THE CHOICE OF IPO VERSUS TAKEOVER: EMPIRICAL EVIDENCE

James C. Brau

Assistant Professor of Finance Department of Business Management

Marriott School, TNRB 660 Brigham Young University

Provo, UT 84602 Phone: (801) 378-8952 Fax: (801) 378-5984

E-mail: jbrau@byu.edu

Bill Francis Associate Professor of Finance

Department of Finance University of South Florida

4202 East Fowler Avenue, BSN 3403 Tampa, FL 33647-5500 Phone: (813) 974-6330

E-mail: bfrancis@coba.usf.edu

Ninon Kohers Assistant Professor of Finance

Department of Finance University of South Florida

4202 East Fowler Avenue, BSN 3403 Tampa, FL 33647-5500 Phone: (813) 974-6337

E-mail: nkohers@coba.usf.edu

First: January 2000 Current: June 2001

The authors thank Rob Daines, Hal Heaton, Andrew Holmes, Mike Lemmon, Beverly Marshall, Grant McQueen, Bill Megginson, Todd Mitton, Mike Pinegar, Mike Schill, Bernell Stone, Steve Thorley, Keith Vorkink, participants at the BYU and USF finance seminars, participants at the 2000 FMA conference, an anonymous referee, and the editor (Albert Madansky) for helpful comments. All omissions/errors are the responsibility of the authors.

The Choice of IPO Versus Takeover: Empirical Evidence

Abstract

Private firm owners interested in gaining increased access to public capital, increasing

their liquidity, and/or changing the control of their firms, face a fundamental choice between an

initial public offering (IPO) or a takeover by a public acquirer. Using a sample of over 9,500

U.S. privately held firms, we address the IPO versus takeover issue by examining market-timing,

industry, deal-specific, and fund demand factors of the IPO versus acquisition choice. Our

results show that the concentration of the industry, the high-tech status of the private firm, the

current cost of debt, the ‘hotness’ of the IPO market relative to the takeover market, the

percentage of insider ownership, and the size of the firm are all positively related to the

probability that a firm will conduct an IPO. In contrast, private companies in high market-to-

book industries, firms in financial service sectors, firms in highly leveraged industries, and deals

involving greater liquidity for selling insiders show a stronger likelihood for takeovers. Finally,

a quantitative analysis of the premiums associated with the IPO versus takeover decision

provides evidence that a liquidity discount exists in takeovers relative to IPOs.

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I. Introduction

Recent literature has highlighted a privately held firm's choice of going public via an

initial public offering (IPO) or staying private.1 This literature addresses only two outcomes,

staying private or conducting an IPO; however an important, yet unexplored alternative pathway

exists for private firms wishing to access public equity markets. Agreeing to a takeover by a

publicly traded acquirer is often an attractive opportunity for private firms and presents an

alternative to the IPO route.

In this study, we focus on the following four key factors advanced in the current IPO and

merger and acquisition (M&A) literature that can impact the IPO versus takeover decision: first,

industry characteristics (e.g., Mitchell and Mulherin (1996), Pagano et al. (1998), Maksimovic

and Pichler (2001), Stoughton, Wong and Zechner (2001)); second, the role of market-timing

(e.g., Ritter (1984), DeLong, Shleifer, Summers, and Waldmann (1990), Golbe and White

(1993), and Rajan and Servaes (1997)); third, the demand for funds by private firms (e.g.,

Mikkelson, Partch and Shah (1997) and Lowry (2000)); and fourth, deal-specific factors such as

the size of the firm, insider ownership, and the liquidity effects of the deal. In the extant

literature these four factors are important separately for IPOs and takeovers. However, to our

knowledge no existing study examines the choice of conducting an IPO or agreeing to a

takeover. In this study, we attempt to fill this void by evaluating the impact of industry, market-

timing, deal-specific, and fund demand effects on a private firm’s choice of an IPO versus a

takeover.

Anecdotal evidence from the financial press indicates that our extension is not trivial. An

increasing number of articles have drawn attention to the choice between a takeover or an IPO.

For example, a recent Fortune article focuses on the strategic restructuring decisions of serial

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entrepreneurs. These entrepreneurs create and grow businesses with the express purpose of

selling out to large publicly traded firms in lieu of conducting an IPO. Many of these same

entrepreneurs previously focused on IPOs and have recently changed to the takeover strategy

(Gimein (2/21/2000)). As another example, a recent Wall Street Journal article tells how the

insiders at Cerent deviated from their original IPO plan and sold-out to Cisco instead, in a classic

example of what has become known as a ‘pick-off’ (Thurm (3/1/2000)). Another Wall Street

Journal article entitled, "Many Firms Take Buyouts after Planning IPOs," articulates several of

the ideas that we formally test in our paper (Fitch and Benjamin (2/27/1998)). Specifically, the

article discusses the dual paths to equity markets (i.e., takeover or IPO) and emphasizes how

factors such as market and industry conditions impact the choice of a takeover or an IPO. The

connection between the takeover and IPO markets is further highlighted by the observation that

surges in IPO volume have been associated with downturns in takeover activity (July-August,

1996, Mergers and Acquisitions, p. 5).

The lack of an academic study on this fundamental restructuring choice as well as the

recognition of this issue in the current financial press and among practitioners motivate us to

explore which factors determine whether a privately-held firm reorganizes via an IPO or a

takeover. Although both choices allow firms to access public equity markets (directly with an

IPO and indirectly with a takeover), we conjecture that different motivations and market

conditions exist that impact the choice between an IPO and a takeover.

Two important motives for choosing an IPO or a takeover may be the level of liquidity

and ownership insiders require following the completion of the transaction. The takeover

arrangement may make cashing out (or significantly increasing liquidity) more efficient than an

IPO for the insiders of the firm. Leland and Pyle (1977) argue that insiders who sell large

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portions of their firm in the IPO send a signal that the firm is overvalued. Insiders who attempt

to liquidate by selling a large amount of personally owned (i.e., secondary) shares in the IPO

may depress the price of their firm and decrease both the amount raised in an IPO and the

probability of full subscription through the negative signal they convey. These negative

signaling effects are less likely in takeovers, since acquiring firms might face fewer information

asymmetries relating to the target firm’s value (see Leland and Pyle, 1977). Thus, takeovers

offer selling insiders the ability to divest the entire firm by selling to an existing company that

may not interpret the exit by insiders as a negative signal.

Closely related to the issue of liquidity is that of ownership and control. Insiders who

wish to maintain a controlling ownership in the firm while obtaining access to capital markets

may prefer an IPO. Relative to target insiders, IPO insiders do not have an acquiring firm to deal

with in matters of control, and depending on the proportion of primary to secondary shares may

retain effective ownership after the IPO. In our empirical analysis, we examine the relative

importance of insider ownership in the IPO versus takeover decision to ascertain whether, on

average, differences in control preferences drive private firm owners to choose one type of

restructuring route over the other.

In addition to examining the liquidity and ownership effects of the IPO versus takeover

decision, we investigate external factors that can influence the relative attractiveness of IPOs and

takeovers for private firms. Specifically, we argue that certain macroeconomic, stock market and

industry factors are important determinants in a private firm's restructuring decision.2 Our

investigation of these external influences shows that the degree of concentration of the private

firm’s industry, the high-tech industry affiliation of the firm, the ‘hotness’ of the IPO market

relative to the takeover market, and the current cost of debt are positively related to the

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probability that a firm will conduct an IPO. Also, an analysis of the influence of certain deal

related factors on the IPO versus takeover decision reveals that larger private firms are more

likely to choose IPOs, and the level of post deal insider ownership tends to be higher for IPOs

than takeovers. In contrast, our results indicate that private companies in high market-to-book

industries, in financial service industries, and in high debt industries show a stronger likelihood

for takeovers. Further, examination of the liquidity versus ownership implications of these two

types of transactions indicates that the level of post deal insider liquidity (ownership) tends to be

higher (lower) for takeovers than for IPOs.

In a separate comparison of premiums earned by insiders of IPOs versus insiders of

takeovers, we find that in the aggregate sample, target insiders receive a takeover payoff that

equals approximately 78 percent of an IPO payoff. Regression analysis suggests that takeover

insiders are willing to accept this 22 percent discount due to the greater liquidity they obtain.

