042

0.8614Industry included included included includedWald test 56.72 (6)

0.00008.49 (6)0.2042

33.49 (6)0.0000

33.04 (6)0.0000

Notes: The table shows the results from a weighted two stage least square (W2SLS) estimation of equations (1)(4) of the system of linear equations described in section III.3. The dependent variable in column (1) is BOARDSIZE, which is the number of directors on the board of the company.The dependent variable in column (2) is OUTSIDER, which is measured by the percentage of boardseats held by non-ofcers without relationship to the founding family (if any). The dependent vari-able in column (3) is LEV, which is computed as the ratio of total (non-equity) liabilities to totalassets. The dependent variable in column (4) is OWNERSHIP, which is the percentage of cumulatedvoting rights exercised by large investors with > 5% of voting rights. The description of the exoge-nous variables can be found in Table 2. The sample contains 165 Swiss rms listed on Swiss Ex-change (SWX), excluding banks, insurance and nancial services companies. A Wald test is per-formed for the simultaneous signicance of all coefcients (except the constant and the industrydummies). The numbers beneath the coefcients are probability values for two-sided tests. The symbols ***, **, * denote statistical signicance at the 1%, 5%, 10% level, respectively.


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timal choice. An exception is ownership structure, which constitutes an exter-nally chosen mechanism. In this case, variation across rms may reect both

differences in rms environment and non-value maximizing choices. Hence,even a carefully specied regression may reveal a cross-sectional relation be-tween rm valuation and the extent to which an external mechanism is used.Table 6 shows the empirical results.

In the rst column of Table 6 we test equation (5) using simple OLS, withTobins Q as the dependent variable. Given that all four mechanisms are unre-lated and independent, we can treat them as exogenous in this simplest speci-cation. Note that this setup does not allow for any interdependence in thechoices of governance mechanisms, but it does allow for the availability of al-ternative governance mechanisms. To control for a possible nonlinear relation-ship between board size and rm valuation, we add a quadratic term ( BOARD-SIZE 2) in the second column. As one may expect, the respective coefcient isnegative, but insignicant. In the third column we also add an interaction term,OWNERSHIP * RESTR, to account for the strong relationship between the twovariables. In all three equations BOARDSIZE has a negative coefcient, butthey are far from being statistically signicant. Therefore, we cannot reject thenull hypothesis that board size has no inuence on Tobins Q. This conrms theinitial intuition from a mere visual inspection of Figure 1 , where board size is plotted against average Tobins Q.

BecauseOWNERSHIP constitutes an external mechanism, it should not besurprising that the corresponding coefcients in columns (1) and (2) are signif-icant at the 5% level. What is surprising, however, is the negative sign of thecoefcient, i.e., a more dispersed ownership leads to a higher Tobins Q. Whenwe include the interaction termOWNERSHIP * RESTR in column (3), it becomesevident that not ownership concentration itself drives the results, but instead theexistence of shares with different voting rights. While the coefcient onOWN-

ERSHIP becomes insignicant, the coefcient on the interaction term is nega-tive and signicant at the 1% level. This result has an important practical impli-cation. It clearly indicates that the interests of dominating shareholders (possiblyin combination with some voting restrictions) and other shareholders are not al-ways in line (see Morck, Shleifer and Vishny 1988). In fact, many Swiss rmshave abandoned their common dual class shares and introduced unitary sharesonly in recent years (see Kunz 2002). This seems to be an important step towardsoverall rm value maximization. In column (4) we include both board sizesquared as well as the interaction term, but again only the latter is estimated sig-nicantly.

The regression setup in columns (1)(4) assumes that protability is heldconstant. Accordingly, we test a direct relationship between board size and rm


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Table 6 Results from OLS and W2SLS regressions using Tobins Q

Dependent variable: Tobins Q (N = 165)Independentvariable

(1)OLS

(2)OLS

(3)OLS

(4)OLS

(5)OLS

(6)OLS

(7)W2SLS

Constant 1.2100.1046

1.1810.1171

0.7670.3037

0.7210.3420

0.5690.4550

0.5270.4896

1.1870.4639


0.0040.9646

0.0160.4576

0.0130.8739

0.0260.2639

0.0020.9770

0.0360.6705

BOARDSIZE^2 0.0010.7838

0.0020.6664

0.0020.6816

LEV 0.3710.3390

0.3720.3389

0.4770.2164

0.4790.2150

0.6090.1375

0.6090.1375

2.7320.3634

OWNERSHIP 0.449**0.0451 0.449**0.0458 0.0390.9005 0.0360.9070 0.3100.1885 0.3100.1886 1.250**0.0184OWNERSHIP*RESTR 0.570***

