How do Poison Pill Adoptions Affect Value Relevance?
Bin Srinidhi*
School of Accounting and Finance
The Hong Kong Polytechnic University
723, LiKaShing Tower, Hung Hom, Kowloon, Hong Kong
Tel: (852) 2766 7032
Fax: (852) 2330 9845
Email: bin.srinidhi@gmail.com , afbin@inet.polyu.edu.hk
Kaustav Sen
Department of Accounting
Lubin School of Business
Pace University,
New York, NY 10038-1502
Tel: (212) 618 6413
Fax: (212) 648 6410
Email: ksen@pace.edu
September 2007
*
Corresponding author
We gratefully acknowledge the comments we received on an earlier version of this paper
by the seminar participants at City University of Hong Kong, The Hong Kong
Polytechnic University, Pace University and Rutgers University. We are also grateful to
Ashiq Ali, Samir El-Gazzar, Jere Francis, Ferdinand Gul, Bikki Jaggi, Yaw Mensah and
Suresh Radhakrishnan, for their valuable comments.
How do Poison Pill Adoptions Affect Value Relevance?
Abstract
We explore the effect of poison pills on the contemporaneous association between
earnings and market returns, defined as value relevance. We find that value relevance
declines for poison-pill-adopters. As supporting evidence, (informed) affiliated block
holders decrease their ownership and free cash flow declines more in poison pill
adopters than non-adopters. We also find that value relevance decline is insignificant
in larger and high-product-competition adopters where greater market scrutiny of
earnings is more likely. These results are supportive of the view that poison pills
weaken corporate governance and reduce value-relevant information in reported
earnings.
Keywords: Poison Pills, Value Relevance, Corporate Governance
JEL Classifications: G34, D21, M41
2
1. INTRODUCTION
In this paper, we examine how poison pill adoption affects the market’s perception of
firms’ earnings reports. In particular, we explore its effect on value relevance defined
as the relationship between earnings or earnings components (cash flows and
accruals) and contemporaneous returns.
Our study of the effect of poison pills on value relevance is motivated by a lack of
direct evidence in the literature on how these widely used devices affect the ability of
earnings to capture value-relevant events in a timely and meaningful fashion. In
contrast, there have been a number of studies that investigate the effect of poison pill
adoptions on shareholder value but they provide mixed evidence (For example, see
Comment and Schwert 1995; 1988; Malatesta and Walkling 1988; Ryngaert 1988).
Even though direct evidence on the effect of poison pill adoption on value relevance
of earnings is lacking, prior literature provides some links between the two. One such
stream of literature is the corporate governance literature. In this literature, poison
pill adoption is treated as a weakening of the governance (Gompers et al. 2003;
Bebchuck et al. 2005; Bebchuck and Cohen 2005; Murray 2006). Taken in
conjunction with the accounting literature that associates increases in discretionary
accruals with weakening of corporate governance (Leuz et al. 2003; Bushman et al.
2004a; Bushman et al. 2004b; Klein 2002), these studies suggest that poison pill
adoption might be associated with lower transparency in reporting. Bushman and
Smith (2001 page 287) hint at such a link when they suggest, “ a change in takeover
pressure can alter managerial incentives to distort firms’ accounting numbers and thus
change their role in contracting and performance evaluation.” Some studies find that
3
poison pill adoptions are associated with higher discretionary accruals, (Pornsit 2005),
which in turn has the effect of reducing the value relevance of earnings (Ghosh et al.
2005; Lee et al. 2006).
The second stream of literature that we can draw from is the one on association
between the adoption of poison pills and the value of the firm. Poison pill adoptions
change the expectations about the future cash flows to investors from future takeovers
and operations. In particular, Comment and Schwert (1995) and Stein (1988) argue
that poison pill adoptions could result in higher expected takeover premiums for
investors. These changes in expectations will be immediately reflected in the market
valuation of the firm. However, generally accepted accounting principles do not allow
these changed expectations to be recognized in current income1 (See Basu 1997; Ball
and Shivakumar 2005). In fact, increased takeover premiums, even when they are
realized, will not be reflected in accounting income. This divergence between the
market’s recognition of changed expectations and accounting’s non-recognition
weakens the association between current earnings and market returns.
The third stream of literature that links poison pill adoption to value relevance
addresses how the adoption could affect the mix between long term investments and
short term costs (Pearce II and Robinson Jr. 2004; Rose 2005). To the extent that the
adoption favors long-term investments, the increased potential for positive-NPV long
term investments will be reflected in the market price immediately but will not be
1
Earnings can be viewed as a composite measure of the value-increasing current cash flows and the
expected value of future incremental cash flows. The latter part is presumably captured by accruals.
However, accounting methods also incorporate conditional conservatism (Ball and Shivakumar 2005)
which means that the accruals – both non-discretionary and discretionary – do not fully reflect
increases in future cash flows but do reflect decreases in future cash flows.
4
reflected fully in current earnings because of conservatism in accounting principles.
As the benefits of the long-term projects are realized, the future accounting income
numbers will reflect the realized benefits. This separation in time between market’s
and accounting recognition of changed expectations weakens the association between
current earnings and market returns. On the other hand, many short term costs are, in
fact, reflected in current earnings. If the mix between positive-NPV long term project
expenditures and short term costs shifts towards the long term projects, the value
relevance is likely to decline after pill adoption. On the other hand, if the poison pill
adoption emboldens the managers to cut research and development or training or
maintenance costs, the market reacts adversely to the decrease in value but the
reported earnings increase, further reducing the association between market returns
and current earnings.
The aforesaid effects presage a decline in value relevance after poison pill adoption.
However, arguments could be advanced as to why value relevance might increase as
well. One such argument is that the management of earnings by using discretionary
accruals, is undertaken by managers who are under pressure to do it. For example,
managers motivated by a desire to avoid short-term losses (Burgstahler and Dichev
1997) or by a desire to meet or beat analyst forecasts (Burgstahler and Eames 2003)
are likely engage in earnings management. In a similar vein, Healy (1985) provides a
compensation-based motivation and Jones (1991) uses the context of import relief
investigations for earnings management. Similarly, managers of firms that are facing
unmanaged earnings that are close to but still less than perceived expected earnings
benchmark might also be more motivated to cut research and development (Bushee
1998) and other discretionary expenditures. In the absence of such specific
5
motivations, earnings management might be motivated by general underperformance
and the possibility of corporate takeover. By reducing these pressures, the adoption of
poison pills, might decrease earnings management in some contexts and thereby
increase the value relevance of current earnings.
These conflicting predictions from earlier literature do not support directional
hypotheses on the association between poison pill adoption and value relevance. It
renders the association between poison pills and value relevance an issue for
empirical resolution. The objective of this paper is to empirically address this issue
and provide insights on the interplay between value-relevance-decreasing and valuerelevance-increasing forces in the face of poison pill adoption. Our empirical results
show a significant decline in the value relevance after poison pill adoption. However,
the decline becomes insignificant under alternative conditions that demand market
scrutiny such as size and competition.2 Further, we document decreases in affiliated
block-holder ownership and free cash flows in firms subsequent to poison pill
adoption. Together, these results show that in the absence of alternative conditions
that demand market scrutiny, poison pill adoptions decrease the ability of earnings to
incorporate value-relevant information.
The primary contribution of this paper is in providing empirical validity to the
proposition that in the absence of other conditions that demand elevated levels of
scrutiny by market participants, poison pill adoption makes accounting earnings less
value-relevant. In other words, the adverse effect of poison pill adoption on the
2
Prior literature on political cost hypothesis (Watts and Zimmerman 1986) argues that larger firms are
scrutinized more by both regulators and market participants such as investors, analysts and auditors. In
a similar vein, firms in highly competitive markets are scrutinized by customers and their disclosures
are followed more closely by analysts and investors.
6
usefulness of financial statements overshadows any potential benefits. The
implications of this finding are relevant to financial analysts, investors, managers and
regulators. Financial analysts and investors need to be cautious in interpreting the
earnings reported by poison pill adopters, especially if other conditions that demand
scrutiny are not present. In deciding to implement poison pills, managers need to
consider not only the potential effect of this decision on the value of the firm but also
on the credibility of financial statements of the firm. Further, the findings in this paper
complement the literature on the effect of corporate governance on earnings
management and on value relevance of earnings. This result is relevant to regulators
and policy-makers who are interested in increasing the informativeness of financial
statements.
