Chapter 3: Block Investment and Partial Benefits of Corporate Control: The Case of Belgium

Chapter 3:

Block Investment and Partial Benefits of Corporate Control: The Case of Belgium

1. Introduction

What are the determinants of the shareholder structure of a listed company? Are there rules robust enough to remain valid across different systems of corporate governance?

Continental Europe and Belgium in particular belong to Corporate Governance systems that are quite different from the one in place in the United States to many extents. In Continental Europe, ownership is more concentrated and less institutionalised, firms are smaller, managers are less powerful compared to large shareholders and minority shareholders globally less protected. In both systems, descriptive data on ownership structure are difficult to apprehend and to summarise and the internal logic driving the figures is not obvious to identify. Does it exist, and is it the same for both continents?

The work of Zwiebel (1995), “Block investment and partial benefits of corporate control”, brings a partial answer to the question. The author develops a theoretical model using game theory to show the dynamics of coalitions among shareholders. We use here detailed databases presented in chapter 2 on direct and ultimate ownership of listed Belgian companies to assess the validity of this model. This way, we can underline, on sound empirical bases, the common points and the differences between Continental and Anglo- Saxon Corporate Governance in the relations between shareholders of public companies.

The model tends to explain why, according to US data, many investors choose to hold significant blocks of equity in the same firm, despite theoretical recommendations for diversification. The author elaborates a co-operative game where small shareholders of a firm may decide to join together in order to build controlling coalitions, conferring to their members partial benefits of control.

This has three implications in terms of shareholder structure:

1) the largest shareholders tend to “create their own space”, their presence dissuade other large shareholders from investing in the firm,

2) the shareholder structure in corporations will exhibit a clientele effect among block investors : the bigger a shareholder is, the fewer smaller shareholders there will be around him in the same firm, and firms without a large leading shareholder tend to have a greater number of moderate size shareholders. More precisely, the model predicts that there are, in equilibrium, three shareholders structures : (a) firms with one very large shareholder and no smaller blockholder, (b) firms with one large shareholder and many smaller block shareholders, (c) firms having no dominant shareholder but numerous small block shareholders,

3) in the same idea, the third implication of the model is that there is a threshold size above

which a large shareholder is not challenged for control within the firm.

After confronting Zwiebel’s tests to Belgian data, we develop a specific methodology to assess the extent of the applicability of the model to the Belgian case. We test the statement for direct ownership data, ultimate ownership data and ultimate control data. Our results allow us to discuss the common points as well as the differences existing between very different Corporate Governance systems and contingent to this, its limitations.

The paper structures as follows: section 2 places the paper in its context by giving a short overview of the literature on control contests and on benefits of control. Section 3 reviews the main differences between Continental and Anglo-Saxon corporate governance systems.

Section 4 underlines the innovating points of the original paper, it details the theoretical findings and summarises the examples and empirical evidence shown by the author. Section 5 starts the sections about Belgium with some descriptive figures about Belgian ownership data. Section 6 replicates for Belgium the empirical testing run by Zwiebel with US data, before developing more specific tests on the theory. Section 7 discusses the merits and the limitations of the model. Section 8 concludes.

2. Review of the Literature

The paper of Zwiebel is one of the first to underline the notion of partial benefits of control.

The author points out a third way between controlling the firm entirely with the absolute majority, and having nothing at all when one does not control 50% of the votes. Before him, a vast literature has been dedicated to control contests seen as a battle between an incumbent and a potential raider.

In that field, one of the first and the most famous references is the Grossman-Hart (1980) contribution. The hypothesis made by the model is that the ownership structure is so dispersed that no shareholder has enough power to individually influence the outcome of the control contest. The main innovation of the authors is the notion of the free-rider problem. In case of a takeover, the small shareholders refuse to sell their shares to the raider at a price below the future expected value of the firm, in case the takeover succeeds. Acting this way, small shareholders take away all the potential profit from the raider, deterring him from undertaking a takeover. By this, the authors show how firms that are not run in the interest of the shareholders may however not be vulnerable to a takeover bid.

Following this contribution, several papers have been attached to the resolution of the free rider problem. Among them, Grossman and Hart (1980), of course, who propose to write a clause in the corporate charter excluding, in case of a successful takeover attempt, the non- tendering shareholders from the benefits of the corporation, in the years following the takeover. Later, Shleifer and Vishny (1986) examine the possibility for the raider to benefit from a price increase on the shares bought before the start of the takeover attempt.

Besides this aspect of the problem, many authors consider the existence of private benefits of control to the raider that might be large enough to compensate the free rider problem.

Grossman and Hart (1988) demonstrate the superiority of the one share - one vote rule that

maximises the benefits of control to securityholders relative to the benefits of the controlling

party. It then encourages the selection of a performing management team. However, the one

share - one vote rule might not be optimal in case of takeover battles. When there are private

benefits both on the incumbent side and on the raider side, other voting structures might

then extract more surpluses from the private benefits. Empirically, we observe in fact

deviations from the one share - one vote rule (like dual classes of shares) when private

benefits are high.

Harris and Raviv (1988) concentrate on the determinants of the corporate takeover methods and their price effects depending on the outcome. The authors concentrate on capital structure changes (increasing the firm leverage) as a resistance strategy to hostile bids. The authors show for example that the stock price of the targeted firm appreciates more in case of a successful tender offer than in case of a proxy contest. In case of a tender offer however, there is no price change if the offer appears to be unsuccessful, while stock price appreciation following an unsuccessful proxy contest is strictly positive. The intuition for these results follows from the idea that the appearance of a raider is a positive signal for investors because it increases the probability that a more efficient management team will take control, leading to an increasing value of the firm. The price increase that accompanies a takeover attempt thus depends on two factors: the magnitude of the potential improvement in management if a change occurs, and the likelihood of such a change.

Based on a famous hostile takeover that took place in Belgium in 1988, the paper of Dewatripont (1993) analyses the strategy of the “leading shareholder” – control without majority ownership – for a potential takeover bidder. The trade-off in such a strategy is, if it succeeds, to allow the leading shareholder to enjoy the benefits of control, without having to buy 50% of the shares. On the other hand, the leading shareholder bears the risk of losing control if another investor can successfully acquire 50% of the company. The model analyses the benefits and costs of control and characterises stock price dynamics. A first main result of the model is to show that, when the raider buys more shares initially, it induces him to behave more aggressively in the contest, trying to deter the white knight (a rival company competing for control) from starting the battle. The raider faces the trade-off between the cost of buying more shares and the cost of facing a rival. The second main result shows that, under the assumption of rational expectations, small shareholders tend to focus on the gains in security benefits versus private benefit extraction. They compare each competitor’s ability to generate security benefits to the amount of private benefit they could extract during the contest.

