Edith Ginglinger
email: edith.ginglinger@dauphine.fr

Jacques Hamon
email: jacques.hamon@dauphine.fr.

Paul André

Eric De Bodt

François Degeorge

Ariadna Dumitrescu

Thierry Foucault

Ulrich Hege

Hubert De

La Bruslerie

Ernst Maug

Christine Parlour

Christophe Perignon

Fabrice Riva

Myron Slovin

Ownership, control and market liquidity

Keywords: JEL classification: G32, G34, G10 ownership, blockholders, long-term shareholders, ultimate control, pyramids, voting rights, liquidity, bid-ask spread JEL classification: G32, G34, G10 ownership, blockholders, long-term shareholders, ultimate control, pyramids, voting rights, liquidity, bid-ask spread

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Introduction

Whether corporate governance affects market liquidity is a matter of much debate. Market liquidity is an important issue for investors and firms. Liquidity is a component of the transaction costs born by investors and a determinant of the cost of capital [START_REF] Amihud | Asset pricing and the bid-ask spread[END_REF][START_REF] Amihud | The Effects of Beta, Bid-Ask Spread, Residual Risk, and Size on Stock Returns[END_REF]and Pastor and Stambaugh, 2003). Therefore, investors prefer to invest in liquid stock markets. There are two potential explanations for the association between ownership structure and secondary-market liquidity. First, the trading hypothesis posits that the liquidity of a stock is increasing in the free float, limited when a firm's ownership is concentrated. Second, according to the adverse selection hypothesis, the presence of large informed shareholders should increase the adverse selection discount associated with the trading of the stock, which implies a reduced liquidity.

In this paper, we examine the effect of decoupling voting and economic rights of blockholders on adverse selection and market liquidity, and explore whether transparent and non transparent decoupling devices have different effects on liquidity. We study these issues within the French institutional setting, which is characterized by firms with concentrated ownership and large control-ownership deviations. French firms use two primary devices to enhance control: pyramid structures (18.5% of our sample) and a specific double voting right mechanism that rewards long-term shareholders (68.3% of the sample). 1 In contrast to dual-class shares, double voting right shares and single voting right shares trade at the same price and on the same trading line. When a double voting right share is sold, it loses the second voting right. France is therefore an ideal laboratory to analyze the effect of decoupling shares from votes on secondary market liquidity.

We make three contributions to understanding the ownership-liquidity relation. First, we find that block ownership, whether measured directly or by ultimate ownership, is detrimental to the firm's market liquidity. Second, controlling for free float[EG1], deviation of control from ownership is associated with lower liquidity, confirming the adverse selection hypothesis. Third, different devices used to enhance control have different effects on liquidity, since pyramid structures impair liquidity, whereas double voting rights enhance liquidity. Double voting rights reduce the number of insiders trading on private information, because if an insider sells a share with the rights and buys it back, the share only has a single voting right. By using double voting rights to enhance their control rather than other devices, blockholders reduce the degree of asymmetric information and offer higher secondary market liquidity to outside investors. This paper is related to three areas of recent research. One area is research that investigates the effect of blockholdings on liquidity. Several theoretical analyses, when considering the costs and benefits of ownership concentration, emphasize that increased market liquidity is a positive consequence of dispersed ownership (see for example [START_REF] Bolton | Blocks, liquidity and corporate control[END_REF]Von Tadden, 1998 andMaug, 1998). Block ownership can affect the firm's market liquidity through two major mechanisms: by altering the firm's trading activity (trading hypothesis) or by increasing the probability of informed trading (adverse selection hypothesis). One, in the presence of a large shareholder, only shares included in the free float are likely to be traded. Thus, the availability of shares is limited, fewer shareholders can participate in the trading of the stock, the frequency of trades is reduced (Demsetz, 1968) and the acquisition and production of information is discouraged (Holmström and Tirole, 1993). Two, concentrated ownership is potentially costly, because blockholders may have private information about firm value, and as a result of this higher probability of informed trading, liquidity providers widen spreads. A large body of theoretical work describes how markets react to the presence of informed traders (see for example Glosten and Milgrom, 1985). Previous empirical studies that examine the impact of blockholders on market liquidity, mainly conducted on U.S. data, lead to ambiguous results, partly because they do not distinguish between insider and institutional blockholdings. 2 More recently, Rubin (2007) documents a high negative correlation between insiders' blockholdings and institutional holdings, confirming that institutions are more willing to invest in firms with less concentrated insider ownership. He reports that total institutional holdings have a negative effect on spreads, whereas institutional blockholdings widen spreads. Brockman, Chung and Yan (2009) find that block ownership impairs the firm's market liquidity. However, in accordance with the trading hypothesis, their results suggest that it is the relative lack of trading, and not the threat of informed trading that explains the inverse relation between block ownership and market liquidity. Using the SEC's definition of insiders, our study concentrates on manager and controlling shareholder ownership. We do not take into account institutional investors, unless they control the firm. Our approach is further motivated by the fact that blockholdings are on average very large in France (more than 50% on average) relative to the U.S. where Rubin (2007) and Brockman et al. (2009) document that insider blockholdings are on average only 5%. Despite the different institutional environment and the more concentrated ownership of French firms, we also find a negative relation between blockholdings and liquidity, confirming previous results.

However, in contrast to Brockman et al. (2009), we find that both adverse selection and trading effects are responsible for the negative effect on liquidity.

The second area of the literature related to our work concerns the relation between corporate governance characteristics and market liquidity. Prior research examines how internal and external corporate governance structures as well as control-ownership divergence affect firm value, the cost of capital, and stock returns. 3 Moreover, most previous studies examine the impact of ownership on liquidity within a one-share-one-vote setting. In this regard, the separation of control and cash-flows rights can have several effects on market liquidity. Control can generate private benefits for controlling shareholders and the presence of such benefits makes outside investors reluctant to buy the stock, reducing market liquidity. The ultimate owner may adopt a poor disclosure policy to be able to trade on private information. However, evidence on these effects is limited. Chung, Elder and Kim (2010) find that stocks of companies with better governance structures have narrower spreads, a higher market quality index, smaller price impact of trades, and a lower probability of information-based trading. To our knowledge, [START_REF] Attig | Effects of large shareholding on information asymmetry and stock liquidity[END_REF] are the first to examine the relation between stock liquidity and ultimate ownership. Using a sample of Canadian publicly-traded firms for the year 1996, they find that a greater separation between ultimate control and ownership results in more severe information asymmetry and wider bid-ask spreads. We use a French sample of 1550 firm-year observations to examine the relation between ownership characteristics and market liquidity and find that the deviation of ultimate control from ownership has a negative impact on liquidity. We therefore extend the previous results for a longer period of analysis, within a different legal context, and also evaluate several measures of market liquidity.

A third area of the literature to which our work is related analyzes different control enhancing devices. In our work, the two primary methods that separate voting rights from cash flow rights are pyramiding and having different classes of shares that provide different voting rights for given cash flow rights. A pyramid structure allows indirect control of a firm by a chain of ownership relations that have only a small cash flow stake. Several studies relate firm valuation and pyramidal structure. 4 In this paper, our aim is to relate pyramids to asymmetric information and liquidity. Manconi and Massa (2008) find that organizational complexity, measured as the number of layers in the firm's subsidiary structure, increases the asymmetry of information between the firm and the market. Therefore, pyramids should have a negative impact on secondary-market liquidity. Through the use of different classes of shares, a controlling shareholder can achieve separation by owning the firm's high vote shares and selling the shares with inferior or no voting rights. 5 We investigate whether differential voting right structures have positive effects on market liquidity. First, by using higher voting right shares, a large shareholder can hold a lower fraction of the shares while ensuring control, which has a positive impact on liquidity (see for example [START_REF] Becht | European corporate governance: Trading of liquidity against control[END_REF]. Second, with dual-class shares or equivalent mechanisms, insiders generally hold superior voting right shares, and therefore, do not trade inferior voting right shares. As a consequence, the probability of market participants trading against insiders is reduced, increasing liquidity. Consistent whith this view, [START_REF] Boehmer | Managerial bonding and stock liquidity: an analysis of dual-class firms[END_REF] show that the bid-ask spread of low voting right dual class shares is smaller because insiders hold shares with high voting rights. In the case of dual class shares, there are two trading lines, so liquidity may be split. Our paper focuses on a French specific device that allows double voting rights for registered shares, with the additional voting right lost when the shares are sold. Thus, blockholders have to choose between the double voting rights and the liquidity of their shares. In contrast to dual class shares, the double voting right share is sold as a single voting right share and on the same trading line. This characteristic makes it a better experiment than dual class shares to test the hypothesis of an impact of differential voting right shares on market liquidity, since the double voting rights is a disincentive for insiders to sell, but not to buy shares. However, insiders are more likely to sell in order to liquidate their holdings, unlike institutional investors, and double voting rights restrain insiders from sell/buy back transactions on their stocks. Thus, the probability of market participants trading against informed traders is reduced in the presence of double voting right shares, implying increased liquidity for outside investors. Controlling for market and ownership characteristics, we find that pyramid structures reduce liquidity and increase asymmetric information on the French market, whereas firms that use double voting rights experiment improved secondary-market liquidity. Overall, our study confirms the adverse selection hypothesis to explain the ownership-liquidity relationship.

