Free Riding and Ownership Structure:
Evidence from a Natural Experiment∗
Alan D. Crane†
Jones Graduate School of Business
Rice University
Andrew Koch‡
Katz Graduate School of Business
University of Pittsburgh
November 16, 2013
Abstract
Free riding among dispersed shareholders can reduce monitoring and the enforcement of
shareholder rights. We use a natural experiment to establish a causal effect of free riding on
ownership structure, governance, and firm performance. We find that when incentives to free
ride increase, ownership becomes more concentrated and shifts from individuals to institutions.
The usage of governance tools increases among these firms, and ROA drops among firms whose
ownership structure does not change.
Keywords. Free riding; Ownership Structure; Governance; Institutional Ownership; Securities
Class Action;
∗
We thank Alex Butler, Dave Denis, Diane Denis, Stu Gillan, Ken Lehn, Sébastien Michenaud, Shawn Thomas,
James Weston, and seminar participants at Rice University and University of Pittsburgh for their helpful comments.
†
[email protected]
‡
[email protected]
1
Introduction
Monitoring of management by shareholders plays an important role in obtaining financing (Jensen
and Meckling (1976). Monitoring is, generally, a good whose provision is private but benefits are
shared. Therefore, the production of monitoring often suffers from free riding. Incentives to free
ride are determined in large part by ownership structure. If a single shareholder owns 100% of the
firm, that owner accrues all of the benefits of monitoring. However, if ownership is dispersed, any
individual owner has less incentive to monitor management.
It is well understood that ownership structure impacts incentives to free ride. In this paper
we ask whether the opposite is also true. Do differences in the potential for free riding cause
differences in ownership structure? In theory, this causal link exists (see e.g., Grossman and Hart
(1980); Zingales (1995); Burkart et al. (1997); Pagano and Röell (1998)). In particular, Shleifer
and Vishny (1986) develop a model in which ownership, through markets, endogenously adjusts
to free riding incentives. Empirical identification of this relation, however, is difficult. Ownership
structure is a function of many different factors such as contractual rights, governance mechanisms,
the need for financing, legal protections, stock liquidity, and the market for corporate control. It is
possible that the free rider problem is primarily an outcome, not a cause, of the observed ownership
structure.
In this paper, we use a natural experiment in which the incentives to free ride increase for
reasons independent of ownership structure. Our experiment takes advantage of exogenous variation in the availability of a specific coordinating mechanism designed to reduce free riding. These
mechanisms use contracts to internalize the benefits of monitoring, or shift the costs to the beneficiaries. Different types of coordinating devices are at owners’ disposal, depending on the different
ways in which they monitor (e.g. voting, takeovers, threat of litigation).1 One example is securities
class action. Instead of litigating individually, atomistic owners can form a class, thereby allowing
the provision costs (e.g., legal fees) to be shared pro rata in the same way as the benefits.2 This
1
For example, regarding monitoring via takeovers, owners can employ dilution mechanisms such that the benefit
to takeovers is spread not over all owners, but only those that sell as in Grossman and Hart (1980). Regarding
monitoring via voting, shareholder services such as ISS allows owners to shift the costs of voting from private to
shared.
2
Class action was introduced specifically to mitigate free riding. In reference to Rule 23(b)(3), which established
1
mechanism is distinct in that it is defined by law. It is not the endogenous outcome of any firm or
ownership structure decisions.
In 1999, the Ninth Circuit Court of Appeals issued a ruling that reduced access to the class action
coordinating mechanism, effectively increasing incentives to free ride. The ruling disproportionately
affected firms headquartered in the Ninth Circuit. Importantly, any individual owner’s ability to
litigate was unaffected by the ruling. It only affected owners’ ability to coordinate as a group.3 We
use this geographic and time series variation to test if or how free riding affects ownership structure.
We expect dispersed owners to sell to those willing to form positions large enough to internalize
sufficient benefits to monitoring. Using a variety of empirical methodologies, including matching
estimates and difference in difference regression approaches, we find evidence consistent with this
hypothesis. Institutional ownership increases on average by six percentage points among treatment
firms after the ruling, relative to control firms. Alternative measures of ownership structure, such
as the percentage owned by the top five owners, or the number of 5% external blockholders, also
increase by similar magnitudes. These effects are not temporary. Ownership differences persist to
today, as does the legal effect of the ruling.
If this change in ownership is a response to an increase in incentives to free ride, then we
expect the change to be stronger among certain firms. The impact of the ruling should be greater
among firms whose owners relied more heavily on coordination ex ante. We proxy for this using the
structure of ownership prior to the ruling. Class action litigation is likely to be relied upon more
heavily by owners of firms in which no external blockholders exist, and is less important among
firms with large external blockholders in place prior to the ruling. Consistent with this, we find
that the increase in institutional ownership is over twice as large among firms without an external
blockholder relative to firms with at least one.
We conduct further tests to help establish that the changes in ownership structure are driven
modern class action litigation in the US, “The policy at the very core of the class action mechanism is to overcome
the problem that small recoveries do not provide the incentive for any individual to bring a solo action prosecuting
his or her rights. A class action solves this problem by aggregating the relatively paltry potential recoveries into
something worth someone’s (usually an attorney’s) labor.”, Seventh Circuit opinion, Mace v. Van Ru Credit Corp.,
109 F. 3d 338, 344 (1997).
3
The ability of an single owner to sue is unchanged provided the owner is willing to bear the entire cost of the
litigation or arbitration (Usmani (2001).)
2
by a need to substitute for the monitoring effects of litigation. To do so, we use prior literature
that defines monitoring institutions as those that are ‘independent’ (Chen et al. (2007); Brickley
et al. (1988)) and therefore likely to act as monitors. We find that the increased institutional
ownership we observe is driven largely by these institutions. We find little evidence that insurance
companies or pension funds move in. Rather, most of the effect is driven by independent investment
companies, including mutual funds and hedge funds.
Finally, we examine ex-post outcomes of firms based on these changes in ownership structure.
The response in ownership structure is unlikely to be a perfect substitute for the class action
coordinating mechanism. To the extent that it is not, we may see the implementation of other
governance features and/or a decrease in firm performance due to a net loss in monitoring. We
use ROA to measure firm operating performance. We find evidence that operating performance
falls among treatment firms relative to control firms. The drop in ROA suggests that a change in
ownership structure (and unobserved change in other response variables) does not serve as a perfect
substitute for class action litigation.
We also examine other potential substitutes for the loss in monitoring due to the ruling. We
focus on the six items identified in Gompers et al. (2003) that reflect director and officer protection.
These protections are related to the liability exposure of directors and officers in the face of lawsuits.
A decrease in these protections will therefore act as a substitute for the monitoring effects of
litigation. We find that these protections decrease on average. This average effect has multiple
interpretations. It may be that institutional investors remove these protections as part of their
monitoring role, similar to evidence on institutional voting on takeover amendments (Brickley
et al. (1988)). Or, perhaps this increase in director and officer liability is being employed among
firms where ownership structure does not change, as a next best substitute for litigation. This
issue can be examined by studying ex-post outcomes conditional on ownership changes. This is
difficult to test. While the 1999 Ninth Circuit decision was exogenous, the response of owners is
not. Institutions will endogenously choose which firms to enter based on benefits of their ownership.
We instrument for variation in ownership changes within the treatment group using ex-ante
characteristics correlated with institutions’ revealed preferences or costs of monitoring (e.g. the
3
institutional preference for dividends, Grinstein and Michaely (2005), Shleifer and Vishny (1986)).
We find no increase in D&O governance among firms that do not pay dividends. Among firms that
do pay dividends, director and officer protections drop by 15%. This is consistent with Brickley
et al. (1988), and suggests that one of the ways institutions exert monitoring and control is by
employing governance mechanisms. This also suggests that the ROA drop we observe across the
treatment firms should be driven by those firms where the costs of a change in ownership are high
enough to prevent institutions from moving in. Consistent with this, we find that ROA is lower by
0.7% (a drop of 10% relative to the median ROA) among firms that pay no dividend, and no drop
in ROA among firms that pay dividends.
As with any difference in difference using an exogenous treatment, our results are subject to
alternative interpretations based on confounding events. A particular concern is that ownership of
treatment firms is responding to some confounding event that also occurred in 1999 and disproportionately affected firms in the Ninth Circuit. These firms are headquartered in the Western part of
the United States around the end of what is popularly referred to as the “tech bubble.” We discuss
this issue extensively in Section 3.2. Overall, we conclude that this alternative explanation does
not appear to be driving our findings.
An additional concern is that, even if one accepts a causal effect of free riding on ownership
structure, it may be that the response has little to do with monitoring but is related to a reduction
in “non-meritorious” litigation.4 An alternate interpretation is that free riding prevents wealth extraction by lawyers, not monitoring by owners. Under this interpretation, the changes in ownership
we observe are in response to an increase in the prevention of wealth extraction, not an increase in
free riding in monitoring. We also address this concern in detail in Section 3.2 and conclude that
the effect is not driven by firms most subject to these non-meritorious lawsuits.
The 1999 ruling affects only the coordination failures associated with monitoring and enforcing
rights, ex post, via litigation. This ruling does not affect the free riding problem associated with
monitoring ex ante (e.g. proxy voting, “voice”, threat of exit). Nor does it affect free riding
4
It is important to note that if litigation is viewed through the lens of costly state verification (Townsend (1979)),
then all realized litigation events will be “non-meritorious” as they will occur randomly. However, this does not mean
they do not serve to monitor managers and provide an incentive for those managers to act in a particular way.
4
associated with takeovers or renegotiations, or some of the benefits of free riding that have been
documented in prior literature (e.g. see Edmans and Manso (2011)). Therefore, our results are
unlikely to represent the overall impact of free riding on ownership structure. Further, while we can
establish a causal relationship running from free riding incentives to ownership structure, we do not
rule out the possibility that in other situations, other factors that determine ownership structure
will effect free riding incentives (we do not have exogenous variation in that direction).
This paper contributes to our understanding of how the potential for free riding influences
ownership structure. Demsetz and Lehn (1985) find cross sectional relationships consistent with
the hypothesis that ownership is related to free riding. Our results compliment and extend these
results by examining the response of ownership to a plausibly exogenous shock to free riding incentives. Further, our empirical results compliment much of the theoretical work related to ownership
structure and monitoring, for example, Shleifer and Vishny (1986).
In a similar vein, we contribute to the literature that examines how firms respond to the loss
of some governance tool. Schranz (1993) studies how variation in takeover regulations relate to
ownership concentration, executive compensation, and the substitutability of various monitoring
mechanisms. Other related studies examine similar effects of exogenously lost governance (see e.g.,
Karpoff and Malatesta (1989), Szewczyk and Tsetsekos (1992), and Bertrand and Mullainathan
(2003)). Our paper differs in one important regard. Litigation as a governing tool remains available
to all owners throughout the sample. In fact, the costs of litigating (for a given owner) are unchanged
by the ruling. It is only the ability to coordinate across multiple owners that is changed. In this
way, the variation we use is the result of lost monitoring due to free riding. To our knowledge, no
prior paper has examined the effects of lost governance due to free riding.
