Download Ownership Concentration and Corporate Performance

Ownership Concentration and Corporate Performance:
New Evidence from the Budapest Stock Exchange*
John S. Earle
Central European University and Upjohn Institute for Employment Research
Csaba Kucsera
Loránd Eötvös University Budapest and Central European University
Álmos Telegdy
Budapest University of Economic Sciences and Central European University
May 2002
Abstract
Panel data on Hungarian firms listed on the Budapest Stock Exchange (BSE) provide
an opportunity to estimate the effects of alternative measures of ownership concentration on
firm performance. As in other continental European economies, ownership on the BSE is
highly concentrated: the median shareholding is 40% for the largest owner and 61% for all
5% or greater blockholders. The proportion of shares held by the largest blockholder is
estimated to increase performance strongly, with coefficients of 0.294 for return on assets and
0.942 for operating efficiency. When concentration is measured as the shareholding of
multiple blockholders, the estimated effects are much smaller and statistically insignificant.
The evidence suggests that the marginal costs of concentration may outweigh the benefits
when the additional concentration is achieved through multiple blockholders rather than a
single large block.
This paper was written with support from the European Community’s Phare ACE Program 1998. Part of the
ownership data collection was supported by the Phare ACE Program through the European Corporate
Governance Network. The content of the paper is the sole responsibility of the authors and it in no way
represents the views of the Commission or its services.
*
1. Introduction
The effects of ownership concentration on firm performance are theoretically complex
and empirically ambiguous.
Conceptually, concentrated ownership may improve
performance through increased monitoring and alignment of incentives (e.g., Shleifer and
Vishny, 1986), but other mechanisms may work in the opposite direction. As discussed by
Wruck (1989), Barclay and Holderness (1989) and Shleifer and Vishny (1997), large
shareholders may exercise their control rights to create private benefits, sometimes
expropriating smaller investors. Moreover, fear of expropriation may limit the ability of firms
with high ownership concentration to raise fresh finance through borrowing or new share
offerings. Takeovers may become more costly for raiders to carry out when ownership is
highly concentrated, due to the smaller fraction of liquid shares available to establish a
"toehold," thus reducing the strength of this disciplinary device. The reduced liquidity lowers
the utility of the firm's share price as a measure of managerial performance. Finally, none of
these effects may matter if ownership structure tends to be optimally adjusted to firm
characteristics, in which case, as argued by Demsetz (1983), there may be no relationship
with performance whatsoever.
Empirical studies of the firm performance-ownership concentration relationship have
also produced mixed results. Among studies of the U.S., Demsetz and Lehn (1985) find no
effect of concentration on accounting profits, and McConnell and Servaes (1990) find no
effect on Tobin's Q (although they do find a positive effect of ownership by corporate insiders
and by institutional investors). On the other hand, Wruck (1989) reports that private sales of
blocks of shares, associated with increasing concentration, have an effect, although one that is
nonmonotonic, on abnormal market returns. Similarly to Morck, Shleifer, and Vishny's
(1988) analysis of managerial ownership, she finds that returns are increasing in concentration
when concentration is low, they are decreasing when concentration is moderate, and they are
again increasing at higher levels; as the coefficient for low concentration is statistically
insignificant, this suggests a roughly U-shaped relationship. An interpretation of these results
is that the negative effects of concentration outweigh the positive effects over some ranges of
the level of concentration.1
1
Studies of non-U.S. economies also produce mixed results. For the U.K., Leech and Leahy (1991) report
inconsistent findings, including a negative relationship when performance is measured as profitability, while
Gorton and Schmid (2000) find that concentration increases the market-to-book ratio and returns to assets in
Germany, although only the former result is statistically significant. For Japanese firms, Prowse (1992) finds no
relationship, linear or nonlinear, between profitability and ownership concentration, while Claessens and
Djankov (1999) find an inverse U-shaped relationship in the Czech Republic.
