The importance of ownership structure related to firm performance
The importance of ownership structure related to firm performance
Name of University:
Tilburg University
Faculty name:
Faculty of Economics and Business administration
Graduation department:
Department of Finance
Name of Supervisor:
Rachel Pownall, MA
Subject:
Master Thesis
Name:
Maarten van Hoof, BSc
ANR:
610635
Date of submission:
31-10-2011
1
Abstract
This paper focuses on whether there is a pattern in the relationship between ownership
concentration and firm performance. Through the years, many things in the economic
environment have changed last century except the main goal of investors: collect money. From
past empirical research is known that investors could divert their risk by selecting a number of
shares and hold an investment portfolio. On the other hand, it could be useful to just have one
share in your portfolio. The question is whether this benefits or harms shareholders. Shareholders
with only one share in their portfolio bear more risk than when they diversify and so they will
ask for a higher return. This paper investigates whether it is beneficial to hold a block of shares
within a single company or diversify your risk. From OLS regression models in this thesis, no
significant relationship is found between ownership structure and firm performance, so no
pattern exists. After a robustness check, the results found, are confirmed.
2
Table of contents
I. Introduction
4
II. Past Research
6
III. Data and methodology
17
IV. Empirical Results
24
V. Discussion
29
VI. Conclusion and Recommendations
32
VII. References
34
3
I. Introduction
The origin of the problem between ownership and control takes us back to Adam Smith’s Wealth
of Nations. This man was the first who made the point that managers control money that is not
theirs. After that, Berle and Means (1932) found that production took place in firms where one
person was manager and owner at the same time. After the Industrial Revolution, the work of
Berle and Means, with the conclusion that ownership and control should be separated, became
the basis for further research until now. After that, the famous paper by Jensen and Meckling
(1976) about agency issues showed there were multiple problems between the principals
(shareholders) of the firm, and the agents (managers). This problem is known as the classical
agency problem. Later on, the agency issues turned to the problem between large and minority
shareholders within the same firm. Kang and Sorensen (1999) investigate the relationship
between the agency issues mentioned by Berle and Means and later on by Jensen and Meckling
and the Coasian view. They concluded that a firm is only a true competitor in the market when it
is able to minimize the number of contracts and optimize the relationship between manager and
shareholders of the firm. Ownership is concentrated in the hands of a few small shareholders
within a particular company these days (La Porta et al 1999). Past research found a positive
relationship between blockholdings and firm performance, Shleifer and Vishny (1986), Thomsen
and Pedersen (2000) and de Miguel et al (2004), a negative relationship Roe (1990), or no
relationship at all, Demsetz and Lehn (1985). In this paper, the relation between ownership
concentration and firm performance is tested directly due to regression analysis. Furthermore,
based on the results found from these regressions, it can be seen whether a pattern exists
throughout the years. The conclusion will give new insights in how this relationship will develop
now and in the future. This paper is comprised in the following way. Section II provides an
4
overview of theoretical and empirical research from the past. Section III describes the data and
methodology used in this study. In section IV, the regression output is presented and analyzed
and section V will discuss the relevance of the study. Last but not least, section VI concludes the
story and recommendations and limitations based on this study will be given. Note upfront: in
this paper the terms ‘shareholder’ and ‘blockholder” as well as ‘share’ and ‘stake’ will be used
interchangeably.
5
II. Past research
The foundation of the issue between ownership structure and firm performance lies in the work
of Berle and Means (1932). They first noticed a distinction between ownership and control
within growing firms after the Industrial Revolution. Furthermore, they argued that the
distinction between ownership and control brought specialization through the firms as a benefit,
and agency issues as a cost, since managers and owners have different goals within a firm. They
were not able to find any relationship between ownership structure and firm performance, since
there was no accurate data. On the other hand at the time, there was the Coasian view (1937),
where the tradeoff between firms and markets was explained. The most important advantage of a
firm as opposed to a market is that contracts are avoided and so multiple costs are saved. A
disadvantage of a firm is that different stages of the value chain will occur within the same firm
and this will lead to suboptimal outcomes. These topics were a long time of no importance in the
economic world, but this changed last decades. Based on the theories of Berle and Means and
Coase, Jensen and Meckling (1976) came up with their famous agency paper. In this paper, they
argued the problems that arise in a firm when ownership and control is separated from each other
and when contracts are avoided as much as possible. A few years later, Fama and Jensen (1983)
extended this theory. Barclay and Holderness (1989) discussed the monitoring issue within firms
and they concluded that large stakes within a firm decrease the chance of being a takeover target
which reduces firm value. These agency issues will be explained later in this section.
Furthermore, a lot of authors came up with a theory about the relationship between ownership
structure and firm performance. Shleifer and Vishny (1997) argue in their paper that
blockholdings and firm performance are positively correlated. This due to the fact that large
shareholders have a strong incentive to monitor the management and as a consequence can force
6
the management more easily to act in their interests. This will reduce agency costs and will
maximize shareholder value and so profit. Following the path of Shleifer and Vishny, a firm
performs best when it has a couple of large shareholders and no minority shareholders at all. In
line with this, Maury and Pajuste (2005) found that a couple of blockholdings within a firm can
jointly reduce the costs of private benefits, but that this will not always be the case, for example
when two blockholders within the same firm have different goals. Thomsen and Pedersen (2000)
support the view that having a large shareholder on board will increase firm performance in
general, but they argue the relation is a bell shaped curve. After a certain point, more shares in
hands of the majority shareholder will lead to entrenchment and adverse effects on performance.