The remainder of this paper proceeds as follows. Section II contains a discussion of the

theoretical underpinnings for our empirical tests. In Section III, we present the data and

difference testing between samples consisting of takeover and IPO firms. Section IV contains

multivariate tests of the hypotheses and Section V contains an analysis of the premiums received

by issuers in an IPO and sellers in a takeover. We summarize and conclude in Section VI.

II. Factors Influencing the Relative Attractiveness of IPOs versus Takeovers

In examining the IPO versus private target takeover decision, we focus on certain

industry-related characteristics, market-timing factors, deal-specific factors, and fund demand

determinants that can influence the relative attractiveness of one restructuring route versus the

other. We discuss the possible impact of these factors in the following subsections. Most of the

variables we examine are broad market and industry-related factors and, thus, a clear theoretical

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prediction for each factor's influence on the IPO versus takeover decision is not always available.

For variables with no clear prediction, we analyze both sides of the issue by presenting the

opposing arguments that predict how each factor can influence the decision to choose an IPO or

a takeover. After discussing the potential effect of each factor, we test these empirical issues by

examining the relative importance of each variable on the IPO versus takeover choice. For

convenience, Table I provides a succinct summary of this section. The first column of Table I

lists the variables in question. The second column provides the arguments in favor of an IPO,

while the third column provides the arguments in support of a takeover.

[INSERT TABLE I ABOUT HERE.]

A. Industry Related Factors

Panel A of Table I lists the industry-related factors that are likely to determine the choice

of an IPO or takeover. First, the level of concentration within an industry may influence whether

privately held firms conduct IPOs or instead agree to acquisitions. The likelihood of a takeover,

as opposed to an IPO, can be smaller in relatively high concentration industries because high

concentration industry environments would have less potential for further consolidation.

Further, anti-trust concerns and government scrutiny would be more prevalent in high

concentration industries, leading to greater difficulties in implementing takeovers. Thus,

mergers, as opposed to IPOs, would be more likely to occur in low concentration (fragmented)

industries.

However, industries with lower concentration may not be inclined towards increased

concentration if the technological dynamics and demand characteristics of the industry make

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concentration unattractive as an industrial strategy.3 Further, firm survival can be more difficult

in industries that are highly concentrated, making the takeover route an attractive strategy for

smaller, less competitive private firms (see Sharma and Kesner (1996) and Audretsch (1995)).

Thus, given these two counter-arguments, the role of industry concentration in influencing the

relative attractiveness of IPOs versus takeovers becomes an empirical issue. Similar to Pagano

et al. (1998), and others, we employ the Herfindahl index as a measure of the degree of

competition within an industry.4 In essence, this index represents the sum of squared market

shares of all members of a particular industry and is a measure of the degree of concentration

within an industry. Higher index values indicate higher industry concentration. The Herfindahl

index is calculated using sales data obtained from Compustat.

In addition to examining the importance of the degree of concentration within industries,

we also test for the influence of distinct types of industries through the use of industry dummy

variables. Investor enthusiasm towards newly public firms operating in high-tech industries in

recent years illustrates the popularity of these new, emerging fields and technologies among

investors searching for the next super growth IPO (see Business Week, March 31, 1997, p. 58).

For example, the notoriously lofty valuations of many internet companies that are often not

expected to produce positive earnings in the near future, have provided some indication of the

favorable perception of firms involved in certain high-tech pursuits and emerging industries

(Maksimovic and Pichler (2001)). Given the popularity of high-tech IPOs among investors over

the time period examined, privately held high-tech firms may be more likely to capitalize on this

enthusiasm by choosing an IPO instead of agreeing to a takeover (Allen and Gale (1999)).

Further, a firm’s decision to go public provides a signal to customers and investors that the

company is willing to provide the periodical Security and Exchange Commission reporting

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documents and undergo the scrutiny of outside analysts. This aspect of going public can be of

particular importance to firms in high-tech industries where there is a significant amount of

uncertainty about the quality of its product(s) and where competitive dynamics are an important

consideration for the firm’s longevity (Stoughton, Wong, and Zechner (2001)).

In contrast, Yosha (1995) and Maksimovic and Pichler (2001) argue that the potential

loss of confidentiality can deter high-tech firms from choosing an IPO. Additionally, in recent

years high-tech firms have been attractive takeover targets for acquiring firms in search of

enhanced growth opportunities. In examining this high-tech attraction, Kohers and Kohers

(2000) find that the premiums paid for high-tech targets during the late 80’s through the mid 90’s

were significantly larger than those paid for non-high-tech targets. In our empirical analysis, we

examine which of the predictions is more important in explaining the tendency of private high-

tech firms to choose an IPO or to agree to a takeover. High-tech industry identifications are

based on classifications made by Securities Data Company (SDC), and include areas in

biotechnology, chemicals, computers, defense, electronics, communications, medical, and

pharmaceuticals, among others.

In addition to isolating high-tech industries, we test for effects associated with private

firms operating in financial service industries. The deregulation occurring in financial services,

in conjunction with the relatively high degree of fragmentation within these industries, has

created an environment that is conducive towards acquisitions and widespread consolidation.

Berger, Kashyap and Scalise (1995) and Berger, Demsetz, and Strahan (1999) present evidence

that supports the consolidation hypothesis. Specifically, they show that consolidation-promoting

bank policy that lifts geographic restrictions (for example, the Riegle-Neal Interstate Banking

and Branching Efficiency Act of 1994) leads to mergers. Institutions that merge often benefit

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from economies of scale that allow income to grow faster than expenses. Further, although the

firms we examine are privately held companies, public information is often available for

financial firms. As a result, the information acquisition role for conducting an IPO becomes less

important (Shah and Thakor (1988), Holmstrom and Tirole (1993), van Bommel (1997), Maug

(1999), and Stoughton, Wong, and Zechner (2001)). Based on the consolidation and information

acquisition arguments, financial service firms would be more likely to agree to a takeover rather

than to choose an IPO.

However, the consolidation occurring in financial services’ areas might also promote IPO

activity. Because bidders’ stock is often used as a method of payment in these types of mergers,

potential acquirers that are privately held could be constrained from engaging in merger activity

because of their limited financial options. Conducting an IPO would provide the firm with a

publicly traded stock that could be used as a payment method in future acquisitions. This

enhanced ability to undertake acquisitions and adapt to changing industry conditions could, in

turn, increase the firm’s competitiveness within the industry. In a similar view, even if stock is

not needed for acquisitions, the cash raised from public equity sales allow financial service firms

to take advantage of the deregulatory environment.

Our next industry-related factor captures the capital structure characteristics of the private

firm’s industry. Following Pagano et al. (1998), we use the firm's debt level as a proxy for

financial risk. Because leverage ratios are not available for many of the private firms in our

sample, we assume an equilibrium capital structure in industries and proxy for firm leverage with

the industry leverage ratio (measured as debt/assets). Given the data constraints, this proxy

seems reasonable since previous studies such as Bradley, Jarrell, and Kim (1984) have

documented strong intra-industry similarities in individual firm leverage ratios. When evaluating

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privately-held firms, investors may perceive high debt levels as a potential risk factor, especially

since these investors do not have wide access to other sources of reliable information that would

be useful in evaluating these companies. Thus, private firms from highly levered industries may

be viewed with an extra degree of caution. As such, all else constant, these firms would be more

severely underpriced in an IPO transaction, thereby leaving a significant amount of money on the

table. Consequently, the more conservative takeover route may be the more appealing

restructuring path for private firms belonging to highly leveraged industries.

However, an alternative is that highly leveraged firms are generally required to undergo

close scrutiny and monitoring by creditors, making the investigation costs lower for these firms

(see Harris and Raviv (1990, 1991)). If these firms have already passed the hurdles of lenders,

potential shareholders may free ride on prior bondholder and bank scrutiny and view more highly

levered firms as attractive IPO candidates. These observations suggest that firms in highly

leveraged industries are likely to use IPOs as their restructuring choice. Overall, in view of these

competing arguments, the effect of the industry’s leverage ratio on the choice of IPO versus

takeover is an issue to be resolved through empirical testing.

We also employ the market-to-book ratio of the private firm’s industry to capture the

potential influence of industry valuations on the IPO versus takeover choice. In their

examination of the going public decision, Pagano et al. (1998) note that high market-to-book

ratios in an industry may create an environment conducive to IPOs. Alternatively, takeovers

may be attractive for private firms in high market-to-book industries since these multiples can

serve as a basis in the target valuation process (Golbe and White (1993)). Our empirical analysis

is designed to reveal the relative importance of industry valuations, as proxied by the market-to-

book ratio, for the IPO and private target takeover decision.

