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Is there tunneling in Small Business Groups?

Evidence from French SMEs.

Anaïs HAMELIN*

LaRGE, Institut d’études Politiques, Université de Strasbourg

CEB, Solvay Business School, Université Libre de Bruxelles

Preliminary version: February 2009

Abstract:

Using a unique firm level data set on ownership and balance sheet information, we test for

the influence of the separation between ownership and control on firm performance and

risk. This paper fills a gap in the empirical governance literature on the agency cost of

pyramidal control by investigating if it is influenced by group size. It also shed light on the

use of complex ownership structure for risk management.

This paper investigates the interaction between complex ownership structure and group size

on firm individual performance and risk. Results point out that corporate governance issues

related to complex ownership structures are influenced by group size. They also support the

idea that risk management practices cannot be understood in a corporate governance

perspective without consideration of group size.

Key words: Ownership, Control, Group Size Effect, Risk management, Tunneling

JEL Codes: G32, G34

* 47, Avenue de la Forêt-Noire, 67082 Strasbourg Cedex. Anais.Hamelin@unistra.fr, Tel : 0388417737

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1. Introduction

The influence of ownership structure on firm performance is widely studied. On the one

hand, large shareholders have strong incentives to maximize their firm’s value and have the

incentives to collect information and oversee managers (Jensen and Meckling (1976);

Shleifer and Vishny, 1986)). On the other hand, ownership concentration can induce costs as

“large shareholders may represent their own interest, which need not coincide with the

interests of other investors” (Shleifer and Vishny (1997), p758). Empirical evidence provides

strong support for this two sided incentive effect of concentrated ownership. Most studies

find a non-monotonic relation between ownership concentration and firm performance

(Morck et al. (1988); McConnel and Servaes (1990); Denis et al. (1997); Mueller et Spitz

(2006)).

This topic is quite important because widely held corporations are quite exceptional outside

the United States and United Kingdom. Control concentration might result from several

mechanisms: family control, state control, confusion between ownership and management,

complex ownership structures. Pyramid structure is one of the mechanisms used to

concentrate corporate control around the world. According to La Porta et al (1999), 38% of

the larger French firms are characterized by pyramidal control.

In complex ownership structures control concentration can be boosted by organizational

features. Pyramidal structure is a mechanism that introduces a separation between control

and cash-flow rights. This then allows the ultimate shareholder to secure control rights,

without commensurate cash flow rights (Almeida (2006)). In pyramid controlled group

performance is driven by two opposite incentive mechanisms: a positive effect due to the

shareholders’ cash-flow rights and a negative entrenchment effect linked to potential

private benefits of control related to their control rights. Hence, firm performance should be

influenced by the degree of separation between control and cash-flow rights of the

controlling shareholder. Empirical evidence (Classens et al. (2002), Bae et al. (2002); Joh

(2003); Lins (2003)) tends to confirm the negative impact of pyramidal control on firm

performance, for large companies.

Affiliated firms, in which the ultimate shareholder’s cash flow rights are small whereas he

controls the firm, are then exposed to tunneling. Johnson et al. (2000) define tunneling as

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the act of transferring value from one firm to another in a group. Within group wealth

transfers might then lead to the expropriation of minority shareholders. Indeed, ultimate

shareholders have distorted incentives due to the divergence between their control and

cash-flow rights. Therefore, tunneling should occur in firms where their cash-flow rights are

relatively small, thus where minority shareholders stakes are important. Bertrand et al

(2002) found strong support for tunneling value decreasing actions in business groups.

Evidence on the agency cost of pyramidal control on firm performance and tunneling is

widely reported, but only for large business groups ((see Morck et al. (2005) for a survey).

However, complex ownership structures are also quite common in smaller organizations.

Small business groups correspond to business groups which economic weight is the same as

an SME. In France, firms affiliated to small business groups have doubled in ten years and

they now represent one third of French firms (Loiseau (2001); Bloch and Kremp (2001);

Nahmias (2007); Cayssials et al.(2007); Kremp and Philippon (2008)). Existing empirical

studies on small business groups focus on the effect of group affiliation on financing (Kremp

and Sevestre (2000); Kremp and Philippon (2008); Gorodnichenko et al. (2008)).

Yet, Bloch and Kremp (2001) underline the presence of pyramidal structure in small business

groups. We complement their work by looking at the extent of the agency cost of pyramidal

control in small groups.

