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Directors’ and Officers’ Liability Insurance, Corporate Risk and Risk Taking:
New Panel Data Evidence on the Role of Directors’ and Officers’ Liability Insurance*
By M. Martin Boyer HEC Montréal, Université de Montréal
and
Sharon Tennyson Cornell University
First Draft July 2008
Current Draft December 2011
Abstract. In this paper, we develop and estimate models of the determinants of firms’ demand
for directors’ and officers’ liability insurance. We add to and validate the existing empirical
literature by testing hypotheses regarding the relationship between D&O insurance purchase
and firm size, governance characteristics and business risk. Our data set allows us to test both
purchase decisions and limits choices. We present separate estimates of these decisions along
with estimates that allow for their joint determination and recognize the potential for selection
bias in the estimates of coverage limits models. To shed additional light on the role and
consequences of D&O insurance we make additional use of the panel structure of our data to
examine the effects of D&O insurance purchase on corporate governance.
* Comments and suggestions are welcomed. Please do not distribute, cite or quote without the
authors’ permission. Copyright © 2008 and 2011 by M. Martin Boyer and Sharon Tennyson.
1
Directors’ and Officers’ Liability Insurance, Corporate Risk and Risk Taking: New Panel
Data Evidence on the Role of Directors’ and Officers’ Liability Insurance
1. Introduction
Members of the boards of directors of publicly traded corporations in many countries around the
world face personal liability for breach of the duties of care and loyalty to the company’s
shareholders (Romano, 1991). Imposing liability is thought to aid in aligning managers’
incentives with the interests of shareholders, by providing shareholders with a mechanism for
recouping losses brought about by director malfeasance. Permitting shareholder suits is also a
means to deal with the classic agency problem, acting as a disciplinary force on managers and
directors (see Becht et al, 2003, and Bauer et al, 2008).1
The latest Towers-Watson (2011) survey finds that 29% of public companies reported having a
D&O claim in the previous 10 years; with two-thirds of public companies reporting at least one
direct shareholder or investor lawsuit (the same for derivative lawsuits). Surveys of U.S. and
Canadian firms find that the most common reasons for D&O suits brought against public
companies are inadequate or inaccurate disclosure (42%), stock or other public offerings (20%)
and general breach of fiduciary duty (13%); and that the majority of suits (53%) are brought by
shareholders (Towers-Watson, 2007). This pattern has remained relatively stable over the last
decade. For example, the 2002 edition of the same survey of D&O trends (Towers-Watson,
2002) highlights that 46% of complaints arose from disclosure related issues or stock offerings.
Shareholders remained the largest source of complaints against public companies (58%) in that
year.2
One puzzle is that the strength of this shareholder liability threat is often mitigated by the
corporation’s purchase of directors’ and officers’ liability insurance (D&O insurance hereafter) on
1 For example, DuCharme et al. (2004) argue that discovered false earning signals have important
reputational consequences that result in a higher difficulty of raising capital in the future. The threat of a shareholder suit may reduce earnings restatements and thus increase the value of the firm. McTier and Wald (2011) present an alternative view that shareholder suits arise from “legal rent-seeking” by opportunistic plaintiffs' attorneys who sue firms that experience large stock price drops in order to expropriate a settlement from the firm's D&O insurance policies (see also Beck and Bhagat, 1997). 2 Prior to 1996, mergers and acquisitions activity was the greatest source of shareholder complaints
against public companies, representing as much as 40% of all complaints against public companies in 1990 (Towers-Watson, 2002).
2
the board’s behalf.3 D&O insurance provides indemnity for damages and legal fees awarded to
claimants who bring suits for losses stemming from negligent actions on the part of directors
and officers.4 D&O insurance policies exclude losses arising from deliberate fraud or dishonesty,
however (Ross et al, 2000). As such, D&O insurance provides coverage to a company’s officers
and directors against risks arising from day-to-day management. Thus, on the one hand
corporate owners threaten directors with liability but on the other hand they provide insurance to
indemnify them for court costs and judgments.
The purchase of D&O insurance raises the obvious concern that lowering directors’ liability risk
will increase agency problems within the firm, and will decrease board effectiveness (see
Barrese and Scordis, 2007, and Bradley and Chen, 2011).5 Under this point of view D&O
insurance may lead to inefficiencies and is more likely to be purchased by entrenched
management. Others theories suggest that purchase of D&O insurance enhances board
efficiency. For example, liability exposure may induce managers to be overly conservative and
may cause them to forego risky positive-NPV projects (an under-investment problem). D&O
3 It used to be that D&O insurance was only available to organizations incorporated in common law
countries such as England, Canada, the United States, and Australia. The globalization of markets seems to have generated a demand for protection by corporate directors in civil law countries. This is a relatively new turn of events. Gutiérrez (2003) reported that D&O insurance was rarely used in continental Europe because it reduces director accountability; she wrote that D&O insurance was “forbidden in Germany, where the legislature considers that its use would both reduce the levels of diligence of directors and increase the compensatory demands of plaintiffs” (p.517). However, the German Corporate Governance Code of 2002 now allows directors to have such insurance (see Werder et al, 2005, and Talaulicar and Werder, 2008). Recently, LaCroix (2009) posted the following: “Most large European companies carry some amount of D&O insurance, although the perceived level of D&O insurance coverage need varies among countries. Many small to mid-sized European public companies do not purchase D&O insurance at all” In Japan, the usefulness of D&O insurance is limited because the concept of punitive damages is regarded as incompatible with the public order. In France, the action sociale limits the scope of derivative lawsuits. D&O insurance protection is now the norm for directors in Taiwan (see Chen and Li, 2010). Interestingly, Towers-Watson (2011) reports that 47 percent of for-profit organizations with international operations purchased a local D&O policy in a foreign jurisdiction in 2010. Two years before, only 2 percent of respondents with international operations had purchased a local policy in a foreign jurisdiction. 4 D&O insurance policies offer three different types of coverage, which are called “sides” in the insurance
business (Gustafson, 2006). “Side A” (or, individual) coverage ensures direct reimbursement for directors and officers when a company is unable (for legal reasons or because of bankruptcy) or does not wish to reimburse them. “Side B” (or, corporate) coverage is the most common type of D&O coverage, and ensures that a company will be reimbursed for any amounts paid to claimants on behalf of the directors and officers. The third form of coverage is “Side C” (or, entity) which provides for direct reimbursement of costs that the company itself may incur from D&O related suits. Most D&O insurance policies consist of a mix of all three types of coverage (Towers-Watson, 2011). 5 D&O insurance policies are not the only means of protection available to directors and officers. There
are several other contracts that ensure peace of mind to directors and officers in their day-to-day decision-making. For example, in Canada and in most U.S. states corporations are allowed to indemnify directors for legal expenses associated with lawsuits in which they are not found negligent; in these cases D&O insurance may increase moral hazard by increasing directors’ certainty of being indemnified and increases the extent of indemnification offered (Romano, 1991, 2006).