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B. Market-Timing Factors

Panel B of Table I lists the market-timing variables that are hypothesized to influence the

choice between an IPO and a takeover. Ritter (1984) and Ibbotson, Sindelar, and Ritter (1994),

among others, document the existence of “hot issue” periods in the IPO market. DeLong,

Shleifer, Summers, and Waldmann (1990), Lerner (1994), Loughran, Ritter, and Rydqvist

(1994), Rajan and Servaes (1997), and Pagano, Panetta, and Zingales (1998), among others, also

provide evidence of market-timing behavior by managers and underwriters in the IPO market.

One explanation for hot issue periods is time variation in adverse selection costs that leads to

periods of favorable market environments, or windows of opportunities for issuing equity. This

literature contends that during periods characterized by high information asymmetry, adverse

selection costs are high and, as a result, fewer firms choose to issue equity. Lowry (2000) and

Lowry and Schwert (2000) provide evidence of the impact of adverse selection costs on the

volume of IPOs; while Bayless and Chaplinsky (1996) and Choe, Masulis, and Nanda (1993)

also find that adverse selection costs influence the timing of seasoned equity offerings.

Another important aspect of the IPO timing hypothesis is that of investor sentiment. The

investor sentiment hypothesis argues that periods exist when investors are overly optimistic and

are willing to overpay for IPOs. Thus, during these periods, managers and underwriters are more

likely to bring IPOs to the market. Lee, Shleifer, and Thaler (1991), Helwege and Liang (1996),

Rajan and Servaes (1997), and more recently, Lowry (2000) present evidence of a positive

relationship between IPO volume and investor sentiment in the U.S. market. Pagano, Panetta,

and Zingales (1998) present similar evidence for the Italian market. We use two proxies to

capture the level of investor sentiment. The first is the return on the stock market (Lowry

(2000)). The second is a lagged relative volume variable that measures the quarterly volume of

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IPOs occurring in a particular industry in the prior quarter, divided by the quarterly volume of

private target takeovers occurring in that industry over the same time frame. This variable is

motivated by the fact that both the theoretical literature (Maksimovic and Pichler (2001),

Hoffmann-Burchardi (1999)) and empirical evidence (Ritter (1984), Lowry (2000)) show that the

clustering of IPOs is predominantly an industry phenomenon.

Mitchell and Mulherin (1996), among others, provide evidence on market-timing in

merger activity by revealing clustering of mergers over time. They show an increase in merger

activity during industry or economic contractions, periods when information asymmetry tends to

be relatively high. Although not strictly comparable because they focus on mergers and

acquisitions involving publicly held firms, this observed tendency may also be evident in the

private takeover market. The anecdotal evidence cited earlier suggests that IPOs and takeovers

occur in waves that are negatively correlated. If the cycles are actually simultaneous, then the

relative volume of IPOs to takeovers may not have an effect on the choice between conducting

an IPO or takeover.

C. Deal-Specific Factors

Panel C of Table I reports the four deal-specific factors and how they may influence the

choice between an IPO and a takeover. Perhaps the most defining firm-level characteristic is

firm size. Firm size can provide some indication of the private firm’s ability to successfully

compete as an independent publicly traded firm. Holmstrom and Tirole (1993) and Pagano and

Roell (1998), to name a few, argue that IPOs involve high explicit fixed costs. Evidence

provided by Ritter (1987) is consistent with this argument. Thus, for relatively small private

firms, conducting an IPO can be quite costly, and the potential for success as an independent

12

public company may be limited. Whereas small firms may not be equipped to successfully

operate as stand-alone public companies, they can provide value for acquiring firms who could

share their own resources and skills with the target firm. Similar to Pagano et al. (1998), we use

the total assets of the firm as well as the scaled transaction value as proxies for size and as

measures of the potential for independent survival. Based on our preceding arguments, we

predict a positive relation between the size of the firm and the choice of an IPO (and thus a

negative relation with the choice of a takeover).

The level of insider ownership after the reorganization varies when comparing takeovers

and IPOs. The typical IPO allows for gradual changes in ownership for insiders wishing to

relinquish control of their firm slowly over time (see Rydqvist and Hogholm (1995), Zingales

(1995), Mello and Parsons (1998), and Bebchuk and Zingales (1999)). In a takeover, the

controlling stake in the private firm changes hands at the time of the transaction. However, the

target owners can maintain a non-controlling stake in the merged firm, depending on the method

of payment used. For example, the acquisition of a private firm through a stock offer enables its

owners to retain some stake, albeit indirectly, in their firm after a merger. At the other extreme,

cash takeovers provide the most dramatic change in ownership structure, enabling owners to

divest completely and thereby relinquish their stakes in the firm. Since owners can tailor the

design of either an IPO or a takeover to result in various levels of control, the degree of insider

ownership may not be a critical factor in the IPO versus takeover decision. The ownership issue

is thus an empirical one. We measure insider ownership in IPOs as the percentage of the firm

not offered in the IPO (i.e., one minus the ratio of the number of shares offered in the IPO

divided by the total number of shares outstanding after the offer). For mergers, insider

ownership is the percentage of the stake that target insiders have in the newly combined firm

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(i.e., the ratio of the target firm value to the combined firm value, all times the proportion of the

takeover paid in stock).

Closely related to the level of insider ownership is the issue of insider liquidity. Private

firm owners may seek a particular level of liquidity, which can be achieved, to varying degrees,

through either an IPO or a private target takeover. For smaller liquidity needs, the owners may

decide on a partial sale of the firm via an IPO, or for maximum liquidity, the private firm owners

can completely cash out by agreeing to acquisition via a cash offer (Dhillon, Raman, and

Ramirez (2000) and Brown, Ditmar, and Servaes (2000)). However, similar to the insider

ownership issue, the proper design of a transaction, whether an IPO or a takeover, could allow

the initial owner to achieve the desired level of liquidity and is, thus, an empirical matter.5 For

takeovers, we measure liquidity as the percentage of the offer that is in cash. The metric is

bounded above by one (for total cash-outs) and below by zero (for total stock deals). For IPOs,

liquidity equals the ratio of secondary shares offered to total shares (also bounded by zero and

one). Proceeds from secondary shares sold in the IPO go directly to selling insiders as cash

payments.

D. Funding Demand Factors

Panel D of Table I lists three demand for fund factors and their potential influence on the

choice between an IPO and takeover. Mikkelson, Partch, and Shah (1997) and Lowry and

Schwert (2000) present evidence that one of the most important reasons for going public is to

raise funds for new investments. Since information on the demand for capital by private

companies is not available, we use as proxies certain variables that have been shown to be good

indicators of future investment opportunities. Specifically, we use the return on a portfolio that

is long on high book-to-market stocks and short on low book-to-market stocks (HML), and the

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return on a portfolio that is long on small capitalization stocks and short on large capitalization

stocks (SMB). The choice of these variables as proxies for the demand for funds is based on

evidence provided by Liew and Vassalou (2000). They find that HML and SMB, shown by

Lowry and Schwert (2000) to be good proxies for private firm fund demand, also reliably predict

future gross domestic product. In comparing IPOs to takeovers, the preferable restructuring

decision for private firms wishing to increase their access to financing is not clear. As pointed

out earlier, an IPO is one path to enhanced financing choices; yet a takeover by a publicly traded

acquirer also provides the private target with access to public capital markets, via the acquiring

firm. Thus, our tests are constructed to reveal whether or not the demand for funds plays a

stronger role in either type of transaction.

In addition to HML and SMB, the 3-month T-bill rate is used as a proxy for borrowing

costs at the time of the transaction. Since many acquirers use debt to finance acquisitions,

periods of higher interest rates can result in less attractive takeover environments (Golbe and

White (1993)). The pecking order hypothesis of Myers and Majluf (1984) contends that, for

firms that require external financing, the use of debt is attractive only up to a certain level, after

which it gets prohibitively costly and external equity becomes the chosen alternative. Thus, for

firms that are highly leveraged, equity issues may represent an important source of financing

during periods of high interest rates. Taken together, these arguments suggest that, as interest

rates increase, the likelihood of IPOs relative to takeovers increases. Conversely, a higher

interest rate may indicate lower firm value in IPO pricing.6 Additionally higher interest rates

may also indicate lower future growth opportunities for IPOs. In this case, high interest rate

environments may decrease activity in the IPO market relative to takeovers. Once again, we are

left with an empirical issue.

