Corporate Scandals, Capital Structure andContagion E¤ect
Stefano Bonini*New York University, Stern School of Business44W 4th St., 10012, New York, NY, USA
Diana BoraschiBocconi University,
Via Roentgen 1, 20122, Milan, [email protected]
This draft: 1st May 2009
JEL Codes: G32, G33, K41Keywords: corporate scandals, security o¤erings, capital structure, contagion ef-
fect, market timing.
Acknowledgement 1 *Corresponding author. We thank Julian Franks, Matthew Pritskerand seminar participants at the NYU Pollack Center for Law and Business for helpful com-ments and suggestions. We are particularly indebted with Je¤rey Wurgler for invaluable sug-gestions and support. We gratefully acknowledge Cornerstone Research support for providingsecurity class action data The ideas expressed in the paper do not necessarily re�ect those ofthe authors�a¢ liation. Any errors remain our own.
Abstract
A wave of corporate scandals has recently hit the market reviving attention on the e¤ectsof these events on shareholders�value, corporate governance and stock market reaction. Thedocumented far-reaching e¤ects of corporate scandals on security prices may have a markettiming value that managers may be willing to exploit. In this paper we analyze whethercompanies involved in a security class action do exhibit di¤erential capital structure decisionsand if the information revealed by a corporate scandal a¤ects security issuances by industrypeers. Our �ndings show that before a SCAS is �led, companies engaged in a scandal had ahigher number of security o¤erings and due equity mispricing they were more likely to useequity as a �nancing mechanism. Following the SCAS �ling they also exhibit decreasing bookand market leverage. �nally we observe signi�cant contagion e¤ects on industry peers. Theseresult suggest that investors tend to process company-speci�c news as a more industry-wideinformation.
Introduction
A wave of corporate scandals has recently hit the market reviving attention on the
e¤ects of these events on shareholders�value, corporate governance and stock market
reaction. Academic research has shown that companies su¤er a considerable decline in
both stock prices and debt ratings upon Chapter 11 �ling announcements, �nancial re-
ports re-stating or �nancial distress announcements (Palmrose, Richardson and Scholz,
2004; Lang and Stulz, 1992; Brewer and Jackson, 1997). Scandals early detection,
if not prevention, is therefore valuable to stakeholders. Agrawal and Chadha, (2005)
document that appropriate corporate governance mechanisms may positively in�uence
the probability of earnings restatments. Agrawal and Cooper (2007) support this ev-
idence highlighting the higher turnover of top management and top �nancial o¢ cers
soon before and immediately after an accounting scandals. Dyck, Morse and Zingales,
(2007) show that non-traditional mechanisms and stakeholders-at-large play a consid-
erable role in triggering fraud-detection. Given the documented far-reaching e¤ects of
corporate scandals, it is interesting to ask whether managerial behavior in companies
engaged in a corporate scandal a¤ects also �nancial decision on capital raising, and
in particular whether managers, anticipating the risks of a corporate scandal exhibit
di¤erent capital structure policies than those of their peers. Surprisingly though this
question is still unanswered. In this paper we try to �ll this gap by looking at the
security issuance patterns of companies engaged in Security Class Actions Suit between
1996 and 2005. In particular, we address three main research questions:
(a) What is the ex-ante and ex-post �nancing pattern of �rms engaged in a corporate
scandal?;
(b) Is there a contagion e¤ect in the �nancing pattern of the industry after a cor-
porate scandal was revealed?;
(c) Is there a contagion e¤ect in the stock prices of the industry after a corporate
scandal was revealed?
Previous literature has addressed corporate scandals by studying cases of bank-
ruptcy announcement, public announcement of frauds in the press and earnings re-
statements. In this paper we adopt the engagement in a security class action suit as
a proxy of a corporate scandal. We collect data from the Stanford Securities Class
Action Clearinghouse (SSCASC) database1. This measure of corporate scandals allow
to generalize the results to a broader set of cases because it deals with actions that: a)
1Database is mantained in cooperation with Cornerstone Research.
3
are important enough to have meaningful e¤ects on security-holders value and b) leave
the company as a going concern allowing menaningful ex-ante and ex-post di¤erential
analysis. In fact less than 10% of cases included in the SSCAC database end up in
bankruptcy announcements.
Our �ndings show that before a SCAS is �led, companies engaged in a scandal had
a higher number of security o¤erings compared to their industry average. At the same
time, we document that since �rms before the scandals experienced overvaluation in
stock prices they were more likely to use equity as a �nancing mechanism. Compared
to their peers, �rms involved in a security class action consistently issue more equity in
the two-year period preceding the �ling of the suit. Consistently with Market Timing
Hypotheses, we �nd that SCAS �rms exhibit decreasing book and market leverage
before the �ling due to abnormal volumes of equity o¤erings. Soon after the �ling
though, leverage increases sharply and signi�cnatly due to the readjustment in equity
market value.
Looking at contagion e¤ects on the �nancing pattern of the industry, we �nd that
equity issuances decrease for both peers and SCAS �rms over time, and this decrease
is more pronounced for SCAS �rms. We observe that close to the SCAS �ling there is
a decrease in debt and equity issuances for both samples. The existence of a signi�cant
negative equity and debt issuance trends can be interpreted as a contagion e¤ect in the
�nancing pattern, i.e. a SCAS �ling generates a decrease in equity and debt o¤erings
in the industry.
Finally, we investigate the e¤ect of corporate scandals on the �rm�s competitors�
stock prices. We test the presence of a negative contagion e¤ect on stock prices of the
industry of the �rm involved in a corporate scandal. For the [-1,0] and [-5,5] event
windows we �nd that peers su¤er a cumulative abnormal return of -.20% and -.65%
respectively. These results shed light to the fact that corporate scandals do have a
negative impact on their industry. Furthermore we study this contagion e¤ect dividing
the sample into accounting and non-accounting allegations and we �nd that the negative
stock price reaction of focal �rms with non-accounting allegations is strongly signi�cant
for the [-15,+15] and [-20,+20] event windows, while this is not the case for accounting
allegations. Cases with accounting allegations do not show a statistically signi�cant
contagion e¤ect in their industry. This result is aligned with Gande and Lewis (2009)
who provided evidence on the price reaction to SCAS �lings.
These results allow to shed light on the �nancing and security issuance behavior of
�rms engaged in corporate scandals. Our results also allow to conclude that indepen-
4
dently from their intensity, corporate scandals do generate e¤ects at the industry level
by leading to a contraction in security o¤erings and a decrease in stock returns for all
the industry constituents.
The remainder of this paper is organized as follows. Section I summarize previous
work on corporate scandals and present the hypotheses that we test in our study.
Section II presents the data and summary statistics. Section III presents the results of
our empirical analysis of the �nancing pattern of �rms engaged in corporate scandals.
Section IV presents the results of our empirical analysis of the contagion e¤ect in stock
prices and �nancing pattern. Section V presents the robustness tests performed and
Section VI concludes the paper.
1 Motivation and Hypotheses
1.1 Corporate Scandals and Security O¤erings
Corporate scandals can be de�ned as widely publicized incidents involving allegations
of managerial wrongdoing, disgrace, or moral outrage of one or more members of a com-
pany. Typical schemes of fraudulent behavior include misstatements of �nancial �gures
on current, past or future investments or operations, failure to disclose information or
delay information retention, bribery, insider trading, and any other illegal activities
that hurt the shareholders of the �rm (Dyck, Morse and Zingales, 2007). Companies�
misconduct may have two separate but important e¤ects on managerial actions: �rst,
it may signi�cantly reduce stock prices making secondary equity o¤erings increasingly
diluting and costly; second it will reasonably reduce, or cancel altogether, manager-
ial independence in taking capital structure-related decisions. Managers, arguably, are
aware of the risks associated with malpractices and therefore have strong incentives
to �make the best out of it while it lasts�. It is then reasonable to expect that they
will exploit this information asymmetry to increase the amount of funds they collect
to anticipate a potential capital constraint after the scandal eruption. Funds then may
be used in several ways: to deliver a steady stream of cash �ows, dividend payments
and investments, to pursue buyback plans, to rebalance at a lower cost the �nancial
structure of the company or simply to enhance the liquidity stock in a similar spirit to
Ivashina and Scharfstein (2009). SCAS �ling documents provide meaningful examples
of these behaviors. In Cisco (2001) the plainti¤ alleges that: "[...] After completing
5
more than 20 major acquisitions between 9/99 and 2/01, by issuing more than 400 mil-
lion shares of Cisco stock, [...] , on 2/6/01, Cisco announced extremely disappointing
2ndQ F01 results"; similarly in Bay Networks (1997) it is alleged that: "[...] materially
false or misleading statements enabled Bay Networks to Complete stock-for-stock acqui-
sitions during the Class Period". Working capital �nancing is claimed by the plainti¤
in Supergen 2003: "[...] SuperGen sold millions of shares and notes [...] so as to pro-
vide it with ample monies to fund its operations. However, this all took place prior to
revelations concerning the veracity of the Company�s statements regarding Mitozytrex".
In this spirit we conjecture our �rst hypothesis:
Hypothesis 1: Ex-ante, �rms engaged in a corporate scandal have a greater amountof security o¤erings compared to their industry average.