1
In this paper, we argue that an important issue in these studies, albeit one that has
received relatively little attention, concerns the implications of alternative measures of
ownership concentration. Most empirical research has followed Demsetz and Lehn (1985) in
measuring concentration with respect to a group of owners, usually as the total equity share
held by the largest five or largest 20 investors. Zwiebel (1995) has provided some indirect
theoretical justification for this measure by suggesting that a large owner will tend to "create
its own space," discouraging other blockholdings from forming, while in the absence of a
large owner smaller shareholders may form coalitions to exercise joint control; this implies
that a measure of the shareholdings of the group of largest blockholders captures either
possibility. But it also stands to reason that small blockholders may face collective action
problems and they may even quarrel, due to differing interests or conflicting views of
corporate strategy. In the presence of a large owner, the marginal contributions to managerial
monitoring of additional blockholders may be low, and they may serve only to increase costs
of concentration by reducing liquidity. If the additional blockholders do not produce net
benefits, then the inclusion of their shareholdings serves only to add measurement error to the
concentration variable, thus reducing the magnitude of the estimated performance effect and
increasing the estimated standard error.
Thus, the estimated effect of concentration on
performance may depend crucially on how blockholders interact with another one and on the
measure of concentration employed in the analysis, the lack of attention to which could
explain, at least partially, the conflicting findings of previous studies.
We address these issues drawing on data from Hungary, an economy which has, as we
show, a high average ownership concentration that is typical of Continental Europe and much
of the non-Anglo-American economies , as shown by LaPorta, Lopez-de-Silanes, and Shleifer
(1999). Around this high average, we observe cases of quite dispersed as well as extremely
concentrated ownership. Contrary to Zwiebel's (1995) predictions, large blockholdings often
co-exist within a single firm. Our empirical strategy involves the estimation of fixed-effect
panel regressions of return on assets and operating efficiency on various measures of
ownership concentration using all firms traded on the Budapest Stock Exchange (BSE)
between 1996 and 2000. These within-estimators compare the effect of an increase in the
largest shareholding with an increase in the shareholding of all blockholders, as well as some
intermediate cases. We find that only the largest shareholding has a positive, statistically
significant effect on corporate performance, while other blockholdings have coefficients that
are statistically insignificant and usually negative; the sum of all blockholdings (the
traditional measure in such studies) has effects that are estimated to be positive, but they are
2
always statistically insignificant and smaller in magnitude than that of the largest blockholder.
The data show no evidence of nonmonotonicities in the performance-concentration
relationship, and indeed there is some evidence that the marginal impact of the largest
blockholding increases slightly as the blockholding rises. We conclude that the data strongly
support the view that agency problems are reduced by ownership concentration – when
concentration refers to the largest blockholder – but they provide no evidence that small
blockholder cooperation can substitute for a single dominant shareholder, and they provide
some suggestion that additional blockholdings actually tend to reduce value, possibly due to
quarreling among blockholders and possibly by making the firm's shares less liquid.
2. Data Description and Estimation Framework
This study analyzes official data published by the BSE (Budapest Stock Exchange and
Bank & Tőzsde, 1996 – 2000). These data supply basic financial information for all listed
firms as well as information on the direct blockholders of the firms (any owner possessing
more than five percent of the company's shares). One shortcoming of our database, however,
is that it has information only on direct holdings.2 The lack of indirect holdings may create a
systematic downward bias of our measures of ownership concentration.
The ownership information pertains to May in 1996 and 2000, and June for the other
years. As we want to estimate the effect of the concentration on firm performance, which we
measure as the year-on-year growth in two indicators, as described below, for consistency we
define the ownership variables as the average across years t and t-1.
Our first measure of concentration is the percent held by the largest blockholder (C1).
Second, we add up the holdings of the largest and the second largest blockholder (C2), then
we sum up the holdings of the three largest blockholders (C3). Our last measure of ownership
concentration is very similar to that used in many of the earlier literature: the sum of all
blockholders (Call).