3
insurance may also help to attract higher quality risk-averse outside directors (Priest, 1987). It
has also been suggested that D&O insurance may substitute for direct shareholder monitoring
by relying on the insurer’s screening mechanisms (Holderness, 1990).6 These arguments
suggest that D&O insurance will benefit shareholders by encouraging optimal risk taking, and
that D&O insurance is part of an efficient contract between shareholders and directors.
Although theoretical discussions of the demand for and the effects of D&O insurance have
developed significantly, relatively fewer empirical studies have been conducted. This is likely
due to the fact that data on D&O insurance purchases are not readily available. Beginning in
the 1990s several countries including England and Canada require publicly traded companies to
report D&O insurance purchases to shareholders; but obtaining this information often entails
hand-collection of data from annual reports (Core, 1997, 2000, Park-Wynn, 2008; O’Sullivan,
1997, 2002). Other research has taken advantage of voluntary D&O insurance disclosures
(Bhagat et al, 1987), proprietary data from insurance brokers (Holderness, 1990; Chalmers et
al, 2002; Kaltchev, 2004; Kim, 2005), or survey data from Tillinghast Towers-Perrin or Towers-
Watson (Cao and Narayanamoothy, 2010).7 One consequence of the difficulties of obtaining
data is that the sample sizes used in empirical work have been small, and are generally
confined to a cross-section of firms.8
To allow for a more rigorous empirical testing of the different theories we construct a unique
panel dataset of firm level data. Our original sample consists of data from over 200 publicly
traded Canadian corporations listed on the Toronto Stock Exchange (excluding financial and
mining firms). The sample period covers the years 1996 through 2005 and includes firms from
seven sectors of the economy. We include in our sample both newly listed firms and firms that
disappear from the data during the period, to avoid problems of survivor bias. A key advantage
6 A related idea is that D&O insurance enhances efficiency by providing a commitment device to induce
shareholders to sue negligent directors (Bhagat et alii, 1987; Sarath, 1991; Gutierrez, 2003; Chang and Yeh, 2011). Gutierrez (2003) develops a formal theoretical model of this view which is based on the assumptions that director negligence is unobservable, that potential shareholder losses are greater than directors’ wealth, and that lawsuits are costly for shareholders. In these circumstances the model shows that D&O insurance can serve to commit shareholders to bring costly litigation against directors in the event of losses or disappointing returns (see also Boyer, 2005, and Kremslehner, 2011, for similar arguments). 7 The 2010 Directors and Officers (D&O) Liability survey is the 32
nd in a series that was initiated by Wyatt
in 1992 (previously it was titled Health care organization directors and officers liability survey), continued by Watson-Wyatt, then by Tillinghast Towers-Perrin and Towers-Perrin. The survey is now conducted by Towers-Watson and no longer covers Canada independently from the United States. 8 One exception is Kaltchev (2004) who analyzes a panel dataset of U.S. firms that purchase D&O
insurance from one insurance broker.
4
of the dataset for our purposes is that the purchase of D&O insurance is less prevalent in
Canada than in the U.S. during the period of our study. Moreover, our data include both firms
that purchase D&O insurance and firms that do not, as well as firms that change their insurance
status over the sample period. In addition, many firms change their D&O insurance limits over
the period, which provides an additional source of variation for empirical testing.
Using the extant theoretical literature on D&O insurance purchase, coupled with the literature on
corporate insurance purchases, we develop and estimate models of the determinants of firms’
demand for D&O liability insurance. We add to and validate the existing empirical literature by
testing hypotheses regarding the relationship between D&O insurance purchase and firm size,
governance characteristics and business risk. Our analysis differs from previous research in
recognizing that D&O litigation risk depends on the affected shareholders exposure and not on
all shareholders exposure. Also, while previous studies have assumed that purchase decisions
and limits choices depend on the same variables, this is not strictly true and we can separately
analyze these two decisions.
Our dataset allows us to test both purchase decisions and limits choices. We first present
separate estimates of these decisions. We then present estimates that allow for their joint
determination, and that recognize the potential for selection bias in the estimates of insurance
coverage limits choices if the purchase decision is not accounted for (Heckman selection
corrected estimates). To shed additional light on the role and consequences of D&O insurance
we make further use of the panel structure of our data to examine the effects of D&O insurance
purchase on corporate governance measures.
2. Existing Empirical Literature
Support for the hypothesis that providing D&O insurance is part of an efficient contract with a
firms’ directors and officers is provided by several event studies which find a positive or
insignificant share price reaction to events that reduce directors’ personal liability. Bhagat et al
(1987) find suggestive evidence of positive share price effects (and no significant negative
share-price effects) of firms’ announcements of the purchase of D&O insurance. Similarly,
Brook and Rao (1994) find no significant stock price reactions to firms’ adoption of director
indemnification plans. Changes in the legal regime regarding director liability also appear to
have had no negative effects on firm value. Bhagat et al (1987) find that a New York law
broadening director indemnification had no significant effects on share prices, results that are
5
echoed in Janjigain and Bolster’s (1990) study of Delaware rule changes regarding director
liability.
Other research has focused on the moral hazard effects of D&O insurance, and these results
must be seen to temper the conclusions of the event studies. The first such study, by Chalmers
et al (2002), examines the purchase of D&O insurance around initial public offerings of 72 U.S.
firms. The study finds that firms’ long-run stock performance is negatively related to the amount
of D&O insurance purchased. Kim (2005) uses proprietary data to construct a matched sample
of 93 U.S. firms and finds that firms which purchase greater-than-predicted amounts of D&O
insurance are significantly more likely to engage in earnings restatements. Boubakri et al (2008)
use data from a sample of 138 Canadian seasoned equity offerings to examine the relationship
between D&O insurance and earnings management.9 Similar to Kim, these authors find that
excessive D&O insurance coverage is associated with more aggressive earnings management.
They also find that firms appear to purchase D&O insurance coverage in anticipation of
opportunistic behavior, but that this likelihood is reflected in a higher insurance premium.
A small empirical literature has emerged to test hypotheses regarding the relationship between
firm characteristics and the demand for D&O insurance. Using cross-section data on Canadian
and British firms respectively, Core (1997, 2000) and O’Sullivan (1997) provide the first such
analysis. O’Sullivan relates the D&O insurance purchase decisions of 366 firms in the United
Kingdom to their corporate governance characteristics, and concludes in favor of Holderness’
(1990) view that D&O insurance serves as a form of monitoring of directors and officers.
Specifically, O’Sullivan finds that the purchase of D&O insurance is positively related to firm size
and, and negatively related to insider ownership of shares. These corporate features are
predicted to increase the demand for monitoring or to increase the cost of monitoring
alternatives to D&O insurance.