The Market Timing Hypothesis of Capital Structure states that when making deci-
sions about funding, managers take into account the current conditions of the debt and
equity markets. Managers will choose the funding scheme that looks more favorable
pro-tempore, and if none seems to be favorable then fund raising might be deferred.
Support to the market timing theory comes from the empirical evidence that shows the
existence of managers�opportunism when it comes to the �rm�s �nancing needs (Gra-
ham and Harvey, 2001). Although this theory is short in explaining many of the factors
that have been traditionally considered in the studies of corporate capital structure, it
has strong empirical evidence that supports the existence of a behavioral component
in managers when it comes to �nancing their �rms. Baker and Wurgler (2002) build
their capital structure predictions on the historical stock prices of �rms and further
evidence con�rms that indeed stock prices play an important role in explaining capital
structure and capital structure changes (Welch, 2004). As for stock prices, the market
timing hypothesis argues that �rms tend to issue equity after the value of their stock
has increased (Hovakimian, Opler and Titman, 2001) and that corporate leverage is
best understood as the cumulative e¤ect of past attempts to time the market (Baker
and Wurgler, 2002). One important assumption underlying the market timing hypoth-
esis is the possible existence of stock price misvaluation. If this is the case, managers
of a �rm that has overvalued (undervalued) stock price will opportunistically exploit
this mispricing by issuing equity (debt). This later fact was con�rmed by Graham and
Harvey (2001). In a interview survey to 392 U.S. and Canadian CFOs, 76% of the
sample reported that the amount by which their stock was over or undervalued was an
"important" or "very important" factor when taking decisions about equity issuance.
6
Corporate scandals act as information revelation mechanisms to equity market par-
ticipants. A scandal shed new light on the actual managerial and accounting practices
of the �rm, revealing information that was previously unavailable to investors. Evidence
show that in extreme cases ending in bankruptcy �ling, investors reaction is strong and
signi�cant with sharp declines in stock prices of the �rms involved in the scandal (Lang
and Stulz, 1992; Rao and Hamilton, 1996; Agrawal and Chadha, 2005). The stock price
drop following such events can be interpreted as evidence of a previous stock overvalua-
tion due to either an accounting phenomenon (such as a misrepresentation of earnings)
or also because some information regarding the company�s investments or risk exposure
was not fully available to the market. Accordingly, we expect that:
Hypothesis 2: Ex-ante, �rms engaged in a corporate scandal made greater use ofequity �nancing compared to their industry averages.
If managers -due to the information asymmetry which eventually lead to a scandal
- time the market issuing more equity when the stock is overvalued, then we can con-
jecture two ancillary predictions. First, if equity issuance is higher than their peers,
leverage by construction should be lower Similarly, once a scandal erupts, the abnormal
security issuance pattern should revert towards the industry mean. Accordingly we
de�ne the following two hypotheses:
Hypothesis 3: Ex-ante, �rms engaged in a corporate scandal had lower levels ofleverage compared to their industry average.
Hypothesis 4: After the corporate scandal is unveiled, the stock price of these �rmsadjusts to its �fair�price and thus �rms start �nancing themselves as the mean of their
industry.
1.2 Corporate Scandals and Contagion E¤ect on �nancing pat-
tern
Academic research on contagion e¤ects at the corporate level, has focused on the
spillovers of shocks occurring in one entity to other entities. Previous literature has
explored the contagion e¤ects on stock returns following a bankruptcy (Lang and Stulz
1992), earning restatment (Gleason et al. 2008) and managerial forecasts announce-
ments (Ramnath 2002). Similarly, Giesecke (2003) and Theocarides (2007) have ex-
plored contagion in the corporate bond market showing that bond prices, yields and
7
spreads react to �rm-speci�c information. Yet, no previous study has investigated the
existence of a contagion e¤ect on capital structure decisions by companies. Since listed
companies raise capital in the market, they are exposed to investor sentiments and
market momentum and, possibly, to information concerning contiguous companies that
investors may transfer to the entire industry. The recent �nancial crisis has provided
an illuminating example of this phenomenon where inherently sound companies have
experienced the same dry-up in capital as weaker peers in their industry. Despite their
managers�e¤orts, "the capital market window [was] just closed" for both high and low
quality companies (Federal Reserve Board (2008)).
In this spirit, a SCAS �ling is a signal that a meaningful mismanagement has oc-
curred in a company. Investor may infer that this behavior can be common practice
across the industry and therefore increase the capital constraints on peer companies. A
highly constrained �nancing environment will lead to increased cost of external �nanc-
ing and ultimately to a contraction of the total security o¤erings of the industry. Thus,
we generate the following hypothesis:
Hypothesis 5: The eruption of a corporate scandal will cause a contagion e¤ect onthe �nancing pattern of the industry peers, generating a contraction in both debt and
equity issuances.
There are several characteristics in an industry that can a¤ect the existence and
magnitude of a contagion e¤ect. We expect the degree of similarity among the �rms�
cash �ows to intensify the extent of the contagion e¤ect on the �nancing pattern of
one industry. This intensi�cation of the contagion e¤ect is due to the fact that highly
similar �rms are likely to have investments with similar cash �ow characteristics and
similar risk exposures (Lang and Stulz, 1992). If a security class action suit conveys
bad news about the projection of cash �ows or �rm risk, then investors will be more
likely to reassess also the �rm�s competitors�cost of �nancing. Measuring similarity as
the correlation of returns between the competitors and the �rm engaged in a corporate
scandal2, we expect that:
Hypothesis 6: Coeteris paribus, the contagion e¤ect on the �nancing pattern ofthe peers group is larger for industries in which competitors show a higher degree of
cash �ows similarity with �rms involved in the corporate scandal.
2As measured by the correlation of returns between the industry portfolio and the �rm engaged inthe corporate scandal in the year preceding the �ling of the class action suit.
8
1.3 Corporate Scandals and Contagion E¤ect on stock prices
A natural second step would be to evaluate if these corporate scandals a¤ected also
the competitors� returns. Most studies on contagion e¤ects have focused mainly on
US bank failures (Kannas, 2004). These studies state that the failure of a large bank
can undermine public con�dence in the banking system as a whole, which may in turn
threaten the stability of the �nancial system by causing runs on other banks (Diamond
and Dybvig, 1983; Aharony and Swary, 1983; Swary 1986). One seminal study in the
topic of the contagion e¤ect that departs from the banking industry, investigates the
e¤ect of bankruptcy announcements on the equity value of the �rm�s competitors (Lang
and Stulz, 1992). The authors �nd that on average the market value of a weighted port-
folio of the common stock of the bankrupt �rm�s competitor�s decreases by 1% at the
time of the bankruptcy announcement and that this decline is statistically signi�cant.
Lang and Stulz (1992) tested the existence of a contagion e¤ect in non-�nancial �rms
at an intra-industry level and later Brewer and Jackson (2002) extended these results at
the inter-industry level working on a database of commercial banks and life insurance
companies. Ferris et al. (1997) demonstrated that large �rm bankruptcies generate a
dominant contagion e¤ect. In their study, competitors experience a signi�cant loss of
0.56% in the three-day window around Chapter 11 announcement. Small �rm bank-
ruptcies also generate a dominant contagion e¤ect among smaller sized competitors.
This research question is closely related with Gande and Lewis (2009) who documented
statistically signi�cant market price e¤ects following a corporate scandal. Looking at
security class actions they use stock price returns, legal environment and the expected
e¤ects of a class action to develop a probabilistic model to predict the initiation of a
SCAS. The corporate �nance-related variables they use in their model are unexpected
earnings and managerial compensation but there is no metric addressing capital struc-
ture phenomena. Yet, it is reasonable to expect that corporate scandal have a di¤erent
impact on stock prices of industry peers of a company involved in a SCAS conditional
on previous capital structure decisions such as leverage and cash �ow level. To test this
intuition we generate the following hypotheses
Hypothesis 7: Ex-post, �rms engaged in a corporate scandal will cause a negativecontagion e¤ect on stock prices within their industry.
Standard corporate �nance show that leverage increases a company�s riskiness and
therefore its stock volatility. Thus, when a scandal is unveiled, stock price reaction by
9
peers should be positive and increasing in leverage due to greater elasticity of equity
value to the total value of the �rms.
Hypothesis 8: The contagion e¤ect on stock prices of peer companies is larger forhighly leveraged industries.
Firms�cash �ows similarity may as well result in a higher response of peers stock
prices. Firms with comparable investment structures generating similar cash �ows are
arguably exposed to the same risk factors (Lang and Stulz, 1992). Since a security
class action suit generally conveys bad news about future cash �ows and the �rm�s risk,
investors will be more likely to reassess the value of peers�equity the higher the degree
of similarity in cash �ows. Measuring similarity as the correlation of returns between
the competitors and the �rm engaged in a corporate scandal, we expect that:
Hypothesis 9: The contagion e¤ect on stock prices of peer companies is larger thehigher the degree of cash �ow similarity of the competitors of the �rm involved in the
corporate scandal.