The rest of the paper is organized as follows. In Section 2, we give a brief description
of poison pills and a discussion of their potential effect on shareholder value and the
value relevance of earnings. In Section 3, we describe the research design, explain the
data, and provide the results. We also describe some additional analyses to
corroborate the validity of our main results. In section 4, we give the conclusions.
2. POISON PILLS AND THEIR POTENTIAL EFFECTS
Description of Poison Pills
Poison pills are anti-takeover devices (See Bruner 1991) that could either entrench
managers3 by reducing the ability of investors to fire them after take over the firm or
enhance shareholder value by allowing the managers to take up long term investments
3
Poison pill adoption is an event that affects shareholder rights and has been classified as an important
corporate governance variable (Gompers et al. 2003).
7
and increasing the premiums that could be negotiated in the case of a serious takeover
offer (Comment and Schwert 1995). The board of directors can usually approve
poison pill adoptions without shareholder approval4. The Board can also alter poison
pill provisions quickly at a minimal cost. First, we note that poison pill adoptions are
primarily management decisions. Appendix 1 provides excerpts and descriptions of
two poison pills. The first one shows the penalty for anyone intentionally buying a
controlling block. The second one shows how the managers amend the provisions to
allow for acquisition actions that have management consent. Second, we note that
poison pill adoptions are quite common. Over 1000 firms have issued poison pills
since the mid-1980. These include most of the Fortune-500 firms, both profitable and
unprofitable firms, firms with more and less debt, firms in industries with high and
low competition as well as high and low growth firms (Sundaramurthy 2000; Jiraporn
2005). This seems to have slowed down the takeover activity 5 providing indirect
evidence that poison pills are deterrents to takeover. Pound (1987) provides direct
evidence that the takeover frequency is lower in firms with anti-takeover provisions.
4
Managers often propose and get the rights to adopt, extend and amend poison pills without
shareholder approvals. This is allowed under Delaware state law after the Delaware supreme court
ruling in Moran v. Household International, Inc.(Monks and N.Minnow 2004 page 236). The following
story in Wall Street Journal, April 2, 2003 is illustrative:
“H-P Holders Approve Rules on Poison Pill
H-P shareholders narrowly approved a proposal that the computer and printer maker not adopt or
extend any "poison pill" measures without a shareowner vote. H-P's management had opposed the
measure. ”
5
Comment and Schwert (1995) provide evidence of the changes in takeover activity as well as the
adoption of anti-takeover provisions including poison pills. The takeover offers were averaging about
1.5% per month during 1987 but dropped to .5% per month in 1990. The adoption of poison pills by
firms rose from near zero in 1986 to about 35% of all firms listed on NYSE and AMEX in 1991.
8
Poison Pill adoption and Shareholder value
There are two competing theoretical perspectives that either argue for poison pill
adoptions as shareholder-value-increasing events or as shareholder-value-reducing
events. Many reasons are posited for why poison pills might improve shareholder
interest (Berkovitch and Khanna 1990; Harris 1990; Knoeber 1986). In the presence
of takeover threats, managers are often forced to adopt short-term defensive strategies
and are unable to take up shareholder-value-increasing long term positive NPV
projects that might have adverse effect on the current and near-term earnings. Poison
pills allow the managers to focus on long-term projects without the detraction of a
constant pre-occupation to fend off takeover threats. Similarly, managers with longer
expected tenures are better motivated to make valuable firm-specific human capital
investments. Comment and Schwert (1995) provide evidence that the takeover
premium increases in the presence of poison pills because of the better negotiating
power of the firm. First, only serious bidders who see considerable synergies by
acquisition will bid for a firm that has poison pill. Second, the target firm managers
will be in a better position to negotiate a fair return for their shareholders. These
reasons suggest that poison pill adoptions might increase the value for current
shareholders.
In contrast to the shareholder-value-increasing rationale for poison pills given above,
the market for corporate control could be seen as one of the mechanisms available to
the shareholders for mitigating the agency cost of the separation of ownership
between shareholders and managers. Takeover possibility provides a credible threat of
management change if managers under-perform and this threat could reduce the cost
of moral hazard.
There is evidence that takeovers are often accompanied by
9
management change (Morck et al. 1989; Martin and McConnell 1991; Ikenberry and
Lakonishok 1993) as well as board restructurings (Walsh and Ellwood 1991; Martin
and McConnell 1991; Agrawal and Walkling 1994). Denis and Denis (1995) show
that it is rare for management changes to occur from internal board monitoring
without external takeover threats. By reducing the threat of takeover, poison pills
could reduce investors’ ability to motivate better performance6. This line of reasoning
suggests that poison pill adoptions might decrease the value for shareholders.
Poison pill adoption and the value relevance of earnings
The previous subsection provided the rationale for how the adoption of poison pill
affects the value of the firm by changing the incentives of managers. These incentive
changes affect the process by which managers generate value for the shareholders. By
the same token, these incentive changes also affect the ability of earnings to reflect
value-relevant events. Furthermore, poison pills also change the reporting incentives
of managers and this might affect the earnings quality of the adopters and thereby
affect the value relevance of earnings.
As discussed in the Introduction, if the adoption is motivated by managerial intent to
improve the shareholder value, the managers are less constrained by unexpected
6
Grossman and Hart (1980), Rappaport (1990) and Jensen (1986) strongly advocate the view that the
external market for corporate control are very important and that other factors of managerial control
such as product market competition, internal board controls and managerial labor markets are
ineffective substitutes. Martin and McConnell (1991), and Morck et.al. (1989) argue that hostile
takeovers are disciplinary in nature since they tend to be directed at poorly performing firms as
measured by stock market performance. Dahya and Powell (1998) provide evidence from UK that
hostile takeovers are associated with a greater degree of both top team and top executive forced
departure rates.
10
takeover possibilities and are more likely to invest in long-term projects and improve
the human capital. The stock market reacts to these value-increasing activities sooner
than it gets reflected in the earnings, because of conservatism in the GAAP (Basu
1997; Ball and Shivakumar 2005). Furthermore, accounting earnings are less
informative about the prospects of high-growth firms (Ahmed 1994; Lee et al. 2006;
Watts and Zimmerman 1986). These effects could cause a decline in value relevance
of earnings. At the same time, well-intentioned managers who feel less constrained by
unexpected takeover possibilities because of poison pill adoption are less motivated to
manage earnings. This improves earnings quality and as a result, the value relevance
could improve.
If the adoption is driven by the opportunism of managers, there could still be two
outcomes. If the managers have contractual incentives to manage earnings or intend to
preserve their private control benefits (Leuz et al. 2003), they feel less constrained
after the adoption to deliberately embed discretionary accruals or cut discretionary
expenditures. This behavior decreases the earnings quality and could drive down the
value relevance. On the other hand, even if the poison pill adoption is motivated by
the desire of managers to protect their jobs, they may not have any contractual or
private control benefit reasons to manage earnings after the adoption. In fact, they
might make the earnings less variable (Fudenberg and Tirole 1995) which, in turn,
could increase the value relevance of earnings (Bao and Bao 2004; Michelson et al.
2000). These arguments suggest that the value relevance of earnings could either
decrease or increase after poison pill adoption.
11
In summary, the findings in the literature do not allow a theoretical prediction of the
directional effect of poison pill adoption on value relevance and renders it an issue for
empirical resolution.
Size, Product Competition and the effect of poison pill adoption on value relevance
While it is not possible to predict the directional effect of poison pills on value
relevance, the magnitude of the effect is likely to be influenced by the conditions
under which the firm operates. Financial statements of larger firms face higher
scrutiny than those of smaller firms by market participants such as auditors, investors,
analysts and regulators (Watts and Zimmerman 1986). Therefore, they are less likely
than smaller firms to exhibit a decrease in earnings quality and a consequent decrease
in value relevance compared to the smaller firms. In a similar vein, intense product
competition also demands more disclosures, greater scrutiny and stronger corporate
governance. Denis and McConnell (2003) categorize corporate governance
mechanisms into internal and external mechanisms. The takeover market acts as an
external corporate governance mechanism. Another market mechanism that affects
disclosures and their accuracy is the competition faced by the firm in the product
market. Prior literature (Darrough and Stoughton 1990) shows that competition in the
product market encourages more disclosure because of lower proprietary costs of
disclosure. This result is further complemented by Wagenhofer (1990) and Clarkson
et al. (1994). Competition in the product market induces firms to also make additional
disclosures on firm technology (Entwistle 1999) and product pre-announcements
(Bayus et al. 2001). This pressure to make additional disclosures limits declines in
transparency and earnings quality.