0.0058 0.573***

0.0058OUTSIDER 0.228

0.5038 0.233

0.5002 0.334

0.3373 0.342

0.3286 0.256

0.4552 0.263

0.44910.1220.9360

SIZE 0.0380.3215

0.0360.3633

0.064*0.0991

0.0620.1231

0.081**0.0446

0.078*0.0659

0.1180.2810

GROWTH 0.5550.1688

0.5540.1705

0.5750.1400

0.5740.1416

0.6750.1199

0.6740.1214

0.5280.1687

ROA 2.046***

0.0034

2.042***

0.0035

1.957***

0.0028

1.951***

0.0029

1.702*

0.0733Industry included included included included included included includedWald test 20.62 (7)

0.004421.54 (8)0.0059

34.29 (8)0.0000

34.53 (9)0.0001

12.18 (6)0.0582

13.99 (7)0.0513

25.86 (7)0.0005

Adjusted R 2 0.459 0.456 0.482 0.479 0.412 0.408 Notes: The table shows the results from OLS regressions of Tobins Q on all governance mechanismsalong with different combinations of the exogenous control variables included in equation (5), as de-scribed in section III.3. Tobins Q is the ratio of market value to book value of assets. Market value of assets is computed as market value of equity plus book value of assets minus book value of equity. Thenal column (7) contains the results from a weighted two stage least squares (W2SLS) estimation of the complete system, as described in equations (1)(5). Only the coefcient estimates for equation (5)

are reported. BOARDSIZE is the number of directors on the board of the company. OUTSIDER ismeasured by the percentage of board seats held by non-ofcers without relationship to the foundingfamily (if any). LEV is computed as the ratio of total (non-equity) liabilities to total assets. OWNER-SHIP is the percentage of cumulated voting rights exercised by large investors with > 5% of votingrights. SIZE denotes the natural logarithm of sales, GROWTH the average annual growth of sales over the past three years (19992001), and ROA the ratio of operating income and total assets (return onassets). RESTR is a dummy variable equal to 1 if the rm has different share categories with differentvoting rights attached, and 0 otherwise. The sample contains 165 Swiss rms listed on Swiss Exchange(SWX), excluding banks, insurance and nancial services companies. A Wald test is performed for thesimultaneous signicance of all coefcients (except the constant and the industry dummies). The numbers beneath the coefcients are probability values for two-sided tests. The symbols ***, **, * denotestatistical signicance at the 1%, 5 %, 10% level, respectively.


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valuation, independent of a rms protability. This is the implicit notion thatunderlies the Jensen (1993) and Lipton and Lorsch (1992) argument of coordi-

nation problems and director free-riding, among others, with increasing boards.However, the analysis may ignore a potentially importantindirect relationship between board size and rm valuation. Specically, smaller boards could affect protability, which then in turn leads to higher valuations17. To allow for this in-direct relationship between board size and rm valuation through increased protability, we exclude ROA as a control variable. The results are shown in col-umn (5). Interestingly, the coefcient of board size changes only marginally andremains statistically insignicant. Even when we add the quadratic BOARD-SIZE 2 variable in column (6), the results are unchanged. To further explore the possibility of an indirect effect between board size and Tobins Q, one may alsoapply ROA as the dependent valuation measure and explore whether board sizeaffects protability. We postpone this analysis until section V.3.