Besides the attention given in the theoretical literature to private benefits of control, other empirical papers are devoted more precisely on the sources of these benefits. These can take very different forms, like synergies obtainable through mergers, favours conferred by a firm, access to inside information, utility derived directly from power of control, …

In the field of empirical research for the existence of benefits of control, we can mention two event studies run by Barclay and Holderness (1989 and 1991). In a first analysis, Barclay and Holderness (1989) find that in private negotiations large blocks of stock trade at a premium to the exchange price. The authors analyse the pricing of 63 block trades between 1978 and 1982 involving at least 5% of the common stock of NYSE or Amex corporations. They explain the premiums paid - which average 20 percent - reflect the value of private benefits that accrue exclusively to the blockholder because of his voting power. Authors show that the premiums increase with firm size, fractional ownership, and firm performance. Individuals pay larger premiums for firms with greater leverage, lower stock-return variance and larger cash holdings. Regression results estimate private benefits of control up to 4% of the total value of equity.

In a following article (1991), the authors examine 106 negotiated trades of at least 5% of the common stock of NYSE over the same period (1978-1982). Their primary objective is to assess the impact of these trades on the value of the firms involved. Secondly, the authors also investigate the impact of the blockholders ‘activism after the trade on the value of the firm.

They find that the initial public announcement of the negotiated block trades is associated

with average abnormal returns on the stock price of approximately 16%. The increases tend to be larger when the control passes to the new blockholder. When the firm is not acquired, stock price increases with the announcement of the trade, then decline gradually over the 40 following days. Even with the decline, average cumulative abnormal returns are about 5.6%.

Two points of interest of the paper are, first, the identification of negotiated block trades of common stock as corporate control events and, second, empirical evidence that the skills and expertise of large-block shareholders – and not just the ownership concentration – can affect firm value.

A few years later, Zingales (1994) examines, on the Milan stock exchange, the very large premiums associated to voting stocks. The author tries to determine the value attributed to voting rights that is related both to the size of the private benefits and to the degree of competition in the market for corporate control. To measure the strategic value of voting rights in the hands of small shareholders, Zingales uses (just as Zwiebel) the Shapley value of small shareholders’ votes. The Shapley value measures the probability that a vote not held by holders of large blocks is pivotal. The variable turns out to be the best proxy for the control value of these votes. Results suggest that, in Italy, the value of controlling a corporation is well above 60 percent of the value of the equity. As an explanation for so high private benefits, the author justifies the fact that the Italian legal system is very inefficient in preventing exploitation of a control position and, in particular, the dilution of minority property rights.

In a research applied this time to the United States, Zingales(1995) develops and tests a model that explains to what extent and when the value of private benefits is reflected in the exchange price of a vote. He shows that the value of a vote is determined by two factors: the likelihood that the vote will be pivotal in a contest for control and the price it will fetch in case of such a contest. The Shapley value is here again used as a proxy for the marginal value of a vote in a control contest. Regression results show an estimated coefficient of 4.2%

representing the relative size of the private benefits of control, very similar to Barclay and Holderness’ (1989) results (4%) but substantially lower than in other countries and Italy in particular as shown in Zingales (1994). One possible source of private benefits of control is abnormal salaries that controlling shareholders might pay to themselves. Results show that the value of this extra compensation is reflected in the market price of vote and this specification can explain 30% of the overall variability in the voting premiums. Finally, the author argues that voting rights are less valuable in the United States than in other countries because the private benefits are smaller, not because ownership is less concentrated.

Finally, related to these topics, a last type of empirical papers are those looking for evidence that blockholders effectively pursue private benefits. During control contests, the opponents actively recruit these active blockholders.

The contribution of Brickley, Lease and Smith (1988) display empirical evidence showing

that institutional shareholders and block shareholders vote more actively on antitakeover

amendments than nonblockholders, and that opposition by institutions is greater when the

proposal appears to harm shareholders. Interestingly, the authors find significant differences

across the various types of institutional investors. In particular, evidence suggest that the

institutional investors that tend to build business ties with the firms in which they invest

(like banks or insurance companies) are more likely to vote in the sense of the management

than other institutional investors.

If related to many extends to this literature, Zwiebel’s paper is innovating in several ways as we will review in section 4. Testing it, as it is done here, is a step further in this new direction of research on the determinants of the ownership structure of public companies.

3. The US and Continental Europe: Review of Two Corporate Governance Systems

Anglo-Saxon countries and Continental Europe differ widely in terms of Corporate Governance systems. Besides the traditional question of ownership concentration, the roots of the systems are different since the two groups of countries belong to different traditions of law. To this end, one can remind the relevant distinction made in their study by La Porta et al. (1996), between countries having a tradition of common law, like Anglo-Saxon countries, and countries having a tradition of civil law, like Continental Europe:

In general, commercial laws come from two broad traditions: common law and civil law. Legal rules of civil law countries are derived from Roman Law, and “are

conceived as rules of conduct intimately linked to ideas of justice and morality (David and Briereley, 1985, p22). These rules are usually developed by legal scholars, and incorporated into civil codes.

In contrast, common law is British origin, and was “formed primarily by judges who tried to resolve specific disputes” (David and Briereley, 1985, p24). Because scholars play little role in the development of common law and the law develops through precedents, it tends to be less abstract than civil law (David and Briereley, 1985, p24).

Furthermore, the number of major civil law traditions or families that modern commercial laws originate from is very small, 3 to be exact. These families originate in the French Civil Code of 1804, the German Civil Code of 1896, and, in the case of Scandinavian countries, in Nordic codes dating back to the 18

century.

By looking at the differences in laws between countries, the authors find that the most striking differences are between common law countries (like US, UK) and French Civil Code countries (including Belgium). While common law countries give both shareholders and creditors strongest protections, the second group of countries are those who protect investors the least.

The authors use several dummy variables reflecting investor protection, these are : - One share-one vote : Belgium : 0, US : 0

- Proxy by mail : Belgium : 0, US : 1

- Shares blocked before meeting : Belgium : 1, US : 0

- Cumulative voting (equals one if law allows shareholders to cast all of their votes for one candidate standing for election to the board of directors) : Belgium : 0, US : 1

- Oppressed minorities mechanism (equals one if law grants minority shareholders either a juridical venue to challenge the management decisions or the right to set out of the company when they object to fundamental changes) : Belgium : 0, US : 1

- Percentage of share capital to call an extraordinary shareholder meeting (equals one if the needed percentage if below 10%) : Belgium : 0, US : 1

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La Porta et al., 1996, p 4.