2 Data and summary statistics
2.1 Data
Previous literature on corporate scandals has adopted earnings restatements, bank-
ruptcy announcement and announcement of frauds in the press as measures of a scan-
dal. In this paper we depart from these approaches and we proxy a corporate scandal
by the the �ling of a security class action suit in the United States, as emerging from
the Stanford Securities Class Action Clearinghouse database. This de�nition of corpo-
rate scandal helps us generalize the results to a broader set of corporate events because
it deals with less severe cases than a �nancial default, as less than 10% of our cases
end up in bankruptcy announcements. By adopting data at the Security Class Action
level we can test whether scandals do a¤ect �rms and their peers behavior condition-
ally and unconditionally on the scandal intensity. Our database includes several types
of corporate scandals such as self-dealing frauds, disclosure failure, misrepresentation
of accounting data, etc. One important concern, as highlighted by Dyck, Morse and
Zingales (2007), is the possible inclusion of cases that were just frivolous allegations; to
deal with this potentially severe sample bias issue we also exclude actions �led before
10
the passing of the Private Securities Litigation Reform Act of 1995 (PSLRA) that was
designed, among others, with the goal of reducing courts�workload on trivial suits.
The original Class Action Suits database has 2,479 cases from January 1996 to
December 2006. We keep only cases �led between January 1996 and December 2005
to allow for the availability of at least two years of �nancial statement data after the
suit �ling. We then dropped highly speci�c SCAS classi�ed as �Analyst related�, �IPO
Allocation�, �Mutual Fund�and �Option Backdating� (thus we only leave �Classic�
SCAS cases)3. The rationale is that these cases are generally related to one isolated
event (listings or managerial compensation) that is less likely to have an impact on
a broader cross-section of security holders. We dropped private holdings, �rms in the
�nancial and utilities sectors (sic codes 6000-6999 and 4900-4999), and cases that didn�t
have Compustat and CRPS information for the period required. The �nal sample
reduces to 793 security class action suit cases. Fifty four percent (432) of the cases
involve accounting allegations, and the remaining 46 percent (361) are classi�ed as
cases involving non-accounting allegations. At the time of data collection, 16 percent
(127) of the cases were still ongoing, while the remaining 84 percent (666) of the cases
were already settled. We matched the �rms from the SCAS database with Compustat
and CRPS using the �rm�s cusip. In the �nal sample of SCAS cases we have 765 cusips,
meaning that several �rms might have more than one security class action suit �ling.
Mean total assets in the �ling year of these �rms were $4,642.62 millions. The sample
contains a total of 204 di¤erent 4-digit sic codes, that we use to generate peer-groups
comparisons. To identify the dispersion of cases by industry we classi�ed each case
according to the Fama & French industry classi�cation (1997): on average we have 21
di¤erent Fama & French industries in each �ling year (see Table I).
INSERT TABLE 1 HERE
Finally, to control that security class action suits are not a proxy of bankruptcy -
3The majority of the cases in the database are classi�ed as Classic. �IPO Allocation cases� arecases �led from 2001 to 2002 alleging that underwriters engaged in undisclosed practices in connectionwith the distribution of certain IPO shares. �Analyst related cases�are cases �led from 2001 to 2004alleging that the brokerage �rm analysts falsely provided favorable coverage for certain issuers. TheseAnalyst cases involve securities directly a¤ected by allegedly false analyst research reports. �MutualFund cases�are cases �led from 2003 to 2004 alleging wrongful acts in the management of the funds.All Mutual Fund cases involve funds alleged to have engaged in market timing practices. When themutual fund parent company is sued only for misstatements or omissions of material information, thecase is classi�ed as Classic rather than Mutual Fund. Classic cases are cases involving 10(b) claims(misstatements or omissions) and/or other common securities law violations.Classic cases are all cases that are not IPO Allocation, Analyst and Mutual Fund cases.
11
more speci�cally of Chapter 11 �lings - we matched our data with LoPucki�s UCLA
Bankruptcy Research Database. We manually merged information from the two data-
bases and observed that on average only 6% of the �rms in our sample �led for chapter
11 in the period 2 years before or after the �ling of the suit. This result allows us
to argue that, since SCAS are not a proxy for bankruptcy, capital structure changes
are not a result of bankruptcy driven corporate restructuring . Table II provides the
distribution of cases included in our sample by event year, type of allegations and by
amount of copanies that eventually �led for Chapter 11 in the two years before or after
the �ling of the security class action suit.
INSERT TABLE 2 HERE
To allow comparisons with the average �nancing behavior industry peers, we con-
struct a measure given by the value-weighted portfolio of �rms not involved in the SCAS
in the event year that are classi�ed with the same 4-digit sic code.
2.2 Variables de�nition
Capital structure variables were collected following Baker & Wurgler (2002). Book
equity is measured as total assets minus total liabilities and preferred stock plus deferred
taxes and convertible debt. Market equity is measured as the number of common shares
outstanding multiplied by the stock price. Book debt is measured as total assets minus
book equity. Book leverage is measured as book debt divided by total assets. Market
leverage is measured as book debt divided by the sum of total assets minus book equity
plus market equity. The amount of total �yearly- security o¤erings is measured as
the sum of debt issuances and book equity issuances. Debt issuances are measured as
the change in total assets minus change in book equity divided by total assets. Book
equity issuances are measured as the change in book equity minus the change in balance
sheet retained earnings, divided by total assets4. Additionally, since debt and equity
issuance are sometimes negative, indicating repurchases or debt and equity voluntary
cancellations,we constructed a dummy variable equal to one when wither equity or debt
issuances are smaller than zero, and zero otherwise.
4Debt and equity issues could also be measured using cash �ow data. We used balance sheet databecause there was more data available, and thus the amount of cases under analysis was greater.
12
3 Corporate scandals and Capital Structure
3.1 Security o¤erings
We conjectured that since fraud detection may a¤ect the availability and cost of future
�nancing, managers have incentives to take advantage of this information asymmetry
with the market to increase the amount of funds they raise. Similarly, we expected a
�rm engaged in a fraudulent behavior -such as lack of disclosure of information and/or
misstatement of accounts- to have greater needs of cash and liquidity, which would
translate in a greater amount of capital raise. Following this intuition, we compared
the weighted average amount of security o¤erings made by the sample of �rms engaged
in a SCAS with the average amount of o¤erings made by their peers (the value-weighted
portfolio of the remaining �rms with the same 4-digit sic code). The comparison was
performed using data for the 6 years window f�2;+3g around the �ling of the SCAS.Results reported in Table 3 o¤er support to our hypotheses.
INSERT TABLE 3 HERE
Ex-ante, �rms engaged in a corporate scandal issue signi�cantly more securities
than their peers. Yet, this issuance pattern is abnormal and disappears after the SCAS
�ling. On average, two years before the event, �rms engaged in a corporate scandal
issue 5.35 times more securities than their peer sample. One year before the �ling,
abnormal security issuance starts decreasing but is still 2.52 times higher than that
of the industry peers. In the event year, i.e. when, the SCAS is �led, the abnormal
issuance is 101% higher than the peer group All di¤erences are statistically signi�cant
at the 1% level on both one and two-tailed tests
Hypothesis 4 predicted that once the information gap with the market that allowed
abnormal security issuance is eliminated, the issuance pattern should revert towards
the market mean. Results reported in table 3 con�rm this intuition: On the three
years after the SCAS �lings, sued �rms decrease considerably their security o¤erings
and their issuance pattern is not statisticaly di¤erent from that of their peers. In fact
there is a mild evidence, although insigni�cant, that issuances are less than the industry
average. This result is not surprising and can be interpreted as an overshooting e¤ect:
market reacts sharply to the SCAS and prices drop below their "fair" value reducing
the chances for capital raising.
13
3.2 Financial mix: Equity and Debt o¤erings
The previous analysis showed that there is robust evidence of greater security issuance
before a scandal erupts, which supports the idea that �rms and managers exploited a
temporary overpricing due to undisclosed information. Yet, this information gap should
e¤ect more havily equity than debt. According to the Market Timing Hypothesis, �rms
with higher current stock prices -relative to their past stock prices, book values or
earnings- are more likely to issue equity rather than debt and repurchase debt rather
than equity (Hovakimian, Opler and Titman, 2001). In this light we argue that the
retained information allows �rms to mantain overvalued stocks, leading to higher equity
issuances. Accordingly, we expect these �rms to show smaller evidence of a di¤erential
issuance of public debt.
INSERT TABLE 4 HERE
Results reported in Table IV con�rm our predictions. Ex-ante SCAS �rms issue
far more equity than their comparable weighted average portfolio of peers, and the
di¤erence is statistically signi�cant for all dates. Two years before the event, �rms
engaged in a corporate scandal issue 7.7 times more equity than their peer sample.
Similarly to results observed for the security issuances test, this pattern is decreasing in
time although signi�cance is consistently high at the 1% level. In particular, one year
before the event the event (t = �1) SCAS �rms issued 4.26 times more than their peers;during the year of the �ling of the security class action, the abnormal equity issuance
drops to 2.39 times than the peers�sample. As predicted, after the event, SCAS �rms
reduce considerably their equity issuances which are never signi�cantly di¤erent from
the industry average.
