Product Market Competition and Agency Conflicts: Evidence from the Sarbanes Oxley
Law
Vidhi Chhaochharia
University of Miami
Yaniv Grinstein
Cornell University
Gustavo Grullon
Rice University
Roni Michaely
Cornell University
Abstract
We study the effect of product market competition on the alignment of incentives between
management and shareholders in public U.S. firms. We find that competition reduces agency
conflicts. Firms in less competitive industries are less efficient than firms in more competitive
industries and the Sarbanes Oxley regulation, aimed at mitigating agency conflicts, improved
efficiency mainly in the less competitive industries. Product market competition is also a
substitute for other governance mechanisms as firms in less competitive industries are more
likely to employ stronger governance mechanisms to align management interests with those of
the shareholders.
1. Introduction
The agency conflicts between management and shareholders and the importance of having
mechanisms to overcome the conflict have been the center of attention in corporate finance
research in the last thirty years. Among these mechanisms are compensation contracts (e.g.
Holmstrom 1979), financial contracts (e.g., Jensen and Meckling 1976), monitoring by the
board of directors (Fama and Jensen 1983), the market for corporate control (Shleifer and
Vishny 1986), and others.
While research on the importance of these mechanisms on incentive alignment is abundant,
we still find ourselves perplexed by how well corporations do even when many of these
mechanisms are not in place. For example, Gomes (1997) shows that firms are adhering to
protecting the rights to shareholders even in environments in which there is little legal
protection and very few mechanisms to align incentives. Allen and Gale (2000) point to the
phenomenal success of foreign car maker Toyota, despite the lack of internal governance
mechanisms or takeover threats to align incentives. Clearly, in these cases, management finds
itself motivated not to waste corporate resources because other channels are used to align
incentives, even though no formal mechanisms are in place. One such a potential channel is the
product market competition that the firm faces.
In this study we explore the role of product market competition in aligning managerial
incentives in public U.S. corporations. Looking at U.S. public firms between 2001 and 2005, we
study the relation between product market competition and the level of efficiency in these firms.
We use two main measures of the level of efficiency in firms. The first measure is the ratio of
general, sales, and administrative expenses to sales. This measure captures the overhead costs to
the firm as a fraction of its revenues. The second measure is the ratio of sales to assets. This
measure captures the amount of resources that are put in place to generate a given revenue level.
Both measures have been used extensively in past studies to capture corporate efficiency.
1
Consistent with previous studies, we find that firms in less competitive industries are less
efficient than firms in more competitive industries. The results are significant in each and every
year in the sample and are robust after controlling for industry sectors, size, and firm age.
However, the relation between industry and corporate efficiency could be driven by the
mere fact that different industries have different production functions. Thus, it is possible that
firms in less competitive industries are required to spend more resources to achieve the optimal
level of efficiency than firms in more competitive industries. To account for this possibility we
study the effect of the Sarbanes Oxley law on the level of efficiency in more competitive and
less competitive industries. The Sarbanes-Oxley law was enacted as a result of the corporate
scandals in companies like Enron, Tyco, and others. The law included provisions such as
increased penalties for officers who are charged with fraud, enhanced scrutiny over external and
internal auditors, enhanced disclosure of financial statements, enhanced disclosure on insider
trading, and other restrictions. To the extent that the incentives of managers in firms in more
competitive industries are more aligned with shareholders’ interests, they should be less
affected by the monitoring requirements than managers in firms in more competitive industries.
We find that after the approval of the Sarbanes Oxley law in 2002, firms that belong to less
competitive industries experienced a significantly larger increase in efficiency than firms that
belong to competitive industries. This finding is consistent with the hypothesis that governance
mechanisms are more relevant to firms that face lower product market competition.
We further explore the role of product market competition in aligning incentives by
decomposing the efficiency gains of incentive alignment between small and large firms. There
are two important reasons for differentiating between small and large firms. First, smaller firms
might be more vulnerable to competition than larger firms (e.g., Bolton and Scharfstein 1990).
Second, governance regulations could have a different effect on small firms and large firms. We
2
find that the positive effect of the Sarbanes Oxley law on efficiency affected both large and
small firms.
We also explore the relation between product market competition and the use of other
governance mechanisms to align managerial incentives. We find that product market
competition substitutes for the need to align managerial incentives through other governance
mechanisms. Firms in less-competitive industries have more mechanisms in place than firms in
competitive industries. For example, firms in less-competitive industries have less anti-takeover
provisions, and their board is more independent than firms in more competitive industries.
Our study is reminiscent of the study of Giroud and Mueller (2009) who explore the effect
of the business combination laws in the U.S. in the 1980’s on firms in more competitive and
less competitive industries. Business combination laws reduced the threat of hostile takeovers,
thereby mitigating the disciplinary forces of the takeover markets. Giroud and Mueller (2009)
find that the business combination laws in the 1980’s had negative effect on the efficiency and
the profitability of firms in less competitive industries. The interpretation of their finding is that
the disciplinary role of the takeover market is more important in firms in less competitive
industries. Our results are similar to the results of Giroud and Mueller (2009) since we also find
a stronger effect of governance rules on efficiency in less competitive industries. However, the
ruling event in Giroud and Mueller (2009) is different than the ruling event in our study – a
difference that allows us to shed additional light on the role of governance mechanisms in firms.
In their study, the ruling event is related to external governance mechanisms (the takeover
market). In our study the ruling event is related to internal governance mechanisms (enhanced
accounting reports, enhanced disclosure of insider trading, higher penalties on fraud etc). We
find that the main effect of the anti-takeover laws in the 80’s was on small firms in concentrated
industries, but did not have any effect on large firms in concentrated industries. In contrast, both
3
large firms and small firms in less competitive industries were affected by the Sarbanes Oxley
law.
Our study belongs to a growing literature that studies empirically the role of product market
competition in aligning managerial incentives. Several studies have been focusing on the direct
relation between product market competition and efficiency. For example, Graham, Kaplan, and
Sibley (1983) find that the deregulation of the airline industry in the U.S. was associated with
efficiency gains. Nickel (1996) studies differences in production efficiency between eastern
European firms, which faced less competition, and western European firms, which faced more
competition. Caves and Barton (1998), Green and Maers (1991), and Caves (1992) find that
above a certain level of industry concentration, technical efficiency is reduced. Nickel,
Nicolitsas and Dryden (1997) find that the higher the level of competition the higher the level of
growth in productivity.
Other studies have been focusing on the interaction between the design of compensation
contracts and the type of product market competition (e.g., Aggarwal and Samwick (1999). See
also the survey by Gal-Or (1997)). However, these studies by and large do not explore the role
of other governance mechanisms besides compensation contracts in aligning incentives, and
also do not explore the effect of the different mechanisms on efficiency.
More recent studies have looked at the relation between product market competition and
governance mechanisms. For example, Guadalupe and Perez Gonzales (2006) find that stronger
product market competition reduces the premium for voting shares, and Giroud and Mueller
(2008) find that the governance measure of Gompers, Ishii, and Metrick (2003) better explains
differences in stock returns in non competitive industries.
Our findings complement the above studies in several ways. First, our U.S. large-scale study
looks at much more recent data than previous studies. Arguably, public firms in the U.S. have
been given very strong incentives to improve shareholder value in recent years (e.g., Holmstrom
4
and Kaplan 2003) and it is plausible that product market competition plays no significant role in
aligning incentives in such environment. In addition, we shed new light on the different role
that different governance mechanisms play in mitigating agency conflicts across less
competitive industries.
The rest of this study continues as follows. In the next section we introduce the literature
review and develop the hypotheses. Section 3 describes the data. Section 4 reports the empirical
results and section 5 concludes.