Core (1997) analyzes D&O insurance purchase and coverage limits using a cross-sectional
sample of 222 Canadian firms, using data on board characteristics, insurance purchase and
financial conditions of each firm. Results are generally consistent with theories of corporate
insurance purchase as firms with higher risk are more likely to purchase insurance and choose
higher coverage limits, although few explanatory variables are statistically significant at
conventionally accepted levels. Specifically, the estimates show that firms with prior D&O
9 For more on the relationship between the risk of lawsuits, D&O insurance and earnings management,
see Cao and Narayanamoorthy (2010), DuCharme et al. (2004) and Boyer and Hanon (2009).
6
litigation, higher insider voting control and lower insider ownership percent are more likely to
purchase insurance and also purchase higher coverage limits. Greater risk of financial distress
is also associated with higher coverage limits, as is firm size. Core (2000) uses the same
sample to analyze D&O insurance premiums and finds that premiums are higher for firms that
have weaker corporate governance and higher litigation risk. The importance of corporate
governance for insurer underwriting and premium determination is verified by Baker and Griffith
(2007), who report results of an intensive interview-based study of the D&O insurance
underwriting process.
Although these studies provide important first steps in understanding the characteristics of D&O
insurance market participants, the use of panel data on firms that are drawn from stock market
listings is important if our interest lies in understanding the demand for and effects of D&O
insurance. The only panel data study of D&O insurance demand in the United States uses a
sample of 337 firm-year observations on 113 firms for the period 1997-2002 (Kaltchev, 2004).
The data are proprietary and are obtained from an insurance broker; thus all firms purchase
insurance in each year and firms appear in the sample in a year only if they purchase insurance
through the broker. These features limit the set of decisions that can be analyzed using the
sample, and may introduce selection bias if decisions to purchase insurance or to purchase
through the broker are systematically related to firm characteristics that affect purchase limits.
3. Empirical Framework
This research analyzes the demand for and effects of D&O insurance among publicly traded
companies. First, we examine the characteristics of firms that are associated with the
acquisition of D&O insurance as compared to firms that do not purchase insurance. Second, we
measure the factors that are associated with the choice of the policy limit for an insurance
contract. For those firms that purchase D&O insurance, we examine whether the price of
insurance reflects corporate governance quality, and whether the purchase of insurance
appears to influence board structure and compensation.
Insurance purchase decisions of corporations are determined by a wide variety of factors
including the financial position of the firm in relation to the potential loss severity and probability
distribution of loss; risk tolerance of the board (if directors are risk averse); insurance service
benefits demanded by the firm (and in this context we must include monitoring of the board);
and opportunism by an entrenched board (who get insurance benefits but do not pay the full
7
cost of insurance). This implies that the decision to purchase insurance should be determined
by a large set of firm characteristics including the corporate board structure; firm size and
growth opportunities; and the risk of litigation. The price of insurance will also matter, but the
price at which insurance is offered will be affected by many of these same firm characteristics.
3.1 Litigation Risk
Measuring differences in firms’ litigation risk exposure is the most challenging, but one can
proxy for the risk based on characteristics of the legal and institutional environment. We know
from our previous discussion that shareholders represent the most important (and costly) group
of possible plaintiffs (see the different surveys of Towers-Watson). Yet it is important to realize
that not all shareholders have the right to sue for managerial incompetence or misinformation.
Shareholders need to show the amount of damages they suffered by providing evidence of the
difference between the price at which the stock was purchased and the estimated market price
of the stock if no false statement had been made (perhaps some model market price).10
Suppose that managers reported misleading accounting results on June 1st 2003 (on which day
the share price increased from P0 to P1) and that these false results are acknowledged on June
30th 2003 (on which day the share price falls from P1 to P2). The shareholders who may have a
claim are not those who purchased the stock prior to June 1st (they were buying on correct
information), nor those who purchased and sold prior to June 30th (their information set is the
same). The shareholders that can claim to have lost money because of managerial
misinformation are those who purchased on or after June 1st (after the false news) and held on
to the shares until June 30th (after the correction). Their loss, per share, is P1-P2.11
Assuming there are N shares of stock on the market and a proportion ρ of shareholders that can
claim a loss, the potential lawsuit is equal to 21 PPNS . In terms of returns, we can write
this as 21 1 rNPS , with 0122 PPr . We therefore see that the potential loss is a
function of the proportion of shareholders who purchased on wrong information and held on to
the stock (ρ), the current market value of equity of the company (NP1) and some measure of the
10
Another possible formula for damages could be to have them equal to the average stock market price for one month before the date on which the false statement was publicly announced, minus the average stock market price during the month after the public announcement. 11
If we assume continuously compounded return r , the loss per share between date 1t and date 2t
becomes 1212 1111
ttrttrePePP
.
8
return that will befall the stock when the real information is revealed (1+r2). Of course, assuming
that insurance is purchased on June 1st, the only unknowns are ρ and r2 since the firm's market
value of equity is known at the time the insurance is purchased.12 Because we are dealing with
very different firms in terms of size, it is appropriate to use the log of the potential loss instead of
the expected loss per se. This means that
21 1lnlnlnln rEENPSE (1)
Because the purchase of insurance and the insurance policy limit should be positively related to
the expected loss from shareholder suits E[ln(S)], we observe that insurance purchase and
policy limits should be positively related to the log of the firm's market value of equity, ln(NP1),13
the importance of small shareholders E[ln(ρ)], and the expected downward return of the stock
E[ln(1+r2)].
The log of a firm’s market value of equity can be directly measured using stock market data.
The two other components of the potential loss, ρ and r2, are more difficult to measure. The
proportion of shareholders that have a claim (ρ) depends on the number of new shareholders
that purchase the stock on date t=1 and keep it until date t=2. We may proxy for the percent of
shareholders who potentially suffer a loss due to managerial misbehavior by examining the
frequency with which the firm’s stock has traded in recent time periods. More frequent trades
will increase the percent of shareholders with standing in a suit, and will therefore be positively
related to the firm’s demand for insurance.
We may also expect that ρ is a function of the importance of minority shareholders, or an
inverse function of the presence of important block holders and insider shareholders. Thus the
presence of large block holders should have a negative impact on the demand for D&O
insurance. We thus hypothesize that ρ is a positive function of the float (the proportion of shares
that are available to the public) and a negative function of the presence of block holders and
managerial shareholding. As a proxy for the presence of large block holders in the ownership
structure of Canadian corporations, we shall use the shareholding of large financial institution
(calculated as the percentage of the shares held by financial institutions, provided they own
12
The proportion of shareholders that will be able to claim a loss (ρ) will depend on the number of new shareholders that purchase the stock on date t=1 and keep it until date t=2. 13
Put differently, given that the most damaging lawsuits originate from shareholders so that the more shareholders have to lose because of the managers' incompetence, the more protection the firm will purchase.
9
more than 10% of the stock). Similarly, we calculate the extent of managerial shareholding, the
percentage of the firm’s shares held by insiders (corporate officers or employees) on the board.
We expect these measures of concentrated ownership to have a negative impact on the
demand for insurance.