The remainder of the paper is organized as follows. In Section 2, we describe data and our calculation of ultimate ownership. In Section 3, liquidity measures and methodology are developed. In Section 4, empirical results are reported on the effects of controlling shareholders, control-ownership deviation, and the means of dissociation between ownership and control on secondary market liquidity. Section 5 summarizes and provides conclusions.

Data

Euronext data

We use the Euronext intraday database. Our dataset contains a time-stamped to the nearest second record of all transactions and orders submitted to the market from July 1998 to July 2003 for all French listed firms. The data include transaction prices, volume, and the best limits of the order book (bid and ask prices, and bid and ask size), as well as market capitalization. Euronext Paris is an electronic limit order market. There are two main market models: continuous trading, for the more actively traded stocks, and a double auctions market for the less liquid stocks. A description can be found in Biais, Hillion, and Spatt (1999). A call auction determines the opening and closing price in the continuous market. Trading takes place continuously from 9.00 to 17.25. 6 Traders mainly use limit orders and market orders. Deferred settlement is possible for a subset of the more liquid shares: this market segment is called "Reglement Mensuel" until 2000 and "Service à Réglement Différé" or SRD after 2000. 7 For stocks eligible for the SRD, investors can submit buy or sell orders with settlement at the end of the month. Stocks eligible for the SRD are chosen by Euronext. For all other stocks, only cash trading is possible. All SRD stocks belong to the continuous market. The SRD market segment accounts for approximately 89% of the total market value of Euronext Paris, and 97% of the turnover. As SRD stocks are the more traded and more liquid stocks, we control for SRD eligibility in our regressions.

Ownership and governance in France

In France, as in most Western European countries, ownership tends to be concentrated. Faccio and Lang (2002) show that 36.93% of European firms are widely held, whereas in France this percentage is only 14%. In France, 64.82% of firms are controlled by a single family, versus 44.29% in Europe. In line with Faccio and Lang (2002) and earlier studies, we assume that 20% of the voting shares is sufficient to ensure control. If no shareholder exceeds the 20% threshold, the firm is said to be widely held.

French blockholders use several devices to enhance control. Apart from pyramids, the most common device is double voting rights. The firm's charter can authorise double voting rights for registered shares that have been held for more than x years (where x is between 2 and 4 years). Like all decisions amending a firm's charter, introducing or deleting double voting right shares requires an extraordinary general meeting with a two-thirds majority vote by shareholders to be adopted. In contrast to dual-class shares, the voting right is attached to the shareholder.

Typically, controlling shareholders own double vote shares while most dispersed shareholders own single vote shares.

In addition to different per share votes, the charter may also include voting caps, which limit voting rights in general shareholders' meetings to x% of all shares or to a certain percentage of votes cast at the meeting. A cap means a shareholder can only use a certain percentage of his voting rights, but if he owns 2/3 of the capital, all voting rights can be used.

Finally, some French companies are limited partnership firms. These firms consist of partners who manage the firm, in addition to other shareholders. As the active partners' shares are non-transferable and the charter makes removal of the managing partner practically impossible, this form of legal entity precludes hostile takeovers.

Since there is no electronic database on French firm ownership, including needed information on double voting rights and corporate governance characteristics, we manually collect this information from annual reports for three years 1998, 2000 and 2002. The ownership structures are as of the 31 st December of each year. Our sample, which includes all French listed firms for which the annual reports are available, consists of 1550 firm-observations. In France, annual reports disclose the identity of all shareholders who control at least 5 percent of voting rights, and identify and cluster direct and indirect family ownership. For example, if a family owns 10% directly and 30% through an unlisted holding entity belonging to the family, the annual report discloses the total family ownership of 40%. Since there are numerous family holdings, and family ownership is aggregated we observe fewer pyramids. However, the pyramids we observe are effective pyramids and not intra-familial organization devices. 8

Determining ultimate ownership

We determine ultimate shareholders as in Claessens et al., (2000) and Faccio and Lang (2002), by computing ultimate voting rights in application of the so-called "weakest link" principle. Firm A is said to be controlled through pyramiding if it has an ultimate owner, who controls firm B indirectly through another firm that it does not wholly control. A shareholder of a corporation is said to be an ultimate owner at the 20% threshold if control is via a control chain whose links all exceed the 20% threshold.

As an example, consider the ownership structure of Casino in December 2000. Figure 1 illustrates double voting rights shares and pyramiding in the Euris group, which owns the retail company Casino. All holdings of more than 5 percent of a firm's shares are listed. Jean-Claude Naouri owns Euris through a listed company, Finatis. Finatis owns 84.6% of Euris, which owns 83.06% of the cash flow rights in Foncière Euris, which owns 66.92% of Rallye, which owns 51.9% of Casino. Euris cash flow rights in Casino are therefore 84.6% x 83.06% x 66.92% x 51.90% = 24.4%. According to the weakest link principle, Euris owns 59.90% of the voting rights in Casino (the minimum of 100%, 84.49%, 81.24%, 59.90%).

A second example (Lazard group in 2002), illustrates that there may be complicated ownership loops involving several firms. The family Haussman-Percier owns 18.67% of the cash flow rights in Eurazeo through three channels. According to the weakest link principle, Haussman-Percier owns 63.17% of the voting rights in Eurazeo (Min[68.87%,55.24%,31.51%] + Min[68.87%, 0.04%] + Min[68.87%, 31.62%] = 31.51 + 0.04 + 31.62 = 63.17%). We have taken these loops into account to determine ultimate ownership for all the firms in our sample.

[Insert Figure1 here]

We classify firms into three groups, based on the identity of the ultimate shareholder.

Family controlled firms include firms in which the ultimate owner is a family, an individual, or a firm that is not listed on any stock exchange. In non-family controlled firms, the ultimate owner is a financial firm, the French state, a widely-held corporation, or a cooperative. Widely-held firms are firms without an ultimate owner at the 20% threshold.

Table 1 reports characteristics for the 1550 firm-observations of our database.

[Insert Table 1 here] These data confirm that French firms are closely-held. On average, the largest shareholder directly holds 46.42% of the capital and 51.99% of the voting rights. 9 The second largest shareholder holds on average 7.37% of the capital and 7.65% of the voting rights. The float, the percentage of the capital owned by shareholders not identified or holding less than 5% of the capital, averages 41.06% of capital for the total. On average, employees own 0.83% of firm shares and the firms hold 0.96% of their own shares.

We also identify the ultimate controlling shareholders in the presence of pyramids, for a threshold of 20% of the voting rights. On average, the largest shareholder ultimately holds 43.64% of the capital and 50.99% of the voting rights.

We further take into account the identity of the shareholders. At the 20% threshold, 70.1% of the companies are controlled by a family, holding on average 50.71% of the capital and 60.04% of the voting rights. Thus, French listed companies are largely controlled by families.

Among the other controlling shareholders, are financial institutions (9.2%), widely-held companies (4.8%), and the French State (2.8%). Only 13.1% of the firms are widely-held.

We then examine the methods used by French firms to ensure separation between control rights and ownership rights held by large shareholders (Table 2). Double voting rights are the most frequent device used by 68.3% of the firms; for 52.2% of them, it is the only enhancing device. Pyramids are used by 18.5% of the firms, voting caps by 2.3% of the firms, dual-class shares by 1.2%, and limited partnerships by 1.8%. As pyramids and double voting rights are the main devices used by French firms, we focus our analysis on these two mechanisms.

[Insert Table 2 here]

Liquidity measures and methodology

We include in our study several liquidity measures, divided into trade-based measures and order-based measures, to capture transactions costs. Trade-based measures include the logarithm of the number of trades and the logarithm of relative turnover (trading value divided by market capitalization). Order-based measures include depth and effective relative bid-ask spreads. Depth at the opening is measured by the logarithm of the sum of the value in Euros of shares posted at the best limits first observed in the order book on a given trading day. We calculate the daily average relative effective spread, estimated using full day data records. The number of spreads over a trading day varies according to the number of transactions. The effective spread takes into account the possibility of a transaction within the spread, although in practice this is rare on the Paris exchange. 10 The relative effective spread relates the spread to the midpoint of the spread 11 :

( ( 1) Midpoint Midpoint - Price Trade 2 Spread Relative Effective   , where 2 Price Bid Price Ask Midpoint  
All liquidity variables are averages across all trading days over the 12 months around the date of ownership structure for each year (6 months before and after December 31, for the years 1998,2000,2002). 12 To complement the univariate analysis, we use ordinary least squares (OLS) regressions to explain liquidity. There are four dependent variables: relative effective spread, number of transactions, relative turnover and depth. The independent variables include corporate governance variables and control variables. To take into consideration the combined effect of control variables suggested by previous studies of the determinants of the liquidity 13 , we specify as variables market capitalization and SRD, a dummy equal to one when the share is traded on the deferred settlement market. We also specify a volatility variable (standard deviation of rates of return over one year around the date of ownership structure). Year dummies are included.