Since the ownership structure of the firms on the BSE is very
concentrated, this is almost identical with the joint holdings of the largest five owners. 3 Table
1 presents the basic statistics for these variables.4 On average, the largest blockholder owns at
the median 42 percent of the shares in the period of 1996 – 2000. The data reveal that there is
2
The legislation obliging owners to disclose indirect holdings was adapted only in 2001, and thus this
information is not available for earlier years.
3
The structure of ownership is highly concentrated, as we show below, and even the fourth largest owner has
very small or zero holdings: 30 – 34 companies do not have a fourth blockholder and the average holding of the
fourth blockholder is 1.5 – 2.6 percent (zero holdings included).
3
substantial variation across firms in ownership concentration: despite the large mean and
median, the minimum value for the largest owner's holding is 0 (that is, there are firms in
which no owner holds at least five percent of the shares), and the maximum value is 74 – 84
percent, depending on the year studied.
By contrast with Zwiebel's (1995) predictions concerning ownership structure, we find
that the second largest blockholder also tends to have a large stake: 13.5 percent at the mean
and 13.7 at the median. And the third is also not tiny, with 4.8 at the mean, and 7.0 at the
median. Smaller blockholders tend to be much smaller, however, so there is little difference
between C3 and Call. For all these variables, there is a substantial range across firms. This
variation is useful for testing the relation between the concentration and firm performance.
Insert Table 1 about here.
The figures suggest strong similarity between the Hungarian listed firms and their
counterparts from other continental European stock exchanges. Indeed, at the median, the
largest voting block is around 50 percent in a number of European countries (Austria,
Belgium, Germany, Italy), while it is only 9.9 percent for the United Kingdom and under 5
percent for the New York Stock Exchange (Becht and Röell, 1999).5 Claessens and Djankov
(1999) show that the top five owners possess 68.4 percent in the Czech Republic. Telegdy et
al (2002) report the joint holding of all blockholders for the firms on the Bucharest Stock
Exchange at around 70 percent.
In general, the volume of trading is low on the BSE, as in most continental European
stock exchanges, and we do not believe that the share prices bear much correspondence to the
true firm value, at least not for all listed firms, because many of them are only thinly traded.
Table 2 contains the descriptive statistics for the measures of corporate performance we do
study, the dependent variables in our equations. Return on assets (ROA) is defined as the ratio
between profit and equity, while operating efficiency (OE) is the ratio of real sales to the
number of employees. In both cases, we analyze the growth rather than levels; for ROA this
is the simple difference ROAt - ROAt-1, while for OE it is log(OEt/OEt-1).6
Insert Table 2 about here.
The table also presents summary statistics for the lagged level of performance and
4
The statistics of ownership concentration (and of the variables presented in the next table) do not differ much
across years. To save space, we present them for the whole panel, thus, the unit of observation in these tables is
firm-year.
5
Other studies gathering evidence on the presence of blockholders are La Porta, Lopes-De-Silanes and Shleifer
(1999) for 27 industrialized countries and Claessens, Djankov and Lang (2000) on nine East Asian countries.
6
ROA is sometimes negative, and it is already measured in proportional units. We do not compute OE for the
banking and finance sector because of difficulty of measuring sales for these firms.
4
employment size. ROA changed little on average during this period, although the standard
deviation is substantial. OE grew rapidly, an average of 16 percentage points, again with a
substantial standard deviation. The employment figures document that Hungarian listed firms
tend to be large, with a mean employment level over 2400.
We employ fixed-effects regression methods to eliminate any bias resulting from a
permanent quality difference across firms that could be correlated with ownership structure.7
The regression equation is the following:
Perfit = β0 + β1Cit + β2Perfit-1 + β3Empit-1 + tYeart + i + it,
where Perfit is either ROA or OE, Ci,t measures the concentration of the firm's i ownership
concentration in year t in several alternative specifications, as discussed earlier in this section.
In each of our regressions, we control for the lagged level of performance, lagged
employment, and year effects.