Risk management literature mainly focuses on the agency cost between the creditor and the

shareholder (risk-shifting). However, a similar agency cost might also exist between

controlling and minority shareholders in pyramidal structures, leading to “risk tunneling”. In

general, Commercial law recognizes the principle of controlling firm limited liability in case of

bankruptcy of an affiliated firm1. In those cases, controlling shareholders have the possibility

to secure assets in one firm, and concentrate risk in firm’s where their cash-flow stakes are

lower. Thus, firms where the separation between control and cash-flow rights is higher

should be riskier.

However, this “risk tunneling” should be reinforced by the controlling shareholder net worth

exposure to idiosyncratic risk. In fact, as net worth exposure to idiosyncratic risk increases,

1 Relative to this topic French commercial law is quite protective of controlling companies as there is only three restrictive exceptions to this principle (French commercial code: C.COM art L.621-2; L.651-1 and L.651-1).

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owners get stronger incentives to secure part of their assets through legal settings.

Shareholders of small structures are exposed to high level of idiosyncratic risk due to the

under diversification of their assets portfolio. Indeed, small businesses are characterized by

intermingling between personal and professional patrimony (Berger and Udell (1998); Srank

& Yilmazer (2006)). Moskowitz and Vissing-Jorgensen (2002), document that owners of

private companies have invested 41% of their net worth in private equity. Therefore, a shift

from value decreasing toward risk enhancing tunneling as the size of complex ownership

structures decreases is expected.

The aim of this paper is to assess the interaction between complex ownership structure and

group size on firm individual performance and risk. First, the impact of separation between

ownership and control on performance and value decreasing tunneling is explored. Then,

our sample allows to test for the influence of group size on those patterns. We also observe

the impact of separation between ownership and control on firm individual risk. Finally, we

assess whether size creates a shift from value decreasing toward risk enhancing tunneling in

complex ownership structures.

We use a firm level data source from Coface Service that provides information on ownership

structure and accounting variables for French firms. One of the important strengths of this

dataset is to contain almost exhaustive information on capital links. This allows identifying

pyramidal structures and built integrated control measures. The dataset also contains

detailed balance sheet information on an eight-year period (1997-2003).

Empirical results show that size has to be taken into account when considering corporate

governance issues. Results provide support for the expropriation of minority shareholders by

controlling shareholder in group pyramid. However, they underline that this agency cost is

influenced by group size. Indeed, pyramidal control has a significant influence on firm

performance only when interaction effects with group size are introduced.

Moreover, results point out that separation between control and cash-flow rights has no

effect on firm’s individual risk. However, the corporate governance effect is offset by the size

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effect. Indeed, results show that the probability of risk enhancing tunneling increases as

group size decreases, whereas the separation between ownership and control become

insignificant. Indeed, risk patterns are influenced by the position of the firm in the group

(controlling or not), but not by the extent of separation between control and cash flow

rights.

Overall, results point out that corporate governance issues related to complex ownership

structures are influenced by group size. They also support the idea that risk management

practices cannot be understood in a corporate governance perspective without

consideration of group size.

The remaining part of this paper is structured as follows. Section 2 describes the data set,

explains how groups where identified and defines the variables; Section 3 presents the

methodology and shows the empirical results; and Section 4 concludes.

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2. Data and variables description

The initial database is provided by Coface Service and contains information on ownership

structure and accounting variables for French firms. On the one hand, the database provides

exhaustive information on capital links (1 900 000) between French firms in 2003. Each

observation identifies the owning firm and the owned firm by its Siren (French national id of

firms), the level of ownership (1 if the owning firm has direct control, and greater than 1 if it

is indirect control), and the cash-flow rights of the ultimate shareholder firm. On the other

hand, the database provides individual balance sheet information on 643 000 French firms

from 1997 to 2003.

a. Group identification

A shortfall of the initial database is that it does not identify groups, but only capital links

between firms. Thus, the initial database has to transform in order to identify groups.

We adopt the criteria of majority control2 to distinguish between affiliated and independent

firms3. Then, a group corresponds to a chain of majority control relationships: the ultimate

controlling firm controls (its direct cash-flow rights are greater than 50%) a firm that in turn

controls another firm, and so on.

First, ultimate controlling firms, independent firms (where direct ownership by another firm

is lower than 50%) which have majority control on other firms, are identified. To do so, we

exclude from the database all owning firms which are controlled (directly owned at more

than 50% by another firm), and non-controlling firms (with direct cash-flow rights lower than

50%).