2. Literature review and development of hypotheses
Early scholars such as Alchian (1950), and Stigler (1958) have argued that competition in
the product market is a very powerful force for ensuring that management does not waste
corporate resources. If management wastes or consumes large amounts of resources in a
competitive market environment, the firm will be unable to compete and will become insolvent.
Later studies by Schmidt (1997), Aghion, Dewatripont, and Rey (1999), and others formalized
this intuition in various models.
Scholars also commented on the role of product market competition in reducing the costs of
incentive alignments. For example, Hart (1983) introduced a model where managerial moral
hazard exists because owners cannot observe effort and the manager can claim that profits are
down not because of effort but because of increased input prices. Product market competition
helps alleviate the agency problem because, when competition exists, owners can observe
profits in other firms and use this information as a benchmark to condition the rewards to the
manager. This benchmarking reduces the asymmetric information problem and the costs of
incentive alignment.1
1
We note that not all theoretical studies agree that product market competition necessarily increases efficiency.
Scharfstein (1988), for example notes that because profits are lower in competitive industries and the incentives of
the manager to exert effort are lower. See also Hermalin (1992). Raith (2003) resolves some of this ambiguity by
endogenizing entry into the product market.
5
Our goal in this study is to examine empirically whether indeed product market competition
plays a significant role in aligning incentives. In this section we introduce a tradeoff model to
form the hypotheses. We consider a firm that operates in an industry and faces managerial
agency problems. This firm should weigh the benefits and the costs of different alignment
mechanisms when deciding on which mechanisms to use in order to align incentives (e.g.,
Demsetz and Lehn 1985).
If this firm operates in a competitive industry, then, according to Alchian (1950), Stigler
(1958), and others, the incentives of the manager are already more aligned, and therefore the
firm needs to spend less to further align incentives than they would spend in a non-competitive
industry.
To formalize this intuition, let g≥0 be the firm’s choice of mechanisms to align incentives.
A higher value of g corresponds to more mechanisms in place and a smaller value corresponds
to fewer mechanisms. Let C(g)≥0 be the cost of these incentive mechanisms and let B(g)>0 be
the benefits to the firm from aligning managerial incentives from these mechanisms. The
benefits can be thought of the increased cash flows to shareholders from more efficient
investment decisions and cost reducing activities.2 One can rank these mechanisms in the
analysis assuming that there is a mapping between the choice of mechanisms and the cost of
these mechanisms. These costs could be, for example, increased auditing costs or costs
associated with enhanced disclosure, costs of bringing strong directors to the board to monitor
management, costs associated with structuring more powerful compensation incentives to
management, costs of overcoming managerial entrenchment, etc. We assume that g is additive
in the sense that these mechanisms are additive. We further assume that C’(g)>0, C”(g)>0 for
g>0, C(0)=C’(0) = 0, C’(∞)= ∞. We also assume that B(0) =0, B’(g)>0, and B’’(g)<0 for all
2
Obviously, this reduced form of the choice of mechanisms does not take into account potential interaction among
mechanisms and substitutions across them. However, to the extent that there is a cost-benefit efficient frontier
among these mechanisms, one can order them on the frontier and map these choices into g.
6
g. These assumptions mean that the costs of aligning incentives are convex in g and that the
benefits from alignment mechanisms are concave in g.
We consider the effect of competition on alignment of incentives in the following way: We
assume that industry competition is equivalent to a governance mechanism gc>0, which leads to
added benefits from alignment B(gc) at no cost to the shareholders. A firm that wishes to
implement governance mechanisms g in a competitive industry is therefore facing the benefit
function B(gc +g) rather than B(g). 3
Since B(g) is concave and C(g) is convex, the global solution solves B’(g) = C’(g) for noncompetitive industries and B’(gc +g) = C’(g) in competitive industries. Denote g* the optimal
governance level in competitive industries and g** the optimal governance level in non
competitive industries. Figure 1 illustrates the marginal benefits, marginal costs, and optimal g
for firms in competitive industries and in non-competitive industries.
MC
gc
MB (non comp)
MB (comp)
0
1
g*
g**
Figure 1: marginal cost and benefit functions of incentive-alignment
mechanisms in competitive and non-competitive industries
3
Note that we abstract from the effect of competition on the amount of rents that are captured by the firm. This
simplification is to allow tractability. One way to embed the differences in rents is to assume that the first-best
value depends on the level of competition and that the benefits in the model represent the percentage of the value
that can be returned back to the shareholders. Another way to think about it is to assume that the level of rents that
agents can extract absent alignment mechanisms is constant regardless of the level of competition.
7
Proposition 1: Else equal, incentives of agents in firms in non-competitive industries are less
aligned with those of the shareholders than incentives of agents in firms in competitive
industries.
The proof to Proposition 1 as well as the other propositions is in the appendix. The intuition
behind the proposition is quite simple. In competitive industries, the shareholders gain a level of
incentive alignment because the firm competes in the product market. Therefore, the firm saves
on some of the costs of aligning incentives and can therefore allow itself to reach a higher level
of alignment than firms that have to incur all costs of incentive alignment.
Given the above cost and benefit functions, it is easy to see that firms in competitive
industries will find it less beneficial to invest in incentive-alignment mechanisms, and therefore,
in equilibrium, they should have fewer mechanisms in place compared to firms in noncompetitive industries. Figure 1 illustrates the intuition behind the result. When the incentives
are in place because of product market competition, the marginal utility of adding more
governance mechanisms diminishes, and, to the extent that governance mechanisms bear cost, it
is enough to have fewer governance mechanisms in place. Hypothesis 2 formalizes this
intuition:
Proposition 2: Else equal, firms in non-competitive industries will have more incentivealignment mechanisms in place compared to firms in competitive industries.
In this study, we explore also the effect of the Sarbanes Oxley law on firms in competitive
and non competitive industries. The Sarbanes Oxley law required the implementation of several
governance mechanisms such as enhanced auditing of financial statements, and increased
penalties on corporate fraud. To illustrate the effect of such an outside intervention on
8
alignment of incentives across competitive and non competitive firms, suppose that firms in
competitive and non-competitive industries are required to have additional governance
mechanism which they did not consider before. These mechanisms will add to the existing
mechanisms a constant value ∆ such that firms in competitive industries will move from a level
of g* to g* + ∆ and firms in non competitive industries will move from a level g** to level g** +
∆. Suppose also that the costs of adding these mechanisms are similar across the two firms. We
hypothesize that since the marginal benefit from these additional mechanisms is going to be
smaller in competitive industries than in non competitive industries, firms in competitive
industries are going to benefit less from the Sarbanes Oxley law than firms in competitive
industries. We formulize this idea in hypothesis 3.
Proposition 3: Else equal, an exogenous requirement to include additional governance
mechanisms that are not in place leads to a larger increase in the benefits of alignment of
incentives in non-competitive industries than in competitive industries.
These three propositions lay down the three hypotheses that we examine in the empirical
analysis.
3. Data and variables
The data for the analysis is obtained from several sources. We use the most recent industry
concentration data (the 2002 data) from the Economic Census Bureau, and examine the relation
between industry concentration, efficiency, and governance in the years 2001-2005. We focus
only on this recent data since the Census Bureau has recently made several changes to the
classifications of industries and in its 2002 data it is using the improved NAICS method to
classify industries. (In previous years, industry concentration was given according to SIC
9
codes).4 In addition, the 2002 data includes classification of all industries, while earlier data
focused only on manufacturing industries.5
In the analysis of the relation between product market competition and efficiency we study
the entire Compustat database, merged with the industry concentration data and focus on the
years 2001-2005. In the analysis of the relation between product market competition, efficiency,
and governance mechanisms, we further restrict the original data to firms that also have
governance data (firms that belong to the IRRC database - roughly firms that belong to the S&P
1500 index).
