Do Firms Go Public to Get Acquired?*
Luyao Pana
December 5, 2013
Abstract
Among important motivations for firms to go public is to create an exit strategy for the insiders.
Theory suggests that going public can be an optimal first step in the process of selling a company.
I document evidence in support of this ‘double-exit’ strategy. My finding is two folds. First,
newly listed firms are more likely to be acquired within five years after being listed than are
seasoned firms. In my sample of U.S. IPOs conducted during 1980-2007, 27 percent of the new
issues are acquired within five years after the IPO, which is compared with the seasoned firm
counterpart of 17 percent. Second, as acquisition targets, IPO firms receive higher takeover
premiums than do comparable privately held targets and seasoned target firms. Consistent with
the double-exit strategy predicted by theory, my findings suggest that IPOs facilitate subsequent
sales of the companies and that the strategy is economically justified.
JEL classification: G24, G34
Key words: Initial Public Offering, Takeovers, Exit Strategy
*
I have benefited from valuable comments and suggestions from Paolo Fulghieri, Matti
Keloharju, Xianming Zhou, and seminar participants at the University of Hong Kong. All errors
are my own.
a
School of Economics and Finance, University of Hong Kong, Pokfulam Road, Hong Kong.
Tel.: (+852) 64364673; Email: [email protected].
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1. Introduction
Firms go public for various reasons. In addition to raising public capital and creating
liquidity for the shares, theory suggests another important motive: By allowing the initial owners
to cash out, going public serves as an effective channel for the insiders to exit. In particular, the
insiders can pursue a so-called “double-exit” strategy: To sell the shares in a takeover after the
company goes public. Zingales (1995) provides economic justification for this strategy: Selling
off cash flow rights of a minority stake to dispersed shareholders helps bargaining, in direct
negotiation with future buyers of the majority stake, over private benefits of control. Hsieh,
Lyandres, and Zhdanov (2011) further argue that an IPO benefits the firm as a potential
acquisition target by resolving its value uncertainty thus enabling it to credibly communicate its
value with the bidders. Therefore, going public can be an optimal first step of the process of
selling a company. This motivation establishes a link between a firm’s IPO and its subsequent
sale through acquisition.
In this paper, I empirically examine the double-exit motive by providing evidence on this
link. More specifically, I address two closely related issues: First, are newly public firms more
likely to be acquired than are comparable seasoned firms? If the double-exit strategy is indeed
used in practice, one expects to observe a higher likelihood of newly public firms being taken
over than that of seasoned ones. Second, do newly public firms, as an acquisition target, receive
higher takeover premiums than do comparable private and seasoned firms? A direct implication
of the theories is that the double-exit strategy allows the insiders to sell their shares at higher
prices than they could in alternative exit strategies. Hence, the test for the second issue will
further allow me to determine whether the double-exit strategy is justified economically.
Previous studies have empirically examined various issues regarding firms’ going public.
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These issues include the effects of IPOs on fund raising and long-term growth, capital
restructuring, and managerial incentives. In particular, more recent studies have investigated the
role of IPOs in facilitating subsequent acquisition activities. From a chief financial officers
survey, Brau and Fawcett (2006) report that the primary motivations for going public is to
facilitate aftermarket acquisitions and establish a market price for the firm. Consistent with this
finding, Celikyurt, Sevilir and Shivdasani (2010) document that, on average, firms conduct four
acquisitions within five years after their IPO. Similarly, Hovakimian and Hotton (2010) find that
over one third of newly listed firms enter the market for corporate control as an acquirer within
three years after the IPO. On the other hand, studies of the link between firms’ going public and
subsequent sales as a takeover target have been relatively limited. By examining a sample of
mutual thrifts IPOs, Ciccotello, Field, and Bennett (2001) report that 36 percent of the IPOs were
acquired within five years after being listed. On the other hand, Celikyurt, Sevilir and Shivdasani
(2010) find that only 4.4 percent of the IPO firms in their sample become an acquisition target
within five years after going public, which is significantly lower than a percentage of typically
above 10 percent for seasoned companies. However, given the different research questions of
their focus and hence the confined data, the results of these studies do not present direct evidence
on the link between the firm’s IPO and subsequent sales with respect to the double-exit strategy.
I examine a large sample of U.S. IPOs conducted during the period of 1980-2007. To
address the first issue, for the IPO sample I construct a matching sample of seasoned firms that
have been listed for five or more years, and have similar market capitalization and
market-to-book ratio. Consistent with the hypothesis that firms go public to facilitate subsequent
sales, I estimate the likelihood of newly public firms becoming an acquisition target at 27%,
which is about 10% higher than that for seasoned firms. Such a large difference is economically
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strong, statistically significant, and remains robust after controlling for firm characteristics and
governance factors. Compared with Ciccotello, Field, and Bennett (2001) and Celikyurt, Sevilir
and Shivdasani (2010), my results are obtained from a more comprehensive sample of IPOs and
from a matching sample comparison that helps minimize firm heterogeneity between new lists
and seasoned companies. I interpret my finding as evidence of the double-exit strategy being
used in reality.
I then address the second issue by analyzing acquisition premiums. For the double-exit
strategy to be economically justified, as predicted by theory, it needs to deliver higher values to
the selling insiders than two alternative exit strategies: To sell the firm as a privately held
company or until it becomes seasoned public firm. Some previous studies have examined closely
related issues, though none directly answers the research question here. Brau, Francis, and
Kohers (2003) find that selling the shares at the IPO offer price allows the firm’s insiders to
realize a premium relative to a direct sale through takeover. This finding, referred to as the IPO
valuation premium puzzle, identifies a higher IPO offer price than the corresponding private sale
price. It, however, does not justify the double-exit strategy in a practical sense because insiders
are constrained in immediate sales of new stocks and new stock prices are possibly subject to
investor sentiment and decline in the aftermarket (Ritter, 1991). Officer (2007) further
documents a 15% to 30% acquisition discount for unlisted targets relative to comparable publicly
traded targets. Without distinguishing between new and seasoned public firms, this finding does
not rule out the possibility that the acquisition values are lower for newly listed firms than for
seasoned firms. Indeed, because of relatively high uncertainty and investor sentiment, newly
public firms might be disadvantaged in acquisition valuation relative to seasoned target firms.
To examine acquisition premiums, I compare acquisition price multiples in two dimensions:
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I first compare the multiples of IPO targets with those of private targets, and then compare them
with those of seasoned targets. In both comparisons, I construct matching samples to minimize
firm size and industry heterogeneity. From the IPO-private comparison, I identify higher
acquisition multiples for IPO targets than for private targets; and from the IPO-seasoned
comparison, I further identify higher acquisition multiples for IPO targets than for seasoned
targets. My findings are consistent with Brau, Francis, and Kohers (2003) and Officer (2007), but
further show that selling the firm after it goes public and in the early years after the IPO delivers
higher values to the selling insiders than other exit strategies.
The remainder of the paper is organized as follows. Section 2 discusses the background and
the literature. Section 3 describes the data and sample. Section 4 examines evidence for the
double-exit strategy by comparing firms’ likelihood of getting acquired between IPOs and
seasoned firms. Section 5 examines acquisition premiums by comparing IPO targets with private
targets and seasoned targets, respectively. Section 6 provides concluding remarks.
2. Background and literature
The fundamental research question behind the issues of this paper is why firms go public.
Economic theory has given insights into firms' going public decision. The first and seemingly
apparent motive for the firm to go public is to raise public capital. By selling primary shares
from the IPO, the firm can raise equity capital to fund investment, thus facilitating the firm’s
long-term growth. The improved public information and enhanced ability to bargain with banks
associated with being public provide firms with easier access to the debt and loan markets (e.g.
Rajan, 1992).
In addition to raising capital, going public provides an important exit strategy for firms’
initial owners including private equity funds and venture capitalists. In particular, they can
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pursue the double-exit strategy: To sell their shares in a takeover after the company goes public.