Debt issuance evidence provides additional support to the hypotheses. Before the
scandal is unveiled, SCAS �rms make a remarkably smaller use of debt as opposed to
equity. Cross-sectionally, debt o¤erings are aligned with those of the industry peers
with the exception of one year before the �ling. Yet, �nancing decisions after the SCAS
�ling change sharply: equity issuances shrink and debt issuances turn negative and
signi�cant for the �rst two years of the event window. At t = 3 , debt issuance is
still negative although not signi�cant. Firms in the peers�sample show a signi�cantly
di¤erent behavior with both debt and equity o¤erings being relatively stable in the two
windows before and after the SCAS �ling. Interestingly , issuance �gures show a strong
14
evidence of discrete, one-time downward changes around the event date. Since �gures
are estimated over event windows distributed over a 10 years time horizon, it is not
likely that this change is correlated with market conditions. Di¤erently, we interpret
this change as a possible consequence of a contagion e¤ect on peers: when a SCAS is
�led, investor may increase their risk estimates that other companies have engaged in
similar practices thus reducing stock prices and incresing debt required yields, which
ultimately result in more costly capital and deferred or reduced capital raising. We
address this issue in section 4.
3.3 Leverage
The previous analyses show remarkable di¤erences in the security issuance patterns of
companies targeted by a SCAS. Yet these �gures may not fully capture the complete
set of �nancing decisions by companies. In fact privately negotiated �nancing like bank
loans are by construction excluded from the data. This source of capital is largely used
in addition to publicly placed securities to shape up companies��nancial structures.
In particular, following hypothesis 3 and previous results, we should expect market
leverage to be not signi�cantly di¤erent or decreasing from that of the industry due to
overpriced equity before the SCAS, and to increase soon therafter due to the strong
adjustment in prices following the SCAS announcement. Similarly, book leverage should
decrease before the �ling as an e¤ect of incremental equity increase and rise in the
following years as evidence of a greater use of non-public debt by the company due to
too costly or closed market conditions.
We tested these intuitions by analyzing the market and book leverage �gures for
companies sued by security-holders and the control peers�group.around the event date.
Results reported in Table 5 con�rm these predictions.
INSERT TABLE 5 HERE
Firms engaged in SCAS show decreasing levels of book leverage, although di¤erenes
are not signi�cant except for year �2. Di¤erently, book leverage di¤erences increasesigni�cantly from the �ling date. Furthermore, this result is fully generated by SCAS
�rms�changes since the peer group doesn�t show any signi�cant change in the average
book leverage over the 5 years event window.
Market leverage �gures are not largely di¤erent between the two groups before the
�ling date. Yet, we document a strongly signi�cant increase in market leverage at
15
the event date and for all the following years. Similarly to book leverage, market
leverage �gures for the peer group are constant over time suggesting that di¤erences
are determined by drops in the market value of equity of SCAS �rms.
4 Contagion e¤ect on external �nancing decisions
and stock prices.
4.1 Contagion e¤ect on external �nancing decisions
Lang and Stulz (1995) and Ferris et al (1997) document the existence of signi�cant con-
tagion e¤ects on stock market prices of competitors of �rms �ling for Chapter 11. In a
study focused on the Telecom industry, Akhigbe et al. (2005) show that these e¤ects
are signi�cant the higher the degree of similarity in size and cash �ows of the competi-
tors. These results support the idea that existing stakeholders react to the bankruptcy
�ling news since it reveals adverse information about asset values, practices and future
prospects of the industry as a whole While, price reactions to a bankruptcy �ling are
not surprisingly associated with large price drops, reactions to SCAS initiation on stock
prices of �ling companies and their peers may be less intuitive since less than 7% of the
SCAS eventually evolve in a bankruptcy �ling. Romano (1991) and Francis, Philbrick,
and Schipper (1994) documented negative stock price reactions upon the initiation of
a security lawsuit using two small sets of cases. Gande and Lewis (2009) provide a
�rst comprehensive analysis of the e¤ect on stock prices upon the �ling of a SCAS. On
average, stock market prices drop by more than 14% in the [-10;+1] window around the
�ling. Additionally, they provide preliminary evidence that stock market prices exhibit
contagion e¤ects similar to those observed by Lang and Stulz (1995) and Ferris et al
(1997). If market prices react to a peer�s bankruptcy �ling and a SCAS, arguably equity
and debt �nancing should become relatively more costly changing the external �nanc-
ing opportunity cost. Companies in fact continuously manage their capital structure by
issuing or buying back equity, raising and repaying debt conditional to market condi-
tions. Surprisingly though, to the best of our knowledge, there is no previous study on
contagion e¤ect on capital structure decisions of companies following a bankruptcy or
corporate scandal. Contagion in security issuances would thus be a reaction of investors
to readjustments in their risk evaluation of the overall industry which imposes greater
costs of �nancing.
16
In this section we provide novel evidence on this phenomen by exploring external
�nancing decisions by competitors of �rms involved in a security class-action lawsuit.
Following hypothesis 5, we model a trend variable T aimed at capturing the evolution
of external capital rasing by the aggregate of competitors in the same industry. The
values of the trend variable range from f1; 6g and are linked to the event years so thatT is equal to one when the event year is �2, T takes a value of two when the event year
is �1 and so forth.
To explore these trends in security o¤erings we performed the following cross-
sectional random-e¤ects regression:
Yit = �i + �i(T ) + "it (1)
where, Yit is the dependent variable capturing the aggregate i� th industry equity,debt or total security o¤erings, T is the trend variable, and eit is the error term of the
regression. Regression results are robust to exogenous factors like market momentum,
business cycles and sentiment since we are working with event years and not calendar
years. Business cycles, market trends, sentiment and other variables should not a¤ect
interpretation of our results. Additional robustness tests are presented in Section 5.
Figure 1 and Table 8 show regression results for SCAS �rms and their peers Our
results support the intuitions in hypothesis 5 as overall issuances decrease at an in-
creasing rate for both subsample over time. The trend coe¢ cient for both subsamples
is negative, statistically signi�cant and, not surprisingly, greater for the SCAS subsam-
ple. Intercept are large and positive, indicating a positive net security issuance over
time. Regression signi�cance as captured by Wald statistic�s �2 is robustly signi�cant
at the 1% level.:
INSERT FIGURE 1 HERE
Previous results on security issuance by SCAS �rms suggested the existence of a
di¤erent e¤ect on debt and equity deals. Following this evidence and the prediction in
Hypothesis 6 we break down the security issuance trend analysis by type of security. As
reported in Figure 2 and Table 8, we �nd that equity issuances decrease for both peers
and SCAS �rms. The trend coe¢ cient of the troubled �rms is over 13 time larger than
the one of their peers. Still, peers experience a negative, strongly signi�cant coe¢ cient
which indicates a contraction in capital raising in public markets. Results for debt
17
issuance are somwhat di¤erent. Not surprisingly, regression esitimates for SCAS �rms
are not signi�cant. This result can be explained recalling the evidence on debt issuance
and book leverage of SCAS �rms which showed a strong decrease in debt issuance
after the �ling followed at t = +2 by a recovery. On the other hand, results for the
peers group are strongly signi�cant with a negative coe¢ cient for the Trend variable
which indicates that a Security Class Action lawsuit on one competitor a¤ects the debt
capacity of the entire industry. In summary, we �nd that in the vicinity of the event
there is a decrease of both debt and equity issuances for both samples.
INSERT FIGURE 2 HERE
INSERT TABLE 6 HERE
Contagion e¤ect and cash �ow similarity
Hypothesis 6 argued that if a contagion on capital structure decisions exists, it should
be larger the closer the similarity of companies�cash �ows. To test this hypothesis we
model similarity as the correlation of returns between the industry portfolio and the
�rms engaged in the corporate scandal for the year preceding the �le of the class action
suit We then de�ne a dummy variable equal to one if the correlation of returns between
the industry portfolio and the �rms engaged in the corporate scandal for the year
preceding the �le of the class action suit falls within the 51st and 100th percentile (High
correlation), and zero otherwise (low correlation).Table 9 presents results for the peers
group sorted by the degree of cash-�ows correlation with the relevant SCAS company.
Results are statistically strong and signi�cant at all levels and indicate that security
issuance opportunities are positively a¤ected by corporate events in the industry the
higher the degree of cash �ows similarity between the sued company and its peers. This
result is twice as strong for equity rather than debt suggesting that shareholders react
signi�cantly, reducing �nancing opportunities or increasing their cost for any company
in the same industry niche. .
INSERT TABLE 7 HERE
4.1.1 Negative issuance
Previous results have shown that both SCAS �rms and their peers have a lower level of
security issuance after the security class action �ling. Interestingly, this phenomenon
generates also cases of "negative issuance". Negative debt issuance can be often the
18
simple repayment of outstanding debt without any rollover. In such a case, assuming
that companies have a fairly stable short term �nancial structure, the negative issuance
pattern should be rather stable over the event window. Yet, if some extraordinary event
occurs, a¤ecting the company current and expected cash-�ows an abnormal negative
issuance pattern would be a signal of a debt restructuring process involving some degree
of debt cutting. Negative equity interpretation is less intuitive since book equity is a
permanent liability in a company�s balance sheet.
In table 8 we report �gures for a simple discrete analysis of the number of �rms for
which debt and equity issuances �gures were less or equal to zero during the [-2,+3]
years surrounding the event.
INSERT TABLE 8 HERE
Results show that after the �ling SCAS �rms retire and/or repurchase about 88%
more equity and 74% more debt. In the SCAS subsample, negative debt issuance may
be the result of debt repayment and cancellation due to restructuring taking place after
the suit has been �led. Agrawal and Cooper (2007) show in fact that immediately after
the scandal, most of the company change their top management and initiate profound
restructuring processes encompassing also debt renegotiation. This same interpretation
may apply to the equity �gures: most of the restructuring plans imply that large
dilutions for existing shareholders which result in negative changes in book equity and
retained earnings.