- Antidirectors rights (index ranging from 0 to 5, formed by adding the values taken by the five preceding dummies) : Belgium : 0, US : 5

- Mandatory dividends: Belgium : 0, US : 0

Besides, in the field of investor protection, there are some statements in the Belgian law guaranteeing the equality of treatments between all the shareholders of a firm whatever their size, like : the same rights attached to all shares (same value, one vote per share, except for the non-voting class); the right to attend the General Meeting and to obtain the minutes; the equality of treatment in case of take-over or in case of large block transaction (all shareholders should be offered the same price for their shares).

However, these rules are (or were) not always respected in practice. More generally, in large transactions, minority shareholders are offered prices below the fair value, and large restructuring plans of companies often neglect the interest of minority shareholders.

This is why “Déminor” was founded in Belgium in 1990. The objectives of this company are:

- to create value for institutional, private or corporate shareholders by assisting them in managing their minority stakes

- to promote higher standards of transparency and accountability between corporations, management and shareholders

- to ensure fair and equal treatment of shareholders - to maximise the long term value of minority stake.

More specifically, Déminor advises and assists investors on a case by case basis when dealing with important shareholder or voting issues in listed companies, such as investment or divestment decision, financial restructuring plans, but also discharge of management, approval of accounts, dividend policy, etc. When appropriate, Déminor also forms federations of institutional or private investors to increase their representative interest or voting rights. Déminor is active in Benelux countries and in France.

Starting from the statement of reduced investor protection in Continental Europe compared to the US, La Porta et al. (1996) look for some possible adaptations to the lack of investors’

protection in civil law countries compared to common law countries. Their most interesting result concerns ownership concentration. The authors find a strong negative correlation between concentration of ownership and the quality of legal protection of investors in a country. Everything is as if, when law does not protect them, shareholders have to be large and powerful to balance the power of the management and extract payments from them.

Data thus confirm the idea that legal systems matter for corporate governance.

Indeed, data show that US ownership is far less concentrated than ownership in Belgium or, more generally, than in Continental Europe. On that matter, table 12 is a summary of the international comparisons made by La Porta et al. (1996) over the sum of stakes owned by the three largest shareholders in large private firms across various countries.

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Déminor web site : www.deminor.be

Table 12 Ownership Concentration in Listed Firms Country C3 - Ten largest private firms

Mean Median

Belgium 0.54 0.62

Continental Europe (average)

0.45 0.49

UK 0.19 0.15

US 0.20 0.12

Although these very aggregated data may be not perfect in the methodology used to determine them, they still give a very good idea of the levels of ownership concentration in the different groups of countries.

More specifically, in the comparison between the United States and Belgium, one can compare the following set of figures that provide a more precise picture of the ownership structure in both countries

. One can note that:

- The median of the largest direct stake in a listed company is around 46% in Belgium, while it is around 15% in the United States.

- The three largest owners of listed Belgium companies control on average almost 60% of the votes, while the three largest owners of listed US companies control on average around 32% of the votes.

In a recent paper, Zingales

found very similar figures. His calculations show an average size of 32.3% for the largest shareholder in US companies and a voting power of 47.2 percent controlled by the five largest shareholders, against 62.2% in Belgium.

The concentration ratios here are higher than those provided by La Porta et al. (1996). This is due to the larger sample of companies taken into account in the statistics. La Porta et al.

(1996) took only the values for the 10 largest private firms, while Becht includes the data for all listed companies (6559 listed in the US) and Zingales took a sample of 396 AMEX and NYSE companies.

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Tables for Belgium come from « Ownership and Control in Belgium - European Corporate

Governance Network », M. Becht, Chapelle, A. Report to the European Commission, June 1997. Tables for the US come from BECHT, M. (1998), “Beneficial Ownership of Listed Companies in the United States” in Ownership and Control : A European Perspective, Oxford University Press (forthcoming).

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ZINGALES, L. (1995), “What Determines The Value of Corporate Votes?”, Quarterly Journal of

Economics, 110(4), November,1047-1073

F ^IGURE 9. D ^IRECT S ^TAKES B ^Y R ^{ANK OF} S ^{TAKE FOR} A ^LL L ^ISTED C ^OMPANIES - B ^ELGIUM

5.2 0.0 0.0 0.0 0.0

46.4

10.0 5.3 1.1 0.1

44.8

12.8 6.1 2.0 0.3

99.8

44.1

20.4

11.8

1.1 0

20 40 60 80 100 120

Largest Stake 2nd 3rd 4-10th >10

Minimum Median Mean Maximum

Note: For each of the 135 notified companies the stakes were ranked. For blocks of equal size (ties) the average rank was assigned. This was never the case for the largest stake. For each category the minimum, median, mean and maximum were computed for all stakes in the category.

F IGURE 10. B LOCKS B Y R ANK OF B LOCKS FOR A LL L ISTED C OMPANIES – U NITED S TATES

0.05 0.001 0 0.001 0.08

15.1 9.02 6.99

1.74 0.3

22.77

11.26 7.95

2.08 0.3

99.99

49.99

33.29

5.72 0.6

0 20 40 60 80 100 120

Largest Stake 2nd 3rd 4-10th >10

Minimum Median Mean Maximum

T ABLE 13. S UMMARY S TATISTICS AND C ORRELATION OF C1, C3, C5, C20 AND C

-

B ELGIUM

Measure Mean Std. Dev. Min. Max. C1 C3 C5 C20 C

C1 44.75 20.88 5.22 99.76 1

C3 59.28 20.10 15.25 99.97 0.8050 1

C5 62.25 19.42 15.76 99.97 0.7314 0.9770 1

C20 63.75 19.20 15.76 99.97 0.6777 0.9380 0.9826 1

C

63.83 19.18 15.76 99.97 0.6724 0.9337 0.9788 0.9993 1

T ^ABLE 14. S ^UMMARY S TATISTICS AND C ORRELATION OF C1, C3, C5, C20 ^AND C

- U ^NITED S TATES

Measure Mean Std. Dev. Min. Max. C1 C3 C5 C20 C

C1 22.75 19.48 0.05 99.99 1

C3 32.26 23.85 0.05 99.99 0.8541 1

C5 39.80 26.47 0.05 99.99 0.8155 0.8932 1

C20 43.60 28.95 0.05 99.99 0.7437 0.7804 0.9313 1 C

43.60 28.95 0.05 99.99 0.7437 0.7804 0.9313 1 1

The first 4 columns show the mean, standard deviation, minimum and maximum of the five concentration measures for 5% beneficial owner blocks. The last five columns show a correlation matrix for the five measures. If there were just one direct stake, the correlation between C1 and all other measures would be 1.

To summarise, the two countries belong to very different systems of Corporate Governance.

Ownership in the US is dispersed, institutionalised through pension funds, legalistic in the protection of investors, while Belgium has a highly concentrated ownership like most countries in Continental Europe, there are few institutions among shareholders and legal protection is rather weak.