For the corporate governance, we specify variables for the percentage of capital owned by the controlling shareholder and the second largest shareholder (either direct or ultimate), the identity of the controlling shareholder, the wedge between cash flow rights and control rights, and dummy variables that reflect the presence of pyramids and double voting rights.

Empirical results

Controlling blockholders and liquidity

We expect liquidity measures to be lower for firms with controlling shareholders than for widely held firms. Table 3 presents univariate evidence of market characteristics and liquidity measures for subsamples of widely-held firms, family-controlled firms and non-family-controlled firms (firms that are controlled at the 20% level by financial, state, or widely-held firm blockholders).

[Insert Table 3 here] Widely-held firms are largest in market value, more volatile, involved in the most transactions, and more liquid than family-controlled firms and non-family controlled firms.

Turnover and number of transactions for widely-held firms' are significantly larger than for other controlled firms, which, in turn, are larger than family-firms turnover and number of transactions.

Average relative spread is 1.46% for widely-held firms, 2.99% for family-firms, and 1.97% for non-family controlled firms. On average, 20.81 analysts follow widely-held firms, compared to 6.88 for family-firms and 13.51 for other closely-held firms. The data show that the size and the volatility of companies listed on the same market segment have only limited differences with respect to whether there is a controlling shareholder. However, family-firms are characterized by wider spreads and lower depth. In general, the descriptive statistics indicate that the widely-held companies are the largest and the most liquid firms, and family-controlled companies are the smallest and least liquid firms. Non-family controlled companies fall between these two profiles.

Table 4 reports the estimation results of our multivariate analysis. Liquidity, except for relative turnover, increases with market capitalization, and is greater for firms on the SRD market. Liquidity, regardless of measure, decreases as volatility increases. This result is consistent with previous findings on the determinants of liquidity measures.

[Insert Table 4 here] In the first column, we regress the spread on free float, and find a negative relationship.

As the size of the market for the firm's shares declines, the frequency of trades and the production of information declines, leading to reduced liquidity. To more directly test the impact of controlling shareholders on liquidity, we include two dummy variables for controlled firms.

The first (second) dummy equals one if the firm is controlled by a family (other controlling shareholder) at the 20% threshold. Spreads of family-firm (other controlled firm) shares are 0.44% (0.62%) larger on average than spreads of widely-held shares. We also include the percentage of capital held by the first and the second shareholders. We find that liquidity, regardless of the measure used, decreases with the percentage of the capital held by both the controlling and second shareholder. Inside block ownership reduces liquidity, confirming that the shares of closely-held firms have a less liquid secondary-market.

We then investigate the impact of separating ultimate control and ownership on liquidity.

The discrepancy between cash flow rights and voting rights is measured as the ratio of voting rights minus cash flow rights to cash flow rights. We find that the deviation of control from ownership has a positive impact on spread, a negative impact on the number of transactions and relative turnover, and a negative but insignificant impact on depth. Several reasons may explain this result. First, when minority shareholders suspect private benefits to be a large part of the firm's value, they may prefer selling the shares or avoid buying them. Second, the ultimate shareholder may choose to adopt a poor disclosure policy to trade on private information. Both lead to lower liquidity.

Our results also apply to subsamples by control type. The existence of a controlling shareholder at the 20% threshold reduces liquidity measured by trade-based variables and spread, whether it is a family or not, with a negative but insignificant effect on depth. A second shareholder has a negative impact on liquidity only for family-firms. The deviation between ultimate control and ownership increases the spread for all of the controlled firms, but the impact is more pronounced for family-firms, significantly reducing the number of transactions and the relative turnover, although not affecting depth. Orders may be posted in the order book in a manner that narrows the spread but with smaller quantities. One explanation is that most institutional investors will not invest in a firm with a large control-ownership deviation. Thus, transactions are mainly initiated by individual investors, leading to smaller order size. However, spreads increase since a fraction of these investors are informed. Thus, there is evidence for our hypothesis of reduced liquidity in the presence of controlling shareholders.

Means of enhancing control and market liquidity

We examine the impact of alternative means of enhancing control by estimating regressions to explain liquidity variables. Table 5 reports the regression coefficients for the total sample.

[Insert Table 5 here] In the first set of regressions (columns 1 to 4), liquidity measures are specified as a function of direct ownership variables (as opposed to the ultimate ownership variables used in Table 4): percentage of capital owned by the main and second shareholders, and the deviation between cash flow rights and control rights. The impact of the two direct ownership variables is similar to that of the ultimate ownership variables. However, the direct control/ownership deviation improves liquidity when measured by spread, number of trades and relative turnover, whereas, in Table 4, the ultimate deviation has the opposite effect. Double voting right shares are the main source of direct deviation. Ultimate deviation is the consequence of both pyramiding and double voting rights. This finding may therefore reflect a difference in the impact of these two means of enhancing control on liquidity.

To verify this hypothesis, the next set of regressions (columns 5 to 8) includes two dummies that equal one if the firm has adopted, alternatively, a pyramidal structure or double voting rights. We find that double voting rights have a positive impact on liquidity measured by spread, number of transactions and relative turnover, whereas pyramiding leads to decreased liquidity. This result is robust to the inclusion of direct or ultimate ownership variables and of a free float variable, and is also robust to the inclusion of a dummy for the identity of the controlling shareholder. However, depth is not affected by the inclusion of double voting rights and pyramiding dummies.

Next, we investigate whether our findings are invariant to the controlling shareholder identity. We re-estimate the previous set of regressions for subsamples of family controlled firms and other types of controlled firms (Table 6).

[Insert Table 6 here] For family-firms, we confirm that direct control/ownership deviation has a negative impact on spreads. Double voting rights strongly increase liquidity, measured by spread, number of transactions and relative turnover, whereas pyramiding has the opposite effect. For nonfamily-controlled firms, pyramiding leads to decreased liquidity, as measured by spreads and number of transactions, but double voting rights have no significant effect on liquidity.

Our results confirm that double voting rights have a positive impact on liquidity for family-firms, that has two origins. First, free float is larger for family-firms with double voting rights, which permit family shareholders to ensure control by holding a lower fraction of the shares (trading hypothesis). As the negative impact of double voting rights is robust to the inclusion of the float variable in the regressions, increased float is not the only explanation for the positive impact of double voting rights on liquidity. The second reason is a probable reduction of insider trading. Some informed shareholders are likely to refrain from selling their shares, because of the loss of double voting rights. If a significant number of informed shareholders abstain from trading, the asymmetry of information may decrease, resulting in a greater liquidity (adverse selection hypothesis). Double voting rights, by rewarding long-term shareholders, also enhance liquidity for minority shareholders of small and closely-held firms, and may thus be beneficial for both controlling and minority shareholders.

To verify the robustness of our results, we analyze subsamples of firms that use double voting rights as their only means of enhancing control and firms with no control enhancing device (Table 7, Panel A). Again, we find that for family-firms, double voting rights have a negative impact on spreads and a positive impact on number of transactions and relative turnover.

There is no significant effect for the subsample of non-family controlled firms. For subsamples of firms using pyramids versus firms using no control enhancing device, we find that pyramids increase spreads for both family and non-family-controlled firms (Table 7, Panel B). Pyramids decrease the number of transactions and the relative turnover for family-firms and also for nonfamily controlled firms (although, the effect is not significant). Our results confirm the hypothesis that the impact of control-ownership deviation on liquidity depends on the device used to achieve it and that the effect on liquidity is positive for double voting rights and negative for pyramids.

[Insert Table 7 here]

Ownership structure, means of enhancing control and asymmetry of information

We further investigate the impact of ownership and governance variables on liquidity, to determine whether our prior findings result from variations in the degree of asymmetric information in the presence of blockholdings or when the control-ownership deviation is high.

We use two approaches. First, following [START_REF] Brennan | Investment analysis and price formation in securities markets[END_REF], we measure the level of a firm's asymmetric information by the number of analysts following the firm. Second, we calculate the adverse selection component of the spread.

Measuring asymmetric information by the number of analysts following the firm. We obtain the number of analysts following each firm in our sample at the end of 1998,2000,2002, from the I/B/E/S database. On average (median), there are 9.82 (3) analysts following each firm. Widelyheld firms are followed by 20.81 analysts on average, whereas family-firms are followed by 6.88 analysts. Table 8 reports OLS regressions that relate the number of analysts following each firm to blockholdings and control/ownership deviation.

[Insert Table 8 here] We find that the number of analysts increases with free float at the 20% level and decreases with the ultimate and direct percentages of capital held by the main and the second shareholders, confirming that there are less analysts (and greater asymmetric information according to our hypothesis) in the presence of blockholders, for the total sample and for subsamples by type of controlling shareholder. The number of analysts increases with the direct control/ownership deviation for the total sample and for the family-firms. It declines with the ultimate control/ownership deviation but only for the subsample of family-firms. The double voting right dummy also has a positive effect on the number of analysts for the total sample and the subsamples of family and non family-controlled firms. The pyramid dummy has a negative effect for the total sample and the family-firms sample. The device used to dissociate control and ownership, pyramid or double voting rights, has an opposite impact. Given that the number of analysts is our measure of asymmetric information, we infer that pyramids increase asymmetric information, whereas double voting rights reduce asymmetric information.