12
Both size and competition create conditions under which earnings reports and other
disclosures are closely scrutinized by market participants and therefore act as
substitutes for internal corporate governance. If poison pill adoption affects value
relevance primarily because of a weakening of corporate governance, then larger
firms and firms that face more product competition should exhibit smaller or
insignificant declines in value relevance after poison pill adoption. Conversely, if the
presence of these conditions results in smaller or insignificant declines in value
relevance after adoption, it suggests that the poison pill adoption effect in other firms
is primarily explained by a weakening of corporate governance.
Other Firm characteristics and the effect of poison pills on value relevance
In addition to size and competition, we also examine the effect of other firm
characteristics such as leverage, growth, beta, earnings volatility, earnings persistence
and competition on the magnitude of value relevance declines. We provide here some
justifications for our expectations on the effect of these variables on the magnitudes of
the effect.
Debt plays a monitoring and disciplining role (Berger et al. 1997; Rappaport 1990).
Therefore, ceteris paribus, highly leveraged firms are less likely to suffer value
relevance declines than low-debt firms. Growth potential of firms might affect the
impact of poison pill adoption on value relevance because firms with high growth
potential have a different motivation to adopt poison pills compared to firms with low
growth potential. Further, it has been shown that contemporaneous returns are more
sensitive to current earnings for firms with higher growth prospects (Collins and
Kothari 1989). It has also been documented that value relevance is improved by
13
persistence of earnings (Kormendi and Lipe 1987) but is decreased by the systematic
risk (Easton and Zmijewski 1989). If earnings are not persistent, the earnings shocks
are more transient and have lower effect on the value of the firm. Further, if the firm
adopts poison pill, it is more difficult for investors in low-persistence firms to
disentangle potential earnings quality declines than in high-persistence firms. In
effect, the value relevance is more likely to decline in low-persistence firms after
adoption than in high-persistence firms. Using a similar reasoning, it is more likely to
decline in firms with more earnings volatility and higher beta.
3. RESEARCH DESIGN, DATA AND RESULTS
3.1 Research Design
We examine a sample of poison pill adopters that is likely to be over-represented in
specific firm characteristics and under-represented in others. We control this
truncation bias by the correction procedure developed by Heckman (1976) using a
probit model that classifies poison pill adoptions 7 . First, we describe this method.
Then, we describe the measures we have used for earnings management and value
relevance and the models used for testing the effect of poison pill adoption on them.
7
In the earlier version of the paper, we classified the firm-years into four classes: those predicted to
adopt and actually adopted; those predicted to adopt and did not adopt; those predicted not to adopt but
actually adopted; and those predicted not to adopt and did not adopt. Then we showed that among the
firms that are not predicted to adopt, the adopters have larger discretionary accruals and greater value
relevance declines than non-adopters. In this version, we use the more standard Heckman approach to
correct the self-selection bias.
14
Self-selection
Heckman correction: A comparative examination of discretionary accruals and value
relevance before and after poison pill adoption needs to be corrected for potential selfselection bias. Poison pill adoption is a choice variable for firms and therefore it is
reasonable to expect that at any given time, some firms are more likely to adopt than
others. Consider a set of firm characteristics (denoted by a vector X = {1,x1, x2, . . })
that can discriminate between poison pill adoption events that year from nonadoptions. Denote a composite of these characteristics, z = B’X (B is a vector of
coefficients, b0,b1,b2,…) such that firms with higher z are more likely to be poison pill
adopters in that year than firms with lower z. The sample of adopting firms selected
for a comparison of pre and post-adoption variables is likely to be truncated in the
region with low values of z and over-represented in the region with high values of z.
In order to correct for this truncation bias, we construct a probit model to identify the
vector of variables, X. We compute the Inverse Mills Ratio (IMR) from the above
probit model based on Heckman (1976) to correct for the bias resulting from selfselection (Heckman 1976; Johnston and DiNardo 1997). The probit model is
represented as Pr( zi  1)   ( Bˆ ' X i ) , where zi=1(0) represents the range of the
distribution in which z>z* (z ≤ z*) and ( Bˆ ' X i ) represents the predicted value from
the model. From this probit model, the IMR for adoption events is estimated as
ˆ 
  ( Bˆ ' X i )
where ( Bˆ ' X i ) is the cumulative probability distribution. Similarly,
1  ( Bˆ ' X )
i
 ( Bˆ ' X i )
the IMR for non-adoptions is estimated as ˆ 
. Consistent with Heckman
( Bˆ ' X i )
(1976), the bias resulting from the truncation is controlled by using the IMR as an
15
additional control variable in the models comparing the pre and post-adoption
samples. We discuss below the development of the probit model.
Independent variables: The underlying premise in our probit model is that the chance
of a takeover induces the firm’s managers to avert possible hostile takeovers by
influencing the board to adopt poison pills. Comment and Schwert (1995) use a
similar rationale in predicting poison pills. In addition to the likelihood of takeovers,
we argue that managers of older firms would have built their firm-specific human
capital that might lose value in case of a takeover and are therefore more likely to
protect the rents from their human capital by adopting poison pills. Therefore, we use
log(age) as an explanatory variable. We briefly present below the hypotheses
regarding the likelihood of takeover and the selection of variables based on each
hypothesis for the probit model. These have been presented in detail in Palepu (1986).
The inefficient management hypothesis is based on the premise that takeovers are
more likely in underperforming firms. The adoption of poison pill might also be
prompted when the managers get private information on future underperformance.
The daily excess return on a firm’s stock using the market model, averaged over a
period of four years, (axret) is used to capture the current underperformance.
Additionally, notwithstanding the current performance, managers who expect their
firms to under-perform in the succeeding year have a greater motivation to push for
poison pill adoption. Assuming that such expectations based on private knowledge are
more likely to be realized than not, we use the average excess return axret of the year
ending after poison pill adoption (axret1) to proxy managerial expectation of future
underperformance.
16
Earlier studies such as Myers and Majluf (1984) show that firms are taken over when
there is a mismatch between growth and resources (high growth resource-poor and
resource-rich low growth firms). This is referred to as the Growth-resource mismatch
hypothesis. We measure growth by the average sales growth rate (change in sales
divided by net sales in previous year, averaged over three fiscal years prior to
adoption) and resource-richness by average liquidity (ratio of current assets less
current liabilities divided by average total assets, averaged over three fiscal years
prior to adoption). Further, a growth-resource mismatch indicator (grdummy) that
takes on a value of 1 for high growth-low liquidity or low growth-high liquidity is
also used as an additional variable.
The Industry Disturbance hypothesis suggests clustering of takeovers by industry. We
measure it by using an indicator (idummy) that takes on a value of 1 if an acquisition
has taken place in the same 4-digit SIC code during the previous year or a value of 0
otherwise. Another popular explanation for takeovers is that firms with low priceearnings ratios or low market to book ratios are acquired because it could result in
‘instantaneous capital gain’. Size also affects the probability of takeover because
larger size targets involve higher transaction costs, which might make the takeover of
larger firms less likely.
Dependent variable and the model: We use the hazard model described by Shumway
(2001) to define the dependent variable.8 Shumway (2001) shows that discrete-time-
8
We do not use the approach taken by Palepu (1986), which considers the appearance of each firm
once in the dataset and does not allow for changes in firm characteristics over time. In our case this
17
hazard models produce more consistent estimates than single-period models do. In a
single-period model, in any particular year, the dependent binary variable takes the
value of 1 for adopters and 0 for non-adopters. For example, if the poison pill adopted
in 1986, the value of the dependent variable will be 1 for the adopting firm in 1986
and in future periods. However, the characteristics and properties of the firm is likely
to be different at the time of adoption of poison pill from the time after adoption. In
Shumway’s Hazard model, the dependent binary variable takes the value of 1 at the
time of adoption but reverts back to 0 after adoption. In effect, the dependent variable,
Adopt, will take on a value of 1 only for adopters in the year of the adoption. It will
take on a value of 0 for all non-adopters and for all adopters in non-adoption years. 9
The probit model used for self-selection bias correction is given below:
b0  b1axret  b2 axret1  b3 asg  b4 aliq  b5 alev  b6 Size 
Pr ob( Adopt  1)  F 

b7 mtb  b8 pe  b9 grdummy  b10idummy  b11 ln age   
(SS)
where F is the cumulative normal distribution, Adopt is the indicator of whether the
firm adopted poison pill in that year, axret is the average excess return over four years
before the adoption, axret1 is the average excess return over four years ending with
the year after adoption, asg is the average sales growth over the previous three years,
alev is the average leverage over four years before adoption, Size is the log of average
total assets, mtb is the market to book ratio of equity, pe is the ratio of price per share
to earnings per share, grdummy is the growth-resource mismatch indicator, idummy is
would result in using the firm attribute values only from the calendar year 2000 for the non-adopter
sample.