4. The Theoretical Contribution

Looking for the determinants of investors’behaviour, Zwiebel (1995) develops a theoretical model using game theory to explain why many investors choose to hold significant blocks of equity in the same firm, despite theoretical recommendations for diversification. The author elaborates a co-operative game where small shareholders of a firm may decide to join together in order to build controlling coalitions, conferring to their members partial benefits of control.

The model shows that the largest shareholders tend to “create their own space”; their presence seems to dissuade other large shareholders from investing in their firm. Similarly, the larger the leading shareholder in a firm, the fewer smaller block shareholders are present, and firms without a large leading shareholder tend to have a greater number of moderate sized shareholders.

One of the first motivations of the paper comes from the empirical observation that a great majority of blockholders holds blocks of shares that are significantly smaller than the majority of votes. The observation had already been made by Shleifer and Vishny (1986) who noted that, among US Fortune 500 firms in 1980, the average percentage of the largest shareholder is around 15%. In fact, US data show that many firms do not have a majority shareholder or even a dominant shareholder for the presence of which, however, the hypothesis is generally made in the literature. On the other hand, when one considers the blockholders globally, their hold together a significant fraction of the voting rights in the firm

.

Parallel to this, the author observes that the existing literature does not take into account the reduced size of the blockholder in reality. It focuses instead in details on the analysis and the

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From the data derived from the Fortune 500, 1981: the median largest shareholder holds only about

9%, and the mean largest shareholder 15.4%, whereas the mean top 5 shareholders hold 28.8%.

understanding of the mechanisms of the market for corporate control, and on the reasons motivating the direct opponents for corporate control.

For example, Harris and Raviv (1988) in their article do not take into account a possible co- ordination between the opponents in a control contest, between the raider and any one of the shareholders. But if one makes such a co-operation possible, it could result in large gains for both parties.

So, this paper departs from the previous literature by considering an active role played by block shareholders as a central component in determining corporate control. At a lower level, but according to the same principle, the active role of individual shareholders in controlling coalitions incite them in turn to own blocks.

Finally, most of the papers devoted to private benefits of control consider them as indivisible. However, looking at the various sources of private benefits (synergies through mergers, access to inside information, etc.), these are likely to be shared among several individuals. By considering these benefits as divisible, Zwiebel can take a very different approach from the previous theoretical literature. This leads him to presume that the degree of control an investor derives from a block will depend on the potentiality of this block in forming controlling coalitions. Illustrating the links between block holders in function of their strategic importance, the author derives several interesting predictions that are detailed below. We will submit those predictions to empirical testing in the sections to come.

4.1. The Model

It is a general model to analyse strategic investment decisions when control benefits are divisible. The equilibria of the game found allow predicting three types in firms’

shareholders structure. Brief statistical tests on US data tend to confirm the findings.

In the model, the division of control benefits corresponds to the shareholder’s strategic importance in forming winning coalitions. For example, a shareholder, even small, but having a large strategic importance because he is pivotal in the distribution of votes will have large potential benefits of control. To represent this division of control benefits, the author employs the Shapley values of a normalised co-operative majority game. The Shapley value of votes held by small shareholders is the main proxy for the control value of these votes. This can be thought of as the probability that those votes are pivotal in a random coalition formation.

Simple numeric examples are the best way to illustrate what the Shapley value means in practice. Since it is a probability measure, the sum of the Shapley values attached to all shareholders of a firm must be equal to one.

Consider a firm counting only 3 shareholders owning respectively 40%, 40%, and 10% of the voting shares. The Shapley value of each of them is 1/3. Indeed, each shareholder has an equal probability of forming a controlling coalition with one of the other shareholders.

Consider now a firm in which the three shareholders own respectively 55%, 35%, and 10% of

the shares. In that case, the Shapley value yields 1 for the largest shareholder, and zero for

the two others. Since the largest shareholder has the absolute majority of the votes already,

there is no hope for the two others to be part of a controlling coalition.

The model considers an economy with :

• J identical firms, each with a single class of equity.

• Total private benefits of control in each firm are 1.

To represent the different size of investors, two types of risk-neutral are modelled:

• type 1: N shareholders of size n, who are very large investors, capable of dominating one firm ;

• type 2: M shareholders of size m, medium size investors, large enough to hold significant blocks and to participate in coalitions, but not large enough to dominate a firm.

All shares not held by investors are supposed to be in the hands of liquidity traders who are too small individually to acquire blocks and to obtain any benefits of control. Some of these traders vote randomly, thereby creating noise in the outcome of close control contests and smoothing the value of control to large shareholders.

The game takes place as follows. Shareholders first choose where to invest, and then, shareholders of each firm gather at the annual meeting. Prior to the vote, shareholders try to form winning coalitions. Non-attendees may vote by proxy but cannot participate in the coalition formation. In order to capture the notion that small blocks are more liquid than large blocks, it is assumed that large investors (type1) allocate their wealth before medium- size investors (type2). Attention is then restricted to pure-strategy subgame-perfect equilibria (PSSPE), as only equilibria in pure strategies for type 2 shareholders will be stable in the sense that none of them would want to re-invest. Looking at the market equilibrium, the author derives several propositions.

The resolution of this game leads to proposition 1, stating that there are several equilibria in pure strategy (PSSPE) that have a form depending on the relative size s between large and small shareholders (s = n/m).

Proposition 1 leads to several intuitive results from which the following propositions are derived.

According to the timing of the game, players act as follows:

− first, large shareholders (type1) invest all their wealth in one firm;

− second, medium-size shareholders (type 2) react also by investing all wealth in one firm;

− third, type 2 shareholders distribute themselves across all firms without type 1 shareholders and challenge a subset of firms with type 1 shareholders, in a manner that equates the benefits they receive from all firms in which they invest.

In equilibrium, there are three types of firms:

ƒ firms with one dominant shareholder uncontested by any small blockholder,

ƒ firms with one large shareholder who is contested by smaller blockholders,

ƒ firms having no dominant shareholders but numerous small blockholders.

Since the number of small shareholders needed to challenge a large shareholder increases with the size of the large shareholder compared to the small ones, there will be less firms that can be challenged in equilibrium as the difference in size between large and small investors grows.

It follows that, when s exceeds a limit s*, firms dominated by a type1 (large) shareholder are

not challenged in equilibrium. Since they are not challenged beyond this size s*, type 1

shareholders cease to invest all their wealth in one firm. Instead, they will invest the remaining of their wealth in another firm, in which they create a stake. Under these conditions one understands easily that, above the limit s*, all benefits of control go to type 1 shareholders in firms that are not challenged.