Measuring asymmetric information by the adverse selection component of the spread. We use the Euronext intraday database to calculate the adverse selection component of the spread. We identify and exclude the transactions on opening and closing call auctions. The orders carried out on several limits of prices in the order book are identified and aggregated as a single transaction. 14 Over a one-year period (6 months before and 6 months after) around the year-end 1998, 2000 and 2002, 56.604 million transactions occur for the shares in our sample, among which 6.362 million are executed on at least two price limits. The number of observations available in a given month differs from one share to another. For example, France Telecom has 143,969 transactions in July 2002, whereas 1475 share-months (out of 11,179) have less than 50 transactions.

We use the Huang and Stoll (1997) approach to measure the adverse component of the spread. We denote the price of the transaction at time t as Pt and define Qt to be the buy-sell trade indicator variable for the transaction price, Pt. The indicator equals +1 if the transaction is buyer initiated and -1 if the transaction is seller initiated. As Euronext is an electronic order driven market, the direction of the transactions can be identified in a precise way, by comparing the price and the immediately preceding spread. (2,878 million Euros compared to 97 million for the non-included firms), and the float is significantly larger (56.21% compared to 39.20%). The main ultimate shareholder holds 38.87% of the capital (54.87% for the non-included firms), and the average spread is 1.73% (4.70% for the non-included firms). In general, the smaller sample contains larger and more liquid firms than those of the initial sample.

( ( 2)     11 22 t t t t t t SS P P Q Q Q e            Theand ,
[Insert Table 9 here] We next estimate regressions that explain the adverse selection component of the bid-ask spread to test the hypothesis that larger controlling shareholders and greater control-ownership deviations are associated with more serious information asymmetry (Table 9, Panel B). We find that the adverse selection component of the spread is increasing with the ultimate and direct percentage of capital held by the main and the second shareholders, confirming that controlling shareholders are informed traders. It is also increasing with ultimate control/ownership deviation for the total sample and the subsamples of family and non family-controlled firms. The pyramid dummy increases asymmetric information for the total sample and the family-firm sample. Thus, when the controlling shareholder is able to trade on private information to extract private benefits, in particular by adopting a poor disclosure policy, asymmetric information is higher. In contrast, we observe that neither the direct control-ownership deviation, resulting mainly from double voting rights, nor the double voting rights dummy, have a significant impact on the adverse selection component of spread. Our previous results on double voting rights hold mainly for family-firms, which are on average smaller than other firms, and in Table 9, panel A, it is apparent that more than one-third of the family-firms are excluded in the calculation of the adverse selection component of the spread. Since the reduced sample contains mainly larger and more liquid firms, one interpretation may be that there is an impact of double voting rights on the degree of asymmetric information for small firms, for which we are unable to calculate the adverse selection spread component, a metric that is not observable for larger firms.

Robustness checks

We conduct a series of robustness checks on our results. First, we average the liquidity variables over six months, four months plus two months around the end of the year, and the results are unchanged. Second, we re-estimate our models in Table 4 for each year in our sample, and our findings still hold. Third, we disaggregate the sample by settlement method (cash-only and deferred settlement) and re-estimate our models in Table 4 for each subsample. The results are qualitatively unchanged. Fourth, we re-estimate all of our regressions to include dummies that reflect other governance mechanisms (voting caps, dual class shares and limited partnership), including more detailed ultimate blockholder identity dummies and a free float variable. The results remain the same. Fifth, when all tests are conducted with quoted spreads instead of effective spreads, the results are unchanged. Sixth, we examine the issue of endogeneity.

Previous findings have highlighted that in studies that find a positive impact of institutional investor blockholdings on liquidity, there may be a problem of endogeneity, since institutional investors prefer more liquid stocks. In our study, we take into account controlling blockholders and blockholders have a negative impact on liquidity. As underlined by Brockman and al (2009), it is not obvious why blockholders would prefer less liquid stocks. However, as a test, we performed a 2SLS regression as in Heflin and Shaw (2000) and the results remain the same. We further perform 2SLS regressions that treat the choice of pyramids or double voting rights as endogeneous, and the findings are unchanged.

Conclusion

Our study of the ownership-liquidity relation in France contributes to understanding the impact of ownership structure and the decoupling of ownership/control on market liquidity. We study a large sample of French firms, gathering hand collected data on control enhancing devices.

French firms are characterized by concentrated ownership and the extensive use of double voting rights, a mechanism that rewards long-term shareholders. We find that liquidity is significantly reduced for closely-held firms, and this result is robust with respect to whether the controlling shareholding is determined by direct or ultimate ownership. We take into account the identity of the controlling shareholder. We find that the device chosen to separate control from ownership has important consequences on liquidity and asymmetric information. Pyramids increase asymmetric information and decrease liquidity, whereas double voting rights reduce asymmetric information and increase liquidity, at least for small firms. Pyramids are complex and opaque mechanisms that allow controlling shareholder to trade on private information to extract private benefits. In contrast, double voting rights are transparent, and restrain insiders from using sell/buy back transactions. By using double voting rights rather than pyramids to enhance their control, blockholders reduce the degree of asymmetric information on the market and offer higher secondary-market liquidity to outside investors.

Table 1. Descriptive statistics for ownership

Statistics reported in Panel A are for ownership variables for the full sample of 1550 firm-year observations (year-end 1998, 2000, 2002). Ultimate ownership takes account of indirect control through pyramiding at the 20% threshold. The percentage of firms controlled by different ultimate controlling owners at the 20% threshold, and the mean percentage of capital and voting rights of the controlling owners are reported in Panel B. (year-end 1998, 2000, 2002). Panel A reports the number (percentage) of firms that adopted a given control device, the number of firms that adopted pyramids and another device, and the number of firms that used double voting rights and another device. Panel B presents the control enhancement devices adopted by firms, by identity of controlling shareholders at the 20 percent threshold. Market characteristics are reported for the full sample of 1550 firm-year observations. Parametric and non parametric tests are reported in italics to compare the characteristics of widely-held firms, family-controlled firms and non-family-controlled firms. The daily market value of the firm is averaged over 12 months around the date of availability of the ownership data (year-end). Volatility is the annualized estimate of daily volatility. Turnover is the daily average. Spread is the daily average relative effective spread, estimated using full day data records. Depth is measured using the data closest to the opening of the trading day. All variables are averaged over 12 months around the year-end.

Widely-held (1) N=203

Family-controlled (2) N = 1086

Non-family-controlled (3) N = 261

(2) vs ( 1 Regressions are reported that relate liquidity to ownership and governance characteristics for the full sample of 1550 firm-year observations. Liquidity is measured either by the effective relative spread, the Log(number of transactions), the Log(relative turnover) or Log(depth) for the firm-year. Spread is the daily average relative effective spread, estimated using full day data records. Relative turnover is the ratio of turnover to market capitalization. Depth is measured using the data closest to the opening of the trading day. Log (market value) is the logarithm of the daily market value of the firm. Volatility is the annualized estimate of daily volatility. All variables are averaged over 12 months around the year end. SRD is a dummy variable that takes the value of one when the share is eligible for trading with deferred settlement facilities, and zero otherwise. Other independent variables specified are free-float (at the 20% threshold) and ultimate cash-flow rights held by the largest and the second shareholder. Discrepancy between cash flow and control rights for the main shareholder is equal to the ratio of voting rights minus cash flow rights to cash flow rights. Family control is a dummy equal to one when the main shareholder is an individual or a group of individuals. Non-family control is a dummy equal to one when the controlling shareholder is not a family. The p-values are in parentheses. Regressions are reported for the relation of liquidity to ownership and governance characteristics. Liquidity is represented either by the effective relative spread, the Log(number of transactions), the Log(relative turnover) or the Log(depth) for the firm-year. Spread is the daily average relative effective spread, estimated using full day data records. Relative turnover is the ratio of turnover to market capitalization. Depth is measured using the data closest to the opening of the trading day. Log (market value) is the logarithm of the daily market value of the firm. Volatility is the annualized estimate of daily volatility. All variables are averaged over 12 months around yearend. SRD is a dummy variable that takes the value of one when the share is eligible for trading with deferred settlement facilities, and zero otherwise. Regressions include year indicators. Other independent variables are either ultimate or direct cash-flow rights held by the largest or the second shareholder. Discrepancy between cash flow and control rights for the main shareholder is equal to the ratio of voting rights minus cash flow right to cash flow rights. Double Voting Rights and Pyramid are dummies that equal 1 when the provision is present; N is the number of firm-year observations; p-values are in parentheses. Regressions are reported for the relation of liquidity to ownership and governance characteristics for subsamples by control type: Family controlled (in which the main shareholder is an individual or a group of individuals), firms controlled by non-family shareholders and widely held firms. Liquidity is represented either by the effective relative spread, the Log(number of transactions), or the Log(relative turnover) for the firm-year. Spread is the daily average relative effective spread, estimated using full day data records. Relative turnover is the ratio of turnover to market capitalization. Log (market value) is the logarithm of the daily market value of the firm. Volatility is the annualized estimate of daily volatility. All variables are averaged over 12 months around year-end. SRD is a dummy variable that takes the value of one when the share is eligible for trading with deferred settlement facilities, and zero otherwise. Other independent variables are either ultimate or direct cash-flow rights held by the largest or the second shareholder. Discrepancy between cash flow and control rights for the main shareholder is equal to the ratio of voting rights minus cash flow right to cash flow rights. Double Voting Rights and Pyramid are dummies that equal 1 when the provision is present; N is the number of firm-year observations; p-values are in parentheses. Regressions are reported for the relation of liquidity to ownership and governance characteristics for subsamples by means of control enhancement. Panel A presents regressions on a subsample of firms that use either double voting rights only or no means of control enhancement. Panel B presents regressions on a subsample of firms that use either pyramid only or no means of control enhancement. Liquidity is represented either by the effective relative spread, the Log(number of transactions), the Log(relative turnover) or the Log(depth) for the firm-year. Spread is the daily average relative effective spread, estimated using full day data records. Relative turnover is the ratio of turnover to market capitalization. Depth is measured using the data closest to the opening of the trading day. Log (market value) is the logarithm of the daily market value of the firm. Volatility is the annualized estimate of daily volatility. All variables are averaged over 12 months around year-end. SRD is a dummy variable that takes the value of one when the share is eligible for trading with deferred settlement facilities, and zero otherwise. Regressions include year indicators. Other independent variables are either ultimate or direct cash-flow rights held by the largest or the second shareholder. Discrepancy between cash flow and control rights for the main shareholder is equal to the ratio of voting rights minus cash flow right to cash flow rights. Double Voting Rights and Pyramid are dummies that equal 1 when the provision is present; N is the number of firm-year observations; pvalues are in parentheses. Regressions are reported for the relation of the number of analysts following the firm to ownership and governance characteristics. The dependent variable is calculated as LN(number of analysts + 0.001). Log (market value) is the logarithm of the daily market value of the firm, averaged over 12 months around year-end. Volatility is the annualized estimate of daily volatility averaged over the 12-months around year-end. SRD is a dummy variable that takes the value of one when the share is eligible for trading with deferred settlement facilities, and zero otherwise. Regressions include year indicators. Other independent variables are either ultimate or direct cash-flow rights held by the largest or the second shareholder. Discrepancy between cash flow and control rights for the main shareholder is equal to the ratio of voting rights minus cash flow right to cash flow rights. Double Voting Rights and Pyramid are dummies that equal 1 when the provision is present; N is the number of firm-year observations; p-values are in parentheses.