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III. Data Description and Difference Tests between IPOs and Takeovers

In this section, we describe the sample used in the subsequent empirical tests.

Additionally, we perform difference tests between IPO firms and takeover firms as initial tests of

our hypotheses outlined in the preceding section.

A. Data

Our aggregate sample consists of two subsamples – an IPO sample and a takeover

sample. The IPO sample is obtained from the SDC Global New Issues database. The initial

sample consists of 7,716 firms that conducted a firm commitment IPO from 1984-1998. We

exclude unit issues (1,025), closed-end funds (505), limited partnerships (85), spinoffs (719)

Previous leveraged buyouts (283), and foreign issuers (384) from this original SDC download to

obtain a preliminary group of 4,715 firms. Next we eliminate firms if there are missing data for

the high-tech indicator, financial services indicator, industry market-to-book ratio, transaction

value, or the Herfindahl index resulting in a sample of 4,683 firms. We use the 4,683 firms for

the majority of our univariate difference tests.7 Also, we require that IPO firms have sufficient

data available for the regression models used to examine the influence of the previously

discussed factors. Because some firms have missing variables, the IPO sample size for the

subsequent regressions is 3,147 firms.

Similarly, the takeover sample is drawn from the SDC Mergers and Acquisitions

database and utilizes all completed deals involving 100 percent acquisitions of U.S. private

targets by U.S public acquirers. Using these screening criteria, our initial sample consists of

19,908 firms. Excluding limited partnerships (198) and leveraged buyouts (9,261) results in a

sample of 10,449. Again we eliminate firms if there are missing data for the high-tech indicator,

financial services indicator, industry market-to-book ratio, transaction value, or the Herfindahl

16

index, resulting in a sample of 4,927 firms. We use all 4,927 takeovers for the majority of the

univariate tests.8 The data requirements for the multivariate model lead to a regression sample of

2,691 privately held target firms.

Other databases employed in this study include Compustat (to construct the Herfindahl

industry index) and the Federal Reserve Economic Data (FRED) provided by the Federal

Reserve Bank of St. Louis (for the 3-month T-bill rates and the consumer price index). To

control for inflation effects, we adjust all dollar values to 1998 dollars using the consumer price

index.

The distribution of takeovers and IPOs in our sample is shown over time in Figure 1,

based on the available observations in SDC. We construct Figure 1 prior to eliminating

observations with missing independent variables to capture the overall trend of IPOs and

takeovers, which results in a sample size of 15,164 firms (i.e., 4,715 IPOs and 10,449 takeovers).

In earlier years, IPOs occurred more frequently than takeovers, while in more recent years,

takeovers have clearly gained prominence. Figure 2, which reports the frequency distribution for

the IPO and takeover samples after firms with missing independent variables are omitted

(resulting in 4,683 IPOs and 4,927 takeovers), provides further evidence of these trends. The

bars in the graph represent the ratio of the number of firms in a specific year divided by the total

number of firms over all years for a particular sub-sample. For example, in 1984, 4.9 percent of

the IPO sample occurred (i.e., 229/4683). For each year from 1984-1995, we observe a larger

percentage of IPOs relative to takeovers. This trend reverses from 1996-1998, with takeovers

representing a larger percentage. The largest disparities are in 1997 (8.9 percent IPO versus 30.5

percent takeovers) and 1998 (5.7 percent IPOs versus 30.0 percent takeovers). In our subsequent

tests, this intertemporal pattern is controlled for by using constant 1998 dollars, by performing

17

sub-period tests for the pre and post 1996 samples, and by including year dummy variables in the

regressions.

[INSERT FIGURES 1 AND 2 ABOUT HERE.]

In Figure 3 we report the industry classification breakdown used in Figure 2 (4,683 IPOs

and 4,927 takeovers). Each column represents the percentage of the specific sample (i.e., IPO or

takeover) that is in the particular industry grouping. Our industry classifications are taken from

Kahle and Walking (1996). Based upon the two-digit SIC classifications, takeovers are

relatively more prevalent in the manufacturing and retail trade sectors, with IPOs relatively

higher in the other sectors.

[INSERT FIGURE 3 ABOUT HERE.]

B. Difference Testing between IPO and Takeover Samples

Table II reports the results of difference tests between the IPO sample and the private

target takeover sample. To test for differences in means and differences in medians, we conduct

t-tests and Wilcoxon rank difference tests, respectively. Initial inspection of Table II shows that

the mean and median for each of the industry, market-timing, and deal-specific variables are

significantly different between the IPO and takeover samples (i.e., all the corresponding p-values

are below 1 percent). In the remainder of this section, we examine the relationships between

these factors and the IPO versus takeover decision.

As discussed earlier, if takeovers are less likely to occur in industries that are already

highly concentrated, then the Herfindahl Index for the takeover sample would tend to be less

than that for the IPO sample. Panel A of Table II reveals that the IPO sample mean for the

Herfindahl index is significantly greater than the takeover sample mean (p<0.0001). This

finding suggests that takeovers are less prevalent in higher concentration industries, where the

18

potential for further consolidation may be limited. The results also provide evidence that high-

tech firms, with an IPO sample mean of 24 percent versus only 11 percent for takeovers, are

more likely to go public via an IPO. The soaring popularity of high-tech IPOs with investors

over the time period examined may help explain this result. Table II also shows that owners of

financial service firms are more likely to agree to be acquired rather than to go public via an IPO.

This finding supports the argument that the deregulation occurring in financial service industries

has helped create an environment more conducive to consolidation within these industries.

[INSERT TABLE II ABOUT HERE.]

The findings in Panel A indicate that the IPO sample mean for each firm's industry

leverage ratio is significantly less than that for the takeover sample. If higher financial leverage

serves as a proxy for risk, then private firms from riskier industries have a tendency to take the

more conservative restructuring path, i.e., a takeover. Similarly, an examination of the average

industry market-to-book for the two samples reveals a higher ratio for the takeover sample than

for the IPO sample. Since this ratio can serve as a basis for the valuation of private targets in

takeover transactions, privately held firms may find it advantageous to agree to takeovers when

these industry valuations are relatively high.

Panel B reports the market-timing variables. The relative volume of IPOs to mergers

indicates that during heavy periods of IPO activity, takeover activity tends to be relatively low

and vice versa. This observed clustering of IPOs and takeovers supports the work of Loughran,

Ritter, and Rydqvist (1994) and Mitchell and Mulherin (1996) who analyze IPOs and takeovers

separately. Furthermore, takeovers of privately-held firms tend to occur during periods of

relatively high stock market returns, as evidenced by the higher market return variables for the

19

takeover sample than for the IPO sample. This result suggests that favorable market

environments encourage bidder activity relative to IPO activity.

In examining deal-specific factors, Panel C indicates that larger firms (measured by total

assets) are more likely to undertake an IPO rather than be acquired by a public company.

Specifically, IPO firms tend to have about 2.5 times the assets of takeover targets ($268 million

for IPOs, versus $111 million for private targets). Consistent with this finding, our second proxy

for size, the average transaction value (i.e., the total amount paid to the private firm owners

scaled by the percentage of the firm sold) is significantly larger for IPOs ($138.18 million) than

for takeovers ($48.25 million). An examination of the insider ownership and liquidity

characteristics of IPOs and takeovers provides some preliminary evidence on the ownership

versus liquidity tradeoff in these two types of transactions. Specifically, insider ownership after

the deal is more pronounced in IPOs, where insiders retain an average 64 percent of the firm. In

contrast, in mergers, target firm owners average only about five percent ownership in the

combined firm. The liquidity effects of mergers show that, on average, private firm owners

receive about 60 percent of the deal’s value in cash. On the other hand, the liquidity effects of

IPOs tend to be significantly more modest, providing only about 11 percent liquidity for insiders.

Both the ownership and liquidity findings are consistent with the Leland and Pyle (1977)

framework discussed earlier. In Section V, we examine the relationship between liquidity and

the premiums paid in takeovers versus IPOs.