Secondly, the chain of control is rebuilt identifying for each ultimate controlling firm the

firms it controls directly and majoritarly. Then, for the controlled firms just identified, we

identify the firms they control, and so on. We stop the reconstitution when the controlled

firm does not controls majoritarly another firm. 12307 groups, with 34713 firms, were

2 For a detailed discussion on this topic see Chapelle and Szafarz (2005, 2007). 3 The majority of studies cited before adopts a 10% or 20% threshold for control, however as the paper focuses on small business groups, where control is concentrated, the threshold of 50% seems more accurate to identify real control. Moreover, adopting majority control criteria avoid to be confronted with situations where two firms control the same firm.

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identified according to the majority control rule and for which balance sheet data was

available for all firms belonging to a group.

b. Firm level governance variables

In our regression analysis, we relate firms’ performance and risk patterns with a corporate

governance variable: the separation between control and cash-flow rights.

Due to data limitations we only focus on pyramid control mechanism for separating control

from ownership. Therefore, cross-ownership and dual class shares are excluded from the

analysis4.

Ownership5 is associated with the property rights of the ultimate controlling firm on a

controlled firm’s cash-flow. Ownership is computed as the product of direct cash-flow rights

along the chain of control. In the sample the average ownership in controlled firms (22406)

is quite high (77%). This result is in part driven by the strict definition of group affiliation

adopted.

In turn, control is associated with the voting rights of the ultimate controlling firm. This

notion has been widely studied in the literature, but yet there is no common agreement on

its definition.

La Porta et al (1999) considers that a shareholder has control on a firm when either its direct

or indirect voting rights exceed 10% or 20%. However, Biebuyck et al. (2005) underline the

inconvenient of such method: it does not allow to compute the control coefficient in the

intermediary situations that can arise as they only determine when a firm controls another.

Therefore, the control variable was computed according to the method of Classens et al.

(2000). They define control as the weakest link in the chain of control rights. They use the

threshold of 20%, we use the same method but with a threshold of 50% to built the Control

4 We make the assumption that there is no separation between control and cash-flow rights implied by those

mechanisms in sample firms. This simplistic assumption might undermine the estimation of separation patterns. However, empirical evidence tends to show that they are relatively unused mechanisms compare with control pyramids to separate control and ownership. La Porta et al. (1999) results suggest that dual class shares are not a central mechanism of separating ownership and control ( in France it takes about 19.9957 percent of capital to control 20 percent of the votes), as well as cross-shareholdings. 5 The transformed database allows to identify control patterns between firms, but contrarily to the literature on

ultimate ownership we do not have the information on the controlling shareholder. Thus, we focused our attention on the controlling firm. Control patterns might therefore be overestimated for large firms compared to smaller firms, where ultimate shareholder control tends to be more concentrated.

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variable. It is a continuous variable that retains, for each group, the lowest value of direct

cash-flow rights in the chain of control.

As mentioned above, the analysis focuses on pyramidal control mechanism for separating

control from cash-flow rights. Pyramid control variable corresponds to the difference

between control and ownership.

To account for the non linear effect of control resulting from voting rules we use a variable

that takes value 1 if there is a separation between control and ownership and 0 else. On

average the gap between control and ownership is low (6%). The median (0) underlines that

the distribution is left skewed, indeed only 8% of sample firms undergo pyramidal control.

Thus, in many cases complex ownership structures do not imply separation between control

and cash-flow rights. This result is also partly driven by the fact that an important proportion

of groups (30%) are only compounded of two firms.

One important issue with our data is that we only have information on ownership for one

year (2003), and that we cross it with panel information on several years, however

ownership patterns tend to be stable across time (Khanna, 2000). Moreover, we focus

private firms, where ownership patterns tend to be even more stable due to the illiquidity of

shares.

c. Group size variables

Alternatives measures of group size are considered. Firstly, the sum of affiliated firms

turnover (Aggregated Turnover), it has the advantage of being a continuous variable, but

presents the inconvenient that it might overestimate group economic weight due to intra-

group business flows. Alternatives measures are the number of firms in the group (NbFirms),

and the number of level in the control chain (Level). Descriptive statistics, reported in table

1, underline that small groups are highly represented in the sample, the important gap

between mean (148 M€) and median (16,5 M€) indicates the large range of group size in the

sample.