9
We have conducted tests after removing the adopting frims after their adoption of the poison pill. The
results are unchanged.
18
the indicator of whether there has been an acquisition in the same 4-digit SIC code
over the prior year and age is the age of the firm in years.
As discussed earlier, the Inverse Mills Ratio (IMR) is computed for each firm based
on (SS). IMR is used as a control variable in the regressions to correct for the selfselection bias.
Value Relevance
In this paper, we measure value relevance by the association of earnings and earningsrelated variables (such as change in earnings, discretionary accruals and nondiscretionary earnings) with contemporaneous stock return. Earlier studies such as
Ball and Brown (1968) and Beaver (1968) and subsequent work over the next two
decades defined value relevance of earnings by the “information” perspective wherein
earnings announcement was considered a source of new information. More recent
studies, however, have shifted their focus away from the information content
perspective to the view that earnings should serve as a summary measure of the
relevant events affecting the firm 10. The ability of earnings to summarize relevant
events is measured by the association of market returns with earnings and earnings
change. As Barth et al. (2001) point out, the key commonality in the definitions by
Beaver (1998, page 116) and Ohlson (1999) is that an accounting amount is value
relevant if it has a significant association with equity market value 11. Consistent with
this view, we measure value relevance as the association of the current earnings and
10
See Beaver (2002) on the relevance of the long-window earnings–returns design to examine the
value relevance of earnings.
11
Barth, Beaver and Landsman (2001) points out that value relevance literature is not limited to studies
motivated by questions of interest to standard setters.
19
current stock return. Primary arguments in support of this measure are also given in
Easton and Harris (1991), Easton (1999) and Barth et. al. (2001). We also control for
size, risk, leverage, growth and persistence variables. The risk measures control for
the effect of the firm’s risk on returns (which is market-adjusted). Leverage captures
the effect of the capital structure on returns. The model12 is given below:
R     X   Size   Beta   Leverage   mtb
it
1 it
2
it
3
it
4
it
5 it
  epsvol   epersist   Xchg  
6
it
7
it
8
it
it
(1)
In model (1), Rit is the market-adjusted stock return for the period spanning 9 months
before the fiscal year-end for the firm to 3 months after the fiscal year-end. The
earnings measure X it is the reported earnings before extraordinary items per share
deflated by the closing price Pit 1 . The control variables are measured as before.
Consistent
with
Ohlson
(1995),
we
include
the
change
in
earnings
XChgit= ( X it  X it 1 ) as an additional variable. We will refer to (1) as the basic value
relevance model. We estimate the coefficients of (1) for the year before and the year
after poison pill adoption for all the firms in the sample. Our measure of value
relevance is the sum of coefficients,  v  (1   8 ) . We test for the difference in this
coefficient before and after the adoption of poison pill using the following model that
includes the correction for self-selection bias.
12
We could control for value relevance by interacting each of the control variables with X and Xchg.
That would be consistent with the model used by Warfield, Wild and Wild (1995). However, in the
empirical test, such a model results in unacceptable levels of variance inflation factors. Therefore, we
control for value relevance by running Model (4) separately for different sub-samples that differ in the
levels of control variable.
20
Rit    1 X it   2 Size it   3 Betait   4 Leverageit   5 mtbit   6 epsvolit   7 epersist it
  8 XChgit   9 POSTit  10 POSTit * X it  11 POSTit * XChgit  12 IMRit   it
(2)
where POST and IMR are defined as in (1).
Value relevance might be affected by both the direct effect of managerial decisions on
discretionary expenditures and the indirect effect of managerial decisions on
discretionary accruals. We discuss below the measurement of discretionary accruals.
Discretionary Accruals
Our purpose in the measurement of discretionary accruals is whether these accruals
are affected by poison pill adoption and how these accruals are priced by the market.
Discretionary accruals can either be performance-signaling or performance-hiding
(For a good description, see Guay et al. 1996). Our research question does not
demand the decomposition of discretionary accruals into these two components. If the
discretionary accruals are performance-revealing, they will increase the association
between the income and firm-value-changes (captured by market returns). In other
words, they will increase value relevance. On the other hand, if they are performancehiding, the earnings determination process will not properly capture the valuechanging events and therefore the value relevance will decline. We measure
discretionary accruals computed using the modified Jones model (Dechow et al.
1995)13.
13
We do not use the performance-adjusted discretionary accruals (Kothari et al. 2005) because they
capture only the opportunistic part of discretionary accruals. It is possible that the poison pill adoption
will result in increased performance-revealing discretionary accruals and thereby affect value
relevance.
21
We calculate the following cross-sectional current accrual regression by each twodigit SIC code partition
Accrt  1 (1 / TAt 1 )   2 ( Re vt )  
(3)
Where Accrt is defined as the total accruals (Net income before extraordinary items
given by Compustat item 123 + depreciation and amortization given by Compustat
item 125 – operating cash flow given by Compustat item 308) scaled by the value of
total assets at the close of last year; Rev is the net sales given by Compustat item 12
and ∆Rev = Revt – Revt-1.
The estimates of the coefficients in equation (1) are used to calculate the expected
current accruals in the following equation:
EAccrt  ˆ1 (1 / TAt 1 )  ˆ 2 ( Re vt  AR)
(4)
Where EAccrt denotes the expected accrual; the “hats” denote the estimated
parameters from (3); and ∆AR is the change in Accounts Receivable (Compustat item
# 2) from t-1 to t. The discretionary accrual is measured as (Accrt-EAccrt).
Value Relevance of Discretionary Accruals
Subramanyam (1996) argues that the stock market attaches value to discretionary
accruals by showing that the contemporaneous association between discretionary
accruals and returns is positive and significant after controlling for non-discretionary
accruals. We test the direct pricing effect of discretionary accruals using Model 5 in
which the earnings, Xit in (2) is decomposed into DA and the non-discretionary
earnings, NDE, defined as X less DA.
22
Rit    1a NDE it  1b DAit   2 Size it   3 Beta it   4 Leverageit   5 mtbit
  6 epsvolit   7 epersist it   8 XChg   9 POST  10a POST * NDE it 
10b POST * DAit  11 POST * XChg  12 IMR   it
(5)
In Model (5), 10b measures the change in the value relevance of DA.
3.2 The Sample
Data on stockholder rights are disclosed on Form 8A that is filed with SEC pursuant
to rules 12(b) and 12(g) of the Securities Exchange Act of 1934. We obtain poison pill
data from Bryan (2002) who has compiled these filings. In all, 1,731 poison pill
adoption firms from 1980 to 2000 are listed in the database. We first eliminated from
this set 751 firms that did not have all the data required for the self-selection bias
correction on Compustat or CRSP. That left us with a sample of 980 firms. Out of
these, there were 168 firms that had missing data for the computation of the
association between earnings and returns. The remaining sample consists of 812
firms. The sample selection steps are shown in Panel A of Table 1.
The poison pill adoptions in our sample from 1980 to 2000 shown in Panel B of Table
1 reached a peak first in 1988 with 75 adoptions and after falling to a mere 13
adoptions in 1993, reached a second peak of 148 adoptions in 1996. This pattern is
similar to the pattern of poison pill adopters in the whole population.
Panel C of Table 1 gives the industry categorizations of the poison pill adopters and
descriptive data of size of poison pill adopters. We notice that more than half the
sample is from the manufacturing sector. The Transportation, Communication and
Utilities sector and Service Industries are the other main industries in the sample.
23
Panel D gives the yearly mean values of several firm-specific parameters from year –
1 (1 year before poison pill adoption) to +1 (1 year after poison pill adoption) for all
the adopters. Many significant patters are evident from this Panel. The mean stock
return shows a dramatic decline after the adoption, falling from 5.3% before the
adoption to 3.2% in the year of adoption and further falling to -.2% in the year after
adoption. However, the accounting measures of profitability, namely ROA and ROE
do not show similar declines. In fact, ROA shows a drop in the year of adoption but
increases to a positive 1.3% after adoption. These patterns in profitability suggest a
reduction in the relevance of accounting numbers in capturing the steep decline in
market returns after the adoption. The drops in the price-earnings ratio and marketbook ratio are consistent with market price declines that are steeper than the earnings
declines. The stock price, earnings and book value per share numbers do not show a
significant pattern. However, averaging these values over different firms makes it
difficult to interpret these numbers. The mean absolute values of modified Jones
discretionary accruals show significant increases from –1 to +1 both when they are
winsorized and when they are not winsorized. This pattern suggests that the earnings
management increases in firms adopting poison pills and that the outliers do not drive
this increase. The average sales, operating cash flow and net income, all show
significant increases after poison pill adoption.