Zingales (1995) argues that selling off cash flow rights of a minority stake to dispersed
shareholders helps bargaining, in a direct negotiation with future buyers of the majority stake,
over private benefits of control. Hence, the initial owner can maximize the proceeds in the
eventual sale of his company. Mello and Parsons (1998) suggest that an IPO helps reveal
information about the demand for dispersed shares and the market's assessment of the value of
the firm, which is useful for sellers in negotiating the terms of a sale to an active investor. Hsieh,
Lyandres, and Zhdanov (2011) contend that an IPO benefits the firm as a potential acquisition
target by resolving its value uncertainty thus enabling it to credibly communicate its value with
bidders.
Other theories of going public are also proposed. For example, according to Holmström and
Tirole (1993), managerial incentive considerations are important in driving the IPO decision, for
publicly listed companies can use incentive schemes such as stock-value based incentive pay and
stock options that are unavailable to private companies. Subrahmanyam and Titman (1996) argue
that going public can improve investment decisions through information production by outside
investors. Chemmanur and Fulghieri (1999) propose a similar information production argument:
because a firm’s market value reflects all available information, going public reduces the need
for all investors to engage in costly duplicative information production.
A number of empirical studies have been conducted to examine various issues regarding
firms’ going public decisions. Depending on the major issues addressed, the empirical literature
can be loosely divided into three strands. The first strand focuses on the role of IPOs in raising
capital to fund investment and growth. By examining a sample of Italian firms, Pagano, Panetta
and Zingales (1998) find that firms tend to time the market in their IPO and, importantly, that the
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new equity capital raised upon listing is not used to finance subsequent investment and growth,
but to reduce leverage. Using a large sample from 38 countries, Kim and Weisbach (2008)
examine the use of funds raised in IPOs and SEOs. They conclude that financing investments
and exploiting market misvaluation are important motivations for firms to issue public equity.
Chemmanur, He, and Nandy (2010) find that firms’ product market characteristics such as
concentration, risk, liquidity, and information asymmetry have significant impact on their
going-public decision.
The second strand of the empirical literature focuses on the role of going public in
facilitating subsequent acquisitions. There are apparent reasons for this role; in addition to
providing a fusion of cash as acquisition funding and creating publicly traded stock as potential
acquisition currency, IPOs give firms access to the public equity and debt markets and thus
sources of external capital for acquisitions. From a survey on chief financial officers, Brau and
Fawcett (2006) find that facilitating acquisitions and establishing the firm’s market value are the
top two considerations in firms’ going public decision. Their findings have stimulated recent
studies to examine acquisition activities by newly listed companies. In a sample of IPOs with
high proceeds, Celikyurt, Sevilir and Shivdasani (2010) document that, on average, firms
conduct four acquisitions within five years after their IPO, and that acquisitions are as important
as R&D and capital expenditures to firms’ long-term growth. By examining a larger sample of
IPOs over a longer period, Hovakimian and Hotton (2010) find that over one third of firms enter
the market for corporate control as an acquirer within three years after their IPO. Similarly, Brau,
Couch and Sutton (2012) report that about one third of IPOs in their sample conduct at least one
acquisition before the first IPO anniversary.
The third strand of the empirical literature examines subsequent sales of IPO firms. As
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discussed above, Zingales (1995), Mello and Parsons (1998), and Hsieh et al. (2011) all provide
theoretical justification for cashing out in post-IPO sales. A direct implication of these theories is
that IPO firms are more likely to become an acquisition target than seasoned firms. Empirical
findings regarding this implication are mixed. From their sample of Italian firms, Pagano,
Panetta, and Zingales (1998) identify an increase in turnover of control after the IPO. Ciccotello,
Field, and Bennett (2001) examine mutual thrifts IPOs and find that 36% of the sample firms
were acquired within five years after being listed. On the other hand, Fama and French (2004)
document that the 10-year delisting rate for merger and acquisition reasons is lower for their IPO
sample than for their sample of seasoned firms that have been listed for more than five years.
Celikyurt, Sevilir and Shivdasani (2010) report that only 4.4% of IPO firms in their sample
become an acquisition target within five years after going public, which is lower than typically
above 10% for seasoned companies. However, because the major concern of these studies are not
the double-exit motive, they suffer from apparent data limitations. For example, both Pagano et
al. (1998) and Ciccotello et al. (2001) use a small sample of fewer than 100 firms; Celikyurt et al.
(2010) focus on large IPOs with total proceeds equal to or greater than $100 million; Fama and
French’s (2004) sample includes penny stocks that have a high delisting rate for non-M&A
reasons while being more frequent with IPOs. On the other hand, this study is based on a general
sample of IPOs, the relatively high acquisition likelihood of which is derived from a close
comparison with comparable seasoned firms, controlling for various firm characteristics and
governance variables.
This paper is also related to literature on profitability associated with various exit strategies.
In examining the choice between IPO and takeover, Brau, Francis and Kohers (2003) find that
insiders who choose the IPO route tend to earn a greater premium than insiders who sell out to
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acquirers. They argue that the observed IPO valuation premium can be attributable to a lower
liquidity provided by IPOs than by takeovers to the selling insiders. Similarly, Poulsen and
Stegemoller (2008) document a higher valuation multiple, measured by market value to book
value of assets and market value to book value of sales, for IPOs compared to acquisitions. On
the other hand, Bayer and Chemmanur (2012) find that the IPO valuation premium shrinks or
even vanishes after controlling for observable factors affecting firms' propensity to choose IPO
or acquisition and the long-term component of the expected payoff to insiders from an IPO exit.
In addition to a direct sale or an IPO, insiders can also exit through a takeover subsequent to
the IPO. Koeplin, Sarin and Shapiro (2000) find that private firms are acquired at an average
20%-30% discount relative to similar public companies when using earnings as the basis in
calculating valuation multiples. More recently, a 15%-30% acquisition discount associated with
unlisted targets is documented by Officer (2007), who further interprets the valuation discount as
the higher cost for unlisted firms in obtaining liquidity. Different from Koeplin et al. (2000) and
Officer (2007), I split public targets into IPO and seasoned targets and examine the effectiveness
of double-exit strategy through a comparison of acquisition premium between IPO targets and
private and seasoned counterparts, respectively.
3. Sample and data
I obtain data on IPOs from the Securities Data Company (SDC) New Issues Database. To
make sure that all M&A activities by IPO firms can be tracked for five years, I focus on IPOs
conducted from 1980 to 2007. Following a standard process, I exclude from the initial sample
real-estate investment trusts (REITs), limited partnerships, closed-end funds, penny stocks (with
offer price less than $5), unit offers, financial firms (with SIC code from 6000 to 6999). I also
require firms to have financial data in Standard and Poor’s Compustat database for the IPO year
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and stock return data from the Center for Research in Security Prices (CRSP) database within 3
months after the IPO. The final sample consists of 4,490 IPOs.
I then construct a sample of matching seasoned firms. Following Lyon, Barber and Tsai
(1999), for each IPO, I identify all seasoned firms (which have been listed on CRSP for at least
five years prior to the IPO) of market capitalization within the 70% to 130% range of that of the
IPO, and choose the one with the closest market-to-book ratio as the matching seasoned firm.
This one-for-one matching process results in 4,411 pairs of IPOs and seasoned firms.
Firms’ financial data are obtained from Standard and Poor’s Compustat, and stock return
data from CRSP. As in Fama and French (2004), I use the CRSP delisting code to determine the
reason for firm delisting, which is either due to takeover (as being acquired) or due to other
reasons (mainly liquidation). Survived firms have a delisting code between 100-170, delisted
firms due to takeover have a delisting code between 200-399, and firms delisted for other causes
has a delisting code of 400 and above.
Corporate control factors such as stock ownership by large shareholders and takeover
defense are important determinants of takeovers. I obtain the information of stock ownership by
the firm’s largest institutional blockholder (which is defined as to own at least 5 percent of a
firm’s outstanding shares) from the SEC 13f filings collected by Thomson Reuters. I further
manually collected the information on staggered board from firms’ proxy filings posted on
EDGAR. I leave a more detailed discussion of the corporate control variables to the next section.
Summary statistics of selected firm financial and governance variables are presented in
Table 1. By construction, the two groups of firms have very similar assets, market capitalization,
and market-to-book ratio. However, they differ significantly in other firm variables. Newly
public firms have significantly higher liquidity and sales growth, and lower leverage, property,
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stock return and blockholder ownership. It is interesting to note that IPO firms are more likely to
adopt a staggered board than seasoned firms. This appears to be inconsistent with the finding of
Field and Karpoff (2002); by examining a sample of IPOs conducted between 1988 and 1992,
they find that only 36.2% of the IPOs have a staggered board while the percentage is as high as
55.4% for the seasoned counterparts. On the other hand, Bebchuk and Cohen (2005) documents
an overall percentage of around 60% for firms having a staggered board, which is close to our
number of 54%.