Finally, Panel D provides mixed results for the explanatory power of the demand for fund

factors in the choice of IPOs versus takeovers. The HML and SMB factors tend to be larger for

IPOs, but this is not the case for all the lagged coefficients. In a univariate setting, HML and

SMB are difficult to interpret because, without adequate controls for competing effects, these

20

variables possibly serve as proxies for multiple economic factors. We therefore defer the

interpretation of HML and SMB to the subsequent multivariate setting. The last demand for

fund factor, the three-month T-bill variable, indicates that takeovers tend to occur during times of

lower interest rates than IPOs. Since acquirers often use debt to finance acquisitions, they may

time their takeovers to correspond with cheaper debt markets.

This section has provided, in a univariate setting, initial empirical evidence on the

determinants of the choice between a takeover or an IPO. In an attempt to provide more rigorous

tests, we estimate several multivariate models in the following section.

IV. Logistic Regression Results A. Full Sample Model with the Choice of Either an IPO or Takeover as the Binomial Choice Dependent Variable

The sample under examination includes firms that choose either an IPO or firms that

choose to be acquired by a publicly traded bidder. Firms that remain private or choose any route

other than a) conducting an IPO or b) being acquired by a publicly traded firm are omitted from

the sample. By focusing on this specific sample we are able to examine how different factors

influence the relative attractiveness of IPOs versus takeovers of private firms. We model the

dependent variable as a binomial choice variable of either a) going public via an IPO (in which

case the dependent variable equals zero) or b) agreeing to a takeover by a publicly traded

company (in which case the dependent variable equals one). As a result of the bivariate nature of

the dependent variable, we employ a logistic regression methodology and estimate the following

model:

[0 if IPO or 1 if Takeover] = αi + Σi=1,5βi industry related factors + Σi=6,11βi market-timing factors + Σi=12,13βi deal-related factors + Σi=14,22βi demand for fund factors + εi, (2)

21

where the dependent variable equals zero when the transaction is an IPO and one when it is a

takeover.9 The specific independent variables discussed in Section II are listed in the first

column of Table III. The results show that four of the five industry related factors have

coefficients significantly different than zero. In addition, the sign of each variable is consistent

with the univariate findings in Table II, indicating that industry effects play a prominent role in

the choice of an IPO or takeover. These results are consistent with the theoretical arguments of

Maksimovic and Pilcher (2001), Stoughton, Wong, and Zechner (2001), Hoffmann-Burchardi

(1999) and Mitchell and Mulherin (1996), that emphasize the importance of industry factors

when testing for the determinants of IPOs and mergers independently.

[INSERT TABLE III ABOUT HERE.]

The market-timing variable, an extension of the hot issue theories in the IPO and merger

literature, predicts a negative coefficient for the relative volume of IPOs to mergers. The result

in Table III provides support for this prediction, with a negative coefficient that is different from

zero beyond the one percent level. The significance of the relative volume variable suggests that

private firms tend to time, or herd, when they go public via either an IPO or a takeover. The

relative influence of the market return variables, however, is not as clear. Specifically, the

coefficients for MKT and its corresponding lags are insignificant, except at the first and fourth

lags where they are positive and significant at the 10 percent and five percent levels,

respectively.

Turning to the deal-specific factors, the size proxy (the log of transaction value) shows

that larger transactions are more likely to be IPOs. The size variable result supports the use of

size as an indication of the private firm’s ability to stand alone as an independent company. In

addition, the negative coefficient for size supports the conjecture that flotation costs can deter

22

smaller private firms from conducting IPOs. Furthermore, an examination of the liquidity effects

of the two types of transactions confirms the earlier findings of Table I. Private firm owners who

agree to a takeover experience significantly larger liquidity as a result of the transaction, as

shown by the positive sign of the liquidity coefficient, that is significant at the one percent

level.10

Similar to the market-return results, the proxies for the demand for funds also provide

mixed results. The HML factor is negative and significant at lag 2. The SMB factor is also

negative and significant at lag 2, but positive and significant at lag 4. The instability of signs

across both HML and SMB and the lack of significance on the first lags, suggests that HML and

SMB are not significant determinants in the choice of IPO versus takeover. Finally, the 3-month

T-bill rate is inversely related to the probability of a takeover, which supports the prediction that

acquiring firms are more likely to undertake acquisitions when debt is cheaper.

B. Method of Merger Payment Models

In this section, we test the robustness of our full model results by examining the influence

of the method of payment on the decision to conduct a takeover or an IPO. Similar to the

previous analysis, in this section, the sample consists of firms that were either bought by a

publicly traded firm or went public via an IPO. The dependent variable for each of the first three

models in Table IV is a binomial choice indicator variable that takes a value of one when the

firm is taken over with either a 100 percent cash offer (Model 1), a mixed offer (Model 2), or a

100 percent stock offer (Model 3). When the private firm conducts an IPO, the dependent

variable is zero in all three models. Model 4 in Table IV reports the results of an ordered

multinomial logit regression where the dependent variable is: zero for firms conducting IPOs, 1

for 100 percent stock takeovers, 2 for mixed takeovers, and 3 for 100 percent cash takeovers.11

23

The Table IV analysis is undertaken, in part, because numerous studies have shown that the

method of payment in mergers is an important variable in the value effects of takeover activities

(e.g., Travlos (1987), and Amihud, Lev, and Travlos (1990), Martin (1996) and Ang and Kohers

(2001)). Also, as previously discussed, private firm owners completely relinquish their

ownership of the firm in cash offers, while they still retain some ownership in stock offers.

Thus, from the standpoint of ownership, IPOs and stock offers may be more comparable than

IPOs and cash takeovers.12

[INSERT TABLE IV ABOUT HERE.]

Overall, the results of the method of payment sub-sample analysis are largely consistent

with those found for the full sample of takeovers and IPOs in Table III. There are nevertheless

certain distinctions in the relative influence of the factors on the IPO versus cash offer (Model 1),

mixed offer (model 2), and stock offer (Model 3) decisions. To avoid redundancy, we focus on

the key differences in results between the models. The degree of industry concentration, as

measured by the Herfindahl Index, plays a significant role in influencing the IPO versus stock

offer decision in Model 3, but this factor does not have a distinct impact on the other decisions

captured in Models 1, 2, and 4. Also, the high-tech indicator is insignificant in the IPO versus

stock takeover specification of Model 3, suggesting that high-tech sellers tend not to have a

preference over IPOs or stock takeovers. In contrast, the high-tech indicator is negative and

significant in Models 1, 2, and 4, indicating an increase in the likelihood of an IPO relative to the

types of takeovers captured by these models. This finding suggests that high-tech firm owners,

who often provide a valuable source of human capital in their firms, are more likely to retain

partial ownership in their firm through an IPO instead of completely cashing out via a cash offer.

24

Finally, another difference in the method of payment models involves the role of the T-

bill variable, the proxy for the cost of debt. In particular, this factor is negative and significant in

models 2, 3, and 4, indicating that takeovers are more likely than IPOs when the T-bill rate is

lower. In contrast, the T-bill factor loses its significance in Model 1, which captures the IPO

versus cash offer choice. Since private target takeovers paid fully with cash tend to be relatively

smaller transactions, acquirers often do not require significant amounts of debt financing and,

thus, may not be particularly sensitive to the cost of debt. In sum, while the overall results in

Table IV are similar to those reported for the full samples in Table III, this method of payment

subsample analysis provides additional insights on the relative influence of the factors on the

choice between IPOs and different types of takeovers.

D. Further Robustness Tests

Schwert and Lowry (2000) find that IPO volume fluctuates substantially over time.

Figure 1 supports this finding and indicates that the volume of private takeovers also fluctuates

over time. To control for time period differences, we employed yearly dummy variables and re-

estimated the modified Equation 2. Estimation results (not reported) showed significant

coefficients for the 1997 and 1998 periods. However, the findings for the previously discussed

variables were not qualitatively different. In further robustness tests, an alternative measure for

firm size, total assets, was employed. With the exception of the average market-to-book of the

firm industry and the three-month T-bill rate, all of the results were robust to this specification.

Because the availability of total asset figures for privately held firms is more limited than

transaction size information, using this measure would decrease the sample size and hence the

power of our tests. We therefore choose to report the transaction size specifications.