3.1 Industry concentration
We use the data from the U.S. Census Bureau on concentration of different industries in the
U.S. economy. We use the latest data available, from the year 2002. The database relies on the
North American Industry Classification System (NAICS), and it provides two industry
concentration measures. For manufacturing industries, it provides the Herfindahl index (based
on the sales of the largest 50 firms). For non manufacturing industries, it provides the market
share of the top fifty firms in the industry.
To calibrate competition across these two measures, we use separate rankings for each one
of them: We define industries as concentrated if they are among the top 50% of the industries
4
NAICS (North American Industry Classification System) was developed under the auspices of the Office of
Management and Budget (OMB), and adopted in 1997 to replace the Standard Industrial Classification (SIC)
system. The SIC system was developed in the 1930s at a time when manufacturing dominated the US economic
scene. The system has received increasing criticism about its ability to handle rapid changes in the US economy
(e.g., developments in information services, expansion of services, and high tech manufacturing). NAICS’ sixdigit hierarchical structure allows greater coding flexibility than the four-digit structure of the SIC. NAICS
classifies all economic activity into twenty industry sectors. Five sectors are mainly goods-producing sectors and
fifteen are entirely services-producing sectors. The system allows for the identification of 1,170 industries
compared
to
the
1,004
found
in
the
SIC
system.
For
more
information
see
http://www.census.gov/eos/www/naics/index.html.
5
However, in the robustness section, we also run several specifications with earlier data using the old classification
system. Our results are robust to earlier periods.
10
which use the same concentration criteria (Herfindahl for manufacturing firms and market share
for non-manufacturing firms).
3.2 Incentive-alignment mechanisms
We consider two main governance mechanisms that align managerial interest with those of
the shareholders. The first mechanism is anti-takeover provisions in the corporate charter. Firms
that do not include these anti-takeover mechanisms become more vulnerable to takeovers, and
would therefore be more disciplined by the market for corporate control (Jensen 1986). We use
the anti-takeover charter amendment index of Gompers, Ishii and Metrick (2001) and the index
of the five main anti takeover provisions of Bebchuk, Cohen, and Ferrel (2006).
The second mechanism is the structure of the board. The board of directors is the
representative of the shareholders and as such is monitoring managerial activities. Past studies
have identified a relation between the existence of outsider directors on the board and a weaker
bargaining position of the CEO vis a vis the board (e.g., Hermalin and Weisbach 1988, Boone et
al. 2007). We consider board independence, defined as a majority of independent directors on
the board, and committee independence, defined as a committee composed fully of independent
directors.
3.3 Efficiency
Hypothesis 1 suggests that agency conflicts in firms that face product market competition
should be lower than agency conflicts in firms that do not face such competition. To test the
hypothesis, we need to find a measure of the level of agency conflicts in firms. Much of the
literature on agency conflicts in firms has been focusing on the tendency of management to
capture managerial slack by spending money on non profitable project and spending money on
themselves rather than on returning cash to shareholders (e.g., Jensen and Meckling 1976,
11
Jensen 1986). We therefore focus our attention in this study on efficiency measures. We use two
measures that were used in the past to measure efficiency in firms (e.g., Ang, Cole, and Lin,
2000). The first measure is the ratio of general, sales, and administration costs to sales, and the
second measure is the ratio of sales to assets. The first measure captures the costs that the firm
incurs, not directly related to production. Else equal, firms that have a higher ratio of
administrative expenses to sales spend more of their revenues on overhead administrative costs
and therefore are less efficient. The second measure captures how efficiently assets are used to
generate sales. Firms that generate higher sales relative to their assets are more efficient in
utilizing their assets.
We note that, by definition, firms that operate in less competitive industries are more likely
to capture higher rents from selling their product than firms in more competitive industries.
Therefore, else equal, firms in more competitive industries should bear higher costs to sales and
have higher sales-to-asset ratios than firms in less competitive industries. However, to the extent
that we find higher costs in firms in less competitive, we can still infer that firms in less
competitive industries are less efficient. In addition, our test of the effect of the Sarbanes Oxley
act on firm efficiency controls for firm-specific product market attributes to circumvent this
issue.
3.4 Control variables
Several control variables are used in the analysis. To control for size, we use the market
capitalization of the firm. To control for different production functions and growth opportunities
across industry sectors, we use the 48 industry dummies of Fama and French (1997). In some of
the specifications we also control for growth opportunities using the market to book ratio, and
for firm age.
12
4. Results
4.1 Product market competition and Corporate Efficiency
Table 1 shows the results of the relation between product market competition and corporate
efficiency. Panel A shows the univariate results. This panel shows that for each of the years
2001-2005, the median ratio of sales, general, and administrative costs to sales is significantly
lower in non concentrated industries than in concentrated industries. A similar pattern exists
also in mean ratios although significance varies across the years.
Panel A also shows that the average ratio of sales to assets is significantly larger in
concentrated industries than in non-concentrated industries. The result is significant in each of
the years 2001-2005. The difference in the median ratio is also significant at the 1% level. Panel
B shows the results across the 5 size quintiles. For each year we rank the firms in the sample
into 5 size quintiles based on their market capitalization. We then aggregate all firm-years
within each quintile and calculate average and median ratios. The results show that the
difference in mean and median ratios between concentrated and non concentrated industries
appear across the different quintiles.
The univariate results do not control for other potential reasons for the differences in the
efficiency ratios across industries. These reasons could be related to differences in production
functions across different industries or to differences in where firms stand in the firm’s life
cycle. To account for these potential effects, we run a panel regression where the independent
variables include firm size, dummy for the 48 industry sectors, and firm age. We show the
results in panel C of Table 1. The standard errors in the panel regression (as well as all other
regressions in this paper) are clustered at the firm level to account for correlation in errors
within firms.
Panel C column 1 shows the regression result where the dependent variable is the natural
log of one plus the general, sales, and administrative expenses to sales ratio. The coefficient of
13
the concentrated industry dummy is positive and significant, suggesting that firms in
concentrated industries have larger expenses relative to sales compared with firms in non
concentrated industries. Since the dependent variable is in logs, the coefficient of 0.057 suggests
that the dependent variable is on average 5.7% larger in concentrated industries than in nonconcentrated industries. We also find that size and age are significantly related to the ratio.
Firms that are smaller tend to have lower expense ratios, and firms that are younger tend also to
have smaller expense ratios.
Column 2 decomposes the concentration variable into large firms and small firms. The
column shows that concentration is associated with higher administrative expenses to sales
across both large and small firms.
Column 3 shows the results where the dependent variable is the natural log of sales to
assets. The coefficient of the concentrated industry dummy is negative and significant,
suggesting that firms in concentrated industries have lower sales-to-assets ratios compared with
firms in non concentrated industries. The coefficient of -0.067 implies that firms in more
concentrated industries have sales-to-assets ratios that are about 6.7% smaller than the ratios in
less concentrated industries. Size is negatively related to the ratio of sales to assets and firm age
is positively related to it. When we decompose the effect of concentration into large and small
firms we again find that the effect on the Sales to Assets ratio is about the same across both
small and large firms.
Overall, the results support Hypothesis 1 that firms in concentrated industries are less
efficient than firms in non-concentrated industries.
14
4.2 The effect of the Sarbanes Oxley law on Corporate Efficiency in concentrated and non
concentrated industries
The Sarbanes-Oxley law was enacted as a result of the corporate scandals in companies like
Enron, Tyco, and others. The law included provisions such as increased penalties for officers
who are charged with fraud, enhanced scrutiny over external and internal auditors, enhanced
disclosure of financial statements, enhanced disclosure on insider trading, and other restrictions.
To the extent that the incentives of managers in firms in more competitive industries are more
aligned with shareholders’ interests, they should be less affected by the monitoring requirement
than managers in firms in more competitive industries.
To test this hypothesis (based on Proposition 3), we use the difference-in-difference
approach on a panel of firms between 2001-2005.
