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Is debt a governance device against the control leverage ? The case of European firms
GAUD, Philippe
Abstract
This paper documents that there is no relationship between ultimate ownership structure and firm performance among non-financial listed firms in Europe. The use of the control leverage by some ultimate owners is value destroying however. We show that firms rely on debt to counterbalance this effect because they face market pressures. These results are obtained from a large sample that allows to carry out a simultaneous equation system estimation of firm performance and financial structures where these variables are treated as endogenous.
GAUD, Philippe. Is debt a governance device against the control leverage ? The case of European firms. 2005
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http://archive-ouverte.unige.ch/unige:5758
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2005.06
FACULTE DES SCIENCES
ECONOMIQUES ET SOCIALES
HAUTES ETUDES COMMERCIALES
IS DEBT A GOVERNANCE DEVICE AGAINST THE CONTROLE LEVERAGE ? THE CASE OF EUROPEAN FIRMS
P. GAUD
Is debt a governance device against the control leverage? The case of European firms.
Philippe Gaud* May 2005
Abstract
This paper documents that there is no relationship between ultimate ownership structure and firm performance among non-financial listed firms in Europe. The use of the control leverage by some ultimate owners is value destroying however. We show that firms rely on debt to counterbalance this effect because they face market pressures. These results are obtained from a large sample that allows to carry out a simultaneous equation system estimation of firm performance and financial structures where these variables are treated as endogenous.
JEL classification: G32, G34
Keywords: Ownership structure; Corporate governance; Capital structure; Separation of ownership and control.
* University of Geneva (HEC), 40 boulevard du Pont-d’Arve, CH-1211 Geneva 4, Switzerland, email:
philippe.gaud@hec.unige.ch
1. Introduction
The managerial firm with diffuse ownership is not the typical European firm. Contrary to this view, Faccio and Lang (2002) show that it represents only 36.9% of the European listed firms. Their description highlights the reign of the ultimate owner among shareholders. On average, the ultimate owner holds 34.6% of total dividend rights. Another salient feature of the ownership landscape in Europe is the common use of various instruments to leverage control.
The average owner achieves 38.5% of total control rights by resorting, among other leverage instruments, to dual class shares, pyramiding and multiple control chains.
The present paper aims to go a step further in the understanding of the European ultimate ownership structure and empirically documents that it affects costly conflicts of interest arising from the separation of ownership and control. More specifically, its purpose is to show that the presence of an ultimate owner and her dividend right stake are not affecting the observed firm value per se, but her use of the control leverage does, and that the debt leverage helps resolve this expropriation issue. In other words, debt acts as a governance device against the control leverage in Europe. Although agency and separation of ownership from control issues have received much attention, to our knowledge, this hypothesis has yet to be tested.
Our analysis relates to the large body of corporate governance literature. Many empirical papers are dedicated to the effect of ownership structure on firm performance (among others:
Demsetz and Lehn, 1985; Morck, Shleifer and Vishny, 1988; McConnell and Servaes, 1990;
Himmelberg, Hubbard and Palia, 1999; Demsetz and Villalonga, 2001; Coles, Lemmon and Meschke, 2003). The present analysis is aware of specification issues and applies powerful tests.
The above-mentioned papers neither document the valuation effects of the control leverage nor the interaction between financial structures, i.e. the ownership and the capital structure. An open controversy regarding the role of debt in presence of an ultimate owner has yet to be settled. On the one hand, in an extreme agency cost environment, Harvey, Lins and Roper (2004) argue that
debt is a governance device for firms with a controlling manager that uses the control leverage.
On the other hand, Faccio, Lang and Young, 2002 claim that debt helps expropriation by the ultimate owner in vulnerable firms, though European capital market institutions are sufficiently efficient to limit the use of debt. This paper helps resolve this debate by directly documenting valuation implications of financial structures.
Results show that the concentration of dividend rights in the hands of the ultimate owner does not affect the observed firm value once the endogeneity among simultaneous variables is controlled for. The conclusions of Demsetz (1983), among others, regarding the endogeneity of the relationship between managerial ownership and performance are expanded by our result to ultimate ownership, another type of control. The use of the control leverage by the ultimate owner does affect value to some extent, however. This value destroying impact is reduced when the ultimate owner is a family. Such results are in line with the rent protection theory of Bebchuk (1999). Inefficient structures survived because it is too costly to release control. We argue that the control leverage eventually proxies for institutional arrangements supporting expropriation, but also that firms face a competitive market environment and therefore cannot afford a too high cost of capital. Therefore, some of these firms for which control is leveraged use debt as a governance device, because it is cheaper to adjust through debt rather than through equity. We document a positive value effect of debt leverage when firms have an ultimate owner who uses the control leverage. This positive effect is stronger among firms with large assets in place and low growth opportunities. Finally, results show that the probable exogenous investor protection affects financial structures since better protection favors external financing and diffuse ownership. This is a more efficient situation according to Bebchuk (1999).
In the next section, we present the main hypotheses by resorting to theoretical insights on conflicts and costs arising from the separation of control and ownership and their interaction with the capital structure. Section three describes the simultaneous equation method, the sample and
the variables. Results and their robustness are discussed in section four. Finally, section five contains some concluding remarks.
2. Literature review and main hypotheses.
2.1 Costs arising from the separation of ownership and control
In their seminal book, Berle and Means (1932) take the example of widely dispersed ownership firms to analyse a fundamental aspect of the theory of the firm: the separation of ownership and control. This separation leads to a conflict of interests between the controlling manager and passive shareholders that was later formalized by Jensen and Meckling (1976) as an agency issue. On the one hand, the manager does not always maximise share value because of differences in utility functions. On the other hand, the diffuseness of equity leads shareholders to free ride on the monitoring activity. Managerial ownership is argued to be a solution to this conflict of interest. Stulz (1988) shows that managerial ownership aligns incentives and therefore decreases the agency cost of managerial discretion up to a point where the manager becomes entrenched against market pressures and can again pursue her own maximisation goals at the expense of shareholders.
The power of this strand of literature casts somewhat a shadow on another face of the separation of ownership and control. When ownership is diffuse only to some degree, the blockholder does not let the manager shirking, consuming perquisites or building an empire.