The expected downside risk of managerial wrongdoing, 21ln rE , will be positively related to
D&O insurance ownership and may be related to several observable variables. The first is the
stock's annual volatility of compounded daily returns. The more volatile the stock price is to any
type of information, the greater should be the price jumps following the revelation of managerial
wrongdoing. We also expect a positive relationship between financial distress and the expected
downside return since a firm in financial distress is more likely to observe a very bad return
(bankruptcy represents a return of -100%) than a firm that is financially healthy. Finally, the
firm’s return on assets (ROA) measures the solidity of the firm’s earnings, with ROA negatively
related to the expected downside return of the stock. Stock volatility and risk of financial distress
should be positively related to D&O insurance demand, while ROA should be negatively related
to demand.
3.2 Firm size and growth opportunities
Traditional insurance theory (Mayers and Smith, 1982) implies that larger firms should be less
likely to purchase insurance, predicting a negative relationship between asset size and
purchase decisions. On the other hand, the shareholder protection strategy implies that the
purchase decision should be positively related to firms’ market capitalization (MVE). It is also
true that stakeholders other than shareholders are allowed to sue a firm’s directors and officers.
These lawsuits are usually related to the firm’s operations (employees, clients, suppliers) so that
directors in larger firms are more likely to be sued. For these reasons larger firms, measured
both in terms of operations and shareholder equity, will have a stronger demand for owning
D&O insurance.
The aggregate (annual) limit of a policy must take into account both the expected frequency and
the expected severity of claims. Of primary importance in the coverage limits calculation is the
potential severity of the loss. Moreover, the more frequent are claims the higher should be the
aggregate limit, which must account for the sum of all claims. A policy’s aggregate limit may be
measured as n
nn SfLimit * , where n is the number of possible claims, nf is the frequency
10
distribution of claim n and nS is the severity distribution of claim n . The choice of coverage limit
will depend on those factors that affect the decision to purchase insurance, plus a few additional
characteristics.
There are two primary sources of exposure to a D&O insurance claim: financing and operations.
Lawsuits originate from the shareholders or from individuals who have a close relationship with
the firm’s operations (mostly employees, but suppliers, clients and governments too). Financing-
related claims are likely due to significant decreases in share price, which is why these types of
claims are very infrequent14 for not-for-profit organizations. Operations-related claims are linked
to the size of the firm’s operations: The larger the operations, the more likely and severe will be
the claims. Although financing-related and operations-related claims will both funnel into the
general D&O insurance policy, the determinants of each will be different. Taken together,
however, these factors imply that coverage limits will depend importantly on firm size and future
growth opportunities.
3.3 Board structure and governance
As with other insurance, economic theory predicts that the provision of D&O insurance
protection to directors’ and officers’ will reduce their incentives to monitor managers’ activities
and to provide energetic oversight of the financial condition of the firm. This was the main
reason why D&O insurance was not allowed in many continental European countries until very
recently (see Gutierrez, 2003, Werder et al, 2005, and LaCroix, 2009). Recognizing this
problem, insurers engage in substantial amounts of pre-sale monitoring of potential purchasers
of D&O insurance (Baker and Griffith, 2009). Holderness (1990) states that insurers may
negotiate changes in a firm’s corporate governance as a condition for obtaining insurance,
including diluting the power of the Chairman of the Board and increasing the number of
outsiders on the audit committee.15
As discussed previously, these relationships imply that board structure and governance may
affect both the demand for D&O insurance and D&O insurance prices, and previous empirical
14
Only 7% of not-for-profit organizations report having had a D&O insurance claim related to a derivative lawsuit – the most costly types of lawsuits – in the previous 10 years, compared to 65% of public organizations (Towers-Watson, 2008) and 7% of private organizations. 15
On the other hand, Romano (1991) finds that corporations change their governance structures in reaction to D&O litigation – suggesting that D&O insurers may not provide sufficient monitoring of corporate governance (see also Baker and Griffith, 2006).
11
literature has found some support for these effects (O’Sullivan, 1997; Core 2000). Our empirical
models therefore consider board characteristics for inclusion as explanatory variables. However,
we must first explore the extent to which board characteristics may themselves be determined
by the purchase of D&O insurance. We take advantage of our firm level panel dataset in which
some firms purchase D&O insurance for only some of the years in which they appear in the
sample, to examine whether the (new) purchase of D&O insurance affects board structure or
governance.
3.4 Exogenous factors affecting price
We must also consider the supply side of the market. There is always the possibility that the firm
applies for and is turned down for insurance by an underwriting decision. Under conditions of
symmetric information insurance applications should never be denied in an unregulated
environment. Insurance denials and the resulting shrinking of insurance market size arise from
problems of information asymmetry which lead to adverse selection. In cases where insurance
applicants know their risk better than the insurer and the insurer does not have a perfect means
to sort applicants or to force self-revelation of risk, applications may be denied. However,
Knepper and Bailey (1998) argue that information asymmetry is not an important issue for D&O
insurance. Insurers verify the quality of the managerial team, and the flexibility of the D&O policy
allows the insurer to deny payment in the event that the insured hid relevant information.
Indeed, when underwriting or renewing insurance, insurers require that companies provide them
with complete detailed questionnaires, and any omitted or incorrect information might eventually
lead to a claim denial (Baker and Griffith, 2007). Consequently in such cases, the quality of
financial data reporting, which is a primary cause of complaints, would enable insurance
companies to correctly price the litigation risk faced by firms who seek to purchase D&O
insurance. Based on this evidence, we may model the demand for insurance ownership without
strong consideration of the possibility of insurance denial.16
The price of insurance should nonetheless be an important aspect of the coverage limit chosen,
and the coverage limit and total premium amount will be jointly determined. Insurance theory
tells us that the amount of coverage chosen will depend upon the unit price of insurance -- the
price per dollar of expected loss. It is this price that is appropriately included as an element of
the coverage limits decision. The unit price will reflect the insurer’s mark-up of the total premium
16
Because we cannot observe whether firms in our sample who do not purchase D&O insurance sought to purchase it and were denied, we cannot directly examine this relationship.
12
relative to the coverage limit and will be determined by cost and market conditions. In the
absence of data that would allow us to construct expected losses, we proxy the unit price of
insurance as the price per dollar of insurance limits, that is the total premium divided by the
aggregate policy limits.
As in other insurance markets, insurance market cycles are partly responsible for premium
levels and premium evolution over time. Figure 1 plots the mean, median, first quartile and third
quartile of D&O annual premiums for years 1990 through 2006 to provide some indication of
these trends during our sample period. The data are plotted using the mean for 1990 as an
index base (set equal to 100). Cyclical trends over the subsequent years are apparent, but in
most years the variations are small; a notable exception is the sharp rise in premiums in the
2001 to 2003 period. This may be due to the passage of the Sarbanes Oxley Act (SOX) in the
U.S. in 2002, or more directly to the corporate governance scandals that led to its passage.