4. The likelihood of getting acquired: IPOs vs. seasoned firms
Table 2 presents the statistics of firms’ survival and delisting within five years after the
corresponding issue date. The number (and frequency in parentheses) of firms are shown for the
firms survived, delisted due to acquisition, and delisted for other reasons, separately, with a
comparison between IPOs and seasoned firms. The numbers show a notably large difference in
the percentage of delisted companies as being acquired, which overall is 27.1% for IPOs and
16.9% for seasoned firms. The around 10% difference are observed in all sample subperiods.
This result is in contrast to that documented by Fama and French (2004), who find that the
10-year delisting rate for acquisitions is lower for IPO firms that went public between 1973-1991
than for seasoned firms. Notice that the IPO sample of Fama and French (2004) includes penny
stocks that have very high rate of being delisted for liquidation, the delisting rate for acquisition
of the penny stocks, and thus the overall sample, is squeezed. It is also observed from Table 2
that IPO firms are also more likely to be delisted for other causes than the seasoned counterparts.
However, as this difference is relatively modest, the difference in survival rate between the two
samples is thus largely determined by that in takeover delisting.
Table 3 presents further statistics for each post-IPO year. The numbers reveal significantly
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stronger tendency for IPO firms to get acquired. Except for the IPO year, around 8% IPO firms
become acquisition targets each year, which is compared with the matching seasoned firm
counterpart of around 4%. Consistent with the observation from Table 2, the difference in the
rate of being delisted for other causes is relatively small between the two samples.
The delisting rate for the IPO year should be interpreted with caution. To find matching
counterparts, all firms are required to have financial data at the first fiscal year following the IPO.
As a result, the statistics for delisted firms of the first year are only for those that are acquired or
liquidated in the year but still remain non-delisted by the end of the fiscal year (so their financial
data would still be included in the SDC database). Because this problem affects all delisted firms
(acquired or liquidated) and IPOs and seasoned firms alike, the delisting numbers of this year are
all small and do not show any meaningful patterns.
To show that the IPO-seasoned difference in the frequency of being acquired is not driven
by firm characteristics, I proceed with multivariate regression analysis focusing on the difference
between the two groups of firms. To avoid delisting effects caused by non-acquisition related
factors, I further exclude from the sample delisted firms due to non-acquisition reasons. The final
sample I use in the regression analysis consists of 3,848 IPO firms and 4,050 seasoned firms,
which is further reduced by missing firm variables. As in previous studies (e.g., Palepu, 1986;
Ambrose and Megginson, 1992; Song and Walking, 1993; and Field and Karpoff, 2002), I use a
logit model in which the dependent variable is dichotomous, having a value of one if the firm is
acquired within five years after the corresponding issue date, and having a value of zero
otherwise.
As in Field and Karpoff (2002), control variables are used to capture effects of firm size,
leverage, growth, liquidity, and stock return. Issue year dummy and industry dummy are also
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included. Firm size (assets), leverage and market-to-book ratio are in the first fiscal year
following IPO; liquidity (the ratio of current assets minus current liabilities to total assets) and
growth (of sales) are the average ratio for the three years before acquisition for firms that are
acquired, and for years 3 to 5 relative to the IPO for the firms that are not acquired; stock return
is the abnormal cumulative stock return for the three years after the IPO or up to two months
before the acquisition announcement for those firms that are acquired within three years, using
the equally weighted CRSP index as the market portfolio.
Two variables are used to capture the effects of corporate control factors. The first variable
is stock ownership held by the firm’s largest institutional blockholder, which can be considered a
proxy for internal corporate control. Shleifer and Vishny (1986) point out that large shareholders
are effective monitors, so the value of their effective monitoring should contribute to the gains
realized in takeovers. Hence, this role of large shareholders makes the firm as a takeover target
more attractive to potential acquirers. The second variable is a dummy variable for firms with
staggered board. Field and Karpoff (2002) document that IPO firms are associated with weaker
antitakeover provisions than seasoned firms, and that antitakeover provisions play a significant
role in deterring takeovers. The G-index that includes 24 antitakeover provisions and E-index
that includes 6 provisions are often used to characterize the intensity of the firm’s antitakeover
defenses. Constrained by data availability,1 I focus on one key antitakeover provision: staggered
board, which, as emphasized by Gompers, Ishii and Metrick (2003), Bebchuk and Cohen (2005),
1
The source of firm-specific antitakeover provisions based on which G-index and E-index are derived was
formerly Investor Responsibility Research Center (IRRC) publications compiled by GIM, which, after being
acquired by ISS Governance Services in 2005, is now belonged to RiskMetrics database. The database provides
detailed information on firm's antitakeover provisions since 1990. For the first few years the database covers
approximately 1500 firms including S&P 500 index and the annual lists of the largest corporations published by
Fortune, Forbes and Business week. The sample is expanded in 1998 to include small firms and firms with high
level of institutional ownership (see Masulis, Wang and Xie, 2007). As the result of its limited coverage on small
firms, the database covers only around 10% of my IPO sample.
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and Masulis and Wang and Xie (2007), is considered the most effective in deterring takeovers.2
Because EDGAR posts start from 1996 and became more complete since 1997 (and, for the same
reason, the coverage of Thomason Reuters on 13f filings has greatly improved after 1997), the
two governance variables, blockholder ownership and stagger board, only cover the subperiod of
1997-2007.
In addition, I also include state dummy variables to allow inter-state differences in
antitakeover laws, which covers the whole sample period. The information of the state in which a
firm is incorporated is obtained from Compustat. By using state dummy variables, Boulton (2010)
find a significant effect of state-level antitakeover statutes on deterring takeovers.
Table 4 presents logit regressions for the likelihood of firms getting acquired, where the
dependent variable equals one if the firm was acquired within five years after the IPO date and
equals zero otherwise. To minimize potential outlier effects, in all regressions I winsorize the
sample by removing 1% extreme observations. The results in Table 4 reveal significantly higher
tendency for IPO firms to get acquired within five years after their issue date. The coefficients on
IPO dummy are all statistically significant and economically strong. Based on the three
specifications keeping control variables at their respective mean values, the IPO firms present a
range of 28.1%-30.2% likelihood of a five-year acquisition, which is much higher than the very
narrow range presented by matching seasoned firms of 18.3%-18.4%. The difference of
acquisition likelihood is highest, at 11.8%, when least control variables are included (column (1))
and decreases modestly with the number of control variables. When firm characteristics variables
and state dummy are included, the difference shrinks to 9.8% (column (3)) and remains
2
According to Gompers, Ishii and Metrick (2003), A staggered board (or classified board) is one in which the
directors are placed into different classes and serve overlapping terms. Since only part of the board can be replaced
each year, an outsider who gains control of a corporation may have to wait a few years before being able to gain
control of the board. This slow replacement is one of the few provisions that clearly retains some deterrent value in
modern takeover battles.
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significant at 1% level. As industry and year effects, firm characteristics and state effects all
cannot capture the difference in acquisition likelihood between IPO and seasoned firms, the
difference is robust and suggests a systematic use of double-exit strategy in practice.
Most of the control variables have significant effects on acquisition likelihood. As a
reconciliation of Plepu (1986) and Song and Walkling (1993) who document that acquisition
likelihood is negatively related to firm size, and Field and Karpoff (2002) who find a positive
relationship, I include the natural logarithm of assets (ln(assets)) and its quadratic term. The
coefficients on ln(assets) and its quadratic term are both significant, reflecting a
inverted-U-shaped relationship with acquisition likelihood. This is consistent with the arguments
from both sides that large firms are associated with high transaction costs in acquisitions and
small firms may be too trivial to attract bidders. Therefore, firms that are too large or too small
are less likely to become acquisition targets.
Consistent with some or all of the prior findings (of, e.g., Palepu, 1986; Ambrose and
Megginson, 1992; Song and Walking, 1993; Field and Karpoff, 2002), the coefficients on growth
are significantly positive, and on market-to-book ratio and stock return significantly negative.