Group size variables are used to explore the relevance of a size effect on the influence of

pyramidal control on performance and risk patterns. Therefore, we need to be aware of

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possible dependence between group size variables and pyramidal control variable. Indeed,

results on the interaction between group size and separation between control and cash-

flows rights could be driven by the fact that pyramidal structure is positively correlated with

our measures of group size.

Table 2 reports correlations between those variables and highlight the fact that Level and

Nbfirms are significantly correlated with the pyramidal structure variable. This result is not

surprising as pyramidal control depends on the existence of at least an intermediate level in

the group. For the Nbfirms it is also quite intuitive that more there is firms in the group

higher it is the probability that distortions between control and cash flow rights might be

introduced.

For the reasons afford mentioned we decided to use the aggregated turnover, even if it

might overestimate the group economic weight, as the proxy for group size.

d. Performance and risk measures: how to measure tunneling?

In the corporate governance literature the Tobin Q is generally used as a proxy for firm

value. However, we have to rely on unconsolidated accounting data, because an important

proportion of sample firms are private firms. Therefore, we use the return on asset (ROA) to

proxy for firm performance. This measure is also often used in corporate governance

literature as an alternative measure of performance.

We rather used the ROA than the return on equity (ROE) because the former presents the

advantage of not being affected by the financial and amortization policy of the firm. Thus, it

better reflects firm’s exploitation performance.

The ROA is computed as the ratio of the EBITDA to total asset. We used the average of the

annual individual ROA available from 1997 to 2003, because many observations concern

small firms that tend to have higher cyclical volatility. Then, using average performance

measure on the period allows to limit this size effect on performance measure. Moreover,

this allows to maintain coherence between the performance and risk measures.

Indeed, to asses firm’s individual risk we use the standard deviation of the ROA on the 1997-

2003 period. This measure is commonly used to asses’ firm individual risk (Khanna and

Yafeh, 2005).

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Those measures of performance and risk can raise concern in the specific context of testing

tunneling. Indeed, tunneling predicts that firms with high degree of separation between

control and cash-flow rights will tend to have a lower performance than the other firms in

the group where controlling shareholder stakes are larger. Thus, testing for tunneling implies

to rely on a measure of individual performance relative to the performance of the other

firms in the group. Thus, we computed the ROA and ROA standard deviation at group level,

using the average ROA and ROA standard deviation of the group’s firms.

Then we obtained a measure of performance and risk tunneling simply by computing the

difference between firm individual performance or risk and the group performance or risk.

The following qualitative variables indicate if firm individual risk or performance is rather

higher or lower than group risk or performance.

- Nivperf = 1 if firm ROA > Group ROA and Nivperf = 0 if firm ROA< group ROA, thus

if there is value decreasing tunneling.

- Nivrisk = 1 if firm risk > Group risk, thus if there is risk tunneling , and Nivrisk=0 if

firm risk< group risk,

e. Control Variable

Firm performance and firm risk might be influenced and determined by a large range of

variable. To control for possible omitted variable problems we introduce control variables in

the regressions. We use standard control variables: firm size, age and industry dummies.

Technological constraints affect firm’s performance and risk. Those constraints result from

the importance of economies of scale in the industry were the firm operates, the age of the

firm and characteristics of the market such as its size or the intensity of competition. In

order to take into account those factors we control for firm’s industry, size and age.

The firm’ sector refers to the belonging of the firm to one industry in a 17 sectors

classification (very close to the NACE classification). Firm’s age is the log of the year since its

creation. Finally, firm’ size is the log of its turnover.

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3. Methodology and results

We seek evidence on the influence of group size on tunneling patterns in pyramidal

controlled groups. First, we assess to what extent group size influences value decreasing

tunneling in firms where there is a separation between control and cash flow rights.

Secondly, we investigate whether group size creates a shift from value decreasing toward

risk enhancing tunneling.

a. The influence of group size on value decreasing tunneling

According to the literature, controlling owners of pyramidal groups are most likely to

sacrifice the interests of minority shareholders in firms where there is a separation between

control and cash-flow rights. Several empirical studies present evidence consistent with such

effect. Classens et al (2002) observe that firm value falls when there is a separation between

control and cash flow rights in publicly traded corporations in eight Asian economies. Joh

(2003), finds similar results using data on publicly traded and private firms from Korea.