Insert Table 1 here
3.3 Results
Probit Model for Self-Selection Bias Correction
Panel A of Table 2 gives the relative mean values of the variables that are used in the
probit model for the adoption sample and the non-adoption sample. The differences
24
and the t-statistics for the differences are also given. The adoption sample consists of
980 adoption event-years. The non-adoption sample consists of 73710 non-adoption
event-years. Univariate comparisons show that as expected, the adopters have lower
liquidity, lower sales growth, lower current and future excess returns, worse growthresource matching, higher propensity of acquisition in the industry, and higher age
than non-adopters in the adoption year. Contrary to expectations, the adopters have
higher price to earnings ratio in the year of adoption. It is likely that the higher price
to earnings ratio is a result of lower earnings in the adoption year, given that adopters
have lower sales growth and lower market-to-book ratio. All the variables other than
market to book ratio, size and leverage are significant.
Insert Table 2 here
The results of the probit estimation are given in Panel B of Table 2. All the
coefficients are consistent with the univariate results in panel A. Market to book ratio
and industry (acquisition) dummy are not significant. The model has a highly
significant likelihood ratio with a Chi squared of 2224. The Inverse Mills Ratio
computed from this model has an average value of .790 for non-adoptions and -.808
for adoption events. The difference is highly statistically significant. This has been
shown separately in Panel C of Table 2.
Value Relevance
Table 3 shows that the earnings, X, is significant and positive and the interaction
term, POST*X is negative and significant. This is consistent with our hypothesis of
reduced contemporaneous association between earnings and returns after poison pill
adoption. The change in earnings and its interaction with POST are not significant.
25
However, the sum of POST*X and POST*XChg is negative and significant. The
Inverse Mills Ratio is significant, which implies that self-selection was indeed an
issue that needed correction in this regression. Consistent with our expectation, beta
has a positive coefficient and leverage has a negative coefficient. Size has a positive
coefficient and the market-to-book ratio has a negative coefficient. The other control
variables are not significant.
Insert Table 3 here
Table 4 gives value relevance regression results separately before and after poison pill
adoption with Earnings and Change of Earnings. The sum of the coefficients of
earnings and change of earnings declines significantly after poison pill adoption.
Insert Table 4 here
The results in Tables 3 and 4 provide evidence of reduced value relevance of earnings
in firms after poison pill adoption. We next examine the role of the discretionary
accruals component in earnings in the decline of value relevance after adoption.
Table 5 shows the effect of poison pill adoption on value relevance of discretionary
accruals. It is seen that POST*DA has a significantly negative coefficient that
provides evidence that the value relevance of DA decreases significantly. It is also
interesting to note that after controlling for DA, the non-discretionary component of
earnings (NDE) also becomes significantly less value-relevant after adoption.
Together, these two results indicate that the value relevance of both components of
earnings decline after poison pill adoption.
Insert Table 5 here
26
In Table 6, the value relevance regressions are run separately before and after poison
pill adoption. Both the components of earnings, namely DA and NDE are
significantly priced by the market both before and after the poison pill adoption.
However, the decline in value relevance is significant for both these components.
Together, all earnings related variables, DA, NDE and XChg become significantly
less value relevant after the poison pill adoption.
Insert Table 6 here
The variance inflation factors in all the above regressions are well under 10. This
indicates that multi-collinearity does not affect the results14.
Table 7 gives the effect of size and product competition on value relevance change
(X+XChg) resulting from poison pill adoption. From the results, it is seen that the
value-relevance decline is significant for small firms but not for large firms. This is
consistent with the argument that the reported earnings continue to sustain their value
relevance for larger firms because their disclosures are more closely scrutinized but in
the case of smaller firms, the loss of value relevance is significant. The second part of
the Table gives the results for product competition. We measure product competition
by the Herfindahl-Hirschman Index (HHI- the sum of the market shares of each firm
competing in the same industry as demarked by the 2-digit SIC code).
Insert Table 7 here
The post-adoption value relevance for firms that face high product competition does
not decline (1.30 compared with 0.91) but the difference from the pre-adoption value
relevance is not significant. However, for firms that face lower product competition,
14
If we run the regressions with the control variables interacted with earnings, the variance inflation
factors become very high and the regression results (though they are consistent) are not reliable.
27
the value relevance drops significantly from 0.55 to 0.04. The value relevance in the
pre-adoption period for firms facing low competition is significant but it loses
significance after adoption. The difference in the pre to post-adoption value relevance
changes is also significant. This is consistent with our expectation that the decline in
value relevance is moderated by the competition in the product market.
Table 8 gives the value relevance effects separately for sub-samples split at median
levels of control variables that represent other firm characteristics, namely Leverage,
Market-to-book, Beta, epsvol and epersist and compare the value relevance declines
between the sub-samples.
Insert Table 8 here
The declines for both low-debt firms and for high-debt firms are significant. Yet, the
value relevance drop in low –debt firms is significantly higher than the value
relevance drop in high-debt firms. This is also consistent with the argument that the
disclosures of high-debt firms are more closely scrutinized than those of low-debt
firms. The value relevance drops significantly in the low market-to-book sub-sample
but increases in the high market-to-book sub-sample. Value relevance drop is
significant in the high-beta sub-sample but not in the low-beta sub-sample. Value
relevance drops significantly for firms in the high eps-volatility sub-sample but not
significantly for the low eps-volatility sub-sample. In a similar vein, value relevance
drops significantly for the high earnings persistence sub-sample but not significantly
for low persistence firms.
Additional tests
28
1. Effect of poison pill adoption on insider ownership, free cash flow and long
term investments
Our results show that earnings become less value-relevant after poison pill adoption.
Moreover, both the discretionary accruals component and the non-discretionary
component of earnings become less value-relevant. This is suggestive of a decline in
earnings quality after adoption. In these additional tests, we explore whether this
conclusion is supported by other measures such as the ownership by affiliated blockholders, free cash flows and the long term investments.
Our reasoning for choosing these measures is the following. Affiliated investors
(including executives and non-executive directors) are more likely to be informed
about the future prospects of the firm than other investors. Therefore, if poison pill
adoptions are associated with better (worse) prospects, we should expect a greater
(smaller) affiliated investor interest. Firms can sustain higher (lower) future growth
and profitability with higher (lower) free cash flow (defined as the residual operating
cash flow that is left after investments). Our third measure is the total long-term
investments measured as the sum of capital expenditures, acquisitions and
investments, scaled by the operating cash flow. If the adoption of poison pills is
motivated by a genuine interest in increasing long term investments, we should see an
increase in the long term investment as a percentage of the cash flows generated by
the firm.
In order to test for these effects, we use the following models:
DV    1 POST   2 IMR  
(6)
In the above regressions, the dependent variable DV, is the affiliated investor
ownership percentage, or the free cash flow scaled by average total assets or the long-
29
term investment scaled by operating cash flow. The results shown in Table 9 provide
evidence of a significant decline in the affiliated investor ownership and the free cash
flow. Further, increases in long term investments after the adoption of poison pill are
not significant. Overall, these findings further support the view that poison pill
adoptions are viewed by the market as more likely to harm future prospects than help
them. This lends further support to our finding that earnings and its components
become less value-relevant after poison pill adoption.
Insert Table 9 here
2. Changing the period of comparison: The period of analysis for the main test (-1,+1)
trades off the possible dilution of poison pill effect by other events in long windows
with partial loss of the effect in smaller windows. The results were not materially
different for (-2,+2).
3. Special Items analysis: The net income used in our tests of earnings management
and value relevance includes special items (Compustat data item # 17 that includes
restructuring charges and other non-recurring items). We test for any systematic
differences in the magnitudes and timings of special items between adopters and nonadopters before and after the adoption date. Prior to the adoption date, there is no
significant difference. However, after the adoption date, we find that the special item
magnitudes are lagged in the case of adopters compared to non-adopters. This result is
consistent with the argument that adopters are more likely to defer special items
expense (an income-increasing discretionary accrual choice) than non-adopters.