The 2005 D&O report by Towers-Watson revealed that the American market saw an 8% decline
in premiums in 2004 and a 10% decline in 2005. At the same time there was a 30% increase in
claim frequency, and policy limits increased by 9% in 2004. Premiums in Canada doubled or
tripled for some companies between 2001 and 2005. The subsequent softening of the insurance
market in 2006 led to premium declines of 14% in Canada and 18% in the U.S., with policy
limits remaining stable (Tillinghast Towers-Perrin, 2007).
[Figure 1 here]
D&O insurance prices may also be affected by insurance market structure. Although the market
faces little in the way of regulatory barriers to entry, it remains a highly concentrated insurance
line of business. In 2006 for example, the Towers-Watson survey reports that two primary
insurers (Chubb and American Insurance Group) accounted for 60% of the D&O insurance
premium volume. D&O insurance is one of the most concentrated insurance markets in the
United States with a (countrywide) Herfindahl index of approximately 2000. By comparison, the
countrywide Herfindahl index for homeowners’ insurance is 700 and that for private passenger
automobile insurance is 600. The only line of insurance business that exhibits concentration
levels similar to that of D&O insurance is the mortgage guarantee line, with a Herfindahl index of
2200. This suggests that insurance prices may be less sensitive to individual firm risk (the
marginal cost of providing insurance) than in a competitive market environment.
13
4. Data and Sample Characteristics
We construct a panel dataset of firms’ using publicly available data from stock-exchange traded
Canadian companies. The companies in our sample are traded on the Toronto Stock Exchange,
Canada’s main stock exchange, but are not limited to being in the index. The dataset includes
information on D&O insurance purchases, coverage limits, and premium charges, along with
extensive information on the financial and governance characteristics of each firm. Information
regarding D&O coverage and board composition and compensation is collected from the firms’
annual management proxy and information circular. Firms’ financial data are obtained from
Compustat; stock prices and total returns are drawn from the Toronto Stock Exchange data
retrieval services. The firms are drawn from seven economic sectors (the mining, public
services and financial services sectors are omitted). The sample period encompasses years
1996 through 2005, with the ending date 2005 chosen due to important securities reforms being
passed in Canada that year.
4.1 Characteristics of sample firms
We obtain data on a total of 328 firms and 2,192 firm-year observations over the 1996 through
2005 sample period. Because of missing information in Compustat about Canadian companies,
the number of firm-year observations available for statistical analysis that includes firms’
financial characteristics is smaller than the number of observations on board characteristics and
D&O insurance ownership. As we can see in Table 1, we lose a total of 611 firm-year
observations over the 10 years of data due to some Canadians companies not being included in
the Compustat database. The remaining sample for analysis consists of 1,581 firm-year
observations on 198 firms.
We also see from the table that approximately one third of our data comes from the Industrial
Products sector, but there is a broad distribution of the remaining firms across the other six
sectors. This is true in both the original sample and the Compustat sample, so it appears that
firms in specific sectors are not noticeably more likely to be dropped from the sample. Our data
are distributed relatively evenly over the years, and this is especially true in the Compustat
sample relative to the original sample. This suggests that we are less successful in matching
earlier firm observations to Compustat.
[Table 1 here]
14
Table 2 presents summary statistics for our (Compustat) sample of key firm characteristics of
interest in our study. Firms average $160 million in assets and sales, and close to a zero rate of
return on assets. Boards have an average of just under 9 members, of which 62 percent are
outsiders. Insiders own an average of 24.3 percent of shares, and 32 percent of firms in the
sample have a financial institution as a block holder (owning more than 10 percent of shares).
Nearly 74 percent of our sample firms carry D&O insurance. This represents a total of 1,170
firm-year observations. On average, the typical D&O insurance policy has a policy limit of 24.8
million dollars (in US 2006 constant dollars).17 This compares to an average market value of
equity of approximately 170 million dollars so that the D&O insurance limit represents about
14.6% of the market capitalization of a given firm. Premium data are available for only about
two-thirds of the sample of firms. The average premium paid by corporations to obtain D&O
insurance is just under $186,000, which represents 0.6% of the policy limit amount.
[Table 2 here]
The dynamics of D&O insurance purchase among firms in our sample are illustrated in Figure 2
which shows the percentage of firm-year observations in the sample for which D&O insurance is
purchased by year. The figure shows some slight upward trending over time in D&O insurance
purchase, but the percent in each year does not differ dramatically from the overall sample
mean of 74 percent.
[Figure 2 here]
Figure 3 summarizes the dynamics over the sample period of D&O insurance purchases for
each firm. Of the 198 firms in our sample for analysis, 109 (55%) purchase D&O insurance in
every year that they appear in our database; 33 (17%) never purchase D&O insurance, and 56
(28%) change their purchase behavior during the years which we observe them.
[Figure 3 here]
5. D&O Insurance as a Monitoring Device
One hypothesis for the purchase of D&O insurance is that the insurer may act as a monitor on
behalf of shareholders. Indeed, Holderness (1990) argues that D&O insurance may substitute
17
Canadian dollar values are translated into US dollars using the year-end exchange rate.
15
for shareholder monitoring of managers, hypothesizing that companies in which the cost of
monitoring is high will be more likely to purchase D&O insurance. O’Sullivan notes, however,
that in many firms D&O insurance may be used as a complement to other monitoring
mechanisms. This may be especially true in large corporations and when boards appoint
outside directors to improve monitoring. A related hypothesis is that the insurer monitoring
function operates to require good corporate governance as a condition of insurance. If this form
of the monitoring hypothesis is correct, we should expect to observe stronger governance
characteristics when the firm’s managers are protected under a D&O insurance policy.
The distinction between these alternative views of insurer monitoring is important in its own
right, and will also have implications for the treatment of variables measuring board structure
and governance in our models of insurance demand. To explore these relationships we
compare a variety of board characteristics across firms with D&O insurance and those without.
Because the analysis does not use Compustat data, these comparisons are undertaken using
the original sample of firms. The board characteristics examined are: whether the CEO is also
the chairman of the board (CEO-COB); the overall size of the board; the percentage of outsiders
on the board; the percentage of outsiders on the audit committee; the percent of voting shares
owned by insiders; and the percent of board compensation received in options rather than cash.
We first conduct the analysis using the full sample of firms, comparing all firm-years in which
D&O insurance is present to all firms-years in which it is not. We then restrict the analysis to
firms which changed D&O ownership status during the years that we observe them, comparing
firm-years in which D&O insurance is owned to those in which it is not. This latter comparison
provides a stronger test of whether board differences are likely to be a consequence of D&O
insurance ownership.