Specifically, we run the following regression:
Efficiencyit = firm fixed effecti + sector*year effectt + concentrated industry dummyi *
year>2002 dummy + controlsit + eit.
(1)
We test whether the coefficient of the concentrated industry dummy interacted with the year
dummy is significantly different from zero. A significant coefficient would imply that firms in
concentrated industries have changed their efficiency differently than firms in less concentrated
industries. We further control for year-sector dummies, firm size, firm age, and for firm fixed
effects. Our empirical specification closely follows the Giroud and Mueller (2009) specification
which studies the effect of the anti-takeover laws in the 1980’s on firm performance across
concentrated and non concentrated industries.
The results appear in Table 2. Column 1 shows the results where the dependent variable is
the natural log of the sales, general, and administrative costs to sales, and column 3 shows the
results where the dependent variable is the natural log of sales to assets.
15
The coefficient of the Concentration*year>2002 dummy is significantly negative in column
1. The coefficient is -0.025, implying that firms in concentrated industries have reduced their
sales, general, and administrative costs to sales ratio after the SOX law more than firms in less
concentrated industries by about 2.5%. Column 2 shows the decomposition of the effect across
small and large firms. The results suggest that the effect is about similar for both small and large
firms.
Column 3 shows that these firms have also increased their sales to assets ratio by more than
firms in less concentrated industries by about 1.3%. The effect is significant only in small firms
(Column 4).
The analysis in Table 2 shows that firms in concentrated industries tend to have larger
efficiency gains from the Sarbanes Oxley law. While our model assumed that the Sarbanes
Oxley law imposed new mechanisms over and above existing mechanisms, it is possible that
some firms in concentrated industries were more compliant with the rules to begin with and
therefore they should not be affected by the rule as much as firms in concentrated industries that
were less compliant. Thus, it would be interesting to see whether the Sarbanes Oxley law
affected firms in concentrated industries differently, depending on their governance compliance.
To that end, we repeat the regression (1) except that we interact the concentration*year>2002
dummy with a dummy for whether the firm was more compliant or less compliant with the
regulations to begin with. Our measure of compliance is the level of independence of the board
and its committees, and is taken from Chhaochharia and Grinstein (2007). The measure is the
sum of the dummy variables for whether the firm has a majority of independent directors, and
whether it has an independent compensation and nominating committees. We define a low score
as a measure of 0 or 1, and a high score as a measure of 2, 3. The regression specification
includes the interaction of concentration with score 0 and 1 which represents low governance
and the interaction of concentration with medium score (2 or 3).
16
Table 3 shows the regression results. The table shows that the Sarbanes Oxley law improved
sales to assets and reduced administrative expenses to sales the most for firms that were the
least compliant with the rule to begin with.6 This result corroborates our initial efficiency results
and relates them more directly to the existence of governance mechanisms.
4.3 Comparison of governance rules: the Sarbanes Oxley law and the anti-takeover legislation
of the 1980’s.
In a separate study, Giroud and Mueller (2009) examine the effect of the anti-takeover
legislations in the 1980’s on firms in concentrated and non concentrated industries. The antitakeover legislations were state-level rules whose purpose was to reduce the ability of raiders to
take over firms through hostile takeovers. Giroud and Mueller conjecture that, to the extent that
firms in concentrated industries face stronger agency conflicts, immunizing these firms from the
disciplinary force of takeovers should have worse effect on them than on firms in more
competitive industries, whose incentives are more naturally aligned.
The main variable of interest in their study is the return on assets. In table 5 panel A we
replicate the results of the analysis of Giroud and Mueller. The regression is a differences-indifferences panel regression, similar to the one used by us for the Sarbanes Oxley legislation,
except that the variable BC is a dummy for whether the business combination law was enacted
in the state in which the company is incorporated.7 The interaction BC*Concentration is a
measure of whether firms in more concentrated industries suffered more from the rule than
firms in less concentrated industries.
6
The difference is significant for the Sales to Assets variable.
Note also that Giroud and Mueller included beyond the interaction term also the concentration variable in their
regression. We did not include such measure since our sample spans a shorter period of time than theirs (five years
vs. 20 years), during which our concentration measure did not change. In addition, their concentration variable is
the Herf. measure (rather than our ranking measure), since they consider only manufacturing firms for which the
Herf. measure is available. We also use the log(1+ROA) variable rather than the ROA variable to account for nonlinearities in the data.
7
17
Table 4 panel A column 1 shows that the overall effect of the anti-takeover legislation in
their sample was a 3.7% decrease in (1+ ROA). This number is similar to the one that Giroud
and Mueller find in their sample (Table 3 column 2 in their paper, a 3.3% decrease in ROA).
The other variables are also similar in magnitude and significance.
When we decompose the effect on ROA into large and small firms we find that the large
decrease is due to small firms only. Small firms saw a decrease of 9.4% in ROA during that
time, while large firms did not see any significant decrease in ROA. The result is interesting,
since it suggests that the legislation had a different effect on small and large firms. One
possibility is that the rule had a bite only in small firms, since large firms are inherently harder
to be taken over and therefore were already immuned from hostile takeovers before the
legislation. It is also possible that the rule had affected the nature of product market competition
since firms can no longer decrease the level of competition by simply acquiring small firms.
To further explore the reason for the differences across large and small firms, we
decompose the Return on Assets variable into the following ratios: Sales to Asset,
Administration expenses to Sales, Cost of Goods Sold to Sales, and Operating income to Sales.
We present the results in columns 2-6.
The results suggest that sales to assets have decreased in both small and large firms,
consistent with the hypothesis that both large and small firms experienced a decrease in
efficiency after the regulation. However, the administrative expenses to sales did not changed
for any type of firm. And while operating income to sales decreased in small firms, it actually
increased in large firms. Cost of goods sold increased, but only in small firms.
Our conclusion from this decomposition is that large firms, which saw a decrease in sales to
assets, actually experienced an increase in earnings to sales. This increase in earnings to sale
could come from the fact that costs went down, or from the fact that margins on sales went up
due to higher prices. Since the effect on costs is not significant, it is possible that margins on
18
sales went up due to higher prices. In contrast, small firms saw a decline in sales to assets, as
well as an increase in cost of goods sold to sales. Thus, it seems that inefficiency in investment
as well as the decrease in costs of goods sold have led to a decline in returns. However, the
magnitudes of the changes in cost-of-goods sold are not enough to produce such a large
decrease in margins. It is therefore plausible that the gain in market power for larger firms was
at the expense of smaller firms.
Panel B decomposes the efficiency gains due to SOX. We start with the ROA measure to
allow for a more complete comparison with panel A. As expected, the gains in ROA were in
both large and small firms. The gains are due to a decrease in administrative expenses to sales in
both large and small firms, and to increase in sales to assets, but only in small firms. There was
no effect on the cost of goods sold in either large or small firms.
Thus, it looks from the above analysis that changes in external governance mechanisms
have a different effect on alignment of incentives than changes in internal governance
mechanisms. External governance mechanisms had an impact on the efficiency of investment,
but did not have much effect on the production or overhead efficiencies. In addition, external
governance mechanisms seem to be associated with changes in nature of product market
competition. In contrast, internal governance mechanisms reduce overhead costs in both small
and large firms, and also investment inefficiencies, but only in small firms.
4.4 The interaction between product market competition and governance mechanisms
The second hypothesis states that, to the extent that product market competition reduces
agency conflicts, firms in non-concentrated industries should be less concerned with managerial
incentive alignment and should therefore not require additional governance mechanisms to align
them.
19
Table 5 panel A shows univariate comparison of differences in governance mechanisms
between firms in concentrated and non concentrated industries. The sample is from the IRRC
database, which includes most of the S&P1500 firms. The anti-takeover provision database has
data every other year and so we look at the five years from 1998-2006. Our data for the director
database includes the years 2000-2005.