Because of her sufficiently large stake, she uses costly monitoring technologies to limit managerial discretion costs. But separation1 costs still hurt minority shareholders since utility functions still differ. Although, in some cases, these divergences may not be harmful (the Demsetz and Lehn (1985) amenity potential comes as an example), the premium paid for control (Nenova, 2000; Dyck and Zingales, 2004) suggests that blockholders extract transferable pecuniary private benefits at the expense of minority shareholders. Monitoring is therefore a rent
1 Since a blockholder is not an agent of others shareholders, these costs do not qualify as agency costs, though they arise from the separation of ownership from control.
seeking activity where two controllers, the manager and the blockholder, agreed to expropriate cash flows that should otherwise be paid out to non-controlling minority shareholders. The blockholder prefers private benefits to dividends or share repurchases because she supports only the cash flow rights fraction of its cost (Bebchuk, 1999; Burkart and Panunzi, 2001; Burkart, Panunzi and Shleifer, 2003).
Since control rights allow rent extraction, whereas cash flow rights internalise discipline towards minority shareholders, the blockholder can increase her return on equity by leveraging her control. Although there are efficiency issues, the controlling structure survives at the expense of the non controlling structure because it is too costly for the blockholder to release control (Bebchuk, 1999). As this cost increases with the control leverage, it acts as an expropriation device. Dual class shares, pyramiding and cross holding are examples of strategies used to leverage control in Europe (Faccio and Lang, 2002).
The composition of the ownership landscape might be ultimately a matter of investor protection. In Burkart et al. (2003), the managerial and blockholder firms are two outputs of the same family firm model. In moderate environment, the investor protection and the asset composition determine the optimal ownership structure. They shape it because they affect both the expected private benefits and their repartition between the controlling owner and the manager.
In extreme cases however, i.e. large possible amenity potential (non pecuniary private benefits of control) or highly specialised skills requested for running the firm, the optimal ownership structure is not conditional to law.
In Burkart and Panunzi (2002), the institutional environment also affects conflicts between minority shareholders, the controlling blockholder and the manager, but it is more complex. At first glance, since legal protection is freely available for all shareholders, but monitoring is costly for minority shareholders, these disciplinary devices are not perfect substitutes and the former constitutes a political goal to achieve. Using in their model non equal bargaining power between the manager and the controller, these authors show however that
possible negative indirect effects of the legal protection may arise because it affects simultaneously the level of private benefits, the monitoring and the nature of control (i.e. the choice between private benefits and dividends). As a result, the investor protection and the private monitoring may be complements rather than substitutes.
Consequences of the separation of ownership and control also generate a large body of empirical literature in the field of corporate governance. Among these papers, one of the central questions is how ownership structure affects performance. Nevertheless, theoretical models are equilibrium ones and, although separation issues affect firm value, minority shareholders pay for what they have. Unless an external shock occurs or market frictions generate adjustment costs, there is no reason to expect a causal correlation between ownership concentration and firm value, once endogeneity between these two variables is controlled for. Back in 1983, Demsetz argues that the ownership structure of a corporation should be thought of as an endogenous outcome of decisions that reflect the influence of shareholders and of trading on the market for shares. It does not come as a surprise that empirical evidences of departure from the equilibrium hypothesis generate much debate.
Some empirical papers document a hump shape between managerial ownership and performance (Morck et al., 1988; McConnell and Servaes, 1990), suggesting an optimal managerial ownership structure. Others authors argue this correlation is simply spurious and vanishes when endogeneity between these variables is controlled for (Demsetz and Lehn, 1985;
Himmelberg et al., 1999; Coles et al., 2003). In this paper, we rest on and test the equilibrium with possible friction hypothesis. To handle correctly the endogeneity issue is therefore a primer but then questions remains. Firstly, evidence outside USA and on blockholder firms is still scarce. In their literature review, Denis and McConnell (2003) conclude that the impact of ownership structure appears stronger outside USA and that country and type of blockholder are important determinants of how ownership affects performance. However, the endogeneity issue still limits these conclusions and, until recently, the empirical investigation of the control
leverage and its valuation effect has received little attention. This is surprising because the control leverage should worsen separation costs as it misaligns incentives between the controlling owner and minority shareholders. Harvey et al. (2004) proxy for managerial controlling ownership structure through cash flow right leverage, but do not include the level of the managerial stake. In their sample of emerging market firms, they document a negative impact on firm performance. In a Swedish firms panel, Cronqvist and Nilsson (2003) find a negative value impact of the controlling owner vote stake, especially when the controller is a family, but the control leverage does not has further negative consequences.
Regarding the relationship between ownership structure and performance, this paper aims to document that the fraction of dividend rights owns by the ultimate controller owner does not affect the value of European firms, once endogeneity controlled for. Firm valuation implications of the control leverage should also be reflected in the market price of shares such that no correlation remains in equilibrium. The control leverage acts as an expropriation device because it allows the controlling owner to avoid the internalised disciplinary force of cash flow rights. In Bebchuk (1999), the controller does not release control even if there are efficiency issues because it would be too costly and this cost is increasing with the control leverage. Although in a given environment there is no feasible value improvement, the control leverage may proxy for exogenous institutional market frictions and a negative correlation may therefore arise since investor protection laws are exogenous at least in the short term. The control leverage is ultimately a by-law product and Faccio and Lang (2002) explain important differences in the means to leverage control in Europe by regulation specificities. For family firms, all else being equal, we expect a less negative impact on value of the control leverage. Family owner may gives control more value because of the amenity potential, but this added utility would come at no cost for other shareholders and therefore frictions would be softer. We also document implications of the level of investor protection on firm valuation and financial structures directly. La Porta, Lopez de Silanez, Shleifer and Vishny (2002) find a positive impact of the degree of investor
protection on Tobin’s Q and Himmelberg, Hubbard and Love (2002) find a negative correlation with the ownership concentration.
2.2 How capital structure affects separation costs and firm value
Besides investor protection law and concentration of ownership, financing policy has been argued as another possible disciplinary device to limit the private benefit extraction resulting from the separation of ownership and control. When ownership is diffused debt, helps the manager to disgorge free cash flows because of its mandatory service (Jensen, 1986). In the one hand debt bears its own agency costs (Myers, 1977) that increase with the ratio of investment projects to assets in place, and on the other hand, agency costs of managerial discretion (Jensen and Meckling, 1976, Zweibel, 1996) diminish with profitable projects, as a consequence debt is more valuable when there is a low ratio of profitable projects to assets in place (Jung, Kim and Stulz, 1996).