Table 3 presents means and t-test statistics for these comparisons, along with the predicted
relationships between board characteristics and D&O insurance if D&O insurance is
complementary results in boards with stronger governance characteristics. The table also
reports the sign and statistical significance of the coefficient estimate for an indicator of D&O
insurance ownership obtained from regressing each variable on the D&O insurance indicator,
industry dummies, and year dummies. This regression approach accounts for the fact that D&O
insurance purchase rates differ across industries and increase over time. If board characteristics
16
also vary across industry and time, comparison of means may mistakenly ascribe these
differences to D&O insurance ownership.18
[Table 3 here]
The top panel of the table presents results for the full sample of observations. Both the
comparison of means and the regression estimates reveal substantial differences in governance
structures among firms with D&O insurance and those without. Firms with D&O insurance are
significantly less likely to have a single person act as both CEO and COB, have significantly
larger boards, have a higher fraction of outsiders on the board, a higher fraction of outsiders on
the audit committee, and a higher percentage of voting shares controlled by insiders. Thus,
D&O insurance appears to be complementary to other shareholder monitoring mechanisms.
Comparisons of board structures across the insurance and no-insurance regimes for firms that
change insurance status during the time that we observe them are reported in the bottom panel
of Table 3. Here we observe relatively few significant differences in board structure. In the
comparisons of means, statistically significant differences are observed in the prevalence of a
combined CEO-COB, the size of the board, and the percent of outside directors. The CEO-COB
and board size variables have the expected sign if D&O insurers require board changes to
strengthen monitoring. Results from the regressions controlling for industry and year, however,
are not statistically significant for the CEO-COB variable and the board size difference is only
marginally statistically significant. Moreover, the percentage of outsiders on the board is
significantly lower when firms have D&O insurance, which runs counter to the monitoring
hypothesis. Also unexpectedly, the percent of outsiders on the audit committee is lower and the
voting share of insiders is higher under the insurance regimes, although these differences are
not statistically significant. Results overall provide little support for the idea that the insurance
underwriting process changes board structure to strengthen oversight of management.
6. Estimating Insurance Demand
As described previously, we estimate models of two alternative measures of D&O insurance
demand: ownership of insurance and insurance policy limits. We model the likelihood that a
firm purchases D&O insurance in a year as depending on the market valuation of the firm, the
percent ownership of large block holders and board insiders, measures of the trading volume of
18
Full results are available from the authors.
17
the firm’s stock and stock price volatility, firm financial distress and profitability. To reflect the
timing of the insurance purchase decision, lagged values of financial variables are used in the
models. All monetary values are converted to US 2006 constant dollars. The construction of
regression variables is described in the Appendix table A1, which also reports summary
statistics. Appendix table A2 reports the correlation matrix for the regression variables.
The empirical models include measures of the firm’s market valuation at the end of the previous
year (lag_lnMVE). The percent of shares owned by insiders (inside_own), and the percent
ownership of large financial institution block holders (fin_blockshr), where block holders are
defined as owning at least 10 percent of shares, are included as measures of the importance of
large block holders. The models include stock price volatility over the previous three years
(volatility), a measure of the risk of financial distress (distress), and the previous year’s
profitability (lag_ROA). A measure of financial leverage is included to account for the possible
role of creditors in supervising the firm’s managers (debtratio). Variables to account for board
characteristics, board monitoring tools, and board entrenchment are the number of board
members (n_board), the percent of outside board members (pct_outside), the percent of board
compensation received in options (board_opt), and the power of the CEO as measured by
whether the CEO is also the board chairman (ceocob).
Several additional variables are included in the models of insurance coverage limits. Firm size is
measured as the log of the firm’s sales (lag_lnSales).19 A proxy for the proportion of investors
that are mostly affected by false or misleading accounting is the trading volume of the firm’s
stock in the previous year (pcttrade). We also include measures of the recent growth of the firm,
measured as changes in total assets over the previous three years (growth). The unit price of
insurance (unitp) is included, measured as the premium per dollar of coverage limit.
The models treat the unit price as jointly determined with the coverage limit, due both to the
predicted relationship between price and quantity demanded and due to the construction of the
variable. The excluded instrument in the instrumental variables estimates is the average unit
price of D&O insurance for the industry and year. Because we observe the choice of policy limit
only for those firms that choose to purchase insurance, these estimates rely on a smaller
sample of firm-year observations than are used in the insurance ownership estimates.
19
We do not use firm assets as the size variable since assets are used to calculate other independent variables (return on assets, debt ratio, and asset growth).
18
6.1 Demand for insurance ownership
The first set of estimates we present are those related to firms’ D&O insurance purchase
decisions. Although the purchase decision is a dichotomous (0-1) choice, we present both linear
probability estimates and probit estimates. Alternative estimates including industry fixed effects,
firm-specific fixed effects and firm-specific random effects are reported for the linear
specification, and alternative estimates including industry fixed effects and firm-specific random
effects are reported for the probit estimates. The estimation results are displayed in Table 4.
[Table 4 here]
As we can from the table of results, it is relatively difficult to explain the ownership of D&O
insurance with the available variables. Although the models are statistically significant the R-
squared values are low and relatively few variables are statistically significant. Board
characteristics show the most significant role. D&O ownership is negatively associated with
board compensation through options, reflecting either a trade-off in compensation forms or the
use of options as an incentive alignment tool for board members (and reducing the need for
monitoring by an insurer). The percent of outsiders on the board is positively associated with
D&O ownership in some models, in line with theoretical predictions. Most of the financial
characteristics are not significantly related to insurance ownership. Contrary to expectations
past accounting profitability as measured by the firm’s ROA is unexpectedly associated with an
increased likelihood of owning D&O insurance.
6.2 Insurance policy limit
A second set of regressions examines the D&O policy limit chosen by a firm in a year. We first
present models of the coverage limit choice for firms that choose to purchase insurance. We
then present Heckman selection-corrected estimates of the policy limit, which take into account
the fact that the endogenous choice to purchase insurance determines whether we observe the
policy limit.
Table 5 provides the first set of estimation results for the policy limit. Just as in the previous
estimates, we report alternative specifications that include industry fixed effects, firm-specific
fixed effects and firm-specific random effects. For comparison purposes we report OLS
estimates which treat unit price as an exogenous variable, in addition to IV estimates,
19
[Table 5 here]
As can be seen from the table, these models of the demand for D&O insurance achieve more
explanatory power than those reported previously, and the OLS and IV estimates are similar. In
all specifications, firm size and market valuation are positively related to coverage limits, as
expected. The unit price is negative as expected, and statistically significant. We also observe
the expected negative sign on lagged accounting profitability. The risk of financial distress is
positive and significant in some models, as is the percent of outsiders on the board. Similarly,
the expected positive sign on the percent of firm shares traded is observed, and this is
statistically significant in models with industry fixed effects. The same is true of the leverage
variable. One unexpected result is that growth opportunities, as measured by recent asset
growth, are negatively related to the policy limit.
Several alternative specifications, not reported here, were estimated to try to account for the fact
that the coverage limit and our measure of the unit price may be affected by the deductible
amount chosen.20 In our sample of firms, this further reduces the sample size since some firms
do not report the deductibles on their policies. Among those firms that report deductible
amounts, these tend to be small relative to the policy limits. All estimation approaches yielded
results that are similar to those reported in Table 5, with no effects on the signs and significance
of variables in the model.