Different from all these studies, however, I find a significantly positive effect of leverage on
acquisition likelihood. Overall, these findings suggest that firms with poor performance (as
measured by low stock return) and severe financial conditions (as measured by high leverage)
are vulnerable to takeovers, and those with high growth in sales and low market value are
attractive to bidders in acquisitions.
Table 5 presents subperiod regressions. I consider three periods: 1980-1989, 1990-1996, and
1997-2007. This analysis is useful for me to clarify whether the results from the whole sample
regressions are driven by some specific time period. In addition, the regressions for the subperiod
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of 1997-2007 further allow me to control for the governance factors, blockholder ownership and
staggered bard, of which the data are only available for this subperiod. As in the whole period,
the coefficients on IPO dummy are significantly positive in all subperiods. The magnitude of the
coefficients on IPO dummy is at a similar level to that for the whole period and shows a
increasing pattern overtime. The coefficient on IPO dummy decreases as the two corporate
governance variables are included, capturing a difference in five-year acquisition of 7.4% (in
column (4)), but remains significant at the 1% level. This result indicates that the observed
difference in acquisition likelihood is not driven by specific subperiods and cannot be fully
captured by corporate governance factors. Relevant literature have covered various periods (e.g.
Fama and French (2004) covers years 1973-1991; Celikyurt et al. (2010) covers years
1985-2004). However, none of them find a higher acquisition likelihood for IPO firms.
In column (4), the coefficient on blockholder ownership is insignificant. While the
coefficient on staggered board dummy is positive and significant at the 10% level. This is
counter-intuitive and in contrast to findings of existing literature that document an efficient role
of firm-level antitakeover provisions in deterring takeovers. In an attempt to figure out the
sources of the positive relationship, I run a regression that include an interaction term of
staggered board dummy and IPO dummy and, in addition, an interaction term of largest
institutional blockholder ownership and IPO dummy. The regression results presented in column
(5) reveal remarkably different effect of staggered board on acquisition likelihood between IPO
and seasoned firms. In particular, while staggered board exhibit some effect on deterring
takeovers for IPO firms (as presented by the negative sign of the sum of the coefficient on
staggered board and that on the interaction term of staggered board and IPO dummy), it is
strongly and positively related to acquisition likelihood for seasoned firms. Combining this with
15
the fact that a higher proportion of IPO firms have staggered board, an overall positive effect of
staggered board in column (4) unfairly lowers the magnitude of the coefficient on IPO dummy.
The positive relationship between staggered board and acquisition likelihood for seasoned firms
probably indicates the endogenous nature of the staggered board and, perhaps, other antitakeover
provisions, that firms that are more vulnerable to takeovers are more inclined to use takeover
defenses.
Taken together, the results of the acquisition likelihood analysis suggest a significantly
higher likelihood of a five-year acquisition for IPO firms relative to comparable seasoned firms.
The difference cannot be captured by regular firm characteristics and corporate governance
mechanisms. Nor can it be attributable to specific time periods. This finding lends support to the
IPO motives in double-exit strategy, i.e. firms tend to go public for an eventual sale.
5. Acquisition premium
Above results have shown that newly public firms are more likely to be acquired than
comparable seasoned firms. While this IPO-seasoned difference is not explained by firm
characteristics and governance factors, it is consistent with the motive of insiders to exit through
post-IPO takeovers. Then, a further issue is whether this exit strategy pays relative to alternative
exit strategies such as selling the shares in a direct sale of a privately held company or after the
firm becomes a seasoned public company. To address this issue, in this section I examine
acquisition premiums realized by target firms, comparing IPOs with private targets and seasoned
targets, respectively.
5.1. IPO targets vs. private targets
To compare IPO targets and private targets, I need to focus on the subample of IPO takeover
16
targets that were acquired within five years after the IPO, and construct a matching sample using
private targets. Because all target firms need to have necessary financial data from the SDC
database, I identify the takeover sample from SDC using the criteria described below, which are
more restrictive than the CRSP delisting code used in the previous section. Following Netter,
Stegemoller and Wintoki (2011) and others, I impose the following requirements to screen the
original takeover sample from the SDC Mergers and Acquisitions Database: (i) Acquisitions
made by U.S. public acquirers between January 1, 1980 and December 31, 2012; (ii) all
acquisitions with or without disclosed deal value (with deal type of 1 or 2); (iii) completed deals;
(iv) 50% or more of total shares acquired in transaction; and (v) 90% or more of total shares
owned by the acquirer after transaction. This screening results in total 49,660 takeovers, of which
736 are IPO targets.3 For matching purposes, I require a target to have information on the deal
value and the value-to-sales ratio,4 which further reduces the sample to 712 IPO targets.
I then identify matching private targets. After excluding public targets, limited partnerships,
leveraged buyouts, and deals with missing deal value and missing deal value to sales, I obtain
5,442 acquisitions of privately held companies from the SDC takeover sample, which are used to
match with the IPO targets for announcement year, firm size, and industry. Specifically, for each
IPO target, I choose the matching private target by requiring it to be in the same year of
acquisition (according to announcement), in the same two-digit SIC industry, and to have the
closed sales within 50% to 150% of the IPO target’s sales. The resulting sample contains 436
3
The limited coverage of delisted firms by SDC takeover sample can be attributable to the incomplete
coverage of SDC database per se (Netter, Stegemoller and Wintoki (2011) points out that only after 1992 does SDC
database cover deals of any value, including unreported values. Therefore, the SDC coverage of M&A deals is very
limited before 1992), and a further shrinkage in the aggregate sample as the result of the restrictions I imposed in
selecting the SDC takeover sample.
4
I use these variables to calculate firms' sales prior to acquisition announcements, using the formula sales=
deal value/(ratio of deal value to sales× proportion of shares being acquired in the transaction).
17
pairs of matched IPO targets and private targets5.
As in Officer (2007), I use four financial variables based acquisition multiples as the
measures of takeover premium, which are offer price to book value of equity, offer price to
earnings per share, deal value to sales, and deal value to EBITDA. All acquisition multiples are
provided by the SDC Mergers and Acquisitions Database, which are calculated using the
financial information as of the date of the most current financial information prior to the
acquisition announcement and for which the deal value is adjusted for the proportion of shares
being acquired in the transaction. Table 6 presents the acquisition multiples for the matched
sample of newly public targets and private targets. To minimize the potential outlier effects, I
winsorize the data by removing the top and bottom 1% extreme acquisition multiples. For both
the IPOs and private targets, the mean of each acquisition multiple is higher than the median,
indicating that the distributions of the multiples are skewed to the right. For this reason, I will
emphasize the median numbers in the comparison.
Except the multiple of offer price to book equity, the median numbers for the IPO-private
difference from the other three multiples are all significantly positive. In other words, while IPO
targets are associated with significantly higher offer price to EPS, deal value to sales and deal
value to EBITDA, they have significantly lower offer price to book value of equity relative to the
private counterparts. The inconsistent evidence revealed by the offer price to book value of
equity with other acquisition multiples is not a coincidence. Officer (2007) presents significant
acquisition discounts for private targets with respect to all acquisition multiples other than the
offer price to book value of equity. While Officer (2007) does not provide any explanation, I
5
Except for the ratio of deal value to sales, other acquisition multiples have missing values in both samples.
When comparing these multiples, I remove the pairs of observations that have missing relevant multiple in one or
both of the samples to make sure that the two samples of targets are perfectly matched with regard to each
acquisition multiple.
18
argue that an IPO per se significantly increases book value of equity per share of a firm, making
the multiple based on this financial data unfairly lower and therefore not comparable before and
after a firm goes public. On the other hand, because an IPO does not have direct effects on the
other fundamental measures, the multiples based on which can properly reflect the relative
valuation between targets that have different public status. As the result, in the comparison of
acquisition multiples between IPO and private targets, I focus on offer price to EPS, deal value to
sales and deal value to EBITDA.