3. Regression Results
We start with the results for the summary measures of concentration C1, C2, C3, and Call,
shown in Table 3. The largest blockholding, C1, is estimated to have a large, positive impact
on growth in both ROE and OE, both effects statistically significant at the one percent level.
Insert Table 3 about here.
On the other hand, the point estimate for the coefficient on C2 is much smaller in both
equations, and it is statistically insignificant for ROA and only significant at the five percent
level for OE. The coefficients on C3 and Call shrink still further, and neither of them are
statistically significant for either dependent variable. At the same time, the standard error is
roughly constant for all concentration measures.
These results are inconsistent with the view that blockholders are easily able to form
coalitions to monitor management. They are consistent with the hypothesis that only the top
blockholder matters and that including additional blockholders into a broader measure of
concentration not only introduces noise into the concentration measure, which would diminish
the coefficient and increase its standard error. The fact that the standard error does not
increase suggests that the additional blockholders actually have a negative effect on
performance.
To explore the last point more fully, Table 4 reports the results from disaggregating the
shareholdings of the three largest blockholders and including them separately in the
equations.
Consistent with our findings for C2 and C3, the second and third largest
5
blockholders have negative point estimates for their effects on corporate performance,
although the coefficients are not statistically significant.
Furthermore, the additional
blockholdings are even estimated to diminish the positive effects of the largest shareholding.
These results are consistent with the view that additional blockholdings, beyond the largest,
reduce firm performance.
As we have discussed, this may occur if these additional
blockholders are active, and they quarrel with the largest blockholder. It may also occur if
they are passive but their presence reduces the liquidity of the firm's shares on the market,
which decreases the informational value of the share price and increases the cost of a
takeover, in both cases reducing the effectiveness of these disciplinary devices.
Insert Table 4 about here.
Finally, we consider the possibility that concentration works differently in situations
when the largest blockholder is very large from when it is less dominant. For instance, if the
largest blockholder has a majority stake, then additional blockholders may function only to
create annoyances and reduce liquidity, but they seem unlikely to contribute to further
monitoring of management. On the other hand, if the largest blockholder holds only a
minority stake, then perhaps the additional blockholders would contribute to monitoring and
for a given size of the largest blockholder, they would soak up less of the firm's share
liquidity.
The first situation corresponds to Zwiebel's (1995) picture of a dominant
shareholder "creating its own space," while the second corresponds to his view of coalitions
of smaller blockholders cooperating in the absence of a single dominant investor.
To examine this possibility, we re-estimate the equations including both C1 and Call C1, interacting both with a dummy variable D1 = 1 if C1 > 50 and 0 otherwise. Thus, the
equation is as follows:
Perfit = β0 + γ1C1itD1it+ γ2(Call,it-C1it)D1it+ γ3 C1it(1-D1it) + γ4(Call,it-C1it)(1-D1it)
+ β2Perfit-1 + β3Empit-1 + tYeart + i + it,
where γ1 > 0, γ2 = 0, γ3 = 0, and γ4 > 0 would suggest a regime switch associated with the
largest blockholder's share passing some threshold. Table 5 contains the estimation results.
We find no evidence of a regime switch, as γ1 > 0 and γ3 > 0, and γ2 < 0 and γ4 < 0, in
both equations. γ1 > γ3, so that the effect of share concentration in the largest blockholder's
hands is estimated to increase for C1 > 50, although the difference is not statistically
significant. |γ4| > |γ2 |, which might suggest that additional blockholders have a larger negative
effect when C1 ≤ 50, although again the difference is not statistically significant. Taken at
7
The Hausman test always supports the fixed effects versus random effects specification.
6
face value, the results seem to provide more support for the view that additional blockholders
quarrel with one another than that they reduce liquidity. In any case, the data do not support
the view that smaller blockholders are able to form coalitions to control management and
increase performance – neither in the presence nor in the absence of a dominant shareholder.