Table 9. Adverse selection component of spread

Panel A reports the characteristics of firm-year observations, for which data were available, to calculate the adverse selection component of spread, compared to the firm-year observations for which data were unavailable. Panel B reports OLS regressions that relate the adverse selection component of spread to ownership and governance characteristics. The adverse selection spread component is calculated as in Huang and Stoll (1997) and averaged over 12 months around the year end. Log (market value) is the logarithm of the daily market value of the firm, averaged over 12 months around year-end. Volatility is the annualized estimate of daily volatility averaged over the 12-months around year-end. SRD is a dummy variable that takes the value of one when the share is eligible for trading with deferred settlement facilities, and zero otherwise. Other independent variables are either ultimate or direct cash-flow rights held by the largest or the second shareholder. Discrepancy between cash flow and control rights for the main shareholder is equal to the ratio of voting rights minus cash flow right to cash flow rights. Double Voting Rights and Pyramid are dummies that equal 1 when the provision is present; N is the number of firm-year observations; p-values are in parentheses. Parametric and non parametric tests for Panel A are in italics.

Panel

  which cannot be estimated separately, represent the adverse selection component and the cost of inventory component of the spread as a percentage of the half-spread. The traded spread, S, is estimated using the Huang and Stoll's model for the 11,180 share-months for which at least 50 transactions (call auctions excluded) are available. The adverse selection component of the spread is estimated as: For each share and each of our three periods, we average the adverse selection spread component. All non-positive estimates are set equal to 0. Thus, the sample size for the adverse selection component of the spread (1,087 firm-year observations) is smaller than the sample size for spreads and depths (1,550). Table 9, Panel A, compares the characteristics of the firm-years for which the adverse component of the spread can be calculated versus the other observations. The reduced sample contains 92.61% of the widely-held firms, and only 64.18% of the familyfirms. The firms in the smaller sample are characterized by a larger average market capitalization

Figure 1 .

 1 Figure 1. Casino and Lazard cash flow rights and control rights

Table 2 . Control enhancement devices

 2 Control enhancement devices are reported for the full sample of 1550 firm-year observations

Table 3 . Descriptive statistics for market characteristics

 3

Table 4 . Controlling shareholders and liquidity

 4

Table 5 . Mechanisms of enhancing control and liquidity

 5

	Total sample	Family-controlled firms	Non-family controlled firms

Table 6 . Mechanisms of enhancing control and liquidity, for subsamples by control type

 6

			Direct ownership impact		Type of enhancing control device
	Models	1	2	3	4	5	6	7	8
	variables	Spread Number of	Relative	Depth	Spread Number of	Relative	Depth
			transactions	turnover			transactions	turnover
	Intercept	0.1076	-2.6637	-7.5932	3.1051	0.11048	-3.2114	-8.0299	3.0409
		(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)
	Control variables
	Log (market value)	-0.00551	0.5535	-0.00177	0.3618	-0.0055	0.5651	0.00266	0.3616
		(<.0001)	(<.0001)	(0.9040)	(<.0001)	(<.0001)	(<.0001)	(0.8648)	(<.0001)
	Volatility	0.02960	2.6624	2.2275	-0.2774	0.02982	2.6952	2.2907	-0.2429
		(<.0001)	(<.0001)	(<.0001)	(0.0070)	(<.0001)	(<.0001)	(<.0001)	(0.0188)
	SRD	-0.00402	1.4264	1.1535	0.1474	-0.0050	1.5840	1.3046	0.1674
		(0.0011)	(<.0001)	(<.0001)	(0.0096)	(0.0003)	(<.0001)	(<.0001)	(0.0032)
	Year 2000	0.00020	0.2233	0.05856	-0.09679	0.00008	0.2120	0.05724	-0.1013
		0.8299	(<.0001)	(0.2706)	(0.0245)	0.9303	(<.0001)	(0.3098)	(0.0188)
	Year 2002	0.00516	0.09081	-0.3316	-0.2387	0.00505	0.08453	-0.33478	-0.2466
		(<.0001)	(0.0664)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)
	Direct ownership variables
	Main shareholder	0.00016	-0.01737	-0.02006	-0.00254
		(<.0001)	(<.0001)	(<.0001)	(0.0005)
	Second shareholder	0.00017	-0.02699	-0.02742	-0.00682
		(0.0001)	(<.0001)	(<.0001)	(0.0006)
	Discrepancy between cash	-0.0127	0.6919	0.9315	-0.0690
	flow and control rights for	(<.0001)	(<.0001)	(<.0001)	(0.5179)
	the main shareholder
	Ultimate ownership variables
	Main shareholder					0.00015	-0.01443	-0.01759	-0.00239
						(<.0001)	(<.0001)	(<.0001)	(0.0011)
	Governance dummies
	Double voting rights					-0.00357	0.1624	0.1915	-0.0254
						(<.0001)	(0.0005)	(<.0001)	(0.5058)
	Pyramid					0.00396	-0.5275	-0.3920	-0.0010
						(0.0001)	(<.0001)	(<.0001)	(0.9831)
	Number of observations	1549	1549	1549	1541	1549	1549	1549	1541
	Adjusted R²	0.6016	0.8504	0.5803	0.6430	0.5973	0.8359	0.5269	0.6405

Table 7 . Regressions for subsamples by means of control enhancement

 7

		Family controlled (N=1086)		Non family controlled (N=261)
	Models	1	2	3	4	5	6	7	8
	variables	Spread	Spread	Number of	Relative	Spread Spread Number of	Relative
				transactions	turnover			transactions	turnover
	Intercept	0.1223	0.1336	-2.8025	-8.1129	0.07604	0.07607	-3.8705	-7.3738
		(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)
	Control variables
	Log (market value)	-0.00687	-0.0071	0.5450	0.01013	-0.00402	-0.0039	0.5816	-0.04039
		(<.0001)	(<.0001)	(<.0001)	(0.6010)	(<.0001)	(<.0001)	(<.0001)	(0.3355)
	Volatility	0.02959	0.028965	2.7338	2.5357	0.04678	0.04891	2.4937	1.6598
		(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)
	SRD	-0.00094	-0.00218	1.4373	1.1615	-0.01064	-0.0121	1.9592	1.6604
		(0.5544)	(0.1654)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)	(<.0001)
	Year 2000	0.00126	0.00132	0.1324	-0.02039	-0.00161	-0.0013	0.4629	0.3415
		(0.2639)	(0.2425)	(0.0302)	(0.7547)	(0.4441)	(0.5321)	(0.0015)	(0.0321)
	Year 2002	0.00718	0.00756	-0.07881	-0.4780	-0.000745	-0.0006	0.5174	0.0429
		(<.0001)	(<.0001)	(0.2243)	(<.0001)	(<.0001)	(0.7878)	(0.001)	(0.8013)
	Direct ownership variables
	Main shareholder	0.0002759				0.000146
		(<.0001)				(0.0020)
	Second shareholder	0.000312				0.0000834
		(<.0001)				(0.4134)
	Discrepancy between	-0.00595				-0.00156
	cash flow and control	(0.0755)				(0.8176)
	rights for the main
	shareholder
	Ultimate ownership variables
	Main shareholder		0.0002258	-0.01566	-0.02062		0.00009	-0.01082	-0.01406
			(<.0001)	(<.0001)	(<.0001)		(0.0141)	(<.0001)	(<.0001)
	Governance dummies
	Double voting rights		-0.00479	0.2820	0.3099		-0.0019	0.0040	-0.01804
			(<.0001)	(<.0001)	(<.0001)		(0.2789)	(0.9734)	(0.8911)
	Pyramid		0.00931	-0.6970	-0.7199		0.00455	-0.4413	-0.01804
			(<.0001)	(<.0001)	(<.0001)		(0.0120)	(0.0004)	(0.3251)
	Adjusted R²	0.5943	0.5944	0.7723	0.4777	0.6226 0.6241	0.8254	0.4417