Surprisingly though, also company�s in the peer group show an increasing amount
of negative issuances. The di¤erences are strong and signi�cant both across samples
and time. This could also be interpreted as a contagion e¤ect, meaning that the �ling
of a SCAS in the industry decreased the opportunities for security o¤erings of its peers
around the event.
4.2 Contagion e¤ect on stock prices
Previous results build on the argument that corporate scandals convey information
about a �rm�s cash �ows, accounting or management practices that investors may con-
sider more an industry-wide phenomenon rather than a company-speci�c, isolated event.
This inference generate a negative e¤ect on stock prices of both SCAS �rms and their
peers. First evidence of this e¤ect and the spillovers on competitors has been provided
by Gande and Lewis (2009). Yet, in their study there is no evidence of any di¤erential
19
e¤ect on stock prices conditional on capital structure and �nancial characteristics of
the industry which may arguably impact on the magnitude of investors�response to
scandals at the intra-industry level. In this section we begin by testing general conta-
gion e¤ects on stock prices following a SCAS announcement and control for correlation
of returns, leverage and type of allegation. Adopting an event study methodology, we
examine abnormal returns on a a set of short-term windows (2-day, 3-days, 5-days,
11-days, 31-days and 41 days bracketing the event). We choose to restrict our study to
short-term windows as working with longer horizon could introduce noise in our results.
The speci�c bracketings are constructed to capture quasi-instantaneous and anticipated
or delayed stock price reactions to the �ling announcement.
Following MacKinley (1997) and Khotari and Warner (2006) we estimate a standard
market model for every company sued in a security class action i 2 I where I is the setof SCAS �rms through the following equation:
Rit = �i + �iRmt + "it (2)
where Rit is the predicted normal rate of return of the security i at time � , Rmt is the
value-weighted return of the S&P500 index, �iand �iare the parameters to be estimated,
and "itis the error term of the regression. The distributions of stock returns were
assumed to be jointly multivariate normal and independently and identically distributed
over time, thus E("it) = 0 and var("it) = �2"i. Equation (2) is estimated with daily
observations over the period (� � 250; � � 50) preceding the �ling of the class action suitat � = 0. Using the market model estimated parameters, we compute daily abnormal
returns for both �rms being sued and their peers. The daily abnormal return of a
security is computed by subtracting the predicted normal return from the actual return
for each day in the event window. LettingdARi� be the abnormal returns for �rm i at
time � the sample abnormal return is:
dARi� = Ri� � (�̂i + �̂iRm� ) (3)
wheredARi� is the abnormal rate of return of the security i in the event window, Ritis the actual rate of return of the security i in the event window, and (�̂i+ �̂iRm� ) is the
expected normal rate of return of the security i in the event window calculated using the
market model. The aggregation of abnormal returns is bi-dimensional: through time
and across securities and follows this process. We �rst compute the average abnormal
returns for all i as:
20
AR� =1
I
IXi=1
dARi� (4)
For any security i, we then compute the cumulative abnormal return from � 1to � 2as the sum of the abnormal returns within that event window:
[CARi(� 1; � 2) =�2X�=�1
dARi� (5)
The average abnormal returns, across the I SCAS companies, are aggregated over
the event window as follows:
CAR(� 1; � 2) =
�2X�=�1
AR� (6)
Finally, we tested whether the cumulative abnormal returns were statistically dif-
ferent from zero using:
�1 =CAR(� 1; � 2)
var(CAR(� 1; � 2))1=2� N(0; 1) (7)
This distributional result is asymptotic with respect to the number of securities N
and the length of the estimation window (200 days in this study).
We follow the same procedure for calculating AR and CAR for the 4-digit SIC code
peer group of the sued company, excluding the latter from the estimations.
4.2.1 Event study results
Our results show that �rms engaged in a security class action suit su¤er a negative
�and somewhat signi�cant- cumulative abnormal return of -.0168 in the [-10,+10] event
window. In the [-1, 0] and [-5,+5] event windows we obtain a -.0027 and -.0093 CAR
respectively but with no statistical signi�cance. When comparing our results with
those of previous literature,5 ours seem to be much milder and less signi�cant for the
corporate scandal �rms. The di¤erence in our results could be explained by the fact
5Lang and Stulz (1992) obtain a -.2166 and a -.2825 CAR in the [-1,0] and [-5,+5] event windowsrespectively.Ferris et al. (1997) obtain a -.1755 and a -.2680 CAR in the [-1, 0] and [-5,+5] event windowsrespectively.
21
that security class action suits are not a proxy for chapter 11, and that the other two
papers mentioned here are related to bankruptcy announcements. Thus, while our
results of negative stock price reaction to corporate scandals are not as strong as those
presented in previous somewhat related literature, this is to be expected just by the
de�nition of what is a corporate scandal (bankruptcy announcements are more prone
to stock price declines because �rms have greater probabilities to close operations and
thus their equity value sharply declines).
When evaluating the stock price contagion generated by corporate scandals, our
results show a negative �and statistically signi�cant- cumulative abnormal return of
-.20% (p value=0.057) and of -.65% (p-value=0.049) in the [-1,0] and [-5,5] event win-
dows respectively. These results allow us to test our hypothesis that �rms engaged in
corporate scandals do a¤ect their industry in terms of stock returns. The engagement of
a participant of the industry in a security class action suit negatively a¤ects the returns
of its peers. Although we are not studying bankruptcy announcements, our results are
also consistent with those of Ferris at al. in windows [-1,0] and [-5,+5] (-.23% and -.06%
respectively). At the same time, for the event window [-5,5] our results are bigger in
term of the contagion e¤ect, meaning that in this window a security class action suit
a¤ect more the industry than a bankruptcy announcement of a large �rm.
Overall, our results indicate that SCAS �rms su¤er a negative stock price decline
in a wider event window than their peers do, which could be interpreted as a type of
anticipation e¤ect of the scandal. Peers seem to be a¤ected in a smaller window (nearer
the event). This could mean that investors do not anticipate the consequences of the
SCAS �ling in the industry, or just that there is a lag in the incorporation of the data
at the industry level. Table 9 shows the results of the event study in the di¤erent event
windows.
INSERT TABLE 9 HERE
Interaction e¤ect with industry characteristics
The degree of similarity among the �rms�cash �ows (measured as the correlation of
returns between the industry portfolio and the �rms engaged in the corporate scandal
for the year preceding the �le of the class action suit) should intensify the extent of the
contagion e¤ect. This intensi�cation of the contagion e¤ect is due to the fact that highly
similar �rms are likely to have investments with similar cash �ow characteristics and
similar risk exposures. We hypothesized that ceteris paribus, the �negative- contagion
22
e¤ect on stock prices is greater for industries in which competitors have similar cash
�ows to those of the �rm involved in the corporate scandal. To test our hypothesis
we constructed a dummy variable for returns correlation as in the previous section (to
split the sample among �rms that had high and low correlation of returns with their
industry). Our results indicate this control variable do intensify the contagion e¤ect
on stock returns. We �nd that �rms with high correlation of stock returns generate a
negative �and statistically signi�cant- contagion e¤ect of -1.03% (p value=0.035) in the
[-5,5] event windows. In the overall sample the contagion e¤ect for the same window was
only -0.65% (p value=0.049). As Table 10 depicts, we do not �nd any other signi�cant
changes in the remaining event windows.
INSERT TABLE 10 HERE
Furthermore, we also stated that if the corporate scandal conveys negative infor-
mation about the industry, it is expected that the percentage fall in equity of the
�rm�s competitors increase with their leverage. We expected that ceteris paribus, the
�negative- contagion e¤ect on stock prices is greater for highly leveraged industries. To
test our hypothesis we created a dummy variable equal to one if the industry leverage
mean was within the 51th and 100th percentile of the sample in the year of the �ling
(for both book and market leverage). For us, a dummy equal to one meant that the �rm
was in a highly leveraged industry. We then replicated the contagion e¤ect analysis as
with the �rst control.
Our results indicate that high book leverage has a considerable e¤ect on the [-5,5]
and [-10,10] windows for SCAS stock price reaction. In the overall sample, the stock
price reaction of troubled �rms was of 0.93% and �1.68% (and not signi�cant) on the
[-5,5] and [-10,10] event windows respectively. Instead, studying only highly leveraged
industries, we �nd a statistically signi�cant stock price reaction of -3.04% and �4.50% on
the [-5,5] and [-10,10] event windows respectively. The contagion e¤ect in this analysis
results not signi�cant. Thus, by splitting the sample according to leverage (high and
low) we loose the signi�cance of the contagion e¤ect on stock price. Table 11 shows
the results of the contagion e¤ect for the high and low leverage samples in two event
windows.
INSERT TABLE 11 HERE
23
Accounting vs. non-accounting allegations
Given that the SCAS database provided us with the classi�cation of each �ling into
accounting and non-accounting allegations we divided the sample and explored if the
stock return decline and the contagion e¤ect in these two subsamples were di¤erent. We
expected both phenomenon (stock return decline and contagion e¤ect) to remain con-
stant but to our surprise this was not the case. We found that the negative stock return
reaction of �rms engaged in a security class action suit with non-accounting allegations
is strongly signi�cant for the [-15,+15] and [-20,+20] event windows (-3.65% and -3.69%
respectively). At the same time, non-accounting SCAS generate a statistically signif-
icant -1.09% contagion e¤ect in the [-5,+5] window. Again we see that the contagion
e¤ect exists in the days near the �ling, while the decrease in returns of the SCAS �rms
are visible in wider windows. When studying the contagion e¤ect of this subsample the
results are stronger and more signi�cant than those obtained with the combined sample.