Few models consider blockholding however. In Mahrt-Smith (2005), debt also plays as a governance device but diffuse equity acts as a commitment device. Optimal capital structure trades off soft ownership concentration with hard debt. Diffuse ownership ensures manager’s involvement, and constraining debt binds her to a sufficient performance level. More generally, two conflicting views exist regarding the corporate governance role of debt in the blockholding firm. On the one hand, debt can be viewed as a governance device since it limits the expropriation shield. Such a tool should be more valuable when cash flows are realized and therefore when there is a large proportion of valuable asset in place in comparison to growth opportunities. Furthermore, as debt increases the financial distress costs, it might be more valuable to minority shareholders than to the controller, since the latter might not have sufficiently hedged her investment -human and capital- in the firm. On the other hand, Faccio, Young and Lang (2002) develop a view of debt where it acts as an expropriation device. For a given amount of assets, debt leverage limits the number of voting rights necessary to achieve
control. In corporate groups, debt can also helps tunnelling, financial distress of an affiliate does not necessary have severe negative effects on the wealth and reputation of the ultimate owner, and party related lending can biased the terms of the contract toward her wealth maximisation.
Costs arising from the separation of ownership and control are only part of literature on the capital structure puzzle. Determinants of the optimal financing policy have generated a long debate going back to the seminal paper of Modigliani and Miller (1958)2. Theoretical works have brought two other classes of models to test: the trade-off and the pecking order hypotheses. Under the trade-off hypothesis, the optimal financing policy consists in making adjustments toward the target debt level provided that deviation costs exceed adjustment costs. The target leverage ratio balances the tax benefit with the financial distress cost of debt. Under the pecking order hypothesis, informational asymmetries bias investment policy that in turn affects the firm value (Myers, 1984, Myers and Majluf, 1984). The adverse selection discount leads to rejecting positive net present value projects. The resulting optimal financial policy first exhausts the least sensitive financing source, i.e. internal financing, then debt and, as a last resort, equity. Under expanded Myers-Majluf models, the plain pecking order does not hold. For example, in Wu and Wang (2003) managers only maximize the controlling owner’s value and equity issues are therefore good news under conditions.
Although conflicting, capital structure models share a common feature: they are equilibrium models. Since optimal capital structure maximises firm value under constraints, capital structure and value are endogenous outcomes. If firms follow an optimal target leverage policy and if there are no adjustment costs, the debt level should not affect the observed firm value. Again, the endogeneity control is a primer. Marht-Smith (2005) shows that optimal financial structures are jointly determined and therefore empirical investigation of the link between firm value and ownership structure is biased unless the simultaneity of the relation between the capital structure and the firm value is considered.
2 Harris and Raviv (1991) provide an excellent review of literature of the capital structure puzzle.
Empirically, event studies of share price reactions to change in capital structure allow a control for the endogeneity issue because they focus on the value adjustment to a financing shock3. In a sample of US firms, Berger, Ofek and Yermack (1997) document that debt acts as a defensive governance device against managerial entrenchment. Although managers prefer to avoid to increasing durably leverage, they do so when they are under pressure and this move is value enhancing, especially under a hostile takeover threat. Following the issue of debt contracts with strong monitoring covenants, Harvey et al. (2004) find positive abnormal returns in their emerging market sample of firms. These returns are positively correlated with the managerial use of control leverage when they follow the most constraining issuance, i.e. subsequent issues of internationally syndicated term loans. These authors also use a simultaneous equation system, where the performance is proxied by the Tobin’s Q, the capital structure by the debt ratio, and the ownership structure by the managerial (and their family) control leverage, and they find that debt curbs the negative impact of control leverage on value although it does not eliminate.
Regarding the hypothesis of debt as an expropriation device, Faccio et al. (2002) focus on firms vulnerable to expropriation, i.e. affiliates with an ultimate owner. They document the control leverage enters negatively in regressions of debt ratio determinants for European firms and sign flips for Asian firms. They argue debt financing, and more especially party relating lending, acts as an expropriation device, but the capital market institutions in Europe -contrary to Asian’s ones- are sufficiently effective to prevent its use when firms are vulnerable.
As far as capital structure is concerned, this paper aims to document whether debt acts as an expropriation or as a governance device among vulnerable controlled European firms. To achieve this goal we need not only to control for interaction between financial structures but also to assess if it affects value. Our hypothesis is that European capital market institutions are sufficiently efficient and that market pressures are strong enough for debt to act as a governance device. It is consistent with indirect evidence of both positive abnormal returns for firms of
3 Assuming the choc being exogeneous.
emerging countries issuing Eurobonds (Harvey et. al, 2004) and control leverage that enters negatively in the debt level regression of affiliates in Europe (Faccio et al., 2002). To our knowledge, however, no direct evidence is available. In order to isolate and document the governance property of debt, the debt leverage is interacted with a proxy for vulnerability, i.e. the use of control leverage. The investigation of the impact of control leverage in an equation of capital structure determinants is not sufficient to fix the causality, and the endogeneity between these variables may leads to spurious correlations. Since a governance device is more valuable when the expropriation shield is large, we also test whether the asset composition affects the role of debt.
Some other features of the interaction between capital and ownership structure have yet to be tested. In Mahrt-Smith (2005), optimal ownership concentration decreases with monitoring costs and therefore acts as a complement with debt rather than a substitute. Depending on past performance, the controller is the creditor or the owner, and managerial monitoring costs decrease with a more constraining debt. The harder the debt, the more concentrated the equity.
This model also supposes that owner monitoring is equally beneficial to all shareholders, but it is unlikely to be realistic if private benefits are transferable. Burkart et al., (2003) show that the controller performs monitoring for self-protection and it has either positive or negative externalities for other shareholders. How financial structures interact is also an empirical issue that can be documented once proxies for the constraining nature of debt -institutions and contracts- and for the asset composition are available.
3. Method and Data
3.1 Model and specification tests
In the previous section, we briefly review some theoretical models of optimal capital and ownership structures. They are valuable because they highlight mechanisms through which the separation of control and ownership affects firm value maximisation. But they are equilibrium
models and as such they do not predict that capital and ownership structures affect observed firm value. In an efficient capital market, structural changes are reflected in the market price of assets.
Under this framework, any correct empirical design that reports significant correlations is only reflecting adjustment costs arising from inefficient market frictions. Lack of sufficient endogeneity control dismisses numerous empirical studies because it can be argued that correlations are spurious rather than highlighting adjustment costs.