Table 7 present the regression analysis for the comparison of acquisition multiples between
IPO and private targets. In each regression, the dependent variable is an acquisition multiple and
the IPO target dummy is the key independent variable capturing the acquisition premium on IPO
targets relative to private targets. Following previous studies of valuation of acquisitions and exit
strategies, including Brau, Francis and Kohers (2003), Moeller (2005), Officer (2007) and Bayar
and Chemmanur (2012), I include in the regressions several commonly used control variables.
These variables control for target firm characteristics, such as size, leverage, and industry,6and
deal specific factors, such as acquisition attitude (hostile takeover), method of payment (fraction
of pay in cash), and acquirer-target relationship (within-industry acquisition). All variables are
directly obtained from the SDC Mergers and Acquisitions Database with the financial data of the
fiscal year or quarter immediately prior to the acquisition announcement.
Consistent with the result from the univariate analysis, the multivariate regressions in Table
7 estimate a generally positive coefficient on the IPO dummy, which suggest higher acquisition
values associated with IPO targets. The coefficients on the IPO target dummy are significantly
6
Following Harford, Humphery-Jenner and Powell (2012), high-tech firms include computer hard ware (SIC
codes 3571, 3572, 3575, 3577, 3578), communications equipment (3661, 3663, 3669), electronics (3671, 3672, 3674,
3675, 3677, 3678, 3679), navigation equipment (3812), measuring and controlling devices (3823, 3825, 3826, 3827,
3829), medical instruments (4812, 4813), telephone equipment (4899), and software (7371, 7372, 7373, 7374, 7375,
7378, 7379).
19
positive when the multiples of offer price to EPS and deal value to sales are used, and
insignificantly positive when the deal value to EBITDA multiple is used. Notice that the sample
size of the regressions on offer price to EPS and deal value to EBITDA are very small (in both
cases, only around 60 observations are contained in each sample of targets), the significance of
the coefficients on IPO target dummy can have been understated. Among the control variables,
only target size measured by natural logarithm of target sales has significantly negative effect on
acquisition multiples. An obvious explanation for the negative effect is that sales directly or
indirectly increase the denominators of these acquisition multiples. The coefficients on other
control variables are not significant.
That IPO targets are associated with significantly higher acquisition valuation relative to
private targets confirms the predictions of the theories of Zingales (1995), Mello and Parsons
(1998), and Hsieh, Lyandres, and Zhdanov (2011). From the angles of revealing information and
resolving valuation uncertainty, these theoretical studies all suggest that an IPO helps insiders
realize higher return in a subsequent sale than a private sale. My results are also consistent with
the empirical evidence of Koeplin, Sarin and Shapiro (2000) and Officer (2007) that public
targets as a whole earn a premium in acquisitions compared with private targets. However, by
comparing the acquisition multiples of private targets with IPO counterparts, I rule out the
possibility that the previously documented public valuation premium is driven by seasoned
targets.
5.2. IPO targets vs. seasoned targets
Both Koeplin, Sarin and Shapiro (2000) and Officer (2007) identify a valuation discount of
private targets relative to comparable public targets. That is, these studies have already
established that, overall, public targets are sold with a premium relative to private targets.
20
However, an important question remains unanswered: Is there any difference in the acquisition
value between newly listed public targets and those that have been listed for five or more years.
This question is relevant for apparent reasons. Intuitively, it is the sales of the newly public firms
that are associated with the double-exit strategy. Perhaps more important, newly public and
seasoned firms are different in important aspects including synergy opportunities and short-term
uncertainty. Therefore, in terms of selling motive and valuation mechanisms, the valuation of a
newly listed target can be very different from a comparable seasoned target that has been
screened by the market for many years. Therefore, it remains to be addressed whether newly
public firms are sold at any premium relative to seasoned firms.
Based on the initial sample of IPOs and seasoned firms discussed in Section 4, I obtain a
subsample of takeover target firms by keeping only those that are delisted as an acquisition target
and that have the information on deal value and value-to-sales ratio. This resulting acquisition
target subsample contains 712 IPOs and 420 seasoned firms. I then match the two groups;
specifically, for each IPO target, I choose the seasoned firm as the matching target that is in the
same two-digit SIC industry as the IPO and has the closed sales level within the 50% to 150%
range of that of the IPO. This matching process leads to 225 pairs of IPOs and seasoned targets.
In addition to the four financial value based acquisition multiples that are used in the
IPO-private target comparison, three market-value based acquisition multiples are also used in
the comparison between IPOs and seasoned targets. They are the deal value divided by the target
firm’s market capitalization 3, 11 or 35 trading days, respectively, prior to the announcement
date. One advantage of the market-value based multiples is that they directly reflect the premium
or discount that the selling shareholders actually realize in an acquisition.
Table 8 presents the result of the univarite analysis. Based on median, all market-value
21
based acquisition multiples are significantly higher for the IPO targets. Specifically, while
seasoned targets realize a median premium of 57%, 43% and 39%, based on target's market
value for 35, 11, and 3 trading days prior to the announcement date, respectively, the IPO
counterparts realize a median premium of 62%, 51% and 48%. Among the fundament-value
based acquisition multiples, only deal value to EBITDA is significantly higher for IPO targets,
others are not significantly different between the two samples. The insignificant difference in
offer price to book value of equity indicates that this multiple is quite comparable between
targets that have the same public status.
Table 9 presents the results of the multivariate regressions for the IPO-seasoned comparison
of the acquisition multiples. The model specifications in this table are similar to that in Table 7,
where the key explanatory variable is the IPO target dummy. In order to control for potential
effects of information leakage and stock market on the target’s market value, the variable of
200-day target excess return over the period of 210 to 11 trading days prior to announcement is
included. Consistent with the result from the univarite analysis in Table 8, the coefficients on
IPO target dummy are significantly positive for the regressions on the three market-value based
acquisition multiples and the fundamental-value based multiple measured by deal value to
EBITDA. This indicates that the observed differences in acquisition valuations between IPO and
seasoned targets cannot be captured by firm and deal specific characteristics.
The IPO-seasoned comparison on takeover premiums is new. Theoretical studies do not
provide direct implications on the relative valuation of IPO and seasoned targets. Following the
arguments of Zingales (1995), Mello and Parsons (1998), and Hsieh, Lyandres, and Zhdanov
(2011), one can even infer that seasoned targets should be associated with higher takeover
premium due to their further resolved information asymmetry and value uncertainty. In that sense,
22
my result that IPO targets have higher acquisition valuation is even strengthened. As it allows
insiders to realize higher return than does either a direct sellout or a sale after the firm becomes
seasoned, double-exit strategy is thus justified economically
6. Conclusion
In this paper, I have examined the link between firms’ IPOs and subsequent sales through
acquisitions. The fundamental issue behind this link is the firm’s motive to go public in order for
its insiders to exit. Theory has long predicted that going public can be an optimal first step of the
process of selling a company. However, evidence on this prediction has been limited or
non-existent. By examining a large sample of U.S. IPOs and their matching samples, I document
strong evidence in support of this prediction. My finding is two folds. First, newly listed firms
are more likely to be acquired within five years after the IPO than are seasoned firms. In my
sample, 27 percent of the new issues are acquired, which is about 10 percentage points higher
than the seasoned firm counterpart. This difference is economically strong, and statistically
significant and robust. This observation confirms the so-called double-exit strategy being used in
reality. Second, I find that, as acquisition targets, IPO firms receive higher takeover premiums
than do comparable privately held targets and seasoned target firms. This finding lends further
support to the double-exit strategy, showing that it is economically justified.
A further issue my study does not address is potential implications of the double-exit
strategy to acquirers. If acquiring newly public firms is relatively costly, as the acquisition
multiples indicate, potential acquirers should avoid purchasing such firms. In other words, for the
double-exit strategy to be an equilibrium outcome, newly public firms must have some value
advantages as acquisition targets. It is possible that as new target candidates entering the M&A
market, newly public firms might have the potential to generate greater acquisition synergies
23
than do seasoned firm target candidates. In addition, after becoming a public company, increased
transparency and thus reduced uncertainty of IPO targets might allow potential buyers to make
better acquisition decisions relative to purchasing privately held targets. These issues are beyond
the scope of this paper, and need to be carefully examined in a separate study.
References
Ambrose, B., Megginson, W., 1992., The role of asset structure, ownership structure, and
takeover defenses in determining acquisition likelihood. Journal of Financial and
Quantitative Analysis 27, 575-589.