To assess the robustness of our results, we estimated a variety of alternative
specifications. For instance, we re-estimated the regressions dropping some of the controls,
such as the lagged value of performance, the lagged value of employment, and both variables.
We also re-estimated the equations with lagged concentration measures. In all cases, the
results qualitatively remains the same:
only the size of the largest shareholding has a
positively significant effect on both performance measures, and the estimated magnitude of
the effect declines as the shareholdings of additional blockholders are included.
Similarly to the results in Table 5, we also estimated a variety of non-linear
specifications, permitting the concentration effect to enter piecewise linear, quadratic or cubic
form. The data showed no evidence of nonlinearity. We also respecified the dominant
ownership threshold dummy at alternative levels of 0.25, 0.33, and 0.40. Again, the results
were qualitatively similar to those in Table 5.
Finally, it would be possible to distinguish different types of blockholders in these data,
including domestic and foreign owners, banks and nonbanks, individuals and institutional
investors, and private and state actors (Kucsera, Earle and Telegdy, 2001).
There are
sufficient observations on these types only to permit estimation of the domestic – foreign
distinction. The results from such estimates show no clear ranking of these two owners
concerning their effect on enterprise performance. Only the shareholding of the largest owner
appears to matter, while the identity appears to be secondary.
4. Conclusions
The impact of ownership concentration on corporate performance has been a central
idea in research on corporate governance, but evidence on the nature of the relationship has
been decidedly mixed. Partly this may be due to the fact that concentration has costs as well
as benefits, and if these vary in strength with the level of concentration, the implication is that
the relationship may be nonmonotonic, as argued by Morck, Shleifer, and Vishny (1988) and
by Wruck (1989). Estimates may also vary with data quality, with the estimation method
applied, and due to heterogeneity in the population of firms.
In this paper, we have suggested that estimates may also vary with the measurement of
concentration, an idea that has received little attention in empirical studies. We find that
7
increased concentration in the hands of a single large blockholder is associated with improved
corporate performance, that increased ownership by other blockholders does not improve
performance and may even decrease it, and that there is no evidence of nonmonotonicity in
the impact of any measure of concentration on performance.
The idea that the measure of concentration makes a difference is not a simple argument
either that results are sensitive to measurement considerations, or that one variable is superior
to another, on measurement grounds alone. Rather, it carries implications for our view of
how blockholders function and interact. It suggests that different forms of concentration –
based on a single large blockholder or on a group of smaller blockholders – have different
costs and benefits. Our findings that the marginal value of additional concentration is zero or
negative when it comes in the form of additional holdings by blockholders other than the
largest suggests that the additional blockholders have costs that exceed their benefits.
The usual analysis of the costs of concentration has focused on the possibility that a
dominant shareholder expropriates smaller investors (e.g., Shleifer and Vishny, 1997). We
have argued that other costs, perhaps more significant ones, may be associated with
blockholders quarreling with one another and with the decline in the liquidity of the firm's
shares, which lowers the usefulness of the firm's share price as a measure of managerial
performance and raises the costs of a takeover. Our findings suggest that these costs are
indeed more significant.
How generalizable are our findings? The BSE is a young market, but it appears to be
fairly typical of stock exchanges in continental Europe and throughout most of the world,
both in the degree of ownership concentration and the liquidity of trading. Our analysis
permitted behavior to vary between companies that have a dominant shareholder and those
that do not (the latter as an approximation for less concentrated Anglo-American type
ownership structures), and we have found no evidence of significant differences between
them: in both cases it is only the largest shareholding that matters. Of course, it would be
interesting to investigate these questions with other data sets from other countries, but that is
an effort we leave for future research.
8
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Prowse, Stephen D. (1992), "The Structure of Corporate Ownership in Japan." The Journal of
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10
Tables
Table 1: Descriptive Statistics for Concentration
of Ownership
Mean
Median
Std.Dev.