Table 8 . Ownership structures, means of enhancing control and the number of analysts that follow each firm

 8

  A. Characteristics of the firms for which the adverse component of spread can be calculated compared to other firms Adverse component of spread available

	Panel B. Adverse selection component of the spread and ownership characteristics
				Total sample					Family-controlled firms	Non-family controlled firms
	Models	1	2	3	4			5		6	7	8	9	10	11
	Intercept	0.2623	0.3010	0.1863	0.1994			0.2088	0.2153	0.1973	0.1991	0.2201	0.1961	0.2063	0.2320
		(<0.0001)	(<0.0001)	(<0.0001)	(<0.0001)		(<0.0001)	(<0.0001)	(<0.0001)	(<0.0001)	(<0.0001)	(0.0005)	(0.0004)	(0.0001)
	Control variables
	Log (market value)	-0.00821	-0.00879	-0.00767	-0.00811		-0.00830	-0.00846	-0.01045	-0.01069	-0.01055	-0.00898	-0.00890	-0.00856
		(<0.0001)	(<0.0001)	(<0.0001)	(<0.0001)		(<0.0001)	(<0.0001)	(<0.0001)	(<0.0001)	(<0.0001)	(0.001)	(0.0018)	(0.0030)
	Volatility	-0.00216	-0.00656	0.00237	-0.00325		-0.00340	-0.00526	-0.000209	-0.000364	0.0074	0.0155	-0.01244	-0.01337
		(0.8679)	(0.6164)	(0.8574)	(0.8037)			(0.7989)	(0.6955)	(0.9909)	(0.9843)	(0.6954)	(0.5586)	(0.6391)	(0.6347)
	SRD	-0.03564	-0.03366	-0.03598	-0.03489		-0.03845	-0.03734	-0.02722	-0.02729	-0.03465	-0.03930	-0.03811	-0.04580
	Number of observations (% of total) Year 2000 Number of family-firms Number of other-controlled firms Year 2002 Number of widely-held firms Ultimate ownership variables Market capitalization (€ million) Main shareholder Turnover (daily average in 000 €) Float (20% Threshold), in % of capital Second shareholder	(<0.0001) 0.00708 (0.1733) 0.06772 (<0.0001)	(<0.0001) 0.00744 (0.1517) 0.06831 (<0.0001)	(<0.0001) 0.00604 (0.2464) 0.05659 (<0.0001) 0.0005987 (<0.0001) 0.0006941 (0.0051)	(<0.0001) 0.00645 (0.2152) 0.06712 (<0.0001)		(<0.0001) 1087 0.00715 697 (0.1735) 202 0.06727 188 (<0.0001) Mean 2,878 0.0005178 9,227 (<0.0001) 56.21	(<0.0001) 70.13% 0.00751 64.18% (0.1533) 77.39% 0.06783 92.61% (<0.0001) Median 254 0.0006169 205 (<0.0001) 50.04	(0.0013) 0.00576 (0.4124) 0.07184 (<0.0001) 0.00120 (<0.0001) 0.00150 (<0.0001)	(0.0011) Adverse component of spread unavailable (<0.0001) (0.0006) (0.0011) 463 0.00544 0.00732 0.0115 0.01283 29.87% 389 (0.4373) (0.3014) (0.2698) (0.2331) 35.82% 59 0.07249 0.07389 0.05611 0.05960 22.61% 15 (<0.0001) (<0.0001) (<0.0001) (<0.0001) 7.39% Mean Median p-values from Student test (median test) (0.0001) 0.01438 (0.1967) 0.06065 (<0.0001) 97 25 0.000817 0.0007888 0.0002874 <0.0001 (<0.0001) 16.4 7.8 (<0.0001) (0.0006) (0.1554) <0.0001 (<0.0001) 39.20 37.48 0.0003678 <0.0001 (<0.0001) (0.4347)
	Ultimate % capital of the main shareholder Discrepancy cash flow / control		0.01335				38.87	41.50	0.02436	54.87	56.54	<0.0001 (<0.0001) 0.02295
	Ultimate % of voting rights of the main shareholder rights for the main shareholder		(0.0005)				46.52	52.80	(0.0020)	61.52	64.25	<0.0001 (<0.0001) (<0.0001)
	Ultimate % capital of the second shareholder Direct ownership variables						7.15	5.44		7.76	5.07		0.2178 (0.3489)
	Ultimate % voting rights of the second shareholder Main shareholder			0.0005758	7.81	6.20		8.22 0.00121	6.00		0.4384 (0.4229) 0.0007124
	Discrepancy between ultimate cash flow and control rights for the main (<0.0001)	0.3136	0.1948	0.1785 (<0.0001)	0.07652	<0.0001 (<0.0001) (0.0027)
	shareholder Second shareholder				0.0009334				0.00171			0.0009757
	Average relative effective spread -full day's data records, in %		(<0.0001)	1.73%	1.41%		4.70% (<0.0001)	3.93%	<0.0001 (<0.0001) (0.0477)
	Depth (daily average at opening in 000 €) Discrepancy cash flow / control			-0.01421		41.55	14.34		24.95 0.01824	6.96	0.0038 (<0.0001) 0.00602
	Adverse selection component of spread (in % of total spread) rights for the main shareholder		(0.2350)	0.07736	0.05409		na (0.3306)	na		(0.8513)
	Governance dummies
	Double voting rights							0.00101	0.0003960			0.00843		0.00223
								(0.8289)	(0.9363)			(0.2538)		(0.8021)
	Pyramid							0.01033	0.01507			0.02888		0.00501
								(0.0623)	(0.0181)			(0.0014)		(0.6031)
	Identity of controlling owner
	Family control dummy		-0.01776						-0.00732
			(0.0301)						(0.3912)
	Non-family control dummy		-0.02150						-0.01477
			(0.0203)						(0.1505)
	Number of observations	1087	1087	1087	1087			1087	1087	697	697	697	202	202	202
	Adjusted R²	0.3652	0.3674	0.3646	0.3652			0.3518	0.3519	0.3397	0.3454	0.3270	0.4054	0.3653	0.3356

In contrast to studies focusing on agency costs and private benefits extraction by a dominant shareholder whose voting rights exceed cash flow rights (for example Masulis, Wang and Xie, 2009),[START_REF] Bauguess | Recontracting shareholder rights at closely held firms[END_REF] show that in closely-held firms the shift to disproportionate voting and economic rights can benefit the firm's equity holders, including dispersed shareholders, by allowing risk averse dominant shareholders to reduce their economic ownership without losing control, and permit them to restructure the firm and improve performance for all shareholders.

Before September 20, 1999, trading was carried out from 10.00 to 17.00, and after April 3, 2000, from 9.00 to 17.00. After that date, the closing call auction has been postponed to17.35. Since April 23, 2001, the current schedules are in force.

partial financial support from Europlace Institut of Finance and Edith Ginglinger acknowledges financial support from the « Fédération Bancaire Française Chair in Corporate Finance ».

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2 For example Heflin and Shaw (2000), Sarin, Shastri and Shastri (2000) and Kini and Mian (1995).

3 For example La Porta et al. (2000Porta et al. ( , 2002)), Gompers, Ishii, andMetrick (2003), Masulis, Wang, andXie (2009). See [START_REF] Adams | One Share -One Vote: The Empirical Evidence[END_REF] for a review. 4 See [START_REF] Adams | One Share -One Vote: The Empirical Evidence[END_REF], for a review and Masulis, Pham and Zein (2009) for an assessment of costs and benefits of pyramids.