25

Another robustness check further addresses the issue of ownership. As previously

discussed, in contrast to IPOs, insiders of a takeover often lose substantial, if not entire,

ownership of the firm. In a sub-sample analysis, we re-estimated Equation 2 with all of the

takeovers in our sample, but only those IPOs where the insiders lose majority stake control of the

firm (i.e., they own less than 50 percent of the firm after the IPO). Thus, we focused on the set

of firms that had chosen either an IPO or a takeover and, at the same time, had agreed to give up

majority ownership of their firms. The results of the sub-sample analysis were consistent with

the previous logistic regression analyses and, thus, are not shown.

An additional robustness test involved re-estimating Equation 2 to capture possible time

period shifts in the IPO versus takeover decision. As previously reported in Figure 1, the

frequency of takeovers grew significantly in the period from 1996 through 1998. Thus, the first

model was estimated for deals occurring between 1984 and 1995, and the second model covers

deals between 1996 and 1998. In both periods, our results are qualitatively robust, indicating

that time period effects do not drive our findings.

A final robustness test treats for possible industry clustering in the multivariate logit

model (Table IV, Model 4). Moulton (1986) provides evidence that adjusting for the cross-

correlation of the error terms in a regression if clustering exists can increase efficiency of

estimators. Using an adaptation of Diggle, Liang, and Zeger's (1994) method, we construct a

generalized estimating equation that controls for clustering by two-digit SIC code. The results of

this model are nearly identical to the results of Model 4 reported in Table IV.13 Overall, these

alternative tests and different model specifications provide strong validation of the robustness of

the previously examined factors and their role in the IPO versus takeover choice for privately

held firms.

26

V. Seller Premiums to Insiders in IPOs and Takeovers

Thus far, we have not specifically examined the premiums received by selling insiders.

In this section, we explore the pay-offs that selling insiders receive through either the takeover or

the IPO.

Using the argument of Leland and Pyle (1977), insiders who retain a larger stake of a

risky firm issue a costly, and therefore credible, signal of the quality of the firm. This signal of

quality would allow them to obtain a better price for the stake they sell. However, if a

controlling stake affords the firm’s new owners the ability to extract some private benefits of

control from the company, then a controlling stake may command a premium (Zingales (1994)).

In an attempt to test this issue we analyze the ratio of offer price per share to book value of

equity per share for each firm. By using a measure on a per share basis, we are able to capture

the premium for the portion of the firm sold in the transaction (either IPO or takeover).

Table V reports the results of parametric t-tests (and Wilcoxon rank tests) between the

mean (and median) of the IPO and Takeover samples. The first column of the table reports sub-

samples based on the conditioning variables of method of payment and high-tech industry status.

[INSERT TABLE V ABOUT HERE.]

The complete sample difference tests indicate that the premiums for IPOs are significantly

greater on average than the takeover premiums (13.3 versus 10.9 mean, 7.1 versus 4.7 median,

both p-values < 0.01). Thus, insiders who choose the IPO route tend to earn a greater premium

(22 percent larger, on average [i.e., (13.3-10.9)/10.9]) than insiders who sell out to acquirers.

One potential reason for the IPO premium may be the existence of a liquidity discount which

private target owners experience in takeovers. We documented earlier that takeovers provide

greater liquidity on average than IPOs for selling insiders. This greater liquidity in takeovers

27

may result in a liquidity discount, as target firm insiders are generally not willing to bear the non-

liquidity risk that is associated more with IPOs. The next two rows of Table V indicate that this

relationship holds for non-high-tech firms, but it does not hold statistically for high-tech firms.

The finding that high-tech takeover premiums are not significantly smaller than IPO premiums

extends the work of Kohers and Kohers (2000) who show that high-tech takeover targets

generally receive higher premiums than non-high-tech targets.

The remaining six rows consider the method of payment and compare IPOs with cash and

stock offers, respectively. The premiums paid to IPO insiders are greater than takeover insider

premiums in all scenarios except the stock only high-tech sample. Consistent with the high-tech

indicator result in Model 3, Table IV, the IPO and stock offer high-tech takeover premiums are

not significantly different, supporting the notion that liquidity may be the driving force behind

the premiums. Focusing on the takeover columns, the stock takeover sample average 13.0 is

greater than the cash takeover sample average 9.5 (p-value = 0.0542, not reported in table). The

significant difference between the cash and stock takeover samples also supports the liquidity

discount hypothesis advanced in the paragraph above.

We have suggested that the disparity in premiums reported in Table V may be due to

varying levels of liquidity between the choice of IPO or takeover. To formally test this

conjecture, we estimate the following Tobit regression model:

Offer/book value = 13.87 – 0.04 LIQUIDITY – 0.45 TAKEOVER, (3) (< 0.0001) (< 0.0001) (< 0.6124) where the dependent variable is the premium paid to selling insiders (i.e., the offer price per

share to book value of equity per share), LIQUIDITY is the percentage of the takeover or IPO

transaction value received in cash by sellers, and TAKEOVER is an indicator variable that

28

equals one when the firm is a takeover and zero when the firm is an IPO.14 Estimated

coefficients are reported in equation (3) and p-values for each are reported beneath in

parentheses. The regression results confirm our intuition that the disparity in premiums reported

in Table V is driven by the liquidity associated with the deal. Additionally, the negative

coefficient on TAKEOVER suggests that mergers receive a smaller premium than IPOs;

however it is not statistically significant.15 The results of equation (3) indicate that insiders in

takeovers experience a discounted payoff relative to IPOs due mainly to the greater average

liquidity associated with takeovers.

VI. Summary and Conclusions

A fundamental decision facing privately held firms interested in reaching public equity

markets is the choice between an IPO and a takeover by a publicly traded acquirer. Whereas

previous studies have recently highlighted the importance of industry and market-timing factors

in the decision to go public via an IPO versus staying private, none of this research has addressed

alternative corporate strategies for private firms to access public equity markets. Additionally,

the large numbers of privately-held companies undertaking IPOs and takeovers make the

identification of economic factors that influence firms to choose one route versus the other

inherently interesting.

Using a sample of over 9,500 U.S. privately held firms, we address this issue by

examining the determinants of the IPO choice versus the decision to be acquired by a publicly

traded firm. Our results show that four factors – industry, market-timing, deal-specific, and to a

lesser degree demand for funds – play a role in the IPO versus takeover choice. Specifically, the

concentration of the industry, the high-tech industry status of the private firm, the ‘hotness’ of

the IPO market relative to the private target takeover market, the current cost of debt, the

29

percentage of insider ownership maintained in the firm, and the size of the firm are all positively

related to the probability that a firm will conduct an IPO. In contrast, firms in high market-to-

book industries, financial service firms, firms in high debt industries, and deals involving greater

liquidity for selling insiders show a stronger likelihood for takeovers. Finally, a quantitative

analysis of the liquidity effects of the IPO versus takeover decision provides evidence that a

liquidity discount of approximately 22 percent exists in takeovers. Overall, in addressing the

IPO versus takeover choice, our study sheds new light on a previously unexplored dimension of

the going public decision for privately-held companies and identifies key determinants that

influence this fundamental restructuring choice for private firms.

30

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34

Figure 1.

Volume of IPOs and Takeovers of Private Firms from 1984-1998

0

50

100

150

200

250

300

350

40019

84

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1955

1966

1997

1988

Num

ber o

f Firm

s C

ondu

ctin

g Ei

ther

an

IPO

or T

akeo

ver p

er M

onth

IPO Takeover

The volume of IPOs and the volume of private target takeovers for firms that conducted either an IPO (n = 4,715) or were taken over (n = 10,449) from 1984-1998.

35

Figure 2.

Frequency Distribution of IPO and Takeover Sample by Year, 1984-1998

0

5

10

15

20

25

30

35

Perc

ent

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

% of IPOs % of Takeovers

The volume of IPOs and the volume of private target takeovers for the firms in the sample are shown over time. The dark (light) bar represents the proportion of IPOs (takeovers) for that year relative to the entire sample of IPOs (takeovers). The total sample contains 4,683 IPOs and 4,927 takeovers.

36

Figure 3.

Frequency Distribution of IPO and Takeover Sample by Industry, 1984-1998

05

101520253035

Per

cent

A B C D E F G H I

% of IPOs % of Takeovers

SIC Manual Two-Digit Industry description Division Major Group Agriculture, Forestry, and Fishing A 01-09 Mining B 10-14 Construction C 15-17 Manufacturing D 20-39 Transportation, Communications, Electric, Gas, and Sanitary Services E 40-49 Wholesale Trade F 50-51 Retail Trade G 52-59 Finance, Insurance, and Real Estate H 60-67 Services I 70-89 Public Administration * J 91-97 * There are no public administration firms in our sample.