The benefits curve to type 2 shareholders is different according to the presence or not of a dominant shareholder in the firm. In case of absence of a dominant shareholder, private benefits of each type 2 investor is a decreasing function of the number of investors in the firms. In case of a presence of one dominant shareholder, control benefits of type 2 investors become positive as soon as the number of type 2 investors in the firms exceeds (s-1). The benefits curve increases rapidly to reach a maximum (depending on the value of s), and starts to decrease slowly as the number of type 2 investors grows in the firm. The intuition is that type 2 shareholders need to from a coalition to better contest the dominant, but, once they have reach their objective, they also must split these joint benefits among more of themselves.

S-1

No dominant shareholder

One dominant shareholder

C. be ne fits of ty pe 2 in ve sto rs

Nbr of type 2 investors in firm

So now, one can understand that, among all equilibria defined by proposition 1, the most desirable one for type 2 shareholders is the one where they challenge the maximal number of dominant shareholders. This is the outcome that would be obtained if type 2 shareholders co-ordinate their actions.

More generally, type 2 shareholders do better, and type 1 shareholders worse, in equilibria with more type 1 shareholders challenged.

Proposition 3 states that as type 1 shareholders’ size approaches that of type 2 (s tends to 1), type 2 shareholders tend to distribute themselves symmetrically across all firms they challenge. In particular, when s=1, (all shareholders are identical in size), all firms have the same number of shareholders. The equilibrium distributions of type 2 shareholders are unaffected if parameters are proportionally scaled up or down.

Alternatively, as the difference in size between large and smaller shareholders grows (s rises):

− type 1 (large) shareholders do better: they gather more benefits of control and they are challenged in a smaller cases.

− type 2 (smaller) shareholders do worse: for symmetric reasons.

− the number of type 2 shareholders challenging a large shareholder falls, consequently to

proposition 1 : the presence of a large shareholder dissuade smaller shareholders from

investing in the firm.

− the number of type 2 shareholders in any firm without a large shareholder rises : they are relegated in firms without dominant shareholders. Since they are more numerous in each firm, they have to split control benefits in more parts.

To conclude this section, it is useful to remind the main results coming from the resolution of the game modelled:

* The shareholdings structure will exhibit a clientele effect. In other words, the larger the first investor is, the smaller the other shareholders will be in the firm. In particular, there are three types of firms in equilibrium:

− firms with one dominant shareholder uncontested by any small blockholder,

− firms with one large shareholder who is contested by smaller blockholders,

− firms having no dominant shareholders but numerous small blockholders.

* There is a threshold size s* above which a large shareholder is not challenged for control within the firm.

* The largest shareholders tend to “create their own space”, their presence dissuade other large shareholders from investing in the firm.

So, according to the last result, the type of ownership structure that is excluded is the one where several large shareholders cohabit in one firm.

(1) 4.2. Example and Empirical Evidence

A following section of the theoretical paper considers a few numerical examples using fictive data. One example is enough here to understand the mechanism of the model.

Consider an economy with 3 firms, 2 large block shareholders, and 60 small block shareholders. Large shareholders are five times larger than small ones (s=5).

In all pure-strategy subgame-perfect equilibria (PSSPE), each of the two large block shareholders allocate all their wealth to separate firms, namely firms 1 and 2, without loss of generality. But, as far as type 2 shareholders are concerned, there are three PSSPE :

1) 60 type 2 shareholders in firm 3 and no large shareholder challenged. Expected benefits of control are distributed as follow : benefits to type 1 investors : φ

= 1 ; benefits to type 2 investors : φ

= 1/60 = 0.017

2) 27.1 type 2 shareholders in firm 1 or 2 and 32.9 in firm 3; one large shareholder is challenged. Expected benefits of control are: benefits to type 2 investors : φ

= 1/32.9 = 0.031; benefits to type 1 investors φ

= 1- ((27.1 / 2)*0.031) = 0.589 ;

3) 17.9 type 2 shareholders in both firms 1 and 2 and 24.2 in firm 3, both large shareholders are challenged. Expected benefits of control are: φ

= 1- (17.9*0.041) = 0.265; φ

= 1/24.2 = 0.041.

The last equilibrium is the best for type 2 shareholders and it survives refinement chosen to capture the dynamic structure of the game

. Note that with s=10, there is no longer an equilibrium where both large shareholders are challenged.

53

In particular, this equilibrium is immune to all Pareto-improving deviations by any coalition that

are in turn immune to Pareto-improving counter-deviations in a future period.

In order to display some empirical evidence confirming his theoretical predictions, the author briefly applies the model to US data, for the 456 firms reported in 1981 CDE Stock Ownership Directory: Fortune 500.

To test the first implication according to which largest shareholders tend to “create their own space”, Zwiebel tests whether there is a significant difference between the distributions of blocks of shares above 10% and 20% respectively in each firm of the US top 500 compared to random distributions, as shown in Table 1.

For the random allocation, each large block is taken to have an identical chance of being allocated in any firm.

Table 1 Distribution of Large Block Shareholders: Actual versus Random Distributions Blocks > 10%

Number of blocks in Firm Number of Firms (actual) Number of Firms Under Random Choice

1 178 143.7

2 28 38.7

3 4 6.9

4 0 0.9

5 0 0.1

Goodness of fit, χ

(3) = 16.14 (0.001)

Blocks > 20%

Number of blocks in Firm Number of Firms (actual) Number of Firms Under Random Choice

1 117 94.1

2 3 12.6

3 0 1.1

4 0 0.1

Goodness of fit, χ

(3) = 14.51 (0.003)

Goodness of Fit tests show a significant difference at 0.001 level between the real distributions and the random distributions, confirming the theory. The great majority of US firms count only one or two large shareholders.

To test the clientele effect, the author runs an OLS regression of the number of 1% blocks of shares on the size of the largest shareholder and a constant. The regression coefficient found is significantly negative at a 0.001 level. This confirms proposition 2 stating that the largest the first shareholder, the fewer the other shareholders of the firm.

5. The Case of Belgium: Data for Listed Companies

Based on this model identifying the possible underlying determinants of a shareholding structure seeming to apply to US companies, it should be interesting to check whether this type of model suits to a country that belongs to another Corporate Governance system like Belgium does.

To test the validity of the model on Belgian companies, we will use the data bases displayed

in chapter 2 on the shareholdings of listed Belgian companies by the end of 1995. We will test

the statements both for direct and ultimate ownership data. We will then apply the same

methodology to the ultimate control data, coming from the matrix of control stakes built in

the last chapter and where 50.01% of the votes equals 100% of control. Symmetrically, less than 50.0% of the votes equals to 0 where there is already a shareholder having the absolute majority in the firm. This will allow us to test the distribution of shareholders in terms of control power and not just in terms of ownership size.