The use of the Ordinary Least Squares estimator (OLS) in corporate governance and capital structure studies is therefore questionable. Since the endogenous variables are correlated with the error term, OLS yields biased and inconsistent results. Himmelberg et al. (1999), Cronqvist and Nilsson (2003), among others, use the fixed effect panel data estimator to control for the unobserved firm heterogeneity in the contracting environment. Zhou (2001) argues fixed effect tests lack power since they essentially removed all the cross sectional component of the total ownership variance. But this component is likely to have a heavier weight than the time series ones. Furthermore, the single equation regression does not easily handle the possible interaction between capital and ownership structures. The equation system comes as a straightforward econometric tool to handle endogeneity and simultaneous relationship between variables. It allows to documenting the causal link between structures. In equilibrium, financial structures affect each other but these interactions are priced, and unless endogeneity is controlled for spurious correlations remain another possible explanation.
Finding a correct specification and appropriate instrumental variables for the system is a difficult task. The lack of structural models of the firm leads to an ad hoc allocation of instruments to some endogenous variables. For example, Demsetz and Villalonga (2001) consider value and managerial ownership in their system, Harvey et al. (2004) include a third debt equation and proxy for ownership structure with the managerial control leverage. Coles, Lemmon and Meschke (2003) show that when the system is instrumented with a somewhat arbitrary approach, it gives rise to a specification issue.
We therefore have to be cautious regarding the choice of both the specification and the estimator of our simultaneous equation system. First, following the Davidson and MacKinnon procedure (1993), we perform Durbin-Wu-Hausman tests on our endogenous variables. These tests allow to assess the extent to which endogeneity is a quantitative problem in our sample. As results show that the OLS is not suitable, we consider two other estimation techniques: the limited information method (Two Stage Least Square estimator or 2SLS) and the full information method (Three Stage Least Square estimator or 3SLS). The choice of the method depends on whether the system is correctly specified or not. On the one hand, 3SLS is more efficient than 2SLS but it is inconsistent if one of the system equations is misspecified. On the other hand, 2SLS remains consistent in the latter case because misspecification is not transmitted to other equations. Specification is therefore not only a theoretical issue but also an empirical one. To test the specification of our model we perform a Hausman (1978) test. It is constructed on the search for a statistically significant difference between an efficient estimator under the null hypothesis (3SLS) of correct specification and a consistent estimator (2SLS) under the alternative hypothesis of misspecification. If Hausman tests are rejected then our model is correctly specified, and it is safe to use 3SLS.
3.2 Sample creation
To construct our sample, we first use the freely available database of Faccio and Lang (2002) that describes patterns of ultimate ownership and control among European firms.4 We merge this dataset with financial data available from Worldscope© using 1996 as a base year (ownership data of Faccio and Lang (2002) range from 1996 to 1999, with the majority of observations occurring in 1996). We also complete the sample with weekly prices of shares and of indexes available from Datastream© over a 104-week period surrounding the last week of 1996. Financial firms (SIC between 66-69) have been excluded since legal requirements on their capital structure might overcome separation of ownership and control issues. To minimize the
4 http://jfe.rochester.edu/. We are grateful to these authors who render the present paper possible.
impact of outliers, we eliminate the smallest corporations (total assets or total sales not exceeding
€5 million5), firms whose financial data are note credible (i.e negative equity market value or negative financial debt) and we trimmed the remaining observations.6 We finally obtained a cross sectional sample of 1860 consolidated non-financial listed firms in 13 European countries (Austria, Belgium, Finland, France, Germany, Ireland, Italy, Norway, Portugal Spain, Sweden, Switzerland and United Kingdom). Table 1 presents the distribution by countries. This sample covers 34% of listed firms (financial firms included) in these 13 countries and matches 43% of the non-financial firms included in Faccio and Lang (2002). The country weights are very close between the two samples.
3.3 System specification, variable definitions and summary statistics
Our econometric model aims to enhance our understanding of the interaction between financial structures and its valuation implication. It has Tobin’s Q, Debt to capital and Own -the fraction of dividend rights owned by the ultimate owner- as dependant variables. This system of simultaneous equations has the following general form:
ε X α capital to Debt
* d α capital to
Debt α
Own α Own α Q s
Tobin' = 1 + 2 2 + 3 + 4 + 5 +
Eq. (Q) ν
Y β Own β Q s ' obin T β capital to
Debt = 1 + 2 + 3 +
Eq. (D) η
Z δ capital to
Debt δ Q s Tobin' δ
Own= 1 + 2 + 3 +
Eq. (O)
where Tobin’s Q, Debt to capital, Own : endogenous variables,
d : dummy variable equals to one when the
control owner used the control leverage, X, Y, Z : vectors of explanatory variables,
5 01.01.2001 is used as conversion base date.
6We exclude observations inside the 0.25% and 99.75% tails for Tobin’s Q, Capex, AR, ROA, Cash, Tang, Mktr, StdE and observation inside the 99.5% tails for Own and C/O. Variables are defined in Table 1.
ε
, ν , η : stochastic error terms.In line with previous works analyzing the relationship between the firm’s performance and its ownership structure, we use an approximation of Tobin’s Q to measure the performance.
Our proxy is a Market to Book ratio where the numerator is the sum of the market value of equity and the book value of total liabilities, and the denominator is the book value of total assets. With Demsetz and Villalonga (2001), we agree it is an imperfect measure in particular because it weakly integrates the degree of reliance to intangible assets in its denominator. However, it better fits our requirements than the profit rate. First, it takes into account the value of assets in place and growth opportunities and both dimensions are likely to affect the nature of agency and asymmetric information costs (Myers and Majluf, 1984; Stulz, 1988, among others). Second, the regression technique allows a control for possible temporary noise introduced by investor psychology or other market frictions. Controlling for national and industry differences in accounting norms and habits reflected in the profit rate is much more difficult.
We use the fraction of cash flow rights owned by the ultimate owner (Own) as the endogenous ownership variable. We define an ultimate owner as a shareholder who holds directly or indirectly a minimum of 20% of the voting rights (Faccio and Lang, 2002; La Porta, Lopez de Silanes and Shleifer, 1999). To control for the possible non-linearity of the relation between ultimate ownership and firm value, we include a squared variable of Own (Own2) in Eq. (Q).