Each bar represents the proportion of either IPOs (n = 4,683) or takeovers (n = 4,927) for that industry relative to the entire sample.

37

Table I. Summary of Factors of the IPO and Takeover Decision

Dependent variable = 0 Dependent variable = 1 Theories predicting Theories Predicting Variable IPO Takeover

Panel A. Industry Related Factors Herfindahl index for private/issue firm industry

High concentration industries are less conducive to corporate combinations; anti-trust concerns make takeovers moredifficult

Firm survival may be more difficult in highly concentrated industries (Sharma and Kesner (1996) and Audretsch (1995)

High-tech indicator Investors' attraction to high-tech IPOs may encourage IPO activity (Maksimovic and Pichler (2001), Allen and Gale (1999))

High-tech targets tend to receive relatively attractive premiums (Kohers and Kohers (2000)); ability to maintain confidentiality (Yosha (1995))

Financial services indicator Deregulation may motivate private firms to do IPOs to allow for stock payment in future acquisitions or to raise cash for future acquisitions

Deregulation of fragmented industry makes consolidation more feasible (Berger, Demsetz, and Strahan (1999))

Average debt ratio for private/issue firm industry

High leverage firms have already under-gone the scrutiny of lenders, leading to lower investigation costs for investors (Harris and Raviv (1990))

Higher leverage firms may opt for the more conservative restructuring path, i.e., a takeover

Average market/book for private/issue firm industry

High industry M/B provides favorable environment for IPOs (Pagano, et al. (1998))

Target valuation may be based on industry M/B, leading to attractive premiums (Golbe and White (1993))

Panel B. Market-Timing Variables Relative volume of IPOs to mergers Hot issue periods have been found for

IPOs (Ritter (1984), Hoffmann-Burchardi (1999))

Clustering of merger activity has been documented (Mitchell and Mulherin (1996))

Market return (MKT) IPOs may be strategically timed during favorable market environments (Lowry (2000))

Favorable markets can also encourage bidder activity (Golbe and White (1993))

Panel C. Deal-Specific Factors Total assets and Scaled transaction value

High fixed cost component of the IPO process may deter smaller private firms from IPOs (Ritter (1987), Holmstrom and Tirole (1993))

Insider ownership after offer (%) Owners who wish to maintain control prefer IPOs (Bebchuk and Zingales (1998))

Target owners can structure takeovers via stock purchases to retain varying levels of control

Liquidity IPO insiders may sell secondary shares for liquidity needs (Dhillon, Raman, and Ramirez (2000)).

Takeovers may be an effective cash-out strategy (Brown, Ditmar and Servaes (2000)). IPO insiders selling large personal shares may devalue firm (Leland and Pyle (1977))

Panel D. Demand for Fund Factors HML Private firms' need for funds leads to

IPOs (Mikkelson, Partch, and Shah (1997), Lowry and Schwert (2000))

A takeover by a public acquirer can provide private firms with needed financing as well

SMB Similar to HML, used as a proxy for demand for funds (Lowry (2000))

Like HML, a proxy for demand for funds

3-month T-bill rate High cost of debt makes IPOs more attractive via the pecking order (Myers and Majluf (1984)); high cost of debt makes takeovers harder to fund (Golbe and White (1993))

High cost of debt may decrease the value of an IPO firm when using discounted cash flows or considering future growth opportunities

38

Table II. Difference Tests Between IPO and Takeover Sample Occurring from 1984 to 1998

IPO Sample Take-over Sample Difference Parametric Wilcoxon Mean Mean in Means p-value p-value Panel A. Industry Related Factors

Herfindahl index for private/issue firm industry 0.09 0.07 0.02 <.0001 <.0001

High-tech indicator 0.24 0.11 0.12 <.0001 <.0001

Financial services indicator 0.17 0.21 -0.04 <.0001 <.0001

Average debt ratio for private firm industry 0.47 0.52 -0.05 <.0001 <.0001

Average market/book for private firm industry 1.48 1.67 -0.20 <.0001 <.0001

Panel B. Market-Timing Variables

Relative volume of IPOs to mergers 3.15 0.45 2.70 <.0001 <.0001

Market return (MKT)t 1.44 1.97 -0.53 <.0001 <.0001

MKTt-1 1.55 1.88 -0.33 <.0001 <.0001

MKTt-2 1.65 2.10 -0.45 <.0001 <.0001

MKTt-3 1.54 2.15 -0.61 <.0001 <.0001

MKTt-4 1.65 2.18 -0.53 <.0001 <.0001

Panel C. Deal-Specific Factors

Total assets ($ million) 267.76 111.38 156.38 0.0008 <.0001

Transaction value/stake of firm sold ($ million) 138.18 48.25 89.93 <.0001 <.0001

Insider ownership after deal (%) 63.73 4.60 59.13 <.0001 <.0001

Liquidity of deal (%) 10.77 60.40 -49.63 <.0001 <.0001

Panel D. Demand for Fund Factors

HMLt-1 0.20 0.28 -0.08 0.1068 0.0639

HMLt-2 0.19 0.16 0.03 0.5395 0.5593

HMLt-3 0.25 0.19 0.05 0.2768 0.3011

HMLt-4 0.25 0.09 0.17 0.0011 0.0013

SMBt-1 -0.17 -0.25 0.09 0.1314 0.0004

SMBt-2 0.08 -0.16 0.24 <.0001 <.0001

SMBt-3 0.02 -0.18 0.20 0.0006 <.0001

SMBt-4 -0.07 -0.06 -0.02 0.7925 0.0022

3-month T-bill rate 5.34 5.00 0.34 <.0001 <.0001

The mean values for selected variables are shown for a sample of IPOs (n = 4,683) and a sample of takeovers involving private targets (n = 4,927). Differences in the mean values for the two samples are also provided, along with significance levels for parametric t-tests and non-parametric Wilcoxon rank tests.

39

Table III. Logistic Regressions on Full Sample to Predict a Takeover versus an IPO

Wald Standard Variable Estimate Error Chi-Square p-value

Intercept 0.71 0.27 7.04 0.0080

Herfindahl index -2.25 0.51 19.55 <.0001

High-tech indicator -0.07 0.09 0.67 0.4124

Financial services indicator 0.85 0.11 56.78 <.0001

Average debt ratio for private firm industry 0.37 0.17 4.73 0.0296

Average market/book for private firm industry 0.48 0.08 35.13 <.0001

Relative volume of IPOs to mergers -0.60 0.04 283.51 <.0001 Market return (MKT)t 0.01 0.01 1.29 0.2556 MKTt-1 0.03 0.01 2.91 0.0880 MKTt-2 -0.01 0.01 1.02 0.3114 MKTt-3 0.00 0.01 0.08 0.7744 MKTt-4 0.03 0.01 5.42 0.0199 Log of transaction value -0.46 0.03 226.88 <.0001

Liquidity 0.04 0.00 892.64 <.0001 HMLt-1 0.02 0.02 0.53 0.4653 HMLt-2 -0.05 0.02 5.47 0.0194 HMLt-3 -0.02 0.02 0.84 0.3585 HMLt-4 -0.01 0.02 0.12 0.7287 SMBt-1 -0.01 0.02 0.34 0.5597 SMBt-2 -0.03 0.02 4.58 0.0323 SMBt-3 -0.02 0.02 1.40 0.2366 SMBt-4 0.05 0.02 10.68 0.0011 3-month T-bill rate -0.17 0.04 20.23 <.0001

-2 Log Likelihood 4646.8 <.0001

The dependent variable is an binary variable equal to 1 for private firms taken over by publicly traded companies and equal to 0 for private firms conducting an IPO. Each of the lagged factors (SMB, HML, and the market return, MKT) is shown with the corresponding number of lags. The sample consists of 3,147 IPOs and 2,691 takeovers.