Recall that ultimate ownership data are data on shareholders sitting at the top of the ownership pyramids. Direct ownership come from the Transparency Law that demands to shareholders holding more than 5% of the votes in a listed company (either directly or indirectly) to make themselves known to the Markets Authorities. Indirect ownership come from specific CD-ROMs. Ultimate ownership has then been computed from extensive direct ownership links, using an input-output matrix methodology developed by Brioschi et al.

(1989).

Ownership data can be presented in many different ways. Our choice is here to display the data in the same way as they will be tested. Direct ownership and ultimate ownership data are presented successively. For each type of ownership data, firms are divided into categories according to the size of the largest shareholder of the firm in terms of percentage of voting rights

. The thresholds defining the categories correspond to legal threshold of votes.

5.1. Direct Ownership Data

For direct ownership, categories are delimited by 25% (1

blocking minority), 33% (threshold size above which a full takeover offer is mandatory; 33% of the votes is also a 2d blocking minority level), 50% (simple majority), 66% (qualified majority (1)), 75% (qualified majority (2)). Qualified majorities are required to take some important decisions at the General Assembly, like changing the Acts of Incorporation, or raising the capital.

In each category, four variables are defined, characterising the ownership structure of the firm: (1) the size of the largest shareholder, (2) the size of the second largest shareholder, (3) the number of other shareholders (largest shareholder excepted), and (4) the average size of these other shareholders.

Table 2 Direct Ownership Data

Category 1 Category 2 Category 3 Category 4 Category 5 Category 6 Largest owner 0 % – 25% 25 % - 33% 33% - 50% 50% - 66% 66% - 75% 75% - 100%

1

owner % 16.8 27.8 41.8 55.2 69.8 86.4

2d owner % 9.6 15.6 15.2 8.2 4.4 2.2

Size others % 5.0 8.1 8.3 5.7 2.2 2.2

# others 9.0 6.0 4.4 3.1 2.4 0.4

# firms 24 20 33 37 9 12

54

See chapter 2 for details.

55

There will be only 135 listed firms taken into account here for the categories. For the five others left

indeed, there is no ownership declaration registered since there are no shareholder controlling more

than 5% of the votes.

Figure 1. Direct Ownership Data per Firm Category

Synthetic graph : direct shareholdings

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00

25%

Category 1

33%

Category 2

50%

Category 3

66%

Category 4

75%

Category 5

100%

Category 6

act-max 2d-act nbr-oth avg-oth

Before any statistical analysis of significance, this synthetic graph already seems to go in the sense of Zwiebel’s results. It shows that all the variables representing the size and the number of the other shareholders than the largest one decrease as the size of the largest shareholder increases, seeming to confirm the clientele effect.

For the last two categories, the dominant shareholder is almost the only one left in the shareholder structure of the firm. For smaller dominant shareholders however, such as in categories 2 and 3, there does not seem to be much difference between the residual structures. Interestingly, although the number of shareholders constantly decreases as the size of the dominant shareholder increases, it is not the case of the second largest shareholder: this tends to increase in size as long as the dominant shareholder remains below 33% of the votes. We can imagine that, up to a certain point, the two largest shareholders join to form a controlling coalition. In category 3 for instance, the sum of the average size of shareholder 1 and shareholder 2 exceeds 50% of the votes. Beyond this point, the largest shareholder controls the firm alone and the size of the other shareholders neatly decreases.

This particular case of collusion seems however to contradict Zwiebel’s third result stating that large shareholders “create their own space”, deterring other large shareholders from investing in the firm.

5.2. Ultimate Ownership Data

For ultimate ownership data, there is an additional category at 10% of voting rights. Ten

percent of the votes do not correspond to any legal threshold, however, it helps clarifying the

data since there are many small size blocks among ultimate owners. Besides, we merged the

last two categories (largest owner above 66% and 75%), otherwise the number of firms in

each category would have been too reduced to make relevant tests.

Table 3 Ultimate Ownership Data

Category 1 Category 2 Category 3 Category 4 Category 5 Category 6 Largest owner 0 % – 10% 10% -

25% 25% -

33% 33% -

50% 50% -

66% 66% - 100%

1

owner % 5.6 16.2 28.8 42.8 55.8 81.3

2d owner % 3.6 6.7 10.3 8.8 5.4 2.9

Size others % 1.2 2.6 5.2 6.7 3.8 2.2

# others 23.4 12.3 6.5 4.8 2.8 1.4

# firms 23 47 17 17 17 14

Figure 2. Ultimate Ownership Data per Firm Category

Synthetic Graph : Ultimate Ownership

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00

10% Category 1 25% Category 2 33% Category 3 50% Category 4 50% Category 5 66% Category 6

Act-max 2d-act Avge others nbr Others

Even more than the one presented with direct ownership data, this synthetic figure displays trends than seem to confirm the clientele effect ; the number of shareholders decreases continuously as the size of the largest shareholder rises. The decrease is the sharpest in the three first categories. In the first two categories, one type of equilibrium seems to apply:

firms with no dominant shareholder and numerous small blockholders. The pattern changes in category 3: the number of other owners is reduced, the second largest shareholder gets smaller compared to the dominant owner, so we are getting to another type of equilibrium:

firms with one dominant shareholder surrounded by small block shareholders. Once the dominant shareholder controls the firm with 50% of the votes – categories 5 and 6 – the residual ownership is so reduced that we can consider being clearly in the third type of equilibrium: firms with one very large shareholder and no smaller blockholder.

So, at first glance, it seems that Zwiebel’s theoretical findings apply rather well to the Belgian

case. However, further statistical analysis will of course be needed to confirm these first

assertions.

6. Empirical Testing for Belgium

In order to keep some comparability, and before going into more detailed tests we will first reproduce the same tests as Zwiebel’s in his initial contribution.

6.1. Test whether Large Shareholders “create their own space”.

Using US data, a goodness of fit chi-square test finds a difference between the actual and a random distribution of blocks above 10% and 20% significant at 0.001 and 0.003 levels respectively. Using Belgian direct ownership data, results are strikingly different. There is no difference at all between a random distribution and the actual distributions of “large” blocks across firms.

Table 4 Distribution of Large Block Shareholders: Actual versus Random Distributions - Direct Ownership

Blocks > 10%

Number of blocks in Firm Number of Firms (actual) Number of Firms Under Random Choice

1 77 143.7

2 44 38.7

3 11 6.9

4 1 0.9

5 0 0.1

Goodness of fit, χ

(3) = 0.1827 (0.98) (2) Blocks > 20%

Number of blocks in Firm Number of Firms (actual) Number of Firms Under Random Choice

1 93 94.1

2 21 12.6

3 1 1.1

4 0 0.1

Goodness of fit, χ

(3) = 0.0558 (0.99)

Table 5 Distribution of Large Block Shareholders: Actual versus Random Distributions - Ultimate Ownership

(i) Blocks > 10%

Number of blocks in Firm Number of Firms (actual) Number of Firms Under Random Choice

1 82 143.7

2 22 38.7

3 5 6.9

4 2 0.9

5 0 0.1

Goodness of fit, χ

(3) = 0.0405 (0.99)

(3) Blocks > 20%

Number of blocks in Firm Number of Firms (actual) Number of Firms Under Random Choice

1 70 94.1

2 5 12.6

3 0 1.1

4 0 0.1

Goodness of fit, χ

(3) = 0.0369 (0.99)

A first reason for this might be linked to the definition of a “large” block on each side of the Ocean. Indeed, as we showed in section 3, ownership concentration differs widely between Continental Europe and the US; a large block of shares in the US is 5%, while in Europe, and in Belgium in particular, a large block might be around 25% or 33%.