They also measure blockholder identity as an important issue. This last point is strongly agreed
by Maury and Pajuste, who stated that blockholder identity is even more important than the
percentage shares hold. Different identities of potential shareholders will be explained later in
this section. Andres (2008) found no theoretical support that large shareholders will act in favor
of all shareholders and so he is not interested in maximizing shareholder value at any time. On
the other hand, Andres did not give arguments that show large shareholders will not maximize
shareholder value. No conclusion can be drawn from the above, except that the relation between
stock ownership and firm performance is suboptimal in any way. The last point is confirmed by
the theory of Becht et al (2008), who stated that a conflict between large shareholders leads to
less effective monitoring and in the near future can even cause a new set of agency problems.
According to Holderness (2003), large shareholders are only interested in holding large stakes
within a particular company for two reasons: they receive the shared benefits of control as well
as the private benefits of control. These benefits must exceed the cost of holding this large stake,
7
which brings an additional risk, because large shareholders are not able to optimize their
investment portfolio. Following Holderness, firms with at least one large shareholder must
perform better to cover the potential costs of holding such a large stake.
As can be read before, the relationship between ownership concentration and firm performance
seems to be positive at first glance. Almost all authors give the reduced agency costs and
effective monitoring as the main instruments to make this happen. In this study, the path of
Shleifer and Visnhy is followed. Since large investors have more power to monitor management,
this management should act more in their interest so shareholder value goes up. Furthermore, the
point made by Thomsen and Pedersen, that after a certain level of percentage hold, the adverse
effects will appear, seems unrealistic since a shareholder with 100% of shares will be in full
control of the firm and can decide what will happen with the investment possibilities.
The general problem in this paper is strongly connected with another type of financial problems,
the agency problems. As mentioned before, the separation of ownership and control is linked
with the Coasian theory. According to Shleifer and Vishny (1997) the central point of agency
theory is how investors receive their investment back plus a certain bonus from the firm. The
classical agency theory is about the problems that arise between principal (shareholder) and
agent (manager) in the well known paper of Jensen and Meckling (1976). They argue that
managers and shareholder in a particular firm have different goals. The shareholder is only
interested in value maximization whereas the manager can have private goals like empire
building or personal status. Solving these problems come at a high cost. Brailsford et al (2002)
would solve the high agency costs by giving the manager a part of the shares. Doing this, goals
8
of manager and owner are more in common. On the other side, when the stake of the manager
becomes too large, he will have the incentive to act in his own interest again. Large shareholders
will have the incentive to monitor the management more closely than minority shareholders do
and in line with this, they are more powerful to force the management to act in their behalf. In
cases where the blockholder dislikes the decisions made by the management, the blockholder can
set up proxy fights to replace management. This is an interesting point, since proxy fights rarely
occur, although large shareholder often disagree with management decisions. Reason is the costs
of proxy fights are high and minority shareholders are not interested in it. So, a large shareholder
will bear all the costs himself, whereas the benefits are shared between him and the minority
shareholders. De Miguel et al (2004) called this the free rider problem. Free riding results in
suboptimal solutions en performances. For example, when having a much diversified portfolio,
with 1% shares in company A, interest in share value of company A is much lower than when
having 10% of shares from company A in the portfolio. The free riding problem is confirmed by
Shleifer and Vishny (1986) who found that minority shareholders profit from efforts of the large
shareholder. Demsetz (1986) disagreed with the last point. He states that a large shareholder in a
company, especially in cases when this is the manager of the firm, has access to more and more
valuable information than do minority shareholders. Furthermore, they have the choice whether
he shares this information or not.
According to Maury and Pajuste (2005), the most important agency issues are no longer between
shareholder and manager in a firm, but between large shareholders and minority shareholders
within the same firm. Large shareholders have more power in a firm than minority shareholders
do. This seems logic at first glance, since they bear more risk. Nevertheless, large shareholders
9
can benefit minority shareholders by monitor the management very close and put pressure on
value maximization. On the other side, the can harm minority shareholders when their goals are
other than value maximization. This point is made by Burkart et al (1997) and gave new insights
in the agency issues. The traditional principal agent problem is replaced by a problem between
large shareholders and minority shareholders. The large shareholder becomes the most powerful
party within a firm and the question is whether he likes this powerful but vulnerable position or
not. This comes together with stock market liquidity.
The liquidity of the stock market is an important factor when it comes to monitoring (Maug
1998). He stated that in a more liquid stock market, large shareholders can more easily get rid of
their stakes and when they expect shares prices to fall, they sell their shares instead of force the
management out of the firm. On the other hand, when stock markets tend to be less liquid,
shareholders will monitor the management more closely. However, when stock market liquidity
increases, monitoring decisions by large shareholders are not influenced. As mentioned before,
on the one side, more liquid stock market implies more incentive to sell large stakes, but on the
other had it is a relative cheap way to obtain additional shares. Knowing this, liquid markets
could help large investors overcome the free rider problem.