Panel A shows that for each year in our dataset there are more anti-takeover provisions in
non-concentrated industries than in concentrated industries. The effect is statistically significant
in the majority of the years. We find a similar relation between industry concentration and the
entrenchment index: Firms in non-concentrated industries have on average an entrenchment
index that is higher than firms in concentrated industries in each and every year of our sample.
The effect is significant in three of the five years that we examine.
Panel A also shows differences in director independence between firms in concentrated and
non-concentrated industries. A larger fraction of firms in concentrated industries have
independent boards and independent committees compared to firms in non concentrated
industries. This result is consistent with previous studies that have looked at the relation
between director independence and product market competition in other countries. For example,
Randøy and Jenssen (2004) find that boards are more likely to be independent in non
competitive industries.
To better account for differences in firm attributes that could lead to the above differences,
we run several regressions where the dependent variables are the governance measures and the
independent variables are a dummy for whether the firm is in concentrated industry and a host
of controls. We present the results in Panel B.
Panel B shows that in all regressions the sign of the industry-dummy coefficient is in the
direction suggesting more controls in concentrated industries. The effect is statistically
significant (5% level or higher) in five of the six regressions.
20
4.5 Robustness Tests
As a first robustness test, we check whether our results regarding the relation between
product market competition and efficiency and product market competition and governance
hold outside the period we examine. To that end, we use industry concentration data from 1970
until 2005 from the Census and run the regression (2) on the entire sample period. Due to data
availability, we can only look at manufacturing firms and use the Herfindahl measure at the
four-digit SIC code level (rather than at the NAICS level). Table 6 panel A shows the results.
Firms in concentrated industries have lower sales to assets and higher administrative expenses
to sales. The results are consistent with our previous results. However, only the effect on salesto-assets is significant at the 5% level or better.
Panel B shows the results where we run the regression in (4) on the Gompers, Ishii, Metrick
index and on the Entrenchment index. The data is extended to include the entire IRRC data
(1990-2005). The results show that the concentration has a significant effect on the imposition
of anti-takeover mechanisms. Firms in more concentrated industries have a significantly lower
score over the period 1990-2005, implying that they have fewer anti-takeover mechanisms in
place.
In addition to the above tests, we include as a robustness check another measure of industry
concentration, which captures the level of entry and exit of firms in the industry. Industries that
are more concentrated face barriers of entry and are less likely to have additional firms entering
and leaving them. In contrast, the more competition firms face, the higher the potential for new
firms to enter the industry and for firms to leave the industry.
We define entry rate as the number of firms in a given year that enter the industry as a
percentage of the existing firms in the beginning of the year. Similarly, exit rate measures the
percentage of firms in an industry that seized to exist. We sort the exit rate and the entry rate
across industries and generated a dummy variable which equals 1 if the industry is in the bottom
21
50% of the industries in entry rates and exit rates. This variable is created at the 2 digit SIC code
level. We obtain data on entry and exit from Klapper, Laeven and Rajan (2005)8. Our results
(not shown) are generally consistent with the results using the Herfindahl measure, although
significance varies.
5. Conclusion
This study explores the role of product market competition in aligning managerial incentives
in public U.S. corporations. We find that firms in less competitive industries are less efficient
than firms in more competitive industries. The results are significant in each and every year in
the sample and are robust after controlling for industry sectors, size, and firm age. In addition,
we find that the Sarbanes Oxley law was associated with significantly larger increase in
efficiency in firms that belong to less competitive industries than in firms that belong to
competitive industries.
We contrast the effect of the Sarbanes Oxley act on efficiency to that of the anti-takeover
legislations of the 1980’s. We find that the anti-takeover legislations in the 1980’s affected
efficiency mainly in small firms, while the Sarbanes Oxley act affected efficiency in both large
and small firms. In addition, it seems that the anti-takeover legislation had a side effect on the
division of rents between large and small firms in concentrated industries.
Finally, we find that firms in competitive industries employ more lenient governance
mechanisms than firms in less competitive industries. These findings suggest that product
market competition substitutes for the need to discipline managers through other mechanisms.
8
Klapper, Laeven and Rajan (2005) provide it at the 2 digit SIC code level and obtain the data from Dun and
Bradstreet.
22
References
Aghion P, Dewatripont M and Rey P, 1999, Competition, Financial Discipline, and Growth,.
Review of Economic Studies 66, 825-852
Alchian, A., Uncertainty, Evolution, and Economic Theory, 1950, Journal of Political Economy
58, 211-221.
Allen, F., Gale, D., 2000, Corporate Governance and Competition, In Vives, X., Corporate
Governance, Theoretical and Empirical Perspectives, Cambridge University Press, Cambridge,
MA.
Bebchuk, L, Y. Grinstein and U. Peyer, 2008, “Corporate governance and timing of option
grants”, Journal of Finance, forthcoming.
Bolton, P. and D. Scharfstein, 1990. A Theory of Predation Based on Agency Problems in
Financial Contracting, American Economic Review 80, 93-106.
Boone, A.L., Casares Field, L., Karpoff, J.M., and Raheja, C.G., 2007. The Determinants of
Corporate Board Size and Composition: An Empirical Analysis, Journal of Financial
Economics 85, 66-101.
Caves, R, 1992, “Technical efficiency, rent seeking and excess profits in US manufacturing
industries, 1977,” Empirical Studies in Industrial Organization: Essays in honor of Leonard W
Weiss, edited by David B. Audretsch and John J Siegfried ( Dordrecht: Kluwer Academic,
1992). 187-206.
Chhaochharia V and Y. Grinstein, 2007, Corporate Governance and Firm Value: The Impact of
the 2002 Governance Rules, Journal of Finance 62, 1789-1825.
Demsetz, H and K. Lehn, 1985, “The Structure of corporate ownership: causes and
consequences,” Journal of Political Economy, 93, 1155-1177.
Giroud, X., Mueller, H., 2009. Does corporate governance matter in competitive industries?
Unpublished working paper. New York University.
Giroud, X., Mueller, H., 2008. Corporate governance, product market competition, and equity
prices. Unpublished working paper. New York University.
Gomes, A, 2000. Going Publicallv without governance: managerial reputation effects, Journal
of Finance 55, 615-646.
Gompers, P., Ishii, J., Metrick, A., 2003. Corporate governance and equity prices. Quarterly
Journal of Economics 118, 107-155.
Graham, D.R., Kaplan, D.P., and D.S. Sibley, 1983. Efficiency and competition in the airline
industry. Bell Journal of Economics 14, 118-138.
Guadalupe, M., Pérez-González, F., 2005. The impact of product market competition on
private benefits of control. Unpublished working paper. Columbia University
23
Fama , E. F and M.C. Jensen, Separation of ownership and control, Journal of Law and
Economics 26, 1983, 301-325.
Gal-Or, E., 1997. Multiprincipal agency relationships as implied by product market
competition, Journal of Economics & Management Strategy 6, 235-256.
Hart, O., 1983. The market as an incentive mechanism. Bell Journal of Economics 14, pp. 366–
382.
Hermalin B., 1992. The effects of competition on executive behavior, Rand Journal of
Economics 23, 350-365.
Hermalin, .B. E., and M. Weisbach, 1988. The Determinants of Board Composition, RAND
Journal of Economics 19, 589-606.
Holmstrom, B., 1979. Moral Hazard and Observability, Bell Journal of Economics 10, 74-91.
Holmstrom, B., and S.N. Kaplan, 2003, The State of U.S. Corporate Governance: What's Right
and What's Wrong? The Bank of America Journal of Applied Corporate Finance, 15, 8-16.
Januszewski, Silke I., Koke, Jense, and Joachim K. Winter, 2002, Product market competition,
corporate governance and firm performance: an empirical analysis for Germany, Research in
Economics 56, 299-232.