Finally, in column (7) we treat all four governance mechanisms as endog-enous and allow for possible interrelations. The system of equations (1) (5) isagain estimated simultaneously using weighted 2SLS. For the sake of brevity,we only report the results from equation (5), with Tobins Q as the dependentvariable18. The coefcient on BOARDSIZE is negative, but again insignicant.Similarly, the coefcients on the other internal governance mechanisms, LEV andOUTSIDER , are also insignicant. This is in contrast to Agrawal and Knoe-

ber (1996), who report a persistent effect of board composition on rm per-formance. Our results are consistent with optimal choice of allinternal mech-anisms. Hence, the cross-sectional variation in the use of these mechanisms toa large extent reects differences in rms underlying environments, rather than mistaken choices, which need to be reversed. This also implies that anychanges in their use leave rm valuation unaffected at best, but possibly lead toa decrease in Tobins Q. But in this case, it isnot because some other factor isresponsible for a spurious correlation between any of the internal mechanisms(e.g., board size) and rm valuation, but it is because the mechanisms are al-ready in optimal use. One obvious explanation for this result is that average board size in our sample (6.59) is just below the critical value of 78, as pos-tulated by Lipton and Lorsch (1992) and Jensen (1993). Accordingly,on aver-age , the number of board members in our sample of Swiss rms is just aboutoptimal, i.e., the advantages of larger boards from increased management ca-

17. The problem of fragile empirical linkages, where small changes in the conditioning informationset can lead to extremely different policy implications, was discussed by Levine and Renelt(1992) in their study of the determinants of long-run macroeconomic growth.

18. The coefcients on Tobins Q in equations (1) (4) are always insignicant.


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pacities are offset by the potential disadvantages from coordination, communi-cation, and decision-making problems. Taken together, our results inTable 5

and 6 suggest that board size is an independent governance mechanism, andrms choose board size just optimal. This interpretation is consistent withHarts (1995) notion that boards are part of the equilibrium (but still second- best) solution to the contracting problem in rms with dispersed shareholders.

The nal column inTable 6 also reveals a signicant negative relationship be-tweenOWNERSHIP and Tobins Q, i.e., more cumulated voting rights exercised by large investors lead to lower rm valuations. This is inconsistent with the no-tion in Stiglitz (1985) and Shleifer and Vishny (1986) that a natural way to improve corporate governance is to ensure that a company has one or more largeshareholder. Empirically, however, Morck, Shleifer and Vishny (1988) show ev-idence that large shareholders have a mixed role; there is a non-monotonic rela-tionship between Tobins Q and the fraction of company stock owned byinsiders19. A possible explanation for the signicant negative relationship in our Swiss sample could be that large shareholders use their voting power to improvetheir own position at the expense of other shareholders. Recall, however, that we presumed thatOWNERSHIP was anexternal governance mechanism. The cross-sectional differences inOWNERSHIP and the negative relationship with TobinsQ may at least partly reect non-value maximizing choices, which are out of di-rect control by rms decision makers. Finally, as expected, current level of prof-

itability, measured by return on assets, has a positive association with Tobins Q.The explanatory powers of our cross-sectional regressions are reasonablyhigh, the adjusted R-squares range between 0.456 and 0.482. Again, Wald testsfor the null hypothesis that all coefcients are jointly zero (except the constantand the industry dummies) strongly reject.

3. Robustness Tests

To make sure our results are accurate, we conduct several robustness tests.

First, in untabulated regressions we reproduced all our results using three-stageleast square (3SLS), but they are qualitatively the same. Because the expandedsystem of equations (1)(5) is just identied equation-by-equation, the coef-cient estimates in weighted 2SLS and 3SLS are identical in this case. Second,

19. Note that the relationship betweenOWNERSHIP and Tobins Q is supposedly highly non-linear.For low and moderateOWNERSHIP levels, incentive-alignment effects result in a positive re-lationship. But as managerial ownership increases, entrenchment-related costs will dominateand produce a negative relationship betweenOWNERSHIP and Tobins Q. Obviously, our 5%criteria with regards to voting rights exercised by large investors is above the threshold.


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instead of the return on assets (ROA) we used cumulated risk-adjusted returns(CAR) over the 24 months period from 2000.01 to 2001.12 (using weekly re-

turns) as a controlling variable, but again the results did not change.Third, we used alternative measures of rm valuation. In the spirit of Eisen- berg, Sundgren and Wells (1998), we compute an industry-adjusted Tobins Q.This variable is dened as the residual between a rms and the correspondingindustrys median Tobins Q. Alternatively, we also use the ratio of market-to- book equity as a measure of rm value. Our results are robust in both cases, andthe interpretations do not change. Finally, we use ROA as the dependent variable. Given the discussion about direct and indirect relationships between boardsize and rm valuation in section V.2, this is a particularly interesting robustnesscheck. Smaller boards may affect protability, which then in turn leads to higher valuations. To further explore this possibility of an indirect relationship, we apply ROA as our nal measure of rm valuation and estimate the impact of boardsize. Table 7 reveals that our results are still robust, i.e., the coefcients on