Our results also contribute by providing evidence of the importance of the threat of litigation
as a monitoring device. Because we test the effects of free riding in the production of monitoring
by way of litigation, our analysis depends on litigation (or the threat of litigation) having some
value in monitoring managers. There is evidence that financial economists (Strahan (1998)), legal
scholars (Thompson and Sale (2003)), and regulators believe litigation to be a valuable form of
5
governance.5 However, it is also likely that litigation is a blunt instrument (e.g., Jensen (1993)).
The response we measure suggests that the threat of litigation has value. To the extent that it did
not, we would be unlikely to see any change in ownership structure as a result of the shock.
2
The Experiment
2.1
Background
Shareholders initiate class action litigation for a variety of reasons, the most common of which
relate to accounting misstatements, insider trading, withholding material information regarding
the firm’s operations or external business conditions, and more broadly, violating SEC rules (see
Gande and Lewis (2009) for details on common reasons behind lawsuits). These litigation events
are not uncommon. From January 1996 through August 2013, there have been 3,669 securities
class action filings initiated by shareholders. At least one officer or director is listed as a defendant
in virtually all cases.6 It is also quite common to list accounting firms or underwriters as additional
defendants. In many cases, defendants have insurance in place for such liabilities. However directors
and officers internalize at least some of the insurance premia, and these are likely fairly priced.7
Shareholder litigation is viewed as a necessary governance tool. The SEC considers class actions
“a necessary supplement to Commission action” in policing fraud (J. I. Case Co. v. Borak, 377
U. S. 426, 432 (1964)). Strahan (1998) finds evidence consistent with the view that class actions
help solve agency problems. He finds that firms with severe agency problems are more likely to
face class action litigation and CEO turnover increases following the filing of the suits. Thompson
and Sale (2003) argue that federal securities litigation plays an increasing role in governance over
time. While state law governs behavior of directors, much of the recourse with regard to executives
is through federal securities litigation. Finally, in the presence of asymmetric information between
5
SEC Commissioner in statement on April 11, 2012, “In light of the limited resources available to the
SEC, private enforcement of the federal securities laws is a necessary tool to combat securities fraud.”,
http://www.sec.gov/News/PublicStmt/Detail/PublicStmt/1365171490204#.UnqKxhAwBlE
6
According to http://media.law.stanford.edu/publications/archive/pdf/Plus%20Part%20I.pdf, across all litigation
events in 2000-2003, the CEO is named as the defendant in 99% of cases, CFO’s 80%, outside directors 40%.
7
Insurers pay zero or only part of the settlement in 47% of cases. However, the company (current shareholders)
generally picks up the remainder of the tab. In 6% of cases to officers or directors make out-of-pocket payments.
6
managers and owners, it is easy to see how class action litigation can serve as costly state verification
of cash flows (Townsend (1979)).
Nonetheless, Jensen (1993) describes litigation as a “blunt instrument” that is far from ideal
in terms of addressing agency problems. It is almost certain that there are other governance
mechanisms that can address specific agency problems more efficiently than litigation. In fact,
class action litigation may be particularly ill suited for certain classic agency problems such as the
consumption of perquisites like corporate jets (e.g. Yermack (2006)). However, agency problems
that result in fraud and misreporting for the manager’s benefit clearly fall within the realm of
federal class action litigation (Thompson and Sale (2003)). It is difficult to argue that the threat
of this type of litigation serves no monitoring role.
Prior to 1995, all types of class action litigation were governed by the same rule (Rule 23, Federal
Rules of Civil Procedure). In 1995, Congress passed the Private Securities Litigation Reform Act
(PSLRA), which established rules that apply distinctly to securities class actions. The PSLRA
was introduced to address abuses in securities class actions, specifically, non-meritorious claims.8
The PSLRA established pleading standards - conditions that must be satisfied for owners to legally
form a class.
The passage of PSLRA was anticipated and affected all U.S. firms. Therefore, it is not an
ideal instrument for variation in the potential for free riding. However, the law was challenged
independently in various US circuit courts, where interpretation of the pleading standard was left
to the individual circuit judges. On July 2, 1999 the Ninth Circuit Court of Appeals issued a ruling,
Re: Silicon Graphics Inc., that led to an interpretation of the pleading standard that was more
strict than all other circuits. The Ninth Circuit ruling states “The Reform Act requires plaintiffs
to plead, at a minimum, particular facts demonstrating deliberate or conscious recklessness.” In
effect, shareholders of firms must have evidence of conscious and intentional misconduct prior to
establishing a class, whereas in other circuits shareholders must simply show recklessness (e.g.
that a misstatement exists or information was withheld). This is a much harder standard to
8
Non-meritorious claims refer to those in which “the attorney knows facts that indicate that the defendant would
prevail at trial”, or those in which “the attorney has engaged in inadequate prefiling investigation”, see Perino (2003)
for a detailed discussion.
7
meet. Evidence as to whether management’s actions were deliberate often come about during the
discovery phase of litigation, which occurs only after the class has been established. This decision
was unanticipated and likely unrelated to the future ownership structure of the firms in that circuit.
We use this ruling to instrument for variation in incentives to free ride.
2.2
The Ruling as a Shock to Free Riding
The Ninth Circuit ruling has several advantages for testing the causal effects of free riding on
ownership structure. It was an economically important shock to coordination that affected a
specific “treatment” group of firms. Further, it was both surprising and arguably unrelated to
the ownership structure choices of firms in the Ninth Circuit.
The ruling was made on the morning of July 2, 1999 and affected firms located in states in
the Ninth Circuit (Alaska, Washington, Oregon, Idaho, Montana, California, Nevada, Arizona, and
Hawaii). The treatment group is therefore determined by location of headquarters.9 It is unlikely
that, when managers chose a headquarters location, they did so in anticipation of the 1999 ruling.
It is also unlikely that the judges’ decision was made as a function of firms’ future ownership (or
of unobservable, time-invariant firm characteristics correlated with future ownership). In contrast
to the passage of laws, which is done by legislators that face re-election risk and are tasked with
representing their constituents, the Ninth Circuit ruling was issued by judges that are appointed for
life and are tasked with interpreting laws according to their own views of the legislation, relevant
precedent, and the constitution, not the views of persons (or firms) in their circuit. As a result, we
believe this decision to be independent of ownership structure choices.
Anecdotal evidence suggest that the 1999 Ninth Circuit ruling was not anticipated. Several
circuit courts were challenged with interpreting the pleading standard in the PSLRA, and the
Ninth was the outlier. This outlier status is discussed in the dissenting opinion of the rejection of
the appeal of the Re:Silicon Graphics decision:
“...Thus, our circuit was the first to arrive at the remarkable conclusion that proving recklessness is no
9
In private securities class action litigation, because shareholders are often geographically dispersed, a case can
be brought in any (or several) of the federal circuits. However, over 85% of class action cases are consolidated to the
federal circuit of the corporation’s headquarters (Cox et al. (2009)). Importantly, to the extent that venue shopping
is possible, we should see no effect of the Ninth Circuit’s ruling on the ability of shareholders to monitor.
8
longer sufficient. We did not start a trend, however.
...For all its ambiguity and peculiarity, however, two things are clear: (1) the “deliberate recklessness”
standard is deliberately designed to make it more difficult for innocent persons injured by the reckless
conduct of the issuers of securities to obtain recoveries, and (2) the substantive change in the law was
made not by Congress but by a panel of this court that substituted its own policy views for those of
the legislative branch.”
As described in this quote, and in the previous subsection, the Ninth Circuit ruling requires
plaintiffs to establish that the defendant acted with “deliberate recklessness”. If not, owners are not
legally allowed to form a class. This standard is more stringent than that in all other US Circuits.
A unique feature of this ruling is that the increased pleading standard only applies to class action
litigation. Any single owner can still sue under a lower pleading standard, even in the Ninth Circuit
(Usmani (2001)). However, in this case, the owner would bear the entire cost of the litigation or
arbitration. It is unlikely that small owners would pursue this avenue for the very reason that these
costs would exceed the benefit they would accrue, as the benefit is a function of the the ownership
stake. For this reason, the Ninth Circuit ruling serves as a shock not to litigation per se, but to
the ability of shareholders to coordinate and litigate.
It is widely acknowledged in academic literature that the increased pleading standard is economically meaningfully different from that in other circuit courts. Governing agencies also recognize
that the Ninth Circuit ruling substantially hurt shareholders’ ability to form classes. “The Securities and Exchange Commission (“SEC”) and other critics of the “deliberate recklessness” standard
have warned that the Ninth Circuit’s interpretation will be very harmful to investors because it
will discourage the filing of meritorious suits.” (Johnson et al. (2000)). In fact, the increase in
the pleading standard and the resulting effect on the ability of shareholders to file class actions are
acknowledged by the Ninth Circuit judges themselves (see the above quote).
Not surprisingly, this new pleading standard had a large impact on actual realizations of class
action litigation. If the ruling reduced the ability of shareholders to file suit and managers adjusted
to this lower threat by misbehaving more, then there might be no recognizable effect on the frequency of lawsuits. However, we argue that ownership should endogenously adjust to the reduced
9
threat of a suit to partially substitute for the monitoring that was lost. Therefore, in this case we
do expect class action litigation to drop following the ruling.
Comparing the frequency of securities class action filings in the first half of 1999 relative to the
second half indicates that the filings dropped on average. However, the drop in the Ninth is roughly
three times the magnitude of the drop in other circuits. In the Ninth Circuit there were 38 filings
prior to the ruling and 17 after, a drop of 55%. In all other circuits, there were 84 filings prior to
the ruling and 69 after, a drop of 18%. These data are obtained from Stanford’s Securities Class
Action Clearinghouse. They are available only for 1996-2012, and are summarized in Table 1.
Similar differences are found if the sample period is extended. From the beginning of 1998 to
the end of 2000, the number of suits drops in the Ninth Circuit by 37%, compared to a 9% drop
across all other circuits. Examining differences in suits across 1996 (post PSLRA) to 2012, this
significant decline is still evident. The decline for firms in the Ninth circuit is 35%, compared to
7% for all other circuits. These findings are consistent with the view that the ruling in the Ninth
Circuit reduced the threat of class action litigation.
2.3
Drawbacks of using the Ruling as an Experiment
Given that the Ninth Circuit ruling is not a controlled experiment, it is subject to several potential
criticisms. It is possible that the ruling had effects other than the shock to coordination. This
would affect our interpretation of the channel driving any results we measure. Second, it is also
possible that any effects we measure are not due to the Ninth Circuit Ruling at all, but rather to
some confounding event.
A plausible alternative interpretation of the ruling is related to a debate among legislators and
in the literature as to the socially optimal level of the pleading standard. Prior to the PLSRA
in 1995, lax pleading standards created incentives for lawyers to “race to the courthouse” and file
poorly researched suits immediately following significant stock price drops (see Perino (2003)). In
effect, these non-meritorious suits amounted to lawyers relying on frictions in the legal system to
expropriate wealth from managers, third parties such as underwriters, and a subset shareholders.