30
4. Effect of poison pill adoption on discretionary accruals: We examine the effect of
poison pill adoption directly on the magnitude of discretionary accruals using the
following model
DA     POST   IMR   Size   Beta   Leverage
it
1
it
2
it
3
it
4
it
5
it
  mtb   epsvol   epersist  
6 it
7
it
8
it
it
(7)
Where the dependent variable, DA is the absolute value of the Modified Jones
Discretionary accrual measure and other variables are defined as before. We find
(results are not tabulated) that discretionary accruals increase after poison pill
adoption (  1 =.02; t=1.87; p=.06). The increase in discretionary accrual magnitude
and the loss of its value relevance are consistent and suggestive of poison pill being
perceived in the market as a corporate governance weakness.
4. Conclusion
In this we find that firms that adopt poison pills exhibit a drop in value relevance of
earnings and both its components, namely discretionary accruals and nondiscretionary earnings. The lower association between earnings and its components
with the market returns suggests that the earnings determination process becomes less
able to summarize value-relevant events after poison pill adoption. The drop in value
relevance was insignificant in larger firms and for firms facing high competition in
the product market. Further, the drop in value relevance was significantly higher in
low-debt firms which do not have as much scrutiny by investors, lenders, analysts,
regulators and auditors as high-debt firms. The drop in value relevance was also
higher in low-growth firms, firms with low earnings persistence and higher earnings
volatility. All these findings are consistent with the proposition that the market views
31
poison pill adoption as a weakening of corporate governance and expects such
adoptions
to
hurt
rather
than
help
the
future
prospects
of
the
firm.
32
Appendix: Some excerpts from poison pills
1. Excerpt from the poison pill of Alltrista Corporation (incorporated in Indiana)
This is a typical poison pill provision that penalizes any person or group that,
together with his or its affiliates, acquires more than a certain percentage of the
outstanding common stock with the intention of controlling or influencing the
management or policies of the company. The poison pill was adopted on March
22, 1993 and further amended on May 7, 1999 and July 19, 2001.
“. . . if a Person or a group becomes the Beneficial owner of fifteen percent (15%)
or more of the outstanding Common stock, subject to certain exceptions, holders
of each Right issued under the Agreement (other than the Acquiring Person) will
have the right to purchase, upon payment of the exercise price of a Right,
Registrant’s Common Stock having a market value of two times the exercise
price”
In the above poison pill provision, all common stock holders other than the
Acquiring Person hold the right to purchase the common stock at half the market
price as on the date that the Acquiring Person crossed the 15% threshold. There
are exceptions to this rule laid out in the provisions. The company, its subsidiaries,
employee benefit plan of the company, a Person who comes to own more than
15% because of repurchase of outstanding common shares by the company and a
Person who inadvertently acquires more than 15% and certifies within 10 business
days that he (it) acquired the stocks inadvertently are exempted from the penalty
that applies to the Acquiring Person. (The use of the upper case letters indicates
that these terms are defined in the provision).
2. Amendment to the poison pill of American Water Works Company,
incorporated in Delaware (Amendment date: September 16, 2001)
This amendment exempts an acquirer from the penalties of the poison pill. In this
case, the management of the above company agreed to merge with Thames Water
Aqua Holdings GmbH, a German company.
33
“. . . The Rights Amendment provides that the execution, delivery and
performance if the Agreement and Plan of Merger dated Septermber 16, 2001, by
and among the Company, RWE Aktiengesellschaft, a company organized under
the laws of the Federal Republic of Germany (“RWE”), Thomas Water Aqua
Holdings GmbH, a company organized under the laws of the Federal Republic of
Germany (“Thames”), and Apollo Acquisition Company, a Delaware corporation
(“Sub”), will not cause RWE, Thames, Sub or any of their affiliates to become an
“Acquiring person” (as defined in the Rights agreement) nor give rise to a
“Distribution Date”, “Shares Acquisition Date” or “Triggering Event” (as each
such term is defined in the Rights Agreement).”
In effect, the poison pill provision penalizes those who acquire more than a
threshold percentage of stocks without the approval of the management. On the
other hand, when the management approves mergers or other changes, they
register an amendment to the poison pill provision to facilitate those changes.
.
34
Table 1: Poison Pill Sample Descriptive Data
Panel A: Sample Size
Poison pill adopting firms listed in Bryan (2000)
1731
Less: Missing data incomplete for computing Inverse Mills Ratio
751
980
Less: Missing data for computing other variables
168
Sample size
812
Panel B: Adoption By Year
Adoption year
Count
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
46
16
74
62
35
33
18
13
27
68
147
68
98
71
36
Panel C: Adoption By Industry
Description
Count
Agriculture, forestry, fisheries
Mineral Industries
Construction Industries
Manufacturing
Transportation, Communication, Utilities
Wholesale Trade
Retail Trade
Finance, Insurance, Real Estate
Service Industries
Other
2
43
3
462
98
31
55
15
98
5
35
Table 1 (Continued)
Panel D: Mean Values
Variables
Time = -1
Time = 0
Time = 1
N
715
812
755
Stock Return
5.1%
3.3%
-0.1%
Return on Equity
-3.2%
-4.8%
-2.0%
Return on Assets
1.6%
-2.6%
1.3%
Price to Earnings
18.9
19.4
15.3
Price to Book
3.3
2.9
2.5
Stock Price
24.93
25.38
24.97
Earnings per share
1.12
0.99
0.84
Book value per share
11.46
11.73
11.53
Absolute discretionary accruals (Modified Jones)
0.1085
0.1229
0.1338
Winsorized Absolute discretionary accruals
0.1037
0.1097
0.1212
Log of total assets
6.20
6.28
6.39
Log of market value of equity
6.15
6.16
6.21
Sales
1796
1889
2067
Operating Cash Flow
259
251
326
Net Income
90
84
104
Definitions of Variables
Stock Return = (Closing Stock Price at the end of the last day of t – Closing Stock Price at the end of
the last day of t-1)/ Closing Stock Price at the end of the last day of t-1
Return of Equity = [Net Income (172) – Preferred Dividends (19) – Common Dividends (21)]/ Average
Stockholders equity (60)
Return on Assets = [Net Income (172) + [1-Tax Rate]*Interest Expense (15) + Minority Income (49)]/
Average Total Assets, where Tax Rate = Tax Expense (16) / Pre Tax Income (170)
Price to Earnings ratio = Price per share (24) / Earnings per share (58)
Book Value per share = [Stockholders equity (216) – Preferred equity (130)]/Number of outstanding
shares (25)
Price to Book Ratio = Price per share (24) / Book Value per share
Discretionary Accruals (Modified Jones) = Discretionary accruals computed using the Modified Jones
Model
36
Table 2: The Probit Model For Separating The Adopters From Non-Adopters
Panel A: Descriptive Statistics Of The Probit Model Variables
The Model:
b0  b1axret  b2 axret1  b3 asg  b4 aliq  b5 alev  b6 Size  
Pr ob( Adopt  1)  F 

b7 mtb  b8 pe  b9 grdummy  b10idummy  b11 ln age   
Variable
Alev
Aliq
Asg
Axret
axret1
Grdummy
Idummy
Lnage
Mtb
Pe
Size
N
Nonadopter
0.917
0.349
1.548
0.000
0.000
0.429
0.925
2.642
3.317
14.277
3554.6
73710
Adopter
0.028
0.332
1.227
0.000
0.000
0.391
1.000
2.887
2.859
26.884
3324.4
980*
Difference
0.889
0.017
0.322
0.000
0.000
0.038
-0.075
-0.245
0.458
-12.607
230.2
t
1.2
2.4
3.5
6.2
3.4
2.4
-77.3
-11.1
1.3
-2.7
0.7
P value
0.215
0.017
0.000
0.000
0.001
0.016
0.000
0.000
0.211
0.008
0.512
*
We have used the largest sample with available data for the probit model. This includes but is
more than the final sample of poison pill adopters given in Table 1. Using the probit model on the
smaller sample gives similar results.
Definitions of the Variables
Adopt: Binary variable equals 1 if the firm adopted poison pill in the observation year; 0 otherwise.