The size factor appears to be a limitation to the suitability of Zwiebel’s model to European countries. Proposition 3 of the model states that the equilibrium distributions of type 2 shareholders are unaffected if parameters are proportionally scaled up or down, but it does not mention the changes in equilibrium induced by a change in size of the large (type 1) shareholders. What the theory says is that when s (the relative size between large and small investors) tends to 1, smaller shareholders tend to distribute themselves symmetrically across all firms they challenge. If we imagine that, in Belgium, blocks of 10% and 20% are small and not large shareholder in the sense of the model, they effectively tend to distribute themselves symmetrically across firms in a country where s is low, due to high ownership concentration.

A second reason might have to do with the tendency of the two largest shareholders of a firm to collude to form a winning coalition, as we could tell from figures 1 and 2. Of course, collusion of small owners in order to get the control over a company is precisely the point of the model, but the fact that these owners are already quite large - in the context of higher ownership concentration in Continental Europe - certainly affects the results of the tests.

Thus we can expect so far a few differences in the ownership structure between Belgium (and maybe also Continental Europe, having similar concentration levels) and the United States. We seem to have here, to some extent, the existence of structure where several large owners cohabit, while this is specifically excluded for the US, both by the theory and by the empirical tests made on US data.

The objective of the tests run in the following section is precisely to check to what extent Zwiebel’s predictions are robust across different corporate governance systems.

6.2. Test of a Clientele Effect in the Shareholder Structure

Regressing the number of 1% block shareholders on the size of the largest block shareholder

and a constant, Zwiebel found a negative coefficient for the size of the largest block,

significant at 0.001 level.

Using data for Belgium and regressing the number of 1% to 5% block shareholders

on the size of the largest block shareholder and a constant, we found a negative coefficient as well (- 0.03), both for direct and ultimate ownership data, significant at 0.001 level.

Contrary to the results given by the goodness of fit tests, the clientele effect of the model seems here to be confirmed for Belgian data as well.

6.3. Specific Tests Applied to Belgian Data

Descriptive statistics, even helpful to give a good overview of the situation, and preliminary empirical investigation are obviously not sufficient to find evidence confirming with good probability Zwiebel’s theoretical findings. The following statistical tests will then be performed in order to show with more accuracy whether the model applies to Belgium and to what extent.

We choose here to use a non-parametric test to assess the validity of the model for Belgian data. Non-parametric tests do not imply any assumption on the shape of the distributions, using only the ranks and signs of the observations. This makes them more robust to extreme values and to deviations from a pre-supposed shape of distribution. This is particularly useful in our case since we face as many ownership variable distributions as categories of dominant shareholder.

The Kruskal-Wallis test is a test on k independent samples. It is the generalisation of the Wilcoxon- Mann-Whitney test applicable to two samples only. The Kruskal-Wallis test is defined as follows.

Consider k independent samples of n

observations per sample (with 1≤ j ≤ k). The null hypothesis to test is the equivalence between all the k distributions. Let define R

the rank of the observation x

in the set { x

| 1 ≤ j ≤ k , 1 ≤ i ≤ n

}. R

is the rank of the i

observation in the j

distribution.

We have thus: 1 ≤ R

≤ n

+ n

+…+n

= N

The average rank of the j

distribution is noted: R

= (1/n

) Σ

R

The average rank of all distributions is (N+1)/2.

Under the null hypothesis, we expect that the average rank of each distribution equals roughly the global average rank, that is: R

≈ (N+1)/2 for each 1≤ j ≤ k.

A measure of the deviation from the null hypothesis is thus given by:

It can be shown that there is a constant C depending on N such that:

56

The Transparency Law stipulates a declaration threshold of 5% ownership. However, many listed companies reduce this threshold to 3% and some shareholders declare even smaller stakes.

2 1 1

2

.

)

2 ( 1

)

(

∑

^{− +   →}

=

j

d j

j

R N n N

C

KW χ

∑

− +

k j

j j

R N n

1

2

.

)

2

( 1

when n

,…, n

→ ∝. We reject H

when:

This test is the Kruskal-Wallis test.

It is the non-parametric equivalent of the analysis of variance with one factor (“One Way ANOVA”). Parametric ANOVA tests uses least squares to fit linear models. Although more powerful in linear cases, it is inappropriate here since ownership distributions are not linear.

Alternatives in non-parametric tests like the sign test or the Wilcoxon signed rank test are inapplicable here also since they are aimed to test differences between dependent distributions. Here of course, ownership distributions across companies are independent.

Another type of alternatives to the Kruskal-Wallis test is parametric tests applicable to discrete variables, representing here for instance the number of shareholders per firm. Logit, mlogit and probit models are excluded since here the variables are neither binary nor qualitative. A Poisson model can yet be considered. However, tests have rejected the hypothesis that the data on the number of shareholders were Poisson distributed.

Kruskal-Wallis: Methodology

Six categories, times 3 variables makes a lot of distributions and results can be confusing. We will thus use the same approach for direct and for ultimate ownership data, structured as follow:

- check whether all the distributions per category are different,

- check the difference between categories 2 by 2 and per variable, to find eventually useless categories,

- on the basis of the last results, merge the categories that are not different from one another, or subdivide one category if necessary,

- check the results with the new categories,

- interpret the results in the light of Zwiebel’s theoretical predictions.

For each step, the three variables i.e.: size of the second shareholder, number of other shareholders, average size of other shareholders will be treated separately.

(a) 6.3.1. Direct Ownership Data

For each variable, the six distributions are statistically different from one another.

When we check for a difference two by two, the results can be summarised in the following table.

Legend: a figure in % in the cell gives the level of significance of the difference, a sign “/”

means there is no significant difference between the categories.