The benefit of monitoring comes forward when studying the paper of Pagano and Roell (1998).
They argued that when an ownership structure reaches a certain limit of concentration, large
shareholders are willing to pay a certain amount to monitor the management. In order words,
they invest in monitoring to save their returns. When shares are more concentrated, equity
10
finance will be less costly, whereas monitoring costs increases and agency costs decreases. As a
result, the manager of the firm can spend less money for own consumption so the return to
shareholders will increase. In a world with less concentrated ownership the reverse is true. So
this implies a positive relationship between ownership concentration and firm performance. In
addition to this, Thomsen and Pedersen argue that portfolio risk of large shareholders is larger
than that of minority shareholders so they are more interested in monitoring the management in
the first place.
Besides all theoretical approaches mentioned above, a lot of empirical research has been done on
the question whether a relationship between ownership concentration and firm performance
exists. First of all, empirical research done by Thomsen and Pedersen (2000) implied a bell
shaped curve on the relationship between ownership structure and firm performance. They found
a growing performance when ownership concentration increased. After 51% of shares additional
performance is low, however. The top of the curve lies at 83% when market to book value is the
dependent variable and 60% when return on assets is. McConnell and Servaes (1990) got the
same results as Thomsen and Pedersen although the maximum ownership stakes are lower in
both cases. De Miguel et al (2004) found a cubic shaped figure consisting three different areas.
In the first segment, which counts blockholdings from 0 till 35%, firm performance and
ownership concentration are positive related. In the second segment, from 35 till 70%, there is a
negative relation which is called the entrenchment effect, and in the last segment from 70 till
100%, the positive relation appears again but is less strong. From the study of Claessens et al
(2002) can be concluded that there is a positive relationship between firm performance and
ownership for the largest shareholder in that firm, whereas Shleifer and Vishny (even before
11
their theoretical paper in 1997) found a significant positive relationship for blockholdings larger
than 20%. However, they did not mention anything about the other shareholders or what will
happen in cases of more than one large shareholder. Maury and Pajuste (2005) found that
multiple blocks can have a positive influence on firm performance, but that this will not
necessarily be the case. This relation is linked to the size of the blockholding and blockholder
identity. This last point is explained in more detail later on. La Porta et al (1999) and Gompers
and Metrick (2001) found a positive relationship within large firms, where they classify large as
total assets over $100.000.000. Last but not least, Kang (1998) found that more powerful
shareholders in terms of voting rights are more active and so monitor the management more
closely. He concluded that active shareholders do benefit firm performance where passive
shareholders do not.
So, up to this point, the positive relationship that came forward from the theoretical part is
agreed. However, Andres (2006), Holderness and Sheehan (1988), as well as Demsetz and Lehn
(1985) did not found a statistical significant relationship between ownership structure and
accounting profitability. Demsetz and Lehn, in their cross country study, found ownership
concentration and control of the firm in the same hands can be beneficial. They found also that
firms are too different to compare and that even if there is a relationship between blockholder
ownership and firm performance, this is heavily influenced by the environment (law, climate,
economic situation of the country of origin). Another point here could be that one large
shareholder is beneficial to firm performance, but that two or more blockholders jointly undo this
effect.
12
Thomsen et al (2006) and Roe (1990) report a significant negative relationship between
ownership and performance. Thomsen et al mention agency issues between large and minority
shareholders as the most important factor for this. Roe blame the lack of inside shareholding as
the largest problem. His point is that a substantial amount of inside block ownership will
improve firm performance. This point is supported by Pagano and Roell (1998) who stated that
the controlling shareholder, whether this is an inside or outside shareholder can reduce profit
diversion by monitoring the management very close. In cases of inside ownership, the
blockholder is mostly the founder of the company or is in the board of directors.
Besides the size of blockholdings, the distribution of voting rights across all shareholders is very
important. In some firms, a shareholder owns for example 55% percent of the shares, but only
10% of voting rights. In this case, he is less powerful than when he owns 20% of the shares, and
40% of the voting rights. Maury and Pajuste comment on this when founding that the more
equal the voting rights are spread between the large shareholders, the better the economic
performance is. They name family firms as the best example to prove this.
From the above is known that the relationship between ownership concentration and firm
performance can have a significant positive, significant negative or no relationship at all.
Following the theoretical arguments of Shleifer and Visnhy, a positive relationship is most likely
to occur. Because this paper focuses not only on the relationship, but mainly on the pattern there
may exists, the main hypothesis which will be tested in this is paper is: There exists a pattern in
the relationship between ownership concentration and firm performance.
13
Thomsen and Pedersen (2000) found the identity of blockholders to be very important in the
ownership/performance relationship. They argue that different types of blockholders act different
although the percentage shares held is the same. This comes mainly through the fact that many
investors are intermediates and not final investors.