(Takes the value of 0 both in case of non-adopters and in case of adopters during years when the
adoption did not take place)
alev: average leverage over three fiscal years prior to the observation year. Leverage is defined as Long
term debt (9) /[Common equity (11) +Preferred equity (10)]
aliq: Average liquidity over three fiscal years prior to the observation year. Liquidity is defined as
[Cash & marketable securities (1)-current liabilities (5)] / Total assets (6)
asg: Average sales growth over three fiscal years prior to the observation year. Sales growth in any year
t is defined as [(Sales in year t – Sales in year t-1)/Sales in year t-1], using annual data item 12 for Sales
axret: Average excess return per day over a period of four years before the observation year. Excess
return is defined as the firm’s actual return less the expected return from a two parameter market
model. The parameters of the market model are estimated using the data of the fifth year before the
observation year. The data on returns are drawn from CRSP daily stock return file.
axret1: axret of the year next to the observation year.
grdummy: This is the growth-resource dummy defined as a binary variable on the basis of three
variables: growth, liquidity and leverage defined above. The dummy variable is set equal to 1 if the
firm has a combination of either low growth-high liquidity-low leverage or high growth-low liquidityhigh leverage, where high and low refer to above or below median values. In all other cases, the
dummy variable is set equal to zero.
idummy: Industry dummy defined as a binary variable that equals 1 if there has been an acquisition in
the firm’s primary SIC industry during the year prior to the observation year. Otherwise, the variable is
zero.
lnage: The natural logarithm of the age of the firm as of the beginning of the observation year
mtb: The ratio of market value of common equity (24x25 ) to its book value (60), both measured at the
beginning of the observation year.
pe: The ratio of the stock price (24) to its basic earnings per share (58) at the beginning of the
observation year.
37
Size: Total assets (6) at the beginning of the observation year.
N: Number of observations
It should be noted that we did not consider average ROE as an alternative to axret (as in Palepu, 1986)
since we investigate the impact of pill adoptions on earnings, which in turn will affect ROE.
Panel B: The Probit Model Paremeter Estimation
Variable
Intercept
axret
axret1
asg
aliq
alev
size
mtb
pe
idummy
grdummy
lnage
Likelihood Ratio
Wald
Estimate
-6.24701
-17.38194
-3.68652
-0.00257
0.09267
-0.00046
-1.486
.4723
0.00025
3.49259
-0.04822
0.20074
ChiSq
0.41
142.40
13.72
1.68
7.48
5.56
20.78
0.32
71.87
0.13
10.41
781.66
2224
1093
p value
0.52
0.00
0.00
0.20
0.01
0.02
0.00
0.57
0.00
0.72
0.00
0.00
0.00
0.00
Panel C: The Inverse Mills Ratio (IMR)
IMR
Nonadopter
0.790
Adopter
-0.808
Difference
1.598
t
11298.1
P value
0.000
38
Table 3: Effect Of Poison Pill Adoption On Value Relevance Of Earnings
Model:
Rit    1 X it   2 Sizeit   3 Betait   4 Leverageit   5 mtbit   6 epsvolit   7 epersistit
  8 XChg   9 POST  10 POST * X it  11 POST * XChg it  12 IMRit   it
Variable
Intercept
POST
IMR
Size
Beta
Leverage
mtb
epsvol
epersist
XChg
POST *Xchg
X
POST *X
N
Adjusted R2
Estimate
-32.78
-0.01
40.42
0.06
0.06
-0.21
-0.004
0.002
-0.05
0.005
-0.002
0.57
-0.36
1441
0.1143
t
-8.75
-0.52
8.67
7.2
2.12
-2.39
-1.81
0.47
-1.04
0.19
-0.02
3.74
-2.02
p value
0.00
0.61
0.00
0.00
0.03
0.02
0.07
0.64
0.29
0.85
0.984
0.0002
0.04
The interactions with POST of X and Xchg, are in bold.
The white-adjusted t statistics give results that are consistent with the one presented above.
Definitions of the Variables
POST takes a value of 0 for years before adoption and a value of 1 for the years after adoption. The
year of poison pill adoption has been deleted from the sample. The pre-adoption and post-adoption
periods for this table are -1 and +1 respectively.
X: annual earning per share (53) / price per share (199) at t-1
XChg: change in X from t-1 to t
IMR: Inverse Mills Ratio
Size: Logarithm of the market value of equity (199x25)
Beta: The stock beta estimated using data from t-5 to t-1 in the two-parameter market model.
Leverage: [long term debt (9) + debt in current liabilities (34)]/Total Assets (6)
mtb: The ratio of market value of common equity (24x25 )to its book value (60)
epsvol: Standard deviation of the quarterly earnings per share (19) over the previous 16 quarters
epersist: Autocorrelation between quarterly earnings per share (19) over previous 16 quarters
N: Number of observations.
39
Table 4: Comparison of Pre and Post-adoption Value Relevance of Earnings and
Change in Earnings
R    1 X it   2 Sizeit   3 Betait   4 Leverageit   5 mtbit
Model: it
  6 epsvolit   7 epersistit   8 Xchg it   9 IMRit   it
Variable
Intercept
X
XChg
IMR
Size
Beta
Leverage
Mtb
Epsvol
Epersist
N
Adjusted R2
Pre-adoption
Post-adoption
Estimate
t
p value Estimate
t
p value
-35.86 -7.22
0.00 -30.28 -5.58
0.00
0.58 4.14
0.00
0.22 2.09
0.04
0.01 0.29
0.77
-0.01 -0.06
0.95
45.24 7.19
0.00
37.84 5.50
0.00
0.05 4.45
0.00
0.07 5.63
0.00
0.02 0.62
0.54
0.10 2.26
0.02
-0.22 -1.84
0.07
-0.21 -1.68
0.09
-0.01 -1.79
0.07
0.00 -1.23
0.22
0.00 0.28
0.78
0.07 1.38
0.17
-0.05 -0.79
0.43
-0.04 -0.61
0.54
705
745
0.11
0.12
Comparison of Coefficients: Post-Pre Adoption
Variable
Estimate
t
p value
X
-0.36 -2.14
0.03
XChg
-0.02
0.02
0.98
X+XChg
-0.38 -2.41
0.02
The white-adjusted t statistics give results that are consistent with the one presented above.
Definitions of the Variables
The pre-adoption and post-adoption periods for this table are -1 and +1 respectively.
X: annual earning per share (53) / price per share (199) at t-1
XChg: change in X from t-1 to t
IMR: Inverse Mills Ratio
Size: Logarithm of the market value of equity (199x25)
Beta: The stock beta estimated using data from t-5 to t-1 in the two-parameter market model.
Leverage: [long term debt (9) + debt in current liabilities (34)]/Total Assets (6)
mtb: The ratio of market value of common equity (24x25 )to its book value (60)
epsvol: Standard deviation of the quarterly earnings per share (19) over the previous 16 quarters
epersist: Autocorrelation between quarterly earnings per share (19) over previous 16 quarters
N: Number of observations.
40
Table 5: Effect Of Poison Pill Adoption On Value Relevance Of Discretionary
Accruals
Model:
Rit    1a NDE it  1b DAit   2 Sizeit   3 Betait   4 Leverageit   5 mtbit
  6 epsvolit   7 epersistit   8 XChg   9 POST  10 a POST * NDE it 
10b POST * DAit  11 POST * XChg it  12 IMRit   it
Variable
Estimate
t
p value
Intercept
-31.27
-8.63
0.00
POST
.026
.86
0.39
IMR
39.21
8.54
0.00
Size
0.07
8.35
0.00
Beta
0.05
1.60
0.11
Leverage
-0.27
-3.18
0.00
mtb
-0.005
-2.09
0.03
epsvol
0.002
.37
0.71
epersist
-0.04
-0.80
0.42
DA
0.44
2.35
0.02
POST*DA
-0.90
-4.28
0.00
NDE
0.87
5.12
0.00
POST *NDE
-1.25
-6.78
0.00
XChg
0.0016
0.06
0.95
POST *Xchg
0.55
1.25
0.21
N
1439
Adjusted R2
0.1436
The white-adjusted t statistics give results that are consistent with the one presented above.
Definitions of the Variables
POST takes a value of 0 for years before adoption and a value of 1 for the years after adoption. The
year of poison pill adoption has been deleted from the sample. The pre-adoption and post-adoption
periods for this table are -1 and +1 respectively.
X: annual earning per share (53) / price per share (199) at t-1
XChg: change in X from t-1 to t
DA: Absolute Discretionary accruals computed using the modified Jones method scaled by market
value of equity (199x25) at t-1
NDE: X – DA
IMR: Inverse Mills Ratio
Size: Logarithm of the market value of equity (199x25)
Beta: The stock beta estimated using data from t-5 to t-1 in the two-parameter market model.