However, the 1999 Ninth Circuit ruling set a pleading standard above and beyond that of
10
the PSLRA. Its outlier status suggests that judges in other circuits (and legislators in Congress)
view this standard as one that is likely to inhibit meritorious suits more than it is to inhibit nonmeritorious suits. Nevertheless, the ruling is likely to reduce both frivolous suits and those that
govern/enforce rights. The question arises as to what the impact of the ruling was on average. If
the average effect was in fact not a negative shock to governance, but rather a positive shock to
shareholder value by reducing the probability of expropriation, then our results would have a very
different interpretation.10
It’s also important to note that our treatment group consists of firms located on the west coast
after 1999. A significant concern is that any effects we measure are due not to the ruling, but to
events related to the the bursting of the “tech bubble”. Most natural experiments are subject to
criticism of confounding events. However, given the documented economic effects of the internet
boom, this alternative hypothesis is of particular concern.
We address these weaknesses in detail in a variety of ways in Section 3.4. Our results are not
driven by firms subject to frivolous litigation, nor are they driven by firms in California or the
tech industry. Moreover, we will examine cross sectional results and effects over different horizons
that are inconsistent with a variety of alternative interpretations. As we will show, when taken
in total, our results suggest that these potential weaknesses of the experiment are not biasing our
conclusions.
3
Data and Results
3.1
Data
We use annual firm data from Compustat over 1980 to 2009. We combine this with return data
from CRSP and institutional ownership data from Thomson-Reuters 13F database. Our set of
treatment firms are those subject to the 1999 Ninth Circuit ruling. We identify these firms with an
10
In fact, much of the debate surrounding the 1995 Private Securities Ligation Reform Act (PLSRA) centered
around the tradeoff between reducing frivolous suits but at a cost of reducing suits that govern management. This
tradeoff is evident in the empirical literature on the pleading standard set in the PSLRA. Researchers have found a
higher market reaction to the PSLRA among firms with high exposure to frivolous suits (Spiess and Tkac (1997)),
and a lower market reaction when the estimated probability of being sued for committing fraud is high (Johnson
et al. (2000)).
11
indicator variable Ninth Circuit which equals one for any firm headquartered in the Ninth Circuit,
zero otherwise. We indicate the time period after the ruling with a dummy variable Post 1999 set
to one for all years after 1999, and zero for all years prior to 1999.11
There is no obvious best way to summarize ownership structure. Some papers use a 5% cutoff
to determine blockholders, some use ownership of the top X owners, and others use all institutional
ownership. Given that incentives to monitor should be continuously increasing in ownership (until
ownership is very large), it is not clear what cutoff indicates a position large enough to overcome
free riding incentives. See Edmans (2013) for a discussion of these issues and some approaches in
prior literature.
We focus on institutional ownership as a percent of shares to measure changes in ownership
structure. Institutions own large positions, resulting in a larger incentive to monitor, and using
all institutional ownership has the benefit of including large positions, even if they are not above
5%. Secondly, evidence suggests institutions are better able to monitor, either through litigation or
standard ex ante monitoring. They are required by law to invest nominally in ex-ante monitoring
due to proxy voting requirements, and are better able to coordinate through the use of third
party proxy advisory services. Finally, the level of institutional ownership is easy to measure and
interpret.
Our primary variable of interest is Institutional Ownership, which measures the percent of the
total firm owned by institutions as reported by Thomson-Reuters. For each institution, we use
holdings as of the latest report date in the calendar year, provided the report date is no earlier
than October. We include other measures of ownership structure as well, primarily for robustness.
The level of institutional ownership is highly correlated with other measures of concentration such
as a Herfindahl, or the presence of external 5% blockholders. In the appendix we report results from
our main tests using ownership structure as measured in Demsetz and Lehn (1985), as well as both
the number of 5% external blockholders and the probability of having a 5% external blockholder.
Summary statistics are presented in Table 2. Panel A presents the full sample summary statistics. Panel B and C present summary statistics for firms outside the Ninth Circuit Court of Appeals
11
We exclude 1999 from our sample because the ruling occurs exactly in the middle of the year and so we do not
assign it to either pre or post period. Our results are not affected by including 1999 in either the pre or post group.
12
and within the Ninth Circuit respectively. Dividend Payer is an indicator variable equal to one if
the firm the paid a dividend in the year, and zero otherwise. Market Equity is the dollar market
equity value of the firm and Market to Book measures the ratio of market value of equity to book
value of equity. ROA is the measure of operating income before interest and depreciation scaled
by prior period total assets. Annual returns measure the compounded monthly returns for the 12
months during the Compustat reporting period.
Ownership structure variables include Institutional Ownership, which measure the percent of
the total firm owned by institutions.12 The Institutional Blockholder Dummy is an indicator for
whether the firm has at least one institutional owner that has a five percent or greater stake the
firm. Similarly, Number of Institutional Blockholders captures the number of institutions with a
five percent or greater stake the in the firm. Following Demsetz and Lehn (1985), we calculate Top5
concentration as the logit transformation of the ownership percentage of the five largest institutional
% Ownership of Top Five Owners
13
owners, ln( (1−%
Ownership of Top Five Owners ).
It is immediately clear from Table 2 that there are differences in the types of firms across U.S.
appeals court circuits. Firms in the Ninth Circuit are smaller, less likely to pay dividends, have
more growth options and have lower leverage and profitability. They tend to have more institutional
ownership, more top 5 concentrated ownership, and more blockholders, on average. It is important
to take these systematic differences into account in any empirical analysis. However, provided that
the court’s decision is independent of these differences, we can still make causal inference regarding
the effect of a shock to free riding on ownership structure. Given the discussion provided by the
courts, we believe that this exclusion restriction is satisfied.
12
In several cases the total shares held by institutions equals more than the shares outstanding as reported by
CRSP. We exclude these observations, however results are robust to including these data, or including winsorized or
trimmed data.
13
We use 13f holdings data to identify 5% blockholders and firms without ex ante blockholders. Holderness (2009)
hand collects ownership data and finds that most firms have at least one blockholder. However, the kind of blockholders that we observe in our data are those that are likely to have the incentive and ability to file litigation alone.
Some of the data that are missing from our sample are the blockholdings of officers and directors. Of course these
owners are the defendants, and so this ownership does not reflect the incentive to monitor by way of litigation.
13
3.2
Results
In Figure 1 we summarize institutional ownership for treatment and control firms around the 1999
ruling. In this figure we control for industry differences by subtracting from each firm’s institutional
ownership the industry median value in that year, where the firm’s industry is defined by the twodigit SIC code. We report the median industry-adjusted institutional ownership separately for firms
in the Ninth Circuit and all other firms. The grey line in the figure indicates the time at which the
Ninth Circuit issued the ruling.
It is evident in the figure that industry-adjusted institutional ownership increases following the
ruling, but only among treatment firms. Year-by-year data are presented below the figure. In the
far right column we report p-values from Wilcoxon tests for differences in medians. This table also
summarizes the number of firms in the treatment and control groups. In a typical year, about
one in six firms is in the Ninth Circuit. There is no difference in institutional ownership between
treatment and control firms until 2000, at which point the difference grows and continues to be
statistically significant throughout the remainder of the sample.
The difference in ownership structure persists through today. This suggests that our effect
is not a simple story of the tech crash. This alternative would have to predict some permanent
shift in ownership structure across the treatment and control sample. We also note that the total
adjustment to ownership structure does not occur immediately but develops over several years.
This suggests some frictions with respect to the ability of institutional owners to acquire positions,
or uncertainty in the permanence of the ruling.
3.2.1
Propensity Score Match
The result in Figure 1 controls only for industry differences. However, as evident in Table 2,
treatment and control firms differ on several dimensions. We introduce additional firm controls
and examine a simple difference in institutional ownership between the treatment group and a
control group. To define a control group, we use nearest neighbor propensity score matching using
a set of observable variables. We examine the level of institutional ownership in 2000 for firms
in the Ninth Circuit relative to those outside. Our underlying identifying assumption is that the
14
treatment, the ruling by the Ninth Circuit, is independent of ownership differences between Ninth
Circuit firms and other firms. We can take into account the choice of headquarters location, which is
likely a function of things such as industry and firm characteristics, by matching on those observable
characteristics prior to the exogenous shock (similar to a difference in difference approach). We do
this by matching on observable characteristics in 1998. Panel A of Table 3 shows the first stage
of the matching estimate, using a logit model to predict assignment to the treatment group. We
estimate the following logit model for all firms in the sample:
P r(T = 1)ij = βXi + δj + ij
where we estimate the probability that firm i in industry j is in the treatment sample (Ninth
District) in 1998.14 In this model, Xi represents a vector of observable firm characteristics. In
addition to standard firm control variables (see Table 3) we also include the value of Institutional
Ownership in 1998 to account for unobserved characteristics that would drive differences across
circuits. We also include industry effects, δj, to capture any unobserved industry differences.
In general, the results of the first stage regression support the differences observed in the summary statistics. We use the values from this regression to determine propensity scores for being
in the Ninth Circuit for firms located outside the Ninth. In the second stage, we compare Institutional Ownership in 2000 (the year following the shock) between the Ninth Circuit firms and
the propensity score matched sample. The propensity score matched sample is based on nearest
neighbor matching with replacement. Our estimates are robust to other matching procedures.
Panel C of Table 3 presents results of this estimate. Following the treatment, Ninth Circuit
firms have higher institutional ownership than their matched sample counterparts. This average
effect of treatment on the treated (ATT) is estimated at four percentage points and is significant
at the one percent level. This effect is economically large. A four percentage point treatment
effect represents a 13% increase over the average institutional ownership in 1998. This evidence
suggests that the increased potential for free riding that results from the ruling caused an increase
14
In principle, we would could also analyze this effect defining treatment as the probability of a lawsuit. Unfortunately the number of lawsuits in any given year is too small to generate good matches. Given that the ruling affects
Ninth District firms, the approach we take is the natural alternative.
15
in institutional ownership relative to other circuits, even taking into account differences across the
circuits prior to the ruling. Panel B of Table 3 gives diagnostics as to the quality of the matching
estimator. The covariates across the two samples are well balanced. There are no significant
differences across the two samples on any of the observable dimensions, including most importantly,
pre-period institutional ownership.
3.2.2
Difference in Difference Estimator
The propensity score matching method establishes a causal effect of the ruling on ownership structure in the year immediately following the court decision. In this section, wee focus now on a
difference in difference approach. This has several advantages in that the results are presented in
a regression framework and are therefore easier to interpret. Further, we can easily examine longer
term effects.15 We can also easily examine conditional relationships.
We estimate the following regression specification:
yitkj = αi + αt + αj + δTkt + βXit + itkj
where yitkj represents the institutional ownership of firm i, located in state k in industry j at time
t. δ is the main coefficient of interest and represents the treatment effect - firms in the Ninth
District after 1999. Each specification includes the same observable characteristics included in the
propensity score match as a vector of control variables, Xit . Controls for industry effects are αi ,
time effects, αt , and firm effects, αj , and are included in certain specifications.
Table 4 presents the results of the basic difference in difference analysis. Included in the specification is the treatment group identifier, Ninth Circuit. This establishes the difference in institutional
ownership between Ninth Circuit firms and others prior to the treatment. Consistent with prior
results, we find that, even prior to the treatment, firms in the Ninth Circuit have higher institutional ownership on average. This difference is three percentage points, and is both statistically and
economically significant, suggesting firm location is not random. However, as long as the treatment
15
Our results are robust to excluding firms that delist over this period. Estimates are not merely driven by samples
that change differentially across circuits.