Institutional investors can be characterized by having arms length contracts with firms. The most
important goals they have are shareholder value and liquidity (Thomsen and Pedersen 2000).
Shareholder value gives them a cash flow and liquidity gives the institutional investor the
possibility to sell their stake easily in cases the management will not follow the goal of
shareholder value. According to Gompers and Metrick (2001), institutions are a growing market
within the shareholder world. In 1996, their size was twice as big as in 1980. The largest stake in
the institution segment are pension funds followed by investment companies or mutual funds.
The third group are insurance companies, fourth are bank and trust companies. The smallest
groups in this segment are foundations.
An important upcoming group in this segment are hedge funds. Klein and Zur (2006) define a
hedge fund as an institution which buys at least 5% of shares of a particular firm. Klein and Zur
further discuss the difference between active and passive institutions, where they define active
institutions as institutions where the management is monitored closely. In cases of bad
management, they organize proxy fights where they replace management by election. Passive
institutions, on the other hand, just sit down and earn their money.
14
Family firms are not only more profitable than widely held firms; they outperform companies
with other types of blockholders (Andres (2006)). This is only the case when members of the
founding family are actively involved in the executive or supervisory board. If not, performance
does not distinguish from other companies; other blockholders affect performance either in the
adverse way or not at all. Apart from the identity problem, family block ownership is the only
variable showing a significant positive relation.
Differences with other stockholders: families are a unique type of investor who has exceptional
concerns over firm survival and extreme incentives to monitor management therefore.
Investment decisions are long term based instead of short term, because these family firms has to
be passed on generation to generation. Family relations generate trust and loyalty. The other side
is that family ownership and control in a firm leads to potential suboptimal decision making
since everybody acts in the way the family wants.
Government ownership integrates the vision of the government within a particular firm. Nonprofit organizations are most likely to be chosen for government ownership, since the goal for
the government is most of the time the influence in how the company is managed, not
shareholder value.
Ownership of one firm in another, so called corporate ownership, has become common last
decades (Thomsen and Pedersen (2000)). Especially firms which are vertical partners in the
15
value chain will control the firm below or above itself to make the total structure more effective.
Results of this method are mixed, however. On the one hand, improved structure effectiveness
leads to lower costs, but on the other there will appear a kind of hierarchy which is not optimal
for at least one of the two firms.
However it is prohibit in the United States, bank ownership does play an important role in the
European stock market. With bank ownership, companies can have privileged possibilities to
additional resources as capital or cash. Banks are a credible party to involve in a company
(Thomsen and Pedersen (2000)). Cable (1995) found a positive effect when a bank is a large
shareholder in a company. At last, to underline the importance of blockholder identity, Makhija
and Spiro (2000) did research about different identities and stock value and found a significant
positive influence for insiders, foreigners and restitutions but not for funds.
Although it seems that blockholder identity indeed plays an important role, in this study only
individual blockholders are discussed. To investigate whether the identity of a blockholder solely
influences firm performance, the total amount of shares in hands of blockholders is divided into
five subparts of blockholders.
The five different sub categories are employee shareholdings, officer shareholdings, director
shareholdings, outside shareholdings and affiliated shareholdings.
16
III Data and methodology
The data used in this study to investigate whether there is a pattern in the relationship between
ownership structure and firm performance includes Fortune 500 firms. The Fortune 500 list
yearly lists the largest 500 firms, in terms of revenues, headquartered in the United States.The
Fortune 500 was preferred over for example the S&P 500 because of its positive and reliable
attitude, as mentioned by Golicic et al (2010). The main data source used in this empirical study
is the Wharton Research Data Services (WRDS). Datasets used are Blockholders, Compustat,
CRSP and Compustat/CRSP Merged. Time horizon for this study is 1998 till 2001, since no
more accurate data is available for the percentages shares held by different types of blockholders
needed for this study and which thus results in four separate databases ( one each year). The
Fortune 500 firms used in the study should have a data ticker in the WRDS system so the
necessary data could be collected. After all data was collected, a total number of 1010
observations were valuable. Divided by year, these number of observations are: 1998, N=242,
1999, N=250, 2000, N=259 and 2001, N=259.
The method used is regression. Ordinary least square (OLS) regression is chosen because it is the
most practical way to investigate whether there exist a significant relationship between a
dependent variable and a (set of) independent variable(s).With OLS regression, a line is fit
through all observations for which the sum of the errors is the least. In this study, so called
multiple regression, or multivariate regression is used which means that more than one
independent variable is regressed on the dependent variable at the same time. In order to answer
17
the main question, several steps have to be taken. An OLS multivariate regression will have the
following general model:
Yi= β0+ β ixi+εi
First of all, using the multivariate regression, for all four year regression is run in order to
investigate whether a relationship exists between ownership structure and firm performance for
that specific year. These regressions are run with return on assets (ROA) as well as return on
equity (ROE) as dependent variable. Independent variables are the total percentage shares by
blockholders in year t, divided by subcategory. Five subcategories are mentioned which are,
affiliated, non officer director, employee, officer and outside blockholders. This is done after the
point made by Thomsen and Pedersen (2000) that blockholder identity is important in the
influence the blockholding has on firm performance.