Finally, Lins (2003) observe a negative influence of excess of insider control rights over their

cash flow rights on firm performance in emerging markets.

Thus, we estimate equation (1), using ordinary lest square method, to test to what extent

the separation between control and cash flow rights influences firms’ performance,

controlling for firm size, age and industry.

iiiii mmiesIndustryDuAgeSizeDivROA εβββα +++++= 321 (1)

Where i indexes firms, ROAi is the firm average return on asset for the 1997-2003 period,

Sizei is the log of the firm turnover, Agei is the log of the firm age and ε is the error term. Divi

is equal to 1 if there is a separation between control and cash-flow rights in the firm, and 0

else.

Column 1 in table 3 shows that pyramidal control, proxied by Div, does not influence

significantly firm performance in our sample.

However, results could be driven by the high heterogeneity of sample firms. Thus, we focus

on the impact of pyramidal control on firm intra-group relative performance (NivPerf). In

order to estimate equation (2) we use a binary logistic regression model.

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mmiesIndustryDuAgeSizeDivNivPerfP iiii ++++=+== 321 )0()0( βββα (2)

Where )0( =iNivPerfP is the probability that firm performance is lower than the average

performance of firms affiliated to the same business group. 0=iDiv models the impact of

non separation between control and cash-flow rights on the probability of value decreasing

tunneling. Therefore, if 1β is negative the separation between control and ownership

influences positively the probability of value decreasing tunneling.

Results in column 2 of table 3, indicate that pyramid controlled firms are no significantly

more likely to have a lower performance than their group average performance.

Overall, those results do not provide support for the existence of value decreasing tunneling

at the expense of minority shareholders in pyramidal controlled groups. However, this

conclusion might be driven by group size.

Thus, we return to the previous specifications, and introduce interaction terms between

pyramidal control and group size. This method is commonly used in small business literature

to underline size effects (Beck et al (2008)). Specifications 3 and 4 allow to assess the

variation of the relation between pyramidal control and performance patterns according to

group size (GSi).

iiiiiiii IndustryAgeSizeGSDivGSDivROA εβββββα +++++++= 54321 * (3)

IndustryAgeSizeGSDivGSDivNivPerfP iiiiiii +++++=+== 54321 *)0()0( βββββα (4)

Hence, we explore whether the insignificant relation between pyramidal control and

performance patterns varies according to group size. Coefficient β3 indicates if an increase in

group size does increase or decrease the influence of separation between control and cash-

flow rights on firm performance.

Results, in column 3 of table 3, show that separation between control and cash flow rights

has a significant negative impact on firm performance when group size is introduced in the

regression. Moreover, the coefficient of the interaction term is positive and significant,

indicating that group size increases the negative effect of pyramidal control on firm

performance. The estimates so far can be interpreted to show that performance of firms

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affiliated to bigger groups is more likely to be impacted negatively by the separation

between control and cash-flow rights. Those results suggest the existence of a size effect on

tunneling.

Maximum likelihood estimators reported in column 4 of table 3 confirm the previous result.

Indeed, when we introduce interaction effect between group size and pyramidal control we

observe a significant positive impact of the separation between control and cash-flow rights

on the probability that firms’ performance is lower than its group average performance.

Overall, results suggest that group size influences the impact of separation between control

and cash-flow rights on performance. Indeed, results show that the separation between

control and cash-flow rights does not affect significantly firm individual performance when

group size is not taken into account. Results, underline that the agency cost of pyramidal

control increases as the size of the group increases.

Our interpretation of results is twofold. If we adopt the point of view of Shleifer and Vishny

(1986), the negative performance effect could result from the fact that lower cash-flow

stakes of large shareholder reduce their incentives to monitor actively management, thus

leading to lower firm performance because of managerial entrenchment. Thus, the fact that

this phenomenon is lower in smaller groups could just come from the fact that in small

groups the controlling shareholder is implicated in group firms’ management. However,

those results could also be driven by the fact that minority shareholder expropriation occurs

through other channels in smaller groups.

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b. Is there a shift from value decreasing toward risk enhancing tunneling in small

business groups?

To investigate this hypothesis we look for evidence of risk enhancing tunneling action in

groups and the influence of group size on this effect. To our knowledge, there is no study on

this topic. The literature on risk effect of group affiliation only focuses on the comparison of

affiliated and independent firms (see for example Khanna et Yafeh, 2005).