16
decision is unrelated to this difference, our analysis can help us determine the causal impact of free
riding on ownership structure.
The interaction between Ninth Circuit and a dummy for observations after the treatment (Post
1999 ) indicates the effect of the treatment on the Ninth Circuit firms. This is the coefficient on the
difference in difference estimator. The interpretation of this result is that the treatment, the 1999
decision, caused an increase in institutional ownership of five percentage points relative to nonNinth Circuit firms. This result is statistically significant at the one percent level and represents a
17% increase in institutional ownership relative to the median in 1998. This is consistent with the
results of the matching estimator described earlier.
Column 2 of Table 4 includes year dummies to take into account the significant time trend
associated with institutional ownership. Note that, with the year dummies included, the Post
1999 dummy is no longer identified by itself as it is the sum of the 2000-2009 dummies. However,
the interpretation of the interaction term is unchanged. Results are similar. The difference in
difference estimate is six percentage points, or a 20% increase in institutional ownership for Ninth
Circuit firms. This result is significant at the one percent level. Finally, Column 3 presents a fixed
effect estimate. This specification, controls for the mean levels of institutional ownership for each
firm and will account for any time invariant unobserved heterogeneity not captured by the control
variables. Because firms’ headquarters location is time invariant (with a few exceptions) the Ninth
Circuit dummy is not identified on its own in this specification. The treatment effect remains large.
Consistent with other specifications, there is a 17% increase among firms in the Ninth Circuit as
a result of the treatment relative to control firms. Overall, these results provide strong evidence
that ownership structure changed in response to reduced access to the class action coordinating
mechanism.
Bertrand et al. (2004) point out that the standard errors produced from standard difference in
differences regression approaches can be biased when using a large number of years both before
and after the treatment. This is a result of persistent characteristics within firms. We use standard
errors clustered by firm to attempt to correct for this bias. However, to test whether our inference
may still be biased, we conduct placebo tests and examine the distribution of estimates and t-
17
statistics for random samples. This also helps establish that the effect we are measuring is in fact
a function of the circuit court’s decision and not an alternative mechanical explanation.
To conduct these tests, we use 5000 simulated data sets in which we randomly assign each firm
to a given state. This effectively randomizes the treatment status for a given firm. Importantly,
this retains any correlation structure within the firm related to persistence of ownership and other
firm characteristics. We then run the regression specification described in Table 4, Column 2, for
each of these 5000 simulated data sets. Figure 2 plots a histogram of the coefficient estimates and
t-statistics. The estimate and t-statistics from the true data are shown by the red lines. The figure
clearly indicates that our coefficient estimate is significant at the one percent level compared to the
distribution under the null of random firm-state assignment. Moreover, our estimate and t-statistic
are larger than any simulated outcome. Finally, these distributions are centered around zero. This
suggests that not only are our baseline regressions unbiased, but that the geographic assignment is
the true driver of the effect we measure.
We examine alternate measures of ownership structure in Table 5. We find economically and
statistically large causal effects of the increase in free riding incentives on Top5 concentration, the
number of institutional blockholders, and the probability of having a blockholder. Column one
shows that as a result of the ruling, Top5 concentration increases by 21% relative to the median
concentration before the ruling. Similarly, Column two shows that the number of institutional
blockholders present in the firm increases by 16% relative to the pre ruling median. Finally, in
Column three we estimate an odds ratio of having a blockholder that indicates that firms in the
Ninth Circuit, post treatment, are 1.3 times more likely to have a blockholder relative to firms
outside the circuit before 1999. Results from alternative regression specifications for these variables
can be found Tables A1, A2, and A3 of the Appendix. The remainder of the paper focuses on the
effect of institutional ownership for ease of exposition and interpretation.
3.3
Conditional Relationships
The results presented above, including in Figure 1 and Tables 3 and 4, support the view that
the Ninth Circuit’s decision has a causal effect on the ownership structure of firms. We conduct
18
additional tests to provide evidence that the change in ownership is in fact a response to increasing
incentives to free ride in the production of monitoring.
If ownership is responding to changes in the potential for free riding, then we expect the response to be stronger among certain firms, and weaker in others. We expect the change in ownership
structure to be greatest among firms whose owners relied most heavily on the coordination mechanism ex ante. When there is heterogeneity in ownership size within a firm, a subset of atomistic
owners may free ride off the monitoring of large owners (Shleifer and Vishny (1986)). Therefore, we
expect firms with large owners in place prior to the ruling to be less effected by the ruling. Firms
with no large owners prior to the ruling are those whose owners are likely to rely on coordination
mechanisms to a greater degree, and hence should experience a larger change in ownership.
In Table 6, we identify firms that have at least one large institutional owner in the year before
the 1999 Ninth Circuit decision. The presence of a large institutional owner suggests that these
firms have a least one outside shareholder with a sizeable position and incentive to monitor. We
use the 5% cutoff to define a large blockholder. We identify firms without any large owners with
the indicator variable No Blockholder.
The presence of a blockholder is an endogenous outcome of firm and market characteristics.
However, provided the Ninth Circuit’s decision is unrelated to the presence of the large shareholders
in the circuit, we can condition on the presence of these shareholders as a proxy for the impact the
decision will have on firms.
The results in Table 6 strongly support our conditional prediction. We find that the effect is
primarily driven by firms with no large shareholders ex-ante. The triple difference result is positive
and significant, both economically and statistically. While firms with blockholders still experience
an increase in institutional ownership of two to three percentage points, the effect on firms without
blockholders is significantly larger. The coefficient on the interaction between Ninth Circuit, Post
1999, and No Blockholder is significant at the ten percent level. Moreover, it suggests that the effect
for these firms is up to five percentage points greater, for a total increase in institutional ownership
of approximately eight percentage points. This is consistent with the view that the driver behind
the causal impact of the Ninth Circuit’s decision on ownership is related to coordination problems.
19
We further examine whether these results are consistent with a free riding in monitoring explanation by examining the types of institutions that increase ownership around this decision. Prior
literature defines monitoring institutions as those that are ‘independent’ (Chen et al. (2007); Brickley et al. (1988)) and therefore likely to act as monitors. These institutions have been shown to
affect outcomes related to such things as voting, governing amendments, and mergers. In Table 8
we examine ownership by institutional type.16 Column two indicates that the effect is largest for
“Investment Companies”. These institutional types increase their ownership by three percent of
the total firm after 1999 relative to firms outside the Ninth Circuit. This effect is large economically and statistically significant at the ten percent level. We also find a smaller increase in Bank
type institutions (Column one). We observe no effect for pension funds and insurance companies.
These results are consistent with the evidence presented earlier that supports a free riding in the
production of monitoring channel.
3.4
Potential Alternative Explanations
There are two broad concerns with the interpretation of our results. First, it may be that the ruling
had effects other than a reduction in monitoring due to increased free riding, and ownership may
be responding to these alternate effects. Second, there may be other events that occurred around
July 1999 that disproportionately affected firms located in the Ninth Circuit, and ownership is
responding to these confounding events.
The ruling, by raising the pleading standard, reduced owners’ ability to litigate. We verify that
litigation drops around the ruling in Table 1 as a result of owners’ inability to coordinate. Our
interpretation is that by reducing the ability to coordinate (equivalently, increasing free riding),
monitoring is lost due to the reduced threat of litigation. An alternative interpretation is that an
increase in owners’ inability to coordinate reduces wealth extraction by lawyers. That is, the ruling
increases free riding, but this free riding is primarily beneficial in that it prevents “non-meritorious”
lawsuits.
Under this alternate interpretation, if institutions have a preference for firms that cannot be
16
We use data provided by Brian Bushee (Bushee (1998)) to identify owner types from the 13F database. The
Bushee data corrects for the well known misclassification present in the Thomson-Reuters data after 1999.
20
sued, the increase in ownership could be unrelated to monitoring and control, and instead be fully
explained by this preference. We test this hypothesis by examining cross sectional variation in
the treatment effect, conditional on exposure to non-meritorious lawsuits. If this is the channel
by which ownership increases in response to the Ninth Circuit’s pleading standard, then we would
expect to see the effect driven by firms likely to face frivolous litigation.
Following Johnson et al. (2000), we proxy for this likelihood by measuring the value effect of
the announcement of the Ninth Circuit’s decision. We measure three day CAR’s around the July
2, 1999 decision. For firms exposed to the risk of frivolous litigation, there should be a positive
increase in equity value as a result of this decision. The average CAR for the firms in the Ninth
Circuit is statistically indistinguishable from zero suggesting this was not, on average good news
for firms in the Ninth Circuit.
There is, however, cross-sectional variation in the magnitude of the CAR’s. In Table 7 we examine a triple difference for firms in the Ninth Circuit post 1999 that also had positive announcement
returns to the Ninth Circuit decision. We find that firms that did not have positive CAR’s drive
the average effect we observe. Specifically, the interaction between Ninth Circuit and Post 1999,
which represents the effect for firms with zero or negative announcement returns, is positive and
significant and equal to the unconditional effect reported in Table 4. Moreover, the effect for firms
with positive announcement returns (the triple interaction between Ninth Circuit, Post 1999, and
Pos. Car ) is not statistically significant and, if anything, suggests a smaller effect.
Next we turn to the second concern regarding potential confounding events that disproportionately affected firms in the Ninth Circuit. This alternative suggests that our results are not related
to free riding, but rather to some unobserved characteristics of firms in this circuit. Because the
Ninth Circuit contains California firms and the period coincides with the “Internet Bubble”, it is
possible that the causal effect we identify is merely the result of an institutional preference for
certain characteristics of firms that changed at the same time as the ruling (and that those firm
characteristics are based on unobservable time varying characteristics). We examine this alternative
in a variety of ways.
First, we note that results presented earlier are inconsistent with this view. As seen in Figure
21
1, the difference in ownership persists to the present (as does the difference in pleading standards
for the Ninth Circuit). This is inconsistent with a valuation-, or internet bubble-based explanation,
as the bubble burst in early 2000.
Secondly, we test this directly by excluding firms in high tech industries (defined by Johnson
et al. (2000) as the Fama-French Electronics, Computers, and Pharmaceutical industries). Table
9, Column one shows the results of this regression. The estimate for the increase in institutional
ownership is essentially unchanged when we exclude these industries, which indicates that our
results are not driven by high tech firms. In Column two we exclude all firms headquartered in
California. Again we find the results are unchanged relative to the entire sample (see Table 4).
Finally, we also note that this alternative does not necessarily suggest a differential effect based on
ex-ante blockholders as we show in Table 6.
On balance, we believe these results are consistent with an interpretation that the causal relationship we observe between ownership structure and the ruling, is driven by a free riding problem
in monitoring.
3.5
Governance and Operating Performance Effects
We have found that large positions established by institutions substitute for small, dispersed ownership when free riding in monitoring increases. It likely that this substitution is not perfect. If
the new ownership structure was optimal compared to the original ownership structure (or as good
as), we would likely observe higher institutional ownership to begin with. Therefore, we think it is
likely that some firms’ operating performance may change as a response to poorer governance. Furthermore, it may be that other governance structures are put into place to mitigate this imperfect
substitution.