In the second step, the results for each year are compared in order to see whether a pattern exists
through the years. When comparing the results for those four years, most attention is paid to the
OLS regression line. When a positive pattern is observed, the line should have a slope which is
somewhat steeper than in the previous year. Is the pattern negative, this slope should be less
steep. Another possible outcome is that there is no pattern at all. In this case, the line can be flat,
in cases there is no relationship between ownership structure and firm performance at all, or the
18
slope in the four years is the nearly the same, which could imply that the relationship between
ownership structure and firm performance is somewhat steady irrespective of time.
In the third step, the solutions found by step two are checked by a so called robustness check.
This robustness check either confirms or rejects the results found from the OLS model. In this
case, since not every firm has data for all of the four year, there appears an unbalanced panel,
where ‘year’ is the panel variable. Panel analysis is used in cases where time could play an
important role for regression outcomes. This regression is run for the ROA as well as the ROE
model. In this unbalanced panel model with fixed effects, the general model that holds is:
Yit= βo+ βixit+εit
After having completed the three step procedure, the main hypothesis can be answered and a
conclusion can be drawn. To set up this study, a list with all variables used in this study is
presented in table 1.
19
abb.
variable name
function
Y1
Return on assets
dependent variable, measure of firm performance
Y2
Return on equity
dependent variable, measure of firm performance
AFF
affiliated block ownership
subcategory of blockholders 1
NOF
non officer director block ownership
subcategory of blockholders 2
EMP
employee block ownership
subcategory of blockholders 3
DIR
director block ownership
subcategory of blockholders 4
OUT
outside shareholders block ownership
subcategory of blockholders 5
TURN turnover
control variable for firm risk
INTA
control variable for asset specificity
intangibility
TOBQ Tobin's Q
control variable for firm risk
SIZE
control variable for firm risk
Firm size
Table 1. Variables, variable names, and function
Firm performance will be measured in two ways. Either return on assets (Y1) or return on equity
(Y2) will be the dependent variable. Return on assets is calculated as the after tax income of a
company divide by the total assets for that fiscal year. Return on equity is measured as the after
tax income of a company divided by the total book value of equity for that fiscal year. Return on
assets and return on equity are chosen because history showed that they are a good performance
indicator and are widely known. The variable affiliated blockholders (AFF) includes
shareholders which hold blocks within a company but are not actively involved in monitoring the
management. The second subcategory is about the non officer directors (NOF). This group
officers is not in the executive board and most of the time are more long term oriented. The third
group is an important one, the employees (EMP), who are actively involved in the production
process and are in advance expected to influence firm performance positively if they hold shares.
20
Fourth are the directors (DIR) of the firm. These are the executive directors of the firm who are
in the agency of Jensen and Meckling (1976) principal and agent at the same time. Outside
blockholders (OUT) is the last group. Institutions, banks, large companies or just a wealthy
person can belong in this category. To avoid misunderstandings, blockholdings in this study are
shareholdings of five percent or more within the same company.
The control variables should preserve the results for biases. Turnover (TURN) is a control variable that
controls for firm specific risk. Turnover is measured as sales divided by total assets and therefore is a
percentage. Intangibility (INTA) gives the ratio of intangible assets in relation to total assets. It is a
control variable for asset specificity and is calculated as intangible assets divided by total assets. Tobin’s
Q (TOBQ) gives the relation between market value and bookvalue within a firm in order to see a firm is
credit worthy. Tobin’s Q controls for firm risk in cases that firms do report their results in a proper way
and is calculated as market value divided by book value. Firm size (SIZE) is calculated as the natural log
of the book value of total assets and controls for firm risk.
After all the variables are explained, the model can be expressed. Note that both models are exactly the
same, except in model the upper model the dependent variable is return on assets and in the lower model
it is return on equity.
Y1= β0+ β1aff+ β2nof+ β3emp+ β4dir+ β5out+ β6turn+ β7inta+ β8tobQ+ β9size+ε
Y2= β0+ β1aff+ β2nof+ β3emp+ β4dir+ β5out+ β6turn+ β7inta+ β8tobQ+ β9size+ε
21
For each of the years 1998, 1999, 2000 and 2001 the descriptive statistics are given in table 2 A/D.