Jensen, Michael C and William M Meckling, “ Theory of the Firm: Managerial Behavior,
Agency Costs and ownership Structure,” Journal of Financial Economics, October 1976.
Klapper, L ,L. Laeven and R . Rajan, “Business Environment and firm entry: Evidence from
International data,
Nickell, S., 1996. Competition and corporate performance. Journal of Political Economy 104,
pp. 724–746.
Nickell, S., Nicolitsas, D., Dryden, N., 1997, What makes firms perform well? European
Economic Review, 783-796.
Raith, M, 2003. Competition, risk, and managerial incentives. American Economic Review 93,
1425-1436.
Randøy, T., and J.I. Jenssen, 2004. Board independence and product market competition in
Swedish firms. Corporate Governance: An International Review 12, 281-289.
Scharfstein, D., 1988. Product market competition and managerial slack. Rand Journal of
Economics 19, 147–155.
Schmidt, K., 1997, Managerial incentives and product market competition, Review of
Economic Studies,64, 191-203
Shleifer, A., Vishny, R.,1997, A Survey of Corporate Governance, Journal of Finance.
24
Shleifer, A., Vishny, R.,1986, “Large shareholder and corporate control, Journal of Political
Economy, 94(3): 461-488.
Stigler, G., 1958. The economics of scale. Journal of Law and Economics 1, 54-71
25
Appendix
Proof of Proposition 1:
Need to show that B(gc + g* )-C(g*)> B(g** )- C(g** ). Proof by contradiction. Suppose that
B(gc + g* ) - C(g* )< B(g** ) - C(g** ). Consider a candidate solution to the competitive firm g=
g** (the optimal governance of the firm in the non competitive industry) . The net benefit to the
competitive firm from the candidate solution is B(gc + g** )- C(g**). But this net benefit is
larger than B(g** )-C(g** ) since B(gc + g** )> B(g** ) . However, by assumption, the optimal
solution g* leads to net benefits that are smaller than B(g** ) - C(g** ). Therefore, the candidate
solution g** leads to higher benefits than the optimal solution g*. Contradiction. Therefore,
B(gc + g* ) - C(g* )> B(g** ) - C(g**). QED
Proof of Proposition 2:
The optimal governance structure for the competitive industry solves: B’ (gc + g* )=C’(g* ). The
optimal structure for the non competitive industry solves B’(g** )=C’(g** ). We need to show
that g*< g**. Suppose that g*≥ g** . Then B’(gc +g* )<B’(g**) which implies that C’(g* ) <
C’(g**). But since C’(g ) >0 and C’’(g ) >0, C’(g* ) < C’(g**) implies that g* < g** .
Contradiction. QED
Proof of Proposition 3:
Need to show that B (gc +g*+ ∆ )- B (gc +g* )< B (g** + ∆)- B (g** ) which can be rewritten as B
(gc +g*+ ∆ )- B (gc +g* )-[B (g** + ∆)- B (g** )]<0.We can write the inequality as follows:
∆
∫ B' ( g c + g
*
+ δ ) −B' ( g ** + δ )dδ < 0 .
0
Since B is concave, it is sufficient to show that gc+g*>g** to ensure that the integrand is
negative for every δ and therefore the entire integral is negative. Suppose that gc+g*≤g**. Then
B’(gc + g* )≥ B’(g** ). But this implies that C’(g*)≥ C’(g**) (since in equilibrium B’(gc + g* )=
C’(g*) and B’(g** )= C’(g**)). Since C() is convex, this implies that g*> g**. But then
gc+g*>g** since gc>0. Contradiction. Therefore, gc+g*>g**, which implies that the inequality
holds. QED
26
Table I
Product market competition and corporate efficiency
The table presents univariate and regression results of corporate efficiency in public firms in concentrated and non
concentrated industries. The sample consists of all Compustat firms between the years 2001-2005.
Administrative/Sales is the ratio of Selling, General, and Administrative costs (Compustat data # 189) to Sales
(Compustat data # 12). Sale/Assets is the ratio of Sales (Compustat data # 12) to Assets (Compustat data #6). The
sample is winsorized at the 1% and 99% levels for each of the variables. Concentration index is obtained from the
Economic Census (2002). For manufacturing industries, the Census provides the Herfindahl index at the NAICS
code level, and for non manufacturing industries it provides the market share of the largest 50 firms at the NAICS
industry level. Concentrated industry (Non concentrated industry) in our sample is defined as any industry whose
concentration index is at the top half (bottom half) of all industries that use the same concentration index.. In panel
B firms are divided into size quintiles based on market cap in any given year. In panel C, Size is the natural log of
the market capitalization of the firm and age is the number of years that the firm exists in Compustat. Year-sector
fixed effects are dummy variables for the 48 Fama French sectors multiplied by each of the years 2001-2005.
Standard errors are clustered at the firm level. *, **, *** indicate significance at the 10%, 5%, and 1% respectively.
Panel A: Univariate
Year
Variable:
Administrative
Exp./Sales
Non Concentrated
N
2001
2002
2003
2004
2005
Median
N
Average
Median
1655
1624
1545
1495
1421
0.488
0.449
0.439
0.492
0.493
0.261
0.254
0.255
0.255
0.252
3619
3594
3571
3502
3289
0.545
0.483
0.456
0.477
0.451
0.277
0.293
0.303
0.304
0.292
7740
0.472
0.256
17575
0.483
0.294
Year
Variable:
Sales/Assets
Average
Concentrated
Non Concentrated
N
Average
Median
Concentrated
N
Average
Median
2001
2002
2003
1655
1624
1545
1.275
1.277
1.262
1.106
1.106
1.097
3619
3594
3571
0.885
0.899
0.894
0.671
0.699
0.700
2004
2005
1495
1421
1.231
1.243
1.056
1.091
3502
3289
0.889
0.890
0.695
0.689
7740
1.259
1.091
17575
0.891
0.689
27
Diff
(t-test)
Diff
(Wilcoxon)
**
***
***
***
***
***
***
Diff
(t-test)
Diff
(Wilcoxon)
***
***
***
***
***
***
***
***
***
***
***
***
Panel B: Univariate by size
Variable:
Quintile(1=smallest)
1
2
3
4
5
Administrative Exp/Sales
Non Concentrated
N
Mean
1903
1472
1400
1497
1103
0.598
0.597
0.475
0.315
0.233
Variable:
0.288
0.268
0.269
0.238
0.208
Concentrated
Mean
N
2935
3398
3463
3199
3530
0.732
0.588
0.487
0.347
0.281
Median
0.369
0.325
0.306
0.258
0.233
Diff
(t-test)
Diff
(Wilcoxon)
***
***
***
***
***
***
***
***
T-test
Z-test
***
***
**
***
***
***
***
***
***
***
Sales/Assets
Quintile (1=smallest)
1
2
3
4
5
Median
N
1903
1472
1400
1497
1103
Not Concentrated
Mean
1.564
1.227
1.104
1.183
1.064
Median
1.368
1.099
0.992
1.054
0.922
N
2935
3398
3463
3199
3530
28
Concentrated
Mean
1.192
0.793
0.796
0.842
0.847
Median
1.054
0.546
0.616
0.667
0.676
Panel C: Pooled Regression Results
Dependent variable:
log(1+Administrative
Expenses/Sales)
(1)
Concentration
0.057
(0.008)
log(1+Sales/Assets)
(2)
(3)
***
-0.063
(0.009)
(4)
***
Concentration*Large
0.038
(0.008)
***
-0.066
(0.010)
***
Concentration*Small
0.078
(0.010)
***
-0.060
(0.011)
***
Size
-0.027
(0.001)
***
-0.022
(0.001)
***
-0.024
(0.001)
***
-0.025
(0.001)
***
Age
-0.042
(0.003)
+
+
32905
***
-0.042
(0.003)
+
+
32905
***
0.045
(0.003)
+
+
40463
***
0.045
(0.003)
+
+
40463
***
Year Sector ( 48 Industry) Fixed Effects
Clustered Standard Errors
N
R2
0.26
29
0.26
0.52
0.52
Table 2
Product market competition and corporate efficiency – the effect of the Sarbanes Oxley Law
The table presents regression results of changes in corporate efficiency in public firms around the Sarbanes Oxley act, in concentrated and non concentrated industries. The sample
consists of all Compustat firms between the years 2001-2005. Administrative/Sales is the ratio of Selling, General, and Administrative costs (Compustat data # 189) to Sales
(Compustat data # 12). Sale/Assets is the ratio of Sales (Compustat data # 12) to Assets (Compustat data #6). Concentrated industry is as defined in Table 1. Size is the natural log of
the market capitalization of the firm and age is the number of years that the firm exists in Compustat. Year-sector fixed effects are dummy variables for the 48 Fama French sectors
multiplied by each of the years 2001-2005. Large (small) firms are defined as firms that belong to the top half (bottom half) of the sample in terms of market capitalization. Standard
errors are clustered at the firm level. *, **, *** indicate significance at the 10%, 5%, and 1% respectively.