We also found that SCAS with accounting allegations do not su¤er �statistically signi�cant-
stock price reactions and that they do not generate a statistically signi�cant contagion
e¤ect in their industry. This result is surprising because one would expect any type of
SCAS �ling to at least generate a negative return after the scandal is unveiled.
To justify the existence of the contagion e¤ect uniquely in the non-accounting allega-
tions subsample, it is possible to argue that these type of allegations have an unknown
outcome (predicting what will happen after the lawsuit is di¢ cult for investors), while
the accounting allegations are easily interpreted and investors can foresee what will
happen after the suit. Table 12 depicts the results obtained in each subsample.
INSERT TABLE 12 HERE
5 Robustness tests
To test the validity of our results we performed a series of robustness checks. We split
our original database according to di¤erent criteria and then replicate our analyses.
� Type of allegations
We split our sample according to the type of allegation of the security class action
suit. The database had an accounting and non-accounting allegations classi�cation.
24
The results of the analysis of leverage, �nancing pattern and issuing trend of SCAS and
peers remained unchanged.
� Chapter 11 �lings
We matched our database with LoPucki�s Bankruptcy Research Database at UCLA.
We created a dummy variable equal to one if the troubled �rm �led for chapter 11 in
the period 2 years before or after the security class action suit �ling. The results of
the analysis of leverage, �nancing pattern and issuing trend of SCAS and peers remain
unchanged. Overall, �rms that eventually �led for chapter 11 do not di¤er from those
who didn�t.
� Sentiment of the �ling year
Using Baker and Wurgler�s (2006) sentiment index we created a dummy equal to one
if the sentiment of the SCAS �ling year was greater than zero, zero otherwise. Again,
the results of the analysis of leverage, �nancing pattern and issuing trend of SCAS and
peers remain unchanged. The market sentiment of the �ling year doesn�t a¤ect the
results of our analysis.
� Size
To control for size we used two di¤erent measures. First, using total assets, we
created a dummy variable equal to one if the SCAS was within the 51th and 100th
percentile of the SCAS �rm sample (zero otherwise). This �rst measure attempted to
catch a size e¤ect within the SCAS sample. Second, and again using total assets, we
created a dummy variable equal to one if the SCAS was within the 51th and 100th
percentile of its industry (zero otherwise). This second measure attempted to catch a
size e¤ect within the industry. We repeated all the analyses splitting the sample by size
and obtained basically the same results as before.
6 Conclusions
This paper presented the analysis of the ex-ante and ex-post �nancing pattern of �rms
engaged in security class action suits as well as the contagion e¤ect that these scandals
generate in the industry in terms of stock returns and �nancing pattern as well. In the
�rst part of the paper we tested that ex-ante, �rms engaged in a corporate scandal have
25
a greater amount of security o¤erings compared to its industry average. On average, two
years before the event, �rms engaged in a corporate scandal issue 435% more securities
than their peer sample. The year before the event they issue 252% more securities
than their peer sample. And the year were the event happens (the �ling of a SCAS)
the di¤erence of means is 101% more and still statistically signi�cant. In line with
the predictions of the market timing hypothesis, we tested that ex-ante, �rms engaged
in a corporate scandal made greater use of equity �nancing compared to its industry
average. Two years before the event, �rms engaged in a corporate scandal issue on
average 670% more equity than their peer sample. This di¤erence alone is more than 6
times higher than the average amount of equity o¤erings that their peers�sample issued.
This behavior is persistent in the year preceding the event and in the year of the event
itself. Contrary to what the theory would predict, ex-ante �rms engaged in a corporate
scandal had higher levels of leverage. We �nd book leverage of corporate scandal �rms
to be higher in all the periods (and this di¤erence is statistically signi�cant in all years).
On average, during the �ve periods that we studied, �rms engaged in a SCAS had 1.42
times the book leverage that their peers did. For the market leverage analysis we �nd
the same results. Ex-post, we found that �rms engaged in a security class action suit
�nance themselves in the same manner as the mean of their industry. Ex-post, debt
issuances are lower than equity issuances for both samples, and this e¤ect is even more
pronounced for SCAS �rms. The weighted average peers�sample show a more steady
issuing behavior, and both equity and debt issues decrease but not as sharply as in
the SCAS sample. Ex-post the di¤erence in the means of debt and equity issuances of
SCAS �rms and their peers is not statistically signi�cant, which lead us to conclude
that both means are the same for both samples.
In the second part of the paper we analyzed the existence of a trend in the security
o¤ering pattern that can be interpreted as a contagion e¤ect in the �nancing pattern of
the industry. The results show that surrounding the event, both the corporate scandals
�rms and the weighted average matched sample of competitors have a signi�cant and
decreasing trend in both equity and debt issuances. We conclude that the �ling of a
security class action suit do a¤ect the opportunity that �rms within an industry have
to o¤er securities to the market. We control for returns correlation and �nd that the
more similar the �rm is to its industry, the lower the contagion e¤ect on their issuing
pattern.
Finally we tested the existence of a contagion e¤ect in the industry�s stock returns due
to the �ling of a security class action suit. Our results show a negative �and statistically
26
signi�cant- cumulative abnormal return of -0.20% (p value=0.057) and of -0.65% (p-
value=0.049) in the [-1,0] and [-5,5] event windows respectively. We also �nd that
the contagion e¤ect is mainly generated by �rms engaged in security class action suits
with the non-accounting allegations. SCAS with accounting allegations do not su¤er
�statistically signi�cant- cumulative abnormal returns and that they do not generate a
statistically signi�cant contagion e¤ect in their industry.
27
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30
Table IYearly distribution of events and
Fama & French industriesThis table reports the distribution of security class action suit cases by filingyear, from January 1996 to December 2006. Fama & French industries wereassigned using 4digit sic codes and the classification provided in their paperof 1997.
Filing year (SCAS) N Fama French industries1996 47 191997 66 221998 88 241999 75 222000 87 212001 81 202002 90 252003 63 212004 82 212005 67 242006 47 18Total 793
Table IIAmount of cases studies by event year, type of allegation
chapter 11 filingThis table reports the distribution of security class action suit cases by event year. The event year(t=0) is defined as the year in which the security class action suit was filed against the firm. Thepercentages of cases according to the type of allegation (accounting and nonaccounting), and tothe filing of chapter 11 (2 years after or before the filing) are also presented.
Year (event) NAccountingallegations
Nonaccountingallegations
Filed forChapter 11in t=[2,2]
Didn't file forChapter 11 in
t=[2,2]t=3 735 55.5% 44.5% 8.5% 91.5%t=2 754 55.0% 45.0% 8.8% 91.2%t=1 717 54.3% 45.7% 7.6% 92.4%t=0 627 53.4% 46.6% 5.4% 94.6%t=1 551 53.4% 46.6% 4.4% 95.6%t=2 458 54.8% 45.2% 4.2% 95.8%t=3 366 54.8% 45.2% 4.0% 96.0%
31
Table IIIMean security offerings by event year
This table reports the –weighted mean security offerings of firms engaged in a corporate scandal (proxied bythe filing of a security class action suit), and that of a valueweighted portfolio of the remaining firms with thesame 4digit sic code (by event year). The event year (t=0) is defined as the year in which the security classaction suit was filed against the firm. The amount of total –yearly security offerings is measured as the sum ofdebt issuances and book equity issuances. Debt issuances are measured as the change in total assets minuschange in book equity divided by total assets. Book equity issuances are measured as the change in book equityminus the change in balance sheet retained earnings, divided by total assets. The last two columns of the tablepresent the results of the one and twotailed meandifference tests.
t Variable Obs Mean Mean(diff) Pr(|T|>|t|)(1) Pr(T>t) (2)
2 Security offerings SCAS 629 0.576302 Security offerings PEERS 629 0.10765 0.46865 0.0002 (***) 0.0001 (***)1 Security offerings SCAS 638 0.389631 Security offerings PEERS 638 0.11058 0.27905 0.0000 (***) 0.0000 (***)0 Security offerings SCAS 553 0.184030 Security offerings PEERS 553 0.09158 0.09245 0.0002 (***) 0.0001 (***)1 Security offerings SCAS 483 0.042061 Security offerings PEERS 483 0.07192 0.02986 0.4090 0.79552 Security offerings SCAS 403 0.064282 Security offerings PEERS 403 0.06875 0.00447 0.8840 0.55803 Security offerings SCAS 322 0.074223 Security offerings PEERS 322 0.06732 0.00690 0.9275 0.4637
(1)Ha: mean(diff) ≠ 0(2)Ha: mean(diff) > 0
32
Table IVMean debt and equity issuances by event year
This table reports mean debt and equity issuances of firms engaged in a corporate scandal (proxied bythe filing of a security class action suit), and a valueweighted portfolio of the remaining firms with thesame 4digit sic code (by event year). The event year (t=0) is defined as the year in which the securityclass action suit was filed against the firm. Debt issuances are measured as the change in total assetsminus change in book equity divided by total assets. Book equity issuances are measured as the changein book equity minus the change in balance sheet retained earnings, divided by total assets. The lastthree columns of the table present the results of the one and twotailed meandifference tests.
