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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
3
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).
4
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
5
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.
6
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
9
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).
10
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
13
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.
16
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.
17
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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.
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