C1
39.4
42.2
19.4
C2
52.9
55.9
23.1
C3
57.7
62.9
23.7
Call
60.9
67.2
24.6
Source: Budapest Stock Exchange and Bank & Tőzsde
(1996 – 2000).
Note: Number of firm-years: 168. Ownership measured as
the average holding for year t and t-1.
Table 2: Descriptive Statistics for Employment,
Return on Assets and Operating Efficiency
ROAt – ROAt-1
Mean
0.00
Median
-0.01
SD
0.17
0.12
0.12
0.18
ROAt-1
Emp t-1
2407
907
4010
Log(OEt/OEt-1)
0.16
0.16
0.22
OE t-1
2.43
2.41
0.84
Emp t-1
2302
1066
3693
Source: Budapest Stock Exchange and Bank & Tőzsde
(1996 – 2000).
Note: Notes: 168 firm-year observations for ROA, 153
for OE. Return on Assets (ROA) defined as the ratio of
profit to equity. Operating efficiency (OE) defined as
the ratio of real sales to the average number of
employees. Profits and sales deflated by 2-digit PPIs.
OA not computed for financial institutions.
Table 3: Estimated Effects of Ownership Concentration on Firm
Performance
C1
C2
C3
Call
ROAt – ROAt-1
Std.
Coeff.
Error
0.294**
0.099
0.171
0.100
0.115
0.097
0.075
0.088
R2
0.760
0.746
0.743
0.741
Log(OEt/OEt-1)
Std.
Coeff.
R2
Error
0.942**
0.233
0.465
0.560*
0.247
0.404
0.313
0.240
0.383
0.249
0.215
0.381
Notes: 168 observations for the ROA, 153 for OE regressions. All regressions
include controls for previous performance, employment size, year effects, and firm
fixed-effects. Financial firms excluded from the regressions using operating
efficiency as dependent variable. ** = significant at 1 percent level, * = significant at
5 percent level.
11
Table 4: Estimated Impact of Individual Blockholders on Firm Performance
Largest block
Second largest
Third largest
R2 (within)
N
ROAt – ROAt-1
Coeff.
Coeff.
Coeff.
(Std. Err.) (Std. Err.) (Std. Err.)
0.294**
0.261**
0.258*
(0.099)
(0.103)
(0.107)
-0.189
-0.179
(0.167)
(0.183)
-0.046
(0.352)
0.760
0.763
0.763
168
168
168
Log(OEt/OEt-1)
Coeff.
Coeff.
Coeff.
(Std. Err.) (Std. Err.) (Std. Err.)
0.942**
0.830**
0.778*
(0.233)
(0.245)
(0.251)
-0.538
-0.361
(0.386)
(0.429)
-0.776
(0.815)
0.465
0.476
0.481
153
153
153
Source: Company Fact Books 1996 – 2000.
Notes: All regressions include controls for previous performance, employment size, year effects, and firm fixedeffects. Financial firms excluded from the regressions using operating efficiency as dependent variable.
** = significant at 1 percent level
* = significant at 5 percent level
Table 5: Performance Effects of Largest Blockholder and Other
Blockholders, By Majority or Non-Majority Stake of the Largest
C1*D1
(Call – C1) *D1
C1*(1-D1)
(Call – C1)*(1-D1)
R2 within
ROAt – ROAt-1
Coeff.
SE
0.284*** 0.113
-0.074
0.129
0.228*
0.134
-0.203
0.193
0.763
Log(OEt/OEt-1)
Coeff.
SE
0.963***
0.268
-0.133
0.296
0.745**
0.311
-0.702
0.435
0.419
Notes: 168 observations for the ROA, 153 for OE regressions. D1 = 1 if the
firm's largest owner owns more than 50 percent of the shares, 0 otherwise. All
regressions include controls for previous performance, employment size, year
effects, and firm fixed-effects. Financial firms excluded from the regressions
using operating efficiency as dependent variable. *** = significant at 1 percent
level, ** = significant at 5 percent level, * = significant at 10 percent level.
12