Gaëlle Blanco-Lainé
email: gaelle.blanco-laine@iut2.upmf-grenoble.fr

Eric Céret
email: eric.ceret@imag.fr

Sophie Dupuy-Chessa
email: sophie.dupuy@imag.fr

LEARNING SOFTWARE PRODUCTION BY PROJECT AND ACTION: CASE STUDY AND LESSONS LEARNT

Keywords: Technical institute, website development, project, action, creativity, autonomy, selfconfidence, engagement

Our context is the teaching of software production at the license level of a technical institute. Software production gathers together many knowledge and know-how in computer science i.e. managing projects, designing and developing the functionalities (data and programs) and the human-computer interfaces of the software. Our goal is to increase students' creativity and self-confidence in the concept application phase of the learning cycle. So we introduced pedagogy based on project and action, which followed the 5 key-principles of gamification. This case study has changed the students' approach and behaviour relatively to courses and teachers. They had the opportunity of putting together various courses and got a better perspective of each of them relatively to the others. It also has modified students' and teachers' engagement, increasing curiosity and satisfaction. We were also surprised by their creativity while selling their work to professionals.

INTRODUCTION

Our context of work is a technological bachelor degree. The general objective of Technical University (IUT) Information Technology departments is training professionals who participate in the design, production and implementation of Information Technologies (IT) solutions corresponding to users' needs. The degree is constrained by the existence of a National Pedagogical Program requiring thematic volumes and schedules for the implementation of this degree.

The National Pedagogical Program is divided in traditional business areas: 1) "computing" disciplinary fields, like Algorithms, Hardware architecture, Database management systems or Analysis, design and applications development and 2) disciplinary fields covering scientific, social and human culture, like Mathematics, Economy, Law, Communication and English. Teachers work in teams by specialty area and there is a small overlap area. This fragmentation leads to a sectored teaching, which in turn makes some students lacking a global understanding of IT techniques and encountering some difficulties for articulating and linking efficiently the various approaches.

Although the courses attached great importance to training and despite the work that students have to do frequently in pair, we observe difficulties for students to transform knowledge into know-how. For instance, an excepted know-how would be to choose the appropriate technique from the various possibilities they have learned. So our concern applies to the concept-application phase of the teaching life cycle [START_REF] Karplus | Science Curriculum Improvement Study, Teacher's Handbook[END_REF] where students must try out their new ideas by applying them to situations that are relevant and meaningful to them. It is also related to the Elaboration phase of the 5E learning cycle, in which students' understanding and skills are challenged through new experiences in order to make them "develop deeper and broader understanding, more information, and adequate skills" [START_REF] Bybee | The BSCS 5E instructional model: Origins and effectiveness[END_REF]. During application of a concept, learners may discover new information that may cause a change in the learners' understanding of the concept being applied. Thus, this step is crucial for Learning as it permits the process of learning to be cyclical.

The reform of the National Pedagogical Program, which took place in 2013, gave us the opportunity to experiment new teaching methods for facilitating the construction of know-how in the concept application phase of learning. One of the 2 nd year modules entitled "Methodology for software production" targets:

• Requirements analysis for the design and development of information systems in an organization;

• Project organization and management for covering the software life cycle and integrating all the required points of view: work organization and strategy, users expectations, project management, quality and technology, corrective and evolutionary maintenance.

This module is defined as including (1) technical topics such as functionalities (data and programs) design and development, business processes analysis and modelling, production of the technical specifications and the software human-computer interfaces and (2) management aspects like preliminary studies and requirements analysis, elicitation of the standards to be applied for software (e.g. W3C) and quality (e.g. ISO/IEC 9126 [3]), project organization and follow-up and communication.

In the setting-up of this module, the teaching staff pursued the following objectives:

• Promote mobilizing existing knowledge,

• Application in a realistic context,

• Acquisition of new knowledge in semi-autonomy,

• Developed students' self-confidence and creativity.

This module also allowed us to promote transdisciplinarity between teachings. This should allow to highlight the overall global consistency and the existing interconnections between the various modules of our training cursus.

In this context, we expected students to encounter the following difficulties: 1) the mobilization of already acquired knowledge and know-how; 2) their application in a realistic situation and 3) the need to acquire new knowledge in semi-autonomy.

We therefore introduced a pedagogy based on project and action, which also uses gamification elements. This paper presents the setting-up of the "Methodology for software production" module, our educational choices and the lessons learnt from this case study.

The following section describes the implementation of the "Methodology for software production" module. The next section discusses the lessons learnt and their limits. Finally, the paper ends with some conclusions and perspectives.

THE "METHODOLOGY FOR SOFTWARE PRODUCTION" MODULE

Overview

We chose to implement this module ("Methodology for software production") as a project module based on a semi-autonomous work supervised by a multidisciplinary teaching team.

It concerned about 100 students. The teaching staff was composed of 5 pairs of teachers grouped by area of expertise, i.e. (1) project management, (2) computer modeling, (3) Human Computer Interaction and web interfaces, (4) IT development and (5) communication.

The project to be achieved by students was large enough to require them to work in groups. According to the estimated amount of work, we chose to create groups of 6 or 7 students. The students were in charge of creating and organizing these groups. All groups had the same project to realize. The theme was the creation of a responsive website (i.e. available on a laptop as well as on smartphones, tablets and so on) a for tourism in mountain. The requirements were really simple: "Gather your team together and revolutionize the way of organizing mountain holidays. Imagine an online service, an innovative application, a new way of preparing one's holidays by letting the user build a 'shopping cart of leisure'... "

The project lasted 15 weeks divided into 3 iterations, the last week being full-time dedicated to the "marketing", i.e. to the definition of the product communication.

Organisation

The 14 first weeks: development of IT solution

During the 14 first weeks, as shown on fig. 1, the students had to produce a functional prototype, here a website. During this time, they had 4 hours planned each week in their schedule. Teachers were facilitators: they met students regularly and were also available during the weekly 4 hours to answer their questions. Some occasional lectures have been set up on specific aspects, which were not known by students at this time. They mainly concerned modeling, like process modeling with BPMN [START_REF]OMG Business Process Model and Notation v2.0[END_REF] or feature and data modeling with UML [START_REF]OMG Unified Modeling Language (OMG UML) v2[END_REF].

Students were not free about the strategy for developing their website. We imposed a semi-agile logic for the project life cycle:

• A first iteration centered on requirements gathering, analysis of the existing, leading them to define their project scope, and create some mockups • The two following iterations have been devoted to the prototype development, the students had to produce the software source code An evaluation took place at the end of each iteration. Each evaluation included: an oral presentation by the group (containing a presentation on the status of the project advancement and, in iterations 2 and 3, a scenario-based presentation and/or demonstration), a project file and an individual oral assessment. Each group was evaluated by two teachers with different expertise areas.

The project file had to be delivered one week before the oral presentation and was used as a basis for defining the individual questions. The purpose was (a) to focus on the expected improvements for the next iteration and (b) to avoid excessive specialization of students in the group -each student was taking a question draw -and make them share knowledge and skills acquired during the project.

We imposed the structure of the project file, which was evaluated at the end of each iteration. The students had to correct and enrich this document throughout the project. The imposed structure was divided in three parts:

 Project scope, based on (5WH): WHO, WHAT, WHERE, WHEN, WHY and HOW.

o WHO? Identifies the stakeholders. It describes the business domain and its specificities, identifies the policymakers and their expectations, the users and their needs and the specific skills required for the development team. For instance, the users of a website for organizing holidays could be families, policymakers could be tourism offices or ski resorts.

o WHAT? Describes the project, especially the functional requirements, such as booking a room in an hotel, a table at a restaurant or skiing lessons.

o WHERE? Describes the context, for instance looking at existing mountain websites and more largely to merchant sites. In fact, this is part of competitive intelligence. The goal is also to identify either or why the policymakers need the intervention of contractors.

o WHEN? Describes the temporal constraints and the project planning. In our specific case, the students had no choice about the temporal structure, which was defined by the three iterations. They could choose and use planning tools, such as GANTT charts [START_REF] Gantt | Work wages and profit[END_REF].

Fig. 1 -project life cycle

o WHY? Identifies the objectives, expected benefits from the project: whishes and requirements (expressed or implicit) and leads to define SMART 1 goals [START_REF] Doran | There's a S.M.A.R.T. way to write management's goals and objectives[END_REF]. For instance, improve the image of the resort or increase its attractiveness.

o HOW? Expresses the constraints, risks and possible solutions. The constraints refer to anything (temporal or technical) that could restrict the designer's freedom or impact on project. Risks identification is meant to specify mitigation strategies (i.e. strategies for reducing these risks), accordingly to the risks criticality (i.e. impact and emergence probability). A result of this analysis could be the definition of indicators and a dashboard for following the criticality. For instance, an important risk for the students was the lack of time, which could be mitigated thanks to the project evolution followup.

 Functional expression of needs, which describes the user's requirements and infers what the software should do. This activity often implies to use modeling tools. It includes:

o A description of the expected functions, distinguishing main functions (which must be available in the final prototype) and complementary functions (which will be -fully or in degraded mode -developed if there is enough time). For instance, as shown on fig. 2, the user needed to book some activities (skiing material, going to the restaurant,...).

o A description of functions hierarchy, identifying what functions will be developed during which iteration. It allows to follow the initial planning and identify the remaining functions to produce. For instance, the initial planning might start by developing the function of booking housing.

o A specification of the expected software quality level (with some flexibility): according to ISO/IEC9126 [3], the students had to specify 6 criteria they aimed at achieving. For instance, the software should ensure data security, especially as banking information will be recorded during payment.