When the book debt leverage is the best available proxy for the debt to asset in place ratio, it allows to test agency issues, as the Barclay, Morellec and Smith (2003) model shows that the debt capacity of growth options is negative. On the contrary, the traditional market debt leverage gives rise to an identification problem. Changes in market prices due to temporary noise or to change in asset values generate a mechanical negative correlation with Tobin’s Q. Rajan and Zingales (1995) also discuss the pros and cons of various leverage measures. To reduce accounting and sector biases in an international setting, they advocate for consolidated debt to
capital ratios. They also adopt other adjustments to further increase the degree of comparison across their samples, but we do not implement such adjustments as argued below. They adjust leverage ratios for cash and cash equivalents, but Opler, Pinkowitz, Stulz and Williamson (1999), show that cash should not be considered as negative debt. We include cash as an instrument in Eq. (D). Rajan and Zingales (1995) write off intangible assets against equity due to the high level of intangibles in the United States. As we only consider European firms, intangibles are kept in the assets. They also adjust equity for differed taxes, though they recognize that the extent to which differed taxes are equity-like may vary across countries. Since the Worldscope database used to construct our sample does not disclose the exact amount of differed taxes, no adjustment is made. Booth, Aivazian, Demirguc-Kunt and Maksimovic (2001) make extensive use of the long-term leverage ratio, arguing that it is a better proxy for the financial debt ratio than the total liabilities to total assets ratio. Since Worldscope reports short-term and long-term financial debt, we use the total consolidated financial debt to book capital (Debt to capital) as a leverage measure.
Levels of endogenous variables in our sample are broadly consistent with those observed in other studies. Table 2 shows that the main features of ownership structure are similar to those of the Faccio and Lang’s (2002) larger dataset. The proportion of controlled firms at the 20%
threshold is 65% in Table 2 against 63% in their data. We find that 36% of these ultimate owners use the control leverage (C/O) defined as the ratio of ultimate voting rights to cash flow rights.7 27% of these ultimate owners are coded as family. These figures are slightly higher than those of the original database (31% and 16%, respectively). Table 3 presents descriptive statistics of firm specific variables used in regressions. Debt levels are closed to those reported by Rajan and Zingales (1995) in their sample of G-7 firms. The mean debt level of 0.318 is also in line with the 0.340 documented by Gaud, Hoesli and Bender (2005) on a larger sample of European firms.
Finally, a mean Tobin’s Q of 1.566 is closed to those documented in these papers as well.
7 As a result, the control leverage is set to zero for non controlled firms.
Consequently, we conclude that our sample gives a fair view of consolidated non-financial listed companies in Europe.
In Eq. (Q) we do not expect Debt to capital and Own to affect Tobin’s Q since financial structures and the firm value should be endogenous outcomes of a maximisation process reflected in the market price of the firm.8 Since the control leverage can sharpen the expropriation of minority shareholders, we include it in Eq. (Q) and expect a negative impact. Table 3 shows that a median C/O of one and a mean value of 1.067, reflecting the use of C/O is clustered in 36% of controlled firms. In order to test whether debt plays a governance device role by diluting the value-destroying use of control leverage, we interact Debt to capital with a dummy variable (d) equals to one when the ultimate owner use the control leverage.
Eq. (Q) also includes various control variables. AR, a measure of the market adjusted share return, aims to control for temporary firm specific share price effects that could affect the numerator of the Tobin’s Q proxy. Following Harvey et al. (2004), we also include a firm size (Size) and a capital expenditure (Capex) proxies. We use the natural logarithm of sales for two reasons. Firstly because sales are less accounting dependant than total assets (Rajan and Zingales, 1995; Booth et al., 2001). Secondly, in Coles and al. (2003), total assets and the firm performance are endogeneous due to a production function where return to scale is decreasing. As an instrument, Size is therefore expected to negatively impact Tobin’s Q. Capex proxies for growth opportunities and a positive coefficient in Eq. (Q) is expected. As suggested by Harvey et al (2004), it may also measure systematic overinvestment.
In addition to simultaneous variables Tobin’s Q and Own, C/O is also included in Eq. (D).
It may act as a complement or a substitute for Debt to capital, depending on whether debt acts as a governance or as an expropriation device. We also include a proxy for the industry debt level by using the 2-digit SIC Debt to capital median (DebtSIC). A positive impact on Debt to capital is
8 Such an insignificant sign of Debt to capital implies that the optimal capital structure policy is well described in terms of debt ratios.
expected since the debt capacity is depending on the asset composition (Myers and Majluf, 1984;
Barclay et al. 2003). DebtSIC may also control for industry specificities in financial policy.
Eq. (D) includes several other variables, which are commonly used in capital structure studies. Size is included because an increase in Size could positively affect the debt level through a decrease in financial distress costs and an increase in the debt tax shield value. Two variables account for the operating performance. Profitability (ROA) is defined as the ratio of earning before tax, interest and depreciation to total assets (Rajan and Zingales, 1995) and it proxies for the internal finance capacity. As we do not correct Debt to capital for cash, we include Cash -the ratio of cash and cash equivalents- to total assets, in our set of explanatory variables. This ratio serves as a proxy for the past accumulation of financial slack. Expected signs for operating performance measures are negative because, in a static model, preference for internal financing should dominates other effects. The ratio of tangible assets to total assets (Tang) is used to proxy for tangible assets (Rajan and Zingales, 1995). The expected sign is positive because tangible assets can act as collaterals.
Beside Debt to capital and Tobin’s Q, we also include Size and C/O in Eq. (O) and we expect a negative sign for both variables. Since, ceteris paribus, the required investment to own a given fraction of equity increases with the firm size, the portfolio diversification objective and limited resources should curb both the number of ultimate owners and their dividend rights stake.
On the contrary, the higher the control leverage, the lower is the cash flow right level necessary to achieve control. Following Demsetz and Lehn (1985), Demsetz and Villalonga (2001) and Harvey et al. (2004), we include two risk measures of holding a control stake in the firm. Mktr is the beta from a regression of the weekly stock return on its Datastream© national market index for a 104-week period. StdE is the standard error of the regression’s estimates over the period.
Expected signs are unclear because these variables may also proxy for the level of asymmetrical information between insiders and outsiders and consequently for the potential for expropriation.
Mahrt-Smith (2005) model prompts to the addition of two variables.
The debt level is an imperfect measure of the hardness of debt because it is not corrected for cash and it remains silent about maturity. One might expect the shorter the maturity, the most constraining is the debt, since the firm faces the discipline of external investors more often.