t Variable Obs MeanMean(diff) Pr(|T|>|t|)(1) Pr(T>t)(2) Pr(T<t)(3)
2 Equity issuances SCAS 629 0.538372 Equity issuances PEERS 629 0.06988 0.46849 0.0180(*) 0.0090 (**) 0.99101 Equity issuances SCAS 638 0.308941 Equity issuances PEERS 638 0.07248 0.23647 0.0000(***) 0.0000(***) 1.00000 Equity issuances SCAS 553 0.147920 Equity issuances PEERS 553 0.06199 0.08593 0.0000(***) 0.0000(***) 1.00001 Equity issuances SCAS 483 0.074331 Equity issuances PEERS 483 0.04548 0.02885 0.2560 0.1280 0.87202 Equity issuances SCAS 403 0.089342 Equity issuances PEERS 403 0.04590 0.04344 0.0886 0.0443 (*) 0.95573 Equity issuances SCAS 322 0.081923 Equity issuances PEERS 322 0.04269 0.03923 0.0911 0.0455 (*) 0.9545
2 Debt issuances SCAS 632 0.037732 Debt issuances PEERS 632 0.039880.00215 0.9901 0.5050 0.49501 Debt issuances SCAS 640 0.081221 Debt issuances PEERS 640 0.03920 0.04202 0.0077(**) 0.0038 (**) 0.99620 Debt issuances SCAS 555 0.036060 Debt issuances PEERS 555 0.03158 0.00448 0.7657 0.3829 0.61711 Debt issuances SCAS 485 0.032591 Debt issuances PEERS 485 0.029340.06193 0.0026(**) 0.9987 0.0013 (***)2 Debt issuances SCAS 406 0.025192 Debt issuances PEERS 406 0.023680.04887 0.0688 0.9656 0.0344 (*)3 Debt issuances SCAS 325 0.010693 Debt issuances PEERS 325 0.024720.03541 0.5677 0.7161 0.2839
(1)Ha: mean(diff) ≠ 0(2)Ha: mean(diff) > 0(3)Ha: mean(diff) < 0
33
Table VMean market and book leverage by event year
This table reports the mean market book leverage of firms engaged in a corporate scandal (proxied by the filing of asecurity class action suit), and for a the valueweighted portfolio of firms with the same 4digit sic code by event year,excluding the SCAS firm. The event year (t=0) is defined as the year in which the security class action suit was filedagainst the firm. Market leverage is measured as book debt divided by the sum of total assets minus book equity plusmarket equity. Book leverage is measured as book debt divided by total assets. The last two columns of the tablepresent the results of the one and twotailed meandifference tests.
PANEL A: MARKET LEVERAGE
t Variable Obs Mean Mean(diff) Pr(|T|>|t|)(1) Pr(T>t)(2)
2 Market leverage SCAS 607 0.236362 Market leverage PEERS 607 0.23316 0.00320 0.7186 0.35931 Market leverage SCAS 633 0.251901 Market leverage PEERS 633 0.23412 0.01778 0.0496 (*) 0.0248 (*)0 Market leverage SCAS 570 0.372130 Market leverage PEERS 570 0.23748 0.13465 0.0000 (***) 0.0000 (***)1 Market leverage SCAS 498 0.381131 Market leverage PEERS 498 0.23873 0.14240 0.0000 (***) 0.0000 (***)2 Market leverage SCAS 417 0.359922 Market leverage PEERS 417 0.23091 0.12901 0.0000 (***) 0.0000 (***)3 Market leverage SCAS 327 0.364733 Market leverage PEERS 327 0.23017 0.13456 0.0000 (***) 0.0000 (***)
PANEL B: BOOK LEVERAGE
t Variable Obs Mean Mean(diff) Pr(|T|>|t|)(1) Pr(T>t)(2)
2 Book leverage SCAS 706 0.653272 Book leverage PEERS 706 0.42999 0.22328 0.0265 (*) 0.0132 (*)1 Book leverage SCAS 660 0.483291 Book leverage PEERS 660 0.42294 0.06035 0.1058 0.0529 (*)0 Book leverage SCAS 572 0.526150 Book leverage PEERS 572 0.42488 0.10127 0.0000 (***) 0.0000 (***)1 Book leverage SCAS 501 0.625561 Book leverage PEERS 501 0.43461 0.19096 0.0068 (**) 0.0034 (**)2 Book leverage SCAS 420 0.581462 Book leverage PEERS 420 0.42081 0.16065 0.0001 (***) 0.0001 (***)3 Book leverage SCAS 330 0.754973 Book leverage PEERS 330 0.41863 0.33634 0.0369 (*) 0.0185 (*)
(1)Ha: mean(diff) ≠ 0(2)Ha: mean(diff) > 0
34
Figure ISecurity offering trend analysis
This graph reports the results of the regression: Yjt=αj+βj(T)+εjt; where, Yjt are totalsecurity issuances, T is a trend variable that ranges from {1,5}, and eit is the errorterm of the regression. The amount of total –yearly security offerings is measured asthe sum of debt issuances and book equity issuances.
0.1
.2.3
.4.5
Xb
4 2 0 2 4t
SCAS PEERS
35
0.1
.2.3
.4X
b
4 2 0 2 4t
Avg Equity issuances SCAS Avg Debt issuances SCASAvg Equity issuances PEERS Avg Debt issuances PEERS
Figure IIEquity and debt issuance trend analysis
This graph reports the results of the regression: Yjt=αj+βj(T)+εjt; where, Yjt are totaleither equity or debt issuances, T is a trend variable that ranges from {1,5}, and eit is theerror term of the regression.
36
Table VISecurity offering trend analysis
This table reports the results of the regression: Yjt=αj+βj(T)+εjt; where, Yjt are eitherequity, debt or total security issuances, T is a trend variable that ranges from {1,6}, and eit
is the error term of the regression. The amount of total –yearly security offerings ismeasured as the sum of debt issuances and book equity issuances. Debt issuances aremeasured as the change in total assets minus change in book equity divided by total assets.Book equity issuances are measured as the change in book equity minus the change inbalance sheet retained earnings, divided by total assets.
Sample: SCAS firms
Dependent variableEquity
issuancesDebt
issuances
Totalsecurityofferings
Intercept 0.509521 (***) 0.082482 0.586441 (***)P>|z| 0 0.313 0
Trend coeff. 0.0783101 (***) 0.018758 0.0927902 (***)P>|z| 0.001 0.392 0
N 721 724 721Wald chisquare 10.67 (***) 0.73 32.05 (***)P>chisquare (0.001) (0.392) (0.000)
Sample: PEERS
Dependent variableEquity
issuancesDebt
issuances
Totalsecurityofferings
Intercept 0.078071 (***) 0.044634 (***) 0.120455 (***)P>|z| 0 0 0
Trend coeff. 0.0057357 (***) 0.0038771 (***) 0.0092945 (***)P>|z| 0 0 0
N 782 782 782Wald chisquare 47.75 (***) 21.96 (***) 57.18 (***)P>chisquare (0.000) (0.000) (0.000)
37
Table VIIContagion effect analysis according to correlation of stock returnsThis table reports the results of the regression: Yjt=αj+βj(T)+εjt; where, Yjt are eitherequity, debt or total security issuances, T is a trend variable that ranges from {1,6},and eit is the error term of the regression. The amount of total –yearly securityofferings is measured as the sum of debt issuances and book equity issuances. Debtissuances are measured as the change in total assets minus change in book equitydivided by total assets. Book equity issuances are measured as the change in bookequity minus the change in balance sheet retained earnings, divided by total assets.The high/low correlation of returns dummy is defined as: 0 if correlations of returns(between SCAS and PEERS in the year preceding the filing) lies within the [150th]percentile and 1 if it lies within the [51100]th percentile in the year before the filing ofthe SCAS.
PEERSCorrelation of returns High LowDependent variable: Total security offeringsIntercept 0.138329 (***) 0.100738 (***)
P>|z| 0.000 0.000Trend 0.0115997 (***) 0.0045924 (***)
P>|z| 0.000 0.000N 197 198Wald chisquare 3746.40 705.71P>chisquare 0.000 0.000
Correlation of returns High LowDependent variable: Equity issuancesIntercept 0.096095 (***) 0.066687 (***)
P>|z| 0.000 0.000Trend 0.0090866 (***) 0.0028100 (***)
P>|z| 0.000 0.000N 197 198Wald chisquare 4397.23 611.42P>chisquare 0.000 0.000
Correlation of returns High LowDependent variable: Debt issuancesIntercept 0.049363 (***) 0.035994 (***)
P>|z| 0.000 0.000Trend 0.0045173 (***) 0.0012588 (***)
P>|z| 0.000 0.000N 197 198Wald chisquare 1533.82 93.26P>chisquare 0.000 0.000
38
Table VIIISecurity offering trend analysis –Discrete analysis
This table reports the results of negative debt and equity issuances in the different event years. Wecounted the amount of cases where debt/equity issuances were less or equal than zero.