First, we estimate equations (5) and (6), where firm’s risk measure is the dependent variable.

OLS estimates in column 5 of table 4 indicate that separation between control and cash flow

rights does not significantly influence individual firm risk, measured by its ROA standard

deviation on the 1977-2003 period. Estimates of equation (6), in column 6, confirms that

those results hold even when interaction effects with group size are introduced. Those

results, point out that pyramidal control does not influences firm individual risk in our

sample.

We then test for the influence of the separation between control and cash-flow rights on the

probability of observing risk enhancing tunneling. We estimate equation (7) using a binary

logistic regression.

)7()0()0( 321 IndustryAgeSizeDivNivriskP iiii +++=+== βββα

Where, the probability modeled )0( =iNivriskP is the probability that the firm is less risky

than the average risk of its group firms.

Results in column 7 of table 4 indicate that the probability of non risk enhancing tunneling is

positively affected by the fact that there is separation between control and ownership.

Therefore, firms affiliated to pyramidal group have a higher probability of being less risky

than the average firm risk in their group. This result goes against our hypothesis of a shift

toward value decreasing tunneling in pyramid groups.

)5(4321 iiiiii mmiesIndustryDuAgeSizeROADivROA εββββασ ++++++=

)6(* 654321 iiiiii IndustryAgeSizeROAGSiDivGSiDivROA εββββββασ ++++++++=

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However, when estimating equation (8), which takes into account group size, we observe an

intriguing result: the corporate governance effect is offset by the group size effect when

considering risk enhancing tunneling.

)8()0()0( 4321 IndustryAgeSizeGSDivNivriskP iiiii ++++=+== ββββα

Indeed, results show that the probability of risk enhancing tunneling decreases as group size

increases, whereas the separation between ownership and control become insignificant.

Overall, those results indicate that firm affiliated to small groups is on average riskier than

their controlling firm. Indeed, remind that when we compute the average risk and

performance of groups, we also took into account the data for the controlling firm. In order

to confirm this we run a new regression on a sample including ultimate controlling firms and

a new dummy variable (Controlling) equal to 1 if the firm is the controlling firm, and 0 else.

Results in column (9) do confirm that there is risk enhancing tunneling patterns in small

groups. Indeed, being a non controlling firm decreases the probability of being less risky than

the average firm risk in the group, thus it increases the likelihood of undergoing risk

tunneling. Finally, results in column (10) underline that this effect is even more important

when we consider group size. Moreover, group size has a negative impact on the probability

of observing risk tunneling.

We interpret those results as support for the hypothesis that size influences corporate

governance issues. An important factor driving small firms controlling shareholder financial

behavior is linked to the peculiar structure of small business owner’s portfolio. Small firms

investors are characterized by an under diversification of their assets portfolio, as most of

their wealth is vested into the firm. In order to increase the mean-variance efficiency of their

portfolio they might be willing to lower their global portfolio risk. One way, would be to sell

shares of the firm and invest it in well diversified assets. However, what characterized small

business is the high illiquidity of their shares. Therefore, they might adopt alternative risk

reduction strategies. One of these strategies seems to be to use of the limited liability as a

tool to immunize part of their assets.

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Conclusion

Using a unique firm level data set, on ownership and balance sheet information, we were

able to study complex ownership features on a large sample of French group.

First, we find that the agency cost resulting from the separation between control and cash-

flow rights is subject to the influence of group size. Indeed, pyramidal control has a

significant influence on performance only when we control for group size interaction. Value

decreasing tunneling appeared to be significantly influenced by the separation between

control and ownership only in larger groups. We think that the relative under performance

of firms characterized by a separation between control and cash-flow rights is more related

to the ownership incentive effect. Indeed, we interpret the fact that tunneling is positively

influence by group size as the fact that in large groups the controlling shareholder, when its

cash flow are low, has less incentives to monitor management. Whereas, in smaller group

the controlling shareholder is generally involved in firms management, then offsetting the

monitoring issue.

Secondly, results on risk provide support to the hypothesis that complex ownership

structures might be used as an alternative hedging mechanism for under diversified owners.

Ownership structure does not have a significant effect on firm’s risk. However, the

probability of risk tunneling is influenced negatively by group size, given support to the

existence of “patrimony securization” strategies in small business groups.