30
Dependent variable:
log(1+Administrative expenses/Sales)
(1)
Concentration*Year>2002
-0.025
(0.006)
log(1+Sales/Assets)
(2)
(3)
***
0.013
(0.006)
(4)
**
Concentration*Year>2002*Large
-0.026
(0.006)
***
0.007
(0.006)
Concentration*Year>2002*Small
-0.023
(0.009)
***
0.023
(0.008)
**
Size
-0.016
(0.003)
***
-0.016
(0.002)
***
-0.027
(0.002)
***
-0.027
(0.002)
***
Age
-0.065
(0.008)
+
+
+
32905
***
-0.066
(0.007)
+
+
+
32905
***
0.037
(0.005)
+
+
+
40463
***
0.037
(0.005)
+
+
+
40463
***
Year Sector ( 48 Industry) Fixed Effects
Firm Fixed Effects
Clustered Standard Errors
N
R2
0.89
31
0.89
0.85
0.85
Table 3: The effect of SOX across more compliant and less compliant firms
The table presents regression results of changes in corporate efficiency in public firms around the Sarbanes Oxley act, in concentrated and non concentrated industries. The sample
consists of S&P 1500 firms between the years 2001-2005 with data on board structure from the IRRC database. Administrative/Sales is the ratio of Selling, General, and Administrative
costs (Compustat data # 189) to Sales (Compustat data # 12). Sale/Assets is the ratio of Sales (Compustat data # 12) to Assets (Compustat data #6). Concentrated industry is as defined
in Table 1. Year-sector fixed effects are dummy variables for the 48 Fama French sectors multiplied by each of the years 2001-2005. For each firm the score is the sum of three dummy
variables for whether the firm has a majority of independent directors, an independent compensation committee in the year 2001 and an independent nominating committee. Standard
errors are clustered at the firm–period level. *, **, *** indicate significance at the 10%, 5%, and 1% respectively.
Dependent variable:
log(1+Administrative
Expenses/Sales)
log(1+Sales/Assets)
(1)
(2)
Concentration*Year>2002*Score(0,1)
-0.016
(0.009)
*
0.018
(0.010)
Concentration*Year>2002*Score (2,3)
-0.006
(0.002)
**
0.0001
(0.005)
Size
-0.017
(0.002)
***
-0.0088
(0.004)
Age
0.004
(0.003)
+
+
+
5745
0.0013
(0.009)
+
+
+
6915
0.8
0.75
Year Sector ( 48 Industry) Fixed Effects
Firm Fixed Effects
Clustered Standard Errors
N
R2
32
*
***
Table 4: Comparison of the effect of SOX to the effect of the anti-takeover legislation in the 1980’s
Panel A shows effect of the antitakeover legislation in the U.S. in the 1980’s on performance in competitive and non competitive sector. The regression specification follows Giroud
and Mueller (2009) and the sample consists of all Compustat firms between 1976-1995. The Herfindahl index is defined from Compustat at the four-digit SIC level using sales (Data
12). The dependent variable is Log(1+ROA) where ROA is Data13/Data6. Administrative/Sales is the ratio of Selling, General, and Administrative costs (Compustat data # 189) to
Sales (Compustat data # 12). Sale/Assets is the ratio of Sales (Compustat data # 12) to Assets (Compustat data #6). Operating income to sales is defined as data 13/data12. Cost of
goods sold to sales is defined as Data 41/Data12. All dependent variables are winsorized at the 1% and 99% levels. BC is a dummy variable that takes a value 1 if an antitakeover law
was passed in a particular state. Size is the log of assets and age is number of years the firm has been in Compustat. State year and industry year is the mean of dependent variable for
each state year and industry year combination. The standard errors are clustered at the state of incorporation level and firm and year fixed effects are included. In panel B, the
concentrated industry is defined as the three-digit SIC code industry that belong to the top half in terms of industry concentration index across industries in the sample. Concentration
index is obtained from the Economic Census (2002). For industrial firms, concentration index is defined as the Herfindahl index. For non-industrial firms, concentration index is
defined as the share of largest four companies in the industry. Size is the natural log of the market capitalization of the firm and age is the number of years that the firm exists in
Compustat. Year-sector fixed effects are dummy variables for the 48 Fama French sectors multiplied by each of the years 2001-2005. Large and small firms are defined on the median
value of market capitalization. *, **, *** indicate significance at the 10%, 5%, and 1% respectively.