Bayar, O., Chemmanur, T., 2012. What drives the valuation premium in IPOs versus acquisitions?
An empirical analysis. Journal of Corporate Finance 18, 451-475.
Bebchuk, L., Cohen, A., 2005. The costs of entrenched boards. Journal of Financial Economics
78, 409-433.
Brau, J., Couch, R., Sutton, N., 2012. The desire to acquire and IPO long-run underperformance.
Journal of Financial and Quantitative Analysis 47, 493-510.
Brau, J., Fawcett, S., 2006. Initial public offerings: analysis of theory and practice. The Journal
of Finance 61, 399-436.
Brau, J., Francis, B., Kohers, N., 2003. The choice of IPO versus takeover: Empirical evidence.
The Journal of Business 76, 583-612.
Boulton, T., 2010. Venture capital and the incorporation decisions of IPO firms. Journal of
Economics and Business 62, 477-501.
Celikyurt,U., Sevilir, M., Shivdasani, A., 2010. Going public to acquire? The acquisition motive
24
in IPOs. Journal of Financial Economics 96, 345-363.
Chemmanur, T., Fulghieri, P., 1999. A theory of the going-public decision, Review of Financial
Studies 12, 249-279.
Chemmanur, T., He, S., Nandy, D., 2010. The going-public decision and the product market.
Review of Financial Studies 23, 1855-1908.
Ciccotello, C., Field, L., Bennett, R., 2001. The thrift IPO as the first stage of its subsequent sale.
Financial Markets, Institutions & Instruments 10, 19-39.
De, S., Jindra, J., 2012. Why newly listed firms become acquisition targets. Journal of Banking
and Finance 36, 2616-2631.
DeLong, J., Shleifer, A., Summers, L., 1990. Noise trader risk in financial markets. Journal of
Political Economy 98, 703-738.
Fama, E., French, K., 2004. New lists: Fundamentals and survival rates. Journal of Financial
Economics 73, 229-269.
Field, L., Karpoff, J., 2002. Takeover defenses of IPO firms. The Journal of Finance 57,
1857-1889.
Gompers, P., Ishii, J., Metrick, A., 2003. Corporate governance and equity prices. Quarterly
Journal of Economics, 118, 107-155.
Harford, J., Humphery-Jenner, M., Powell, R., 2012. The sources of value destructions by
entrenched managers. Journal of Financial Economics, 106, 247-261.
Holmström, B., Tirole, J., 1993. Market liquidity and performance monitoring. Journal of
Political Economy 101, 678-709.
25
Hovakimian, A., Hotton, I., 2010. Merger-motivated IPOs. Financial Management 39,
1547-1573.
Hsieh, J., Lyandres, E., Zhdanov, A., 2011. A theory of merger-driven IPOs. Journal of Financial
and Quantitative Analysis 46, 1367-1405.
Kim, W., Weisbach, M., 2008. Motivations for public equity offers: An international perspective.
Journal of Financial Economics 87, 281-307.
Koeplin, J., Sarin, A., Shapiro, A., 2000. The private company discount. Journal of Applied
Corporate Finance 12, 94-101.
Lyon, J., Barber, B., Tsai, C.,1999. Improved methods for tests of long-run abnormal stock
returns. The Journal of Finance 54, 165-201.
Masulis, R., Wang, C., Xie, F., 2007. Corporate governance and acquirer returns. The Journal of
Finance 62, 1851-1889.
Mello, A., Parsons, J., 1998. Going public and the ownership structure of the firm. Journal of
Financial Economics 49, 79-109.
Moeller, T., 2005. Let’s make a deal! How shareholder control impacts merger payoffs. Journal
of Financial Economics 76, 167-190.
Netter, J., Stegemoller, M., Wintoki, M., 2011. Implications of data screens on merger and
acquisition analysis: a large sample study of mergers and acquisitions from 1992 to 2009.
Review of Financial Studies 24, 2316-2357.
Officer, M., 2007. The price of corporate liquidity: acquisition discounts for unlisted target.
Journal of Financial Economics 83, 571-598.
26
Pagano, M., Panetta, F., Zingales, L., 1998. Why do companies go public? An empirical analysis.
The Journal of Finance 53, 27-64.
Palepu, K., 1986. Predicting takeover targets: a methodological and empirical analysis. Journal
of Accounting and Economics 8, 3-35.
Poulsen, A., Stegemoller, M., 2008. Moving from private to public ownership: selling out to
public firms versus initial public offerings. Financial Management 37, 81-101.
Rajan, R., 1992. Insiders and outsiders: The choice between informed and arm's-length debt. The
Journal of Finance 47, 1367-1400.
Ritter, J., 1984. The hot issue market of 1980. Journal of Business 57, 215-240.
Ritter, J. R., 1991, The long-run performance of initial public offerings. Journal of Finance 46,
3-27.
Shleifer, A., Vishny, R., 1986. Large shareholders and corporate control. Journal of Political
Economy 94, 461-488.
Song, M., Walkling, R., 1993. The impact of managerial ownership in acquisition attempts and
target shareholder wealth. Journal of Financial and Quantitative Analysis 28, 439-457.
Subrahmanyam, A., Titman, S., 1999, The going public decision and the development of
financial markets, Journal of Finance 54, 1045-1082.
Zingales, L., 1995. Insider ownership and the decision to go public. The Review of Economic
Studies 62, 425-448
27
Table 1. Summary Statistics of Selected Variables
This table presents summary statistics of firm characteristics and corporate governance variables. The initial sample consists of 4,411 pairs of IPOs and matching
seasoned firms. After excluding firms delisted for reasons other than takeovers, the final sample consists of 3,848 IPOs and 4,050 seasoned firms, covering up to five years
after the IPO. Market capitalization and assets are in the IPO year. Market-to-book ratio is the ratio of market value of the firm’s stock plus book value of debt over the book
value of assets in the IPO year. Leverage is the ratio of total liabilities to total assets in the IPO year. Property is the ratio of property, plant, and equipment to total assets in
the IPO year. Liquidity is the average ratio of net liquid assets (current assets minus current liabilities) to total assets over up to three years before acquisition for acquired
firms, or over the third to fifth years for survived firms. Growth is the average sales growth of acquired firms over up to three years before acquisition, or of survived firms
over the third to fifth years after the IPO. Stock return is the abnormal cumulative return of an acquired firm over the period from the IPO date to two months before the
acquisition announcement, or of a survived firm over the first three years after the IPO, where the equally weighted CRSP index is used as the market portfolio. Block is the
percentage of the firm’s shares held by the largest blockholder in the quarter immediately after the IPO. Staggered board dummy equals one if an acquired firm has staggered
board in the fiscal year before the acquisition or if a survived firm has staggered board in the fifth year, and equals zero otherwise. All non-dummy variables are winsorized at
the 1% level. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% level, respectively.
IPO firms
Assets ($million)
Market capitalization ($million)
Market-to-book ratio
Leverage
Property
Liquidity
Growth
Stock return
Block (in %)
Staggered board dummy
Seasoned firms
IPO-Seasoned difference
Mean
Median
Obs.
Mean
Median
Obs.
Mean
168.67
342.51
3.21
0.35
0.31
0.35
0.49
-0.13
7.06
0.65
60.30
127.93
2.38
0.31
0.20
0.35
0.22
-0.46
4.59
1.00
3,810
3,810
3,810
3,802
3,796
3,729
3,766
3,805
1,220
1,219
166.82
332.42
3.12
0.39
0.47
0.34
0.23
-0.02
8.01
0.43
59.17
119.99
2.35
0.37
0.39
0.34
0.11
-0.26
7.39
0.00
4,010
4,010
4,011
3,998
3,928
3,788
3,993
3,978
1,162
1,127
1.86
10.10
0.09
-0.04***
-0.16***
0.01***
0.26***
-0.11***
-0.95***
0.22***
28
p-value
0.820
0.485
0.149
0.000
0.000
0.006
0.000
0.000
0.000
0.001
Table 2. Firm Delisting due to Takeover: IPOs vs. Seasoned Firms
The total sample consists of 4,411 IPOs conducted during the period of 1980 to 2007, and the same number of size and market-to-book ratio matched seasoned firms.