Overall, results point out that corporate governance issues related to complex ownership

structures are influenced by group size. They also support the idea that risk management

practices cannot be understood in a corporate governance perspective without

consideration of group size.

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19

Table 1: Descriptive statistics

Mean STD MedianSeparation between ownership and controlCash-flow rights 77% 24% 90%Pyramid Control 8% 26% 0%

Group SizeGroup turnover (million €) 148 906 17Nbfirms 6 8 4Level 2,39 0,68 2,00

Performance and risk measureROA 10,52% 19,15% 9,32%SROA 8,13% 58,04% 0,39%

TunnelingNivROA 2,65% 23,82% 1,78%Nivperf 61,41% 48,68% 100,00%Nivsroa -57,25% 68,04% -0,03%Nivrisk 46,57% 26,43% 0,00%

Control variablesFirm size (million €) 13,66 121 3,07Firm age (year) 16 34 11

Table 2: Correlations between group size measures and the pyramid control variable

nbfirm levelGroup

TurnoverPyramid Control

1.00000 0.49559 0.18785 0.09911<.0001 <.0001 <.0001

22406 22406 22406 224060.49559 1.00000 0.23964 0.43393<.0001 <.0001 <.0001

22406 22406 22406 224060.18785 0.23964 1.00000 0.02043<.0001 <.0001 0.0022

22406 22406 22406 224060.09911 0.43393 0.02043 1.00000<.0001 <.0001 0.0022

22406 22406 22406 22406

Group Turnover

Pyramid Control

nbfirm

level

20

Table 3 : Estimation results of performance

Estimation method GLM Logit GLM LogitSpecifications (1) (2) (3) (4)Dependent Variable ROA NIVPERF=0 ROA nivperf+0

Pyramid Control(Div) -0,0042 -0,0181 -0,1276** -0,7246**0,0048 0,0260 0,0556 0,3021

Group turnover -0,0046*** 0,1072***0,0009 0,0176

Deviation*Group turnover 0,0072** 0,0442***0,0031 0,0168

Firm size -0,0012 -0,0343*** 0,0022* -0,1499***0,0010 0,0112 0,0012 0,0136

Firm age 0,0022* -0,0716*** 0,0020* -0,0644***0,0011 0,0125 0,0012 0,0125

Intercept 0,1214*** 0,6439 0,1482*** 0,36230,0153 0,3683 0,0162 0,4644

R2 0,018 0,019F 21,530 20,760Number of observations 22406 22406 22406 22406

0 8646 86461 13760 13760

Likelihood ratio 164*** 394***Score 164*** 395***Wald 163*** 386***

Logit

*** indicates that the parameters is significant at the 1% level, ** indicates that the

parameters is significant at the 5% level.

0,0001 is the standard error.

21

Table 4 : Estimation results of risk

Estimation method GLM GLM Logit Logit Logit LogitSpecifications (5) (6) (7) (8) (9) (10)Dependent Variable SROA SROA nivrisque = 0 nivrisque = 0 nivrisque = 0 nivrisque = 0

Pyramid Control(Div) -0,1468 -2,4880 -0,1651*** 0,01980,1554 1,7994 0,0263 0,3175

Controlling -0,4582*** -1,0893***0.0142 0,1637

Group turnover -0,0320 0,2093*** 0,1967***0,0230 0,0185 0,0121

Group turnover*Div 0,13250,1003

ROA -23,6348*** -23,6446***0,2162 0,2163

Firm size -0,0812** -0,0609 0,3099*** 0,153*** 0,2514*** 0,092***0,0331 0,0404 0,0117 0,0140 0.0097 0,0123

Firm age 0,0420 0,0403 -0,0125 -0,0022 0.0090 0,01930,0372 0,0372 0,0124 0,0125 0.0111 0,0112

Intercept 3,7235*** 3,9584*** -4,5249*** -6,0673 -3.4194*** -4,4995***0,4959 0,5244 0,3696 0,4771 0.3147 0,3349

R20,349 0,349

F 598,840 544,520Number of observations 22406 22406 22406 22406 31973 31973

0 11971 11971 19209 192091 10435 10435 12764 12764

Likelihood ratio 865 *** 1296*** 2260*** 2868***Score 840*** 1250*** 2131*** 2756***Wald 806** 1182*** 2002*** 2560***

Logit

*** indicates that the parameters is significant at the 1% level, ** indicates that the

parameters is significant at the 5% level.

0,0001 is the standard error.