33
Panel A: The effect of the anti-takeover legislation of the 1980’s in competitive and non competitive industries
BC
Herfindahl
Herfindahl * BC
Log(1+ROA)
(1)
(2)
-0.001
0.0006
(0.006)
(0.006)
0.039
(0.019)
-0.037
(0.009)
**
Herfindahl * BC*Large
Size ( squared)
Age
State-year
Industry-year
Year Fixed Effects
Firm Fixed Effects
Clustered Standard Errors
N
R
2
0.14
(0.009)
-0.01
(0.001)
-0.129
(0.009)
0.282
(0.036)
0.276
(0.033)
+
+
+
0.0408
(0.019)
**
0.009
(0.015)
-0.094
(0.029)
0.0015
(0.016)
0.139
(0.009)
-0.0103
(0.001)
-0.1221
(0.009)
0.276
(0.035)
0.273
(0.033)
+
+
+
***
-0.085
(0.011)
-0.126
(0.014)
-0.026
(0.011)
-0.003
(0.001)
0.132
(0.017)
0.039
(0.009)
0.085
(0.006)
+
+
+
***
Log(1+Administrative
Exp/Sales)
(4)
0.006
(0.003)
Log(1+Operating
Income/Sales)
(5)
-0.004
(0.004)
0.013
(0.021)
-0.005
(0.009)
***
0.009
(0.018)
0.007
(0.016)
-0.004
(0.004)
-0.028
(0.004)
0.0012
(0.000)
-0.002
(0.007)
0.053
(0.011)
0.079
(0.015)
+
+
+
-0.098
(0.016)
0.022
(0.011)
0.091
(0.016)
-0.005
(0.000)
-0.102
(0.017)
0.013
(0.008)
0.0127
(0.005)
+
+
+
***
0.03
(0.011)
-0.015
(0.011)
-0.016
(0.011)
0.00005
(0.0006)
0.015
(0.013)
0.0006
(0.001)
-0.0001
(0.001)
+
+
+
Log(1+Cogs/Sales)
(6)
0.003
(0.008)
*
Herfindahl * BC*Small
Size
Log(1+Sales/Assets)
(3)
0.024
(0.007)
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
83629
83629
83896
72073
79737
83896
0.7
0.7
0.8
0.7
0.7
0.7
34
***
Panel B: The effect of SOX in competitive and non competitive industries
Dependent variable:
(1)
Concentration*Year>2002
0.036
(0.007)
(2)
Concentration*Year>2002*Small
Age
Year Sector ( 48 Industry) Fixed Effects
Firm Fixed Effects
Clustered Standard Errors
N
R2
0.057
(0.003)
0.021
(0.006)
+
+
+
38089
0.89
log(1+Operating
Inc/Sales)
log(1+Sales/Assets)
(3)
(4)
log(1+Cogs/Sale)
(5)
(6)
***
Concentration*Year>2002*Large
Size
log(1+Administrative
Expenses/Sales)
Log(1+ROA)
***
***
0.033
(0.007)
0.044
(0.010)
0.058
(0.003)
0.021
(0.006)
+
+
+
38089
***
-0.026
(0.006)
-0.023
(0.009)
-0.016
(0.002)
-0.066
(0.007)
+
+
+
32905
***
***
***
0.89
0.89
35
***
***
***
***
0.007
(0.006)
0.023
(0.008)
-0.027
(0.002)
0.037
(0.005)
+
+
+
40463
0.85
**
***
***
0.3
(0.007)
0.032
(0.010)
0.05
(0.003)
0.052
(0.008)
+
+
+
35715
0.8
***
***
***
***
-0.009
(0.006)
-0.010
(0.009)
-0.008
(0.003)
-0.031
(0.007)
+
+
+
39678
0.85
***
***
Table 5: Product market competition and corporate governance
The table presents univariate and multivariate results for the relation between antitakeover governance mechanisms and product market competition. The sample consists of
the S&P 1500 firms from 1998-2006 that have information about their anti-takeover measures the IRRC database.. The entrenchment index is a measure of the level of antitakeover measures and is defined as the sum of the following anti-takeover measures: staggered boards, limits on amending by-laws, limits on amending charters,
supermajority requirements, poison pills, and golden parachutes (see Bebchuk et al.) The GIM index is the Gompers Ishii, Metrick (2003) anti-takeover index and consists of
the sum of 24 anti-takeover measures. Concentration Low (High) are firms which are ranked in the bottom half (top half) in terms of industry concentration across all
industries in the sample. Concentration index is obtained from the Economic Census (2002). *, **, *** indicate significance at the 10%, 5%, and 1% respectively.
Panel A: Univariate results
Year
N
Variable: External
Governance
GIM Index
Conc.
Non Conc.
8.77
9.18
9.31
9.47
***
***
9.32
9.24
**
***
1998
1017
2000
1313
2002
2004
1846
1401
8.66
8.96
8..84
9.01
2006
1341
9.02
8.9
Variable: Internal
Governance
Year
2000
2001
2002
2003
2004
2005
N
952
1163
1650
1308
1334
1327
Majority Independent
Entrenchment Index
Diff
Independent Nom. Com.
Conc.
Non Conc.
Diff
Conc.
Non Conc.
83.26%
82.22%
81.83%
89.06%
91.88%
92.92%
86.93%
78.30%
77.08%
80.23%
85.37%
91.45%
90.63%
84.93%
*
***
28.13%
34.22%
39.64%
63.73%
79.85%
80.90%
56.25%
26.55%
31.25%
36.93%
59.31%
74.87%
77.97%
53.29%
36
Diff
**
**
Conc.
Non Conc.
Diff
1.37
1.46
1.46
1.6
**
1.48
2.24
1.65
2.37
***
*
2.24
1.76
2.31
1.89
***
Independent Comp.. Com.
Conc.
Non Conc.
74.41%
75.21%
75.18%
80.90%
86.08%
87.45%
80.20%
72.32%
73.21%
75.25%
78.72%
82.90%
84.30%
78.30%
Diff
Score
Conc.
Non Conc.
Diff
2.85
2.92
2.96
3.34
3.58
3.61
3.23
2.78
2.81
2.93
3.23
3.49
3.53
3.16
*
*
*
***
Panel B: Regression results
Dummy for Concentration
Size
Book to Market
Age
Industry Fixed Effect
Year Fixed Effect
N
R
2
External Mechanisms
Entrenchment
GIM Index
Index
Majority
Independent
Internal Mechanisms
Independent
Independent
Nominating
Compensating
-0.031
(0.036)
0.008
-0.249
(0.077)
0.105
0.17
(0.051)
0.036
0.087
(0.044)
0.065
(0.011)
(0.024)
0.281
(0.063)
***
***
***
***
**
(0.017)
(0.014)
**
***
0.196
(0.047)
0.0287
***
*
Score
0.114
(0.029)
0.036
(0.015)
(0.009)
0.091
(0.056)
0.52
(0.136)
***
-0.005
(0.093)
0.156
(0.083)
*
0.116
(0.088)
0.001
0.033
***
0.012
0.009
***
0.005
(0.001)
(0.002)
(0.001)
(0.001)
(0.001)
(0.001)
+
+
+
+
+
+
+
+
+
+
+
+
6261
6261
6348
6216
6202
6222
0.16
0.16
0.11
0.16
0.05
0.15
37
***
0.006
***
***
***
Table 6
Robustness: Different time periods
Panel A presents regression results of corporate efficiency in public firms in concentrated and non concentrated industries. The sample consists of all Compustat firms
between the years 1970-2005 in the manufacturing sector. Administrative/Sales is the ratio of Selling, General, and Administrative costs (Compustat data # 189) to Sales
(Compustat data # 12). Sale/Assets is the ratio of Sales (Compustat data # 12) to Assets (Compustat data #6). Concentrated industry is defined as the four-digit SIC code
industry that belong to the top half in terms of industry concentration index across industries in the sample. Concentration index is obtained from the Economic Census
(1970-2002). For industrial firms, concentration index is defined as the Herfindahl index. Size is the natural log of the market capitalization of the firm and age is the number
of years that the firm exists in Compustat. Year-sector fixed effects are dummy variables for the 48 Fama French sectors multiplied by each of the years 1970-2005. Panel B
presents multivariate results for the relation between antitakeover governance mechanisms and product market competition. The sample consists of the S&P 1500 firms from
1990-2006 that have information about their anti-takeover measures the IRRC database.. The entrenchment index is a measure of the level of anti-takeover measures and is
defined as the sum of the following anti-takeover measures: staggered boards, limits on amending by-laws, limits on amending charters, supermajority requirements, poison
pills, and golden parachutes (see Bebchuk et al.) The GIM index is the Gompers Ishii, Metrick (2003) anti-takeover index and consists of the sum of 24 anti-takeover
measures. Standard errors are clustered at the firm level. *, **, *** indicate significance at the 10%, 5%, and 1% respectively.
Panel A: Multivariate regression for manufacturing firms : 1970-2005
Dependent variable:
Log(1+Administrative
Exp./Sales)
Log(1+Sales/Assets)
(1)
0.017 **
(0.008)
-0.03 ***
(0.002)
-0.092 ***
(0.006)
(2)
-0.023 ***
(0.007)
-0.017 ***
(0.002)
0.105 ***
(0.006)
+
+
N
42480
47779
R2
0.21
0.31
Concentrated Industry dummy
Size
Age
Year Sector (48 industry) Fixed Effects
38
Panel B: Multivariate regression for manufacturing firms: 1990-2005
External Mechanisms
Dummy for
Concentration
Size
Book to Market
Entrenchment
Index
GIM Index
(1)
(2)
-0.186
(0.613)
0.0314
(0.022)
-0.063
(0.021)
Industry Fixed Effect
Year Fixed Effect
N
R
***
***
-0.514
(0.157)
0.269
(0.057)
-0.208
(0.053)
+
+
+
+
3466
3466
0.14
0.09
2
39
***
***
***