2 1 ,

1 α

χ

〉

KW

Table 6 KW Tests on Categories - Direct Ownership Data

Category = size 1

owner Size 2d owner # other owners Size other owners

C1 (0-25) / C2 (25-33) 1% / 10%

C2 (25-33) / C3 (33-50) / / /

C3 (33-50) / C4 (50-66) 2% 7% /

C4 (50-66) / C5 (66-75) / / /

C5(66-75) / C6(75-100) / 6% /

C1 (0-25) – C3 (33-50) / / /

C3 (33-50) – C5 (66-75) 2% 10% 2%

C4 (50-66) – C6 (75-100) 1% 0.1% 2%

C1 – C2 – C3 (< 50%) 8% / /

C4 – C5 – C6 (> 50%) 2% 0.4% 4%

Categories 1, 2 and 3, where the dominant shareholder owns stakes below 50% of the votes do not differ much from one another. The only significant difference lies in the size of the second shareholder. One can imagine that the two largest shareholders might join together in category 1 or even category 2, when they are of rather similar size.

The situation is different when the dominant shareholder gets bigger and “works alone”. But the tests show that this possible collusion between the two largest shareholders does not affect the rest of the ownership structure.

In contrast, categories 4, 5, and 6, where the dominant shareholder owns stakes above 50% of the votes, are quite different from one another when they are compared by three. Taken two by two, categories 4/5 and 5/6 are too small to be significantly different, but the very significant difference between categories 4 and 6 clearly shows that, above the threshold size of 50%, the dominant shareholder has a significant influence on the rest of the ownership structure.

Results display also significant differences between the categories where the dominant shareholder controls more or controls less than 50% of the votes (C3 – C4 and C3 – C5).

To clarify these results and to underline the main conclusions, we merge similar categories.

These are categories 1-2-3 into category “123”, where the dominant shareholder does not have the majority, and categories 5-6 into category “56”, where the dominant shareholder has a qualified majority, more than 66% of the votes. Category 4 (50-66%) is maintained.

Table 7 KW Tests on Merged Categories - Direct Ownership Data Category = size 1

owner Size 2d owner # other owners Size other owners

C 123 – C 4 – C 56 0.01% 0.01% 0.02%

C123(<50%) – C4(50-66%) 0.1% 0.6% 5%

C4 (50-66%) – C56 (>66%) 1% 1% 2%

C123 (<50%) – C56 (>66%) 0.01% 0.01% 0.01%

Not surprisingly, these categories are all very different form one another. These threshold sizes of the dominant shareholder can thus be considered as those affecting significantly the ownership structure of a firm. The average figures synthesising the ownership structure for these categories are:

Table 8 Direct Ownership Data - Merged Categories

Category 123 Category 4 Category 56

Largest owner 0 % – 50% 50% - 66% 66% -100%

1

owner % 30.4 55.2 79.3

2d owner % 13.6 8.2 3.2

Size others % 7.2 5.7 2.2

# others 6.3 3.1 1.3

# firms 77 37 21

Looking at table 8, one can see two of the three equilibrium types of ownership structures mentioned by Zwiebel :

- Type 2: firms with one large shareholder, challenged for control by many smaller block shareholders. It corresponds to the first category “123”. In this category, firms count on average more than six shareholders around the largest owner, these shareholders control on average 7.2% of the votes and, in case of collusion, their voting power exceeds the voting power of the largest shareholder. The ratio “s” between the size of the largest shareholder and the size of smaller investors ranges here between 2.2 (30/13) and 4.2 (30/7), which is not much.

- Type 3: firms with one very large shareholder and no smaller blockholder. This is the case in category 4, where the dominant shareholder controls the majority of the votes, and where he is surrounded by few (3 on average) small blockholders controlling around 5 to 8% of the votes each. Even if all these shareholders collude, they do not achieve the first blocking minority, with 17% of the votes. “s” range here between 7 and 10. So, we can roughly predict that 7 is the threshold size above which a large shareholder is not challenged for control, according to Zwiebel’s second theoretical result. And, obviously, type 3 corresponds also to the firms belonging to category “56”, where the dominant shareholder have a qualified majority in the firm and can take all the strategic decisions.

There is on average one very small other shareholder, often none.

(b) So it appears that only the two most concentrated ownership types are represented here. It is not surprising considering what has already been said about ownership concentration in Belgium compared to the US. But there might be also another factor explaining this high level of

concentration: the relatively moderated size of the companies in Belgium. Of course, one controls more easily a large fraction of the ownership of a smaller company.

(c)

(d) Indeed, data seem to confirm this hypothesis: the ten largest companies listed on the Brussels stock exchange (having a market capitalisation above BEF 50 bn in 1995) are all in the category

“123” and a majority of them have a largest shareholder below 33% of the votes. In particular, if we regress the stake of the largest shareholder on the size of the company for the whole the sample, we find a negative coefficient significant at 0.1%, confirming the fact that ownership

concentration and company size are negatively correlated.

However, given the complexity of ownership structure of listed companies in Belgium - as it has been extensively presented in chapter 2 - direct ownership data may not be the most relevant to consider. Ultimate ownership data, dealing with “real” owners at the end of the ownership chain may be more meaningful.

(e) 6.3.2. Ultimate Ownership Data

For each variable, the six distributions are statistically different from one another, just as for direct ownership data. When we check for a difference two by two, the results can be summarised in table 9.

Table 9 KW Tests on Categories - Ultimate Ownership Data

Category = size 1

owner Size 2d owner # other owners Size other owners

C1 (0-10) / C2 (10-25) 0.6% 7.6% 0.01%

C2 (10-25) / C3 (25-33) 6.99% 8% 0.5%

C3 (25-33) / C4 (33-50) / / 11%

C4 (33-50) / C5 (50-66) / / /

C5 (50-66) / C6 (66-100) / / /

C1 (0-10) / C3 (25-33) 2.0% 3.0% 0.03%

C3 (25-33) / C5 (50-66) 1.8% / 0.6%

C4 (33-50) / C6 (66-100) / / 5.0%

C1 – C2 – C3 (<33%) 3.8% 5.8% 0.08%

C4 – C5 – C6 (>33%)

C3 - C4 - C5 - C6 (>25%) /

2.0% /

11% /

0.4%

The situation is here opposed to the one with direct ownership data. There is no difference in the rest of the ownership structure since the largest shareholder controls more than 50% of the votes and even as soon as he controls one third of the votes. Indeed, there is no real difference between categories 4 to 6. On the other hand, the ownership structure changes significantly as the size of the dominant shareholder increases while remaining below 33% of the votes.

Since they are not different, we can merge the categories 4, 5, 6 into a category “4” gathering the firms in which the dominant shareholder controls at least 33% of the voting shares.

Categories 1 to 3 are different enough to create some sub-categories for firms where the dominant shareholder holds less than 25% of the votes, in order to determine more precisely the thresholds size for which the largest owner influences the ownership structure. The most relevant new categories are: 0% - 5% ; 5% - 25% ; 25% -33% ; 33% - 100%.

Results from these new categories are summarised in table 10.