BOARDSIZE and BOARDSIZE ^2 remain insignicant in all specications20.We conclude that there is no unobserved indirect effect between board size andrm valuation through increased protability that drives our main results. Theonly noteworthy changes in results are that the coefcient onOWNERSHIP isnow positive and the coefcient on LEV becomes signicant. The negative signof the coefcient on LEV is consistent with Myers (1984) pecking order theory

of the capital structure, where more protable rms use internal sources to re-alize value-enhancing projects and can avoid approaching the capital market.To make sure causality runs from board size to rm valuation, Yermack

(1996) and Eisenberg, Sundgren and Wells (1998) test whether companies expand board size in response to bad performance. They both nd that poor per-formance leads to both more departures of board members and more appoint-ments to the boards, but net board size remains constant. While we think thatour approach appropriately controls for endogeneity problems, we test for this possibility in a very simplistic way by including lagged values of the return onassets in the BOARDSIZE equation (equation (1)). We use lags of one and twoyears, but in both cases the coefcients are insignicant.

To double-check the validity of the results inTable 6 , we replicate the OLSregressions with Tobins Q as the dependent variable separately for each gov-ernance mechanism. We use the same exogenous variables (SIZE , GROWTH ,

ROA and IND ) in each of the four regressions. As before, only the coefcient

20. Because our initial system inTable 6 was just identied, we cannot provide W2SLS estimatesin Table 7 without an additional exogenous variable.


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Table 7

Results from OLS regressions using ROA

Dependent variable: ROA (N = 165)

Independent variable (1)OLS

(2)OLS

(3)OLS

(4)OLS

Constant 0.313**0.0385

0.320**0.0317

0.330**0.0354

0.338**0.0289


0.0010.9615

0.0050.1552

0.00020.9861

BOARDSIZE^2 0.00030.6189

0.00030.5909

LEV 0.116*0.0507 0.116*0.0513 0.120**0.0481 0.120**0.0485

OWNERSHIP 0.068**0.0318

0.068**0.0320

0.085*0.0663

0.085*0.0658

OWNERSHIP*RESTR 0.0230.4362

0.0240.4270

OUTSIDER 0.0140.8617

0.0150.8509

0.0180.8180

0.0190.8060

SIZE 0.021***0.0024

0.021***0.0055

0.022***0.0030

0.022***0.0061

GROWTH 0.0590.3212 0.0590.3258 0.0600.3168 0.0600.3216

Industry included included included included

Wald test 18.17 (6)0.0058

21.85 (7)0.0027

19.89 (7)0.0058

23.75 (8)0.0025

Adjusted R 2 0.215 0.210 0.213 0.208

Notes: The table shows the results from OLS regressions of ROA on all governance mechanismsalong with different combinations of exogenous control variables. The dependent variable in all four columns is ROA, which is the ratio of operating income to total assets (return on assets). BOARD-SIZE is the number of directors on the board of the company. OUTSIDER is measured by the per-

centage of board seats held by non-ofcers without relationship to the founding family (if any). LEVis computed as the ratio of total (non-equity) liabilities to total assets. OWNERSHIP is the percent-age of cumulated voting rights exercised by large investors with > 5% of voting rights. SIZE denotesthe natural logarithm of sales, and GROWTH is the average annual growth of sales over the pastthree years (19992001). RESTR is a dummy variable equal to 1 if the rm has different share cat-egories with different voting rights attached, and 0 otherwise. The sample contains 165 Swiss rmslisted on Swiss Exchange (SWX), excluding banks insurance and nancial services companies. AWald test is performed for the simultaneous signicance of all coefcients (except the constant andthe industry dummies). The numbers beneath the coefcients are probability values for two-sidedtests. The symbols ***, **, * denote statistical signicance at the 1%, 5 %, 10% level, respectively.


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on OWNERSHIP is signicant. BOARDSIZE , LEV and OUTSIDER are esti-mated insignicantly in the corresponding regressions, respectively.