Debtors will not care about future cash flow until cash is sufficient to cover requirements.
Therefore, we define Tight as the ratio of short-term debt net of cash to the total financial debt net of cash and we set it equal to zero when cash exceeds short-term debt. If a more constraining debt decreases ownership concentration, then Tight should positively affect Own. In his paper, Mahrt- Smith (2005) also suggests that dispersed equity acts as a valid commitment device on the manager only when valuable projects are long term. We include the ratio of intangibles assets to tangible assets (LTtoSTp) to proxy for the weight of long-term projects and we expect a negative impact on Own. A long-term protection of the manager is valuable because it allows her to invest human capital, but a short-term discretion facilitates expropriation. Finally, we include a dummy variable equals to one when the ultimate owner is a family and we expect a positive impact on Own. Amenity potential being unique to the founder and her heirs (Burkart et al., 2003), a family will have a higher stake of dividend rights than other types of ultimate owners, all else being equals.
Country dummy variables are included in each of the equations of the system. They aim to control for the unexplained variance arising from differences in national environments. This standard procedure adopted in international empirical studies might be insufficient. Differences in equilibrium conditions may still generate correlations among variables, though the level of homogeneity in our –West- European sample of non-financial listed firms should be higher than in more internationally diversified samples. Concerning debt-equity choice of European firms, Gaud et al. (2005) argue that a dummy control procedure is adequate in Europe except for share repurchases. Results should therefore be interpreted cautiously. The regression system is also run with proxies for investor protection instead of country dummies in order to check for robustness.
4. Results
4.1 Estimation of the basic equation system and specification tests
Table 4 presents estimation results of the system described in Section 3.3. With the exception of Own in Eq. (Q), all Durbin-Wu-Hausman tests are satisfied. As a result, endogeneity exists between Tobin's Q, Debt to capital and Own, and OLS is biased and inconsistent. No change in sign between 3SLS and 2SLS are documented. 3SLS appears more efficient since several confidence intervals are smaller, for example, AR, StdE and Tight become significant.
More formally, Hausman tests are satisfied9, therefore 3SLS is consistent and efficient, and the equation system is correctly specified. In the subsequent tables, we only report 3SLS regressions.
Interesting features concerning the separation of control and ownership emerge from Table 4. First, the fraction of dividend rights owned by the ultimate controller does not affect value. Own and Own2 are not significant in Eq. (Q). This is consistent with results of US studies regarding managerial ownership (Himmelberg et al., 1999; Demsetz and Villalonga, 2001).
Though a given ownership structure bears its own separation cost, it appears that it also conveys compensating advantages since it is the result of a maximisation process including both the firm specificities and its environment. Second, the control leverage is value destroying as C/O enters negatively in Eq. (Q). This is in line with the Bebchuk model (1999) where the controller does not give up control even if it would enhance value because she supports the cost of turning to the non-controlling structure, and where the control leverage increases this cost. In decreasing the fraction of dividend rights necessary to achieve control, the control leverage increases aversion against a non-controlling structure. It therefore plays the role of an expropriation device ultimately allowed by law.
Debt to capital enters with a negative sign in Eq. (Q) but the sign flips for firms having an ultimate controller who exercises the control leverage. The sum of the coefficients for Debt to capital and d*Debt to capital is positive and the linear restriction test rejects the null hypothesis of
9 The same result is reported in Table 5 and 6.
no significance. The debt leverage appears to counterbalance the negative effect of the control leverage and therefore plays the role of a governance device. One might have expected the controlling owner to simply diminish her level of control leverage rather than using the discipline of debt. Instead, our result implies it is cheaper to adjust through capital rather than through ownership structure. Gaud et al. (2005) document only one significant equity transaction -issue or share repurchase- for seven significant debt transactions, suggesting it is harder to change ownership structure than debt. Even if the debt discipline is cheaper, it can be argued that the ultimate owner does not need discipline at all. European firms ultimately face a competitive marketplace and need external finance, such that we argue they cannot afford a too high cost of capital. The lower mean level of C/O compared to a sample where firms have potentially extreme costs born from the separation of control and ownership (Harvey et al. 2004) suggest that, in Europe, the cost of capital minimization criterion is binding the overall expropriation. Yet, the control leverage could be prohibited, but creating and enforcing appropriated rules is costly (Bebchuk 1999). Furthermore, if the controller extracts some private benefits, and other shareholders pay for what they have, political pressures toward more investor protection are likely to be weak, resulting in a strong path dependence in ownership structure.
Going back to the Debt to capital ratio, its negative impact on Tobin’s Q does not come as a surprise. Financing policy of European firms is complex and dynamic. Gaud et al. (2005) find that firms constraint themselves to an upper debt level, but they take large downward deviations suggesting they do not have a lower debt leverage boundary. The reported negative sign should reflects these large downward deviations and, therefore, should be an artefact arising because the dynamic financing policy is not well described using cross sectional debt levels. However, debt levels are sufficient to highlight the separation pf ownership and control issue that is the prime objective of this paper. The other firm specific signs in Eq. (Q) are found to be as expected. The estimated slope for Size is positive and this variable appears to correctly instrument total assets.
The positive coefficient of Capex shows that it proxies for growth opportunities rather than
systematic overinvestment. Finally, taken together, we do not find that country dummy variables affect Tobin’s Q. As the Wald test Wc in Eq. (Q) shows, the null hypothesis of no impact of these variables cannot be rejected. Firm specific variables are the core determinant of performance, and country specificities only have an indirect effect on performance through simultaneous variables.
In our view, this result helps legitimate empirical studies at the European level.
In Eq. (D), Tobin’s Q is not found to affect Debt to capital. On the other hand, the ownership structure affects the capital structure. Own enters positively in Eq. (D) whereas C/O is insignificant. Ultimate owners increase the amount of assets under control with debt leverage, but Eq. (Q) shows that this device does not serve to expropriate minority shareholders when they are exposed to the control leverage. Estimated coefficient for DebtSIC is positive, suggesting that the industry debt level is a proxy for the firm’s debt capacity. Size enters with a positive sign, in line with the hypothesis that larger firms have more stable cash flows and a higher debt capacity.
Stable cash flows decrease the probability of bankruptcy and therefore the cost of financial distress. They also increase the probability that the debt tax shield can be fully exhausted.