 Solutions

o Technical solutions detail the functional specifications, refine the User Interfaces mockups and their ergonomic evaluation (as defined in [START_REF] Bastien | Ergonomic Criteria for the Evaluation of Human-Computer Interfaces[END_REF]), as well as the implementation aspects, such as the technical environment, the programming languages and tools to be used. A comparative description of the various technical possibilities (their advantages, complexity, benefits,...) is also expected. Figure 3 presents an example of mockup realized during this stage by a group of students. o Project organization includes Work Breakdown, which identifies the tasks, their distribution and the corresponding schedule, that is in turn followed for tracking and analyzing differences between expected and realized tasks durations during iterations 2 and 3.

Last full-time week: communication and marketing strategy

Following the website development, students had a full-time week to define their communication strategy and produce marketing materials. This week was supported by the communication teachers with the support of e-learning technicians. For instance, one of the groups, who produced a website named BookYeti, imagined a communication campaign based on the Yeti, including a logo, a video, a sticker and a dramatized presentation, as shown on figure 4.

The final result was evaluated by a jury composed of teachers and experts in the development of IT solutions, the industrial transfer of researches or the creation of start-ups. All students could also vote -as shown on figure 5 -for each project, thanks to VotAR 2 .

All along this final stage and beyond the technical dimensions, we wanted to show how important it is to master communication aspects when developing IT solutions. 2 VotAR is an Augmented Reality audience voting system. Available on Google Play, please refer to libre-innovation.org.

Educational choices

As we mentionned in the introduction, the main objective was to support a concept application phase of software development by leading students to mobilize their existing knowledge and to apply it in a realistic context. To achieve this objective, we chose a project-based pedagogy. It completes the numerous existing experiences [START_REF] Thomas | A review of research on project-based Learning[END_REF] by proposing a transdisciplinary approach where "life skills" or "process skills" including social skills, group process skills, multiple intelligences, and dispositions for independent learning are required. It was also a long-term project created to be realistic thanks to a context studied with the 5WH (Who, What, Where, Why, When, How).

To develop new knowledge in semi-autonomy, teachers were available as facilitators. They gave occasional lectures about new knowledge and provided guidance during the project development.

The project mode in semi-autonomy was also expected to develop students' self-confidence. Experts' feedbacks at the end of the project were also presented as very important, because they show students that their projects are interesting outside their educational scope.

To increase creativity, the subject of the project (website for tourism in mountains) was coarse-grain and needed to be refined to propose a solution. We also encouraged students in thinking about innovative solutions by asking them to study existing websites and to propose something new.

The module was designed so as to encourage students' engagement by using gamification elements. We followed the 5 key-principles of gamification:

 The learners' choice must have a significant effect: in our case, the students could choose the features and human-computer interfaces of their website, as well as their professional context (e.g. if they were sensed to be a start-up with a new idea, a web agency working for a mountain resort...);

 The teaching situation in the game must be contextualized: here, students were considered as professional development teams who have to develop the website;

 The game must be credible: there was a real need for such a website and there was no existing site answering all the given requirements;

 There must exist several success ways: many different approaches, services and look and feel could be explored;

 Gamer must be able to define his/her own objectives. At the beginning, students had to define the specifications of their own website based on their choices.

Moreover, we added some challenges by rewarding the three best technical projects and the three best "project sellers". We also organized an evaluation where students had to play the role of sellers.

In this situation, they were in front of a non-academic jury composed of experts, teachers and all other students.

Fig. 5 -Students voting with VotAR

At the end of the module, we proposed to students to fulfill a questionnaire. By mistake, some students answered by group, while the others gave individual answers, giving a total of 18 answers. Therefore, we can only make a qualitative analysis of their feedbacks.

The goals defined for this module have been mainly achieved. We have seen an increase in students' satisfaction, engagement and autonomy.

The global satisfaction index is 8 on a maximum of 10. Many students mention how much they learned about project management, work organization and communication within a team. They also estimate that they have learned a lot about techniques and tools. One group even thinks that this module "was certainly the main source of knowledge during the semester".

According to their statements and our sightings, our students were highly involved in this module. Indeed, students estimate that each of them worked between 90 and 100 hours when the module is sensed to require about 75 hours of work per student.

Moreover, during the "open house day" of our institute, several students' behaviors demonstrated their commitment to this module. First, the videos they had prepared for the final presentation were displayed in the ground floor, in the IT department room, and the students were very proud of their achievements. Moreover, having followed this module modified their perception of the cursus and their ability to present it: they had became able to present much more easily its key objectives and content, explaining several modules by their usefulness in the "Methodology for software production" module. One of the groups didn't want to stop their "mission" so soon and they participated to a national challenge named "the mobile banking factory3 ".

We noticed that our students increased their capacity of working autonomously. The first remark we made is that they increased their capacities for searching information and self-training, e.g. with online documentation and tutorials. Many of them were reluctant for doing this before this module. For instance, one group explored management tools by themselves and chose to use IceScrum 4 , a platform for agile developments.

Another goal was to make students creative. It is difficult to state that we increased creativity. At least, we were very satisfied by their findings. Some groups had good ideas when proposing new services for holidays in mountains (for instance, one group suggested activities packages according to the customers' age, another one had the idea of collaborative holidays). We were surprised by their creativity in communication. If Fig. 4 shows an excerpt of the best communication campaign, all groups created very good communication support like video, ad messages in which they showed a lot of humor and imagination.

We also noticed their decreasing need for teachers' guidance along the module correlated with an increasing quality of the project file, which we interpret as a growing autonomy. When interviewed Fig. 6 -Students evaluation over technical, management and communication aspects about their novel ability to take a step back, students referred almost systematically to the project module.

Most of the produced prototypes met requirements, some even being of professional quality. We have the full results for the 14 first groups, the 4 others have not yet finished the module, as their cursus is out of phase. As shown on figure 6, two groups (over 14) have been evaluated as very good on technical, management and communication aspects. Two groups have produced inadequate technical and management work and just fair enough communication material. All the others have globally reached the objectives.

Beyond this global evaluation, some other aspects are worth enough noting. The students testify having increased their technical competencies, particularly in JavaScript, PHP… They also improved their communication abilities, because they had to speak in front of a jury made of two teachers at the end of each iteration and in front of a whole amphitheater at the end of the project. Moreover, they learned how to create a "pitch" (i.e. a very short speech expressing the key points of their proposal), to handle the tools for creating their communication support (slides, videos, image processing editor,…).

The students also acquired know-how, especially for starting and managing a project with professional deliverables and skills.

Beyond our own feelings, a global feedback given by the teaching team of the department is that this work induced a positive evolution in the relationship between them and the students who showed more confidence and attention.

All these good results must be nuanced by the fact that it was the first time that we proposed such a big transdisplinary project to students. They might be a novelty effect, which could improve the feedbacks of this year. We will see if the positive effects of project-based pedagogy continue on long term.

Even during this first year, we have already noticed some limits. Indeed, even if the students mainly approved the organization of the teaching activities on this module, they mention some difficulties, such as the risk of discovering troubles lately due to the granted freedom or their feeling of lacking support in group management, and more particularly about conflict management.

We also realized that it will be necessary to provide, during the project start, a more precise scope and to specify expectations in terms of deliverables, particularly regarding explanations about the structure and expected content of the project file.

Finally, according to the workload estimated by the students, we also believe that the chosen topic was probably too ambitious. Indeed, as already mentioned, students say they have been working between 90 and 100 hours whereas, when applying the calculation rules for ECTS 5 , the workload should have been 75 hours maximum.

CONCLUSION AND PERSPECTIVES

In this paper, we presented how we built a module for increasing students capacities of mobilizing their existing knowledge in a realistic context, where they were expected to act like professionals, and for increasing their autonomy, self confidence and engagement. We also intended to promote transdisciplinarity and highlight the global consistency.

We implemented a pedagogy based on project and action in a module dedicated to the production of an IT solution. It had the characteristics of being transdisciplinary and of requiring life skills. We presented the details about the module organization and the good results in terms of students' increased autonomy, satisfaction, engagement and creativity.

Considering all these results, the module structure will be refined and will take place in the training with the same form in the coming years. We will refine its organization while keeping the gamification elements which contribute to make it a success. This case study clearly shows us the interest of introducing games and action in pedagogy. By sharing it, we would like to help teachers in seeing the practical benefits of project-based pedagogy with gamification.

Fig. 2 -

 2 Fig. 2 -an example of expected functions made by students (in french)

Fig. 3 -Fig. 4 -

 34 Fig. 3 -an example of mockup made by students (in french)

Please see http://mobilebankingfactory2.bemyapp.com

Please see http://www.icescrum.org

European Credits Transfer System

ACKNOLEDGEMENTS

This project has been supported by the French government's "Investment for future" program IDEFI (ANR-11-IDFI-0031) (initiative for excellence in innovative training).

We also thank our colleagues who took part to the project: Francis Brunet-Manquat, Annie Culet, William Delamare, Diane Dorelon, Sylvie Pesty, Dominique Rieu, Wellore Tamboura.