Equity issuances (discrete analysis)SCAS PEERS
t Obs Eq_iss<=0 % Eq_iss<=0 Obs Eq_iss<=0 % Eq_iss<=02 629 90 14.31% 754 91 12.1%1 638 95 14.89% 717 103 14.4%0 553 145 26.22% 627 99 15.8%1 483 135 27.95% 551 108 19.6%2 403 105 26.05% 458 97 21.2%3 322 96 29.81% 366 73 19.9%
Debt issuances (discrete analysis)SCAS PEERS
t Obs Debt_iss<=0 % Debt_iss<=0 Obs Debt_iss<=0 % Debt_iss<=02 632 175 27.69% 754 154 20.4%1 640 174 27.19% 717 135 18.8%0 555 211 38.02% 627 153 24.4%1 485 244 50.31% 551 128 23.2%2 406 217 53.45% 458 109 23.8%3 325 159 48.92% 366 92 25.1%
39
Table XContagion effect analysis by event window
This table reports the cumulative abnormal returns of firms engaged in a corporate scandal(proxied by the filing of a security class action suit), and a valueweighted portfolio of theremaining firms with the same 4digit sic code (by event year). The event year (t=0) is definedas the year in which the security class action suit was filed against the firm. The dailyabnormal return of a security is computed by subtracting the predicted normal return(estimated using the market model) from the actual return for each day in the event window.
Day/windowrelative toSCAS filing Reaction of SCAS firms Reaction of PEERS
N AR/CAR t P>|t| N AR/CAR t P>|t|
10 522 0.0006784 0.33 0.741 527 0.000399 0.46 0.6479 522 0.0009623 0.44 0.662 527 0.0001764 0.21 0.838 522 0.0010429 0.42 0.676 527 0.0001714 0.19 0.8487 522 0.0037979 1.78 0.076 527 0.0004275 0.51 0.6126 522 0.0003093 0.14 0.892 527 0.0009647 1.13 0.2595 522 0.0001869 0.07 0.945 527 0.0018305 2.15 0.0324 522 0.0011983 0.62 0.535 527 0.0000035 0 0.9973 522 0.0014929 0.69 0.491 527 0.0008165 0.95 0.3452 522 0.0016338 0.68 0.499 527 0.0012778 1.54 0.1241 522 0.0007261 0.34 0.735 527 0.0023747 3.28 0.001(**)0 522 0.0034582 1.22 0.223 527 0.0002952 0.37 0.7131 522 0.0017424 0.73 0.465 527 0.0001036 0.13 0.8962 522 0.0007818 0.36 0.718 527 0.0006204 0.75 0.4563 522 0.0027343 1.16 0.246 527 0.0018219 2.06 0.04 (*)4 522 0.0036303 1.66 0.098 527 0.0006182 0.66 0.5125 522 0.00227 0.9 0.369 527 0.0016159 1.45 0.1496 521 0.0018141 0.74 0.458 527 0.0015726 1.82 0.077 522 0.0020588 0.75 0.454 527 0.0006809 0.79 0.4328 522 0.0032792 1.45 0.149 527 0.0000998 0.08 0.9349 523 0.0018022 0.73 0.466 527 0.0003127 0.33 0.73810 523 0.0005527 0.29 0.769 527 0.0016415 1.22 0.224
[1,0] 527 0.0027062 0.81 0.42 527 0.0020795 1.91 0.057(*)[0,+1] 527 0.0051513 1.68 0.094 527 0.0001916 0.18 0.861[1,+1] 527 0.004432 1.21 0.225 527 0.0021831 1.67 0.095[5,+5] 527 0.0093642 1.28 0.202 527 0.0065921 1.98 0.049(*)
[10,+10] 527 0.0168449 1.72 0.086 527 0.0023214 0.48 0.632
40
Table XIContagion effect analysis according to correlation of stock returns
This table reports the cumulative abnormal returns of firms engaged in a corporate scandal(proxied by the filing of a security class action suit), and a valueweighted portfolio of theremaining firms with the same 4digit sic code (by event year). The event year (t=0) isdefined as the year in which the security class action suit was filed against the firm. The dailyabnormal return of a security is computed by subtracting the predicted normal return(estimated using the market model) from the actual return for each day in the event window.The high/low correlation of returns dummy is defined as: 0 if correlations of returns (betweenSCAS and PEERS in the year preceding the filing) lies within the [150th] percentile and 1 ifit lies within the [51100]th percentile in the year before the filing of the SCAS.
Sample A: HIGH correlation of returns
Day/windowrelative toSCAS filing Reaction of SCAS firms Reaction of PEERS
N AR/CAR t pvalue N AR/CAR t pvalue
[1,0] 264 0.0004374 0.11 0.916 264 0.001454 0.82 0.41[0,+1] 264 0.0019944 0.55 0.586 264 0.001227 0.72 0.472[1,+1] 264 0.0023665 0.51 0.612 264 0.0024984 1.19 0.234[5,+5] 264 0.0178436 1.85 0.065 264 0.0103162 2.12 0.035(*)
[10,+10] 264 0.0222732 1.92 0.056(*) 264 0.0024595 0.38 0.707
Sample B: LOW correlation of returns
Day/windowrelative toSCAS filing
Reaction of SCAS firms LOW correlation of returns
Reaction of PEERS LOWcorrelation of returns
N AR/CAR t pvalue N AR/CAR t pvalue
[1,0] 263 0.0049835 0.94 0.348 263 0.0027074 2.11 0.036[0,+1] 263 0.0083201 1.69 0.093 263 0.0016156 1.18 0.237[1,+1] 263 0.0065054 1.16 0.249 263 0.0018666 1.2 0.232[5,+5] 263 0.0008525 0.08 0.939 263 0.0028539 0.63 0.532
[10,+10] 263 0.011396 0.72 0.472 263 0.0021829 0.31 0.76
41
Table XIIContagion effect according to leverage
This table reports the cumulative abnormal returns of firms engaged in a corporatescandal (proxied by the filing of a security class action suit or a bankruptcyannouncement), and a valueweighted portfolio of the remaining firms with the same 4digit sic code. The sample is divided using a dummy variable equal to one if the SCASfirm was within the 51100 percentile of book leverage. Results of the market leverageanalysis are not presented but remain unchanged.
Day/windowrelative toSCAS filing
Reaction of SCAS firms HIGH leverage
Reaction of PEERS HIGHLeverage
N CAR t P>|t| N CAR t P>|t|
[1,0] 183 0.0002762 0.04 0.965 183 0.0012991 0.67 0.503[0,+1] 183 0.0014779 0.27 0.786 183 0.0005994 0.33 0.74[1,+1] 183 0.0028338 0.45 0.65 183 0.0018701 0.85 0.399[5,+5] 183 0.0304444 2.21 0.028(*) 183 0.0082169 1.53 0.128
[10,+10] 183 0.0450035 2.5 0.013(*) 183 0.0079747 1 0.319Day/windowrelative toSCAS filing
Reaction of SCAS firms LOWleverage
Reaction of PEERS LOWLeverage
N CAR t P>|t| N CAR t P>|t|
[1,0] 184 0.005416 0.97 0.336 184 0.0024428 1.63 0.105[0,+1] 184 0.0081828 1.67 0.096 184 0.0007883 0.47 0.639[1,+1] 184 0.0126792 2.05 0.042(*) 184 0.0015167 0.81 0.418[5,+5] 184 0.0119834 1.06 0.288 184 0.0042263 0.82 0.413
[10,+10] 184 0.0013997 0.09 0.925 184 0.0084321 1.05 0.293
42
Table XIIICumulative abnormal returns and contagion
effect by type of allegationThis table reports the cumulative abnormal returns of firms engaged in a corporatescandal (proxied by the filing of a security class action suit), and a valueweightedportfolio of the remaining firms with the same 4digit sic code. The results are dividedin two subsamples according to the type of allegations related to the security classaction suit (accounting and nonaccounting).
Accounting allegations
Reaction of SCAS stock Reaction of peers' stock
Event window N CAR t P>|t| N CAR t P>|t|
[1,0] 262 0.0071 1.27 0.207 262 0 1.19 0.234
[0,+1] 262 0.0074 1.53 0.126 262 0 0.2 0.845
[1,+1] 262 0.008 1.43 0.153 262 0 1.41 0.160
[2,+2] 262 0.0039 0.49 0.623 262 0 0.06 0.951
[5,+5] 262 0.0064 0.57 0.569 262 0 0.41 0.684
[10,+10] 261 0.0088 0.62 0.535 261 0 0.71 0.476
[15,+15] 261 0.0008 0.04 0.964 261 0 0.4 0.692[20,+20] 260 0.0031 0.16 0.872 260 0 0.1 0.916
NonAccounting allegations
Reaction of SCAS stock Reaction of peers' stock
Event window N CAR t P>|t| N CAR t P>|t|
[1,0] 268 0.0011 0.3 0.768 268 0 1.36 0.176
[0,+1] 267 0.0021 0.54 0.593 267 0 0.31 0.759
[1,+1] 267 0.0012 0.26 0.798 267 0 0.99 0.324
[2,+2] 267 0.0014 0.21 0.834 267 0 1.42 0.158
[5,+5] 266 0.012 1.25 0.211 266 0 2.51 0.013(*)
[10,+10] 266 0.0247 1.83 0.068 266 0 1.29 0.200[15,+15] 266 0.0365 2.26 0.025(*) 266 0 1.61 0.108[20,+20] 266 0.0369 1.92 0.057(*) 266 0 1.04 0.299
43