min
affiliated %
non officer %
employee %
officer %
outside %
total %
ROA %
ROE %
turn (sales/assets)
inta %
TobQ (mv/bv)
size (log assets)
0.00
0.00
0.00
0.00
0.00
0.00
-20.08
-28.83
0.07
0.00
-2.92
14.76
max
38.90
25.90
21.25
36.20
80.10
80.10
37.49
474.43
4.97
66.31
36.92
23.08
st.dev
mean
5.44
3.74
3.71
4.01
13.33
15.67
5.44
33.60
0.87
13.64
4.19
1.29
1.56
0.91
1.25
1.29
12.22
17.23
4.92
17.30
1.07
11.30
4.06
18.47
median
0.00
0.00
0.00
0.00
8.20
14.86
3.91
14.51
0.85
6.38
2.67
18.40
Table 2A descriptive statistics 1998, N=242
min
affiliated %
non officer %
employee %
officer %
outside %
total %
ROA %
ROE %
turn (sales/assets)
inta %
TobQ (mv/bv)
size (log assets)
0.00
0.00
0.00
0.00
0.00
0.00
-42.98
-175.68
0.06
0.00
-40.26
16.04
max
38.11
25.10
18.84
30.80
80.10
80.10
26.80
94.70
4.43
66.04
40.63
22.32
st.dev
mean
4.49
2.81
3.63
4.24
13.96
15.31
7.04
24.63
0.84
14.64
5.20
1.16
Table 2B descriptive statistics 1999. N=250
22
1.19
0.59
1.19
1.17
13.32
17.46
4.79
12.31
1.12
12.65
3.96
18.36
median
0.00
0.00
0.00
0.00
9.35
14.19
4.19
15.15
0.98
6.61
2.61
18.27
min
affiliated %
non officer %
employee %
officer %
outside %
total %
ROA %
ROE %
turn (sales/assets)
inta %
TobQ (mv/bv)
size (log assets)
0.00
0.00
0.00
0.00
0.00
0.00
-13.63
-212.74
0.05
0.00
-37.42
15.09
max
38.07
48.00
19.17
31.40
80.10
80.10
24.47
76.72
4.94
67.34
55.02
22.92
st.dev
mean
4.81
5.59
3.82
3.82
13.21
15.09
5.46
22.60
0.93
14.53
5.73
1.16
1.27
1.35
1.43
0.95
19.95
18.94
5.71
14.65
1.14
11.62
4.24
18.25
median
0.00
0.00
0.00
0.00
11.10
17.50
5.03
15.18
0.90
6.58
2.73
18.16
Table 2C descriptive statistics 2000. N= 259
min
affiliated %
non officer %
employee %
officer %
outside %
total %
ROA %
ROE %
turn (sales/assets)
inta %
TobQ (mv/bv)
size (log assets)
0.00
0.00
0.00
0.00
0.00
0.00
-51.51
-125.99
0.07
0.00
-17.24
14.66
max
37.93
35.20
19.95
37.80
80.10
80.10
48.15
325.52
4.29
61.71
73.82
22.32
st.dev
mean
4.55
3.92
3.82
3.94
13.28
14.66
8.02
31.41
0.89
13.77
6.18
1.22
Table 2D descriptive statistics 2001, N=259
23
1.09
0.87
1.36
1.00
13.52
17.83
4.90
14.64
1.14
11.22
4.45
18.44
median
0.00
0.00
0.00
0.00
10.61
15.95
3.92
14.63
0.90
5.22
2.74
18.39
IV. Empirical results
In this part the outcomes of the regression analysis are shown and interpreted. As mentioned in
the three step procedure in the previous section, the four years are tested separately on the fact
whether there is a relationship between ownership structure and firm performance for that year.
Results of those regressions mentioned in steps one and two are presented in table 4.1. As can be
seen in the table, for every variable, two numbers are reported. The upper number is the
regression coefficient and the lower number is the corresponding t-statistic. The t-statistic judges
whether a certain regression coefficient is statistically significant or not. For this study, a tstatistic larger than 1.96 is assumed to be statistical significant, and a number lower than 1.96 as
statistically insignificant. Below the numbers for the different categories of blockholders, for
each study the R-square, F-value and number of observations N, are given.
To begin with the ROA analysis for 1998, it can be seen that none of the five different
blockholder categories shows a positive or negative significant relationship. The regression
coefficients are slightly positive or negative for all, but the t-statistic does not reach the required
1.96. Looking further into the results of 1998, only the regression coefficient of the control
variable Tobin’s Q shows a significant positive relationship (0,691), with t-statistic 9,830, which
means that if the ratio between market and book value increases by 1, ROA would increase by
69,1%. The only statistical significant relationship for this study is the influence of intangibility.
As can be seen from the table, influence is very small -0,004, but significant (-2,030). This
implies for an increase of 1 in the ratio between intangible assets and total assets a decrease of
0,4% in return on assets. The R-square of 0,358 indicates that the model includes 35,8% of the
24
total variation of dependent variable. The F- value of 14,374 is somewhat small which means
that the ratio between explained variance and unexplained variance is relatively low. For the
return on equity model of 1998, results are nearly the same. None of the five different types of
blockholders does have a statistical significant relationship to the dependent variable. Here, as in
the ROA model, the only significant positive relationship comes from the control variable
Tobin’s Q. Note, the R-square of only 6,7% is extremely low which means that 93,3% of the
variation in the model remains unexplained. In addition to this, the F-value only takes a level of
1,857. Number of observations is 242. Based on this 1998 study, for the ROA as well as for the
ROE model, no statistical significant relationship can be found.
For the 1999 study, ROA model, the regression coefficients of the five different blockholder
categories are all close to zero, and very insignificant. Looking at the control variables, only
Tobin’s Q reports a significant t-statistic (-0,966) for the regression coefficient of 0,541.