This table shows the number (frequency in parentheses) of IPO firms that survive for five years or are delisted within five years after the IPO, which are compared with the
corresponding survival and delisting rates of matching seasoned firms. Following Fama and French (2004), I identify delisted firms using the CRSP code: 200 to 399 for
acquired firms, and 400 or above for delisted firms for other causes.
IPO firms
Sample period
1980-1989
1990-1998
1999-2000
2001-2007
Whole period
Seasoned firms
Total pairs
of firms
Survived
Delisted due
to acquisition
Delisted for
other causes
Survived
Delisted due
to acquisition
Delisted for
other causes
1,270
2,048
541
552
4,411
840 (66.1%)
1,170 (57.1%)
272 (50.3%)
369 (66.9%)
2,651 (60.1%)
261 (20.6%)
625 (30.5%)
169 (31.2%)
142 (25.7%)
1,197 (27.1%)
169 (13.3%)
253 (12.4%)
100 (18.5%)
41 (7.4%)
563 (12.8%)
998 (78.6%)
1,472 (71.9%)
411 (76.0%)
426 (77.2%)
3,307 (75.0%)
172 (13.5%)
399 (19.5%)
80 (14.8%)
92 (16.7%)
743 (16.9%)
100 (7.9%)
177 (8.6%)
50 (9.2%)
34 (6.2%)
361 (8.2%)
29
Table 3. By-year Firm Delisting due to Takeover: IPOs vs. Seasoned Firms
This table presents by-year delisting of newly listed firms, in comparison with matching seasoned firms, within five years after the IPO. Delisting percentages are
reported in parentheses. The first year numbers are partial because firms that are delisted before the first fiscal-year end do not appear in the SDC database so are not included
in my sample.
IPO firms
Year after IPO
Seasoned firms
1
2
3
4
5
1
2
3
4
5
4,411
4,344
3,933
3,451
3,022
4,411
4,309
4,051
3,801
3,535
Firms delisted for takeover
55
(1.3%)
289
(6.7%)
314
(8.0%)
293
(8.5%)
246
(8.1%)
79
(1.8%)
186
(4.3%)
161
(4.0%)
167
(4.4%)
150
(4.2%)
Firms delisted for other causes
12
(0.2%)
122
(2.8%)
168
(4.3%)
136
(3.9%)
125
(4.1%)
23
(0.5%)
72
(1.7%)
89
(2.2%)
99
(2.6%)
78
(2.2%)
Firms at the beginning of each year
30
Table 4. Determinants of the Likelihood of Being Acquired
This table presents logistic regressions, where the dependent variable equals one if the firm is acquired
within five years after the IPO issue date, and equals zero otherwise. Market capitalization and assets are in the
IPO year. Market-to-book ratio is the ratio of market value of the firm’s stock plus book value of debt over the
book value of assets in the IPO year. Leverage is the ratio of total liabilities to total assets in the IPO year.
Property is the ratio of property, plant, and equipment to total assets in the IPO year. Liquidity is the average
ratio of net liquid assets (current assets minus current liabilities) to total assets over up to three years before
acquisition for acquired firms, or over the third to fifth years for survived firms. Growth is the average sales
growth of acquired firms over up to three years before acquisition, or of survived firms over the third to fifth
years after the IPO. Stock return is the abnormal cumulative return of an acquired firm over the period from the
IPO date to two months before the acquisition announcement, or of a survived firm over the first three years
after the IPO, where the equally weighted CRSP index is used as the market portfolio. p-values are reported in
the parentheses. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% level, respectively.
Likelihood of being acquired
Constant
IPO dummy
(1)
-2.825***
(0.000)
0.649***
(0.000)
Ln(assets)
[Ln(assets)]2
Leverage
Market-to-book ratio
Property
Liquidity
Growth
Stock return
State dummy
Industry dummy
Issue year dummy
Observations
R2(Pseudo)
No
Yes
Yes
7,408
0.043
31
(2)
-4.393***
(0.000)
0.572***
(0.000)
0.581***
(0.000)
-0.062***
(0.000)
0.750***
(0.000)
-0.029**
(0.025)
0.005
(0.968)
0.274
(0.102)
0.317***
(0.000)
-0.115***
(0.000)
No
Yes
Yes
7,028
0.063
(3)
-4.303***
(0.000)
0.558***
(0.000)
0.584***
(0.000)
-0.062***
(0.000)
0.815***
(0.000)
-0.027**
(0.037)
-0.013
(0.913)
0.264
(0.125)
0.319***
(0.000)
-0.117***
(0.000)
Yes
Yes
Yes
6,899
0.070
Table 5. The Likelihood of Being Acquired: Sub-period Analysis
This table presents sub-period regressions for the logistic model presented in Table 4. The dependent
variable equals one if the firm is acquired within five years after the IPO issue date, and equals zero otherwise.
Market capitalization and assets are in the IPO year. Market-to-book ratio is the ratio of market value of the
firm’s stock plus book value of debt over the book value of assets in the IPO year. Leverage is the ratio of total
liabilities to total assets in the IPO year. Property is the ratio of property, plant, and equipment to total assets in
the IPO year. Liquidity is the average ratio of net liquid assets (current assets minus current liabilities) to total
assets over up to three years before acquisition for acquired firms, or over the third to fifth years for survived
firms. Growth is the average sales growth of acquired firms over up to three years before acquisition, or of
survived firms over the third to fifth years after the IPO. Stock return is the abnormal cumulative return of an
acquired firm over the period from the IPO date to two months before the acquisition announcement, or of a
survived firm over the first three years after the IPO, where the equally weighted CRSP index is used as the
market portfolio. Block is the percentage of the firm’s shares held by the largest blockholder in the quarter
immediately after the IPO. Staggered board dummy equals one if an acquired firm has staggered board in the
fiscal year before the acquisition or if a survived firm has staggered board in the fifth year, and equals zero
otherwise. p-values are reported in the parentheses. ***, **, and * indicate statistical significance at the 1%, 5%,
and 10% level, respectively.
1980-1989
Constant
IPO dummy
Ln(assets)
[Ln(assets)]2
Leverage
Market-to-book ratio
Property
Liquidity
Growth
Stock return
(1)
-3.670***
(0.000)
0.516***
(0.000)
0.160
(0.535)
-0.013
(0.675)
1.691***
(0.000)
-0.158***
(0.007)
0.341
(0.164)
0.881**
(0.024)
0.527***
(0.000)
-0.159**
(0.011)
1990-1996
(2)
-3.459***
(0.000)
0.583***
(0.000)
0.606**
(0.012)
-0.061**
(0.024)
0.547*
(0.055)
-0.033
(0.198)
-0.057
(0.759)
-0.073
(0.789)
0.177***
(0.000)
-0.085**
(0.029)
1997-2007
(3)
-2.133**
(0.020)
0.605***
(0.000)
0.251
(0.444)
-0.029
(0.361)
0.486
(0.143)
-0.030*
(0.069)
-0.137
(0.570)
0.520*
(0.075)
0.459***
(0.000)
-0.139***
(0.007)
Block
(4)
-1.242
(0.198)
0.385***
(0.002)
-0.021
(0.951)
-0.007
(0.821)
0.729**
(0.034)
-0.026*
(0.064)
-0.184
(0.472)
0.611**
(0.042)
0.418***
(0.000)
-0.187***
(0.000)
-0.005
(0.553)
Block × IPO dummy
Staggered board dummy
0.188*
(0.098)
Staggered board dummy × IPO
dummy
State dummy
Industry dummy
Issue year dummy
Observations
Pseudo R2
Yes
Yes
Yes
1,963
0.078
Yes
Yes
Yes
2,692
0.078
32
Yes
Yes
Yes
2,128
0.104
Yes
Yes
Yes
2,003
0.106
(5)
-1.371
(0.158)
0.636***
(0.007)
-0.012
(0.972)
-0.008
(0.808)
0.705**
(0.041)
-0.026*
(0.070)
-0.185
(0.470)
0.607**
(0.044)
0.426***
(0.000)
-0.190***
(0.000)
-0.011
(0.555)
0.007
(0.720)
0.516***
(0.003)
-0.572**
(0.013)
Yes
Yes
Yes
2,003
0.108
Table 6. The Acquisition Value: IPO Targets vs. Private Targets
This table reports acquisition multiples (purchase price to financial variable ratios) for IPO and private target firms. The sample consists of 436 pairs of IPO targets and
matching private targets that were acquired during the years 1980-2012. The IPO and private target firms are one-for-one matched for sales, industry, and announcement year.