The regressions results we presented thus far in terms of the determinants of the policy limit do
not take into account the fact that firms that opt to have no D&O liability insurance are possibly
not similar to the firms that did opt to have D&O insurance coverage. To correct for this we use
a Heckman selection correction. The Heckman selection corrected estimation takes account of
the joint decisions regarding the insurance coverage limit and the purchase of insurance. The
Heckman approach is appropriate since the coverage limit (and price) is observed only if the
insurance is purchased, leading to a classic Heckman-type21 model. In our setting, we want to
examine the effects of the premium and risk variables on the policy limit, but we must account
20
One approach includes the deductible as an explanatory variable in the policy limit model. Other approaches involve constructing a composite coverage amount (limit – deductible) and/or a composite unit price (premium/(limit – deductible) and using these as dependent variables in appropriately modified regression models. 21
For example, the classic Heckman-selection problem arises when we examine the effects of schooling on wages since we must account for the self-selection into working.
20
for self-selection into purchasing insurance. The unobservable variable correlated with both the
choice to purchase insurance and the policy limit is “litigation risk”.
Table 6 provides the estimation results using maximum likelihood estimation. Alternative models
include industry fixed effects and firm-specific fixed effects. Because OLS and IV estimates in
Table 5 yielded similar results, the unit price of insurance is treated as exogenous in these
estimates. Results are similar if the predicted value of unit price obtained from the first stage IV
estimates is used as a proxy. Standard errors are adjusted to allow for general forms of
heteroskedasticity and for arbitrary correlation of errors across time within each firm.
[Table 6 here]
As we see in Table 6, the chi-square test rejects the hypothesis that the two equations are
independent only when firm-specific fixed effects are included, and at only the 10 percent
confidence level. It is thus not surprising that the estimation results after controlling for selection
bias are similar in signs and significance to the single equation results reported previously. Most
of the variables that we hypothesized should have an impact on the policy limit have the
expected sign, and many are statistically significant. These results suggest that firms that are
more at risk of running into financial difficulties purchase more protection against the event of a
lawsuit.
21
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25
Figure 1
Figure 2
0.66
0.68
0.70
0.72
0.74
0.76
0.78
0.80
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Perc
en
t
Year
Percent of Firm-Obs by Year with D&O Insurance
D&O Insurance
26
Figure 3
0
20
40
60
80
100
120
DOI all years DOI no years DOI some years
D&O Insurance Status by Firm
Number of f irms
27
Table 1 Sample of Firms
Original Sample
Year Total
Biotech
and
Pharma
Paper
Products
Industrial
Products
High
technology
Consumer
Goods
Merchandi
zing Media
1996 312 20 36 91 34 59 41 31
1997 303 21 33 88 40 55 40 26
1998 281 21 30 83 40 48 34 25
1999 258 19 26 78 38 43 32 22
2000 217 18 19 66 31 36 28 19
2001 197 17 17 60 27 35 23 18
2002 180 14 17 56 23 33 21 16
2003 166 14 17 47 22 30 20 16
2004 147 14 12 40 19 27 19 16
2005 131 11 11 37 15 24 18 15
Total 2,192 169 218 646 289 390 276 204
Sample with Compustat Data
Year Total
Biotech
and
Pharma
Paper
Products
Industrial
Products
High
technology
Consumer
Goods
Merchandi
zing Media
1996 176 12 17 55 22 27 26 17
1997 186 12 17 60 27 27 26 17
1998 188 12 17 60 28 30 24 17
1999 186 12 17 56 28 31 25 17
2000 166 13 13 52 24 29 21 14
2001 156 13 12 51 21 28 17 14
2002 147 12 13 48 18 27 15 14
2003 139 12 13 41 18 26 15 14
2004 127 11 11 38 15 23 15 14
2005 110 9 10 34 13 18 12 14
Total 1,581 118 140 495 214 266 196 152
28
Table 2 Characteristics of Sample
Variable Obs Mean Std Dev
Market Value of Equity 1559 170,359,100 861,780,500
Assets 1581 160,099,800 405,382,000
Sales 1558 160,554,100 399,563,100
Return on Assets 1578 -0.020 0.289
D&O Insurance Indicator 1581 0.739 0.439
D&O Limit 1581 24,800,000 48,900,000
D&O Premium 1075 185,987 462467.6
D&O Premium/Limit 1075 0.006 0.009
Pct Insider Ownership 1581 24.330 29.478
Number of Block holders 1581 0.939 0.856
Financial Blockholder 1581 0.322 0.467
Number on Board 1571 8.785 2.913
Pct Outsiders on Board 1568 62.013 16.283
29
Table 3 D&O Insurance and Board Characteristics
Full Sample of Firms
Effect if
Insurance
Strengthens
Monitoring
Mean for
Firms without
D&O
Insurance
Mean for
Firms with
D&O
Insurance T-stat Sig.
Effect of
D&O in
Regression
(sig.)
CEO-COB - 0.493 0.363 -5.378 *** - (***)
Number of Board Members + 8.210 8.764 3.952 *** + (***)
Voting Share of Board - 0.261 0.241 -0.944 n/s - (***)
Pct Outsiders on Board + 0.618 0.639 2.616 *** + (***)
Outsider Pct Audit Committee + 0.761 0.802 3.497 *** + (***)
Pct Compensation in Options + 0.136 0.152 0.923 n/s - (n/s)
Effect if
Insurance
Strengthens
Monitoring
Mean for
Firms without
D&O
Insurance
Mean for
Firms with
D&O
Insurance T-stat Sig.
Effect of
D&O in
Regression
(sig.)
CEO-COB - 0.402 0.323 -1.897 * - (n/s)
Number of Board Members + 8.183 8.854 2.553 *** + (*)
Voting Share of Board - 0.239 0.292 1.304 n/s - (n/s)
Pct Outsiders on Board + 0.648 0.615 -2.319 ** - (*)
Outsider Pct Audit Committee + 0.799 0.774 -1.160 n/s - (n/s)
Pct Compensation in Options + 0.126 0.163 1.220 n/s + (n/s)
Firms that Change Insured Status
30
Table 4 Estimates of D&O Insurance Ownership
lag_lnMVE 0.020 0.015 0.013 0.018 0.099
0.870 1.040 1.120 0.790 0.790
Volatility -0.0007 0.0080*
0.0080 -0.0003 0.0469
-0.110 1.660 1.580 -0.050 1.460
lag_ROA 0.066*
0.085***
0.079***
0.065*
0.457
1.820 3.610 3.120 1.650 1.480
Distress 0.0004 0.0005 0.0005 0.0004 0.0066
0.420 0.940 0.960 0.480 0.980
Debtratio 0.018 -0.048 -0.060 0.016 -1.415*
0.150 -0.960 -1.270 0.130 -1.800
Fin_blockshr 0.001 -0.001 -0.0003 0.002 -0.018
1.090 -0.800 -0.660 1.120 -1.620
Inside_own 0.0008 0.0004 0.0003 0.0009 0.0029
0.780 0.500 0.490 0.830 0.390
N_board 0.006 0.003 0.002 0.005 0.049
0.440 0.370 0.330 0.350 0.750
Pct_outsiders 0.426***
-0.048 0.003 0.416***
0.582
3.270 -0.460 0.030 3.150 0.700
ceocob -0.068 0.010 -0.00009 -0.060 -0.074
-1.260 0.310 0.010 -1.130 -0.200
board_opt -0.122*
-0.014 -0.022 -0.144*
-0.542
-1.750 -0.370 -0.580 -1.840 -1.590
Year yes yes yes yes yes
Industry yes no no yes no
Firm no yes yes no yes
N 1354 1354 1354 1354 1354
R-square 0.141 0.058 0.011 0.133 n.a.