Table 10 shows the effects of the Ninth Circuit decision on both operating performance and on
a measure of governance that we think is likely to closely substitute for the monitoring effects of
litigation. Column one shows that, overall, operating performance as measured by ROA (following
Bertrand and Mullainathan (2003)) drops slightly for firms in the Ninth Circuit after the 1999
decision (the interaction Ninth Circuit and Post 1999 ). While this result is marginally significant
22
statistically, the effect is economically small (the difference in difference estimate represents a drop
in ROA of approximately one half of a percentage point, a seven percent drop relative to the
median ROA in 1998). Therefore, while the substitution effect of a change in ownership structure
(combined with any unobserved changes in other response variables) may be imperfect, the effect
on operating performance is small.
Owners might put in place other mechanisms that help mitigate any loss of monitoring due to
the Ninth Circuit’s decision. We examine governance features that are most likely to substitute
for a drop in the threat of litigation. To do so, we use measures of director and officer protection
as identified by Gompers et al. (2003). The dependent variable is the sum of indicators for each
of the following governance features: director indemnification, indemnification contracts, director
liability insurance, executive severance agreements , golden parachutes, and compensation plans
with change in control provisions. Our independent variable increases by one for each of these that
is present in the firm. Because these are D&O protections, a larger value for this index represents
“poorer” governance.
Column four of Table 10 shows the effect of the Ninth Circuit decision on the governance index.
The difference in difference estimate (the interaction Ninth Circuit and Post 1999 ) is negative and
strongly significant. On average, treatment firms experience a reduction in D&O protections by
0.3. Relative to a median of 2 (meaning two of these protections are in place) prior to the event,
this represents and increase in governance of 15%. This suggests that, while the shift in ownership
structure may not substitute perfectly for a decrease in the threat of litigation, it is combined with
other improvements to governance.
What is not immediately clear from these results is if or how the changes in governance and
ROA relate to changes in ownership structure. It may be that the increase in D&O governance is
the result of institutional investors exerting monitoring. This would be consistent with evidence on
institutional voting on takeover amendments (Brickley et al. (1988)). Or, perhaps D&O governance
is the next best substitute, and it is being employed among firms where ownership structure does
not change. This is a difficult issue to address. While our shock to the costs of free riding is
exogenous, the response by institutions is not. Institutions will endogenously choose which firms
23
to enter based on benefits of their ownership.
To address this, we instrument for variation in ownership changes. Prior literature suggests
that there are certain types of firms that are more costly for institutions to own (based on revealed
empirical preference). One such characteristic is whether the firm pays a dividend. Both taxbased and prudent-man explanations have been given to explain institutions’ preference for stocks
that pay dividends (see e.g., Grinstein and Michaely (2005)). Shleifer and Vishny (1986) argue
that a firm can attract monitoring institutions by paying dividends. Because this characteristic
changes very slowly over time, we classify firms as either dividend payers or not prior to the Ninth
Circuit decision. It is hard to argue that the dividend paying status in 1998 is a function of future
institutional ownership changes as a result of the unanticipated Ninth Circuit’s decision. As such,
we use this to instrument for the likelihood of an increase in institutional ownership. We then
examine the effects on performance and governance conditional on this classification.
First we confirm that dividend paying status is in fact correlated with changes in institutional
ownership. In unreported results, we estimate that the effect of the Ninth Circuit’s decision on
institutional ownership for treated firms relative to non Ninth Circuit firms is 2.5 times larger for
firms paying dividends prior to the decision, relative to those that were not.
Column two of Table 10 shows the effect of the Ninth Circuit decision on operating performance
for dividend paying firms. Among these firms, for which it is arguably less costly for institutions
to enter, we find an insignificant difference in difference estimate of the effect of the treatment on
ROA. However, for firms that are more costly for institutions to enter, column three, we estimate a
negative and significant change in ROA. The difference in difference estimate is -0.7%, representing
a drop in ROA of approximately 10% relative to the median ROA in 1998. This suggest that,
among firms in which an adjustment to ownership structure is highly costly, operating performance
declines significantly.
We also find that it is only the firms that are less costly for institutions to own (dividend
paying firms) that experience an improvement in D&O governance. Results in column five suggests
that non-dividend paying firms in the Ninth Circuit exhibit no change in governance after the
Ninth Circuit’s decision. However, dividend paying firms in the Ninth experience a significant
24
and economically meaningful improvement in D&O governance relative to non-Ninth Circuit firms
after the court decision. This result suggest that, after the decision, institutions substitute for the
coordination mechanism of securities class action litigation, and they do this in part by improving
governance. Moreover, firms for which it is costly to change ownership structure see a significant
drop in operating performance as a result of the loss in monitoring.
4
Conclusion
We find causal evidence that the potential for free riding among owners influences ownership structure. We use a natural experiment in which access to a coordination mechanism is reduced for
a subset of firms. We find that ownership among these firms shifts from individuals to institutions, ownership becomes more concentrated, and it is more likely that at least one blockholder is
present. These results are robust to a variety of empirical techniques and specifications. The effects
are strongest among firms whose owners relied heavily on the coordination mechanism prior to the
event. Further, these effects are driven largely by institutions most likely to act as monitors.
Changes in ownership structure may not perfectly substitute for the lost monitoring that results
from increased free riding. Consistent with this, we find that ROA drops on average across the
treatment firms. However, this drop in firm performance is driven only by firms in which a change
in ownership structure is highly costly. Among firms in the treatment group where the cost of
changing ownership is low, there is no significant drop in ROA. We also find that the usage of other
governance tools increases among these firms.
Overall, our results help empirically establish the feedback effect between the potential for
free riding and organizational structure. This compliments several existing theories and supports
much of the existing literature related to ownership structure, the value of large shareholders, and
monitoring.
25
References
Bertrand, M., E. Duflo, and S. Mullainathan (2004). How much should we trust differences-indifferences estimates? The Quarterly Journal of Economics 119 (1), 249–275.
Bertrand, M. and S. Mullainathan (2003). Enjoying the quiet life? corporate governance and
managerial preferences. Journal of Political Economy 111 (5), pp. 1043–1075.
Brickley, J. A., R. C. Lease, and C. W. S. Jr. (1988). Ownership structure and voting on antitakeover
amendments. Journal of Financial Economics 20 (0), 267 – 291.
Burkart, M., D. Gromb, and F. Panunzi (1997). Large shareholders, monitoring, and the value of
the firm. The Quarterly Journal of Economics 112 (3), 693–728.
Bushee, B. J. (1998). The influence of institutional investors on myopic r&d investment behavior.
The Accounting Review , 305–333.
Chen, X., J. Harford, and K. Li (2007). Monitoring: Which institutions matter?
Journal of
Financial Economics 86 (2), 279 – 305.
Cox, J. D., R. S. Thomas, and L. Bai (2009). Do differences in pleading standards cause forum
shopping in securities class actions: Doctrinal and empirical analyses. Wis. L. Rev., 421.
Demsetz, H. and K. Lehn (1985). The structure of corporate ownership: Causes and consequences.
Journal of Political Economy 93 (6), pp. 1155–1177.
Edmans, A. (2013). Blockholders and corporate governance. ECGI Working Paper .
Edmans, A. and G. Manso (2011). Governance through trading and intervention: A theory of
multiple blockholders. Review of Financial Studies 24 (7), 2395–2428.
Gande, A. and C. M. Lewis (2009). Shareholder-initiated class action lawsuits: Shareholder wealth
effects and industry spillovers. Journal of Financial and Quantitative Analysis 44, 823–850.
Gompers, P., J. Ishii, and A. Metrick (2003). Corporate governance and equity prices. The Quarterly
Journal of Economics 118 (1), 107–156.
26
Grinstein, Y. and R. Michaely (2005). Institutional holdings and payout policy. Journal of Finance 60 (3), 1389 – 1426.
Grossman, S. J. and O. D. Hart (1980). Takeover bids, the free-rider problem, and the theory of
the corporation. The Bell Journal of Economics, 42–64.
Holderness, C. G. (2009). The myth of diffuse ownership in the united states. Review of Financial
Studies 22 (4), 1377–1408.
Jensen, M. C. (1993). The modern industrial revolution, exit, and the failure of internal control
systems. the Journal of Finance 48 (3), 831–880.
Jensen, M. C. and W. H. Meckling (1976). Theory of the firm: Managerial behavior, agency costs
and ownership structure. Journal of Financial Economics 3 (4), 305–360.
Johnson, M. F., R. Kasznik, and K. K. Nelson (2000). Shareholder wealth effects of the private
securities litigation reform act of 1995. Review of Accounting Studies 5 (3), 217–233.
Johnson, M. F., K. K. Neslon, and A. C. Pritchard (2000). In re silicon graphics inc.: Shareholder
wealth effects resulting from the interpretation of the private securities litigation reform act’s
pleading standard. S. Cal. L. Rev. 73.
Karpoff, J. M. and P. H. Malatesta (1989). The wealth effects of second-generation state takeover
legislation. Journal of Financial Economics 25 (2), 291 – 322.
Pagano, M. and A. Röell (1998). The choice of stock ownership structure: agency costs, monitoring,
and the decision to go public. The Quarterly Journal of Economics 113 (1), 187–225.
Perino, M. A. (2003). Did the private securities litigation reform act work. U. Ill. L. Rev., 913.
Schranz, M. S. (1993). Takeovers improve firm performance: Evidence from the banking industry.
Journal of Political Economy 101 (2), pp. 299–326.
Shleifer, A. and R. W. Vishny (1986). Large shareholders and corporate control. Journal of Political
Economy 94 (3), pp. 461–488.
27
Spiess, D. K. and P. A. Tkac (1997). The private securities litigation reform act of 1995: the stock
market casts its vote. Managerial and Decision Economics 18 (7-8), 545–561.
Strahan, P. E. (1998). Securities class actions, corporate governance and managerial agency problems. Technical report, Federal Reserve Bank of New York.
Szewczyk, S. H. and G. P. Tsetsekos (1992). State intervention in the market for corporate control:
The case of pennsylvania senate bill 1310. Journal of Financial Economics 31 (1), 3 – 23.
Thompson, R. B. and H. A. Sale (2003). Securities fraud as corporate governance: Reflections
upon federalism. Vand. L. Rev. 56, 859.
Townsend, R. M. (1979). Optimal contracts and competitive markets with costly state verification.
Journal of Economic theory 21 (2), 265–293.
Usmani, F. Z. (2001). Inequities in the resolution of securities disputes: Individual or class action;
arbitration or litigation. Fordham J. Corp. & Fin. L. 7, 193.
Yermack, D. (2006). Flights of fancy: Corporate jets, ceo perquisites, and inferior shareholder
returns. Journal of Financial Economics 80 (1), 211–242.
Zingales, L. (1995). Insider ownership and the decision to go public. The Review of Economic
Studies 62 (3), 425–448.