Consistent with the hypothesis that tangible assets act as collaterals, Tang enters regressions with a positive sign. In case of default, tangible assets have higher residual values. Since debtholders can ask for the selling of assets, they will therefore request tangible assets as collaterals. In addition, external investors can more easily assess tangible assets. Empirically, the negative impact on observed debt levels of Cash and ROA that proxy for operating performance is in line with one of the most documented regularity in capital structure studies. However, static regressions do not allow to discriminating between various theoretical explanations for the effect of operating performance on the debt leverage (Hovakimian, Hovakimian and Tehranian, 2004;
Gaud et al., 2005). The required dynamic tests are beyond the scope of this paper.
Lastly, Tobin’s Q enters positively in Eq. (O), suggesting ultimate owners have private information about future free cash flows. The opposite effect is documented for the C/O slope coefficient. The higher the control leverage, the smaller are the dividend rights necessary to
achieve control over the firm. Regarding the capital structure, Debt to capital and Tight enters positively in Eq. (O) contrary to LTtoSTp. Financial structures come out to act as a complement rather than a substitute. High levels of debt, and of its constraining capacity, go with more concentrate ownership structures, suggesting that the monitoring technology cost is a decreasing function of debt finance. Regarding Mahrt-Smith (2005), we also find that firms have more diffused ownership structures when they have long-term projects, a situation where it is rewarding for controllers to give some discretion to managers for them to invest some amount of human capital. One should note however these results are silent about the equilibrium value effect of the interaction of financial structures. In modifying negatively the monitoring cost, constraining debt may have a beneficial effect on the block control value but it is unclear whether the externality on minority share price is positive or negative. This suggests an avenue for future research.
Estimated coefficients for Mktr and for StdE have opposite signs. The negative slope for Mktr shows that ultimate owners limit their stake of dividend rights when undiversifiable risk is high. Their portfolio might be insufficiently diversified or they may have invested human capital in the firm. The positive sign of the estimated coefficient for Mktr may indicate that the ownership concentration increases with asymmetrical information, which eases to set up expropriation strategies. The Size slope is not significant, possibly because Mktr already captures diversification effects. Finally, results show that owner identities affect their stake, as family firms have a more concentrate ownership structure. It is consistent with the hypothesis that family can increase their utility through consumption of non-transferable amenity potential.
4.2 Robustness of the 3SLS estimation
In Table 5, the system of simultaneous equation is estimated using alternative proxies for Size, Debt to capital and Own. In their empirical investigation, Coles et al. (2003) find that inferences are sensitive to small change in regressions and conclude that serious specification
issues remain even if simultaneous estimation techniques are used. It is therefore important to check the robustness of the results discussed in the previous section. In the first column, we use the natural logarithm of total book assets as a proxy for Size. This measure is somewhat usual in the corporate governance literature (Demsetz and Lehn 1985, McConnell and Servaes, 1990;
Demsetz and Villalonga, 2001). In the structural model of Coles et al. (2003), the total of assets is endogenous and change in sign is empirically documented when an instrument, the log of sale, is used. Signs do not change when the alternative proxy for Size is used, with the exception of AR , which is loosing its significance in Eq. (Q). In the second column, the regression system has been estimated by including the squared value of the natural logarithm of total assets to control for a possible non-linearity in Size. AR is again not significant in Eq. (Q) and Size becomes insignificant in Eq. (D). Other signs of estimated coefficients remain unchanged. Therefore, our three-equation system does not appear to be dramatically sensible to the choice of a proxy for firm size.
In the third column, the market debt leverage is used as a proxy for Debt to capital. We define the market debt to capital as the ratio of total financial debt to the sum of total financial debt and market value of equity. Market debt to capital is a traditional proxy for debt leverage in capital structure studies (Rajan and Zingales, 1995; Hovakimian et al., 2004), but its correlation with Tobin’s Q is not systematically caused by changes in debt capacity. Estimated slopes do not substantially change when the market leverage is used. Apart from AR slope, being again insignificant in Eq. (Q), the sole difference is that Tobin’s Q becomes negative in Eq. (D). This result indicates that simultaneous price effects drive the correlation between market debt leverage and Tobin’s Q (Barclay et al., 2003).
Finally, we run the regression using a 10% voting right threshold for control. This cutoff is also used in the ultimate ownership literature (Faccio and Lang, 2002; LaPorta et al., 1999).
Although our main conclusion regarding the control leverage as an expropriation device tempered by the debt leverage is not altered, results are sensitive to this change of cutoff. The control
leverage coefficient becomes positive in Eq. (D) and the slope for Size becomes negative in Eq.
(O). In this latter equation, Tobin’s Q, Debt to capital and LTtoSTp are no longer significant. We are cautious in interpreting the positive coefficient for the control leverage in Eq. (D) as supporting evidence of a complementary device with the debt leverage. First, the positive sign in the debt regression might be the governance response to an increase in the use of the control leverage. Second, the 10% effective control level appears to be low, not only per se, but also because in our sample the number of firms with an ultimate owner increases dramatically (more than 98% have an ultimate owner at this cutoff). In conclusion, results in Table 5 suggest our inferences are not sensitive to proxy changes and therefore results are robust.
4.3 Further investigations into the separation of ownership and control determinants.
Results presented in Table 6 introduce some complementary variables in the basic equation system defined in Section 3.3. First, regressions aim to highlight whether the identity of blockholder and the composition of assets change the nature of separation conflicts. Second, they allow investigating how investor protection measures developed by La Porta, Lopez-de-Silanes, Shleifer and Vishny (1998) affect the equation system.
In the first column, the expropriation leverage C/O is interacted in Eq. (Q) with the family dummy variable dFam. In their literature review, Denis and McConnell (2003) suggest that outside United States the blockholder identity is an important determinant of the impact of ownership on value. Our previous results do not document that the dividend right stake of the ultimate owner affects value, but her identity may change the expropriation she achieves through the use of the control leverage. Ceteris paribus, for a given level of control, a family controller who obtains a higher utility level through the consumption of amenity potential (Bebchuk, 1999;
Burkart et al., 2003), should use more intensely the control leverage. This excess use should not be detrimental to minority shareholders as it aims to benefit from non-profit related utility gains.