Leverage: [long term debt (9) + debt in current liabilities (34)]/Total Assets (6)
mtb: The ratio of market value of common equity (24x25 )to its book value (60)
epsvol: Standard deviation of the quarterly earnings per share (19) over the previous 16 quarters
epersist: Autocorrelation between quarterly earnings per share (19) over previous 16 quarters
N: Number of observations.
41
Table 6: Comparison of Pre and Post-adoption results of Value Relevance
Regressions with Earnings decomposed into DA and NDE
Model:
Rit     1a NDE it   1b DAit   2 Sizeit   3 Betait   4 Leverageit   5 mtbit
  6 epsvolit   7 epersist it   8 Xchg it   9 IMR it   it
Variable
Intercept
DA
NDE
XChg
IMR
Size
Beta
Leverage
Mtb
Epsvol
Epersist
N
Adjusted R2
Pre-adoption
Post-adoption
Estimate
t
p value Estimate
t
p value
-36.27 -7.41
0.00
-31.24 -5.78
0.00
1.19 6.32
0.00
0.66 3.79
0.00
0.69 4.91
0.00
0.38 3.24
0.00
0.00 0.13
0.90
-0.11 -0.98
0.33
45.63 7.36
0.00
38.99 5.69
0.00
0.06 5.31
0.00
0.08 6.03
0.00
0.03 0.72
0.47
0.10 2.24
0.03
-0.28 -2.45
0.01
-0.24 -1.92
0.06
-0.01 -1.56
0.12
0.00 -0.97
0.33
0.00 0.36
0.72
0.05 0.94
0.35
-0.04 -0.67
0.50
-0.04 -0.54
0.59
704
744
0.15
0.13
Comparison of Coefficients: Post-Pre Adoption
Parameter
Estimate
t p value
DA
-0.53 -2.34
0.02
NDE
-0.31 -1.77
0.08
XChg
-0.11 -1.03
0.31
DA+NDE+XChg
-0.95 -2.73
0.01
The white-adjusted t statistics give results that are consistent with the one presented above.
Definitions of the Variables
The pre-adoption and post-adoption periods for this table are -1 and +1 respectively.
DA: Absolute Discretionary accruals computed using the modified Jones method scaled by market
value of equity (199x25) at t-1
NDE: annual earning per share (53) / price per share (199) at t-1 – DA
XChg: change in X from t-1 to t, where X is annual earning per share (53) / price per share (199) at t-1
IMR: Inverse Mills Ratio
Size: Logarithm of the market value of equity (199x25)
Beta: The stock beta estimated using data from t-5 to t-1 in the two-parameter market model.
Leverage: [long term debt (9) + debt in current liabilities (34)]/Total Assets (6)
mtb: The ratio of market value of common equity (24x25 )to its book value (60)
epsvol: Standard deviation of the quarterly earnings per share (19) over the previous 16 quarters
epersist: Autocorrelation between quarterly earnings per share (19) over previous 16 quarters
N: Number of observations.
42
Table 7: Change In Value Relevance For Adopting Firms Differentiated On The
Basis of Size and Product Competition
Value Relevance Change Estimates a
Variable: Size
Pre-adoption
Post-adoption
Increase (decrease) in
Value relevance
Variable: Competition
Pre-adoption
Post-adoption
Increase (decrease) in
Value relevance
Estimate
t
Below-Median Size
p value
Estimate
t
Above-Median Size
p value
0.58
0.20
3.54
5.10
0.00
0.00
0.93
0.62
2.02
1.57
0.04
0.12
-0.38
-2.25
0.02
-0.32
-0.52
0.60
High Product Competition (Low
HHIb)
0.91
3.68
0.00
1.30
12.33
0.00
0.39
1.44
0.15
Low Product Competition (High HHI)
0.55
2.95
0.00
0.04
0.98
0.33
(0.51)
-2.68
0.01
Definitions of the Variables
a
Value relevance is estimated as 1   8 in the following model.
Rit    1 X it   2 Sizeit   3 Betait   4 Leverageit   5 mtbit
  6 epsvolit   7 epersistit   8 Xchgit   it
b
HHI (Herfindahl-Hirschman Index) represents the product competition and is measured as the sum of
the squared value of the market shares of all firms in that industry (using a two digit SIC code). Market
share for each firm =sales (12)/total sales (12) for that industry. The low-high HHI split is along the
median value at t=-1
43
Table 8: Effect of Other firm Characteristics on the Relationship between Poison
Pill Adoption And Value Relevance Of Earnings
Value Relevance Estimates a
Variable: Leverage
Below-Median Leverage
Pre-adoption
1.05
3.40
Post-adoption
0.23
4.70
Increase (decrease)
-0.82
-2.63
Variable: MTB
Below-Median MTB
Pre-adoption
0.67
4.36
Post-adoption
0.05
1.17
Increase (decrease)
-0.62
-3.93
Variable: Beta
Below-Median Beta
Pre-adoption
Post-adoption
Increase (decrease)
Variable: Epsvol
Pre-adoption
Post-adoption
Increase (decrease)
Variable: Epersist
Pre-adoption
Post-adoption
Increase (decrease)
a
0.53
2.63
0.33
2.90
-0.20
-0.87
Below-Median Epsvol
0.33
0.95
0.89
10.84
0.56
1.59
Below-Median Epersist
0.73
3.62
0.19
4.66
-0.54
-2.65
0.00
0.00
0.01
0.00
0.24
0.00
0.01
0.00
0.38
0.34
0.00
0.11
0.00
0.00
0.01
Above-Median Leverage
0.46
2.51
0.35
3.38
-0.11
-0.50
Above-Median MTB
-0.11
-.20
1.47
13.02
1.57
2.84
Above-Median Beta
0.95
3.71
0.25
5.52
-0.70
-2.68
Above-Median Epsvol
0.76
4.43
0.02
0.45
-0.74
-4.19
Above-Median Epersist
0.56
2.09
1.14
4.31
0.58
1.53
0.01
0.00
0.61
0.84
0.00
0.00
0.00
0.00
0.01
0.00
0.65
0.00
0.04
0.00
0.13
Value relevance is estimated as 1   8 in the following model.
Rit    1 X it   2 Sizeit   3 Betait   4 Leverageit   5 mtbit
  6 epsvolit   7 epersistit   8 Xchgit   it
44
Table 9: Effect Of Poison Pill Adoption On Affiliated Block holdings, Free Cash
Flow And Long Term Investments
Model: DVit    1 POSTit   2 IMRit   it a
Dependent Variable, DV Variable
Proportion Of
Intercept
Ownership By Affiliated
Block-holdersc
POST
IMR
Free Cash Flow/Average Intercept
Total Assetsd
POST
IMR
(Capex+Acquisitons+Inv Intercept
estment) / Salese
POST
IMR
Estimate
p
Nb
Adjusted
R2
-110.76 -2.71 0.01
1.6%
837
-1.07 -2.33 0.02
143.36 2.74 0.01
3.90
5.75 0.00
1.5%
2603
-0.01 -1.63 0.10
-4.93 -5.72 0.00
-16.49 -6.51 0.00
2.0%
2640
0.02
21.19
t
0.99 0.32
6.57 0.00
Definitions of the Variables
a
DV is the dependent variable, which is either proportion of ownership by affiliated block-holders,
ratio of free cash flow to average total assets or the ratio of the sum of capex, acquisitons and
investment to sales.
POST takes a value of 0 for years before adoption and a value of 1 for the years after adoption.
IMR is the Inverse mills ratio
b
The pre-adoption and post-adoption periods for this Table are (-2, -1) and (+1,+2) respectively
c
The dataset used contains standardized data for block-holders of 1,913 companies. The data was
cleaned from biases and mistakes usually observed in the standard source for this particular type of
data. Block-holders' data is reported by firm for the period 1996-2001. The data cleaning procedure is
explained in detail by Jennifer Dlugosz, Rudiger Fahlenbrach, Paul A. Gompers, and Andrew Metrick
in their study "Large Blocks of Stocks: Prevalance, Size, and Measurement" and is available at
http://finance.wharton.upenn.edu/~metrick/data.htm.
d
Free Cash Flow was computed either as
i.
Total Funds from Operations (110) – Capital Expenditures (128) when Compustat data
item 318=1,2 or 3, which is prior to adoption of SFAS 95
ii.
Net Cash Flow from Operating Activities (308) – Capital Expenditures (128) when
Compustat data item 318=7, that is after adoption of SFAS 95
Average Total Assets for year t is the average of Total Assets (6) in years t-1, t
e
This is the sum of Capital Expenditures (128), Acquisitions (129) and Investments (113) divided by
Sales (12).
45
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