28
Figure 1: Institutional Ownership, Ninth vs. All Other Circuits
This figure shows median industry-adjusted institutional ownership for firms in the Ninth Circuit versus
firms in all other Circuits. At the end of each year, we compute total institutional ownership for each firm
using each institution’s latest filing in that year from Thompson Reuters, and scale total shares owned by
the firm’s shares outstanding from CRSP. We adjust for industry by subtracting the industry median, where
the firm’s industry is identified as the two-digit SIC code. Below we plot the median industry-adjusted IO
separately for firms headquartered in the Ninth Circuit and firm in all other Circuits. The grey vertical
line indicates the date of the Ninth Circuit ruling. The data are presented below the figure. p-values from
a Wilcoxon rank-sum test for a difference in medians between Ninth and All Other Circuits by year are
presented in the far right column.
Data for figure:
Yr
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
N
908
997
1106
1158
1146
1161
1198
1098
1068
1030
1075
1064
1072
1122
1101
1075
1114
Ninth Circuit
Median Std Dev
0.01
0.30
0.01
0.31
0.01
0.32
0.00
0.33
0.00
0.34
0.00
0.34
0.01
0.34
0.02
0.37
0.03
0.38
0.06
0.38
0.05
0.39
0.06
0.38
0.06
0.37
0.05
0.37
0.05
0.36
0.06
0.36
0.06
0.37
29
All Other Circuits
N
Median Std Dev
4458
0.00
0.30
4614
0.00
0.30
4922
0.00
0.31
5222
0.00
0.32
5185
0.00
0.32
5077
0.00
0.32
4999
0.00
0.33
4704
0.00
0.34
4562
0.00
0.36
4464
-0.01
0.36
4544
-0.01
0.37
4599
-0.01
0.37
4839
-0.01
0.36
5090
-0.01
0.35
5109
-0.01
0.36
4857
-0.01
0.36
5151
-0.01
0.36
p-value
on dif
0.60
0.39
0.27
0.29
0.28
0.66
0.03
0.02
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Figure 2: Difference in Difference Estimate: Randomized Placebo Treatment Assignment
This chart shows the difference in difference estimates and t-statistics for 5000 placebo simulations. In each
simulation, a firm is randomly assigned to a state headquarters for the life of the firm. This randomizes
the treatment firms relative to the true observed firm location. The distributions represent difference in
differences estimates and t-statistics based on the specification presented in Table 4, Column 2. The dashed
line represents the true estimate and t-statistics given the actual treatment assignment.
30
Table 1: Summary of Class Actions
This table presents a summary of class action litigation events around the Ninth Circuit Court of appeals
decision made on July 1, 1999. These data cover 1996-2012 and are from Stanford’s Securities Class Action
Clearinghouse.
# Pre-ruling
(suits/yr)
# Post-Ruling
(suits/yr)
∆ Pre-to-Post
(%)
Ninth
All Others
76
168
34
138
-55%
-18%
1998-2000
Ninth
All Others
66.7
175.3
42
159.3
-37%
-9%
Full sample,
(1996-2012)
Ninth
All Others
55.7
172.6
36.1
161.4
-35.2%
-6.5%
time period
Circuit
1999
31
Table 2: Summary Statistics
This Table presents summary statistics for the data sample beginning 1980 and ending 2009. Panel A
presents results for the entire sample. Panel B presents results for states not included in the Ninth U.S.
Circuit Court and Panel C presents statistics for firms subject to the 1990 Ninth Circuit ruling in Re: Silicon
Graphics.
Panel A
Market Equity
Market to Book
Dividend Payer
Book Leverage
ROA
Institutional Ownership
Annual Return
Institutional Blockholder Dummy
Top5 Concentration
Number of Institutional Blockholders
Panel B
Market Equity
Market to Book
Dividend Payer
Book Leverage
ROA
Institutional Ownership
Annual Return
Institutional Blockholder Dummy
Top5 Concentration
Number of Institutional Blockholders
Panel C
Market Equity
Market to Book
Dividend Payer
Book Leverage
ROA
Institutional Ownership
Annual Return
Institutional Blockholder Dummy
Top5 Concentration
Number of Institutional Blockholders
Mean Median Std. Dev.
All Circuits
1849.16
103.76
10587.24
1.80
1.06
8.73
0.48
0.00
0.50
0.24
0.19
0.35
0.04
0.09
0.23
0.34
0.25
0.45
0.16
0.06
0.91
0.61
1.00
0.49
-2.12
-1.67
1.71
1.22
1.00
1.49
Non-Ninth Circuits
1980.22
107.43
10740.21
1.73
1.03
9.48
0.51
1.00
0.50
0.25
0.21
0.36
0.05
0.09
0.22
0.33
0.24
0.47
0.16
0.06
0.85
0.59
1.00
0.49
-2.18
-1.71
1.74
1.18
1.00
1.48
Ninth Circuit
1271.85
90.53
9864.73
2.14
1.24
4.12
0.34
0.00
0.47
0.21
0.13
0.33
0.00
0.07
0.28
0.38
0.31
0.31
0.18
0.02
1.17
0.69
1.00
0.46
-1.86
-1.50
1.51
1.39
1.00
1.54
32
Min
Max
0.00
-0.10
0.00
-0.05
-1.70
0.00
-1.00
0.00
-17.30
0.00
587019.00
3133.52
1.00
44.89
0.46
92.90
110.60
1.00
7.49
41.00
0.00
-0.10
0.00
-0.05
-1.70
0.00
-1.00
0.00
-17.30
0.00
516887.70
3133.52
1.00
44.89
0.46
92.90
110.60
1.00
7.49
41.00
0.00
0.00
0.00
0.00
-1.70
0.00
-0.99
0.00
-15.95
0.00
587019.00
255.95
1.00
30.00
0.46
5.30
95.81
1.00
5.01
12.00
Table 3: Propensity Matched Analysis
Panel A: Propensity Match First Stage: Probit Marginal Effects
This panel presents a Probit estimation of the treatment variable (Ninth Circuit) on a variety of firm characteristics.
Marginal effects are presented in lieu of coefficients. Estimation sample consists only of observations with data on
the ultimate propensity matched outcome variable, InstitutionalOwnershipt+1 . Dividend Payert−1 is an indicator
variable equal to one if the firm the paid a dividend in the prior year, and zero otherwise. Market Equityt−1 is the
lagged dollar market equity value of the firm and Market to Bookt−1 measures the lag ratio of market value of equity
to book value of equity. ROAt−1 is the lagged measure of operating income before interest and depreciation scaled
by prior periods total assets. Annual returns measure the compounded monthly returns for the 12 months prior to
the reporting period. InstitutionalOwnershipt−1 is a lagged value of the level of institutional ownership.
VARIABLES
Pr(ninth)
M arketEquityt−1
-0.00
(0.00)
M arkettoBookt−1
0.03***
(0.01)
DividendP ayert−1
-0.49***
(0.06)
ROAt−1
-0.40***
(0.10)
InstitutionalOwnershipt−1 0.32***
(0.10)
Constant
-1.19**
(0.56)
Two Digit Industry Effects
Y
Observations
3,154
Standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
Panel B: Covariate Balance
This panel presents the difference in characteristics between the Ninth Circuit treatment sample and the nearest
neighbor propensity score matched sample.
Variable
M arketEquityt−1
M arkettoBookt−1
DividendP ayert−1
ROAt−1
InstitutionalOwnershipt−1
Treated
1533.7
2.815
0.24724
0.02686
0.38008
Control
1371.8
2.5812
0.24724
0.00235
0.37716
%bias
1.4
3.1
0
7.9
1
t
0.37
0.54
0
1.11
0.18
p > |t|
0.715
0.589
1
0.265
0.858
Panel C: Treatment Effect
This panel presents of the Ninth Circuit court of appeals decision on InstitutionalOwnershipt+1 . Unmatched
represents the estimated differences between all Ninth Circuit observations and all other observations. ATT represents
the average treatment effect based on estimates of the treated observation compared to a nearest neighbor propensity
score matched score matched sample.
Variable
InstitutionalOwnershipt+1
Sample
Unmatched
ATT
Treated
0.41
0.41
33
Controls
0.37
0.37
Difference
0.04
0.04
S.E.
0.01
0.02
T-stat
3.14 ***
2.23 ***
Table 4: Difference in Difference Regression: The effect of Litigation Laws on Institutional Ownership
This table presents a difference in difference estimation of the effect of the 1999 Ninth Circuit Court of appeals
decision on institutional ownership. Column 1 presents a basic difference in difference specification. Column
2 includes year effects and Column 3 includes firm and year effects. The dependent variables is defined as the
total shares owned by institutions as a percent of total shares outstanding. The main variables of interest
include an indicator variable, Ninth Circuit, that takes a value of one if the firm is subject to (headquartered
in) the 1999 ruling of the Ninth Circuit court of appeals. Post 1999 is an indicator variable equal to one for
observations after the appeals court decision in 1999. Dividend Payert−1 is an indicator variable equal to one
if the firm the paid a dividend in the prior year, and zero otherwise. Market Equityt−1 is the lagged dollar
market equity value of the firm and Market to Bookt−1 measures the lag ratio of market value of equity to
book value of equity. ROAt−1 is the lagged measure of operating income before interest and depreciation
scaled by prior periods total assets. Annual returns measure the compounded monthly returns for the 12
months prior to the reporting period. Columns 1 and 2 include a set of dummy variables for each industry
defined at the two digit SIC code.
Ninth Circuit*Post 1999
Ninth Circuit
Market Equityt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Post 1999
Constant
(1)
Institutional
Ownership
(2)
Institutional
Ownership
(3)
Institutional
Ownership
0.06***
(0.01)
0.03***
(0.01)
0.00
(0.00)
0.00
(0.00)
0.05***
(0.00)
0.32***
(0.01)
0.01***
(0.00)
0.17***
(0.00)
0.14***
(0.04)
0.06***
(0.01)
0.03***
(0.01)
-0.00
(0.00)
0.00
(0.00)
0.06***
(0.00)
0.33***
(0.01)
0.01***
(0.00)
0.05***
(0.01)
-0.00
(0.04)
0.56***
(0.01)
Y
Y
N
86,674
0.23
Y
N
Y
86,674
0.83
Year Effects
N
Industry Effects
Y
Firm Effects
N
Observations
86,674
R-squared
0.17
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
34
-0.00***
(0.00)
0.00
(0.00)
0.01*
(0.00)
0.13***
(0.01)
0.01***
(0.00)
Table 5: Difference in Difference Regression: The effect of Litigation Laws on alternative measures
of ownership structure
This table presents a difference in difference estimation of the effect of the 1999 Ninth Circuit Court of
appeals decision on alterative measures ownership structure. Column 1 presents a difference in difference
specification using the Demsetz and Lehn (1985) measure of Top5 concentration. The dependent variables is
% Ownership of Top Five Owners
defined as Ln( (1−%
Ownership of Top Five Owners ). Column 2 presents results using the number of institutional
blockholders as the dependent variable. Finally, Column 3 presents a logit specification using the probability
of having at least one institutional blockholder. The main variables of interest include an indicator variable,
Ninth Circuit, that takes a value of one if the firm is subject to (headquartered in) the 1999 ruling of the
Ninth Circuit court of appeals. Post 1999 is an indicator variable equal to one for observations after the
appeals court decision in 1999. Dividend Payert−1 is an indicator variable equal to one if the firm the
paid a dividend in the prior year, and zero otherwise. Market Equityt−1 is the lagged dollar market equity
value of the firm and Market to Bookt−1 measures the lag ratio of market value of equity to book value of
equity. ROAt−1 is the lagged measure of operating income before interest and depreciation scaled by prior
periods total assets. Annual returns measure the compounded monthly returns for the 12 months prior to
the reporting period. Columns 1 and 2 include a set of dummy variables for each industry defined at the
two digit SIC code.