Linear Probability Estimates Probit Estimates
Industry F.E. Firm F.E. Firm R.E. Industry F.E. Firm R.E.
31
Table 5 Single Equation Estimates of D&O Insurance Limits
Variable
ln_unitp -0.376***
-0.363***
-0.355***
-0.475**
-0.308***
-0.274***
-7.500 -14.280 -14.670 -2.260 -2.630 -2.750
ln_lagsales 0.136***
0.147***
0.149***
0.132***
0.141***
0.153***
3.220 5.290 7.020 3.180 4.580 6.870
ln_lagMVE 0.299***
0.113***
0.188***
0.310***
0.111***
0.165***
7.090 4.920 8.890 6.900 4.790 7.580
ln_pcttrade 0.339***
0.007 0.067 0.398**
-0.011 0.016
2.820 0.150 1.350 2.220 -0.180 0.270
debtratio 0.393*
0.056 0.117 0.452*
0.028 0.061
1.750 0.480 1.030 1.840 0.220 0.510
growth -0.052**
-0.046***
-0.037***
-0.047*
-0.044***
-0.037***
-2.070 -3.450 -2.780 -1.880 -3.200 -2.780
distress 0.005***
0.001 0.001*
0.005***
0.001 0.001
2.840 0.970 1.670 2.810 0.940 1.390
lag_ROA -0.544***
-0.203***
-0.309***
-0.600***
-0.186***
-0.249***
-5.630 -3.280 -4.960 -4.170 -2.600 -3.530
pct_outsiders 0.386*
0.125 0.204*
0.348 0.115 0.179
1.700 0.990 1.690 1.470 0.900 1.490
ceocob -0.064 0.073 -0.004 -0.055 0.073 0.017
-0.770 1.490 -0.100 -0.650 1.500 0.370
n_board 0.030 0.010 0.026**
0.027 0.010 0.023**
1.410 0.840 2.450 1.250 0.820 2.100
board_opt -0.012 0.101**
0.101**
0.014 0.094*
0.089*
-0.110 2.190 2.170 0.120 1.940 1.850
Year yes yes yes yes yes yes
Industry yes no no yes no no
Firm no yes yes no yes yes
N 912 912 912 912 912 912
R-square 0.690 0.387 0.665 0.685 0.383 0.655
Firm R.E.
OLS Estimates IV Estimates
Industry F.E. Firm F.E. Firm R.E. Industry F.E. Firm F.E.
32
Table 6 Heckman Selection Corrected Estimates of D&O Insurance Limits
Variable
ln_unitp -0.366***
-0.167***
-7.270 -2.700
ln_lagsales 0.147***
0.288***
3.390 4.430
ln_lagMVE 0.298***
0.061*
6.830 1.820
ln_pcttrade 0.322**
0.044
2.550 0.480
debtratio 0.372*
-0.246
1.650 -1.290
growth -0.053**
-0.055***
-2.130 -2.990
distress 0.005***
0.000
2.920 0.120
lag_ROA -0.524***
-0.213***
-5.390 -2.670
pct_outsiders 0.581**
-0.032
2.130 -0.140
ceocob -0.081 -0.024
-0.960 -0.320
n_board 0.030 -0.008
1.430 -0.480
board_opt -0.065 0.129
-0.690 1.540
N 1253 1253
Wald test of equation
independence 1.270 3.680 *
Industry F.E. Firm F.E.
Selection Corrected Estimates
Appendix Table A1
Variable Name Description Source Construction Mean Std Dev N
doidum (dummy) Firm purchases D&O insurance SEDAR Equals 1 if firm reports D&O coverage limit 0.7394 0.4391 1581
doi_cdi Corporate deductible for D&O policy SEDAR Deductible for Side B (corporate) coverage 603,857 3,334,580 839
doiagg Coverage limit for D&O policy SEDAR D&O coverage limit 24,800,000 48,900,000 1581
inside_own Percent insider ownership of firm SEDAR Percent of shares owned by four largest insiders 24.3303 29.4779 1581
fin_blockholder (dummy) Financial institution is a blockholder of shares SEDAR Equals 1 if a financial institution owns at least 10 percent of shares 0.3219 0.4674 1581
volatility Stock price volatility over past 3 years TSX Standard deviation of annual stock price over previous 3 years 2.6032 3.0914 1538
lag_roa Lagged value of return on assets COMPUSTAT data172/data6 for previous year -0.0144 0.2869 1562
lag_lnmve Lagged value of market value of equity COMPUSTAT data199*data25 for previous year 5.3898 1.9225 1511
lag_lnasset Lagged value of firm assets COMPUSTAT data6 for previous year 5.6719 1.8659 1532
ln_avgcash Log of average cash to board members SEDAR Cash compensation divided by number of board members 3.0234 5.8467 1571
ln_avgopt Log of average options to board members SEDAR Value of options awarded divided by number of board members -0.6085 3.7895 1571
distress Measure of firm's potential for financial distress COMPUSTAT -Ln[(data199*data25/data6)/(10*stdev ROA over previous 3 years)] -8.0830 18.1199 1456
n_board Number of board members SEDAR Total number on the board 8.7849 2.9133 1571
pct_outside Percent of board who are outsiders SEDAR Percent of board members who are not insiders 0.6201 0.1628 1568
ceocob (dummy) CEO and COB are the same person SEDAR Equals 1 if the CEO is also the COB 0.3706 0.4831 1522
lag_pcttrade Lagged value of percent of firm shares traded COMPUSTAT data28/data25 for previous year 0.3626 0.3510 1536
ln_unitp Log of the per unit price of D&O insurance SEDAR D&O premium/D&O coverage limit -5.5629 0.8946 1060
big_grow (dummy) Large growth in assets COMPUSTAT Equals 1 if data6(t)/data6(t-1) > 1.25 0.1978 0.3985 1532
growth_opp Measure of firm's growth opportunities COMPUSTAT (data199*data25)/data6 1.4390 1.4449 1503