Furthermore, 20% of the total variation is explained by the model, the F-value is only 6,656 and
number of observations is 250. For the corresponding return on equity model for this year, only
the numbers are different from the ROA model, but only Tobin’s Q reports a statistical
significant relationship. R-square and F-value are slightly higher for this model, number of
observations is the same, as expected. For the 1999 study, no statistical significant relationship
can be noted between ownership structure and firm performance.
In the 2000 model, the return on assets model does not provide a significant relationship of one
of the five categories of blockholders and the dependent variable. For control variables, only
25
Tobin’s Q is noted to be statistical significant with a value of 0,405 and a t-statistic of 7,453.
From this perspective, none of the blockholder groups is significant related to return on assets.
R-square is 22,1%, F-value 7,859 and number of observations 259. In the return on equity model
for this year, a negative statistical significant relationship is discovered between the outside
blockholders of the firm and return on equity. The regression coefficient of -0,250 implies a
decline of 25% in ROE for every percent increase of the shares hold by outside blockholders.
The corresponding t-statistic is -2,922. Furthermore, Tobin’s Q is statistically significant related
to ROE with a value of 2,361. The R-square here is 39,5% and F-value is 18,096. Number of
observations is 259. For 2000, a statistical significant negative relationship between outside
blockholders and the dependent variable can be found for the ROE model.
For the 2001 model, none of the five blockholder types scores statistical significant results in the
ROA model. Here only the control variable Tobin’s Q is statistical significant. The same is the
case for the ROE model. Number of observations for this year is 259, the R-square in the ROA
model is 22,7% and 52,2% in the ROE model, where the F-values are 8,146 and 30,258,
respectively. For 2001, there is no significant relationship to be reported between any of the
blockholder types and firm performance.
26
dep.var.
ROA
ROE
Explan.Variable
AFF
0.043 -0.054
0.809 -0.134
NOF
-0.096
0.096
-1.229
0.166
ESOP
-0.093 -0.475
-1.194 -0.818
OFF
-0.059 -0.179
-0.960 -0.389
OUT
0.026
0.145
1.196
0.888
TURN
0.513
3.140
1.370
1.126
jaar
1998 -0.170
-2.030 -0.108
TOBQ
0.691
1.742
9.830
3.327
SIZE
-0.764
0.646
-0.298
0.338
Adjusted Rsquare
0.358
0.067
F-value
14.374
1.857
N
242
242
1999
ROA
ROE
2000
ROA
ROE
2001
ROA
ROE
0.034
0.363
0.047
0.321
0.009
0.082
0.044
0.453
0.005
0.163
1.931
3.215
-0.027
-0.966
0.541
6.846
0.499
1.153
-0.259
-0.831
-0.125
-0.254
0.299
0.782
0.190
0.578
-0.124
-1.245
2.967
1.478
-0.033
-0.351
2.405
9.100
2.777
1.919
0.050
0.783
0.099
1.807
-0.136
-1.688
0.006
0.079
-0.029
-1.252
0.672
1.715
0.011
0.506
0.405
7.453
-0.142
-0.442
0.017
0.074
0.040
0.200
-0.523
-1.778
0.118
0.396
-0.250
-2.922
0.792
0.554
-0.034
-0.446
2.361
11.918
2.342
1.998
0.121
1.222
0.196
1.701
-0.053
-0.448
-0.005
-0.045
-0.033
-0.949
1.076
1.761
0.000
-0.005
0.544
7.423
-0.645
-1.410
0.052
0.171
0.263
0.742
-0.071
-0.194
0.239
0.679
-0.197
-1.854
2.837
1.507
0.080
0.782
3.672
16.251
0.231
0.164
0.200
6.656
250
0.269
9.833
250
0.221
7.859
259
0.395
18.096
259
0.227
8.146
259
0.522
30.258
259
Table 3. Outcomes of the regression analysis
Robustness check
In order to see whether the results from the previous part are correct, a panel- analysis is
performed to double-check the results. As can be seen from the output of this panel analysis in
table 4, in the return on assets model none of the five different sub categories reports a t-statistic
larger than 1.96 which is necessary to label an independent variable as statistical significant.
Looking at the R-square of 4%, this does not seem to be very high, although the P-value of the
model indicates that the model as a whole is significant. Also the return on equity model does
27
not report any statistical significant relationships except the control variable Tobin’s Q. Here the
R-square is 26.6%, but as in the return on assets model, the P-value indicates the model is
significant as a whole. From these robustness results can be concluded that the results found in
the previous OLS regression are valid.
dep.var.