The four acquisition multiples are directly obtained from the SDC Mergers and Acquisitions Database, which are based on the most current financial information prior to the
acquisition announcement. Deal value is adjusted for the proportion of shares being acquired in the transaction. All multiples are winsorized at the 1% level. Two-sided t test
for the mean and Wilcoxon test for the median of the IPO-seasoned difference are conducted. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% level,
respectively.
Offer price to book value of equity
Offer price to EPS
Deal value to sales
Deal value to EBITDA
IPO targets
Private targets
Pairs of
targets
Mean
Median
Mean
Median
146
73
428
76
6.85
76.44
9.81
90.02
4.21
42.00
3.23
26.82
86.52
60.62
2.36
66.01
8.41
16.40
1.13
10.52
33
IPO-Private difference
Mean
-79.67
15.82
7.44***
24.01
Median
-4.20***
25.60***
2.10***
16.30***
Table 7. Determinants of the Acquisition Value: IPO Targets vs. Private Targets
This table reports the results of the regression analysis for the acquisition multiples of IPO and private
targets. Hostile takeover dummy equals one if the attitude of the transaction is indicated as hostile, and equals
zero otherwise. Fraction of pay in cash is the proportion of total payment for the deal using cash.
Within-industry acquisition is a dummy variable that equals one if the acquirer and the target firm have the same
two-digit SIC code, and zero otherwise. Target sales are as of the most current financial information prior to the
acquisition announcement. Target leverage is the ratio of total liabilities to total assets as of the most current
financial information prior to the acquisition announcement. High-tech target dummy equals one if the target is
a high-tech firm, and zero otherwise. p-values are reported in the parentheses. ***, **, and * indicate statistical
significance at the 1%, 5%, and 10% level, respectively.
Dependent variable
Constant
IPO target dummy
Hostile takeover dummy
Fraction of pay in cash
Within-industry acquisition
Ln(Target sales)
Target leverage
High-tech target dummy
Observations
Adjusted R2
Offer price
to book value
32.981**
(0.048)
-14.916*
(0.078)
15.079
(0.794)
-0.099
(0.248)
5.406
(0.475)
-8.817***
(0.010)
46.553***
(0.009)
10.500
(0.161)
248
0.072
34
Offer price
to EPS
9.738
(0.875)
52.869*
(0.081)
-9.596
(0.941)
0.039
(0.886)
13.442
(0.585)
-5.909
(0.626)
76.189
(0.196)
21.141
(0.396)
121
0.024
Deal value
to sales
11.801***
(0.000)
3.853***
(0.006)
1.428
(0.891)
-0.019
(0.180)
1.688
(0.171)
-1.908***
(0.001)
-2.942
(0.277)
1.050
(0.384)
305
0.088
Deal value
to EBITDA
236.695***
(0.002)
52.776
(0.131)
-60.207
(0.704)
0.136
(0.677)
12.041
(0.682)
-42.256***
(0.003)
-53.028
(0.444)
-35.343
(0.241)
124
0.075
Table 8. The Acquisition Value: IPO Targets vs. Seasoned Targets
This table reports acquisition multiples (purchase price over a financial variable or market value) for IPO and seasoned target firms. The sample consists of 225 pairs of
IPO targets and matching seasoned targets that were acquired during the years 1980-2012. The IPO and seasoned target firms are one-for-one matched for sales and industry.
Four acquisition multiples are based on targets’ financial variables and three are based on targets’ market value. The financial variables based multiples are directly obtained
from the SDC Mergers and Acquisitions Database, for which the most current financial information prior to the acquisition announcement is used and deal value is adjusted
for the proportion of shares being acquired in the transaction. All multiples are winsorized at the 1% level. Two-sided t test for the mean and Wilcoxon test for the median of
the IPO-seasoned difference are conducted. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% level, respectively.
Offer price to book value of equity
Offer price to EPS
Deal value to sales
Deal value to EBITDA
Deal value to target market cap 3 days before announcement
Deal value to target market cap 11 days before announcement
Deal value to target market cap 35 days before announcement
IPO targets
Seasoned targets
Pairs of
targets
Mean
Median
Mean
Median
210
95
221
111
201
201
200
4.64
45.26
5.79
56.94
1.63
1.70
1.74
3.32
29.80
2.03
16.72
1.48
1.51
1.62
5.80
262.16
4.81
20.70
1.50
1.57
1.64
3.30
26.00
2.19
13.15
1.39
1.43
1.57
35
IPO-Seasoned difference
Mean
Median
-1.16
-216.90
0.98
36.24***
0.13**
0.13**
0.10
0.02
3.80
-0.16
3.57**
0.09**
0.08**
0.05**
Table 9. Determinants of the Acquisition Value: IPO Targets vs. Seasoned Targets
This table reports the results of the regression analysis for the acquisition multiples of IPO and seasoned targets. Hostile takeover dummy equals one if the attitude of the
transaction is indicated as hostile, and equals zero otherwise. Fraction of pay in cash is the proportion of total payment for the deal using cash. Within-industry acquisition is a
dummy variable that equals one if the acquirer and the target firm have the same two-digit SIC code, and zero otherwise. Target sales are as of the most current financial
information prior to the acquisition announcement. Target leverage is the ratio of total liabilities to total assets as of the most current financial information prior to the
acquisition announcement. 200-day target excess return is the target firm’s excess stock return over the 200 days 10 days prior to the announcement date, using equally
weighted CRSP index as the market portfolio. High-tech target dummy equals one if the target is a high-tech firm, and zero otherwise. p-values are reported in the
parentheses. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% level, respectively.
Dependent variable
(Fundamental-value based)
Constant
IPO target dummy
Hostile takeover dummy
Fraction of pay in cash
Within-industry acquisition
Ln(Target net sales)
Target leverage
200-day target excess return
High-tech target dummy
Year dummy
Observations
Adjusted R2
(Market-value based)
Offer price to
book value
Offer price to
EPS
Deal value to
sales
Deal value to
EBITDA
2.281
(0.599)
-0.825
(0.314)
-0.281
(0.919)
-0.014
(0.161)
1.671*
(0.056)
-0.422
(0.275)
4.714**
(0.020)
2.306**
(0.019)
1.052
(0.245)
Yes
362
0.035
50.466
(0.445)
-15.363
(0.319)
10.023
(0.821)
-0.301*
(0.099)
6.576
(0.686)
1.342
(0.884)
-4.040
(0.923)
38.574**
(0.018)
9.679
(0.601)
Yes
174
0.143
18.454***
(0.000)
0.732
(0.427)
1.267
(0.688)
-0.025**
(0.028)
0.310
(0.755)
-2.423***
(0.000)
-6.003***
(0.009)
3.516***
(0.002)
-1.482
(0.144)
Yes
368
0.153
8.352
(0.896)
34.896**
(0.016)
16.864
(0.710)
-0.117
(0.493)
15.906
(0.330)
0.542
(0.954)
-27.075
(0.492)
69.575***
(0.000)
34.365**
(0.049)
Yes
206
0.066
36
Deal value
to mkt cap
3 days before
announcement
0.940***
(0.001)
0.115*
(0.055)
0.532***
(0.009)
0.001
(0.144)
-0.005
(0.939)
-0.014
(0.620)
0.630***
(0.000)
-0.076
(0.104)
0.112*
(0.087)
Yes
366
0.136
Deal value
to mkt cap
11 days before
announcement
0.918***
(0.001)
0.148**
(0.020)
0.532**
(0.015)
0.001
(0.103)
0.001
(0.991)
-0.032
(0.285)
0.738***
(0.000)
-0.095*
(0.059)
0.114
(0.104)
Yes
366
0.124
Deal value
to mkt cap
35 days before
announcement
0.701**
(0.019)
0.120*
(0.076)
0.614***
(0.008)
0.002*
(0.066)
0.104
(0.157)
0.009
(0.770)
0.808***
(0.000)
-0.048
(0.367)
0.121
(0.104)
Yes
368
0.122