VI. CONCLUSION

Boards of directors are an economic institution, which, in theory, helps to solvethe agency problems inherent in public corporations. While there is only lim-ited theoretical work, the empirical literature is well developed. Most previousstudies have focused on specic board characteristics, such as board composi-tion and board dynamics, and their relationship with rm valuation. Surpris-ingly, there has been relatively little work on the relationship between the sizeof boards and rm valuation. We contribute to this literature by exploringwhether board size constitutes an independent governance mechanism and isrelated to Tobins Q. This is an interesting research question with potentiallyimportant practical implications. Nevertheless, by focusing on board size as theonly governance mechanisms in isolation and ignoring that rms can choosefrom a wide menu of different governance mechanisms with possibly similar valuation effects, previous studies with mainly US evidence are clearly limited.Using a comprehensive set of companies listed at Swiss Exchange (SWX), our results support the notion that board size is indeed an independent governance

mechanism. In particular, board size is independent from board composition.However, in contrast to previous studies we do not nd a signicant relation-ship between board size and rm valuation, as measured by Tobins Q. This sug-gests that Swiss rms, on average, choose their number of board members justoptimally. In a simultaneous system of equations we carefully control for theendogeneity problems inherent in empirical studies on governance. Also incontrast to most of the literature, this empirical setup allows us to distinguish between equilibrium and out-of-equilibrium interpretations of estimation re-sults. Cross-sectional variations in board size to a large extent reect differ-ences in rms underlying environment, and not mistaken choices, whichshould be reversed. Accordingly, even though we nd that board size consti-tutes an independent corporate governance mechanism, any changes leave rmvaluation unaffected at best, but more probably lead to a decrease in Tobins Q.This is consistent with the observation that the average board size in our sampleof Swiss rms (6.59) is just below the optimal value of 78, as hypothesized by Lipton and Lorsch (1992) and Jensen (1993). The advantages of larger boards from increased management capacities may just offset the potential dis-advantages from coordination, communication, and decision-making prob-lems.


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SUMMARY

Using a simultaneous equations framework with a comprehensive set of publicly listed Swiss companies, our ndings suggest that the size of the board of directors is an independent corporate gov-ernance mechanism. This implies that any potential relationship between board size and rm valua-tion is indeed causal. However, in contrast to previous studies, we do not uncover a signicantrelationship between board size and rm valuation, which can be interpreted as support for the hypothesis of the existence of an optimal board size. On average, rms choose the number of boardmembers just optimally. This indicates that cross-sectional variations in board size to a large extentreect differences in rms underlying environment, and not mistaken choices.

ZUSAMMENFASSUNG

Die Ergebnisse der Schtzung eines simultanen Gleichungssystems mit einer reprsentativen Stich- probe brsengehandelter Schweizer Unternehmen zeigen, dass die Grsse des Verwaltungsrates ei-nen eigenstndigen Corporate Governance Mechanismus darstellt. Damit kann ein mglicher Zusam-menhang zwischen der Grsse des Verwaltungsrates und dem Unternehmenswert als kausalinterpretiert werden. Die empirischen Ergebnisse zeigen aber keine Evidenz fr einen derartigen Zu-sammenhang, was die Hypothese einer optimalen Grsse des Verwaltungsrates sttzt. Im Durch-

schnitt weist der Verwaltungsrat Schweizer Unternehmen die optimale Grsse auf. Die Unterschiedein der Grsse der Verwaltungsrte der Stichprobenunternehmen knnen zum grossen Teil durch un-ternehmensspezische Einussgrssen erklrt werden, und sind nicht auf eine falsche Besetzung desVerwaltungsrates zurckzufhren.

RSUM

En utilisant un systme dquations simultan, estim sur lensemble des entreprises inscrites la bourse suisse, nos rsultats montrent que la taille du conseil dadministration rsulte dun mcanismeindpendant de gouvernance dentreprise. Ceci implique quil existe vritablement un lien causal en-tre la taille du conseil dadministration et la valeur de lentreprise. Nanmoins, contrairement auxtudes prcdentes, nous navons pas dcouvert de relations signicatives entre ces deux lments,ce que lon peut interprter comme support pour lhypothse de lexistence dune grandeur optimaledu conseil dadministration. Le nombre de membres du conseil dadministration est en moyennechoisi de manire optimale. Ceci indique que la variation en coupe transversale de la taille du conseildadministration rete en majeure partie des diffrences dans lenvironnement de chaque entreprise plutt que des mauvaises dcisions.

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