One might therefore expect a decrease in the negative effect of the control leverage. Results show
that the use of the control leverage is less detrimental when the ultimate owner is a family, but its effect on value remains negative. The sum of coefficients C/O and dFam*C/O is significant (the linear restriction test rejects the null hypothesis) and negative (-0.230), but smaller than the C/O coefficient alone (-0.335). It appears therefore that family blockholders consume amenity potential as well as pecuniary and transferable private benefits.
In the second column, we further investigate the role of debt as a governance device when the ultimate owner uses the control leverage. The role of debt is likely to be affected by the composition of assets, but the nature of the interaction is unclear. On the one hand, firms with high free cash flows are targets for expropriation by controllers.10 On the other hand, if firms have profitable growth opportunities relying on human capital investment of the controllers, it might be counterproductive to load the capital structure with debt if controllers are risk adverse and under diversified. However, the latter effect is detrimental only to the extent that some valuable investments of the controllers are made, otherwise debt could still play a governance device role since controllers are risk adverse than well-diversified minority shareholders.
To explore this issue, one needs to separate two types of firms according to their asset composition. To do this, we follow a two-step procedure to distinguish between cash cow and high growth firms. First, we derive a score from a factor analysis with principal components on a common proxy for growth opportunities -Tobin’s Q- and on another one for assets in place - Tang-. The eigenvalue of the first factor is 1.12, the component loading for this factor being – 0.747 and 0.747 for Tobin’s Q and Tang, respectively.11 The sign of the score is used to construct a dummy (d2) that takes the value of one for firms having high growth opportunities and low assets in place. Finally, d2 is interacted with d*Debt to capital. The regression is run on a subsample that excludes firms with negative ROA and zero d2, since these firms are more likely to be deadweights than cash cows. Results show that in both cases, debt acts as a governance device against the control leverage, but the positive effect on value is stronger for firms with high
10 Managers and ultimate owners.
11 This score is therefore positive for firms with relatively low growth opportunities and high assets in place.
assets in place and low growth opportunities. The sign for the estimated slope of Debt to capital flips positive when the control leverage is used for the two types of firms, but the coefficient is smaller for d2*d*Debt to capital than for d*Debt to capital. Linear restriction tests reject the null hypothesis, i.e. sums of coefficients are non significant. It appears that debt plays a stronger governance device role when firms have high free cash flows, but also that the risk aversion of controllers broadens somewhat this governance effect. A possible explanation is that ultimate owners, though they are risk adverse, do not invest human capital in long-term valuable projects, unless they are managers.
Finally in the third column, country indicator variables are replaced by investor protection measures λS, λC, λE and LegRes. These measures, developed by La Porta, Lopez-de-Silanes, Shleifer and Vishny (1998), are defined in Table 1. The aim of this regression is twofold. First, it serves to check whether our procedure concerning country dummy variable is valid or not.
Second, it tests if legal protection affects the observed firms value and financial structures. If legal protection is exogenous to the firm, it should increase the firm value since it freely limits the manager’s expropriation. La Porta et al. (2002) document a positive effect of protection levels on Tobin’s Q. Estimation results in the third column do not yield any change in sign for firm specific variables. In line with results reported in the previous section, our main conclusions appear to be robust to change in the regression specification. Investor protection measure, as a whole, does not affect value since Wλ, the Wald test of the null hypothesis of no significance, cannot be rejected.
This result was not expected, as these measures should be exogenous. A possible explanation is that the control leverage proxies for most of investor protection implications on firm value.
Another explanation might be that our sample does not include enough countries. Regarding other international study standards, a 13 countries panel is small. However, it is large enough to document effects of the investor protection on the ownership and capital structure, two dimensions not controlled for in La Porta et al. (2002).
Investor protection measures affect Eq. (D). Wλ is significant and all protection variables enter positively, implying a higher leverage when both the shareholder and the debtholder protection are stronger. This result and the more frequent use of debt finance found by Gaud et al.
(2005) on a similar sample suggest that a better protection develops external financing. It is in line with the well-documented hypothesis that legal protection favors economic growth (La porta et al., 1997; Demirguc-Kunt and Maksimovic, 2002). Investor protection also affects the ownership structure, but with an opposite sign. Wλ is significant and all the protection variables enter negatively in Eq. (O), suggesting a more diffuse ownership structure when both the shareholder and the debtholder protection are stronger. This result indicates that, in our sample, ownership concentration and investor protection are substitutes rather than complements.
Regarding Burkart and Panunzi (2002), among European firms, the freely available enforcement effect of law appears to dominate any indirect effects. This result is in line with Himmelberg et al. (2002) suggesting that a better investor protection allows a decrease in the cost of capital through a better shareholder diversification. It should finally be noted that this result contradicts predictions of the Mahrt-Smith (2005) model. If the monitoring cost decreases with a better debtholder protection, one should expect a positive impact on the ownership concentration since equity dispersion increases with monitoring cost.12
5. Conclusion
In this paper, we document the interaction between ownership and capital structures, and firm performance. Patterns of the ultimate ownership and control are brought into focus because the controlled firm gives a better description than the managerial firm with diffuse shareholders of the typical European firm. We empirically rest on a system of three equations where the firm performance, the capital structure and the ownership structure are simultaneously estimated. It allows to inferring relations of causality in a framework where endogeneity is controlled.
12 Another possible explanation is that measures of debtholder protection are less effective than shareholder ones.
Results show that the observed performance is the output of a maximization process under constraints. According to a given environment and to asset specificities, firms adjust themselves by modifying their financial structures in order to maintain a sustainable cost of capital.
Competition on financial and product markets leads firms to operate efficiently. This constraining level of performance binds the controller expropriation even it is allowed by failures in investor protection. Evidence shows that control leverages are relatively small and that firms rely on debt finance to correct the negative effect of leverages on value. We argue firms counterbalance with debt because it is cheaper. In our sample of European firms, therefore, debt acts as a governance device against an expropriation device, i.e. the control leverage. This result is interesting because it illustrates how the dependence to external finance pressures the ultimate owner to limit expropriation and disgorge free cash flows, although incentives were initially misaligned.
The other main conclusion of this paper is that the level of ownership concentration does not affect observed firm value. As a result, ownership structure does not deviate too much from its optimum level. This is not to say separation costs are low. Debt playing a governance role illustrates that firms adapt themselves to given operating framework, and that there are also advantages to some concentration in ultimate ownership. The level of investor protection is therefore at the heart of the maximization process. Results show that a better protection facilitates external financing and more diffuse ownership. Much remains to be done in the promising field of modeling how the environment shapes financial structures.
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