40

Table IV. Logistic Regressions: IPOs versus Takeovers by Payment Method

Dependent Variable 3 if CASH 2 if MIXED 1 if CASH 1 if MIXED 1 if STOCK 1 if STOCK 0 if IPO 0 if IPO 0 if IPO 0 if IPO (1) (2) (3) (4) Est Est Est Est Variable Coeff p-value Coeff p-value Coeff p-value Coeff p-value

Intercept 0.77 0.0135 1.02 0.0079 0.78 0.0138 2 of 3 significant

Herfindahl index -0.10 0.8390 -0.98 0.1269 -3.39 <.0001 -0.47 0.1814

High-tech indicator -0.66 <.0001 -0.65 <.0001 0.13 0.1996 -0.42 <.0001

Financial services indicator 0.92 <.0001 0.09 0.6004 0.85 <.0001 0.59 <.0001

Average debt ratio for private firm industry 0.36 0.0457 0.64 0.0012 0.17 0.387 0.27 0.0136

Average market/book for private firm industry 0.18 0.0423 0.07 0.5271 0.42 <.0001 0.04 0.5075

Relative volume of IPOs to mergers -0.99 <.0001 -0.99 <.0001 -0.65 <.0001 -0.73 <.0001

Market return (MKT)t 0.03 0.0461 0.05 0.0072 0.00 0.9758 0.03 0.0014 MKTt-1 0.04 0.0113 0.07 0.0007 0.03 0.1570 0.04 0.0003 MKTt-2 0.01 0.5451 0.01 0.7390 0.00 0.7962 0.01 0.2393 MKTt-3 0.02 0.3021 0.00 0.9709 0.01 0.4455 0.01 0.2343 MKTt-4 0.03 0.0453 0.04 0.0734 0.05 0.0134 0.03 0.0052

Log of transaction value -0.53 <.0001 -0.47 <.0001 -0.43 <.0001 -0.32 <.0001

HMLt-1 0.02 0.5149 0.08 0.0174 0.02 0.5782 0.03 0.1270 HMLt-2 -0.01 0.6644 -0.02 0.6257 -0.05 0.0482 -0.01 0.7321 HMLt-3 0.00 0.8966 -0.01 0.6779 -0.01 0.8073 0.00 0.8283 HMLt-4 0.03 0.2725 -0.03 0.3536 0.01 0.7604 0.02 0.1912

SMBt-1 0.00 0.9564 0.02 0.2378 -0.02 0.3367 0.00 0.9365 SMBt-2 -0.01 0.6517 0.00 0.966 -0.03 0.1086 0.00 0.9081 SMBt-3 0.02 0.2224 0.01 0.6725 -0.03 0.0924 0.01 0.2510 SMBt-4 0.07 0.0001 0.09 <.0001 0.07 0.0001 0.05 <.0001

3-month T-bill rate 0.00 0.9331 -0.17 0.0035 -0.17 0.0004 -0.07 0.0301

-2 Log Likelihood 3640.30 <.0001 2520.77 <.0001 3442.01 <.0001 11865.09 <.0001

The dependent variable differs for each model and is indicated at the top of the result columns. Models 1-3 are binomial logit models, Model 4 is an ordered multinomial logit model. Est Coeff is an abbreviation for estimated coefficient. Each of the lagged factors (SMB, HML, and the market return, MKT) is shown with the corresponding number of lags. The cash takeover sample consists of 1,194 firms, the mixed takeover sample consists of 595 firms and the stock takeover sample consists of 902 firms. The IPO sample contains 3,185 firms.

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Table V. Various Premiums Associated with Takeovers and IPOs

IPO Takeover

Difference tests Parametric Non-parametric

Mean Median

Median

Mean

p-value

p-value

Complete sample 13.3 7.1 10.9 4.7

0.0018

<.0001

High-tech sample 13.7 7.9 13.0 7.6

0.7455

0.2178

Non-high-tech sample

13.2 6.6 10.7 4.5

0.0025

<.0001

Stock only merger sample

13.3 7.1 13.0 4.6

0.8597

0.0060

Cash only merger sample

13.3 7.1 9.5 4.2

0.0044

<.0001

Stock only high-tech sample

13.7 7.9 18.9 12.0

0.1651

0.1170

Stock only non-high-tech sample

13.2 6.6 11.8 3.4

0.3606

0.0008

Cash only high-tech sample

13.7 7.9 4.6 3.2

<.0001

0.0019

Cash only non-high-tech sample 13.2 6.6 9.9 4.4 0.0216 <.0001

The mean and median values are for the ratio of offer price per share to book value of equity per share for each respective sample. P-values for tests of differences in the mean and median values for the two samples are provided, parametric t-tests first with non-parametric Wilcoxon rank tests second. The complete sample consists of 4,683 IPOs and 4,927 takeovers.

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Notes

1 Examples of IPO versus staying private literature include Chemmanur and Fulghieri (1999), Gomes (1999), Maug (1999), Stoughton, Wong and Zechner (1999), Bolton and von Thadden (1998), Mello and Parsons (1998), Pagano, Panetta, and Zingales (1998), Pagano and Roell (1998), Stoughton and Zechner (1998), Brennan and Franks (1997), and Roell (1996). 2 In our analysis, we focus on broad external influences, and not on firm-specific factors, for two primary reasons. First, we wish to capture those industry and market-timing factors that are able to explain market-wide tendencies for private firms to take one restructuring route instead of the other. As previously discussed, recent observations reported in the financial press suggest that market-related environmental factors play a role in determining broad trends in takeover versus IPO activity. Additionally, and perhaps more importantly, Mitchell and Mulherin (1996), Pagano, et al. (1998), Stoughton, et al. (1999), and Maksimovic and Pilcher (1999), among others, find that market and industry factors significantly impact IPOs and takeovers independently. To capture these broad tendencies, we examine larger numbers of private firms that make the IPO versus takeover decision. Whereas an examination of firm-specific factors is certainly of interest, the severe lack of available data on private firms would significantly reduce our sample and compromise the ability to identify the external factors that are thought to influence this choice. 3 Different industries would not necessarily have a tendency to move towards the same level of industry concentration since increased concentration may not provide the same efficiency effects across all industries. Thus, in equilibrium, a low concentration industry may have no strong inclination to become more concentrated in the long run. We appreciate this point provided by our referee. 4 In addition to its common use in the finance and economic literature as a measure of industry concentration, the Herfindahl index is also utilized by the Justice Department in assessing market power for antitrust analysis. 5 We thank the referee for highlighting this point. 6 The IPO pricing argument relies on a larger discount rate in a discounted cash flow model. We thank Mike Pinegar for this point. 7 Variables with less than 4,683 observations include industry leverage ratio (4,417), relative volume of IPOs to takeovers (3,450), MKT (4,610), total assets (4,187), HML (4,610), and SMB (4,610). 8 Variables with less than 4,927 observations include industry leverage ratio (3,451), relative volume of IPOs to takeovers (4,095), MKT (4,264), total assets (834), ownership (2,647), HML (4,264), and SMB (4,264). 9 In the subsequent robustness tests, we estimate a multinomial logit and a multinomial general estimation equation. These specifications relax the binomial assumption of the dependent variable. 10 Given the tradeoff between liquidity and ownership for private firm owners, the inverse relationship between these two factors, and the lack of ownership data for takeovers, we include only the liquidity variable in the reported regression analysis. In a separate regression incorporating the ownership variable, the findings showed a negative sign for this factor, which was significant beyond the one percent level. Thus, consistent with the findings of Table II, the level of insider ownership is positively associated with the IPO choice. 11 We take the format of our Table IV from Martin's (1996) Table II. The number of cash takeovers (Model 1) is 1,194; the number of mixed takeovers (Model 2) is 595; the number of stock takeovers (Model 3) is 902. The number of IPOs in each model is 3,185 firms. Model 4 contains all of the observations from

43

Models 1 through 3. Table IV contains 38 more IPOs than Table III because the liquidity variable is not required for Table IV and 38 IPO firms have missing data for liquidity. 12 We do include the method of payment as a dummy variable in Equation 2 because it only applies to takeovers. The nature of the binomial dependent variable creates a quasi-separation that cannot converge when only one of the dependent variable choices has a variable with observations. We overcome this obstacle with the analysis reported in Table IV. 13 We thank Rob Daines for pointing out the potential problem of cross correlation of the error terms and the remedy. 14 We use Tobit methodology because the dependent variable (offer price to book value) is censored on the left tail of the distribution at zero. 15We do not include offer to book value as an independent variable in the full model (i.e., Table III) because we lose a large portion of the merger sample when we do. In unreported testing, we include offer to book value along with all of the other variables listed in Table III. The coefficient on the offer to book variable is not statistically different from zero in the regression.

44