ROA
Explan.Variable
AFF
-0.006
-0.060
NOF
0.218
1.680
ESOP
-0.108
-0.800
OFF
0.016
0.090
OUT
0.008
0.300
TURN
0.636
2.360
INTA
-0.006
-0.440
TOBQ
-0.275
-2.180
SIZE
-0.486
-2.420
R-square
0.040
F-value
3,90(p>0001)
N
283
ROE
0.662
1.600
0.357
0.680
0.060
0.110
-0.044
-0.070
-0.043
-0.380
1.974
1.820
0.037
0.620
10.275
20.170
1.630
2.010
0.266
45.95(p>0000)
283
Table 4. outcomes of the panel analysis
28
V. Discussion
The results presented in the previous sector do not seem to have an important impact on the
existing knowledge at first glance. The results indicate that there is no relationship between
structure ownership and firm performance, which is discovered before by Demsetz and Lehn
(1985). However, looking deeper into these results, one can conclude that with the absence of a
statistical insignificant relationship between ownership structure and firm performance for all of
the four years discovered, it does not matter who actually owns the firm to improve the
profitability. In other words, it does not matter whether a firm holds on to a few large
shareholders or a large number of minority shareholders throughout the years. For firms,
previous results are important to know and understand. Based on this study, they would know
that when ownership structure changes dramatically in one year, firm profit in terms of ROA and
ROE will not differ statistical significant over the next few years, ceteris paribus. In line with
this, and holding the ceteris paribus condition, share prices are not affected by a change in
ownership structure. According to the results, only the name of the shareholder and the
percentages held by the different shareholders will change. On the other hand, firms cannot make
money by changing their ownership structure. In the firms perspective, they would choose for an
ownership structure where agency costs are less, generally spoken. An exception here of course
is family firms, where the founding family normally holds on to a large stake in order to have
controlling power. As stated by Demsetz and Lehn (1985), firm performance is affected by other
factors than ownership structure. They came up with environmental factors as an important issue.
In order to investigate whether environmental factors, such as law, trade restrictions or
geographic location are important, one should set up two identical samples with different
environmental circumstances to check a potential significant difference in profit.
29
For investors, on the other hand, it could be an incentive to not buy additional shares, since the
results indicate that an increase in share ownership will not directly improve firm performance.
Of course, in this study, the effects of monitoring and voting rights are not included, but ceteris
paribus, shareholders do not benefit the next few years from an increase in share ownership.
Furthermore, share prices will not change much when an important change in ownership
structure is announced, ceteris paribus.
The point mentioned by Thomsen and Pedersen (2000), that blockholder identity is important,
does not fit according to this study. The identity of the shareholder is not a clear predictor for a
statistical significant change in profit, so firms or majority shareholders do not have to opt for a
certain shareholder in order to increase performances. For this reason, firms can be irrespective
what kind of shareholder to have on board and how large the stake is this particular shareholder
has, ceteris paribus.
Furthermore, some special attention is paid to the differences between the total market in the
United States and the United Kingdom on the one hand and the European and Asian Market on
the other. In the United States and United Kingdom, the level of ownership concentration tends
to be lower than in continental Europe. Question is, when this study has been done for European
firms, whether the outcomes would be the same or not. One could assume, that if level of
ownership concentration is higher, monitoring is higher, agency costs are lower and therefore the
overall profit is higher. For Asian firms, especially Japanese, firms are connected in a certain
Keiretsu, which is a kind of family of individual firms. The most important objective there is not
30
shareholder value, but the value of the Keiretsu as a whole. With a substantial different goal,
outcomes from the same study that has been done for United States firms could have total
opposite results. So to check whether these results are valid in the European and Asian, one set
up an identical study for these areas and compare the results to the results found in this study.
At last, there could be some possibilities to improve the model as a whole. For example, several
categories of blockholders could be used together in order to check whether they are jointly
significant or not. Another possibility is the use of interactive terms or quadratic terms. This is
done a few times for the year 1998, but results did not tend to differ much from the presented
results in this paper, so the author decided to stop this way of measurement for the other years.
Also other predictors of profitability could be chosen which could perhaps influence the results.
31
VI. Conclusion and recommendations
In this paper the focus is on the fact whether there exists a pattern in the relationship between
ownership structure and firm performance. The relation between ownership structure and firm
performance is many times investigated. As mentioned before, some found a positive
relationship ( Schleifer and Vishny (1989), Thomsen and Pedersen (2000), others, like Roe
(1990)found a negative relationship and the third group, for example Demsetz and Lehn (1985)
found no relationship at all. Based on the results found by this empirical research the conclusion
can be drawn that there is no statistical significant relationship between ownership structure and
firm performance using ROA and ROE as dependent variables, Fortune 500 firms as the source
for the investigated firms, and time period 1998-2001, for the years separately. Only for the year
2000, in the ROE model, an increase in outside blockholder shareholdings would imply a decline
in ROE, significantly. If all years are taken together, there will be no pattern in the relationship
between ownership structure and firm performance. To force up the results found, a robustness
check is done, which confirmed the results found previously. These results are in line with
Demsetz and Lehn (1985), who stated environmental influences are much more important than
ownership structure. So, the main hypothesis has to be rejected, since no pattern between
ownership structure and firm performance exists.
To improve this research, one can look for more accurate data or investigate for example the
European market. The relationship between ownership structure and firm performance is very
interesting to study, since it can give shareholders and managers a manual to act in certain
periods. Looking at the point made here, the pattern between these two economic sources, a
32
wider time horizon and more firms included can lead to different results. Also other dependent
variables and more or other control variables could influence or force the results in a certain way.
33
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