Ninth Circuit*Post 1999
Ninth Circuit
Market Equityt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Constant
(1)
Ownership
Concentration
(2)
Number of Inst.
Blockholders
(3)
P(Blockholder)
0.36***
(0.04)
0.13***
(0.03)
-0.00***
(0.00)
-0.01**
(0.00)
0.20***
(0.03)
1.40***
(0.05)
0.04***
(0.01)
-3.19***
(0.25)
0.20***
(0.04)
0.08***
(0.03)
-0.00***
(0.00)
-0.02***
(0.00)
-0.01
(0.02)
0.86***
(0.04)
-0.04***
(0.01)
0.22
(0.19)
0.32***
(0.07)
0.13***
(0.05)
-0.00***
(0.00)
-0.03***
(0.01)
0.14***
(0.03)
1.37***
(0.07)
-0.01
(0.01)
-1.04***
(0.32)
Y
Y
N
86,674
0.15
Y
Y
N
86,673
0.08
Year Effects
Y
Industry Effects
Y
Firm Effects
N
Observations
86,674
R-squared
0.10
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
35
Table 6: Difference in Difference in Difference Regression: The Effect of Litigation Laws on Institutional Ownership in the Presence of Institutional Blockholders
This table presents a difference in difference in Difference estimation of the effect of the 1999 Ninth Circuit Court
of appeals decision on institutional ownership, conditional on the presence of an institutional blockholder. Column
1 presents a basic difference in difference specification. Column 2 includes year effects and Column 3 includes firm
and year effects. The main variables of interest include and indicator variable, Ninth Circuit, that takes a value of
one if the firm is subject to (headquartered in) the 1999 ruling of the Ninth Circuit court of appeals. Post 1999 is an
indicator variable equal to one for observations after the appeals court decision in 1999. No Blockholderpretreatment
is an indicator equal to one if the firm does not have an institutional blockholder in 1998 (prior to the decision)
and zero otherwise. Dividend Payert−1 is an indicator variable equal to one if the firm the paid a dividend in the
prior year, and zero otherwise. Market Equityt−1 is the lagged dollar market equity value of the firm and Market
to Bookt−1 measures the lag ratio of market value of equity to book value of equity. ROAt−1 is the lagged measure
of operating income before interest and depreciation scaled by prior periods total assets. Annual returns measure
the compounded monthly returns for the 12 months prior to the reporting period. Columns 1 and 2 include a set of
dummy variables for each industry defined at the two digit SIC code.
Ninth Circuit*Post 1999
Ninth*Post 1999*No Blockholder
Ninth Circuit
No Blockholderpretreatment
Ninth*No Blockholder
Post 1999*No Blockholder
Market Equityt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Post 1999
Constant
(1)
Institutional
Ownership
(2)
Institutional
Ownership
(3)
Institutional
Ownership
0.02
(0.01)
0.05*
(0.03)
0.03**
(0.01)
-0.20***
(0.01)
0.01
(0.02)
-0.09***
(0.01)
0.00***
(0.00)
0.00
(0.00)
0.05***
(0.01)
0.28***
(0.01)
0.01***
(0.00)
0.22***
(0.01)
0.20***
(0.07)
0.03**
(0.01)
0.05*
(0.03)
0.02*
(0.01)
-0.21***
(0.01)
0.00
(0.02)
-0.08***
(0.01)
0.00***
(0.00)
0.00
(0.00)
0.06***
(0.01)
0.29***
(0.01)
0.01***
(0.00)
0.04***
(0.01)
0.03
(0.02)
-0.04***
(0.01)
-0.00***
(0.00)
-0.00
(0.00)
0.01**
(0.00)
0.16***
(0.01)
0.01***
(0.00)
0.04
(0.07)
0.08***
(0.01)
Y
Y
N
52,860
0.35
Y
N
Y
52,860
0.79
Year Effects
N
Industry Effects
Y
Firm Effects
N
Observations
52,860
R-squared
0.30
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1 36
Table 7: Difference in Difference in Difference Regression: The Effect of Litigation Laws on Institutional Ownership Conditional on Announcement CARs
This table presents a difference in difference in Difference estimation of the effect of the 1999 Ninth Circuit Court
of appeals decision on institutional ownership, conditional on the presence of an institutional blockholder. Column
1 presents a basic difference in difference specification. Column 2 includes year effects and Column 3 includes firm
and year effects. The main variables of interest include and indicator variable, Ninth Circuit, that takes a value of
one if the firm is subject to (headquartered in) the 1999 ruling of the Ninth Circuit court of appeals. Post 1999 is an
indicator variable equal to one for observations after the appeals court decision in 1999. Positive Car1999Decision is an
indicator equal to one if the firm had a positive announcement return to the Ninth Circuit’s 1999 decision, and zero
otherwise. Dividend Payert−1 is an indicator variable equal to one if the firm the paid a dividend in the prior year,
and zero otherwise. Market Equityt−1 is the lagged dollar market equity value of the firm and Market to Bookt−1
measures the lag ratio of market value of equity to book value of equity. ROAt−1 is the lagged measure of operating
income before interest and depreciation scaled by prior periods total assets. Annual returns measure the compounded
monthly returns for the 12 months prior to the reporting period. Columns 1 and 2 include a set of dummy variables
for each industry defined at the two digit SIC code.
Ninth Circuit*Post 1999
Ninth*Post 1999*Pos. Car
Ninth Circuit
Positive Car1999Decision
Ninth*Positive Car
Post 1999*Positive Car
Market Equityt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Post 1999
Constant
(1)
Institutional
Ownership
(2)
Institutional
Ownership
(3)
Institutional
Ownership
0.04***
(0.02)
-0.02
(0.02)
0.04***
(0.01)
-0.02**
(0.01)
0.01
(0.02)
0.02**
(0.01)
0.00
(0.00)
-0.00
(0.00)
0.05***
(0.01)
0.37***
(0.01)
0.01***
(0.00)
0.16***
(0.01)
0.11*
(0.07)
0.05***
(0.02)
-0.01
(0.02)
0.03***
(0.01)
-0.02**
(0.01)
0.01
(0.02)
0.02**
(0.01)
-0.00
(0.00)
-0.00
(0.00)
0.06***
(0.01)
0.38***
(0.01)
0.01***
(0.00)
0.05***
(0.01)
-0.01
(0.02)
0.01
(0.01)
-0.00***
(0.00)
-0.00
(0.00)
0.01
(0.00)
0.16***
(0.01)
0.00***
(0.00)
-0.03
(0.07)
0.07***
(0.01)
Y
Y
N
55,748
0.21
Y
N
Y
55,748
0.79
Year Effects
N
Industry Effects
Y
Firm Effects
N
Observations
55,748
R-squared
0.16
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
37
Table 8: Difference in Difference Regression: The effect of Litigation Laws on Institutional Ownership by Institution Type
This table presents a difference in difference estimation of the effect of the 1999 Ninth Circuit Court of
appeals decision on institutional ownership by institutional type. All columns present specification 2 from
Table 4 include year effects and a set of dummy variables for each industry defined at the two digit SIC code.
The main variables of interest include and indicator variable, Ninth Circuit, that takes a value of one if the
firm is subject to (headquartered in) the 1999 ruling of the Ninth Circuit court of appeals. Post 1999 is an
indicator variable equal to one for observations after the appeals court decision in 1999. Dividend Payert−1
is an indicator variable equal to one if the firm the paid a dividend in the prior year, and zero otherwise.
Market Equityt−1 is the lagged dollar market equity value of the firm and Market to Bookt−1 measures the
lag ratio of market value of equity to book value of equity. ROAt−1 is the lagged measure of operating
income before interest and depreciation scaled by prior periods total assets. Annual returns measure the
compounded monthly returns for the 12 months prior to the reporting period. Columns 1 and 2 include
VARIABLES
Ninth Circuit*Post 1999
Ninth Circuit
Market Equitykt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Constant
(1)
Banks
(2)
Investment Companies
(3)
Pension Funds
(4)
Insurance
0.02***
(0.00)
-0.00**
(0.00)
0.00***
(0.00)
0.00
(0.00)
0.03***
(0.00)
0.06***
(0.00)
0.00***
(0.00)
0.02***
(0.01)
0.03***
(0.01)
0.02***
(0.00)
-0.00***
(0.00)
-0.00***
(0.00)
-0.01***
(0.00)
0.22***
(0.01)
0.01***
(0.00)
0.05*
(0.03)
0.01
(0.00)
-0.01**
(0.00)
-0.00
(0.00)
-0.00**
(0.00)
0.00
(0.00)
0.01
(0.01)
-0.00
(0.00)
0.06***
(0.01)
0.00
(0.00)
0.00
(0.00)
0.00***
(0.00)
-0.00*
(0.00)
0.01***
(0.00)
0.02***
(0.00)
-0.00
(0.00)
0.04**
(0.02)
Y
Y
N
11,207
0.06
Y
Y
N
58,233
0.04
Year Effects
Y
Y
Industry Effects
Y
Y
Firm Effects
N
N
Observations
79,699
58,446
R-squared
0.15
0.22
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
38
Table 9: Difference in Difference Robustness
This table presents a various robustness specifications for a difference in difference estimation of the effect
of the 1999 Ninth Circuit Court of appeals decision on institutional ownership. All columns use the same
specification as Column 2 in Table 4. Column one excludes all California firms from the estimation. Column
2 excludes all firms in the Fama-French Electronics, Computers, and Pharmaceutical industries. Finally,
Column 3 shows results from a specification using a ten year window around a placebo 1989 treatment.
The main variables of interest include an indicator variable, Ninth Circuit, that takes a value of one if the
firm is subject to (headquartered in) the 1999 ruling of the Ninth Circuit court of appeals. Post 1999 is an
indicator variable equal to one for observations after the appeals court decision in 1999. Dividend Payert−1
is an indicator variable equal to one if the firm the paid a dividend in the prior year, and zero otherwise.
Market Equityt−1 is the lagged dollar market equity value of the firm and Market to Bookt−1 measures the
lag ratio of market value of equity to book value of equity. ROAt−1 is the lagged measure of operating
income before interest and depreciation scaled by prior periods total assets. Annual returns measure the
compounded monthly returns for the 12 months prior to the reporting period. Columns 1 and 2 include a
set of dummy variables for each industry defined at the two digit SIC code.
Ninth Circuit*Post 1999
Ninth Circuit
Market Equityt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Constant
(1)
Institutional
Ownership
(2)
Institutional
Ownership
(3)
Institutional
Ownership
Exclude California
0.05***
(0.02)
0.01
(0.01)
-0.00
(0.00)
-0.00
(0.00)
0.07***
(0.01)
0.32***
(0.01)
0.01***
(0.00)
-0.01
(0.05)
Exclude Tech
0.06***
(0.01)
0.02**
(0.01)
-0.00
(0.00)
-0.00
(0.00)
0.07***
(0.01)
0.35***
(0.01)
0.01***
(0.00)
-0.00
(0.04)
Placebo 1989
0.00
(0.01)
0.03***
(0.01)
0.00***
(0.00)
0.00**
(0.00)
0.10***
(0.01)
0.27***
(0.01)
0.01***
(0.00)
0.11*
(0.06)
Y
Y
N
72,954
0.24
Y
Y
N
26,300
0.19
Year Effects
Y
Industry Effects
Y
Firm Effects
N
Observations
74,558
R-squared
0.22
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
39
40
Table 10: Difference in Difference: Performance and Governance
-0.005**
(0.002)
-0.006***
(0.001)
0.000***
(0.000)
0.001***
(0.000)
0.015***
(0.001)
0.819***
(0.006)
0.028***
(0.004)
-0.037***
(0.009)
Year Effects
Y
Industry Effects
Y
Firm Effects
N
Observations
86,306
R-squared
0.66
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
Constant
Annual Returnt−1
ROAt−1
Dividend Payert−1
Market to Bookt−1
Market Equityt−1
Ninth Circuit
Ninth Circuit*Post 1999
(1)
ROA
All Firms
Firms
Y
Y
N
27,611
0.63
-0.007*
(0.004)
-0.001
(0.003)
0.000***
(0.000)
0.000
(0.001)
0.003
(0.002)
0.793***
(0.011)
0.021***
(0.005)
0.008
(0.013)
(2)
ROA
Non-Dividend
Payers
Y
Y
N
28,775
0.72
0.004
(0.003)
-0.008***
(0.003)
0.000***
(0.000)
0.001***
(0.000)
0.012***
(0.002)
0.843***
(0.014)
0.026***
(0.002)
-0.036***
(0.006)
(3)
ROA
Dividend
Payers
Y
Y
N
15,190
0.13
-0.32***
(0.09)
0.38***
(0.09)
0.00*
(0.00)
-0.08***
(0.01)
0.56***
(0.06)
0.27
(0.21)
0.00
(0.02)
1.26**
(0.63)
(4)
D/O Liability
All
Firms
Y
Y
N
4,261
0.14
0.02
(0.15)
-0.08
(0.16)
0.00
(0.00)
-0.08***
(0.02)
0.16*
(0.09)
0.08
(0.25)
-0.01
(0.02)
1.65***
(0.18)
(5)
D/O Liability
Non-Dividend
Payers
Y
Y
N
9,229
0.12
-0.27**
(0.12)
0.66***
(0.13)
0.00
(0.00)
-0.07***
(0.02)
0.39***
(0.10)
0.33
(0.40)
0.01
(0.03)
1.12
(0.71)
(6)
D/O Liability
Dividend
Payers
This table a difference in difference estimation of the effect of the 1999 Ninth Circuit Court of appeals decision on profitability and ownership. All columns
use the same specification as Column 2 in Table 4. Column one examines the effect of the Ninth Circuit decision on profitability for all firms. Column
2 includes only dividend paying firms (classified in 1998) and Column 3 shows results from a specification that includes only non-dividend paying firms
(also classified as of 1998). ROA is operating income before interest and depreciation scaled by prior periods total assets. Columns 4-6 examines the effect
on director and officer liability. The dependent variables is the sum of indicators for each of the following governance features: director indemnification,
indemnification contracts, director liability insurance, executive severance agreements , golden parachutes, and compensation plans with change in control
provisions. Our independent variable increases by one for each of these features the firm has. Column 4 uses the entire sample, while columns 5 and
6 examine dividend paying firms and non-dividend paying firms (as of 1998) respectively. The main variables of interest in all specifications include an
indicator variable, Ninth Circuit, that takes a value of one if the firm is subject to (headquartered in) the 1999 ruling of the Ninth Circuit court of appeals.
Post 1999 is an indicator variable equal to one for observations after the appeals court decision in 1999. Dividend Payert−1 is an indicator variable equal
to one if the firm the paid a dividend in the prior year, and zero otherwise. Market Equityt−1 is the lagged dollar market equity value of the firm and
Market to Bookt−1 measures the lag ratio of market value of equity to book value of equity. ROAt−1 is the lagged measure of operating income before
interest and depreciation scaled by prior periods total assets. Annual returns measure the compounded monthly returns for the 12 months prior to the
reporting period. Columns 1 and 2 include a set of dummy variables for each industry defined at the two digit SIC code.
Table A1: Difference in Difference Regression: The effect of Litigation Laws on Top5 Ownership
Concentration
This table presents a difference in difference estimation of the effect of the 1999 Ninth Circuit Court of
appeals decision on institutional ownership. Column 1 presents a basic difference in difference specification.
Column 2 includes year effects and Column 3 includes firm and year effects. The dependent variables is
% Ownership of Top Five Owners
defined as Ln( (1−%
Ownership of Top Five Owners ). The main variables of interest include an indicator variable,
Ninth Circuit, that takes a value of one if the firm is subject to (headquartered in) the 1999 ruling of the
Ninth Circuit court of appeals. Post 1999 is an indicator variable equal to one for observations after the
appeals court decision in 1999. Dividend Payert−1 is an indicator variable equal to one if the firm the
paid a dividend in the prior year, and zero otherwise. Market Equityt−1 is the lagged dollar market equity
value of the firm and Market to Bookt−1 measures the lag ratio of market value of equity to book value of
equity. ROAt−1 is the lagged measure of operating income before interest and depreciation scaled by prior
periods total assets. Annual returns measure the compounded monthly returns for the 12 months prior to
the reporting period. Columns 1 and 2 include a set of dummy variables for each industry defined at the
two digit SIC code.
Ninth Circuit*Post 1999
Ninth Circuit
Market Equityt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Post 1999
Constant
(1)
Top5
Concentration
(2)
Top5
Concentration
(3)
Top5
Concentration
0.33***
(0.04)
0.14***
(0.03)
-0.00***
(0.00)
-0.00*
(0.00)
0.14***
(0.03)
1.35***
(0.05)
0.03***
(0.01)
0.44***
(0.02)
-2.58***
(0.26)
0.36***
(0.04)
0.13***
(0.03)
-0.00***
(0.00)
-0.01**
(0.00)
0.20***
(0.03)
1.40***
(0.05)
0.04***
(0.01)
0.12***
(0.04)
-3.19***
(0.25)
-1.31***
(0.03)
Y
Y
N
86,674
0.10
Y
N
Y
86,674
0.75
Year Effects
N
Industry Effects
Y
Firm Effects
N
Observations
86,674
R-squared
0.08
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
41
-0.00***
(0.00)
-0.00
(0.00)
0.03*
(0.02)
0.42***
(0.05)
-0.00
(0.00)
Table A2: Difference in Difference Regression: The Effect of Litigation Laws on the number of
Blockholders
This table presents a difference in difference estimation of the effect of the 1999 Ninth Circuit Court of appeals
decision on the number of institutional blockholders. Column 1 presents a basic difference in difference
specification. Column 2 includes year effects and Column 3 includes firm and year effects. The main
variables of interest include and indicator variable, Ninth Circuit, that takes a value of one if the firm is
subject to (headquartered in) the 1999 ruling of the Ninth Circuit court of appeals. Post 1999 is an indicator
variable equal to one for observations after the appeals court decision in 1999. Dividend Payert−1 is an
indicator variable equal to one if the firm the paid a dividend in the prior year, and zero otherwise. Market
Equityt−1 is the lagged dollar market equity value of the firm and Market to Bookt−1 measures the lag ratio
of market value of equity to book value of equity. ROAt−1 is the lagged measure of operating income before
interest and depreciation scaled by prior periods total assets. Annual returns measure the compounded
monthly returns for the 12 months prior to the reporting period. Columns 1 and 2 include a set of dummy
variables for each industry defined at the two digit SIC code.
Ninth Circuit*Post 1999
Ninth Circuit
Market Equityt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Post 1999
Constant
(1)
Number of Inst.
Blockholders
(2)
Number of Inst.
Blockholders
(3)
Number of Inst.
Blockholders
0.16***
(0.04)
0.09***
(0.03)
-0.00***
(0.00)
-0.02***
(0.00)
-0.08***
(0.02)
0.81***
(0.04)
-0.05***
(0.01)
0.75***
(0.02)
0.77***
(0.20)
0.20***
(0.04)
0.08***
(0.03)
-0.00***
(0.00)
-0.02***
(0.00)
-0.01
(0.02)
0.86***
(0.04)
-0.04***
(0.01)
0.11*
(0.06)
-0.00***
(0.00)
-0.01***
(0.00)
-0.05**
(0.02)
0.03
(0.05)
-0.05***
(0.01)
0.22
(0.19)
2.41***
(0.04)
Y
Y
N
86,674
0.15
Y
N
Y
86,674
0.61
Year Effects
N
Industry Effects
Y
Firm Effects
N
Observations
86,674
R-squared
0.11
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
42
Table A3: Difference in Difference Regression: The Effect of Litigation Laws on the Probability of
an Institutional Blockholder
This table presents a difference in difference estimation of the effect of the 1999 Ninth Circuit Court of appeals
decision on the number of institutional blockholders. Column 1 presents a basic difference in difference
specification. Column 2 includes year effects and Column 3 includes firm and year effects. The main
variables of interest include and indicator variable, Ninth Circuit, that takes a value of one if the firm is
subject to (headquartered in) the 1999 ruling of the Ninth Circuit court of appeals. Post 1999 is an indicator
variable equal to one for observations after the appeals court decision in 1999. Dividend Payert−1 is an
indicator variable equal to one if the firm the paid a dividend in the prior year, and zero otherwise. Market
Equityt−1 is the lagged dollar market equity value of the firm and Market to Bookt−1 measures the lag ratio
of market value of equity to book value of equity. ROAt−1 is the lagged measure of operating income before
interest and depreciation scaled by prior periods total assets. Annual returns measure the compounded
monthly returns for the 12 months prior to the reporting period. Columns 1 and 2 include a set of dummy
variables for each industry defined at the two digit SIC code. Odds ratios are reported in lieu of coefficients.
VARIABLES
Ninth Circuit*Post 1999
Ninth Circuit
Market Equitykt−1
Market to Bookt−1
Dividend Payert−1
ROAt−1
Annual Returnt−1
Post 1999
Constant
(1)
P(Blockholder)
(2)
P(Blockholder)
(3)
P(Blockholder)
0.27***
(0.07)
0.14***
(0.05)
-0.00***
(0.00)
-0.03***
(0.01)
0.02
(0.03)
1.27***
(0.07)
-0.03***
(0.01)
0.86***
(0.03)
-0.17
(0.33)
0.32***
(0.07)
0.13***
(0.05)
-0.00***
(0.00)
-0.03***
(0.01)
0.14***
(0.03)
1.37***
(0.07)
-0.01
(0.01)
0.06
(0.15)
-0.00***
(0.00)
-0.04***
(0.01)
-0.05
(0.05)
0.12
(0.13)
-0.06***
(0.02)
-1.04***
(0.32)
Year Effects
N
Industry Effects
Y
Firm Effects
N
Observations
86,673
Psuedo R-squared
0.06
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, * p < 0.1
43
Y
Y
N
86,673
0.08
Y
N
Y
55,516
0.12